Miracle-dz/UniFAR-FTUs huggingface dataset:
Receive Spatial Modulation for LOS mmWave Communications Based on TX Beamforming

Receive spatial modulation (RSM) is a recently introduced multi-antenna transmission scheme that is capable of achieving high spectral efficiency at low hardware and processing complexity. We study RSM for application in indoor line-of-sight (LOS) millimeter-wave (mmWave) communication. Significantly different from low-gigahertz indoor channels, which are typically modeled by a Rician distribution, indoor mmWave channels are sparsely-scattered and dominated by LOS propagation. Hence, we consider the specific characteristics of the LOS mmWave channel and identify the channel conditions that minimize the symbol error probability (SEP) of RSM. We prove that the SEP of RSM in a LOS channel is minimized by imposing orthogonality conditions to the channel matrix. In addition, we propose a simple hardware architecture for the transmitter (TX), which uses only RF phase shifters for precoding. Simulation results show that RSM can successfully operate in indoor mmWave channels.
Spatial and halophyte-associated microbial communities in intertidal coastal region of India

ABSTRACT Microbial communities in intertidal coastal soils respond to a variety of environmental factors related to resources availability, habitat characteristics, and vegetation. These intertidal soils of India are dominated with Salicornia brachiata, Aeluropus lagopoides, and Suaeda maritima halophytes, which play a significant role in carbon sequestration, nutrient cycling, and improving microenvironment. However, the relative contribution of edaphic factors, halophytes, rhizosphere, and bulk sediments on microbial community composition is poorly understood in the intertidal sediments. Here, we sampled rhizosphere and bulk sediments of three dominant halophytes (Salicornia, Aeluropus, and Suaeda) from five geographical locations of intertidal region of Gujarat, India. Sediment microbial community structure was characterized using phospholipid fatty acid (PLFA) profiling. Microbial biomass was significantly influenced by the pH, electrical conductivity, organic carbon, nitrogen, and sodium and potassium concentrations. Multivariate analysis of PLFA profiles had significantly separated the sediment microbial community composition of regional sampling sites, halophytes, rhizosphere, and bulk sediments. Sediments from Suaeda plants were characterized by higher abundance of PLFA biomarkers of Gram-negative, total bacteria, and actinomycetes than other halophytes. Significantly highest abundance of Gram-positive and fungal PLFAs was observed in sediments of Aeluropus and Salicornia, respectively than in those of Suaeda. The rhizospheric sediment had significantly higher abundance of Gram-negative and fungal PLFAs biomarkers compared to bulk sediment. The results of the present study contribute to our understanding of the relative importance of different edaphic and spatial factors and halophyte vegetation on sediment microbial community of intertidal sediments of coastal ecosystem.
A Multimode Wideband ± 45$ ^{\circ}$ Dual-Polarized Antenna With Embedded Loops

A wideband dual-polarized antenna is proposed for base station applications. Compared to the conventional crossed loop dipole antennas, additional loops are embedded into original loops to generate a new resonant mode. Therefore, a multimode antenna with an enhanced impedance bandwidth is completed. A prototype of the proposed antenna is designed, fabricated, and tested. The measured impedance bandwidth of two ports is 51% with Return Loss > 15 dB from 1.68 to 2.83 GHz, and the isolation between two ports is greater than 27 dB. The measured results also show that a stable radiation pattern with 65.4<sup>o </sup>± 2.4<inline-formula> <tex-math notation="LaTeX">$ ^{\circ}$</tex-math></inline-formula> half-power beamwidth in the horizontal plane for slant 45<inline-formula><tex-math notation="LaTeX">$ ^{\circ}$</tex-math></inline-formula> polarization and a stable gain of 8.8 ± 0.7 dBi are achieved from 1.7 to 2.7 GHz.
Determining Diversity of Freshwater Fungi on Decaying Leaves: Comparison of Traditional and Molecular Approaches

