Multisite is a powerful tool that will help you create a network of sites to fulfill a variety of purposes, and which you can customize to make life easier for your users and help your network run more efficiently and make you money.

Today Matt Mullenweg from MA.TT declared today official plugin developer day because the plugin directory hit 4,000 plugins, check it out: 4,000 Plugins.  

The post January 28th declared plugin developer day appeared first on WPCult.

Nearly 25,000 more Iowans filed unemployment claims in the past week, Iowa Workforce Development reported Thursday.

Continuing weekly unemployment claims total 181,358, the department reported.

Iowa Workforce Development said 24,693 people filed unemployment claims between April 26 and May 2. That included 22,830 initial claims by people who work in Iowa and 1,863 claims filed by people who work in Iowa but live in another state.

State unemployment insurance benefit payments totaled $50,931,302 for the same week, the department said.

Also this week, a total of $111,378,600 in Federal Pandemic Unemployment Compensation benefits was paid to 164,088 Iowans. Since April 4, a total of $439,126,200 has been paid.

A total of $10,046,089 was paid to 15,612 Iowans receiving Pandemic Unemployment Assistance benefits.

The industries with the most claims were manufacturing, 6,053; industry not available, self-employed, independent contractors, 4,010; health care and social assistance, 2,988; accommodation and food services, 2,200; and retail trade, 1,768.

Gov. Kim Reynolds is continuing to allow more businesses to reopen, which may mean more Iowans going back to work.

On Wednesday, after meeting with President Donald Trump at the White House, Reynolds issued a proclamation permitting a variety of businesses to reopen, including dental services, drive-in movie theaters, tanning facilities and medical spas.

She also relaxed mitigation strategies in the 22 counties that remain under more strict orders because the virus is more widespread there.

Beginning Friday in those 22 counties — which include Linn, Johnson and Black Hawk — malls and retail stores may reopen provided they operate at no more than 50 percent of capacity, and fitness centers may reopen on an appointment basis only.

For more information on the total data for this week’s unemployment claims, visit https://www.iowalmi.gov/unemployment-insurance-statistics.

Comments: (319) 398-8375; james.lynch@thegazette.com

Today, the Game of Thrones star announced that 12 random people will get to win a virtual dinner with her. She’s asking people to donate money to her charity SameYou, which helps people heal from brain injuries and strokes. Pledges will be used to assist brain injury survivors in recuperating at home, who have been asked to leave hospitals to make room for coronavirus patients.

By Jake Johnson Common Dreams And colleague says “global warming” no longer strong enough term. “Global heating is technically more correct because we are talking about changes in the energy balance of the planet.” Declaring that after three decades of … Continue reading →

By Jake Johnson Common Dreams And colleague says “global warming” no longer strong enough term. “Global heating is technically more correct because we are talking about changes in the energy balance of the planet.” Declaring that after three decades of … Continue reading →

During an interview on "Fox and Friends," Trump explained why he chose not to go on a firing spree amid Special Counsel Robert Mueller's Russia investigation a la Nixon's Saturday Night Massacre during the Watergate scandal. "I learned a lot from Richard Nixon: Don't fire people," the President said. "I learned a lot. I study history, and the firing of everybody ... .I should've, in one way," he continued. "But I'm glad I didn't because look at the way it turned out."

In this paper, we mainly establish the existence and uniqueness theorem for solutions of the exterior Dirichlet problem for a class of fully nonlinear second-order elliptic equations related to the eigenvalues of the Hessian, with prescribed generalized symmetric asymptotic behavior at infinity. Moreover, we give some new results for the Hessian equations, Hessian quotient equations and the special Lagrangian equations, which have been studied previously.

In this article, we prove that the completeness of the Hamilton flow and essential self-dajointness are equivalent for real principal type operators on the circle. Moreover, we study spectral properties of these operators.

