bluuebunny/crossref_metadata_2025 huggingface dataset:
A Method for Comparative Performance Evaluation of Structural Optimization Codes: Part I — Theory
Authors: Subbarayan G. , Bartel D. L. , Taylor D. L.
Published: April 2021

This paper presents a systematic procedure for the comparative performance evaluation of nonlinear programming codes intended for applications in structural optimization. Part I discusses the issues in the evaluation of nonlinear programming codes and proposes a performance evaluation scheme for structural optimization codes. Aspects of performance evaluation such as the choice of test problems and appropriate set of performance criteria for structural optimization codes are described. A procedure to analyze codes based on their observed geometric behavior for test problems is also presented. The proposed method is contrasted with studies conducted in the past for comparative performance evaluation of nonlinear programming codes. Part II presents an application of the theory described in part I to evaluate two design optimization codes.
Building an Expert System for Power Plant Design
Authors: Akagi S. , Fujita L. , Kubonishi H.
Published: April 2021

An expert CAD system for power plant design is developed with expert system for design built by the authors. The design of power plants is characterized by selecting the candidates for the various machineries and equipments which compose the plants based on the expertise. In the system, design knowledge is described in the form of an object-oriented knowledge representation which can support design process flexibly, and in a user-friendly way. The system also provides the hybrid functions with numerical computations and graphics, as well as AI techniques. Its effectiveness as a design tool is ascertained through the applications to a marine power plant.
Development of a Knowledge Based System Implementing Taguchi Class Methods for Engineering Design
Authors: Phelps T. A. , Karra C. , Ragsdell K. M.
Published: April 2021

A major problem in industry today is inefficient and poor quality design. A general tool to aid in the improvement of this common problem is presented. The proposed tool is comprised of a computer-aided design program embodying Taguchi methods and using knowledge-based system techniques. The primary purpose of such a program is to encourage design improvements early in the design process, thereby making the process more efficient and resulting in a better design. The tool is intended to aid designers unfamiliar with the “Design for Latitude” concept and other parts of the Taguchi methods how to set up and solve problems for solution. The overall result of using this kind of tool should be better design through catching problems and weaknesses very early in the process, before most commitments to manufacturing processes and tooling have been made.
An Integrated Approach to the Optimal Sequencing of Robot Operations in a Workcell
Authors: Sarin S. C. , Desai C. J.
Published: April 2021

In this paper we develop an integrated approach to optimally sequence robot operation in a workcell. The workcell represents a flowshop containing multiple robots with known inverse kinematic solution that are used to transport jobs among machines. The objeotive is to determine the sequence of robot operations so as to minimize the total time needed to complete all jobs (known as makespan). The integrated approach consists of determining optimal robot task sequences using a branch and bound procedure, and a graphical simulation procedure to display robot motion during the performance of transport operations. The graphical simulation is used to detect interference among robots which is hard to be incorporated in the branch and bound procedure. Infeasible robot sequences are discarded and other solutions from the branch and bound procedure are displayed using the graphical simulation procedure to determine a near optimal and feasible sequence. The integrated approach is implemented on a prototype system.
Power-Based Simplification of Dynamic System Models
Authors: Rosenberg R. C. , Zhou T.
Published: April 2021

Simplification of system models is done in a variety of ways. A new approach based on measures of power interaction within a system graph model is presented in this paper. The method can detect the existence and location of weak coupling in both linear and nonlinear systems. Weak coupling may be exploited by partitioning the system into subsystems or by eliminating unimportant effects. Both types of simplification typically lead to reduced computational loads and greater model insight.
A Dynamic Simulation Approach to Machine Component Life Prediction
Authors: Liu T. S. , Haug E. J. , Dopker B.
Published: April 2021

A system simulation approach is presented for dynamic stress analysis and life prediction of components of machines that undergo nonsteady gross motion and elastic deformation. The method employs finite element structural analysis, coupled gross motion-elastic deformation dynamics, and computer-based fatigue analysis, A computer aided engineering methodology is developed for life prediction by linking together software from dynamics, structures, and fatigue life estimation; to compliment conventional fatigue experiments. Dynamic stress analysis is carried out using either an uncoupled gross motion-elastic deformation method or a more accurate approach that takes into account the coupling between large displacements and elastic deformation. With the aid of vehicle operational scenarios, stress/strain histories at critical regions in vehicle components during a projected service life are simulated. A local strain approach is used to calculate cumulative fatigue damage at notches, which is used in assessing fatigue life of components during the design phase; i.e., prior to availability of experimental data A vehicle example is presented, using a simplified dynamic-stress analysis method. The more general and accurate fully coupled dynamic-stress analysis method will be illustrated in a subsequent paper.
A risk-based approach for managing hydraulic fracturing–induced seismicity
Authors: Schultz Ryan , Beroza Gregory C. , Ellsworth William L.
Published: April 2021

Varying the stop lights

Traffic light protocols can help to mitigate induced earthquakes from unconventional oil production. However, they are not geographically tuned to account for how shaking may actually translate to structural damage. Schultz
et al.
incorporated damage tolerance into a traffic light protocol for the Eagle Ford shale play. They found that shut-off may be necessary more quickly in populated regions, whereas sparsely populated areas of the play can take up to a magnitude 5 earthquake without issue. This risk-based strategy provides a more nuanced approach to regulating induced seismicity.

