bluuebunny/crossref_metadata_2025 huggingface dataset:
Aerosol measurement identifies SARS-CoV 2 PCR positive adults compared with healthy controls
Authors: Gutmann Desireé , Scheuch Gerhard , Lehmkühler Timon , Herrlich Laura-Sabine , Hutter Martin , Stephan Christoph , Vehreschild Maria , Khodamoradi Yascha , Gossmann Ann-Kathrin , King Florian , Weis Frederik , Weiss Maximilian , Rabenau Holger F , Graf Juergen , Donath Helena , Schubert Ralf , Zielen Stefan
Published: January 2022

Background

SARS-CoV-2 is spread primarily through droplets and aerosols. Exhaled aerosols are generated in the lung periphery by ‘reopening of collapsed airways’. Aerosol measuring may detect highly contagious individuals (“super spreaders or super-emitters”) and discriminate between SARS-CoV-2 infected and non-infected individuals. This is the first study comparing exhaled aerosols in SARS-CoV-2 infected individuals and healthy controls.

Design

A prospective observational cohort study in 288 adults, comprising 64 patients testing positive by SARS CoV-2 PCR before enrollment, and 224 healthy adults testing negative (matched control sample) at the University Hospital Frankfurt, Germany, from February to June 2021. Study objective was to evaluate the concentration of exhaled aerosols during physiologic breathing in SARS-CoV-2 PCR-positive and -negative subjects. Secondary outcome measures included correlation of aerosol concentration to SARS-CoV-2 PCR results, change in aerosol concentration due to confounders, and correlation between clinical symptoms and aerosol.

Results

There was a highly significant difference in respiratory aerosol concentrations between SARS-CoV-2 PCR-positive (median 1490.5/L) and -negative subjects (median 252.0/L; p<0.0001). There were no significant differences due to age, sex, smoking status, or body mass index. ROC analysis showed an AUC of 0.8918.

Conclusions

Measurements of respiratory aerosols were significantly elevated in SARS-CoV-2 positive individuals and may become a helpful tool in detecting highly infectious individuals via a noninvasive breath test.

Clinical Trial Number

ClinicalTrials.gov Identifier: NCT04739020.

Summary of the main point

In this prospective, comparative cohort study, higher numbers of exhaled respiratory aerosols correlate with a positive PCR test for SARS-CoV-2. Measurement of exhaled aerosols may become a helpful tool in detecting contagious individuals via a readily available breath test.
IL-21 has a critical role in establishing germinal centers by amplifying early B cell proliferation
Authors: Dvorscek Alexandra R. , McKenzie Craig I. , Robinson Marcus J. , Ding Zhoujie , Pitt Catherine , O’Donnell Kristy , Zotos Dimitra , Brink Robert , Tarlinton David M. , Quast Isaak
Published: January 2022

The proliferation and differentiation of antigen-specific B cells, including the generation of germinal centers (GC), are prerequisites for long-lasting, high-affinity antibody-mediated immune protection. Affinity for antigen determines B cell recruitment, proliferation, differentiation and competitiveness in the response, largely through determining access to T cell help. However, how T cell derived signals contribute to these outcomes is incompletely understood. Here we report how the signature cytokine of follicular helper T cells, IL-21, acts as a key regulator of the initial B cell response. By activating AKT and S6, IL-21 accelerates cell cycle progression and the rate of cycle entry of B cells, increasing their contribution to the ensuing GC. This effect occurs over a wide range of initial B cell receptor affinities and the resultant increased proliferation can explain the IL-21-mediated promotion of plasma cell differentiation. Collectively, our data establish that IL-21 acts from the outset of a T cell dependent immune response to increase cell cycle progression and fuel cyclic re-entry of B cells thereby regulating the initial GC size and early plasma cell output.

The cytokine IL-21 is a regulator of B cell responses, increasing antibody quantity and quality. Here, we report that during germinal center initiation, IL-21 acts to increase the response magnitude by accelerating cell cycle speed and rate of entry.
Literary festivals: insights from Ireland
Authors: McGuckin Mary
Published: January 2022

Purpose

The purpose of this paper is to explore literary festivals in Ireland and gain an understanding of the vision and strategic approaches of the stakeholders involved in their development and management.

Design/methodology/approach

This qualitative research study explores literary festivals in terms of how these are managed and developed, as well as the experiences offered, from a supply-side perspective. The research and data collection instruments include bibliographic research and a series of in-depth interviews.

Findings

The strategic vision and approaches of the founders and directors are critical to the success of literary festivals. The findings of this study provide insights into the stages of festival professionalization, as it explores the development and management of six literary festivals in Ireland.

Research limitations/implications

This study is essentially exploratory in nature. This topic is under-represented in the literature and there is potential to extend this research into a more extensive study of literary festivals from the perspective of key stakeholders. This study was limited by the challenges and uncertainty caused by the COVID-19 pandemic and its impact on the festival and events industry.

