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Volume 32, Issue 7, December 2023. Read the full article ›

The post Historicising the perpetrators of sexual violence: global perspectives from the modern world was curated by information for practice.

Abstract Social work, as a human rights–based profession, is globally recognized as a profession committed to enhancing human well-being and helping meet the basic needs of all people, with a particular focus on those who are marginalized vulnerable, oppressed, or living in poverty. Artificial intelligence (AI), a sub-discipline of computer science, focuses on developing computers […]

The post Considering a Unified Model of Artificial Intelligence Enhanced Social Work: A Systematic Review was curated by information for practice.

The post Potential Schizophrenia Medications Point to New Disease Model was curated by information for practice.

The post Co-knowledge production linking science, communities and public policy under deep uncertainty in a modern risk society in Japan was curated by information for practice.

The Seventies House by AR Design Studio blends 1970s charm with modern design in Winchester, UK, creating a seamless indoor-outdoor experience.

Chronic Stress, Volume 8, Issue , January-December 2024. Police officers are frequently faced with chronic and acute stressors, such as excessive workload, organizational stressors and emotionally charged reports. This study aims to examine the relationship between a form of chronic strain (ie, burnout symptoms) and a resource (ie, coping self-efficacy) in a sample of Dutch […]

The post A Loss Cycle of Burnout Symptoms and Reduced Coping Self-Efficacy: A Latent Change Score Modelling Approach was curated by information for practice.

Introduction

Arm architects the pervasive intelligence that is transforming our daily experience. Arm-based chips and device architectures orchestrate the performance of the technology that makes modern life possible.Arm designs the technology which is at the heart of advanced digital products, from wireless, networking and consumer entertainment solutions to imaging, automotive, security and storage devices. Arm improves people’s lives by enabling the intelligence in affordable, easy-to-use electronic products that transform the way we live and work. We work in partnership with a global network of leading technology companies which are using our smart low-power technology. Together we are shaping the future of a better world.

Today, We are well recognized as the market leader in the CPU and System IP industry and this has been achieved by consistently delivering reliable and high-quality IP products. The cost of design and manufacturing and that warrants “right first time” approach for all IP and System products by our partners. Time-to-market is critical for our partners to deal with fierce competition in the marketplace, being first would enable them to get premium value from the end products. In this context, Design Verification of CPU IPs is a big challenge requiring an engineering skillset that is both broad and deep.

About this role

If you are a technical lead with engineering expertise in CPU microarchitecture, performance-model development, performance analysis, or workload analysis, we would like to talk with you about joining Arm’s highly successful CPU performance architecture team based in Austin.  Our team plays a major role in crafting our next-generation Cortex-A class CPU designs and in enabling Arm partners to use our designs in world-class products. As a senior member of this expert team, you will own substantial and challenging performance projects

• Collaborate with other members of the design team - primarily in Austin - to help design our next-generation CPU microarchitecture
• Lend your expertise across all Performance sub-disciplines: microarchitecture and performance model development, microarchitectural performance analysis, RTL/performance-model correlation, workload analysis, and workload development
• Engage with key partners at an engineering level to understand their future performance requirements, performance sensitivities, and workload expectations
• Help develop the team and be a mentor to engineers
• Interact with customers and other third parties to successfully communicate complex technical ideas, and participate in internal and customer meetings

The post Efficacy and Safety of Sustained-release Dexamphetamine in Patients With Moderate to Severe Cocaine Use Disorder was curated by information for practice.

Architects Antonia Frey-Vorhammer and Simon Vorhammer, of SIAN, design jewelry that mirrors their highly intricate + geometric projects.

Organizational Research Methods, Ahead of Print. When modeling responses to items measuring non-cognitive constructs that require introspection (e.g., personality, attitude), most studies have assumed that respondents follow the same item response process—either a dominance or an unfolding one. Nevertheless, the results are not equivocal, as some preliminary evidence suggests that some people use an unfolding […]

The post One Size Does Not Fit All: Unraveling Item Response Process Heterogeneity Using the Mixture Dominance-Unfolding Model (MixDUM) was curated by information for practice.

Culture &Psychology, Ahead of Print. In secular Western societies, individuals often embark on an autonomous quest for meaning in life, which, however, can lead to frustration. In contrast, many East Asian ethical leaders draw on age-old teachings to find fulfillment—an underexplored topic that merits further investigation. By analyzing ancient Confucian tenets and the discourses of […]

The post Ethical leaders’ search for meaning: Ancient Confucian wisdom in Modern East Asia was curated by information for practice.

Space is around us transforms the Kyano apartment in Athens into a sleek, multifunctional space that blends history with contemporary design.