Science
, this issue p.
504
Equity in cost-benefit analysis
Authors: Hahn Robert W.
Published: April 2021

One key way that many governments around the world incorporate scientific research into policy-making is through cost-benefit analysis (CBA). But despite well-established practices for rigorous estimation of the pros and cons of policies, there is room to improve, particularly in characterizing difficult-to-measure benefits and the distribution of the costs and benefits across different segments of society. In this regard, announcements by US President Biden, if brought to fruition, could have far-reaching implications for how CBA is used in government decision-making. But such promising (and familiar) rhetoric is no guarantee of real progress, and the devil, as always, is in the details. These details are where the scientific community has an important role to play to improve the use of CBA and to hold the administration accountable.
Unlocking the secrets of self-awareness
Know Thyself: The Science of Self-Awareness
Stephen M. Fleming
Basic Books, 2021. 304 pp.
Authors: Ruff Christian C.
Published: April 2021

Long neglected by researchers, metacognition has made its way to the scientific spotlight
David William Schindler (1940–2021)
Authors: St. Louis Vincent L. , Schiff Sherry L. , Kelly Carol A.
Published: April 2021

Trailblazing aquatic researcher, advocate, and whole-ecosystem experimentalist
Which psychosocial interventions improve sex worker well-being? A systematic review of evidence from resource-rich countries
Authors: Turner Kevin , Meyrick Jane , Miller Danny , Stopgate Laura
Published: April 2021

Objective

To establish the state of the evidence base around psychosocial interventions that support well-being in sex workers in order to inform policy and practice within a resource-rich geographical context.

Methods

Published and unpublished studies were identified through electronic databases (PsychINFO, CINHAL Plus, MEDLINE, EMBASE, The Cochrane Library and Open Grey), hand searching and contacting relevant organisations and experts in the field. Studies were included if they were conducted in high-income settings with sex workers or people engaging in exchange or transactional sex, and evaluated the effect of a psychosocial intervention with validated psychological or well-being measures or through qualitative evaluation.

Results

A total of 19 202 studies were identified of which 10 studies met the eligibility criteria. The heterogeneity found dictated a narrative synthesis across studies. Overall, there was very little evidence of good quality to make clear evidence-based recommendations. Despite methodological limitations, the evidence as it stands suggests that peer health initiatives improve well-being in female street-based sex workers. Use of ecological momentary assessment (EMA), a diary-based method of collecting real-life behavioural data through the use of twice-daily questionnaires via a smartphone, increased self-esteem and behaviour change intentions.

Conclusions

Work with sex workers should be based on an evidence-based approach. Limitations to the existing evidence and the constraints of this work with vulnerable groups are recognised and discussed.
Genetic and epigenetic mechanisms in the development of congenital heart diseases
Authors: Wu Yue , Jin Xiaosi , Zhang Yuhao , Zheng Jing , Yang Rulai
Published: April 2021

Congenital heart disease (CHD) is the most common of congenital cardiovascular malformations associated with birth defects, and it results in significant morbidity and mortality worldwide. The classification of CHD is still elusive owing to the complex pathogenesis of CHD. Advances in molecular medicine have revealed the genetic basis of some heart anomalies. Genes associated with CHD might be modulated by various epigenetic factors. Thus, the genetic and epigenetic factors are gradually accepted as important triggers in the pathogenesis of CHD. However, few literatures have comprehensively elaborated the genetic and epigenetic mechanisms of CHD. This review focuses on the etiology of CHD from genetics and epigenetics to discuss the role of these factors in the development of CHD. The interactions between genetic and epigenetic in the pathogenesis of CHD are also elaborated. Chromosome abnormalities and gene mutations in genetics, and DNA methylations, histone modifications and on-coding RNAs in epigenetics are summarized in detail. We hope the summative knowledge of these etiologies may be useful for improved diagnosis and further elucidation of CHD so that morbidity and mortality of children with CHD can be reduced in the near future.
Responses of vulnerable fishes to environmental stressors in the Canadian Great Lakes basin1
Authors: Rodríguez Marco A. , Marselli Geoffrey , Mandrak Nicholas E.
Published: April 2021