Practical implications

Against a backdrop of increasing numbers and popularity of literary festivals and related events in Ireland, this study could influence the development and promotion of this sector. Furthermore, the findings identify strategies adopted by festival founders and managers, and this is likely to be of interest to stakeholders at national and international levels.

Originality/value

Even though literary festivals have proliferated in Ireland over the past 20 years, there is a dearth of academic research in this area. To the best of the author’s knowledge, this is the first study exploring a range of literary festivals in Ireland. The research focuses on literary festivals from a “supply” rather than “demand” perspective. Moreover, it discusses the evolution and development of literary festivals as well as the vision of the key stakeholders involved in their management.
Large mammalian herbivores modulate plant growth form diversity in a tropical rainforest
Authors: Souza Yuri , Villar Nacho , Zipparro Valesca , Nazareth Sérgio , Galetti Mauro
Published: January 2022

The world’s terrestrial biomes are broadly classified according to the dominant plant growth forms that define ecosystem structure and processes. Although the abundance and distribution of different plant growth forms can be strongly determined by factors such as climate and soil composition, large mammalian herbivores have a strong impact on plant communities, thus defaunation (the local or functional extinction of large animals) has the potential to alter the compositional structure of plant growth forms in natural ecosystems.

Tropical rainforests sustain a high diversity of growth forms, including trees, palms, lianas, shrubs, herbs and bamboos, all of which play important ecosystem functions. Here, we experimentally evaluate how large mammalian herbivores affect the dominance, diversity and coexistence of these major tropical forest plant growth forms, by monitoring communities of saplings on the understorey in 43 paired exclusion plots in a long‐term replicated exclusion experiment in the understorey of the Atlantic forest of Brazil.

Over the course of 10 years large herbivore exclusion decreased diversity among growth forms, increased the absolute abundance of palms and trees (22% and 38% respectively) and increased the diversity of species within these two groups, to the detriment of other growth forms. Furthermore, all pairwise relationships between growth forms were positive on plots where herbivores had access, whereas several strong negative relationships emerged in plots where herbivores were excluded. This occurred despite strong background directional temporal trends affecting plant communities in both experimental treatments across the region.

Synthesis. Our work indicates that the defaunation alters growth form dominance by favouring palms and trees while eroding diversity among growth forms and coexistence on a temporal scale. Large herbivore mammals promote diversity among growth forms, preventing the hyper‐dominance of trees and palms, yet without supressing the diversity of species within growth forms. We argue that large herbivore mammals affect growth forms through several non‐mutually exclusive mechanisms, including herbivory, seed dispersal and physical disturbance, as well as differential effects linked to the morphological and physiological adaptations of growth forms. We conclude that defaunation might lead to profound impacts on important ecosystem functions underpinned by growth form diversity, and result in vertical and horizontal structural simplification of tropical rainforests.
Teaching and learning for life skills development: Insights from Rwanda’s 12+ programme for adolescent girls
Authors: D’Angelo Sophia , Marcus Rachel , Ngabonzima Ernest
Published: January 2022

Motivation

The development of life skills has been increasingly recognized in formal and non‐formal education programmes as critical to enabling young people to flourish in personal relationships, the workplace, and wider society. Recent competency‐based curricular reform reflects a growing consensus on the importance of developing a combination of socioemotional, cognitive, and practical skills to overcome contemporary social, environmental, and economic global challenges. Yet there is limited research examining the pedagogical practices that lead to the effective development of such skills.

Purpose

This article seeks to fill that gap by drawing on lessons from Rwanda’s 12+ programme, a non‐formal life skills programme for adolescent girls. Examining potential links between pedagogical practices and the programme’s impacts on adolescent girl participants, it enquires into lessons that can be learnt for both formal and non‐formal schooling.

Methods and approach

Insights from focus groups and interviews with 12+ graduates (ages 15–17) and mentors were triangulated with analysis of project documentation including teaching and learning materials.

Findings

Five insights are highlighted: structured teaching and learning materials and scaffolded support for mentors; the use of dialogic teaching; experiential learning opportunities; the importance of safe spaces and trusting relationships; and the engagement of mentors as role models. These combined ingredients of effective life skills programming were perceived to have led to the development of adolescent girls' skills, knowledge, and attitudes, including confidence, voice and agency, financial literacy, self‐efficacy, and self‐care.

Policy implications

Teacher education and ongoing professional development should focus on strengthening teachers' capacity to use learner‐centred, interactive methods, and to foster positive social relationships with and among learners. Sharing of materials and approaches between non‐formal programmes and the formal education system should be encouraged.
Characterization, identification and virulence of Metarhizium species from Cuba to control the sweet potato weevil, Cylas formicarius Fabricius (Coleoptera: Brentidae)
Authors: Baró Yamilé , Schuster Christina , Gato Yohana , Márquez María Elena , Leclerque Andreas
Published: January 2022

Aims

Entomopathogenic Metarhizium fungi are widely recognized for their biological control potential. In Cuba, several fungus-based bio-insecticides have been developed and are produced as part of integrated pest management (IPM) programmes for economically relevant agricultural pests. Screening of fungal isolates from the INISAV strain collection was used for the development of bio-insecticides against important pest insects as, for example the sweet potato weevil, Cylas formicarius.

