bluuebunny/crossref_metadata_2025_split huggingface dataset:
Uncovering the promiscuous activity of IL‐6 proteins: A multi‐dimensional analysis of phylogeny, classification and residue conservation
Authors: Costa André da , Franco‐Duarte Ricardo , Machado Raul , Gomes Andreia C. 
Published: October 2022

AbstractThe IL‐6 family of cytokines, known for their pleiotropic behavior, share binding to the gp130 receptor for signal transduction with the necessity to bind other receptors. Leukemia inhibitory factor receptor is triggered by the IL‐6 family proteins: leukemia inhibitory factor (LIF), oncostatin‐M (OSM), cardiotrophin‐1 (CT‐1), ciliary neurotrophic factor (CNTF), and cardiotrophin‐like cytokine factor 1 (CLCF1). Besides the conserved binding sites to the receptor, not much is known in terms of the diversity and characteristics of these proteins in different organisms. Herein, we describe the sequence analysis of LIF, OSM, and CT‐1 from several organisms, and m17, a LIF ortholog found in fishes, regarding its phylogenetics, intrinsic properties, and the impact of conserved residues on structural features. Sequences were identified in seven classes of vertebrates, showing high conservation values in binding site III, but protein‐dependent results on binding site II. GRAVY, isoelectric point, and molecular weight parameters were relevant to differentiate classes in each protein and to enable, for the first time and with high fidelity, the prediction of both organism class and protein type just using machine learning approaches. OSM sequences from primates showed an increased BC loop when compared to the remaining mammals, which could influence binding to OSM receptor and tune signaling pathways. Overall, this study highlights the potential of sequence diversity analysis to understand IL‐6 cytokine family evolution, showing the conservation of function‐related motifs and evolution of class and protein‐dependent characteristics. Our results could impact future medical treatment of disorders associated with imbalances in these cytokines.
Bioplastic degradation by a polyhydroxybutyrate depolymerase from a thermophilic soil bacterium
Authors: Thomas Gwendell M. , Quirk Stephen , Huard Dustin J. E. , Lieberman Raquel L. 
Published: October 2022

AbstractAs the epidemic of single‐use plastic worsens, it has become critical to identify fully renewable plastics such as those that can be degraded using enzymes. Here we describe the structure and biochemistry of an alkaline poly[(R)‐3‐hydroxybutyric acid] (PHB) depolymerase from the soil thermophileLihuaxuella thermophila. Like other PHB depolymerases or PHBases, theLihuaxuellaenzyme is active against several different polyhydroxyalkanoates, including homo‐ and heteropolymers, butL. thermophilaPHB depolymerase (LtPHBase) is unique in that it also hydrolyzes polylactic acid and polycaprolactone.LtPHBase exhibits optimal activity at 70°C, and retains 88% of activity upon incubation at 65°C for 3 days. The 1.2 Å resolution crystal structure reveals an α/β‐hydrolase fold typical of PHBases, but with a shallow active site containing the catalytic Ser‐His‐Asp‐triad that appears poised for broad substrate specificity.LtPHBase holds promise for the depolymerization of PHB and related bioplastics at high temperature, as would be required in bioindustrial operations like recycling or landfill management.
Residual efficacy of the neonicotinoid insecticide clothianidin against pyrethroid‐resistant Aedes aegypti
Authors: Che‐Mendoza Azael , González‐Olvera Gabriela , Medina‐Barreiro Anuar , Arisqueta‐Chablé Carlos , Herrera‐Bojórquez Josue , Bibiano‐Marín Wilberth , Kirstein Oscar , Vazquez‐Prokopec Gonzalo , Manrique‐Saide Pablo 
Published: October 2022