ABSTRACT Traditional microscope-based estimates of species richness of aquatic hyphomycetes depend upon the ability of the species in the community to sporulate. Molecular techniques which detect DNA from all stages of the life cycle could potentially circumvent the problems associated with traditional methods. Leaf disks from red maple, alder, linden, beech, and oak as well as birch wood sticks were submerged in a stream in southeastern Canada for 7, 14, and 28 days. Fungal biomass, estimated by the amount of ergosterol present, increased with time on all substrates. Alder, linden, and maple leaves were colonized earlier and accumulated the highest fungal biomass. Counts and identifications of released conidia suggested that fungal species richness increased, while community evenness decreased, with time (up to 11 species on day 28). Conidia of Articulospora tetracladia dominated. Modifications of two molecular methods—denaturing gradient gel electrophoresis (DGGE) and terminal restriction fragment length polymorphism (T-RFLP) analysis—suggested that both species richness and community evenness decreased with time. The dominant ribotype matched that of A. tetracladia. Species richness estimates based on DGGE were consistently higher than those based on T-RFLP analysis and exceeded those based on spore identification on days 7 and 14. Since traditional and molecular techniques assess different aspects of the fungal organism, both are essential for a balanced view of fungal succession on leaves decaying in streams.
Quantum mechanics as a gauge theory of metaplectic spinor fields

A hidden gauge theory structure of quantum mechanics which is invisible in its conventional formulation is uncovered. Quantum mechanics is shown to be equivalent to a certain Yang–Mills theory with an infinite-dimensional gauge group and a nondynamical connection. It is defined over an arbitrary symplectic manifold which constitutes the phase space of the system under consideration. The "matter fields" are local generalizations of states and observables; they assume values in a family of local Hilbert spaces (and their tensor products) which are attached to the points of phase space. Under local frame rotations they transform in the spinor representation of the metaplectic group Mp(2N), the double covering of Sp(2N). The rules of canonical quantization are replaced by two independent postulates with a simple group-theoretical and differential-geometrical interpretation. A novel background-quantum split symmetry plays a central role.
ReBoc: Accelerating Block-Circulant Neural Networks in ReRAM

Deep neural networks (DNNs) emerge as a key component in various applications. However, the ever-growing DNN size hinders efficient processing on hardware. To tackle this problem, on the algorithmic side, compressed DNN models are explored, of which block-circulant DNN models are memory efficient and hardware-friendly; on the hardware side, resistive random-access memory (ReRAM) based accelerators are promising for in-situ processing of DNNs. In this work, we design an accelerator named ReBoc for accelerating block-circulant DNNs in ReRAM to reap the benefits of light-weight models and efficient in-situ processing simultaneously. We propose a novel mapping scheme which utilizes Horizontal Weight Slicing and Intra-Crossbar Weight Duplication to map block-circulant DNN models onto ReRAM crossbars with significant improved crossbar utilization. Moreover, two specific techniques, namely Input Slice Reusing and Input Tile Sharing are introduced to take advantage of the circulant calculation feature in block- circulant DNNs to reduce data access and buffer size. In REBOC, a DNN model is executed within an intra-layer processing pipeline and achieves respectively 96× and 8.86× power efficiency improvement compared to the state-of-the-art FPGA and ASIC accelerators for block-circulant neural networks. Compared to ReRAM-based DNN accelerators, REBOC achieves averagely 4.1× speedup and 2.6× energy reduction.
Essentials of corporate governance

