bluuebunny/crossref_metadata_2025 huggingface dataset:
Can a constitutional monarch influence democratic preferences? Japanese emperor and the regulation of public expression
Authors: Annaka Susumu , Kato Gento
Published: April 2022

Objective

This study examines whether hereditary constitutional monarchs have any influence on democratic public opinion, focusing on the case of the Japanese emperor.

Methods

A survey experiment on the regulation of public expression. This issue can be framed both as left wing (i.e., the regulation of hate speech) and right wing (i.e., the regulation of publicly funded anti‐nationalistic exhibitions). Taking advantage of the dual nature of the issue, we test the effects of the emperor's endorsement on support for regulation under each ideological frame.

Results

The (former) emperor's endorsement for freedom of expression does have a cross‐cutting effect and decreases support for regulation. This effect is relatively small but statistically significant. Additionally, the findings provide weak evidence for the emperor's own ideological position conditioning his endorsement effect.

Conclusion

Hereditary monarchs do influence democratic public opinion, and their influence can cross‐cut ideology.
Diagnostic accuracy of Abbott Architect Assay as a screening tool for human T‐cell leukaemia virus type‐1 and type‐2 infection in a London teaching hospital with a large solid organ transplant centre
Authors: Lee Nathaniel , Murphy Jamie , Al‐Khudairi Rasheed , Sturdy Ann , Mahungu Tabitha , Haque Tanzina , Griffiths Paul , Tosswill Jennifer , Irish Dianne
Published: April 2022

Aim

In the United Kingdom, organ donors/recipients are screened for evidence of human T‐cell leukaemia virus type‐1 and type‐2 (HTLV‐1/2) infections. Since the United Kingdom is a low prevalence country for HTLV infections, a screening assay with high sensitivity and specificity is required. Samples with repeat reactivity on antibody testing are sent to a reference lab for confirmatory serological and molecular testing. In the case of donor screen, this leads to delays in the release of organs and can result in wastage. We aim to assess whether a signal/cut‐off (S/CO) ratio higher than the manufacturer's recommendation of 1.0 in the Abbott Architect antibody assay is a reliable measure of HTLV‐1/2 infection.

Methods

We conducted a 5 year retrospective analysis of 7245 patients from which 11 766 samples were tested on the Abbott Architect rHTLV I/II assay. Reactive samples (S/CO >1) were referred for confirmatory serological and molecular detection (Western Blot and proviral DNA) at UK Health Security Agency, (formerly PHE, Colindale), the national reference laboratory. Electronic, protected laboratory and hospital patient databases were employed to collate data.

Results

A total of 45 patients had initially reactive samples. 42.2% (n = 19/45) had an S/CO ratio > 20, with HTLV infection confirmed in n = 18/19 and indeterminate confirmatory results in n = 1/19. No samples with an S/CO ratio <4 (48.9%, n = 22/45) or 4–20 (8.9%, n = 4/45) had positive confirmatory results on subsequent confirmatory testing.

Conclusion

Samples with an S/CO >20 likely represent a true HTLV‐1/2 infection. Reactive samples with an S/CO <4 were unlikely to confirm for HTLV infections. Interpretation of these ratios can assist clinicians in the assessment of low reactive samples and reiterates the need for faster access to confirmatory testing.
The endoplasmic reticulum membrane–bending protein RETICULON facilitates chloroplast relocation movement in Marchantia polymorpha
Authors: Ishikawa Kazuya , Konno Ryota , Hirano Satoyuki , Fujii Yuta , Fujiwara Masayuki , Fukao Yoichiro , Kodama Yutaka
Published: April 2022

Plant cells alter the intracellular positions of chloroplasts to ensure efficient photosynthesis, a process controlled by the blue light receptor phototropin. Chloroplasts migrate toward weak light (accumulation response) and move away from excess light (avoidance response). Chloroplasts are encircled by the endoplasmic reticulum (ER), which forms a complex network throughout the cytoplasm. To ensure rapid chloroplast relocation, the ER must alter its structure in conjunction with chloroplast relocation movement, but little is known about the underlying mechanism. Here, we searched for interactors of phototropin in the liverwort Marchantia polymorpha and identified a RETICULON (RTN) family protein; RTN proteins play central roles in ER tubule formation and ER network maintenance by stabilizing the curvature of ER membranes in eukaryotic cells. Marchantia polymorpha RTN1 (MpRTN1) is localized to ER tubules and the rims of ER sheets, which is consistent with the localization of RTNs in other plants and heterotrophs. The Mprtn1 mutant showed an increased ER tubule diameter, pointing to a role for MpRTN1 in ER membrane constriction. Furthermore, Mprtn1 showed a delayed chloroplast avoidance response but a normal chloroplast accumulation response. The live cell imaging of ER dynamics revealed that ER restructuring was impaired in Mprtn1 during the chloroplast avoidance response. These results suggest that during the chloroplast avoidance response, MpRTN1 restructures the ER network and facilitates chloroplast movement via an interaction with phototropin. Our findings provide evidence that plant cells respond to fluctuating environmental conditions by controlling the movements of multiple organelles in a synchronized manner.
Reducing the Search Space for Global Minimum: A Focused Regions Identification Method for Least Squares Parameter Estimation in Nonlinear Models
Authors: Zhang Guanglu , Allaire Douglas , Cagan Jonathan
Published: April 2022