Methods and results

Six fungal isolates from Cuba were microscopically, morphologically and molecular-taxonomically characterized using marker sequences ef1a, rpb1 and rpb2, and the 5TEF region of the ef1a gene. Five isolates were assigned to the species Metarhizium anisopliae sensu stricto and one isolate to Metarhizium robertsii. The pathogenic potential was evaluated against adults of C. formicarius, and growth and conidial production on different nutritional media were determined. Metarhizium anisopliae strain LBM-267 displayed pronounced virulence against the sweet potato weevil and abundant conidia production on several culture media.

Conclusions

Entomopathogenic fungal isolates from Cuba were assigned to the taxonomic species M. anisopliae sensu stricto and M. robertsii. Virulence assessment with respect to C. formicarius led to the identification of two M. anisopliae isolates holding biocontrol potential. Isolate LBM-11 has previously been developed into the bio-insecticide METASAVE-11 that is widely used to control several species of plant pathogenic weevils, Lepidoptera and thrips in Cuba. Isolate LBM-267 has not been employed previously but is as virulent against C. formicarius as LBM-11; its growth and conidial production capacities on different nutritional media will likely facilitate economically feasible bio-insecticide development.

Significance and Impact of the Study

Metarhizium anisopliae isolate LBM-267 has been selected as a promising candidate for biocontrol of the sweet potato weevil, an economically important agricultural pest in Cuba, and for further R&D activities within the framework of the Biological Control Program of Cuba.
Exploring the therapeutic potential of staphylococcal phage formulations: Current challenges and applications in phage therapy
Authors: Khullar Lavanya , Harjai Kusum , Chhibber Sanjay
Published: January 2022

Unconstrained consumption of antibiotics throughout the expanse of the 21st century has resulted in increased antimicrobial resistance (AMR) among bacterial pathogens, a transpiring predicament affecting the public healthcare sector. The upsurge of multidrug-resistant pathogens, including Staphylococcus aureus, synchronously with the breakdown of the conventional antibiotic pipeline has led to the exploration of alternate strategies. Phage therapy applications have thus gained immense prominence among the scientific community to conquer this notorious pathogen associated with wide-ranging clinical manifestations, especially in immunosuppressed individuals. In this direction, a plethora of phage formulations like topical solutions, medicated dressings impregnated with phages, liposomal entrapments, etc., have been considered as an effective and upcoming strategy. Owing to the synergistic effect of phages with other antibacterial agents, they can be easily exploited for biomedical application. This review primarily focuses on the therapeutic implications of S. aureus phages in the biotechnological and medical arena. Through this review article, we have also discussed the current status and the incurring challenges in phage therapy.
The Automated Test Assembly and Routing Rule for Multistage Adaptive Testing with Multidimensional Item Response Theory
Authors: Xu Lingling , Wang Shiyu , Cai Yan , Tu Dongbo
Published: January 2022

Designing a multidimensional adaptive test (M‐MST) based on a multidimensional item response theory (MIRT) model is critical to make full use of the advantages of both MST and MIRT in implementing multidimensional assessments. This study proposed two types of automated test assembly (ATA) algorithms and one set of routing rules that can facilitate the development of an M‐MST. Different M‐MST designs were developed based on the proposed ATA algorithms and routing rules and were evaluated through two sets of simulation studies. Study 1 used simulated item banks and considered a variety of testing factors, and results from which can inform us the theoretical performance of the proposed M‐MST designs. Study 2 was designed based on a real multidimensional assessment. In addition, a MCAT was simulated as a baseline design to demonstrate the advantage of the proposed M‐MST design in each study. Our simulation results indicate that the proposed ATA algorithms and routing rule can generate M‐MSTs with a good‐quality control and the same or even better ability estimation results than the MCAT given the same condition. This demonstrates the advantage of using M‐MST for multidimensional assessment especially for the one that needs to satisfy many nonstatistical constraints.
A theory of (de)centralization
Authors: Klibanoff Peter , Poitevin Michel
Published: January 2022

This paper compares the efficacy of a centralized and a decentralized rights structure in determining the size of an externality‐generating project. Consider a central authority and two localities. One locality can operate a variable‐size project which produces an externality that affects the other locality. Each locality may have some private information concerning its own net benefit from the project. Under centralization, localities are vertically integrated with a benevolent central authority who effectively possesses all property rights. Under decentralization, localities are separate legal entities (endowed with property rights) who bargain to determine the project size. We examine the performance of these two regimes and show how one or the other may dominate depending on the distributions of private and external benefits from the project.
Characterization of seven new HLA alleles, HLA‐A*01:407, ‐A*01:408, ‐A*03:434, ‐B*40:508N, ‐B*40:511N, ‐DRB1*04:336, and ‐DRB1*11:297Q
Authors: Loginova Maria , Smirnova Daria , Druzhinina Svetlana , Paramonov Igor , Zarubin Maksim
Published: January 2022