Let $k ,=, mathbb{Q}(sqrt[5]{n},zeta_5)$, where $n$ is a positive integer, $5^{th}$ power-free, whose $5-$class group is isomorphic to $mathbb{Z}/5mathbb{Z} imesmathbb{Z}/5mathbb{Z}$. Let $k_0,=,mathbb{Q}(zeta_5)$ be the cyclotomic field containing a primitive $5^{th}$ root of unity $zeta_5$. Let $C_{k,5}^{(sigma)}$ the group of the ambiguous classes under the action of $Gal(k/k_0)$ = $<sigma>$. The aim of this paper is to determine all integers $n$ such that the group of ambiguous classes $C_{k,5}^{(sigma)}$ has rank $1$ or $2$.

We study flows on C*-algebras with the Rokhlin property. We show that every Kirchberg algebra carries a unique Rokhlin flow up to cocycle conjugacy, which confirms a long-standing conjecture of Kishimoto. We moreover present a classification theory for Rokhlin flows on C*-algebras satisfying certain technical properties, which hold for many C*-algebras covered by the Elliott program. As a consequence, we obtain the following further classification theorems for Rokhlin flows. Firstly, we extend the statement of Kishimoto's conjecture to the non-simple case: Up to cocycle conjugacy, a Rokhlin flow on a separable, nuclear, strongly purely infinite C*-algebra is uniquely determined by its induced action on the prime ideal space. Secondly, we give a complete classification of Rokhlin flows on simple classifiable $KK$-contractible C*-algebras: Two Rokhlin flows on such a C*-algebra are cocycle conjugate if and only if their induced actions on the cone of lower-semicontinuous traces are affinely conjugate.

We study a class of fourth order nonlinear parabolic equations which include the thin-film equation and the quantum drift-diffusion model as special cases. We investigate these equations by first developing functional inequalities of the type $ int_Omega u^{2gamma-alpha-eta}Delta u^alphaDelta u^eta dx geq cint_Omega|Delta u^gamma |^2dx $, which seem to be of interest on their own right.

In the spirit of very recent articles by J. Bonet, W. Lusky and J. Taskinen we are studying the so-called solid hulls and cores of spaces of weighted entire functions when the weights are given in terms of associated weight functions coming from weight sequences. These sequences are required to satisfy certain (standard) growth and regularity properties which are frequently arising and used in the theory of ultradifferentiable and ultraholomorphic function classes (where also the associated weight function plays a prominent role). Thanks to this additional information we are able to see which growth behavior the so-called "Lusky-numbers", arising in the representations of the solid hulls and cores, have to satisfy resp. if such numbers can exist.

Let $H$ be an infinite dimensional, reflexive, separable Hilbert space and $NA(H)$ the class of all norm-attainble operators on $H.$ In this note, we study an implicit scheme for a canonical representation of nonexpansive contractions in norm-attainable classes.

We introduce natural deformation classes of generalized K"ahler structures using the Courant symmetry group. We show that these yield natural extensions of the notions of K"ahler class and K"ahler cone to generalized K"ahler geometry. Lastly we show that the generalized K"ahler-Ricci flow preserves this generalized K"ahler cone, and the underlying real Poisson tensor.

A standard approach to evaluating language models analyzes how models assign probabilities to valid versus invalid syntactic constructions (i.e. is a grammatical sentence more probable than an ungrammatical sentence). Our work uses ambiguous relative clause attachment to extend such evaluations to cases of multiple simultaneous valid interpretations, where stark grammaticality differences are absent. We compare model performance in English and Spanish to show that non-linguistic biases in RNN LMs advantageously overlap with syntactic structure in English but not Spanish. Thus, English models may appear to acquire human-like syntactic preferences, while models trained on Spanish fail to acquire comparable human-like preferences. We conclude by relating these results to broader concerns about the relationship between comprehension (i.e. typical language model use cases) and production (which generates the training data for language models), suggesting that necessary linguistic biases are not present in the training signal at all.