Important for many science and engineering fields, meaningful nonlinear models result from fitting such models to data by estimating the value of each parameter in the model. Since parameters in nonlinear models often characterize a substance or a system (e.g., mass diffusivity), it is critical to find the optimal parameter estimators that minimize or maximize a chosen objective function. In practice, iterative local methods (e.g., Levenberg–Marquardt method) and heuristic methods (e.g., genetic algorithms) are commonly employed for least squares parameter estimation in nonlinear models. However, practitioners are not able to know whether the parameter estimators derived through these methods are the optimal parameter estimators that correspond to the global minimum of the squared error of the fit. In this paper, a focused regions identification method is introduced for least squares parameter estimation in nonlinear models. Using expected fitting accuracy and derivatives of the squared error of the fit, this method rules out the regions in parameter space where the optimal parameter estimators cannot exist. Practitioners are guaranteed to find the optimal parameter estimators through an exhaustive search in the remaining regions (i.e., focused regions). The focused regions identification method is validated through two case studies in which a model based on Newton’s law of cooling and the Michaelis–Menten model are fitted to two experimental data sets, respectively. These case studies show that the focused regions identification method can find the optimal parameter estimators and the corresponding global minimum effectively and efficiently.
The Effect of Inlet Conditions on Turbine Endwall Loss
Authors: Coull John D. , Clark Christopher J.
Published: April 2022

There can be significant variation and uncertainty in the flow conditions entering a blade row. This article explores how this variability can affect endwall loss in axial turbines. A computational study of three cascades with collinear inlet boundary layers is conducted. Endwall loss varies by more than a factor of 3 depending on the inlet conditions. This variation is caused by dissipation of secondary kinetic energy (SKE). The results can be understood by observing that the inlet conditions predominantly control how secondary vorticity is distributed within the blade passage. Modestly thick inlet boundary layers with high shape factor tend to displace vorticity toward the center of the passage. This displacement reduces vorticity cancellation, increasing secondary velocities, and SKE. A general method is formulated to estimate SKE in preliminary design. Optimum aspect ratio is shown to depend on the inlet boundary condition. Strategies to reduce endwall loss and minimize sensitivity to inlet conditions are then highlighted.
Fungal Melanin Biosynthesis Pathway as Source for Fungal Toxins
Authors: Gao Jia , Wenderoth Max , Doppler Maria , Schuhmacher Rainer , Marko Doris , Fischer Reinhard
Published: April 2022

Mycotoxins are a major threat for human health. Food safety control relies on the identification of the toxins or the detection of the expression of the respective genes.
Complete Genome Sequence of Colistin-Resistant,
mcr-10
-Harboring, Enterobacter cloacae Isolate AVS0889, Recovered from River Water in Switzerland
Authors: Biggel Michael , Zurfluh Katrin , Hoehn Sarah , Schmitt Kira , Frei Andrea , Jans Christoph , Stephan Roger
Published: April 2022

Here, we report the complete genome sequence of colistin-resistant
Enterobacter cloacae
sequence type 1 (ST1) isolate AVS0889, which was recovered from a river in Switzerland in 2021. The genome consists of a 4.95-Mbp chromosome and five plasmids, including a large plasmid (90.8 kb) harboring a disrupted
mcr-10
gene.
Plants Play Stronger Effects on Soil Fungal than Bacterial Communities and Co-Occurrence Network Structures in a Subtropical Tree Diversity Experiment
Authors: Gan Huiyun , Li Xingchun , Wang Yonglong , Lü Pengpeng , Ji Niuniu , Yao Hui , Li Shan , Guo Liangdong
Published: April 2022

Increasing biodiversity loss profoundly affects community structure and ecosystem functioning. Therefore, revealing the mechanisms associated with community assembly and co-occurrence network structure of microbes along plant species diversity gradients is very important for understanding biodiversity maintenance and community stability in response to plant diversity loss.
Feeding ecology of the endangered Apennine Yellow-bellied Toad (Bombina pachypus) in central Italy
Authors: de Meis Annagiulia , Bissattini Alessandra Maria , Venchi Alberto , Bologna Marco Alberto , Vignoli Leonardo
Published: April 2022

Anurans are generalist opportunistic consumers, but many species show some degree of diet specialization. Within populations, individuals may specialize in specific dietary resources (individual specialization). Indeed, generalist populations may be composed of individuals using the whole range of available resources or of diverse individuals exploiting specific food items. Based on the niche variation hypothesis (NHV), an increase in population niche width may be related to a higher incidence of individual specialization. We analyzed the feeding ecology of the endangered Apennine Yellow-bellied Toad ( Bombina pachypus (Bonaparte, 1838)) in central Italy. This species showed a generalist feeding strategy, wide trophic niche, high individual generalization, and a predominant use of terrestrial resources. The study species inhabits seasonal habitats determining variation in food availability and diversity, and this may have driven toads to be unselective and consume almost any encountered palatable item. The absence of sexual size dimorphism may explain the absence of trophic differentiation between sexes. The analysis of individual feeding traits revealed a week's degree of individual specialization positively correlated to niche width, partly supporting the NHV. The obtained information can be used for the implementation of effective conservation strategies of locally imperilled species, especially those breeding in temporary ponds.
Finite volume effects in the McLerran–Venugopalan initial condition for the JIMWLK equation
Authors: Korcyl Piotr
Published: April 2022

