Miracle-dz/UniFAR-FTUs huggingface dataset:
99% Efficient 10 kV SiC-Based 7 kV/400 V DC Transformer for Future Data Centers

The power supply chain of data centers from the medium voltage (MV) utility grid down to the chip-level voltage consists of many series connected power conversion stages and accordingly shows a relatively low efficiency. Solid-state transformers (SSTs) could improve the efficiency by substantially reducing the number of power conversion stages and/or directly interfacing the MV ac grid to a 400 V dc bus, from where server racks with a power consumption of several tens of kilowatts could be supplied by individual SSTs. The recent development of SiC MOSFETs with a blocking voltage of 10 kV enables the realization of a simple and, hence, highly reliable two-stage SST topology, consisting of an ac/dc power factor correction rectifier and a subsequent isolated dc/dc converter. In this context, an isolated 25 kW, 48 kHz, 7 kV to 400 V series resonant dc/dc converter based on 10 kV SiC MOSFETs is realized and tested in this paper. To achieve zero voltage switching of all MOSFETs, a special modulation scheme to actively control the amount of the switched magnetizing current on the MV- and low voltage-sides is implemented. Furthermore, the design of all main components and, especially, the electrical insulation of the employed medium-frequency transformer are discussed in detail. Calorimetric efficiency measurements show that a full-load efficiency of 99.0% is achieved, while the power density reaches 3.8 kW/L ( $63~\text {W}/\mathrm {in^{3}}$ ).
Effect of Rice Husk Ash on Cement Stabilized Laterite

Consolidation tests have been prepared at optimum moisture content and maximum dry density by adding 4, 8, 16 and 20% by weight of rice husk ash to the originate soil. Specimens have been subjected to increments of vertical pressure of 0.25, 0.50, 1.00, 2.00 and 4.00 kg/cm2 in a fixed ring consoled meter. [1]Coefficient of compressibility (av) and coefficient of volume compressibility (mv) show no significant quality for variation in values with change in proportion of rice husk ash in the soil at a particular effective stress. It has been observed that there is decrease in the values of these parameters with increase in effective stress for a particular percentage of rice husk ash. Compression index (cc) has been found to decrease significantly with increase in percentage of rice husk ash, hence decreasing consolidation settlement of parent material. It has also been observed that the time required for achieving a given degree of consolidation decreases with increase in the percentage of rice husk ash at a particular effective stress[2]. Overall, it has been observed that rice husk ash effectively increase onedimensional stiffness and therefore, reduce settlement.
Hydrological Modelling Using a Rainfall Simulator over an Experimental Hillslope Plot

Hydrological processes are complex to compute in hilly areas when compared to plain areas. The governing processes behind runoff generation on hillslopes are subsurface storm flow, saturation excess flow, overland flow, return flow and pipe storage. The simulations of the above processes in the soil matrix require detailed hillslope hydrological modelling. In the present study, a hillslope experimental plot has been designed to study the runoff generation processes on the plot scale. The setup is designed keeping in view the natural hillslope conditions prevailing in the Northwestern Himalayas, India where high intensity rainfall events occur frequently. A rainfall simulator was installed over the experimental hillslope plot to generate rainfall with an intensity of 100 mm/h, which represents the dominating rainfall intensity range in the region. Soil moisture sensors were also installed at variable depths from 100 to 1000 mm at different locations of the plot to observe the soil moisture regime. From the experimental observations it was found that once the soil is saturated, it remains at field capacity for the next 24–36 h. Such antecedent moisture conditions are most favorable for the generation of rapid stormflow from hillslopes. A dye infiltration test was performed on the undisturbed soil column to observe the macropore fraction variability over the vegetated hillslopes. The estimated macropore fractions are used as essential input for the hillslope hydrological model. The main objective of the present study was to develop and test a method for estimating runoff responses from natural rainfall over hillslopes of the Northwestern Himalayas using a portable rainfall simulator. Using the experimental data and the developed conceptual model, the overland flow and the subsurface flow through a macropore-dominated area have been estimated/analyzed. The surface and subsurface runoff estimated using the developed hillslope hydrological model compared well with the observed surface runoff for a rainfall intensity of 100 mm/h. The surface runoff hydrograph was very well predicted by the model, with correlation coefficient (R2) and Nash–Sutcliffe efficiency coefficient (E) as 0.95 and 0.91, respectively. The observed soil/macropore storage component was estimated with the help of water balance equation and compared with the model predicted macropore storage. The error in computing the soil/macropore storage was estimated as 0.38 mm i.e., 13%.
Deep Hyperspherical Learning