AbstractBACKGROUNDHere we report the residual efficacy of the neonicotinoid insecticide clothianidin against pyrethroid‐resistant Aedes aegypti. We first conducted a range‐finding evaluation of clothianidin on three different substrates (wall, wood, cloth) using three doses (100, 300 and 600 mg a.i. m−2) and conducting World Health Organization (WHO) cone bioassays to assess acute (24 h) and delayed (up to 7 days) mortality. In experimental houses located in Merida (Mexico) and using free‐flying pyrethroid‐resistant Ae. aegypti females, we quantified the acute and delayed mortality after a 24‐h exposure to the targeted indoor residual spraying (TIRS) of two clothianidin doses (100 and 300 mg a.i. m−2).RESULTSRange‐finding studies with WHO cones showed low (<50%) acute mortality for all surfaces, doses and times post spraying. Delayed mortality was higher, with average values above or close to the 60% mark (and 95% confidence interval estimates crossing 80% for the 600 mg a.i. m−2 dose). In experimental houses, a similar low acute mortality was quantified (range of mortality across 12 months was 2–44% for 100 mg a.i. m−2 and 8–61% for 300 mg a.i/m2). However, delayed mortality showed a strong effect of clothianidin on free‐flying Ae. aegypti, with values above 80% up to 7 months post‐TIRS.CONCLUSIONNovel residual insecticide molecules have a promising outlook for Ae. aegypti control and can contribute to the expansion and adoption of TIRS in urban areas. clothianidin can contribute to the control of resistant Ae. aegypti and provide residual control for up to 7 months after application. © 2022 Society of Chemical Industry.
Discovery of rosin‐based acylhydrazone derivatives as potential antifungal agents against rice Rhizoctonia solani for sustainable crop protection
Authors: Xu Renle , Gu Shihao , Chen Kun , Chen Jinyu , Wang Yong , Gao Yanqing , Shang Shibin , Song Zhanqian , Song Jie , Li Jian 
Published: October 2022

AbstractBACKGROUNDThe use of fungicides to protect crops from diseases is an effective method, and novel environmentally friendly plant‐derived fungicides with enhanced performance and low toxicity are urgent requirements for sustainable agriculture.RESULTSTwo kinds of rosin‐based acylhydrazone compounds were designed and prepared. Based on the antifungal activity assessment against Rhizoctonia solani, Fusarium oxysporum, Phytophthora capsici, Sclerotinia sclerotiorum, and Botrytis cinerea, acylhydrazone derivatives containing a thiophene ring were screened and showed an inhibitory effect on rice R. solani. Among them, Compound 4n, with an electron‐withdrawing group on the benzene ring structure attached to the thiophene ring, showed optimal activity, and the EC50 value was 0.981 mg L−1, which was lower than that of carbendazim. Furthermore, it was indicated that 4n could affect the mycelial morphology, cell membrane permeability and microstructure, cause the generation of reactive oxygen species in fungal cells, and damage the nucleus and mitochondrial physiological function, resulting in the cell death of R. solani. Meanwhile, Compound 4n exhibited a better therapeutic effect on in vivo rice plants. However, the induction activity of 4n on the defense enzyme in rice leaf sheaths showed that 4n stimulates the initial resistance of rice plants by removing active oxygen, thereby protecting the cell membrane or enhancing the strength of the cell wall. Through the quantitative structure–activity relationship study, the quantitative chemical and electrostatic descriptors significantly affect the binding of 4n with the receptor, which improves its antifungal activity.CONCLUSIONThis study provides a basis for exploiting potential rosin‐based fungicides in promoting sustainable crop protection. © 2022 Society of Chemical Industry.
Observer‐based consensus tracking control for a class of nonstrict‐feedback nonlinear multi‐agent systems with prescribed performance and input quantization
Authors: Shi Zhengqing , Zhou Chuan , Guo Jian 
Published: October 2022

AbstractThis article investigates the consensus tracking problem with predefined transient and steady performance requirements for a class of nonstrict‐feedback nonlinear multi‐agent systems (MASs) with input quantization under a directed graph. Based on prescribed performance error transformation methods and command filtered backstepping techniques, a novel observer‐based adaptive control protocol is proposed, where neural observers are designed to estimate unmeasurable states and radial basis function neural networks are constructed to compensate command filter errors. The proposed protocol can be applied to a more general class of nonlinear MASs with nonstrict‐feedback nonlinear dynamics and unmeasurable states information. It is strictly proved that all signals in the whole MAS are semi‐globally uniformly ultimately bounded and both the transient and steady performances of the consensus tracking errors satisfy prescribed performance requirements. Finally, three numerical examples are presented to validate the effectiveness of the proposed protocol.
Accessing cash(lessness): Cash dependency, debt, and digital finance in a marginalized Roma neighborhood
Authors: Ravnbøl Camilla Ida 
Published: October 2022