We revisit the numerical construction of the initial condition for the dipole amplitude from the McLerran–Venugopalan model in the context of the JIMWLK evolution equation. We observe large finite volume effects induced by the Poisson equation formulated on a torus. We show that the situation can be partially cured by introducing an infrared regularization. We propose a procedure which has negligible finite volume corrections. The control of the finite volume and finite lattice spacings effects is crucial when considering the numerical solutions of the JIMWLK evolution equation with the collinear improvement.
Gut Flora Mediates the Rapid Tolerance of Electroacupuncture on Ischemic Stroke by Activating Melatonin Receptor through Regulating Indole-3-Propionic Acid
Authors: Li Shan , Zhao Xiaoyong , Lin Feihong , Ni Xuqing , Liu Xia , Kong Chang , Yao Xinyu , Mo Yunchang , Dai Qinxue , Wang Junlu
Published: April 2022

Electroacupuncture (EA) is commonly used to treat cerebrovascular diseases. This study aimed to clarify the mechanisms of action of treatments of cerebral ischemic stroke from the perspective of gut microecology. We used a mouse model and cell cultures to investigate the effects of EA on the intestinal microflora in mice models of middle cerebral artery occlusion (MCAO) and the mechanisms underlying the antioxidant activities of metabolites. Fecal microbiota transplantation (FMT) was used to validate the roles of gut microbiota. Metabolomic analysis was performed to characterize the metabolic profile differences between the mice in the EA + MCAO and MCAO groups. Gavaging with feces relieved brain damage in mice that received EA (EA mice) more than in mice that did not (non-EA [NEA] mice). The gut microbial composition and metabolic profiles of the EA and NEA mice were different. In particular, the microbiota from the mice in the EA or EA-FMT groups generated more indole-3-propionic acid (IPA) than the microbiota from the mice in the MCAO or NEA-FMT groups. We confirmed that IPA binds to specific melatonin receptors (MTRs) in target cells and exerts antioxidant effects by adding MTR inhibitors or knocking out the MTR1 gene in vivo and in the oxygen and glucose deprivation/reperfusion models of N2a cell experiments. EA can prevent ischemic stroke by improving the composition of intestinal microbiota in MCAO mice. Moreover, this study reveals a new mechanism of intestinal flora regulation of stroke that differs from inflammation/immunity, namely gut microbiota regulates stroke by affecting IPA levels.
The Holy Grail of Software Products Success
Authors: El-Deeb Ahmed
Published: April 2022

We can easily misunderstand the prevalence of software products packed with features over the years as an indicator to our success in impressing customers; thinking that we don't need to do something more than just keep shipping features one after another and keep up with competition. We'd better change that misconception before it's too late. The generation that created sustainable existence for some software products today will not be the same as the generations that would make the decision whether these products would continue to exist. For instance, Generation Z, those born mid-to-late 1990 up to early 2010, grew up with tech that they are no longer impressed by the mere notion of Feature. Their lives are so ingrained in utility from day one that software became something they experience rather than use. It is convenience, reliability, security, seamless interactions, performance, speed and all the matters that directly contribute to positive emotional, sensory, or cognitive perception are what's important. Additionally, it's no longer the app or the piece of software alone that matters; it's the entire Brand. This is because such generations have to be acquired before they even hold the product through brand image and maintained by evolving the brand by their ever changing needs. Such perception of the software product formulated by convenience characteristics and a supportive trustable brand is what constitute Customer Experience. In this paper, it is discussed the key elements that are needed by every software company in order to create an excellent Customer Experience to acquire and maintain happy customers.
Report on the 2nd Workshop on Human Centric Software Engineering & Cyber Security (HCSE&CS 2021)
Authors: Chhetri Mohan Baruwal , Liu Xiao , Grobler Marthie , Hoang Thuong , Renaud Karen , McIntosh Jennifer
Published: April 2022

As the creators, designers, coders, testers, users, and occasional abusers of all software systems-including cyber security systems - humans should be at the centre of all design and development efforts. Despite this, most software engineering and cyber security research and practices tend to be function, data, or process oriented. In contrast, human-centric software engineering focuses on the human-centric issues critical to successful software systems' engineering. The aim of the International Workshop on Human Centric Software Engineering & Cyber Security (HCSE&CS) was to provide a venue for sharing research ideas and outcomes on enhanced theory, models, tools, and capability for next-generation human-centric software engineering and cyber security. The Second HCSE&CS Workshop was held on 15 November 2021 in conjunction with ASE 2021, the 36th IEEE/ACM International Conference on Automated Software Engineering. It was originally intended to be held in Melbourne, Australia but was instead held virtually due to the COVID-19 pandemic. This post-workshop report provides an overview of the aims and motivation of the workshop as well as a summary of the presentations and discussions that took place during the workshop.
OnSRAM: Efficient Inter-Node On-Chip Scratchpad Management in Deep Learning Accelerators
Authors: Pal Subhankar , Venkataramani Swagath , Srinivasan Viji , Gopalakrishnan Kailash
Published: April 2022