Quantifying the responses of rare and vulnerable species to environmental stressors poses special challenges. This study examined the responses of vulnerable fish species listed under the Species at Risk Act to environmental stressors in lakes, streams, and wetlands of the Canadian Great Lakes basin. We used a joint species distribution model (JSDM) to improve the estimates of responses of vulnerable species to environmental stressors, and the effects of functional traits on those responses, by “borrowing information” from abundant species for which we have more information. We measured abundance, functional traits, and taxonomic relationships for 115 freshwater fish species (including 12 vulnerable species), and environmental features, at 1972 sites. The JSDM yielded more precise estimates of responses than single-species models fitted to each vulnerable species. Habitat associations inferred from the JSDM showed substantial overlap with those provided in COSEWIC status reports. Model-derived responses to environmental stressors can provide a management-friendly basis for species classification in terms of species’ tolerances to various forms of environmental change, and supplement the qualitative criteria for habitat requirements currently used in assessments of species vulnerability.
The Effect of Organisational Learning Capability on Individual Performance through the Use of Enterprise Resource Planning and User Satisfaction
Authors: Hedayati Alireza , Khalilzadeh Mohammad , Bahari Arman
Published: April 2021

Given the global competition between organisations to deliver products and services, the need for integrated information is felt. Enterprise Resource Planning (ERP) system is one of the important technology tools which play an important role in the integration of information in the organisation and is a prerequisite for joining the global market. This study aims to experimentally test a framework for identifying the relationship between organisational learning capability, using an organisational resource planning system, end-user satisfaction and individual performance. The results can be used to adopt human resource policies in the organisation. Smart PLS 2 software is also used for data analysis as well as the structural equation modelling. The results show that organisational learning ability through user satisfaction and the use of organisational resource planning system affects the individual performance.
Toward Multi-FPGA Acceleration of the Neural Networks
Authors: Biookaghazadeh Saman , Ravi Pravin Kumar , Zhao Ming
Published: April 2021

High-throughput and low-latency Convolutional Neural Network (CNN) inference is increasingly important for many cloud- and edge-computing applications. FPGA-based acceleration of CNN inference has demonstrated various benefits compared to other high-performance devices such as GPGPUs. Current FPGA CNN-acceleration solutions are based on a single FPGA design, which are limited by the available resources on an FPGA. In addition, they can only accelerate conventional 2D neural networks. To address these limitations, we present a generic multi-FPGA solution, written in OpenCL, which can accelerate more complex CNNs (e.g., C3D CNN) and achieve a near linear speedup with respect to the available single-FPGA solutions. The design is built upon the Intel Deep Learning Accelerator architecture, with three extensions. First, it includes updates for better area efficiency (up to 25%) and higher performance (up to 24%). Second, it supports 3D convolutions for more challenging applications such as video learning. Third, it supports multi-FPGA communication for higher inference throughput. The results show that utilizing multiple FPGAs can linearly increase the overall bandwidth while maintaining the same end-to-end latency. In addition, the design can outperform other FPGA 2D accelerators by up to 8.4 times and 3D accelerators by up to 1.7 times.
Real-time Subsurface Control Variates
Authors: Xie Tiantian , Olano Marc
Published: April 2021

Real-time adaptive sampling is a new technique recently proposed for efficient importance sampling in realtime Monte Carlo sampling in subsurface scattering. It adaptively places samples based on variance tracking to help escape the uncanny valley of subsurface rendering. However, the occasional performance drop due to temporal lighting dynamics (e.g., guns or lights turning on and off) could hinder adoption in games or other applications where smooth high frame rate is preferred. In this paper we propose a novel usage of Control Variates (CV) in the sample domain instead of shading domain to maintain a consistent low pass time. Our algorithm seamlessly reduces to diffuse with zero scattering samples for sub-pixel scattering. We propose a novel joint-optimization algorithm for sample count and CV coefficient estimation. The main enabler is our novel time-variant covariance updating method that helps remove the effect of recent temporal dynamics from variance tracking. Since bandwidth is critical in real-time rendering, a solution without adding any extra textures is also provided.
Guided Visibility Sampling++
Authors: Koch Thomas , Wimmer Michael
Published: April 2021

Visibility computation is a common problem in the field of computer graphics. Examples include occlusion culling, where parts of the scene are culled away, or global illumination simulations, which are based on the mutual visibility of pairs of points to calculate lighting. In this paper, an aggressive from-region visibility technique called Guided Visibility Sampling++ (GVS++) is presented. The proposed technique improves the Guided Visibility Sampling algorithm through improved sampling strategies, thus achieving low error rates on various scenes, and being over four orders of magnitude faster than the original CPU-based Guided Visibility Sampling implementation. We present sampling strategies that adaptively compute sample locations and use ray casting to determine a set of triangles visible from a flat or volumetric rectangular region in space. This set is called a potentially visible set (PVS). Based on initial random sampling, subsequent exploration phases progressively grow an intermediate solution. A termination criterion is used to terminate the PVS search. A modern implementation using the Vulkan graphics API and RTX ray tracing is discussed. Furthermore, we show optimizations that allow for an implementation that is over 20 times faster than a naive implementation.
Spatial Transcriptomics: Molecular Maps of the Mammalian Brain
Authors: Ortiz Cantin , Carlén Marie , Meletis Konstantinos
Published: April 2021