Praise for Essentials of Corporate Governance"Mr. Anand's book is a practical study of the complicated issues surrounding the world of corporate governance. He includes excellent case studies and best practice solutions for improving governance programs within all types of organizations. " -Chrisan HerrodV.P. Marketing and Business DevelopmentCompliance Spectrum"This book is a highly practical, accessible guide to post-Enron reforms and an essential resource for managers who want more than just to comply with SOX; this book will help them benefit from it. " -Nell MinowEditor and cofounderThe Corporate LibraryWritten by Sanjay Anand, one of the world's leading corporate governance, risk management, and regulatory compliance experts, this simple-to-use book is designed with appreciation for demanding professional obligations, with information easy to find and at your fingertips. This professional guide's nuts-and-bolts presentation examines why corporate governance is important, to put you in a better position to understand its successful implementation for your organization.Essentials of Corporate Governance will challenge your concept of corporate governance and provide you with an understanding of: The concept of governance The competing goals that corporations may have Why there is a call for corporations to be more ethical The various forms of corporate structure Corporate governance in emerging markets Corporate governance within nonprofit organizations Communicating the idea of corporate governance as a process and an ideal rather than a set of criteria, this accessible and relevant book is the resource and reference guide you will turn to time and again for the knowledge you need to make corporate governance work for your corporation.
Wage Rigidity and Disinflation in Emerging Countries

This paper examines the consequences of rapid disinflation for downward wage rigidities in two emerging countries, Brazil and Uruguay, relying on high quality matched employer-employee administrative data. Downward nominal wage rigidities are more important in Uruguay, while wage indexation is dominant in Brazil. Two regime changes are observed during the sample period, 1995-2004: (i) in Uruguay wage indexation declines, while workers' resistance to nominal wage cuts becomes more pronounced; and (ii) in Brazil, the introduction of inflation targeting by the Central Bank in 1999 shifts the focal point of wage negotiations from changes in the minimum wage to expected inflation. These regime changes cast doubts on the notion that wage rigidity is structural in the sense of Lucas (1976).
Histological changes in murine haemophilic synovitis: a quantitative grading system to assess blood‐induced synovitis

Summary. Haemophilia is a congenital disorder that results in frequent bleeding into joints, in which a chronic and debilitating arthritis develops. The presence of blood evokes an inflammatory and proliferative synovial reaction. Although the molecular mechanisms and biochemical pathways which underlie this disorder are not known, significant advances have been made by studying a murine model of human haemophilic synovitis. In order to better understand and correlate the pathological, molecular and biochemical changes, it has become necessary to grade the histological changes observed. Despite a search of the literature and review of relevant publications, none of the currently utilized schemes were appropriate, and therefore a novel grading scheme was developed. After review of over 1000 histological sections, six characteristic changes were identified: (i) synovial hyperplasia; (ii) vascularity; (iii) discolouration by haemosiderin; (iv) the presence of blood (erythrocytes); (v) villus formation; and (vi) cartilage erosion. Synovial hyperplasia and vascularity were present in variable amounts and were quantitatively scored (0–3), while the other changes were qualitatively scored as absent or present (0 or 1). Application of the grading scheme was tested and a high interobserver correlation (greater than 80%) was found. The scheme was easy to learn even by novices, with no prior experience. The availability of the histological grading scheme for murine synovitis will allow for precise evaluation of the pathological changes following joint bleeding, and facilitate correlations with molecular and biochemical changes that lead to these changes.
ZAP-70 and SLP-76 Regulate Protein Kinase C-θ and NF-κB Activation in Response to Engagement of CD3 and CD28

The transcription factor NF-κB is a critical regulator of T cell function that becomes strongly activated in response to coengagement of TCR and CD28. Although events immediately proximal to NF-κB activation are well understood, uncertainty remains over which upstream signaling pathways engaged by TCR and CD28 lead to NF-κB activation. By using Jurkat T cell lines that are deficient or replete for either the protein tyrosine kinase ZAP-70 or the cytosolic adapter molecule SLP-76, the role of these proteins in modulating NF-κB activation was examined. NF-κB was not activated in response to coengagement of TCR and CD28 in either the ZAP-70- or SLP-76-negative cells, whereas stimuli that bypass these receptors (PMA plus A23187, or TNF-α) activated NF-κB normally. Protein kinase C (PKC) θ activation, which is required for NF-κB activation, also was defective in these cells. Reexpression of ZAP-70 restored PKCθ and NF-κB activation in response to TCR and CD28 coengagement. p95vav (Vav)-1 tyrosine phosphorylation was largely unperturbed in the ZAP-70-negative cells; however, receptor-stimulated SLP-76/Vav-1 coassociation was greatly reduced. Wild-type SLP-76 fully restored PKCθ and NF-κB activation in the SLP-76-negative cells, whereas 3YF-SLP-76, which lacks the sites of tyrosine phosphorylation required for Vav-1 binding, only partially rescued signaling. These data illustrate the importance of the ZAP-70/SLP-76 signaling pathway in CD3/CD28-stimulated activation of PKC θ and NF-κB, and suggest that Vav-1 association with SLP-76 may be important in this pathway.
An Approach for Object Picking using Correlation analysis and Robotic Manipulation