Hardware acceleration of Artificial Intelligence (AI) workloads has gained widespread popularity with its potential to deliver unprecedented performance and efficiency. An important challenge remains in how AI accelerators are programmed to sustain high utilization without impacting end-user productivity. Prior software optimizations start with an input graph and focus on node-level optimizations,
viz.
dataflows and hierarchical tiling, and graph-level optimizations such as operation fusion. However, little effort has been devoted to inter-node on-chip scratchpad memory (SPM) management in Deep Learning (DL) accelerators, whose significance is bolstered by the recent trends in complex network topologies and the emergence of eager execution in DL frameworks.

We characterize and show that there exists up to a 5.2× performance gap in DL inference to be bridged using SPM management and propose OnSRAM, a novel SPM management framework integrated with the compiler runtime of a DL accelerator. We develop two variants, viz.  OnSRAM-Static, which works on static graphs to identify data structures that can be lucratively held on-chip based on their size, liveness and significance, and OnSRAM-Eager, which targets an eager execution model (no graph) and uses a history-based speculative scheme to hold/discard data structures. We integrate OnSRAM  with TensorFlow and analyze it on multiple accelerator configurations. Across a suite of 12 images, objects, and language networks, on a 3 TFLOP system with a 2 MB SPM and 32 GBps external memory bandwidth, OnSRAM-Static  and OnSRAM-Eager  achieve 1.02–4.8× and 1.02–3.1× reduction in inference latency (batch size of 1), over a baseline with no SPM management. In terms of energy savings, we observe average reductions of 1.51× (up to 4.1×) and 1.23× (up to 2.9×) for the static and eager execution scenarios, respectively.
A Survey on Deep Hashing Methods
Authors: Luo Xiao , Wang Haixin , Wu Daqing , Chen Chong , Deng Minghua , Huang Jianqiang , Hua Xian-Sheng
Published: April 2022

Nearest neighbor search aims at obtaining the samples in the database with the smallest distances from them to the queries, which is a basic task in a range of fields, including computer vision and data mining. Hashing is one of the most widely used methods for its computational and storage efficiency. With the development of deep learning, deep hashing methods show more advantages than traditional methods. In this survey, we detailedly investigate current deep hashing algorithms including deep supervised hashing and deep unsupervised hashing. Specifically, we categorize deep supervised hashing methods into pairwise methods, ranking-based methods, pointwise methods as well as quantization according to how measuring the similarities of the learned hash codes. Moreover, deep unsupervised hashing is categorized into similarity reconstruction-based methods, pseudo-label-based methods, and prediction-free self-supervised learning-based methods based on their semantic learning manners. We also introduce three related important topics including semi-supervised deep hashing, domain adaption deep hashing, and multi-modal deep hashing. Meanwhile, we present some commonly used public datasets and the scheme to measure the performance of deep hashing algorithms. Finally, we discuss some potential research directions in conclusion.
Pushing the Level of Abstraction of Digital System Design: A Survey on How to Program FPGAs
Authors: Sozzo Emanuele Del , Conficconi Davide , Zeni Alberto , Salaris Mirko , Sciuto Donatella , Santambrogio Marco D.
Published: April 2022

Field Programmable Gate Arrays (FPGAs)
are spatial architectures with a heterogeneous reconfigurable fabric. They are state-of-the-art for prototyping, telecommunications, embedded, and an emerging alternative for cloud-scale acceleration. However, FPGA adoption found limitations in their programmability and required knowledge. Therefore, researchers focused on FPGA abstractions and automation tools. Here, we survey three leading digital design abstractions:
Hardware Description Languages (HDLs)
,
High-Level Synthesis (HLS)
tools, and
Domain-Specific Languages (DSLs)
. We review these abstraction solutions, provide a timeline, and propose a taxonomy for each abstraction trend: programming models for HDLs;
Intellectual Property (IP)
-based or System-based toolchains for HLS; application, architecture, and infrastructure domains for DSLs.
Explainability-Based Mix-Up Approach for Text Data Augmentation
Authors: Kwon Soonki , Lee Younghoon
Published: April 2022

Text augmentation is a strategy for increasing the diversity of training examples without explicitly collecting new data. Owing to the efficiency and effectiveness of text augmentation, numerous augmentation methodologies have been proposed. Among them, the method based on modification, particularly the mix-up method of swapping words between two or more sentences, is widely used because it can be applied simply and shows good levels of performance. However, the existing mix-up approaches are limited; they do not reflect the importance of the manipulated word. That is, even if a word that has a critical effect on the classification result is manipulated, it is not considered significant in labeling the augmented data. Therefore, in this study, we propose an effective text augmentation technique that explicitly derives the importance of manipulated words and reflects this importance in the labeling of augmented data. The importance of each word, in other words, explainability, is calculated, and this is explicitly reflected in the labeling process of the augmented data. The results of the experiment confirmed that when the importance of the manipulated word was reflected in the labeling, the performance was significantly higher than that of the existing methods.
Explore to Learn
Authors: Darban Mehdi
Published: April 2022

