With e-commerce leaders such as Alibaba, Amazon, eBay, and TikTok on hand to share insights at the China (Shenzhen) Cross Border E-commerce Fair (CCBEC) from 11 – 13 September 2024, the show will welcome nearly 1,500 exhibitors from around the globe.

In the Chinese city of Zhuhai, a car rammed into a crowd of people near a sports center. The 62-year-old driver fled the scene of the accident but was later detained. The victims were hospitalized, China Daily said with reference to local authorities. WARNING: The videos are extremely graphic! Click here to see more photos and videos from the scene.

A two-seat version of the J-20 fighter, the J-20S, was unveiled at the Zhuhai Air Show in China. The J-20S is notable for being the only two-seat design built on a 5th-generation platform. The second seat in the airplane is designed for the UAV operator. This configuration allows the J-20S to control unmanned wingmen thus enhancing the role of the fighter as a central information hub in combat.

Paysend has launched instant and simple cross-border payouts to China UnionPay cards for its Enterprise customers.

According to the dietitian Li Yuanjuan, moderate consumption of eggs per week can contribute to a healthy diet. However, he warns about the possible danger of the product as it can increase cholesterol levels in the blood. The dietitian emphasizes that the key to a healthy diet is the correct amount of egg consumption - from three to six per week, no more than one egg per day. In his interview with the Chinese portal Sina, Li Yuanjuan notes that eggs are the main food for those who adhere to a healthy lifestyle, as they contain high-quality protein that is well absorbed by the body. According to the specialist, the proper consumption of eggs in combination with a varied and balanced diet, as well as regular physical exercise, can help reduce the risk of various diseases and elevated cholesterol levels in the blood. Therefore, adhering to the recommended amount of egg consumption per week is an important aspect of a healthy lifestyle.

A research team has identified 2,586 orphan genes (OGs) in Rosa chinensis, offering new insights into the role of these unique genes in flower development, stress response, and environmental adaptation.

A research team has identified 2,586 orphan genes (OGs) in Rosa chinensis, offering new insights into the role of these unique genes in flower development, stress response, and environmental adaptation.

[Inter-Korea] :
The defense chiefs of South Korea and the United States have condemned the deployment of North Korean troops to Russia in the “strongest” terms with “one voice.” Defense Minister Kim Yong-hyun and U.S. Secretary of Defense Lloyd Austin issued the condemnation on Wednesday in a joint statement after ...

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[Sports] :
Former national football team member Son Jun-ho has been permanently banned by the Chinese Football Association(CFA). The CFA on Tuesday announced the disciplinary action against Son, accusing the football player of engaging in match-fixing and bribery. With the latest decision, Son is permanently ...

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The expression "the cherry on top" refers to a very good thing. You may think differently once you learn how maraschino cherries are actually made.

Chow mein and lo mein are two noodle dishes that are staples in Chinese restaurants worldwide, each boasting its own loyal following. However, for many diners, distinguishing chow mein vs. lo mein and vice versa can be perplexing.

We rely on our washing machine to wash our dirty laundry, but what if it's the cause of dirty clothes? Is there any recourse when our washing machine leaves stains on our clothes?

Small-angle X-ray scattering (SAXS) is widely used to analyze the shape and size of nanoparticles in solution. A multitude of models, describing the SAXS intensity resulting from nanoparticles of various shapes, have been developed by the scientific community and are used for data analysis. Choosing the optimal model is a crucial step in data analysis, which can be difficult and time-consuming, especially for non-expert users. An algorithm is proposed, based on machine learning, representation learning and SAXS-specific preprocessing methods, which instantly selects the nanoparticle model best suited to describe SAXS data. The different algorithms compared are trained and evaluated on a simulated database. This database includes 75 000 scattering spectra from nine nanoparticle models, and realistically simulates two distinct device configurations. It will be made freely available to serve as a basis of comparison for future work. Deploying a universal solution for automatic nanoparticle model selection is a challenge made more difficult by the diversity of SAXS instruments and their flexible settings. The poor transferability of classification rules learned on one device configuration to another is highlighted. It is shown that training on several device configurations enables the algorithm to be generalized, without degrading performance compared with configuration-specific training. Finally, the classification algorithm is evaluated on a real data set obtained by performing SAXS experiments on nanoparticles for each of the instrumental configurations, which have been characterized by transmission electron microscopy. This data set, although very limited, allows estimation of the transferability of the classification rules learned on simulated data to real data.

Animations, videos and 3D models have been designed to visualize the effects of symmetry operators on selected cases of crystal structures, pointing out the relationship with the diagrams published in International Tables for Crystallography, Vol. A.

New software capabilities in RMCProfile allow researchers to study the structure of materials by combining machine learning interatomic potentials and reverse Monte Carlo.

This paper describes real-time statistical analysis of liquid jet images for SFX experiments at the European XFEL. This analysis forms one part of the automated jet re-alignment system for SFX experiments at the SPB/SFX instrument of European XFEL.