Seven novel HLA alleles, HLA‐A*01:407, ‐A*01:408, ‐A*03:434, ‐B*40:508N, ‐B*40:511N, ‐DRB1*04:336, and ‐DRB1*11:297Q in individuals from Irkutsk Region.
Forecasting the Coffee Consumption Demand in Vietnam Based on Grey Forecasting Model
Authors: Nguyen Ngoc Thang , Phan Van-Thanh , Nguyen Van Ðat , Le Thanh Ha , Pham Thao Vy
Published: January 2022

Forecasting the domestic coffee consumption demand is important for policy planning and making the right decisions. Thus, in this study, we try to find out the most suitable model among three proposed models (GM (1,1), DGM (1,1) and Grey Verhulst model (GVM)) for predicting the amount of domestic coffee consumption in Vietnam in the future. Yearly data of coffee consumption from 2010–2020 are used in this research. The experimental results indicated that the GM (1,1) is the most accurate model selected in this study with the lowest average value of [Formula: see text]%. So, the GM (1,1) model is strongly suggested in the analysis of coffee consumption demand in Vietnam. Finding the right tool will help managers make right decisions easily for sustainable development of the coffee industry in Vietnam in the future.
Digitizing MEXART — System Overview and Verification
Authors: Magro A. , Borg J. , Chiello R. , Cutajar D. , Zarb-Adami K. , Gonzalez-Esparza J. A. , Andrade E. , Aguilar-Rodriguez E. , Mejia-Ambriz J. C. , Villanueva P.
Published: January 2022

The Mexican Array Radio Telescope (MEXART), located in the state of Michoacan in Mexico, has been operating in an analog fashion, utilizing a Butler Matrix to generate fixed beams on the sky, since its inception. Calibrating this instrument has proved difficult, leading to loss in sensitivity. It was also a rigid setup, requiring manual intervention and tuning for different observation requirements. The Radio Frequency (RF) system has now been replaced with a digital one. This digital backend is a hybrid system utilizing both FPGA-based technology and GPU acceleration, and is capable of automatically calibrating the different rows of the array, as well as generating a configurable number of frequency-domain synthesized beams to towards selected locations on the sky. A monitoring and control system, together with a full-featured web-based front-end, has also been developed, greatly simplifying the interaction with the instrument. This paper presents the design, implementation and deployment of the new digital backend, including preliminary analysis of system performance and stability.
6G and the Internet of Things: Topic Analysis
Authors: Kim Jinho , Park Kayoung
Published: January 2022

Since the commercialization of the 5G network, the number of research papers related to 6G IoT has increased rapidly due to researchers’ growing interest in next-generation technologies, 6G networks, and IoT technology. Due to the rapidly growing number of research papers in this area, it is difficult to grasp the overall research directions and topics. Therefore, this study has suggested a method of efficiently identifying the topics of 6G-related papers using data mining and presents the topics discovered through this technique. As a result, we extracted nine topics from 623 papers on 6G IoT using the LDA model technique, and we described the studies related to each topic.
Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm
Authors: Yang Fen
Published: January 2022

With the research of machine learning technology and big data intelligent processing technology in engineering application becoming more and more mature, people gradually combine machine learning technology and big data intelligent processing technology. Aiming at the problem of innovative employment in colleges and universities, this paper proposes a dynamic decision tree algorithm based on these two technologies and constructs a dynamic model of graduates’ behavior. Through the analysis of dynamic decision tree algorithm, a big data analysis system is formed. Finally, simulation experiments verify whether the dynamic model can correctly reflect the behavior of college graduates. The results show that the big data integration system based on big data and dynamic decision tree algorithm has high adaptability. Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. The dynamic decision tree algorithm of college employment proposed in this paper has good predictability and provides a certain theoretical reference for college graduates’ entrepreneurship.
An Individual Driving Behavior Portrait Approach for Professional Driver of HDVs with Naturalistic Driving Data
Authors: He Yi , Yang Shuo , Zhou Xiao , Lu Xiao-Yun
Published: January 2022