Explorative information systems behaviors are the ways in which individuals actively revise their usage and discover creative means of applying the system, extending the potentials of the system, and enhancing task performance. This study has developed a specific concept of explorative system behavior-explorative information technology (IT) learning-to describe users' post-training learning behavior-novel use. Adapting a herding lens, we study the individual and team-level triggers of explorative learning cognitions. The study tests the proposed cross-level model and collects data from 225 individuals who are divided into 51 teams. The results indicate that individuals tend to innovatively use a system through developed exploration cognitions in team settings as a response to examined herd behavior triggers. The study uncovered that members of cohesive teams and learners with high uncertainty perceptions are more likely to imitate the observed explorative learning behaviors of their peers and reproduce such behaviors in the long term.
MIGRANT
Authors: Alkaldi Nora , Renaud Karen
Published: April 2022

Password manager applications have the potential to alleviate password pain and improve password strength, yet they are not widely adopted. Password managers are dissimilar to other kinds of software tools, given that the leakage of the credentials they store could give a hacker access to all the individual's online accounts. Moreover, adoption requires a deliberate switch away from an existing (manual) password management routine. As such, traditional technology adoption models are unlikely to model password manager adoption accurately. In this paper, we propose and explain how we validated a theoretical model of smartphone password manager adoption. We commenced by carrying out exploratory interviews with 30 smartphone owners to identify factors that influence adoption. These were used to develop a model that reflects the password manager adoption process, building on migration theory. The proposed model, MIGRANT (MIGRation pAssword maNager adopTion), was validated and subsequently refined in a week-long study with 198 smartphone owners, combining self-report and observation to measure constructs. This study contributes to the information security behavioral literature by isolating the main factors that encourage or deter password manager adoption, and those that moor smartphone owners in their current practices, hindering switching. With this investigation, we introduce migration theory as a reference theory for future studies in the information security behavioral field.
Therapeutic Effect of P-Cymene on Lipid Profile, Liver Enzyme, and Akt/Mtor Pathway in Streptozotocin-Induced Diabetes Mellitus in Wistar Rats
Authors: Arabloei Sani Maryam , Yaghmaei Parichehreh , Hajebrahimi Zahra , Hayati Roodbari Nasim
Published: April 2022

Diabetes is a serious public health problem in low- and middle-income countries. There is a strong link between hyperglycemia, oxidative stress, inflammation, and the development of diabetes mellitus. PI3K/Akt/mTOR is the main signaling pathway of insulin for controlling lipid and glucose metabolism. P-cymene is an aromatic monoterpene with a widespread range of therapeutic properties including antioxidant and anti-inflammatory activity. In the present study, the antidiabetic effects of p-cymene were investigated. Diabetes was induced using streptozotocin in male Wistar rats. The effects of p-cymene and metformin were studied on levels of glucose (Glu), lipid profile, liver enzymes, oxidative stress, and the expression of Akt, phospho-Akt, and mTOR (mammalian target of rapamycin) proteins, using biochemical, histological, and immunohistochemical analysis. Data have shown that p-cymene can improve serum levels of Glu, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein (LDL), very-low-density lipoprotein (VLDL), alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), malondialdehyde (MDA), and the expression of mTOR, Akt, and phospho-Akt protein in diabetic animals. These results suggest that p-cymene has hypoglycemia, hypolipidemia, and antioxidant properties. It can regulate Akt/mTOR pathway and reduce hepatic and pancreas injury. It can be suggested for diabetes management alone or simultaneously with metformin.
Optimization of Green Synthesis of Selenium Nanoparticles and Evaluation of Their Antifungal Activity against Oral Candida albicans Infection
Authors: Safaei Mohsen , Mozaffari Hamid Reza , Moradpoor Hedaiat , Imani Mohammad Moslem , Sharifi Roohollah , Golshah Amin
Published: April 2022

Increasing resistance of microbes to available antimicrobial agents has necessitated the production of new compounds with wider activity and lower toxicity. Candida is one of the pathogenic fungal strains that are highly prevalent in oral diseases. The goal of this study was to optimize the biosynthesis of selenium nanoparticles (NPs) with the suitable antifungal activity on Candida albicans oral pathogen. For this purpose, selenium NPs were synthesized by the green method using the Halomonas elongata bacterium. To optimally synthesize NPs with the maximal antifungal properties, 9 experiments were planned applying the Taguchi method. In the planned experiments, the efficacy of 3 factors, sodium selenite concentration, glucose concentration, and incubation time at 3 various levels was studied, and the most desirable conditions with the suitable performance were determined. Then, optimizing the synthesis of the studied nanoparticles, their properties were evaluated using Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-Vis), X-ray powder diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), electron transmission microscopy (TEM), and thermogravimetric analysis (TGA) to confirm the synthesis of nanoparticles with suitable conditions. The results demonstrated that the synthesized NPs in the experiment 9 condition showed the best performance and prevented more than 70% of fungal growth. Since selenium NPs were effective as an antifungal agent, they can be used in the structure of mouthwashes as an antimicrobial agent in the prevention and treatment of many oral diseases.
A Study to Enhance the Route Optimization Algorithm for the Internet of Vehicle
Authors: Dhanare Ritesh , Nagwanshi Kapil Kumar , Varma Sunita
Published: April 2022