A series of animations, videos and 3D models that were developed, filmed or built to teach the symmetry properties of crystals are described. At first, these resources were designed for graduate students taking a basic crystallography course, coming from different careers, at the National Autonomous University of Mexico. However, the COVID-19 pandemic had the effect of accelerating the generation of didactic material. Besides our experience with postgraduate students, we have noted that 3D models attract the attention of children, and therefore we believe that these models are particularly useful for teaching children about the assembled arrangements of crystal structures.

Structure refinement with reverse Monte Carlo (RMC) is a powerful tool for interpreting experimental diffraction data. To ensure that the under-constrained RMC algorithm yields reasonable results, the hybrid RMC approach applies interatomic potentials to obtain solutions that are both physically sensible and in agreement with experiment. To expand the range of materials that can be studied with hybrid RMC, we have implemented a new interatomic potential constraint in RMCProfile that grants flexibility to apply potentials supported by the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) molecular dynamics code. This includes machine learning interatomic potentials, which provide a pathway to applying hybrid RMC to materials without currently available interatomic potentials. To this end, we present a methodology to use RMC to train machine learning interatomic potentials for hybrid RMC applications.

Small-angle X-ray scattering (SAXS) is a widely used method for nanoparticle characterization. A common approach to analysing nanoparticles in solution by SAXS involves fitting the curve using a parametric model that relates real-space parameters, such as nanoparticle size and electron density, to intensity values in reciprocal space. Selecting the optimal model is a crucial step in terms of analysis quality and can be time-consuming and complex. Several studies have proposed effective methods, based on machine learning, to automate the model selection step. Deploying these methods in software intended for both researchers and industry raises several issues. The diversity of SAXS instrumentation requires assessment of the robustness of these methods on data from various machine configurations, involving significant variations in the q-space ranges and highly variable signal-to-noise ratios (SNR) from one data set to another. In the case of laboratory instrumentation, data acquisition can be time-consuming and there is no universal criterion for defining an optimal acquisition time. This paper presents an approach that revisits the nanoparticle model selection method proposed by Monge et al. [Acta Cryst. (2024), A80, 202–212], evaluating and enhancing its robustness on data from device configurations not seen during training, by expanding the data set used for training. The influence of SNR on predictor robustness is then assessed, improved, and used to propose a stopping criterion for optimizing the trade-off between exposure time and data quality.

The users of synchrotron light are now tens of thousands throughout the world. Paradoxically, many of them do not know much about the early history of their domain. This is regrettable, since education about the initial developments makes it easier to fully understand synchrotron radiation and effectively use its amazing features. Scarcely known, in particular, is the key role of scientists working in Frascati, Italy. Partly based on his personal experiences, the author reports here relevant aspects of this story, including a pioneering French–Italian experiment that started in the early 1960s, and the Frascati contributions in the 1970s and 1980s to the birth of synchrotron light research. Finally, the unwise strategic decisions that prevented Italy from achieving absolute leadership in this domain – in spite of its unique initial advantages – are analyzed.

During beam time at a research facility, alignment and optimization of instrumentation, such as spectrometers, is a time-intensive task and often needs to be performed multiple times throughout the operation of an experiment. Despite the motorization of individual components, automated alignment solutions are not always available. In this study, a novel approach that combines optimisers with neural network surrogate models to significantly reduce the alignment overhead for a mobile soft X-ray spectrometer is proposed. Neural networks were trained exclusively using simulated ray-tracing data, and the disparity between experiment and simulation was obtained through parameter optimization. Real-time validation of this process was performed using experimental data collected at the beamline. The results demonstrate the ability to reduce alignment time from one hour to approximately five minutes. This method can also be generalized beyond spectrometers, for example, towards the alignment of optical elements at beamlines, making it applicable to a broad spectrum of research facilities.

Transition-metal nitro­gen-doped carbons (TM-N-C) are emerging as a highly promising catalyst class for several important electrocatalytic processes, including the electrocatalytic CO2 reduction reaction (CO2RR). The unique local environment around the singly dispersed metal site in TM-N-C catalysts is likely to be responsible for their catalytic properties, which differ significantly from those of bulk or nanostructured catalysts. However, the identification of the actual working structure of the main active units in TM-N-C remains a challenging task due to the fluctional, dynamic nature of these catalysts, and scarcity of experimental techniques that could probe the structure of these materials under realistic working conditions. This issue is addressed in this work and the local atomistic and electronic structure of the metal site in a Co–N–C catalyst for CO2RR is investigated by employing time-resolved operando X-ray absorption spectroscopy (XAS) combined with advanced data analysis techniques. This multi-step approach, based on principal component analysis, spectral decomposition and supervised machine learning methods, allows the contributions of several co-existing species in the working Co–N–C catalysts to be decoupled, and their XAS spectra deciphered, paving the way for understanding the CO2RR mechanisms in the Co–N–C catalysts, and further optimization of this class of electrocatalytic systems.

Cryo-electron tomography (cryo-ET) enables molecular-resolution 3D imaging of complex biological specimens such as viral particles, cellular sections and, in some cases, whole cells. This enables the structural characterization of molecules in their near-native environments, without the need for purification or separation, thereby preserving biological information such as conformational states and spatial relationships between different molecular species. Subtomogram averaging is an image-processing workflow that allows users to leverage cryo-ET data to identify and localize target molecules, determine high-resolution structures of repeating molecular species and classify different conformational states. Here, STOPGAP, an open-source package for subtomogram averaging that is designed to provide users with fine control over each of these steps, is described. In providing detailed descriptions of the image-processing algorithms that STOPGAP uses, this manuscript is also intended to serve as a technical resource to users as well as for further community-driven software development.