A recently introduced classifier, called SS3, has shown to be well suited to deal with early risk detection (ERD) problems on text streams. It obtained state-of-the-art performance on early depression and anorexia detection on Reddit in the CLEF's eRisk open tasks. SS3 was created to deal with ERD problems naturally since: it supports incremental training and classification over text streams, and it can visually explain its rationale. However, SS3 processes the input using a bag-of-word model lacking the ability to recognize important word sequences. This aspect could negatively affect the classification performance and also reduces the descriptiveness of visual explanations. In the standard document classification field, it is very common to use word n-grams to try to overcome some of these limitations. Unfortunately, when working with text streams, using n-grams is not trivial since the system must learn and recognize which n-grams are important "on the fly". This paper introduces t-SS3, an extension of SS3 that allows it to recognize useful patterns over text streams dynamically. We evaluated our model in the eRisk 2017 and 2018 tasks on early depression and anorexia detection. Experimental results suggest that t-SS3 is able to improve both current results and the richness of visual explanations.

Traffic signs are essential map features globally in the era of autonomous driving and smart cities. To develop accurate and robust algorithms for traffic sign detection and classification, a large-scale and diverse benchmark dataset is required. In this paper, we introduce a traffic sign benchmark dataset of 100K street-level images around the world that encapsulates diverse scenes, wide coverage of geographical locations, and varying weather and lighting conditions and covers more than 300 manually annotated traffic sign classes. The dataset includes 52K images that are fully annotated and 48K images that are partially annotated. This is the largest and the most diverse traffic sign dataset consisting of images from all over world with fine-grained annotations of traffic sign classes. We have run extensive experiments to establish strong baselines for both the detection and the classification tasks. In addition, we have verified that the diversity of this dataset enables effective transfer learning for existing large-scale benchmark datasets on traffic sign detection and classification. The dataset is freely available for academic research: https://www.mapillary.com/dataset/trafficsign.

We present results showing the capability of concrete-based information processing substrate in the signal classification task in accordance with in materio computing paradigm. As the Reservoir Computing is a suitable model for describing embedded in materio computation, we propose that this type of presented basic construction unit can be used as a source for "reservoir of states" necessary for simple tuning of the readout layer. In that perspective, buildings constructed from computing concrete could function as a highly parallel information processor for smart architecture. We present an electrical characterization of the set of samples with different additive concentrations followed by a dynamical analysis of selected specimens showing fingerprints of memfractive properties. Moreover, on the basis of obtained parameters, classification of the signal waveform shapes can be performed in scenarios explicitly tuned for a given device terminal.

Convolutional Neural Networks (CNNs) are generally prone to noise interruptions, i.e., small image noise can cause drastic changes in the output. To suppress the noise effect to the final predication, we enhance CNNs by replacing max-pooling, strided-convolution, and average-pooling with Discrete Wavelet Transform (DWT). We present general DWT and Inverse DWT (IDWT) layers applicable to various wavelets like Haar, Daubechies, and Cohen, etc., and design wavelet integrated CNNs (WaveCNets) using these layers for image classification. In WaveCNets, feature maps are decomposed into the low-frequency and high-frequency components during the down-sampling. The low-frequency component stores main information including the basic object structures, which is transmitted into the subsequent layers to extract robust high-level features. The high-frequency components, containing most of the data noise, are dropped during inference to improve the noise-robustness of the WaveCNets. Our experimental results on ImageNet and ImageNet-C (the noisy version of ImageNet) show that WaveCNets, the wavelet integrated versions of VGG, ResNets, and DenseNet, achieve higher accuracy and better noise-robustness than their vanilla versions.

Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed-aided diagnosis technique for COVID-19 classification based on CT images could largely alleviate the burden of clinicians. In this paper, we propose an Adaptive Feature Selection guided Deep Forest (AFS-DF) for COVID-19 classification based on chest CT images. Specifically, we first extract location-specific features from CT images. Then, in order to capture the high-level representation of these features with the relatively small-scale data, we leverage a deep forest model to learn high-level representation of the features. Moreover, we propose a feature selection method based on the trained deep forest model to reduce the redundancy of features, where the feature selection could be adaptively incorporated with the COVID-19 classification model. We evaluated our proposed AFS-DF on COVID-19 dataset with 1495 patients of COVID-19 and 1027 patients of community acquired pneumonia (CAP). The accuracy (ACC), sensitivity (SEN), specificity (SPE) and AUC achieved by our method are 91.79%, 93.05%, 89.95% and 96.35%, respectively. Experimental results on the COVID-19 dataset suggest that the proposed AFS-DF achieves superior performance in COVID-19 vs. CAP classification, compared with 4 widely used machine learning methods.