Design Milk's latest 2024 holiday gift guide will give you enviable objects to splurge on a dearly beloved or special friend.

From imaginative play sets to museum-worthy crafts, these modern gift ideas promise wide-eyed wonder and endless fun for kids of all ages.

The Runda tables by Form Us With Love for Rareraw redefine modern design with adaptable, sustainable features that evolve alongside your home.

From tabletop accessories to wall art to the rug beneath your feet, Design Milk has curated the perfect gift guide with ideas under $100.

Marcus of All Trades posted a photo:

It can costs kids and parents several hundred dollars to play a single sport in high school. Could there be big changes to the "pay-to-play" system in Ohio?

By Marc Malafronte, director of sales, VIPRE Security Group.

As cyberattacks increase in frequency and sophistication, businesses must prioritize cybersecurity as a critical investment area. Managed service providers (MSPs) are crucial in supporting organizations on their cybersecurity journey.

The University of Pennsylvania Graduate School of Education (Penn GSE) has been awarded $3.5 million, part of a larger $8 million grant from Education Initiatives, to partner with the School District of Philadelphia (SDP) to launch The Academy at Penn, an innovative five-year, cohort-based college- and career-readiness model for high school students. Foundations, Inc. and the Consortium for Policy Research in Education (CPRE) were also awarded through the grant as part of the larger partnership. The close collaboration involves working together to design, implement, and evaluate the project.

First national-scale groundwater model in Great Britain developed  British Geological Survey

The rotating substrate method of crystallite deposition is modeled, allowing computation of effective material coefficients of the layers resulting from the averaging. A worked numerical example particularized to 6mm ZnO is provided.

Parameters in analytical models for X-ray form factors of ions f0(s), based on the inverse Mott–Bethe formula involving a variable number of Gaussians, are determined for a wide range of published data sets {s, f0(s)}. The models reproduce the calculated form-factor values close to what is expected from a uniform statistical distribution with limits determined by their precision. For different ions associated with the same atom, the number of Gaussians in the models decreases with increasing net positive charge.

Three-dimensional electron diffraction (3D-ED) is a powerful technique for crystallographic characterization of nanometre-sized crystals that are too small for X-ray diffraction. For accurate crystal structure refinement, however, it is important that the Bragg diffracted intensities are treated dynamically. Bloch wave simulations are often used in 3D-ED, but can be computationally expensive for large unit cell crystals due to the large number of diffracted beams. Proposed here is an alternative method, the `scattering cluster algorithm' (SCA), that replaces the eigen-decomposition operation in Bloch waves with a simpler matrix multiplication. The underlying principle of SCA is that the intensity of a given Bragg reflection is largely determined by intensity transfer (i.e. `scattering') from a cluster of neighbouring diffracted beams. However, the penalty for using matrix multiplication is that the sample must be divided into a series of thin slices and the diffracted beams calculated iteratively, similar to the multislice approach. Therefore, SCA is more suitable for thin specimens. The accuracy and speed of SCA are demonstrated on tri-iso­propyl silane (TIPS) pentacene and rubrene, two exemplar organic materials with large unit cells.

The strong interaction of high-energy electrons with a crystal results in both dynamical elastic scattering and inelastic events, particularly phonon and plasmon excitation, which have relatively large cross sections. For accurate crystal structure refinement it is therefore important to uncover the impact of inelastic scattering on the Bragg beam intensities. Here a combined Bloch wave–Monte Carlo method is used to simulate phonon and plasmon scattering in crystals. The simulated thermal and plasmon diffuse scattering are consistent with experimental results. The simulations also confirm the empirical observation of a weaker unscattered beam intensity with increasing energy loss in the low-loss regime, while the Bragg-diffracted beam intensities do not change significantly. The beam intensities include the diffuse scattered background and have been normalized to adjust for the inelastic scattering cross section. It is speculated that the random azimuthal scattering angle during inelastic events transfers part of the unscattered beam intensity to the inner Bragg reflections. Inelastic scattering should not significantly influence crystal structure refinement, provided there are no artefacts from any background subtraction, since the relative intensity of the diffracted beams (which includes the diffuse scattering) remains approximately constant in the low energy loss regime.

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.

This study examines the quality of charge density obtained by fitting the multipole model to wavefunctions in different basis sets. The complex analysis reveals that changing the basis set quality from double- to triple-zeta can notably improve the charge density related properties of a multipole model.

This study proposes an operation optimization framework for impurity-free recycling of spent lithium-ion batteries. Using a hybrid population balance equation integrated with a data-driven condition classifier, the study firstly identifies the optimal batch and semi-batch operation conditions that significantly reduce the operation time with 100% purity of product; detailed guidelines are given for industrial applications.

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.

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.