Maps of the nervous system inspire experiments and theories in neuroscience. Advances in molecular biology over the past decades have revolutionized the definition of cell and tissue identity. Spatial transcriptomics has opened up a new era in neuroanatomy, where the unsupervised and unbiased exploration of the molecular signatures of tissue organization will give rise to a new generation of brain maps. We propose that the molecular classification of brain regions on the basis of their gene expression profile can circumvent subjective neuroanatomical definitions and produce common reference frameworks that can incorporate cell types, connectivity, activity, and other modalities. Here we review the technological and conceptual advances made possible by spatial transcriptomics in the context of advancing neuroanatomy and discuss how molecular neuroanatomy can redefine mapping of the nervous system.
Use of Video Laryngoscope in Sedated Spontaneously Breathing Patients with Predicted Difficult Tracheal Intubation and Impossibility of Using Fibreoptic Bronchoscopy
Authors: Piroli Alba , Marsili Ida , Marinangeli Franco , Costanzi Silvia , Gentili Luca , Paladini Antonella
Published: April 2021

Intubation with a flexible fibrobronchoscope in an awake patient is frequently considered the technique of choice in patients with predicted difficult intubation. There are, however, situations in which the use of the fibrobronchoscope is not applicable, particularly due to problems attributable to the patient or to limited use of the instrument. In such situations, the video laryngoscope can be a useful alternative, as long as it is associated with adequate sedation of the patient. In fact, it ensures excellent viewing of the glottis, allowing for successful orotracheal intubation to be performed even in case of difficult airways, while keeping the patient spontaneously breathing throughout the procedure. From the data present in the literature, this technique seems to ensure a success rate and a safety profile similar to those obtained with the fibrobronchoscope, moreover, with greater ease of use by the anaesthesiologist. The main purpose of this work is to provide a valid and safe alternative to intubation with a fibrobronchoscope while awake in those patients with anticipated difficult airway management and in whom, for different reasons, fibrobronchoscope cannot be used.
A Study on Distributed Optimization over Large-Scale Networked Systems
Authors: Abeynanda Hansi K. , Lanel G. H. J.
Published: April 2021

Distributed optimization is a very important concept with applications in control theory and many related fields, as it is high fault-tolerant and extremely scalable compared with centralized optimization. Centralized solution methods are not suitable for many application domains that consist of large number of networked systems. In general, these large-scale networked systems cooperatively find an optimal solution to a common global objective during the optimization process. Thus, it gives us an opportunity to analyze distributed optimization techniques that is demanded in most distributed optimization settings. This paper presents an analysis that provides an overview of decomposition methods as well as currently existing distributed methods and techniques that are employed in large-scale networked systems. A detailed analysis on gradient like methods, subgradient methods, and methods of multipliers including the alternating direction method of multipliers is presented. These methods are analyzed empirically by using numerical examples. Moreover, an example highlighting the fact that the gradient method fails to solve distributed problems in some circumstances is discussed under numerical results. A numerical implementation is used to demonstrate that the alternating direction method of multipliers can solve this particular problem, by revealing its robustness compared with the gradient method. Finally, we conclude the paper with possible future research directions.
Total Hip Arthroplasty in a Patient with Mucopolysaccharidosis Type IVB
Authors: van den Eeden Yannick N. T. , Unter Ecker Niklas , Kleinertz Holger , Gehrke Thorsten , Ballhause Tobias M.
Published: April 2021

Introduction. Morquio syndrome or mucopolysaccharidosis (MPS) type IV is a rare autosomal recessive lysosomal storage disease, characterized by abnormal metabolism of glycosaminoglycans associated with specific skeletal deformities, also known as dysostosis multiplex. Case Presentation. We present the case of a 23-year-old patient with advanced osteonecrosis of the femoral head (ONFH) on both sides due to Morquio syndrome. A diagnosis of mucopolysaccharidosis type IVB was made after extensive genetic profiling. The patient had the condition for a long time. At 7 years old, the patient was treated with bilateral pelvic Salter’s osteotomy. Afterward, the patient was able to walk freely but could never take part in sports. At 22 years old, pain in the hip increased, and magnetic resonance imaging showed a bilateral femur head necrosis. Hence, the patient underwent cementless total hip arthroplasty (THA). Intraoperatively, a periprosthetic fracture occurred. Therefore, revision surgery with internal fixation was performed on the next day. Postoperatively, a weight-bearing restriction of 20 kg on the left leg was imposed for 6 weeks. The patient made a full recovery and was able to move without residual complaints. Annual orthopedic evaluation in patients treated with surgical intervention is recommended. Discussion. Orthopedic challenges for mucopolysaccharidoses and corresponding bone alterations, known as dysostosis multiplex, involving trunk and limbs with typical radiological findings have been well described. The hip is invariably involved, with dysplasia affecting the femoral neck (coxa valga), femoral epiphysis (loss of sphericity, osteonecrosis), and a flared hypoplastic iliac wing. Symptomatic therapy consists, on the one hand, of a surgical procedure and, on the other hand, a variety of supportive measures. However, the management of joint replacement in lysosomal storage diseases has not been well reported. All patients with MPS should be considered at high risk for surgical intervention requiring anesthesia because of airway and cardiac disease manifestations. In the case of a need for THA, we recommend cemented stem fixation because of the overall poor bone quality in patients with Morquio syndrome.
Predicting the Number of COVID-19 Sufferers in Malang City Using the Backpropagation Neural Network with the Fletcher–Reeves Method
Authors: Anam Syaiful , Maulana Mochamad Hakim Akbar Assidiq , Hidayat Noor , Yanti Indah , Fitriah Zuraidah , Mahanani Dwi Mifta
Published: April 2021