Water quality has a direct impact on industry, agriculture, and public health. Algae species are common indicators of water quality. It is because algal communities are sensitive to changes in their habitats, giving valuable knowledge on variations in water quality. However, water quality analysis requires professional inspection of algal detection and classification under microscopes, which is very time-consuming and tedious. In this paper, we propose a novel multi-target deep learning framework for algal detection and classification. Extensive experiments were carried out on a large-scale colored microscopic algal dataset. Experimental results demonstrate that the proposed method leads to the promising performance on algal detection, class identification and genus identification.

We establish versions of Conley's (i) fundamental theorem and (ii) decomposition theorem for a broad class of hybrid dynamical systems. The hybrid version of (i) asserts that a globally-defined "hybrid complete Lyapunov function" exists for every hybrid system in this class. Motivated by mechanics and control settings where physical or engineered events cause abrupt changes in a system's governing dynamics, our results apply to a large class of Lagrangian hybrid systems (with impacts) studied extensively in the robotics literature. Viewed formally, these results generalize those of Conley and Franks for continuous-time and discrete-time dynamical systems, respectively, on metric spaces. However, we furnish specific examples illustrating how our statement of sufficient conditions represents merely an early step in the longer project of establishing what formal assumptions can and cannot endow hybrid systems models with the topologically well characterized partitions of limit behavior that make Conley's theory so valuable in those classical settings.

The increasing ubiquity of low-cost wireless sensors in smart homes and buildings has enabled users to easily deploy systems to remotely monitor and control their environments. However, this raises privacy concerns for third-party occupants, such as a hotel room guest who may be unaware of deployed clandestine sensors. Previous methods focused on specific modalities such as detecting cameras but do not provide a generalizable and comprehensive method to capture arbitrary sensors which may be "spying" on a user. In this work, we seek to determine whether one can walk in a room and detect any wireless sensor monitoring an individual. As such, we propose SnoopDog, a framework to not only detect wireless sensors that are actively monitoring a user, but also classify and localize each device. SnoopDog works by establishing causality between patterns in observable wireless traffic and a trusted sensor in the same space, e.g., an inertial measurement unit (IMU) that captures a user's movement. Once causality is established, SnoopDog performs packet inspection to inform the user about the monitoring device. Finally, SnoopDog localizes the clandestine device in a 2D plane using a novel trial-based localization technique. We evaluated SnoopDog across several devices and various modalities and were able to detect causality 96.6% percent of the time, classify suspicious devices with 100% accuracy, and localize devices to a sufficiently reduced sub-space.

What am I supposed to say here?…

You might not know it from the fancy attire they wear on stage at the Fox Theater, but for the musicians in the Spokane Symphony, it's a part-time gig. It's a prestigious gig, to be sure, but like most artists, for the musicians, it's just one piece of a puzzle full of hustle they have to solve to make a living.…

Here are a few ways to keep yourself entertained, and maybe even educate yourself a bit, while you're stuck at home:…

Techniques for evaluation and/or retraining of a classification model built using labeled training data. In some aspects, a classification model having a first set of weights is retrained by using unlabeled input to reweight the labeled training data to have a second set of weights, and by retraining the classification model using the labeled training data weighted according to the second set of weights. In some aspects, a classification model is evaluated by building a similarity model that represents similarities between unlabeled input and the labeled training data and using the similarity model to evaluate the labeled training data to identify a subset of the plurality of items of labeled training data that is more similar to the unlabeled input than a remainder of the labeled training data.