The detection of specific biological macromolecules in cryogenic electron tomography data is frequently approached by applying cross-correlation-based 3D template matching. To reduce computational cost and noise, high binning is used to aggregate voxels before template matching. This remains a prevalent practice in both practical applications and methods development. Here, the relation between template size, shape and angular sampling is systematically evaluated to identify ribosomes in a ground-truth annotated data set. It is shown that at the commonly used binning, a detailed subtomogram average, a sphere and a heart emoji result in near-identical performance. These findings indicate that with current template-matching practices macromolecules can only be detected with high precision if their shape and size are sufficiently different from the background. Using theoretical considerations, the experimental results are rationalized and it is discussed why primarily low-frequency information remains at high binning and that template matching fails to be accurate because similarly shaped and sized macromolecules have similar low-frequency spectra. These challenges are discussed and potential enhancements for future template-matching methodologies are proposed.

Characterization of a material structure with pair distribution function (PDF) analysis typically involves refining a structure model against an experimental data set, but finding or constructing a suitable atomic model for PDF modelling can be an extremely labour-intensive task, requiring carefully browsing through large numbers of possible models. Presented here is POMFinder, a machine learning (ML) classifier that rapidly screens a database of structures, here polyoxometallate (POM) clusters, to identify candidate structures for PDF data modelling. The approach is shown to identify suitable POMs from experimental data, including in situ data collected with fast acquisition times. This automated approach has significant potential for identifying suitable models for structure refinement to extract quantitative structural parameters in materials chemistry research. POMFinder is open source and user friendly, making it accessible to those without prior ML knowledge. It is also demonstrated that POMFinder offers a promising modelling framework for combined modelling of multiple scattering techniques.

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

A multi-slit very small angle neutron scattering (MS-VSANS) instrument has been finally accepted at the China Spallation Neutron Source (CSNS). It is the first spallation neutron source based VSANS instrument. MS-VSANS has a good signal-to-noise ratio and can cover a wide scattering vector magnitude range from 0.00028 to 1.4 Å−1. In its primary flight path, a combined curved multichannel beam bender and sections of rotary exchange drums are installed to minimize the background downstream of the instrument. An exchangeable multi-slit beam focusing system is integrated into the primary flight path, enabling access to a minimum scattering vector magnitude of 0.00028 Å−1. MS-VSANS has three modes, namely conventional SANS, polarizing SANS and VSANS modes. In the SANS mode, three motorized high-efficiency 3He tube detectors inside the detector tank cover scattering angles from 0.12 to 35° simultaneously. In the polarizing SANS mode, a double-V cavity provides highly polarized neutrons and a high-efficiency 3He polarization analyser allows full polarization analysis. In the VSANS mode, an innovative high-resolution gas electron multiplier detector covers scattering angles from 0.016 to 0.447°. The absolute scattering intensities of a selection of standard samples are obtained using the direct-beam technique; the effectiveness of this method is verified by testing the standard samples and comparing the results with those from a benchmark instrument. The MS-VSANS instrument is designed to be flexible and versatile and all the design goals have been achieved.

Serial crystallography experiments at synchrotron and X-ray free-electron laser (XFEL) sources are producing crystallographic data sets of ever-increasing volume. While these experiments have large data sets and high-frame-rate detectors (around 3520 frames per second), only a small percentage of the data are useful for downstream analysis. Thus, an efficient and real-time data classification pipeline is essential to differentiate reliably between useful and non-useful images, typically known as `hit' and `miss', respectively, and keep only hit images on disk for further analysis such as peak finding and indexing. While feature-point extraction is a key component of modern approaches to image classification, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. This paper proposes a pipeline to categorize the data, consisting of a real-time feature extraction algorithm called modified and parallelized FAST (MP-FAST), an image descriptor and a machine learning classifier. For parallelizing the primary operations of the proposed pipeline, central processing units, graphics processing units and field-programmable gate arrays are implemented and their performances compared. Finally, MP-FAST-based image classification is evaluated using a multi-layer perceptron on various data sets, including both synthetic and experimental data. This approach demonstrates superior performance compared with other feature extractors and classifiers.

Macromolecular crystallography contributes significantly to understanding diseases and, more importantly, how to treat them by providing atomic resolution 3D structures of proteins. This is achieved by collecting X-ray diffraction images of protein crystals from important biological pathways. Spotfinders are used to detect the presence of crystals with usable data, and the spots from such crystals are the primary data used to solve the relevant structures. Having fast and accurate spot finding is essential, but recent advances in synchrotron beamlines used to generate X-ray diffraction images have brought us to the limits of what the best existing spotfinders can do. This bottleneck must be removed so spotfinder software can keep pace with the X-ray beamline hardware improvements and be able to see the weak or diffuse spots required to solve the most challenging problems encountered when working with diffraction images. In this paper, we first present Bragg Spot Detection (BSD), a large benchmark Bragg spot image dataset that contains 304 images with more than 66 000 spots. We then discuss the open source extensible U-Net-based spotfinder Bragg Spot Finder (BSF), with image pre-processing, a U-Net segmentation backbone, and post-processing that includes artifact removal and watershed segmentation. Finally, we perform experiments on the BSD benchmark and obtain results that are (in terms of accuracy) comparable to or better than those obtained with two popular spotfinder software packages (Dozor and DIALS), demonstrating that this is an appropriate framework to support future extensions and improvements.