ABSTRACTThis article contributes to contemporary ethnographies concerning poverty and digital financial inclusion in Europe. More specifically, it explores how poor Roma families engage with digital banking cards at home in Romania and when they travel to work in the informal economy in Denmark. The analysis conceptually unfolds “access” as a framework for financial inclusion and applies it to an empirical case of three brothers in a Roma family. On this basis, the article argues that cashless initiatives can, perhaps unintentionally, be a driving element in new practices of social exclusion. Without a comprehensive approach toward ensuring “de facto access” for the marginalized communities, which takes all dimensions of access into account, digital financial initiatives can potentially push them further to the periphery of the global economy.
Corporate social counterpositioning: How attributes of social issues influence competitive response
Authors: Mohliver Aharon , Crilly Donal , Kaul Aseem 
Published: October 2022

AbstractResearch SummaryWhilst existing research generally assumes corporate social responsibility (CSR) is seen as universally positive, firms increasingly adopt practices, and take stands, on highly polarizing social issues (e.g., gun‐control, LGBTQ rights, abortion). To better understand this phenomenon, we develop a theory about when firms will emulate, ignore, or oppose each other's CSR efforts, based on attributes of the underlying social issue (its salience and polarization), the level of market competition, and the substantiveness of CSR. Our theory predicts several distinct equilibrium outcomes, including the potential for social counter‐positioning, whereby rival firms take advantage of socio‐political polarization to horizontally differentiate by taking opposing stances on a polarizing issue. Counterpositioning is more likely when salience is high, but agreement is low, when markets are competitive, and when CSR is largely symbolic.Managerial SummaryFirms increasingly find themselves drawn, willingly or not, to taking stances on a controversial social issue (e.g., gun rights, abortion), though doing so risks alienating (some) stakeholders. In this paper, we develop a theory of why, when, and how firms should take a stance on a polarizing issue. We argue that firms profit from doing so when (1) the issue is salient, (2) markets are competitive, and (3) the actions are mostly symbolic. We also show that taking a stance on polarizing issues creates opportunities for the firms' competitors to counter their ideological positioning, strengthening weaker rivals in the process. Thus, in competitive markets, taking clear stances on polarizing, salient issues can segment the market, increasing the profits of all firms, and, potentially, intensifying polarization.
Oxidation State Modulation of Bimetallic Tin‐Copper Oxide Nanotubes for Selective CO2 Electroreduction to Formate
Authors: Jiang Xingxing , Li Xuan , Kong Yan , Deng Chen , Li Xiaojie , Hu Qi , Yang Hengpan , He Chuanxin 
Published: October 2022

AbstractIn this work, the oxidation state of Sn and Cu active sites for CO2 electroreduction via constructing a Sn‐Cun bimetallic oxide composite with a nanotube structure (SnCu‐CNS) is successfully modulated. Compared to a single SnO2 or CuOx component, the SnCu‐CNS composite holds reinforced electronegativity to generate unique extra Snδ+ centers and higher CuO centers with enhanced oxidation effect. Based on density functional theory calculations, the enlarged energy difference between Snδ+/CuO centers and the reactants accelerates the electron transfer and decreases the energy barrier for the key intermediates to gain higher formate selectivity. Furthermore, the hollow structure and abundant micropores of SnCu‐CNS are also conducive to the reactant transport and availability of active sites during CO2 electroreduction. In a conventional H‐type cell, SnCu‐CNS catalyst exhibits a maximum 95.1% faradaic efficiency for formate production. Switching to a flow cell configuration, SnCu‐CNS can further deliver partial current densities exceeding 200 mA cm−2 and over 90% faradaic efficiencies for the formate, superior to most of the reported Sn‐based electrocatalysts. This strategy of electronic modulation and morphology engineering in bimetallic oxides can have wide applications to raise electrocatalytic performance.
Effect of Wheat and Oat Bran on the Physicochemical Properties of Edible Starch‐Based Films Obtained by Extrusion for Food Packaging Applications
Authors: Ochoa‐Yepes Oswaldo , Ceballos Rocío L. , Famá Lucía 
Published: October 2022