More than 50% major road accidents are caused by risk driving behaviors from professional drivers of Heavy Duty Vehicles (HDVs). The quantitative estimation of driving performance and driving behaviors portrait for professional drivers is helpful to measure the driver’s driving risk and inherent driving style. Previous studies have attempted to evaluate risk driving behavior, but most of them rely on high-demand vehicle and driving data. However, few studies can dig into the causes and correlations behind individual driving behavior and quantify the driving behaviors portrait for professional driver based on long-term naturalistic driving. In this study, the data is from On-Board Unit (OBU) devices mounted in the HDVs in China. Based on the driving behavior pattern diagram and the frequency and ranking of drivers’ typical driving patterns, a driving behavior portrait approach is proposed by comprehensively considering the vehicle safety, driving comfort, and fuel economy indicators. The similarities and differences of different drivers’ driving behaviors are quantitatively analyzed. The high precision and sampling frequency data from vehicles are used to verify the proposed approach. The results demonstrated that the driving behavior portrait approach can digitally describe the individual driving behaviors styles and identify the potential driving behaviors with long-term naturalistic driving data. The development of this approach can help quantitatively evaluate the individual characteristic of risk driving behaviors to prevent road accidents.
Renovascular Hypertension with Superimposed Aortic Arch Baroreceptor Failure: Case Report and Review of Literature
Authors: Daoud Amro , Mustafa Bisher , Alsaid Hamza , Khitan Zeid
Published: January 2022

Background. Atherosclerotic renal artery diseases are among the most common causes of secondary hypertension. Baroreceptors, as carotid and aortic, are important regulatory mechanisms of blood pressure; their disruption can lead to labile blood pressure due to sympathetic overactivity: an entity called neurogenic hypertension. A disease such as aortic dissection can lead to a challenging combined etiology of secondary hypertension. It can affect both or one of the renal arteries leading to a renovascular pathology that can cause hypertension through RAAS activation. Also, surgical repair of the dissected aortic arch can disrupt baroreceptors leading to neurogenic hypertension. Case Report. We report a case of an 83-year-old female patient investigated for recurrent episodes of aphasia. She has a history of hypertension and coronary artery disease. Surgical history is significant for aortic valve replacement complicated by type A aortic dissection requiring surgical repair. Following surgery, the patient developed difficult-to-control and labile blood pressure. Workup included a CT angiogram of the abdominal aorta that showed an infrarenal dominant abdominal aortic aneurysm with juxtarenal aortic dissection; these findings were similar to previous findings. A diagnosis of aortic baroreceptor failure following aortic dissection repair was established, which lead to labile hypertension with superimposed renovascular pathology due to unilateral compromised renal artery blood flow following aortic dissection and thrombosis. Conclusions. This report highlights the importance of accurate diagnosis of secondary hypertension and its underlying mechanisms, as this has a huge impact on the choice of therapy to avoid undertreatment or overtreatment of hypertension.
Long Noncoding RNA Mediated Regulation in Human Embryogenesis, Pluripotency, and Reproduction
Authors: Liu Lei , Fang Fang
Published: January 2022

Long noncoding RNAs (lncRNAs), a class of noncoding RNAs with more than 200 bp in length, are produced by pervasive transcription in mammalian genomes and regulate gene expression through various action mechanisms. Accumulating data indicate that lncRNAs mediate essential biological functions in human development, including early embryogenesis, induction of pluripotency, and germ cell development. Comprehensive analysis of sequencing data highlights that lncRNAs are expressed in a stage-specific and human/primate-specific pattern during early human development. They contribute to cell fate determination through interacting with almost all classes of cellular biomolecules, including proteins, DNA, mRNAs, and microRNAs. Furthermore, the expression of a few of lncRNAs is highly associated with the pathogenesis and progression of many reproductive diseases, suggesting that they could serve as candidate biomarkers for diagnosis or novel targets for treatment. Here, we review research on lncRNAs and their roles in embryogenesis, pluripotency, and reproduction. We aim to identify the underlying molecular mechanisms essential for human development and provide novel insight into the causes and treatments of human reproductive diseases.
Dedifferentiated Low-Grade Central Osteosarcoma of the Mandible
Authors: Yamagata Kenji , Ishibashi-Kanno Naomi , Matsuoka Ryota , Uchida Fumihiko , Fukuzawa Satoshi , Bukawa Hiroki
Published: January 2022

We present the first, to our knowledge, case of a dedifferentiated low-grade central osteosarcoma (LCOS) of the mandible. A 48-year-old Japanese woman underwent enucleation under general anesthesia after a diagnosis of ossifying fibroma. At the second recurrence, the pathological diagnosis after biopsy was of sarcoma with MDM2(+) and CDK4(+) immunohistochemical staining results. Hemimandibulotomy, supraomohyoid neck dissection, and free-flap reconstruction with a rectus abdominal flap were performed. A retrospective reevaluation of the first specimen with additional immunohistochemical staining for MDM2 and CDK4 yielded a final diagnosis of dedifferentiated LCOS. The patient showed no recurrence or lung metastasis 3 years after the final surgery.
Design and analysis of frequency reconfigurable antenna for global positioning system applications
Authors: Jazea Najim Abdallah , Jassim Ali Khalid , Hassan Alaa Kareem
Published: January 2022