A deep-learning algorithm is proposed for the inpainting of Bragg coherent diffraction imaging (BCDI) patterns affected by detector gaps. These regions of missing intensity can compromise the accuracy of reconstruction algorithms, inducing artefacts in the final result. It is thus desirable to restore the intensity in these regions in order to ensure more reliable reconstructions. The key aspect of the method lies in the choice of training the neural network with cropped sections of diffraction data and subsequently patching the predictions generated by the model along the gap, thus completing the full diffraction peak. This approach enables access to a greater amount of experimental data for training and offers the ability to average overlapping sections during patching. As a result, it produces robust and dependable predictions for experimental data arrays of any size. It is shown that the method is able to remove gap-induced artefacts on the reconstructed objects for both simulated and experimental data, which becomes essential in the case of high-resolution BCDI experiments.

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics (e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

The lineup from the "Justice League" animated series.; Credit: Warner Bros.

Bruce Timm's DC Comics animated universe, beginning with "Batman: The Animated Series" and continuing with "Superman," "Batman Beyond," "Justice League," "Justice League Unlimited" and more, remains one of the most beloved and critically acclaimed animated runs in existence. The run was so idenified with the producer that it was sometimes called the Timmverse, but the last show in that continuity ended in 2006 and Timm officially stepped down from working with DC animation in 2013.

Now Timm is back. He's providing a darker take than the optimistic world he became known for in "Justice League: Gods and Monsters," a three-part digital series launching spring 2015 that will be tied in with a full-length animated film that comes out later that year, according to a press release.

Timm's also re-teaming with Alan Burnett, who worked with Timm on "Batman: The Animated Series." It's part of DC Comics' efforts to set up their new film "Batman v Superman: Dawn of Justice," which hits in 2016, with the full Justice League film set for 2018.

DC Comics as a whole has been moving in a darker direction with Christopher Nolan's Batman trilogy, the "Man of Steel" reboot of Superman and a more serious direction in many of its comic books. The company has followed in its tradition of epic storytelling, passing on the quips Marvel has popularized in films from "Iron Man" to "Guardians of the Galaxy."

It's yet to be seen if Timm can recapture any of the magic from his classic cartoons, but there's reason to be optimistic for the creator of the series that introduced fan favorite Joker sidekick Harley Quinn, created a new origin for Mr. Freeze that cemented the character in the Batman mythos and led the team reimagining numerous characters in an iconic, broadly appealing way.

If you want to catch up on Timm's legacy, his previous two Justice League series are available on Netflix and Amazon Prime, along with "Batman Beyond," while the Batman and Superman animated series are available on Amazon Prime.

Timm also recently produced a short for the 75th anniversary of Batman called "Strange Days," setting the character in the retro world of the serialized pulp storytelling from the time Batman was originally created. You can watch that below:

Batman anniversary short

Watch the classic opening to "Batman: The Animated Series":

Batman: The Animated Series opening

And, a personal favorite joke from when Lex Luthor and the Flash trade bodies on "Justice League Unlimited":

Flash/Luthor body swap

The back cover photo splash from Ruth Batchelor's album "Songs for Women's Liberation: Reviving a Dream"; Credit:

I’ve been a member of the LA Film Critics Association since 1999. LAFCA is a good group - collegial and filled with real movie lovers. But it has a problem.

It's a professional organization, meaning a baseline for membership is you have to have a job, and film criticism is overwhelmingly white and male. 78 percent of the top critics listed on RottenTomatoes are male, and women write only 18 percent of the major reviews. So LAFCA is like the profession itself: overwhelmingly a platform for white men.

It's trying to diversify. It has been for years. But how do you do that when the pool you draw from has a huge institutional bias? According to film critic Claudia Puig, "Criticism has been a white male dominated field for very long. And it continues to be. And not just white males, but middle aged."

Claudia is the current LAFCA president - and a legendary critic, who wrote lead reviews for 14 years at USA Today, and now appears regularly on KPCC’s Film Week.

"Very few movies pass the Bechdel Test. Women are often just girlfriends, wives, mothers. They don't get to have a story arc of their own. But if you had more women reviewing these movies, they would point out certain things that people might not notice as potentially offensive. Because we have been harassed, or we have experienced any number of things. It's something I've grappled with through my entire career." - Claudia Puig

I'm on a committee with Claudia for the LA Film Critics. The concept is to mentor young writers - to generate diversity, from the ground up. One idea is to have a scholarship for aspiring female film critics. We thought it would be good to name it after a prominent woman from the group's past.