A system and method for classifying unclassified samples. The method includes detecting a number of classes including training samples in training data sets. The method includes, for each class, determining a vector for each training sample based on a specified number of nearest neighbor distances between the training sample and neighbor training samples, and determining a class distribution based on the vectors. The method also includes detecting an unclassified sample in a data set and, for each class, determining a vector for the unclassified sample based on the specified number of nearest neighbor distances between the unclassified sample and nearest neighbor training samples within the class, and determining a probability that the unclassified sample is a member of the class based on the vector and the class distribution. The method further includes classifying the unclassified sample based on the probabilities.

A system and method for providing more than two levels of classification distinction of a user state are provided. The first and second general states of a user are sensed. The first general state is classified as either a first state or a second state, and the second general state is classified as either a third state or a fourth state. The user state of the user is then classified as one of at least three different classification states.

A computer-implemented method for classifying documents for data loss prevention may include 1) identifying training documents for a machine learning classifier configured for data loss prevention, 2) performing a semantic analysis on training documents to identify topics within the set training documents, 3) applying a similarity metric to the topics to identify at least one unrelated topic with a similarity to the other topics within the plurality of topics, as determined by the similarity metric, that falls below a similarity threshold, 4) identifying, based on the semantic analysis, at least one irrelevant training document within the set of training documents in which a predominance of the unrelated topic is above a predominance threshold, and 5) excluding the irrelevant training document from the set of training documents based on the predominance of the unrelated topic within the irrelevant training document. Various other methods, systems, and computer-readable media are also disclosed.

A computer implemented method for automatic chemical assay classification, the method comprising steps the computer is programmed to perform, the steps comprising: receiving a plurality of sets of parameters, each one of the received sets of parameters characterizing a respective assay of a chemical reaction, calculating a space enhancing proximity among points representative of assays of qualitatively identical chemical reactions, and representing each one of at least two of the received sets of parameters as a respective point in the calculated space, and dividing the points in the calculated space into a number of groups, according to proximity among the points in the calculated space, each group pertaining to a respective chemical reaction, thereby classifying the assays.

A data warehouse is constructed using the relational mapping of a transactional database without reconstructing the data relationships of the transactional database. First, an application programmer analyzes an object model in order to describe facts and dimensions using the objects, attributes, and paths of the object model. Each of the dimensions has an identifier that correlates an item in the transactional database to a dimension record in the data warehouse. The fact and dimension descriptions are saved to a description file. Second, a Data Warehouse Engine (DWE) then access the description file and uses the object model, fact and dimension descriptions, and object-relational mapping to map transactional data to the data warehouse.

The present invention provides a method for performing regeneration of a decolorization capacity of waste clay that has been used for purification of fats and oils, and production of a thermally recyclable compound as a biofuel from oily ingredients in the waste clay at the same time in a convenient manner. That is, a method for producing purified fats and oils of the invention includes: a method for producing regenerated clay including the steps of mixing waste clay that has been used for purification of fats and oils, lower alcohol, and an acidic catalyst; and performing extraction of oily ingredients from the waste clay, and an esterification reaction between the fats and oils and/or a free fatty acid in the oily ingredients and the lower alcohol at the same time so as to regenerate a decolorization capacity of the waste clay; regenerated clay that is produced by the method for producing the regenerated clay; and a process of decolorizing the fats and oils using the regenerated clay.

Disclosed is a method for removing weakly basic nitrogen compounds from a hydrocarbon feed stream by contacting the hydrocarbon feed stream with acidic clay to produce a hydrocarbon effluent stream having a lower weakly basic nitrogen compound content relative to the hydrocarbon feed stream. The hydrocarbon feed stream comprises an aromatic compound and a weakly basic nitrogen compound.

Low bit rate audio coding such as BWE algorithm often encounters conflict goal of achieving high time resolution and high frequency resolution at the same time. In order to achieve best possible quality, input signal can be first classified into fast signal and slow signal. This invention focuses on classifying signal into fast signal and slow signal, based on at least one of the following parameters or a combination of the following parameters: spectral sharpness, temporal sharpness, pitch correlation (pitch gain), and/or spectral envelope variation. This classification information can help to choose different BWE algorithms, different coding algorithms, and different postprocessing algorithms respectively for fast signal and slow signal.