COVID-19 is a type of an infectious disease that is caused by the new coronavirus. The spread of COVID-19 needs to be suppressed because COVID-19 can cause death, especially for sufferers with congenital diseases and a weak immune system. COVID-19 spreads through direct contact, wherein the infected individual spreads the COVID-19 virus through cough, sneeze, or close contacts. Predicting the number of COVID-19 sufferers becomes an important task in the effort to curb the spread of COVID-19. Artificial neural network (ANN) is the prediction method that delivers effective results in doing this job. Backpropagation, a type of ANN algorithm, offers predictive problem solving with good performance. However, its performance depends on the optimization method applied during the training process. In general, the optimization method in ANN is the gradient descent method, which is known to have a slow convergence rate. Meanwhile, the Fletcher–Reeves method has a faster convergence rate than the gradient descent method. Based on this hypothesis, this paper proposes a prediction model for the number of COVID-19 sufferers in Malang using the Backpropagation neural network with the Fletcher–Reeves method. The experimental results show that the Backpropagation neural network with the Fletcher–Reeves method has a better performance than the Backpropagation neural network with the gradient descent method. This is shown by the Means Square Error (MSE) resulting from the proposed method which is smaller than the MSE resulting from the Backpropagation neural network with the gradient descent method.
Tamoxifen: Will Less Equal More in Women with Precancerous Breast Disease?
Authors: Fabian Carol J.
Published: April 2021

Similar risk reduction but fewer side effects would predict more uptake and compliance with low (5 mg) versus full (20 mg) dose tamoxifen. Benefit with low dose is demonstrated for perimenopausal/postmenopausal women with intraepithelial neoplasia and high lesion Ki-67. Longer follow-up needed to determine benefit with low lesion Ki-67.

See related article by DeCensi et al., p. 3576
Biliary Sphincter of Oddi Dysfunction
Authors: Haider Asim , Siddiqa Ayesha , Ali Nisha , Mehershahi Shehriyar
Published: April 2021

Sphincter of Oddi dysfunction (SOD) is a syndrome caused by either dyskinesia or stenosis of the sphincter of Oddi. It has been categorized into biliary and pancreatic SOD based on clinical features and laboratory findings. We present a case of a 51-year-old female (post-cholecystectomy) who presented with intermittent chronic right upper quadrant pain. Laboratory investigations showed persistently elevated liver function tests and a dilated common bile duct without the presence of any stones. Endoscopic retrograde cholangiopancreatography with manometry showed an elevated sphincter of Oddi pressure, thus confirming the diagnosis of SOD. She underwent endoscopic sphincterotomy and papillotomy with normalization of liver function tests and resolution of her chronic symptoms.
Do the Offspring of Sex Reversals Have Higher Sensitivity to Environmental Perturbations?
Authors: Piferrer Francesc , Anastasiadi Dafni
Published: April 2021

Sex determination systems in vertebrates vary along a continuum from genetic (GSD) to environmental sex determination (ESD). Individuals that show a sexual phenotype opposite to their genotypic sex are called sex reversals. Aside from genetic elements, temperature, sex steroids, and exogenous chemicals are common factors triggering sex reversal, a phenomenon that may occur even in strict GSD species. In this paper, we review the literature on instances of sex reversal in fish, amphibians, reptiles, birds, and mammals. We focus on the offspring of sex-reversed parents in the instances that they can be produced, and show that in all cases studied the offspring of these sex-reversed parents exhibit a higher sensitivity to environmental perturbations than the offspring of non-sex-reversed parents. We suggest that the inheritance of this sensitivity, aside from possible genetic factors, is likely to be mediated by epigenetic mechanisms such as DNA methylation, since these mechanisms are responsive to environmental cues, and epigenetic modifications can be transmitted to the subsequent generations. Species with a chromosomal GSD system with environmental sensitivity and availability of genetic sex markers should be employed to further test whether offspring of sex-reversed parents have greater sensitivity to environmental perturbations. Future studies could also benefit from detailed whole-genome data in order to elucidate the underlying molecular mechanisms. Finally, we discuss the consequences of such higher sensitivity in the context of global climate change.
Evolution of SARS-CoV-2: Review of Mutations, Role of the Host Immune System
Authors: Banoun Helene
Published: April 2021