So I went to Myron Meisel, who joined LAFCA in 1979, just four years after it formed, and I asked him, "Is there a woman you can think of who played an especially prominent role in the history of the LA Film Critics Association?" "Oh!," Myron said. "Ruth Batchelor was the founder and driving force..." "Wait, what?" I asked. "LAFCA was founded by a woman?"

"We weren't shocked. You had Ruth, who was very much concerned with creating a Los Angeles equivalent to the New York Film Critics Association. Which she largely pulled together by force of will. While Ruth was the moving force, you really can't discount her ability to martial the enthusiastic support of Charles Champlin as a co-founder, and the imprimatur of the Los Angeles Times behind him. Ruth had an enviable ability to make everything she undertook seem inevitable." - Myron Meisel

It's poignant, isn't it? And a little creepy. A prestigious group commits to gender diversity, and somehow, it doesn't have the institutional memory to know that the pivotal figure in its history was a woman.

How could we forget Ruth? Batchelor was nothing if not memorable. Before she became a pundit, she was a successful pop songwriter in the style of Neil Sedaka, or Goffin and King. She wrote dozens of songs, recorded by everybody from Phil Spector to the Partridge Family. She wrote Elvis Presley numbers, including "Cotton Candy Land," which might be the most hated track in the Presley catalogue.

But Batchelor also wrote "Where Do You Come From?", which is beautiful.

Elvis Presley performing Ruth Batchelor's "Where do you come from?"

Where do you come from, Ruth?

It wasn't easy to find out.

Batchelor's New York Times obituary was full of false leads. It said she was a critic for National Public Radio. She wasn't, but when NPR searched their archives, they unearthed a lead: a Film Comment article from 1982, where Batchelor is described as "Ruth Batchelor of National Public Radio's 'As it Happens.'" "As It Happens" airs on Canada's CBC.

So I placed a call. And I waited.

Meanwhile, I found a blog post about Batchelor as a songwriter on an excellent site called "Zero to 180 - 3 Minute Magic." The title of the post was riveting: "First 'Women's Liberation LP.'"

It turns out in 1971, Ruth Batchelor self-produced and financed a concept album called "Songs for Women's Liberation: Reviving a Dream." 

Myron Meisel told me about Ruth's earthy sense of humor, and it's right there in the first write-up's, where her working title is "A Quarter for the Ladies Room." A Billboard article from August 1971 quotes Batchelor about the album: "Right now I have an album of dirty Women's Liberation poems recorded, and I'm trying to sell the master." Then she laughs. "The last record company I recorded for folded."

Batchelor shopped her record. There were no takers.

But Batchelor proved unstoppable. She created her own record company and called it Femme Records. Then she put out what the leftist journal Broadside called "the first feminist record album," all by herself. "Reviving a Dream" is forgotten, bordering on lost. It's never been available for streaming, or released on CD.

Batchelor's record is a pastiche of radio styles from her era. There's Joan Baez folk, two drawling country laments, even some call and response stuff Batchelor probably learned from Phil Spector and his girl groups.

Are Batchelor's songs any good? They're amazing. Amazing just because they exist.

She fits into the churning sea of anonymous faces so seamlessly it takes awhile to realize: She's Ruth Batchelor. The woman who founded the LA Film Critics. A group currently struggling with gender diversity.

LAFCA prez Claudia Puig agreed to an interview knowing it had to do with LAFCA, but not what it was about. I played her Batchelor's song "Drop the Mop." Batchelor intended it as an anthem, scored to a tempo of marching feet.

The listen was awkward - like force feeding a roommate your iTunes playlist. Claudia took notes the whole time, to occupy her critical mind, but I could see when it ended that she was moved.

 "Yeah, it's a really interesting song," Claudia said. "My reaction is sort of...ummm..."

Claudia hesitated, looking for words.

"And this was the origin of the group. Yeah. It really kind of... It is really interesting. I'd never heard of her. She was right there, fighting that fight." 

"And here, we were looking for an avatar," I said.

"Right. Right. It means something. This is a really important discovery that you made."

A piece of the portrait was missing - an essential one. It came courtesy of Kevin Robertson, a producer for "As It Happens" at the CBC. Batchelor had been the show's "Hollywood Correspondent" in the early 1980s. There was audio in the archives. Kevin provided me with five MP3s.

Batchelor's CBC brand was gender traditional. She was the tinseltown gadfly, a niche created by Hedda Hopper and Louella Parsons in the 1930s. There was gossip about Burt Reynolds and Loni Anderson. Richard Burton's widow. Marvin Hamlisch. TV's "Gomer Pyle."

It was kitsch heaven, so I wasn't disappointed. Not exactly. But it was still a bit like listening to Wonder Woman try to be ordinary, because hey, we all gotta eat.

Ruth Batchelor's "Mr. Principal"

The LA Film Critics get a cameo in Batchelor's Oscar season broadcast, when she mentions her LAFCA Awards vote. For awhile, I thought that would be the only audio connecting the "As It Happens" Ruth Batchelor to the feminist fireball she wanted to be.

Then Batchelor starts riffing on "Partners," a buddy cop farce about a straight cop who goes undercover as a gay man. The film had sparked protests from the gay community. Batchelor is unsympathetic, which is surprising in a civil rights pioneer. Her reasoning is devastating.