X-ray spectroscopy is a valuable technique for the study of many materials systems. Characterizing reactions in situ and operando can reveal complex reaction kinetics, which is crucial to understanding active site composition and reaction mechanisms. In this project, the design, fabrication and testing of an open-source and easy-to-fabricate electrochemical cell for in situ electrochemistry compatible with X-ray absorption spectroscopy in both transmission and fluorescence modes are accomplished via windows with large opening angles on both the upstream and downstream sides of the cell. Using a hobbyist computer numerical control machine and free 3D CAD software, anyone can make a reliable electrochemical cell using this design. Onion-like carbon nanoparticles, with a 1:3 iron-to-cobalt ratio, were drop-coated onto carbon paper for testing in situ X-ray absorption spectroscopy. Cyclic voltammetry of the carbon paper showed the expected behavior, with no increased ohmic drop, even in sandwiched cells. Chronoamperometry was used to apply 0.4 V versus reversible hydrogen electrode, with and without 15 min of oxygen purging to ensure that the electrochemical cell does not provide any artefacts due to gas purging. The XANES and EXAFS spectra showed no differences with and without oxygen, as expected at 0.4 V, without any artefacts due to gas purging. The development of this open-source electrochemical cell design allows for improved collection of in situ X-ray absorption spectroscopy data and enables researchers to perform both transmission and fluorescence simultaneously. It additionally addresses key practical considerations including gas purging, reduced ionic resistance and leak prevention.

Count-loss characteristics of photon-counting 2D detectors are demonstrated for eight bunch-modes at SPring-8 through Monte Carlo simulations. As an indicator, the effective maximum count rate was introduced to signify the X-ray intensity that the detector can count with a linearity of 1% or better after applying a count-loss correction in each bunch-mode. The effective maximum count rate is revealed to vary depending on the bunch-mode and the intrinsic dead time of the detectors, ranging from 0.012 to 0.916 Mcps (megacounts per second) for a 120 ns dead time, 0.009 to 0.807 Mcps for a 0.5 µs dead time and 0.020 to 0.273 Mcps for a 3 µs intrinsic detector dead time. Even with equal-interval bunch-modes at SPring-8, the effective maximum count rate does not exceed 1 Mcps pixel−1. In other words, to obtain data with a linearity better than 1%, the maximum intensity of X-rays entering the detector should be reduced to 1 Mcps pixel−1 or less, and, in some cases, even lower, depending on the bunch-mode. When applying count-loss correction using optimized dead times tailored to each bunch-mode, the effective maximum count rate exceeds the values above. However, differences in the effective maximum count rate due to bunch-modes persist. Users of photon-counting 2D detectors are encouraged to familiarize themselves with the count-loss characteristics dependent on bunch-mode, and to conduct experiments accordingly. In addition, when designing the time structure of bunch-modes at synchrotron radiation facilities, it is essential to take into account the impact on experiments using photon-counting 2D detectors.

Maximizing the performance of crystal monochromators is a key aspect in the design of beamline optics for diffraction-limited synchrotron sources. Temperature and deformation of cryo-cooled crystals, illuminated by high-power beams of X-rays, can be estimated with a purely analytical model. The analysis is based on the thermal properties of cryo-cooled silicon crystals and the cooling geometry. Deformation amplitudes can be obtained, quickly and reliably. In this article the concept of threshold power conditions is introduced and defined analytically. The contribution of parameters such as liquid-nitro­gen cooling efficiency, thermal contact conductance and interface contact area of the crystal with the cooling base is evaluated. The optimal crystal illumination and the base temperature are inferred, which help minimize the optics deformation. The model has been examined using finite-element analysis studies performed for several beamlines of the Diamond-II upgrade.

Density modification is a standard step to provide a route for routine structure solution by any experimental phasing method, with single-wavelength or multi-wavelength anomalous diffraction being the most popular methods, as well as to extend fragments or incomplete models into a full solution. The effect of density modification on the starting maps from either source is illustrated in the case of SHELXE. The different modes in which the program can run are reviewed; these include less well known uses such as reading external phase values and weights or phase distributions encoded in Hendrickson–Lattman coefficients. Typically in SHELXE, initial phases are calculated from experimental data, from a partial model or map, or from a combination of both sources. The initial phase set is improved and extended by density modification and, if the resolution of the data and the type of structure permits, polyalanine tracing. As a feature to systematically eliminate model bias from phases derived from predicted models, the trace can be set to exclude the area occupied by the starting model. The trace now includes an extension into the gamma position or hydrophobic and aromatic side chains if a sequence is provided, which is performed in every tracing cycle. Once a correlation coefficient of over 30% between the structure factors calculated from such a trace and the native data indicates that the structure has been solved, the sequence is docked in all model-building cycles and side chains are fitted if the map supports it. The extensions to the tracing algorithm brought in to provide a complete model are discussed. The improvement in phasing performance is assessed using a set of tests.