A compact frequency reconfigurable antenna is designed and analyzed in this paper to operate with global positioning system (GPS) and worldwide interoperability for microwave access (WiMAX) applications. The designed antenna is printed on flame resistant 4 (FR4) epoxy substrate with relative permittivity is 4.3, loss tangent of 0.03 and overall substrate with ground (GND) plane dimensions of (54.6x54.6x1.6) mm3 and patch dimensions of (45x45) mm2. The antenna is designed and optimized using computer simulation technology (CST) package through series of parametric studies in order to cover the GPS, WiMAX bands with resonant frequency of 1.229 GHz, 1.575 GHz, and 3.34 GHz. Two triangular slots at the patch sides and single elliptical slot at the middle are etched for the best antenna performance. The designed antenna performs frequency re-configurability by using PIN diode switch at the inset feed to change the operating frequencies from double band operation at (1.575 and 3.34) GHz to single band at 1.229 GHz under S11 ≤-10 dB. The proposed antenna produces accepted simulation results with voltage standing wave ratio (VSWR), maximum radiation efficiency and gain of less than 2.76% and 7.035 dBi respectively.
A visual framework for software requirements traceability
Authors: Madaki Abdulkadir Ahmad , Wan Zainon Wan Mohd Nazmee
Published: January 2022

Requirement traceability supports several activities of software development processes such as impact analysis, requirement changes, maintenance, verification, and validation of a software system. For its effective use in those activities, the graphical representation of traceability data plays an important role. However, several traceability tools lack an excellent visual representation to present these type of data. Therefore, this paper presents a visual framework which has been designed and proposed as a prototype tool that can visualize traceability data. The framework applies data visualization techniques to represent requirements and its artefacts relationships as colour-coded symbols on a node-link diagram; users can traverse the graph with an impact analysis method to understand data and make decisions. The evaluation result shows that the proposed tool is useful and easy enough in terms of improving user interaction and to better understand requirement traceability data.
Review on techniques of automatic solid waste separation in domestic applications
Authors: Alcaraz-Londoño Luisa María , Ortiz-Clavijo Luis Felipe , Gallego Duque Carlos Julián , Gutiérrez Betancur Sergio Armando
Published: January 2022

The accelerated modern day urban development is accompanied by an increasing production of solid waste. While managing solid waste on an industrial scale presents different technological challenges, managing household waste requires decentralized solutions dealing with the associated logistic and technical difficulties. In this review, we identify the research trends on household waste recycling by providing a brief description of the main technologies, and the traditional formats commonly used for solid waste (SW) separation. We identify two main threads: the SW management systems within a smart city framework and the design of domestic waste classification systems based on intelligent mechanisms tailored to user psychology. Among the main conclusions, we verify a growing interest in the subject of SW separation in domestic applications, mainly through solutions based on automation and internet of things (IoT). Also, we detected a increasing interest in the analysis of psychological aspects and in citizen education in relation to the importance of recycling, since without this notion the success of proposed solutions might be limited.
Information technology governance: an analysis of the approach in Ecuador
Authors: Molina Andrés Gavilanes- , Rodríguez Vicente Merchán-
Published: January 2022

This work aims to show the Ecuadorian IT governance reality using descriptive research to analyze the approach of IT decisions. Indeed, one hundred and one private and governmental organizations were surveyed to examine their IT governance approach through a decision-making matrix model of responsibilities. The purpose is to distinguish IT governance perspectives and archetypes for IT decision-making, so that we collect relevant information about decision-making of executives, IT executives, C-level, and business unit leader business in a developing economy context. The survey results are conclusive; business monarchy is the centralized approach for decision-making in Ecuador. For instance, IT governance in Ecuador is different from other Latin American nations in terms of digital culture, maturity, and effectiveness. On the other hand, this work encourages practitioners and scholars to increase the research scope to create, adopt, or adapt IT governance decision-making models for low-income countries. This is another step on the ongoing discussion in the extant IT governance literature, rather than as a ﬁnal answer. Finally, future work will analyze and contrast the past normality with the post-pandemic period in Ecuador. Hence, using a survey on Ecuadorian IT governance structures, practices and behaviors will show the IT governance changes, perceptions, and trends.
Applying of (SOM, HAC, and RBF) algorithms for data aggregation in wireless sensors networks
Authors: Abdalkafor Ahmed Subhi , Aliesawi Salah A.
Published: January 2022

Wireless sensor network (WSN) is one of the most promising technologies due to its size, cost-effective nature, and its ability to easily deploy in the target environment, as well as for its entry into many sensitive applications. However, making the most of the potential of this network is very difficult due to many issues, including the data received from the sensor nodes contains a huge amount of data redundant that negatively affects the overall network performance. Recent years have witnessed an increasing interest in data aggregation technology intending to eliminate redundant data from neighboring sensor nodes before transferring to the base station, thus improve performance efficiency and increasing the wireless sensor networks lifespan. This paper focused on applying three intelligent algorithms (SOM, HAC, and RBF) and describing the impact of data aggregation strategy on WSNs through the results obtained. As well as, an accurate description of the literature that applied these algorithms. A Competitive classification accuracy has been achieved when the proposed work is implemented and tested via the intel berkeley research lab dataset.
Method for describing signal conversion processes in analog electronic systems
Authors: Al-Suod Mahmoud , Awwad Abdullah Eial , Al-Quteimat Alaa , Ushkarenko Oleksandr
Published: January 2022