"You know if women got angry every time there was a movie against women," Batchelor says, "there wouldn't be any movies."

Batchelor died of cancer early - she was just 58. 25 years later, men still direct most mainstream movies - 93 percent as of 2015. They have 70 percent of the speaking parts, and play 88 percent of the leads.

While women get to be naked twice as often in American movies.

Men review almost all movies too. Maybe that's why Ruth Batchelor founded the LA Film Critics. Because she lived in that world. She covered it. Spoke to it. Fought hard against it.

And then left behind a hidden legacy.

"She is our avatar," Claudia says, as our interview time runs out. "It sort of makes me want to redouble our efforts to honor her spirit."

This content is from Southern California Public Radio. View the original story at SCPR.org.

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How do galaxies such as our Milky Way come into existence? How do they grow and change over time? The science behind galaxy formation has long been a puzzle, but a University of Arizona-led team of scientists is one step closer to finding answers, thanks to supercomputer simulations. Observing real galaxies in space can only provide snapshots in time, so researchers who study how galaxies evolve over billions of years need to use computer simulations. Traditionally, astronomers have used simulations to invent theories of galaxy formation and test them, but they have had to proceed one galaxy at a time. Peter Behroozi of the university's Steward Observatory and colleagues overcame this hurdle by generating millions of different universes on a supercomputer, each according to different physical theories for how galaxies form. The findings challenge fundamental ideas about the role dark matter plays in galaxy formation, the evolution of galaxies over time and the birth of stars. The study is the first to create self-consistent universes that are exact replicas of the real ones -- computer simulations that each represent a sizeable chunk of the actual cosmos, containing 12 million galaxies and spanning the time from 400 million years after the Big Bang to the present day. The results from the "UniverseMachine," as the authors call their approach, have helped resolve the long-standing paradox of why galaxies cease to form new stars even when they retain plenty of hydrogen gas, the raw material from which stars are forged. The research is partially funded by NSF's Division of Physics through grants to UC Santa Barbara's Kavli Institute for Theoretical Physics and the Aspen Center for Physics.

Image credit: NASA/ESA/J. Lotz and the HFF Team/STScI

SEB Embedded has selected Thought Machine’s cloud-native core banking system, Vault Core, as the foundation for its latest service offering.

Adult Chinook salmon in Alaska and Canada are in trouble, and USGS WFRC scientists are in a race against the clock to find the cause behind their disappearance and a viable solution. A staple in many diets, this salmon species is considered a lifeblood of the region.

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Machine learning algorithms can sometimes do a great job with a little help from human expertise, at least in the field of materials science. In many specialized areas of science, engineering and medicine, researchers are turning to machine learning algorithms to analyze data sets that have grown too large for humans to understand. In materials science, success with this effort could accelerate the design of next-generation advanced functional materials, where development now usually depends on old-fashioned trial and error. By themselves, however, data analytics techniques borrowed from other research areas often fail to provide the insights needed to help materials scientists and engineers choose which of many variables to adjust -- and the techniques can't account for dramatic changes such as the introduction of a new chemical compound into the process. In a new study, researchers explain a technique known as dimensional stacking, which shows that human experience still has a role to play in the age of machine intelligence. The machines gain an edge at solving a challenge when the data to be analyzed are intelligently organized based on human knowledge of what factors are likely to be important and related. "When your machine accepts strings of data, it really does matter how you are putting those strings together," said Nazanin Bassiri-Gharb, the paper's corresponding author and a scientist at the Georgia Institute of Technology. "We must be mindful that the organization of data before it goes to the algorithm makes a difference. If you don't plug the information in correctly, you will get a result that isn't necessarily correlated with the reality of the physics and chemistry that govern the materials."

Image credit: Rob Felt/Georgia Tech

SEOUL, South Korea (AP) — The United States and China, the world's two biggest carbon polluters, agreed to cooperate to curb climate change with urgency, just days before President Joe Biden hosts a virtual summit of world leaders to discuss the issue.

The agreement was reached by U.S. special envoy for climate John Kerry and his Chinese counterpart Xie Zhenhua during two days of talks in Shanghai last week, according to a joint statement.

The two countries "are committed to cooperating with each other and with other countries to tackle the climate crisis, which must be addressed with the seriousness and urgency that it demands," the statement said.

China is the world's biggest carbon emitter, followed by the United States. The two countries pump out nearly half of the fossil fuel fumes that are warming the planet's atmosphere. Their cooperation is key to a success of global efforts to curb climate change, but frayed ties over human rights, trade and China's territorial claims to Taiwan and the South China Sea have been threatening to undermine such efforts.

Meeting with reporters in Seoul on Sunday, Kerry said the language in the statement is "strong" and that the two countries agreed on "critical elements on where we have to go." But the former secretary of state said, "I learned in diplomacy that you don't put your back on the words, you put on actions. We all need to see what happens."

Noting that China is the world's biggest coal user, Kerry said he and Chinese officials had a lot of discussions on how to accelerate a global energy transition. "I have never shied away from expressing our views shared by many, many people that it is imperative to reduce coal, everywhere," he said.