Since the reporting of the first cases of coronavirus in China and the publication of the first sequence of SARS-CoV-2 in December 2019, the virus has undergone numerous mutations. In Europe, the spring outbreak (March–April) was followed by a drop in the number of cases and deaths. The disease may have evolved into a milder form. The increase in PCR-positive cases in late summer 2020 did not lead to the expected increase in hospitalizations, ICU admissions, and deaths, based on the severity of the disease in the spring. This difference in disease severity could be due to factors independent of the virus or to the evolution of the virus. This review attempts to identify the mutations that have appeared since the beginning of the pandemic and their role in the temporal evolution of the pandemic. There are a cell and humoral type cross-reactivity in a large part of the population to common cold coronaviruses (HCoVs) and SARS-CoV-2. Evolutionarily important mutations and deletions have emerged in the SARS-CoV-2 genes encoding proteins that interact with the host immune system. In addition, one of the major mutations (in viral polymerase) is logically associated with a higher frequency of mutations throughout the genome. This frequency fluctuates over time and shows a peak at the time when the epidemic was most active. The rate of mutations in proteins involved in the relationship to the immune system continues to increase after the first outbreak. The cross-reactivity on the 1 hand and the viral mutations observed on the other hand could explain the evolution of the pandemic until the summer of 2020, partly due to the evolution of the virus in relation to the host immune system. The immunization campaign began in December 2020: concerns are emerging about a possible escape of the circulating variants vaccines in early 2021. These variants could also escape immunity acquired through infection with the 2020 strains.
CD48 Expression on Eosinophils in Nasal Polyps of Chronic Rhinosinusitis Patients
Authors: Zoabi Yara , Rahimli Alekberli Fidan , Minai-Fleminger Yael , Eliashar Ron , Levi-Schaffer Francesca
Published: April 2021

Introduction: The pathogenesis of chronic rhinosinusitis (CRS) with nasal polyps (CRSwNPs) is not yet completely understood. Based on current knowledge, the infiltration of mast cells and eosinophils in nasal polyps (NPs) plays an important role. This study aimed to investigate the interplay of asthma and allergy etiopathology in CRSwNPs patients by specifically studying tissue mast cells and eosinophils and the pro-inflammatory marker CD48. Methods: Immunohistochemistry was used to assess eosinophils, mast cells, and CD48 expressing eosinophils infiltrating NPs, and flow cytometry was used to assess surface receptors expression on eosinophils from digested NPs. Results: Immunohistochemical analyses showed that mast cell infiltration in NPs is higher in allergic patients in comparison to nonallergic patients; eosinophils infiltration in asthmatic NPs was significantly elevated in comparison to the nonasthmatic NPs, and membrane CD48 (mCD48) expression on eosinophils infiltrating nonallergic asthmatic NPs was highly elevated in comparison to the other subgroups. Similarly, mCD48 and its high-affinity ligand m2B4’s expression on eosinophils from enzymatically digested NPs were significantly higher in nonallergic asthmatics in comparison to allergic asthmatics. Conclusions: Eosinophil infiltration in NPs for asthmatic patients, and mast cell infiltration for allergic patients, may be used as reliable biomarkers for endotyping CRSwNPs. In addition, CD48 in asthmatic patients who developed CRSwNPs could be regarded as a potential target for treatment.
Inflammatory Markers May Inform the Effects of Electroconvulsive Therapy on Cognition in Patients with Depression
Authors: Belge Jan-Baptist , Diermen Linda Van , Sabbe Bernard , Morrens Manuel , Coppens Violette , de Timary Philippe , Constant Eric , Sienaert Pascal , Schrijvers Didier
Published: April 2021