The aim of the present work is to pick and place an object with the help of robotic manipulator using computer vision. Real time object detection is achieved using a camera to capture the image in the region of interest (ROI). 2-D correlation between the object and captured image, along with image processing techniques, locates the object position. The pixel coordinates are then converted to real time distance coordinates. The object location is conveyed to the robotic arm with the help of software instructions and required operation of pick/place is performed. The object is successfully located and grabbed by the robotic arm, provided the relative position of the robotic arm and the camera is fixed. The method uses two-dimensional image analysis in place of three-dimensional object detecting techniques. Hence the proposed algorithm is simple, requires less memory space, does not require any filter, reduces the instruction set and has high accuracy.
Using Meta-Analysis in Psychiatric Research

Meta-analysis is a technique for summarizing the results of many studies which can allow reviewers in a particular field to arrive at a synthesis of the various findings in a more objective manner than relying on expert opinion and combine the results of these studies to arrive at an overall estimate of the magnitude of the effect of a treatment, to determine if the evidence favours its effectiveness. The technique consists of determining an effect size or odds ratio for each study and combining them, taking into account the fact that studies with large samples should exert more influence than those with small samples. However, the procedure is not mechanical. The reviewer must make a series of decisions regarding the studies to be included or excluded, the weight to place on the methodological rigour of the trials, the results from each study to be used, how to handle differences in the magnitude of the results across studies, how to derive the best overall estimate of the effect across studies, and how to determine the precision of that estimate. Each of these decisions can affect both the quality of the review and the nature of the findings.
The early clinical development of Ebola virus treatments

Filoviruses are highly pathogenic negative-stranded RNA hemorrhagic fever viruses. First discovered in 1967, filovirus infections in humans have increased, culminating with the recent Ebola virus epidemic in 2013–2016 that infected over 28,000 people. There are three genera of filoviruses. Ebolavirus consists of five species: Ebola virus (EBOV), which was first discovered in 1976 and was responsible for the 2013–2016 West African epidemic; Sudan virus (SUDV), Tai Forest virus (TAFV), Bundibugyo virus (BDBV), and Reston virus (RESTV). Marburgvirus (Marburg, MARV, and Ravn, RAVV) is the founding member of the filoviruses and just as lethal as the ebolaviruses. The newest filovirus genera, cuevavirus, is composed of a single species (Lloviu, LLOV). The recent West African EBOV epidemic has brought the need for filovirus therapeutics to the forefront. Presented here is a brief discussion of the different categories of experimental therapeutics for filovirus infection (Figure 1), with an emphasis on those that have been used in EBOV or MARV infection in humans or are in advanced preclinical development.
Detection of licensed users' activity in a random access ultra wideband cognitive system