A sequence of storage devices of a data store may include one or more stripesets for storing data stripes of different lengths and of different types. Each data stripe may be stored in a prefix or other portion of a stripeset. Each data stripe may be identified by an array of addresses that identify each page of the data stripe on each included storage device. When a first storage device of a stripeset becomes full, the stripeset may be shifted by removing the full storage device from the stripeset, and adding a next storage device of the data store to the stripeset. A class variable may be associated with storage devices of a stripeset to identify the type of data that the stripeset can store. The class variable may be increased (or otherwise modified) when a computer stores data of a different class in the stripeset.

An abstraction for storage class memory is provided that hides the details of the implementation of storage class memory from a program, and provides a standard channel programming interface for performing certain actions, such as controlling movement of data between main storage and storage class memory or managing storage class memory.

An SOC implements a security enclave processor (SEP). The SEP may include a processor and one or more security peripherals. The SEP may be isolated from the rest of the SOC (e.g. one or more central processing units (CPUs) in the SOC, or application processors (APs) in the SOC). Access to the SEP may be strictly controlled by hardware. For example, a mechanism in which the CPUs/APs can only access a mailbox location in the SEP is described. The CPU/AP may write a message to the mailbox, which the SEP may read and respond to. The SEP may include one or more of the following in some embodiments: secure key management using wrapping keys, SEP control of boot and/or power management, and separate trust zones in memory.

The burr hole plug comprises a plug base configured for being mounted around a burr hole, and having an aperture through which an elongated medical device exiting the burr hole may pass. The burr hole plug further comprises a retainer configured for being mounted within the plug base aperture. The retainer includes a retainer support, a slot formed in the retainer support for receiving the medical device, and a clamping mechanism having a clamping bar and a flange slidably engaged with the retainer support to laterally slide the clamping bar to secure the medical device. A method comprises introducing the medical device through the burr hole, mounting the plug base around the burr hole, mounting the retainer within the plug base aperture, receiving the medical device into the slot, and sliding the slidable flange relative to the retainer support to laterally slide to secure the medical device.

For use with a percussion instrument, the combination comprises a clamp base to support the percussion instrument, a clamp jaw, adjustable connector structure connecting the jaw to the base for displacing the jaw toward and away from the base, and clamping structure carried on at least one of the jaw and the base to be clamped against a support member in response to relative clamping displacement of the jaw and base, whereby adjustment of the structure accommodates to clamping of different size support members by clamping structure.

A clay mixing apparatus includes a mixing chamber, a rotor arranged within the mixing chamber, a drive unit arranged to rotate the rotor, an ejecting unit, a pressure reducing unit; and an exhaust flow path. The rotor includes a shaft rotated by the drive unit, an extruding member and a mixing member. The mixing member includes a plurality of arms and a plurality of blades arranged at tip ends of the arms. The exhaust opening is opposed, in a radial direction about the center axis, to a portion of the mixing member lying near the extruding member and/or a portion of the extruding member lying near the mixing member.

A combination component handling and connecting device connectable to a multi-axis robot for use in moving and connecting components and subassemblies includes a housing and an actuator fixedly connected to the housing. The actuator includes an actuating link movable from a first position to a second position. Connected to the actuating link is an end effector for concurrent movement with the actuating link. The component handling and connecting device includes a clamp having a first jaw and a second jaw. The second jaw is connected to the actuating link for selectively moving the second jaw toward the first jaw operative to engage a component.

In a cutting tool for chip removing machining a holder for a cutter has a body received therein and movable with surfaces to bear against the cutter for defining the position of the cutter in the direction of an intended axis of rotation of the holder as well as a screw which may be screwed in a threaded bore in the holder. Spring members are arranged to act between the holder and the body for biasing the body against said screw portions.