Biden has invited 40 world leaders, including Chinese President Xi Jinping, to the April 22-23 summit. The U.S. and other countries are expected to announce more ambitious national targets for cutting carbon emissions ahead of or at the meeting, along with pledging financial help for climate efforts by less wealthy nations.

It's unclear how much Kerry's China visit would promote U.S.-China cooperation on climate issues.

While Kerry was still in Shanghai, Chinese Vice Foreign Minister Le Yucheng signaled Friday that China is unlikely to make any new pledges at next week's summit.

"For a big country with 1.4 billion people, these goals are not easily delivered," Le said during an interview with The Associated Press in Beijing. "Some countries are asking China to achieve the goals earlier. I am afraid this is not very realistic."

During a video meeting with German and French leaders Friday, Xi said that climate change "should not become a geopolitical chip, a target for attacking other countries or an excuse for trade barriers," the official Xinhua News Agency reported.

On whether Xi would join the summit, Le said "the Chinese side is actively studying the matter."

The joint statement said the two countries "look forward to" next week's summit. Kerry said Sunday that "we very much hope that (Xi) will take part" in the summit but it's up to China to make that decision.

Biden, who has said that fighting global warming is among his highest priorities, had the United States rejoin the historic 2015 Paris climate accord in the first hours of his presidency, undoing the U.S. withdrawal ordered by predecessor Donald Trump.

Major emitters of greenhouse gases are preparing for the next U.N. climate summit taking place in Glasgow, U.K., in November. The summit aims to relaunch global efforts to keep rising global temperatures to below 1.5 degrees Celsius (2.7 degrees Fahrenheit) as agreed in the Paris accord.

According to the U.S.-China statement, the two countries would enhance "their respective actions and cooperating in multilateral processes, including the United Nations Framework Convention on Climate Change and the Paris Agreement."

It said both countries also intend to develop their respective long-term strategies before the Glasgow conference and take "appropriate actions to maximize international investment and finance in support of" the energy transition in developing countries.

Xi announced last year that China would be carbon-neutral by 2060 and aims to reach a peak in its emissions by 2030. In March, China's Communist Party pledged to reduce carbon emissions per unit of economic output by 18% over the next five years, in line with its goal for the previous five-year period. But environmentalists say China needs to do more.

Biden has pledged the U.S. will switch to an emissions-free power sector within 14 years, and have an entirely emissions-free economy by 2050. Kerry is also pushing other nations to commit to carbon neutrality by then.

This content is from Southern California Public Radio. View the original story at SCPR.org.

; Credit: /Ryan Raphael for NPR

To say Leah Juelke is an award-winning teacher is a bit of an understatement. She was a top 10 finalist for the Global Teacher Prize in 2020; she was North Dakota's Teacher of the Year in 2018; and she was awarded an NEA Foundation award for teaching excellence in 2019.

But Juelke, who teaches high school English learners in Fargo, N.D., says nothing prepared her for teaching during the pandemic.

"The level of stress is exponentially higher. It's like nothing I've experienced before."

It's a sentiment NPR heard from teachers across the country. After a year of uncertainty, long hours and juggling personal and work responsibilities, many told NPR they had reached a breaking point.

Heidi Crumrine, a high school English teacher in Concord, N.H., says this has been the most challenging year she's ever encountered in her two decades of teaching.

"And I say [that] as someone who started her first day of teaching on 9/11 in the Bronx in New York City."

Teaching is one of the most stressful occupations in the U.S., tied only with nurses, a 2013 Gallup poll found. Jennifer Greif Green, an education professor at Boston University, says the additional stress teachers are reporting during the pandemic is worrying because it doesn't only affect educators — it also affects students.

"The mental health and well-being of teachers can have a really important impact on the mental health and well-being of the children who they're spending most of their days with," Green explains. "Having teachers feel safe and supported in their school environments is essential to students learning and being successful."

Lisa Sanetti, a professor of educational psychology at the University of Connecticut, says, "Chronically stressed teachers are just less effective in the classroom."

All that stress can also lead to burnout, which leads to teachers leaving the profession, Sanetti says. "And we have a huge teacher turnover problem in our country."

Districts are trying to help — with yoga classes, counseling sessions and webinars on mental health. Some teachers have organized trivia nights or online happy hours where colleagues can just vent. Teachers told NPR they force themselves to take breaks and go for a bike ride or call a friend. Some have started therapy.

But most of the educators NPR spoke with say they're so exhausted, that even self-care feels like one additional thing to do.

"The reality is, when you're living it, you're just trying to get to the end of the day successfully and try again tomorrow," Crumrine says.

"It feels like we're building the plane while we're flying it"

In March 2020, when schools moved online, teachers across the U.S. had to completely reimagine their approach to education, often with no training or time to prepare. For many, it was a rough transition.

Teachers told NPR they've spent the past year experimenting with different methods of online and hybrid teaching, while also providing tech support for their students and families. Many say they routinely work 12-hour days and on weekends, yet struggle to form relationships with children virtually. Answering emails can take two hours a day.

Rashon Briggs, who teaches high school special education in Los Angeles, spent a lot of time worrying about his students during remote learning (his district only recently started offering in-person options). "One of the biggest challenges is knowing that the kids were not getting the same level of service that they were getting in person," he says.