In this work it is considered a ultra wideband cognitive radio network where multiple secondary users (SUs) communicate with an access point (AP) in an opportunistic way. The SUs adopt a distributed medium access control (MAC) scheme based on time contention through random medium access. One or multiple primary users (PUs) may become active in the entire band or in part of it, which may impact in the communications of the SUs. Departing from a classical random access scheme for the SUs, it is derived a solution to estimate the level of activity of the PUs through the observation of different data available at the MAC layer of each SU. Differently from the majority of the works already proposed, no physical spectrum sensing is needed to estimate the activity of the PUs since the estimation only relies on data collected at the MAC layer. Based on the level of PUs' activity detected by each SU, it is proposed a solution to regulate the SU's medium access in order to guarantee a given level of protection to the PUs. The formal methodology is evaluated through simulation and several results confirm the effectiveness of our proposal.
Determine Of the Exercise Intensity That Elicits Maximal Fat Oxidation In Untrained Male Students

Fat and carbohydrate are the main sources of energy for consumption during rest, exercise and training activities, and they are related to factors like duration and intensity of exercise. The present study was designed to determine the maximal fat oxidation rate in untrained male students following an incremental training session. To do so, 9 untrained male students (VO2max: 36.58 ± 2.95 ml.kg.min and BMI 24.28 ± 1.83) took an incremental running test with 3 minute intervals on the treadmill. During the test, fat oxidation rate was measured using indirect stoichiometry method. Maximal fat oxidation and total fat oxidation rate variables were determined during this test. The mean value of fat oxidation rates were compared in 7 levels of exercise intensity with repeated measurement and LSD test. The results showed that maximal fat oxidation rate was 0.23±0.02 g.min in untrained subjects. The total fat oxidation rate in untrained subjects was 1.20 ± 0.13g/min. There was a significant different between the fat oxidation rate during 7 levels of exercise. Based on VO2max and HRmax percentage, the maximal fat oxidation was occur in 42 72±3 01 percent of VO2max and 60 09±3 37 percent of HRmax in untrained subjects. Based on the results, with increase the exercise intensity until Fatmax point the fat oxidation rates were increase and afterward that decrease in higher exercise intensity.
Chirality and drugs used to treat psychiatric disorders.

Numerous psychiatric drugs, particularly antidepressants, have one or more chiral centres (centres of asymmetry) introduced during synthesis; this results in the formation of enantiomers (nonsuperimposable mirror images) which may differ from one another markedly with regard to pharmacodynamic and pharmacokinetic properties.1 During synthesis, enantiomers are usually produced in equal quantities, and the resultant drug is a racemate (mixture of enantiomers in equal proportions). Separation of enantiomers is often difficult and costly, and in the past, most such drugs have been marketed as racemates, despite the fact that use of single enantiomers may have several advantages.
A New Linkage between Corporate and Public Governance Through the Lens of Incremental Cash Flows

While in the study of Corporate Governance we can avail ourselves of the incremental cash-flow model (ICFM), the analysis of Public Governance has been falling behind with this issue. The paper sets forth an innovative linkage between both fields of learning and practice, by means of a suitable framing of such model that would allow us to take advantage of a deeper research focus just within the interface of both governances. Firstly, the ICM is derived in the current shape that experts in Corporate Governance make use of it. Secondly, we sharpen up the ICFM to match variegated needs in research and applications of Public Governance.
Financial decision support using neural networks and support vector machines

Abstract: Bankruptcy prediction and credit scoring are the two important problems facing financial decision support. The multilayer perceptron (MLP) network has shown its applicability to these problems and its performance is usually superior to those of other traditional statistical models. Support vector machines (SVMs) are the core machine learning techniques and have been used to compare with MLP as the benchmark. However, the performance of SVMs is not fully understood in the literature because an insufficient number of data sets is considered and different kernel functions are used to train the SVMs. In this paper, four public data sets are used. In particular, three different sizes of training and testing data in each of the four data sets are considered (i.e. 3:7, 1:1 and 7:3) in order to examine and fully understand the performance of SVMs. For SVM model construction, the linear, radial basis function and polynomial kernel functions are used to construct the SVMs. Using MLP as the benchmark, the SVM classifier only performs better in one of the four data sets. On the other hand, the prediction results of the MLP and SVM classifiers are not significantly different for the three different sizes of training and testing data.