AbstractObtaining edible and biodegradable films for food packaging applications has been a strong desire of consumers, scientific community and industry for years. In this context, edible films from cassava starch with wheat or oat bran (0, 5 and 10 wt.%) manufactured from an industrially established process for packaging, such as extrusion technique, are investigated. Wheat bran is found to have a high content of total dietary fiber, being able to provide a nutritional contribution to the packaging and to consumers. Some broken bran grains smaller than 1 µm are observed, distributed quite homogeneously in the matrix and without the presence of phase separation, suggesting great miscibility between the components. Brans acted as reinforcement in concentrations of 10 wt.%, leading in thecase of wheat bran to increases of 850%, 45% and 25% in Young modulus, strength at break and toughness, respectively, and to decreases in moisture content. The incorporation of bran not significant change the thermal stability and biodegradation of the films. This investigation showed that biodegradable and edible cassava starch‐based films can be manufactured by a scalable process with possible improvements in nutrition and mechanical strength using 10 wt.% of bran for its potential employ as food packaging.
Diagnosis and management of rare sequels to feline lower urinary tract disease in two cats
Authors: Mazda Delna , Ahamad Azahari Ikhwan Saufi , Megat Abdul Rani Puteri Azaziah , Omar Sharina , Lau Seng Fong 
Published: October 2022

AbstractThe present case report describes the clinical course and outcome of two cats initially diagnosed with feline lower urinary tract disease. The first cat proceeded to develop emphysematous cystitis. This report documented the first occurrence of Enterobacter cloacae in a case of emphysematous cystitis. The other cat developed pseudomembraneous cystitis, a condition rarely documented in cats. This report revealed the first occurrence of Pasteurella pneumotropica in a case of feline pseudomembraneous cystitis. Both conditions are uncommon sequels to feline lower urinary tract disease and can be identified by ultrasonography. They can develop secondary to severe bacterial urinary tract infections. Cats were treated medically and surgically, depending on the severity of their condition. An early diagnosis and appropriate medical therapy could lead to avoidance of surgical intervention in both conditions. The report highlights the importance of ultrasonography in early diagnosis and continuous monitoring of such conditions.
Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
Authors: Moridian Parisa , Shoeibi Afshin , Khodatars Marjane , Jafari Mahboobeh , Pachori Ram Bilas , Khadem Ali , Alizadehsani Roohallah , Ling Sai Ho 
Published: October 2022

AbstractApnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep apnea may last for a few seconds and happen for many while sleeping. This reduction in breathing is associated with loud snoring, which may awaken the person with a feeling of suffocation. So far, a variety of methods have been introduced by researchers to diagnose sleep apnea, among which the polysomnography (PSG) method is known to be the best. Analysis of PSG signals is very complicated. Many studies have been conducted on the automatic diagnosis of sleep apnea from biological signals using artificial intelligence (AI), including machine learning (ML) and deep learning (DL) methods. This research reviews and investigates the studies on the diagnosis of sleep apnea using AI methods. First, computer aided diagnosis system (CADS) for sleep apnea using ML and DL techniques along with its parts including dataset, preprocessing, and ML and DL methods are introduced. This research also summarizes the important specifications of the studies on the diagnosis of sleep apnea using ML and DL methods in a table. In the following, a comprehensive discussion is made on the studies carried out in this field. The challenges in the diagnosis of sleep apnea using AI methods are of paramount importance for researchers. Accordingly, these obstacles are elaborately addressed. In another section, the most important future works for studies on sleep apnea detection from PSG signals and AI techniques are presented. Ultimately, the essential findings of this study are provided in the conclusion section.This article is categorized under:
Technologies > Artificial Intelligence
Application Areas > Data Mining Software Tools
Algorithmic Development > Biological Data Mining
Liberty, Paternalism, and Road Safety
Authors: Hansson Sven Ove 
Published: October 2022