The axoneme, a microtubule-based array at the center of every cilium, has been the subject of structural investigations for decades, but only recent advances in cryo-EM and cryo-ET have allowed a molecular-level interpretation of the entire complex to be achieved. The unique properties of the nine doublet microtubules and central pair of singlet microtubules that form the axoneme, including the highly decorated tubulin lattice and the docking of massive axonemal complexes, provide opportunities and challenges for sample preparation, 3D reconstruction and atomic modeling. Here, the approaches used for cryo-EM and cryo-ET of axonemes are reviewed, while highlighting the unique opportunities provided by the latest generation of AI-guided tools that are transforming structural biology.

Lanthanide ions have ideal chemical properties for catalysis, such as hard Lewis acidity, fast ligand-exchange kinetics, high coordination-number preferences and low geometric requirements for coordination. As a result, many small-molecule lanthanide catalysts have been described in the literature. Yet, despite the ability of enzymes to catalyse highly stereoselective reactions under gentle conditions, very few lanthanoenzymes have been investigated. In this work, the mononuclear binding of europium(III) and gadolinium(III) to the active site of a mutant of the model enzyme phosphotriesterase are described using X-ray crystallography at 1.78 and 1.61 Å resolution, respectively. It is also shown that despite coordinating a single non-natural metal cation, the PTE-R18 mutant is still able to maintain esterase activity.

During the automatic processing of crystallographic diffraction experiments, beamstop shadows are often unaccounted for or only partially masked. As a result of this, outlier reflection intensities are integrated, which is a known issue. Traditional statistical diagnostics have only limited effectiveness in identifying these outliers, here termed Not-Excluded-unMasked-Outliers (NEMOs). The diagnostic tool AUSPEX allows visual inspection of NEMOs, where they form a typical pattern: clusters at the low-resolution end of the AUSPEX plots of intensities or amplitudes versus resolution. To automate NEMO detection, a new algorithm was developed by combining data statistics with a density-based clustering method. This approach demonstrates a promising performance in detecting NEMOs in merged data sets without disrupting existing data-reduction pipelines. Re-refinement results indicate that excluding the identified NEMOs can effectively enhance the quality of subsequent structure-determination steps. This method offers a prospective automated means to assess the efficacy of a beamstop mask, as well as highlighting the potential of modern pattern-recognition techniques for automating outlier exclusion during data processing, facilitating future adaptation to evolving experimental strategies.

The availability of highly accurate protein structure predictions from AlphaFold2 (AF2) and similar tools has hugely expanded the applicability of molecular replacement (MR) for crystal structure solution. Many structures can be solved routinely using raw models, structures processed to remove unreliable parts or models split into distinct structural units. There is therefore an open question around how many and which cases still require experimental phasing methods such as single-wavelength anomalous diffraction (SAD). Here, this question is addressed using a large set of PDB depositions that were solved by SAD. A large majority (87%) could be solved using unedited or minimally edited AF2 predictions. A further 18 (4%) yield straightforwardly to MR after splitting of the AF2 prediction using Slice'N'Dice, although different splitting methods succeeded on slightly different sets of cases. It is also found that further unique targets can be solved by alternative modelling approaches such as ESMFold (four cases), alternative MR approaches such as ARCIMBOLDO and AMPLE (two cases each), and multimeric model building with AlphaFold-Multimer or UniFold (three cases). Ultimately, only 12 cases, or 3% of the SAD-phased set, did not yield to any form of MR tested here, offering valuable hints as to the number and the characteristics of cases where experimental phasing remains essential for macromolecular structure solution.

Highly accurate protein structure prediction can generate accurate models of protein and protein–protein complexes in X-ray crystallography. However, the question of how to make more effective use of predicted models for completing structure analysis, and which strategies should be employed for the more challenging cases such as multi-helical structures, multimeric structures and extremely large structures, both in the model preparation and in the completion steps, remains open for discussion. In this paper, a new strategy is proposed based on the framework of direct methods and dual-space iteration, which can greatly simplify the pre-processing steps of predicted models both in normal and in challenging cases. Following this strategy, full-length models or the conservative structural domains could be used directly as the starting model, and the phase error and the model bias between the starting model and the real structure would be modified in the direct-methods-based dual-space iteration. Many challenging cases (from CASP14) have been tested for the general applicability of this constructive strategy, and almost complete models have been generated with reasonable statistics. The hybrid strategy therefore provides a meaningful scheme for X-ray structure determination using a predicted model as the starting point.