The invention relates to an indexable insert (1) for fitting in supporting tools (5) for the machining of workpieces, with an upper side (2) and an underside (3), on which clamping recesses are arranged, and with a circumferential geometry (4) joining the upper side (2) and the underside (3), wherein cutting corners and cutting edges (6) are arranged at the transition from the upper side (2) and the underside (3) to the circumferential geometry (4). In order that the clamping situation during machining is improved significantly, and at the same time the introduction of the clamping recesses is made easier, it is proposed that the clamping recess consists of grooves (10) which are arranged on two crossing straight lines (11), wherein the two straight lines (11) run at right angles in relation to each other and all the grooves (10) are arranged at the same distance from the center axis or longitudinal axis (12) of the indexable insert (1), and the crossing point (13) of the two straight lines (11) lies on the center axis or longitudinal axis (12) of the indexable insert (1).

A cutting insert (14) is formed with an insert aperture (32) opening out to insert top and bottom surfaces (14A, 14B) of the cutting insert (14). In a plan view of the insert top surface (14A), the cutting insert (14) and the insert aperture (32) both have oblong shapes which are elongated along a common insert longitudinal axis (AIL). The aperture (32) includes first and second side surfaces (32A1, 32A2) which each extend along the insert longitudinal axis (AIL), and aperture first and second end surfaces (32B1, 32B2) which each extend transverse relative to the insert longitudinal axis (AIL). At least one of the aperture first and second end surfaces (32B1, 32B2) is formed with a clamping lip (32C1, 32C2).

The present invention relates to a ventilator autoclave comprising a chamber (1) with a space (5) for receiving goods (18) to be sterilized, at least one fan arrangement (2) for circulating steam and/or air in said chamber, and at least one first heat exchanger arrangement (11) for cooling and/or heating said steam and/or air, wherein said fan arrangement is arranged and configured to circulate said steam and/or air in said chamber (1), wherein said chamber (1) is configured such that said steam and/or air that is circulated in said chamber (1) follows a flow path passing at least a part of said first heat exchanger arrangement (11) before reaching said goods (18) to be sterilized, wherein said autoclave further comprises at least one second heat exchanger arrangement (19) that is provided upstream of said first heat exchanger arrangement (11) in said flow path, and wherein said second heat exchanger arrangement (19) is provided at such a distance from the periphery of said fan arrangement (2) that said flow of steam and/or air being circulated by said fan arrangement has a tangential velocity component, as seen in relation to the fan arrangement, when it passes said second heat exchanger arrangement (19).

Within machine vision, object movement is often estimated by applying image evaluation techniques to visible light images, utilizing techniques such as perspective and parallax. However, the precision of such techniques may be limited due to visual distortions in the images, such as glare and shadows. Instead, lidar data may be available (e.g., for object avoidance in automated navigation), and may serve as a high-precision data source for such determinations. Respective lidar points of a lidar point cloud may be mapped to voxels of a three-dimensional voxel space, and voxel clusters may be identified as objects. The movement of the lidar points may be classified over time, and the respective objects may be classified as moving or stationary based on the classification of the lidar points associated with the object. This classification may yield precise results, because voxels in three-dimensional voxel space present clearly differentiable statuses when evaluated over time.

A recyclable ring binder apparatus comprises a ring metal incorporating a set of binder rings that are formed of a pair of ring halves. The ring metal can be firmly fastened to a spine section of a binder hardcover by utilizing a post and a small arched snap clamp with a tap. The tap of the snap clamp can be pressed around a neck of the post utilizing a quick release clipping mechanism. The snap clamp can be accessed with an index finger and slid away from the post to remove the ring metal from the hardcover. The ring metal, the hardcover, the snap clamp and the post can be quickly separated into their perspective categories due to the clipping mechanism. Hence, it retains conformance of all components of the ring binder apparatus for recycling without increasing development and production cost.

Activities, actions and events during user performance of physical activity may be detected using various algorithms and templates. Templates may include an arrangement of one or more states that may identify particular event types and timing between events. Templates may be specific to a particular type of activity (e.g., types of sports, drills, events, etc.), user, terrain, time of day and the like.