One of the main tasks of information technology is to improve existing and develop new methods for formal recording of various dynamic logical operations of analog and digital signal conversion in electronic control systems, acquisition, and processing of information. The stage of formal recording of any signal transformation process must be presented in the form of analytic symbols, the sequence of which must form a fully functional mathematical model. The improved method of the signals conversion processes description based on a representation of the mathematical models of the electronic circuits’ components in the grapho-analytical form with the increased information content allows integrating the developed models of electronic circuit elements with object-oriented programming language in the form of functional structures. It opens the way to perform parametric analysis of circuits and other tasks, related to the modeling of electronic systems.
Early faults diagnosis and severity assessment of rolling element bearings on wireless signal transfer
Authors: Mustafa Ghulam , Khushnood Shahab
Published: January 2022

Machine condition monitoring in remote locations and harsh environment where network infrastructure is not feasible, or hardwired network connectivity is not possible, wireless communications provides an alternative which also offer installation cost savings, improve reliability and quicker deployment. This paper describes the implementation of wireless sensor network (WSN) for early fault diagnosis of rolling element bearings based on signal autocorrelation technique. A low-power 2.4 GHz wireless HART transceiver, a low-cost wireless vibration transmitter, 26.76 mv/g accelerometers and a 1420 wireless gateway with AMS software was implemented. The research describes the methodology of acquiring peak values data in high frequency region. The noise was averaged out by applying four-time averaging and natural frequencies or fault frequencies of bearing elements was captured. The experimental results show that the signal autocorrelation algorithm can successfully diagnose the roller bearing faults at early stage on wireless signal transfer. As the raw data was processed before wireless transmission on analyzing unit and spectrum was transferred in JPG format on display unit, minimum power consumption has been noted. The technique provided a better alternative of wired system for real time condition monitoring of roller bearings in rotating equipment installed in remote area.
Labeling of an intra-class variation object in deep learning classification
Authors: Widyastuti Santiary Putri Alit , Swardika I Ketut , Irawan Purnama Ida Bagus , Raka Ardana I Wayan , Kusuma Wardana I Nyoman , Cahya Dewi Dewa Ayu Indah
Published: January 2022

Machine orientation learning had demonstrated that deep learning (DL)-convolutional neural networks (CNNs) were robust image classifiers with significant accuracy. Although to been functional, DL scope classification as tight, well-defined as possible uses a 2-class object, for instance, cats and dogs. The DL classification faced many challenges, e.g., variation factors, the intra-class variation. This nature is presented in every object, its diversity of an object. The label was an exact given name of an intra-class variation object. Unfortunately, not every object had a specific name, in exceptionally high similarity inside the category. This paper explored those problems in flower plants’ taxonomy naming. In supervised learned of DL, image datasets musted labeled with a meaningful word or phrase that humans are familiar with, a taxonomy naming. Labeled with visual feature extraction brought a fully automatic classification. Flower Plumeria L labeling extracted from perspective dimension scale of petal flower which automatically obtained by contour detection, and peaks of blue green red (BGR) histogram channels from bins histogram after object masked. Dataset collected on photography workbench equipped with webcam and ring light. Results showed labels for intra-class variation of Plumeria L in form of dimension-scale and BGR-peaks. The result of this study presented a novelty in building datasets for intra-class variation for the DL classification.
Optimal economic dispatch using particle swarm optimization in Sulselrabar system
Authors: Marhatang Marhatang , Djalal Muhammad Ruswandi
Published: January 2022

In this study, a particle swarm optimization (PSO) is proposed to optimize the cost of generating thermal plants in the South Sulawesi system. The study was con ducted by analyzing several methods using the lagrange and ant colony optimization (ACO). PSO algorithm converges on the 11th iteration algorithm with the lowest generation cost obtained, which is Rp129687962.17/hour. While the ACO algorithm converges on the 34th iteration with a generation cost of Rp131,473,269.39/hour. The results of optimization using PSO produce a total thermal power of 400.75 MW and losses of 26.15 MW. The PSO method is able to reduce the cost of generating the South Sulawesi system by Rp11,118,312.07/hour or 7.9%. While using the ACO method generates a generation cost of Rp131,473,269.39/hour to generate power of 400,812 MW with losses of 26,219 MW. The ACO method is able to reduce the cost of generating the South Sulawesi system by Rp9,333,004.9/hour or 6.62%. PSO algorithm provides the lowest cost calculation of generator compared with conventional methods and ACO smart methods. This is also shown in the calculation process, the PSO method completes calculations faster than the ACO method.
Implementation of FaceNet and support vector machine in a real-time web-based timekeeping application
Authors: Vu Ly Quang , Trieu Phan Thanh , Nguyen Hoang-Sy
Published: January 2022