Convolution as inner product has been the founding basis of convolutional neural networks (CNNs) and the key to end-to-end visual representation learning. Benefiting from deeper architectures, recent CNNs have demonstrated increasingly strong representation abilities. Despite such improvement, the increased depth and larger parameter space have also led to challenges in properly training a network. In light of such challenges, we propose hyperspherical convolution (SphereConv), a novel learning framework that gives angular representations on hyperspheres. We introduce SphereNet, deep hyperspherical convolution networks that are distinct from conventional inner product based convolutional networks. In particular, SphereNet adopts SphereConv as its basic convolution operator and is supervised by generalized angular softmax loss - a natural loss formulation under SphereConv. We show that SphereNet can effectively encode discriminative representation and alleviate training difficulty, leading to easier optimization, faster convergence and comparable (even better) classification accuracy over convolutional counterparts. We also provide some theoretical insights for the advantages of learning on hyperspheres. In addition, we introduce the learnable SphereConv, i.e., a natural improvement over prefixed SphereConv, and SphereNorm, i.e., hyperspherical learning as a normalization method. Experiments have verified our conclusions.
Erratum: Faraday ghosts: depolarization canals in the Galactic radio emission

Narrow, elongated regions of very low polarized intensity ‐ so-called ‘canals’ ‐ have recently been observed by several authors at decimetre wavelengths in various directions in the Milky Way, but their origin remains enigmatic. We show that the canals arise from depolarization by differential Faraday rotation in the interstellar medium and that they represent level lines of Faraday rotation measure RM, a random function of position in the sky. Statistical properties of the separation of canals depend on the autocorrelation function of RM, and so provide a useful tool for studies of interstellar turbulence.
Stochastic resonance on a circle.

We describe a new realization of stochastic resonance, applicable to a broad class of systems, based on an underlying excitable dynamics with deterministic reinjection. A simple but general theory of such single-trigger'' systems is compared with analog simulations of the Fitzhugh-Nagumo model, as well as experimental data obtained from stimulated sensory neurons in the crayfish.
Flocculence of Saccharomyces cerevisiae cells is induced by nutrient limitation, with cell surface hydrophobicity as a major determinant

Initiation of flocculation ability of Saccharomyces cerevisiae MPY1 cells was observed at the moment the cells stop dividing because of nitrogen limitation. A shift in concentration of the limiting nutrient resulted in a corresponding shift in cell division and initiation of flocculence. Other limitations also led to initiation of flocculence, with magnesium limitation as the exception. Magnesium-limited S. cerevisiae cells did not flocculate at any stage of growth. Cell surface hydrophobicity was found to be strongly correlated with the ability of the yeast cells to flocculate. Hydrophobicity sharply increased at the end of the logarithmic growth phase, shortly before initiation of flocculation ability. Treatments of cells which resulted in a decrease in hydrophobicity also yielded a decrease in flocculation ability. Similarly, the presence of polycations increased both hydrophobicity and the ability to flocculate. Magnesium-limited cells were found to be strongly affected in cell surface hydrophobicity. A proteinaceous cell surface factor(s) was identified as a flocculin. This heat-stable component had a strong emulsifying activity, and appears to be involved in both cell surface hydrophobicity and in flocculation ability of the yeast cells.
Measuring Semantic Similarity by Latent Relational Analysis