Introduction: The neurobiological mechanisms underlying the acute cognitive effects of electroconvulsive therapy (ECT) remain poorly understood. Prior research has shown that proinflammatory cytokines such as IL-6, TNF-α, IL1-β, and IL-10 may interfere with cognitive functioning. Interestingly, immunomodulation is one of the proposed modes of action of ECT. This study investigates whether changes of peripheral levels of IL-6, TNF-α, IL1-β, and IL-10 are related to changes in cognitive functioning following ECT. Methods: In the week before and 1 week after an acute course of ECT, 62 patients suffering from depression underwent a neuropsychological evaluation to assess their processing speed using the Symbol Digit Substitution Test (SDST), verbal episodic memory using the Hopkins Verbal Learning Test-Revised (HVLT-R), and their retrospective autobiographic memory using the Autobiographical Memory Interview (AMI) with the peripheral inflammatory markers being measured at the same 2 time points. Results: Patients improved drastically following ECT, while their main performance on both the HVLT-R and AMI declined and their SDST scores remained stable. The levels of IL-6 and IL1-β had both decreased, where the decrease in IL-6 was related to the decrease in HVLT-R scores. Higher baseline IL-10 levels were associated with a more limited decrease of the HVLT-R scores. Conclusion: Our findings tentatively suggest that the effects of ECT on verbal episodic memory may be related to the treatment’s immunomodulatory properties, most notably due to decreased IL-6 levels. Moreover, baseline IL-10 appears to be a potential biomarker to predict the effects of ECT on verbal episodic memory. Whilst compelling, the results of this study should be interpreted with caution as, due to its exploratory nature, no correction for multiple comparisons was made. Further, a replication in larger cohorts is warranted.
Numerical analysis of the photovoltaic system inspection with active cooling
Authors: Mohammed Ahmed Hasan , Hasan Ghanim Thiab , Ali Kamil Jadu
Published: April 2021

The use of solar energy may replace the present fossil fuel or gas to produce electricity. The goal of this study is to set up a simulation model to survey the performance of a photovoltaic thermal system (PV/T) based on the computational fluid dynamics (CFD) method. Ansys fluent software has been used for the simulation procedure. The electrical panel output and its efficiency were investigated numerically. In addition, the effect of variations in absorbed radiation on inlet fluid and absorber panel temperature on the system performance was investigated. The study was conducted for three cases, in a first case, where there is no refrigerant in the system and in the latter case, at constant fluid rate of the pump, whereas the third case with optimal pump operation. The numerical findings obtained from CFD simulators have been compared with the test records of the experimental results of the literature. The two results have a good agreement. From the obtained results, it can be noted that the system shows a good improvement for the electric net efficiency level of 3.52% with a lower reduction of the thermal system efficiency of 1.96% in comparison to the system when using the constantly high flow rate.
A new energy regeneration system for A BLDC motor driven electric vehicle
Authors: Palanisamy R. , Sahasrabuddhe Rohit , Hiteshkumar Mathur Kartik , Puranik Jay Anil
Published: April 2021

Amidst the ever-increasing advancements in the technological realm-the electrical vehicle industry too has seen several leaps. This particularly owes to three primary factors one, the fact that we are running out of conventional resources like petrol and diesel; two, higher efficiency of electric vehicles; and finally, less pollution caused by them. This has led to a burgeoning in the use of BLDC motors with electronic commutation not only in EVs but also in industrial and commercial applications. This requires an enhanced driving and control mechanism to tap the efficiency that such motors provide to increase performance and to get better controllability and reliability. This paper presents a controller for this EV motor driver with increased efficiency by combining various strategies.
A four-element UWB MIMO antenna using SRRs for application in satellite communications
Authors: Abdelhamid Chafai , Sakli Hedi , Sakli Nizar
Published: April 2021

This paper proposes a method for designing a new ultra wide band (UWB) multiple-input multiple-output (MIMO) antenna with two and four elements. First we presented an ultra-wide band antenna we studied these performances. Then, we studied the application of metamaterials to the design of MIMO antennas for miniaturization and the performance of antennas, in order to guarantee the proper functioning of the MIMO system with a much reduced separation distance between the radiating elements (λ/12), where the coupling can be very weak. The application of these circular double ring SRRs materials on the front plan of the antenna has contributed to the increasing of the antenna performance is studied in terms of S-Parameters, efficiency, diversity gain (DG), radiation properties and envelop correlation coefficient (ECC). It offers advantages such as the reduction of weight and congestion that is beneficial for their integration into satellite communications systems.
Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine
Authors: Agrawal Aditi , Paulus Rajeev
Published: April 2021

Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high.
Inter-cell interference mitigation using adaptive reduced power subframes in heterogeneous networks
Authors: Aal-nouman Mohammed I. , Abdullah Osamah , Al Shaikhli Noor Qusay A.
Published: April 2021

With the remarkable impact and fast growth of the mobile networks, the mobile base stations have been increased too, especially in the high population areas. These base stations will be overloaded by users, for that reason the small cells (like pico cells) were introduced. However, the inter-cell interference will be high in this type of Heterogeneous networks. There are many solutions to mitigate this interference like the inter-cell interference coordination (ICIC), and then the further enhanced ICIC (Fe-ICIC) where the almost blank subframes are used to give priority to the (victim users). But it could be a waste of bandwidth due to the unused subframes. For that reason, in this paper, we proposed an adaptive reduced power subframe that reduces its power ratio according to the user’s signal-to-interference-plus-noise ratio (SINR) in order to get a better throughput and to mitigate the intercell interference. When the user is far from the cell, the case will be considered as an edge user and will get a higher priority to be served first. The results show that the throughput of all users in the macro cells and pico cell will be improved when applying the proposed scheme in term of throughput for the users and the cells.
Performance analysis of OFDM-IM scheme under STO and CFO
Authors: Suyoto Suyoto , Subekti Agus , Satyawan Arief Suryadi , Mardiana Vita Awalia , Armi Nasrullah , Kurniawan Dayat
Published: April 2021