In the Internet of Things (IoT), the advancement of the new modern era of Internet-off driving, known as the Internet of Vehicles (IoV), is aimed at the Intelligent Transportation System (ITS) to improve road safety and traffic. Therefore, IoV is better for traffic management. But perhaps, the main challenges in this type of network are that timely decision to make adequate decisions by a driver under certain conditions of rapid change in topology, high vehicular mobility, and frequent link failures is hard to improve road safety. Therefore, an optimized and congestion-free route is required to collect real-time data from vehicles. Thus, some of the latest bioinspired optimization routing algorithms in the IoV environment are presented in this study. Hence, monitoring speed limits, pollution checks, and emergency responses to traffic accidents should also be considered while performing vehicle routing to avoid traffic problems. In the previous decades, many route-directing protocols for the IoV environment have been proposed that can handle the requirements of reliability and security. But such routing of protocols suffers from high complexity and scalability limitations in big-scale networks, routing overlays, etc. Therefore, their strengths, weaknesses, and critical characteristics are compared using various criteria for such algorithms. Then, a suggestion is made to propose a prescribed combined model of a multimodular bioinspired approach to IoV routing. Finally, the main future directions of research in this sector are highlighted.
Application Layer-Forward Error Correction Raptor Q Codes in 5G Mobile Networks for Factory of the Future
Authors: Ramly Athirah Mohd , Nordin Rosdiadee , Abdullah Nor Fadzilah
Published: April 2022

The future communication requirements for industrial automation will differ significantly from existing technologies. Traffic in Industry 4.0 imposes real-time requirements, requiring ultra-reliable communication (URC) with high reliability and minimal latency. The demand for ultra-high reliability as high as 99.999999 percent and as low as 1 ms end-to-end latency is the major challenge of the NOMA communication system in the factory of the future. The high expectations on reliability and latency need modifications to the radio system’s baseband signal processing, medium access control (MAC) layer, and application layer to protect against packet losses. Thus, this paper investigates the utilization of Raptor Q codes, which is a type of Application Layer Forward Error Correction (AL-FEC), by developing an end-to-end system level simulator to evaluate and analyze the performance of the transmission signals based on cross-layer approach; from the physical layer (PHY), MAC layer, and application layer parameters in an indoor factory network setting. The factory is assumed to be operated with various factory robots of different speeds, from static to 10 km/h. The 5G technology relies heavily on flexible network operations. High user density, high user mobility, deployment, and coverage are all qualities that allow for this flexibility. Through extensive simulations, the results showed that the Raptor Q codes are not only able to give good results, i.e.,

packet
 
reception
 
rate
 

PRR

=
0.9

of 10 m or 1.8% to 10 m or 3.4% depending on different scenarios, but are also able to meet

PRR
=
0.9

in the mobility scenario at 10 km/h. Thus, the Raptor Q codes can be seen as a good candidate for obtaining results within a strict range of requirements set by URC communications for the factory of the future replacing RLNC.
Consumers’ Knowledge of Food Adulteration and Commonly Used Methods of Detection
Authors: Essuman Edward Ken , Teye Ernest , Dadzie Rosemond Godbless , Sam-Amoah Livingstone K.
Published: April 2022

Food adulteration has become a threat to many countries as most individuals have consumed food items without knowing that it has been adulterated, leaving the consumer with various ailments. This study identifies the degree of adulteration in some commonly used food items bought by consumers and the means of detection. The study comprised 384 women who patronized various food items for food preparation. They were asked if they have come into contact with adulterated food products before and to illustrate how they detect if a food item is adulterated. From the findings of this study, the respondents indicated that they will not consume a food item if they get to know that it has been adulterated, and 50.5% indicated that they have come into contact with adulterated food during preparing food. Various reasons were given by the respondents why they will not consume adulterated food, and the reasons included the following: the food may be dangerous to consume and not healthy for consumption and can cause stomach disorders. Few numbers (11 out of 384) of the respondents also indicated that they will still go ahead and consume adulterated food items since not all adulterants are toxic. Food items that are prone to adulteration as mentioned by the respondent included groundnut paste, chilli pepper, tomato powder, and honey with their adulterants ranging from flour, colour, Sudan IV dye, chalk powder, foam, cola nut powder, avocado pear seed powder, and many more. Means of detecting the presence of adulterants as indicated by the respondent were sensory and textural characteristics due to the cost involved in the use of other advanced techniques.
Research on Multicamera Photography Image Art in BERT Motion Based on Deep Learning Mode
Authors: Zhao Zhao , Song Mingyang , Tang Hongyue
Published: April 2022