This paper introduces Latent Relational Analysis (LRA), a method for measuring semantic similarity. LRA measures similarity in the semantic relations between two pairs of words. When two pairs have a high degree of relational similarity, they are analogous. For example, the pair cat:meow is analogous to the pair dog:bark. There is evidence from cognitive science that relational similarity is fundamental to many cognitive and linguistic tasks (e.g., analogical reasoning). In the Vector Space Model (VSM) approach to measuring relational similarity, the similarity between two pairs is calculated by the cosine of the angle between the vectors that represent the two pairs. The elements in the vectors are based on the frequencies of manually constructed patterns in a large corpus. LRA extends the VSM approach in three ways: (1) patterns are derived automatically from the corpus, (2) Singular Value Decomposition is used to smooth the frequency data, and (3) synonyms are used to reformulate word pairs. This paper describes the LRA algorithm and experimentally compares LRA to VSM on two tasks, answering college-level multiple-choice word analogy questions and classifying semantic relations in noun-modifier expressions. LRA achieves state-of-the-art results, reaching human-level performance on the analogy questions and significantly exceeding VSM performance on both tasks.
Stochastic Analysis of Non-Slotted Aloha in Wireless Ad-Hoc Networks

In this paper we propose two analytically tractable stochastic models of non-slotted Aloha for Mobile Ad-hoc NETworks (MANETs): one model assumes a static pattern of nodes while the other assumes that the pattern of nodes varies over time. Both models feature transmitters randomly located in the Euclidean plane, according to a Poisson point process with the receivers randomly located at a fixed distance from the emitters. We concentrate on the so-called outage scenario, where a successful transmission requires a Signal-to-Interference-and-Noise Ratio (SINR) larger than a given threshold. With Rayleigh fading and the SINR averaged over the duration of the packet transmission, both models lead to closed form expressions for the probability of successful transmission. We show an excellent matching of these results with simulations. Using our models we compare the performances of non-slotted Aloha to previously studied slotted Aloha. We observe that when the path loss is not very strong both models, when appropriately optimized, exhibit similar performance. For stronger path loss non-slotted Aloha performs worse than slotted Aloha, however when the path loss exponent is equal to 4 its density of successfully received packets is still 75% of that in the slotted scheme. This is still much more than the 50% predicted by the well-known analysis where simultaneous transmissions are never successful. Moreover, in any path loss scenario, both schemes exhibit the same energy efficiency.
Investigation on the effect of drilling parameters on the tool wear and delamination of glass fibre-reinforced polymer composite using vibration signal analysis

Glass fibre-reinforced polymer composite materials are widely used in industrial, aerospace and automotive sector. It has excellent properties such as high strength to weight ratio, higher fatigue limit, high stiffness to weight ratio, corrosion resistance and design flexibility. The strength of the composite highly depends upon orientation of the fibre material. Drilling is one of the major machining operations that are carried out on Glass fibre-reinforced polymer composite materials to the need for components assembly. There are many problems encountered while drilling glass fibre-reinforced polymer composites. The major problems are excessive tool wear and delamination of the composite during drilling, which reduce the strength of the composite during application. In the present study, the experimental investigations are carried out to analyse the effect of various machining parameters, i.e. cutting speed and feed rate on the tool wear and delamination. The time and frequency domain analysis of vibration signals measured using sound sensor is also used to predict the effect of machining parameters on delamination as well as to develop the tool replacement strategy.
Updates on intra-articular hyaluronic Acid therapy for knee osteoarthritis.

Osteoarthritis (OA) is the most common form of arthritis in the United States. Prevalence in the United States was estimated at 27 million in 2008, an increase from 21 million in 1995. OA results from inflammatory and mechanical factors in susceptible individuals leading to joint pain, stiffness, and loss of range of motion. No therapies have been shown to alter the natural history of OA. In the absence of disease modifying osteoarthritis drugs (ie, DMOADs), treatment of OA is focused on controlling symptoms, especially pain. Non-pharmacologic therapies include weight loss, low-impact exercise, and physical therapy. Medical options include acetaminophen, nonsteroidal anti-inflammatory drugs (NSAIDs), tramadol, and opioids in selected patients. Topical therapies include capsaicin, methylsalicylate, and NSAIDs.
Early galaxy evolution from deep wide field star counts - II. First estimate of the thick disc mass function