In this letter, performance analysis of orthogonal frequency division multiplexing with index modulation (OFDM-IM) is presented in term of bit error rate (BERs). The analysis considers its performance under two impairments, symbol time offset (STO) and carrier frequency offset (CFO) in frequency-selective fading channel. As orthogonal multicarrier system, OFDM-IM is subject to both inter-symbol interference (ISI) and inter-carrier interference (ICI) in a frequency-selective fading channel. OFDM-IM is a new multicarrier communication system, where the active subcarriers indices are used to carry additional bits of information. In general, in the previous existing works, OFDM-IM are evaluated only for near-ideal communication scenarios by only incorporating the CFO factor. In this work, the OFDM-IM performance is investigated and compared with conventional OFDM in the presence of two impairments, STO and CFO. Simulation results show that OFDM-IM outperforms the conventional OFDM with the presence of STO and CFO, especially at high SNR areas.
Comparative analysis of ReliefF-SVM and CFS-SVM for microarray data classification
Authors: Naofal Hakim Mochamad Agusta , Adiwijaya Adiwijaya , Astuti Widi
Published: April 2021

Cancer is one of the main causes of death in the world where the World Health Organization (WHO) recognized cancer as among the top causes of death in 2018. Thus, detecting cancer symptoms is paramount in order to cure and subsequently reduce the casualties due to cancer disease. Many studies have been developed data mining approaches to detect symptoms of cancer through a classifying human gene data expression. One popular approach is using microarray data based on DNA. However, DNA microarray data has many dimensions that can have a detrimental effect on the accuracy of classification. Therefore, before performing classification, a feature selection technique must be used to eliminate features that do not have important information to support the classification process. The feature selection techniques used were ReliefF and correlation-based feature selection (CFS) and a classification technique used in this study is support vector machine (SVM). Several testing schemes were applied in this analysis to compare the performance of ReliefF and CFS with SVM. It showed that the ReliefF outperformed compared with CFS as microarray data classification approach.
Potential key challenges for terahertz communication systems
Authors: Solyman Ahmad A. A. , Elhaty Ismail A.
Published: April 2021

The vision of 6G communications is an improved performance of the data rate and latency limitations and permit ubiquitous connectivity. In addition, 6G communications will adopt a novel strategy. Terahertz (THz) waves will characterize 6G networks, due to 6G will integrate terrestrial wireless mobile communication, geostationary and medium and low orbit satellite communication and short distance direct communication technologies, as well as integrate communication, computing, and navigation. This study discusses the key challenges of THz waves, including path losses which is considered the main challenge; transceiver architectures and THz signal generators; environment of THz with network architecture and 3D communications; finally, Safety and health issues.
Association rule hiding using integer linear programming
Authors: B. Suma , G. Shobha
Published: April 2021

Privacy preserving data mining has become the focus of attention of government statistical agencies and database security research community who are concerned with preventing privacy disclosure during data mining. Repositories of large datasets include sensitive rules that need to be concealed from unauthorized access. Hence, association rule hiding emerged as one of the powerful techniques for hiding sensitive knowledge that exists in data before it is published. In this paper, we present a constraint-based optimization approach for hiding a set of sensitive association rules, using a well-structured integer linear program formulation. The proposed approach reduces the database sanitization problem to an instance of the integer linear programming problem. The solution of the integer linear program determines the transactions that need to be sanitized in order to conceal the sensitive rules while minimizing the impact of sanitization on the non-sensitive rules. We also present a heuristic sanitization algorithm that performs hiding by reducing the support or the confidence of the sensitive rules. The results of the experimental evaluation of the proposed approach on real-life datasets indicate the promising performance of the approach in terms of side effects on the original database.
Robotic hex-nut sorting system with deep learning
Authors: Almanza Cristian , Baquero Javier Martínez , Jiménez-Moreno Robinson
Published: April 2021

This article exposes the design and implementation of an automation system based on a robotic arm for hex-nut classification, using pattern recognition and image processing.  The robotic arm work based on three servo motors and an electromagnetic end effector. The pattern recognition implemented allows classifying three different types of hex-nut through deep learning algorithms based on convolutional neural network architectures. The proposed methodology exposes four phases: the first is the design, implementation, and control of a robotic arm. The second is the capture, classification, and image treatment; the third allows gripping the nut through the robot’s inverse kinematic. The final phase is the re-localization of the hex-nut in the respective container. The automation system successfully classifies all the types of hex-nuts, where the convolutional network used is an efficient and recent pattern recognition method, with an accuracy of 100% in 150 iterations. This development allows for obtaining a novel algorithm for robotic applications in hex-nut sorting.