In order to improve the artistic expression effect of photographic images, this article combines the deep learning model to conduct multicamera photographic image art research in BERT motion. Moreover, this article analyzes the external parameter errors caused in the calibration process and uses the checkerboard in the common field of view to calibrate the spatial coordinates of the corners of the board in multiple camera coordinate systems. In addition, this article aims to match the spatial coordinates of the corresponding points to each other and solve the rotation and translation matrix in the transformation process. Finally, this article uses the LM algorithm to optimize the calibration parameters of the camera and combines the deep learning algorithm to perform image processing. The experimental research results show that the research method of multicamera photography image art in BERT motion based on the deep learning mode proposed in this article can effectively improve the expression effect of image art.
Finite Element Analysis of the Dynamics of Power-Law Fluid around an Obstacle in a Channel
Authors: Mahmood Rashid , Jaradat Mohammed M. M. , Ali Rifaqat , Siddique Imran , Majeed Afraz Hussain , Mehmood Asif
Published: April 2022

Control of fluid forces is an emerging area of research with numerous engineering applications. The uneven wake behind an obstacle causes undesirable structural oscillations, which can lead to fatigue or structural failure. Controlling the wake phenomena could directly benefit a wide range of engineering applications, including skyscrapers, naval risers, bridges, columns, and a few sections of airplanes. This study is concerned with the time dependent simulations in a channel in presence of an obstacle aiming to compute fluid forces. The underlying mathematical model is based on nonstationary Navier–Stokes equations coupled with the constitutive relations of power law fluids. Because the representative equations are complex, an effective computing strategy based on the finite element approach is used. To achieve higher accuracy, a hybrid computational grid at a very fine level is used. Theℙ2−ℙ1elements based on the shape functions of the second and first-order polynomials were used to approximate the solution. The discrete nonlinear system arising from this discretization is linearized by Newton’s method and then solved through a direct linear solver PARADISO. The code validation study is also performed for Newtonian fluids as a special case, and then the study is extended to compute drag and lift forces for other cases of viscosity as described by the power law index. When looking at the phase plot, it can be seen that for the Newtonian case n = 1, there is only one closed orbit after the steady state is reached, whereas forn=0.5, there are multiple periodic orbits. Moreover, the effects of shear rate on the drag-lift phase plot are also discussed.
Study on the Imbibition Characteristics of Different Types of Pore-Throat Based on Nuclear Magnetic Resonance Technology
Authors: Liu Xiong , Zhang Yang , Zhang Ziming , Xu Jinze , Zhou Desheng , Su Jian , Tang Ying
Published: April 2022

“Fracturing network+imbibition oil production” is a new attempt to effectively develop low-permeability tight reservoirs. Fracturing fluid is not only a carrier for sand carrying but also a tool in the process of imbibition. On the basis of imbibition experiments, combined with nuclear magnetic resonance and pseudo-color processing technology, this paper clarified the dominant forces of different types of pore-throat and quantitatively characterized the contribution of different levels of pore-throat to imbibition oil recovery. The results show that gravity is the main controlling force of imbibition for reservoirs with higher permeability. Fluid replacement mainly occurs in the early period of imbibition. Macropores contribute most of the imbibition recovery, mesopores have a weak contribution, and the contribution of micropores and pinholes can be ignored. For the reservoirs with low permeability, capillary force is the main controlling force of imbibition. Fluid replacement mainly occurs in the later period of imbibition. Macropores contribute most of the imbibition recovery rate, mesopores contribute a small part of the imbibition recovery factor, and the contribution of micropores and pinholes can be ignored. This paper clarified that macropores and mesopores are the main sources of the contribution of imbibition recovery efficiency, and oil content and connectivity are key factors for the imbibition recovery efficiency.
Analysis of Hepatic Artery Infusion (HAI) Chemotherapy Using Randomized Trials of Floxuridine (FUDR) for Colon Cancer Patients with Multiple Liver Metastases
Authors: Li Yuanming
Published: April 2022

Colorectal cancer (CRC) is one of the leading causes of cancer-related death, with most of the people who have the disease developing numerous liver metastases. Sixty percent of colon cancer patients have liver metastases. Only 25% of those with resectable hepatic metastases are alive, and recurrence occurs in nearly half of these cases. Regardless of the fact that left-sided cancer has a higher rate of liver metastases, past study reveals that left- and right-sided liver metastatic colon cancer patients have different survival rates. Hepatic artery infusion (HAI) combined with systemic chemotherapy is a treatment option for patients with unresectable liver-only or liver-dominant colon liver metastases. Although HAI has only been performed in a few locations previously, this study used randomized trials of floxuridine (FUDR) to characterize patient selection and first perioperative results during the deployment of a new HAI program. In this research, we also looked at the technical aspects of placing implantable pumps and catheters for HAI chemotherapy, as well as the efficacy, morbidity, and outcomes of this therapy in colon cancer patients with numerous liver metastases. The parameters like toxicity, overall survival rate, response rate, and progression-free response for the suggested therapy are also analyzed. These findings have important implications for colon cancer adjuvant HAI chemotherapy.
Effects of Rhizobium Inoculation and P Fertilizer Levels on Selected Soil Properties, Yield, and Yield Components of Faba Bean (Vicia faba L.): The Case of Abuna Gindeberat, West Shewa Zone, Ethiopia
Authors: Chimdi Achalu , Negasa Dereje , Chala Girma
Published: April 2022