AbstractTraffic safety measures such as seat belts, helmets, and speed limits have often been opposed by people claiming that these measures infringe on their liberty. Safety measures are often described as paternalistic, i.e., as protecting people against their own will. This chapter provides a historical account of such criticism of safety measures, beginning with nineteenth-century opposition to sanitation measures, which were claimed to threaten the freedom to drink dirty water. The historical analysis has a surprising conclusion: Opposition to safety measures does not seem to have much to do with paternalism. Some measures that would typically be described as paternalistic, such as seat belts in commercial aviation and hard hats on construction sites, have met with no significant opposition. In contrast, some of the most vehemently opposed measures, such as speed limits and the prohibition of drunk driving, cannot with any vestige of credibility be described as paternalistic. This is followed by an analysis showing that due to our tendency to follow examples set by others (herd effects), purely self-affecting behavior is much less common than what has usually been assumed. Most of the opposition to safety measures in road traffic seem to result from some individuals’ desires to engage in activities that endanger other people’s lives. The social need to restrain the satisfaction of such desires is obvious.
Final Reflections
Authors: Bjørn Pernille , Menendez-Blanco Maria , Borsotti Valeria 
Published: October 2022

AbstractWorking on research in equity, inclusion, and diversity in technology development has brought us many interesting reflections on the kinds of research we do, what we include, and what we exclude – and on the kind of institutions we are part of, were part of earlier, and will take an active part in creating in the future.
Die-Less Forming of Fiber-Reinforced Plastic Composites
Authors: Rath Jan-Erik , Graupner Robert , Schüppstuhl Thorsten 
Published: October 2022

AbstractFiber-reinforced plastics (FRP) are increasingly popular in light weight applications such as aircraft manufacturing. However, most production processes of thin-walled FRP parts to date involve the use of expensive forming tools. This especially hinders cost-effective production of small series as well as individual parts and prototypes. In this paper, we develop new possible alternatives of highly automated and die-less production processes based on a short review of current approaches on flexible thin-walled FRP production. All proposed processes involve robot guided standard tools, similar to incremental sheet metal forming, for local forming of the base materials. These include woven glass fiber fabrics which are locally impregnated with thermoset resin and cured using UV-light, woven commingled yarns made out of glass fibers and thermoplastic fibers which are locally heated and pressed, as well as pre-consolidated thermoplastic organo sheets which require selective heating for forming. General applicability of the processes is investigated and validated in practical experiments.
Implementation of a Novel Fully Convolutional Network Approach to Detect and Classify Cyber-Attacks on IoT Devices in Smart Manufacturing Systems
Authors: Shahin Mohammad , Chen FFrank , Bouzary Hamed , Hosseinzadeh Ali , Rashidifar Rasoul 
Published: October 2022

AbstractIn recent years, Internet of things (IoT) devices have been widely implemented and industrially improved in manufacturing settings to monitor, collect, analyze, and deliver data. Nevertheless, this evolution has increased the risk of cyberattacks, significantly. Consequently, developing effective intrusion detection systems based on deep learning algorithms has proven to become a dependable intelligence tool to protect Industrial IoT devices against cyber-attacks. In the current study, for the first time, two different classifications and detection long short-term memory (LSTM) architectures were fine-tuned and implemented to investigate cyber-security enhancement on a benchmark Industrial IoT dataset (BoT-IoT) which takes advantage of several deep learning algorithms. Furthermore, the combinations of LSTM with FCN and CNN demonstrated how these two models can be used to accurately detect cyber security threats. A detailed analysis of the performance of the proposed models is provided. Augmenting the LSTM with FCN achieves state-of-the-art performance in detecting cybersecurity threats.