Teachers in districts that opened earlier for in-person learning say they have additional responsibilities now, such as sanitizing desks between classes, making sure children follow school safety protocols and keeping track of students who have had to quarantine.

"I have a calendar and it says who's quarantined, who is cleared to return on what day, who was absent," explains Rosamund Looney, who teaches first grade in Jefferson Parish, La. "Then I follow up with those families to see: 'Are you OK?' So there's just so much space taken up by that monitoring."

Looney also worries about her students' learning. Everyone in her district has to wear masks in class, which she says she completely agrees with. But those masks mean she can't see her first graders' mouths as they learn phonics.

"You are watching your teacher sound out words and then figuring out how to do that. And it's really hard for me to gauge what they are and aren't able to say." She says she's especially concerned about students who are more at risk of falling behind academically, like English learners.

In New Hampshire, Crumrine says quarantines and positive cases among school staff have led to a constant shifting between fully online and hybrid classes. The fluctuations have been exhausting for her. "We started the year remote. Then we went back to school in October, then we were remote again in November, December. We went back to hybrid [in early February]," she says. New Hampshire's governor has now ordered all schools reopen for full-time, in-person classes by this week.

"It feels like we're building the plane while we're flying it and the destination keeps changing on us," Crumrine says.

Balancing work and home life

In addition to worrying about their students, many teachers are also concerned about their own children. Crumrine, whose husband is also a teacher, has three children and says she feels pulled by competing demands.

"I feel this sense of guilt that I'm not a good enough teacher for my students and I'm not a good mother for my own kids. It just feels like a constant wave of never feeling like I can do what I know I'm good at."

Juelke, in North Dakota, is a single mom with a 9- and 3-year-old. "I'm juggling the children and making sure my daughter is in her class and my 3-year-old is entertained. And that is definitely taking a toll."

Many teachers say they are eating and drinking more, and exercising and sleeping less.

Briggs, in L.A., says his sleeping patterns are completely off. "Being awake all hours of the night, going to bed at 2, 3 a.m., drinking coffee late at night and try to finish work so I can be more prepared the next day."

He's stressed, in part, because there are no clear work-life boundaries anymore. "When you're waking up in the same space that you're on Zoom, that you're grading papers, that you're watching Netflix, those lines are blurred very easily."

Others say they're not as active at home, and they're eating more junk food and putting on weight. The tight schedules means they don't always move between classes, or even remember to drink water.

"There are a lot of dehydrated teachers out there," says Looney.

Many, like Juelke, say they miss having personal time. "That time where I could sit in the car and drive to work and just kind of relax a little, or my prep time at school alone. That's gone now. And so I feel like my mental health has struggled in that way."

She says even though it breaks her heart, she's started looking for another profession.

Leonda Archer, a middle school math teacher in Arlington, Va., says she's usually a very upbeat person, but the pandemic — coupled with the racial turmoil in the country — has taken a toll. She's African American, and says reports of Black men and women being killed by police makes her fear for her husband's safety.

"There were some points of lowness that I hadn't experienced before. There are some days where I feel like it's hard to keep going."

Archer says she has had difficulty sleeping, and doesn't have an appetite. "And right when I get into a groove, another traumatic experience happens."

Briggs says it was hard not being able to process events like George Floyd's death and the Black Lives Matter protests with his colleagues. In the past, those conversations informed what he would say in the classroom to help his own students make sense of the news.

"The teachers were not able to talk to each other about 'How do you talk about this? How do you present that?' " he says. "There was a lack of ability for us to communicate a message about social justice and rights and the wrongs."

Crumrine says she misses the social aspect of being with her students, and other teachers. "We're not eating lunch together. We're not popping into each other's classrooms. We're all in our little silos."

The school reopening divide

Teachers told NPR they feel a growing chasm in their communities: Parents want schools to open, but teachers first want to make sure it's safe. Many feel they are not being included in these conversations, and their concerns aren't being taken seriously.

Crumrine says it's been devastating hearing elected officials and parents criticize teachers, insisting that schools need to open, even though teachers are concerned about their own health. She says some community members acted like online classes meant teachers weren't working at all. In fact, she says, they were working harder than ever. "It just makes it feel so much worse when you read these horrible things that people say about us or these assumptions that they make about what we are or are not doing."

She says many states, including her own, didn't prioritize vaccines for teachers, which to her revealed just "how deep that lack of value of educators is."

Sarahi Monterrey, who teaches English learners in Waukesha, Wisc., says she's felt a "huge divide" in the community. "It almost seems like us against them." She was in a Zoom school board meeting where parents and students were present, and a teacher testified that her husband had COVID-19. "And a parent in the room said, 'Who cares?' And I was blown away. Just blown away."

In Virginia, Archer says, at the beginning of the pandemic, "We were seen as angels. Like, 'Oh my God, I've been home with my child for two months, how do teachers do it?' And now the narrative has totally flip-flopped."

She says she also misses "the vibe of school, the energy, all of that. But I don't want people to be sick."

Archer works 12-hour days, and says people need to remember that teachers are people too. "Our profession is a nurturing one, but we also are humans that need to be poured into. We need to be nurtured, too."

This content is from Southern California Public Radio. View the original story at SCPR.org.

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