This paper presents in detail how to build up and implement a real-time web-based face recognition application. The system works so that images of people are recorded and compared with the references on the database. If they match, the information about their presence will be recorded. As for the system architecture, the multi-task cascaded neural network was deployed for face detection. Followingly, for the recognizing tasks, we conducted a study to compare the accuracy level of three different face recognizing methods on three different public datasets by means of both the literature review and our simulation. From the comparison, it can be drawn that the FaceNet algorithm in-used with the support vector machine (SVM) classifier performs the best among others and is the most suitable candidate for the practical deployment. Eventually, the proposed system can deliver a highly satisfactory result, proving its potentials not only for the research but also the commercial purposes.
Urgency and relevance of feminist social work to curb domestic violence amid COVID-19
Authors: Shah Saloome Showkat , Mufeed S A
Published: January 2022

As the world is witnessing unprecedented circumstances and humans are making every possible effort to save their lives and livelihoods from the Coronavirus, unfortunately, there is a segment of the populace that is even more vulnerable. Women are compelled to stay indoors during quarantine, which makes them more exposed to domestic violence from their intimate partners. In these times of emergency, feminist social work is needed more than ever. Therefore, this article highlights the issue of domestic violence women are facing during pandemics around the globe and signifies the relevance of feminist social workers in domestic violence amid COVID-19.
Comparative Analysis of Laboratory and Prototype Models of Pervious Concrete Mixes Containing Reclaimed Asphalt Pavement Aggregates
Authors: Sahdeo Surya Kant , R.N. G.D. Ransinchung , Debbarma Solomon
Published: January 2022

Pervious concrete (PC) is lightweight concrete with higher porosity and permeability than conventional concrete, making it suitable for reducing storm-water runoff from pavements. Incorporating reclaimed asphalt pavement (RAP) aggregates as a replacement for natural aggregates will likely enhance the porosity and permeability of PC pavement mixes. This paper provides a comparative analysis of the influence of RAP in PC pavement mixes when prepared in two different conditions (laboratory and field). To simulate field conditions, a prototype model tank consisting of subgrade and reservoir layers and a PC slab was constructed. Studies showed that the compaction types and efforts affect the RAP-PC prototype slab and require 50% extra cement to achieve the recommended 28-day compressive and flexural strength of PC pavements. The prototype model tank’s surface infiltration (SI) test demonstrated a higher permeability but less density than laboratory-prepared specimens, indicating that the use of binary graded RAP aggregates contributes to a porous network structure, which improves the transport properties of PC pavement mixes. A correlation with a high R2 value between the laboratory and prototype model tank was also established, indicating the coexistence of a relationship between the density and porosity of laboratory and Prototype-PC pavement mixes. Interestingly, it was reported that the use of standard proctor hammer compaction to cast laboratory specimens produced the same effect when the vibratory hammer compacted the RAP-PC prototype for 20 s. It is, therefore, recommended that 25% to 50% of RAP be used as a coarse aggregate replacement to produce PC pavement mixes.
Now and Forever: Creating Knowledge to Honor People
Authors: Lucio-Villegas Emilio
Published: January 2022

After the restoration of democracy in Spain, the victims of the dictatorship were never recognized and the murderers were never judged. Silence was the norm in reference to the Civil War, the dictatorship, and the people who fought for democracy. Only a few civil society organizations and other similar groups tried to reclaim the memory of the victims by looking for their remains in mass graves and ditches and telling a different history than the official one presented in the textbooks. One of these groups is adult learners in the adult education school M. R. in Seville, Spain. They try, from the stories of common people, to create new knowledge and to restore the memory of and honor the victims. They are doing this by recovering oral testimonies and biographies and publishing them as a collective history. In the article, I will present the research conducted by these adult learners. It can be considered participatory research because it enables individuals to restore their memories, to create new knowledge confronting the official narrative, and, through publications and public speeches, to disseminate this knowledge and organize community practices honoring the victims.
The application of artificial intelligence in the sonography profession: Professional and educational considerations
Authors: Edwards Christopher , Chamunyonga Crispen , Searle Benjamin , Reddan Tristan
Published: January 2022

The integration of artificial intelligence (AI) technology within the health industry is increasing. This educational piece discusses the implementation of AI and its impact on sonography. The authors investigate how AI may influence the profession and provide examples of how ultrasound imaging may be enhanced and innovated by integrating AI technology. This article highlights challenges related to the application of AI and provides insight into how they could be addressed. The critical distinction between the role of a sonographer and the reporting specialist in the context of AI is highlighted as a key issue for those developing, researching, and evaluating AI systems. A key recommendation is for the sonography community to address ultrasound education, particularly how AI knowledge could be incorporated into university education. This is an important consideration that should be extended to practising professionals as they may be involved in evaluating the efficiency and methodologies used in new research that may incorporate AI technologies.