Star counts at high and intermediate galactic latitudes, in the visible and the near infrared, are used to determine the density law and the initial mass function of the thick disc population. The combination of shallow elds dominated by stars at the turno with deep elds allows the determination of the thick disc mass function in the mass range 0.2{0.8 M. Star counts are compared with simulations of a synthesis population model. The t is based on a maximum likelihood criterion. The best t model gives a scale height of 800 pc, a scale length of 2500 pc and a local density of 10 3 stars pc 3 or 7:1 10 4 M pc 3 for Mv 8. The IMF is found to follow a power law dN/dm/ m 0:5 . This is the rst determination of the thick disc mass function.
High contrast near‐infrared polarized reflectance images of demineralization on tooth buccal and occlusal surfaces at λ = 1310‐nm

Sound enamel manifests peak transparency in the near‐IR (NIR) at 1310‐nm, therefore the near‐IR is ideally suited for high contrast imaging of dental caries. The purpose of this study was to acquire images of early demineralized enamel on the buccal and occlusal surfaces of extracted human teeth using NIR reflectance imaging and compare the contrast of those images with the contrast of images taken using other methods.
Evaluating change in mobility in people with multiple sclerosis: relative responsiveness of four clinical measures

Background and objectives: Determining responsiveness of measures across different samples and settings is important for selecting measures of mobility and understanding multiple sclerosis (MS) study results. Currently such information is limited. Methods: This exploratory study examined the relative responsiveness of four mobility measures (walking velocity, 6-minute walk distance, Rivermead Mobility Index and MS Walking Scale) in a community sample (n = 70), after three annual assessments. Distribution based estimates and anchor-based methods (comparison against transition questions) determined responsiveness. A head-to-head comparison was made. Results: While variations in individuals occurred, the group mean change scores for all measures was small, suggesting that there was minimal deterioration in the total sample. Consistent with this, total sample Effect Size (ES) was negligible to small (ES −0.32 to +0.03) for all measures. Differentiation between sub-groups, defined by the participants’ perception of change in mobility over the past year (transition questions), showed that some instruments could detect clinically significant changes (small sample sizes limited this interpretation). Correlation analyses between change scores demonstrated that these measures captured related, but different information (r < 0.364). Conclusions: The measures were broadly comparable in detecting mobility changes in this community sample. These correlations highlight that in selection of measures, one should also consider the discrete mobility dimension that the intervention intends to impact.
Analogies, Adaptation, and Anomalies

Abstract This paper studies decision makers characterized by a stock of models, or analogies, who respond to strategic interactions by applying what appear to be the most suitable models; balancing the gains from more sophisticated decisionmaking against the cost of placing heavier demands on scarce reasoning resources. Equilibrium models will be finely tuned to interactions, leading to seemingly “rational” behavior, when the interactions are sufficiently important and sufficiently distinct that a more generic model entails a prohibitive payoff reduction. Interactions that are infrequently encountered, relatively unimportant, or similar to other interactions may trigger seemingly inappropriate analogies, leading to behavioral anomalies. Journal of Economic Literature Classification Numbers: C70, C72.
A Reinforcement Learning Approach to Online Clustering

A general technique is proposed for embedding online clustering algorithms based on competitive learning in a reinforcement learning framework. The basic idea is that the clustering system can be viewed as a reinforcement learning system that learns through reinforcements to follow the clustering strategy we wish to implement. In this sense, the reinforcement guided competitive learning (RGCL) algorithm is proposed that constitutes a reinforcement-based adaptation of learning vector quantization (LVQ) with enhanced clustering capabilities. In addition, we suggest extensions of RGCL and LVQ that are characterized by the property of sustained exploration and significantly improve the performance of those algorithms, as indicated by experimental tests on well-known data sets.
The importance of assessing body composition of dogs and cats and methods available for use in clinical practice.