Poor soil fertility status and inappropriate agronomic practices are the major factors for low crop productivity like legumes. Thus, the experiment was conducted to evaluate the effect of the P fertilizer rate and rhizobium inoculation on selected soil properties and yield of faba bean. In order to achieve this objective, a field experiment was laid out in a randomized complete block design in a factorial arrangement with replication. The treatments consisted of five P levels (0, 23, 46, 69, and 92 kg P2O5 ha−1) and two rhizobium inoculants (Fb17 and Fb18). Faba bean (Moti variety) was used as the test crop. Soil samples were collected before and after planting for laboratory analysis. All soil and agronomic data were subjected to the analysis of variance (ANOVA) using statistical analysis software version 9.2. The main effect of strain positively improved soil porosity, but soil bulk density was negatively influenced. Soil chemical parameters such as organic carbon, total N, available P, available sulfur, Ca, Mg, and K were positively influenced. The interaction effects of the P fertilizer rate and rhizobium inoculation significantly influenced organic carbon, total N, available P, and yield parameters (pod per plant, numbers of nodules per plant, biomass yield, straw yield, and grain yields). The combined application of 69 kg P2O5 ha−1 and Fb18 rhizobium inoculants gave the highest grain yield (4.4 t ha−1) of faba bean. Thus, the integrated application of strain and P2O5 fertilizer improved soil fertility and faba bean crop yield. Therefore, reducing soil fertility constrains of the soils through the integrated application of strain and P2O5 fertilizer could be a possible option to reduce the yield gap seen between smallholder farmers and experimental fields. So as to maintain soil fertility and sustain faba bean crop production, farmers of the study area are advised to make integrated use of strain type Fb18 and P2O5 fertilizer at 69 kg/ha−1 with appropriate agronomic practices.
Identification of Mine Water Source Based on AHP-Entropy and Set Pair Analysis
Authors: Zhao Xianming , Xu Zhimin , Sun Yajun
Published: April 2022

After a water inrush disaster occurs in the mine production process, it is urgent to identify the source of water inrush and formulate corresponding countermeasures in the complex hydrogeological condition of coal mines. Therefore, accurate identification of mine groundwater source is one of the keys to prevent mine water disasters. According to the difference between the hydrochemical compositions of three aquifers in Chengjiao coal mine, six primary ions (Na++K+, Ca2+, Mg2+, SO42-, Cl,- and HCO3-) were selected as the indexes for groundwater source identification. On this basis, a mathematical model for groundwater source identification was established by combining the analytic hierarchy process- (AHP-) entropy weight method and the set pair analysis (SPA) theory. Next, this model was used to identify the sources of 10 sets of water samples from the mine, and then, the identification results were compared with the results of conventional models established using Fisher discriminant analysis (FDA) and Bayes discriminant analysis (BDA) methods. The results show that the SPA-based model performs better in identifying the groundwater sources. Furthermore, the model was used to identify the source of water inflow in the No. 21304 panel. The analysis on identification results reveals that the area close to the F20 normal fault tends to receive water supply from the Ordovician limestone aquifer and the Taiyuan Formation limestone aquifer, so it should be regarded as a key area for water inrush prevention and control.
Lipopeptide Biosurfactants from Bacillus spp.: Types, Production, Biological Activities, and Applications in Food
Authors: Ali Nawazish , Pang Zhengjun , Wang Fenghuan , Xu Baocai , El-Seedi Hesham R.
Published: April 2022

Biosurfactants are a functionally and structurally heterogeneous group of biomolecules produced by multiple filamentous fungi, yeast, and bacteria, and characterized by their distinct surface and emulsifying ability. The genus Bacillus is well studied for biosurfactant production as it produces various types of lipopeptides, for example, lichenysins, bacillomycin, fengycins, and surfactins. Bacillus lipopeptides possess a broad spectrum of biological activities such as antimicrobial, antitumor, immunosuppressant, and antidiabetic, in addition to their use in skincare. Moreover, Bacillus lipopeptides are also involved in various food products to increase the antimicrobial, surfactant, and emulsification impact. From the previously published articles, it can be concluded that biosurfactants have strong potential to be used in food, healthcare, and agriculture. In this review article, we discuss the versatile functions of lipopeptide Bacillus species with particular emphasis on the biological activities and their applications in food.
A Novel Teaching-Learning-Based Optimization with Laplace Distribution and Experience Exchange
Authors: Zhai Zhibo , Dai Yusen , Xue Yingfang
Published: April 2022

Teaching-Learning-Based Optimization (TLBO) algorithm is an evolutionary powerful algorithm that has better global searching capability. However, in the later period of evolution of the TLBO algorithm, the diversity of learners will be degraded with the increasing iteration of evolution and the smaller scope of solutions, which lead to a trap in local optima and premature convergence. This paper presents an improved version of the TLBO algorithm based on Laplace distribution and Experience exchange strategy (LETLBO). It uses Laplace distribution to expand exploration space. A new experience exchange strategy is applied to make good use of experience information to identify more promising solutions to make the algorithm converge faster. The experimental performances verify that the LETLBO algorithm enhances the solution accuracy and quality compared to original TLBO and various versions of TLBO and is very competitive with respect to other very popular and powerful evolutionary algorithms. Finally, the LETLBO algorithm is also applied to parameter estimation of chaotic systems, and the promising results show the applicability of the LETLBO algorithm for problem-solving.