521 Both the World Small Animal Veterinary Association1 and American Animal Hospital Association2 have developed nutritional assessment guidelines to aid veterinary health-care teams in determining the nutritional needs of companion animals. Body composition is the sum of various biological components, which include fat, bone, and lean tissue.3–5 Lean tissue encompasses water, muscle tissue, nervous tissue, organs, tendons, and ligaments.6 Accurate measurement of body composition can be challenging because body components are not compartmentalized; instead, they are mixed in various tissues in the body.6 However, body composition assessments are crucial for preventing excess storage of BF and loss of lean BM in pets of all ages.
Optimization of fermentation conditions for green pigment production from Bacillus cereus M116 (MTCC 5521) and its pharmacological application

Optimal culture conditions for the production of green pigment was investigated. The optimal culture condition for the production of an extracellular green pigment by growing Bacillus cereus M116 (MTCC 5521) in a complex medium containing (g l−1) Peptone‐4·0, Beef Extract‐9·0, NaCl‐7·0, MgSO4·7H2O‐1·0 and KH2PO4‐5·0 was as follows pH‐7·0 at 30°C for 72 h in a 5 l fermenter. Aeration rate and agitator speed had no effect on the pigment production. Thin layer chromatogram of the pigment extracted from the fermented broth with chloroform on silica gel GF254 using ethyl acetate and hexane (1 : 1) as solvent showed three fractions. The major fraction (C3) was separated out and identified as 9‐methyl‐1, 4, 5, 8‐tetra‐azaphenanthrene. Acute toxicity test revealed the nontoxic nature upto a dose of 2000 mg kg−1, b.wt. , of mice. MTT assay showed the cytotoxic nature in HL60 cells having an IC50 of 2·47 mmol. So, this biopigment may have application in food, textile colorant and pharmaceutical industry.
Display gamut comparison with number of discernible colors

The quantitative description of the size of a display gamut is crucial for designing the wide-gamut display of high saturation primaries. A method to count the discernible colors in a display gamut with the color-difference formula CIE94 is shown. The color difference between neighboring discernible colors in a display gamut is assumed to be unit ΔE 94 (ΔE 94 =1). The counting result shows that there are 199,491 discernible colors for the ITU-R BT.709 standard display. The number of discernible colors of two wide-gamut LED displays is compared with the standard display, which is more meaningful for representing their relative gamut sizes. For the considered three- and four-primary LED displays, their gamut volumes in CIELAB color space are respectively 1.76 and 1.98 times larger than the standard display. It is found that the number of discernible colors of the two LED displays is only 1.38 and 1.49 times larger than the standard display. The impact of flare on the reduction of the number of discernible colors and gamut volume is shown. The number of discernible colors and gamut volume is respectively reduced by 30%, with about 3.3 and 2.5% flare levels for the three displays considered in this work.
CrbpI Modulates Glucose Homeostasis and Pancreas 9-cis-Retinoic Acid Concentrations

ABSTRACT Cellular retinol-binding protein type I (CrbpI), encoded by Rpb1, serves as a chaperone of retinol homeostasis, but its physiological effects remain incompletely understood. We show here that the Rbp1−/− mouse has disrupted retinoid homeostasis in multiple tissues, with abnormally high 9-cis-retinoic acid (9cRA), a pancreas autacoid that attenuates glucose-stimulated insulin secretion. The Rbp1−/− pancreas has increased retinol and intense ectopic expression of Rpb2 mRNA, which encodes CrbpII: both would contribute to increased β-cell 9cRA biosynthesis. 9cRA in Rbp1−/− pancreas resists postprandial and glucose-induced decreases. Rbp1−/− mice have defective islet expression of genes involved in glucose sensing and insulin secretion, as well as islet α-cell infiltration, which contribute to reduced glucose-stimulated insulin secretion, high glucagon secretion, an abnormally high rate of gluconeogenesis, and hyperglycemia. A diet rich in vitamin A (as in a standard chow diet) increases pancreas 9cRA and impairs glucose tolerance. Crbp1 attenuates the negative impact of vitamin A (retinol) on glucose tolerance, regardless of the dietary retinol content. Rbp1−/− mice have an increased rate of fatty acid oxidation and resist obesity when fed a high-fat diet. Thus, glucose homeostasis and energy metabolism rely on Rbp1 expression and its moderation of pancreas retinol and of the autacoid 9cRA.