bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Savings of Simultaneous Heating and Cooling System According to Indoor Set Temperature Changes in the Comfort Range
Authors: Shin Dae-Uk , Jeong Chang-Ho
Published: November 2021

This study was conducted to derive the amount of energy savings when applying the method of making the load similar by changing the set temperature of the room in the building to which the simultaneous heating and cooling (SHC) system is applied. Energy savings were derived through theoretical analysis and comparisons through static simulations were performed to verify the proposed method. As a result, the energy savings are proportional to the energy limit that can be additionally input to the SHC and is proportional to the ratio of the coefficient of performance (COP) difference between the SHC and auxiliary heat source and the auxiliary heat source COP. That is, to increase the amount of energy savings, the maximum possible energy should be input for the SHC, or the SHC COP must be greater than the auxiliary heat source COP. In addition, comfort can be achieved stably by varying the set room temperature in a room with a small load. When a heat storage tank is installed or changing the indoor set temperature of both the hot and cold zones in real time by predicting the indoor load is possible, more energy can be saved.
Review on Detection and Analysis of Partial Discharge along Power Cables
Authors: Zhang Xiaohua , Pang Bo , Liu Yaxin , Liu Shaoyu , Xu Peng , Li Yan , Liu Yifan , Qi Leijie , Xie Qing
Published: November 2021

Partial discharge (PD) detection and analysis plays a crucial role for acceptance testing and condition monitoring of power cables. Various aspects are related to PD in power cables from theory to practice. This paper first summarizes the PD mechanism and models used for PD analysis in power cables. Afterwards, PD detection is addressed in the aspects of off-line test, on-line test, and sensors. PD analysis is discussed in detail. Specifically, related quantities and algorithms for PD analysis are outlined. PD characteristics with affecting factors, e.g., dielectric type, load, and applied voltage are discussed. Experience on PD development trend with measurements in field is analyzed. Based on the comprehensive review, challenges of PD detection and analysis along a power cable are proposed.
Physically Motivated Water Modeling in Control-Oriented Polymer Electrolyte Membrane Fuel Cell Stack Models
Authors: Du Zhang Peng , Kravos Andraž , Steindl Christoph , Katrašnik Tomaž , Jakubek Stefan , Hametner Christoph
Published: November 2021

Polymer electrolyte membrane fuel cells (PEMFCs) are prone to membrane dehydration and liquid water flooding, negatively impacting their performance and lifetime. Therefore, PEMFCs require appropriate water management, which makes accurate water modeling indispensable. Unfortunately, available control-oriented models only replicate individual water-related aspects or use oversimplistic approximations. This paper resolves this challenge by proposing, for the first time, a control-oriented PEMFC stack model focusing on physically motivated water modeling, which covers phase change, liquid water removal, membrane water uptake, and water flooding effects on the electrochemical reaction. Parametrizing the resulting model with measurement data yielded the fitted model. The parameterized model delivers valuable insight into the water mechanisms, which were thoroughly analyzed. In summary, the proposed model enables the derivation of advanced control strategies for efficient water management and mitigation of the degradation phenomena of PEMFCs. Additionally, the model provides the required accuracy for control applications while maintaining the necessary computational efficiency.
Optimisation of the Two-Tier Distribution System in Omni-Channel Environment
Authors: Sawicki Piotr , Sawicka Hanna
Published: November 2021

This paper deals with the problem of the design and configuration of a distribution system that supports the delivery of goods to customers using various commercial channels. In this sense, a modelled distribution system, called an omni-channel distribution system, should ensure the delivery of the same products in different ways while guaranteeing its highest efficiency. The authors propose a single-criterion mixed-integer programming model for the configuration of a complex distribution system of goods in an omni-channel environment. A minimized cost function, composed of key logistics elements including transport, warehouse location, and manipulation processes, is the objective function. The model was experimentally verified, and as a result, potential savings of around 5–8% of the omni-channel design distribution system costs versus the multi-channel distribution system costs were identified. In the paper, an extended sensitivity analysis is also performed to show how specific parameters of the model can change the final recommendation.
Pharmacological Abortion in a Pandemic: An Italian Medico-Legal Perspective
Authors: Cestonaro Clara , Aprile Anna , Bolcato Matteo , Rodriguez Daniele , Feola Alessandro , Di Mizio Giulio
Published: November 2021

The limitations caused by the spread of the SARS-CoV2 virus have had repercussions on the voluntary termination of pregnancy. During the pandemic, Italy issued updated guidelines regarding voluntary termination of pregnancy by means of mifepristone and prostaglandin. This included news concerning the time limit and location in which this procedure could be accessed: updates partially recognize women’s needs, and they are into line with the European parliament’s recent exhortations. However, these updates do not change the previously provided responsibilities that lie with doctors. This article aimed to compare regulations concerning medical abortion in Italy and other countries, with a focus on recent Italian updates in the context of pandemic.
Transcriptome Profiles of Leaves and Roots of Goldenrain Tree (Koelreuteria paniculata Laxm.) in Response to Cadmium Stress
Authors: He Qihao , Zhou Tao , Sun Jikang , Wang Ping , Yang Chunping , Bai Lei , Liu Zhiming
Published: November 2021

Cadmium (Cd) pollution is a widespread environmental problem. In this study, we explored the transcriptome and biochemical responses of goldenrain tree (Koelreuteria paniculata Laxm.) leaves and roots to Cd stress. Leaf and root growth decreased substantially under Cd stress (50 mg/L CdCl2), but leaf and root antioxidant mechanisms were significantly activated. In RNA-seq analysis, roots treated with 25 mg/L CdCl2 featured enriched GO terms in cellular components related to intracellular ribonucleoprotein complex, ribonucleoprotein complex, and macromolecular complex. In leaves under Cd stress, most differentially expressed genes were enriched in the cellular component terms intrinsic component of membrane and membrane part. Weighted gene co-expression network analysis and analysis of module–trait relations revealed candidate genes associated with superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities and malondialdehyde (MDA). Ten transcription factors responded to Cd stress expression, including those in C2H2, MYB, WRKY, and bZIP families. Transcriptomic analysis of goldenrain tree revealed that Cd stress rapidly induced the intracellular ribonucleoprotein complex in the roots and the intrinsic component of membrane in the leaves. The results also indicate directions for further analyses of molecular mechanisms of Cd tolerance and accumulation in goldenrain tree.
Garden Access, Race and Vegetable Acquisition among U.S. Adults: Findings from a National Survey
Authors: Robinson-Oghogho Joelle N. , Thorpe Roland J.
Published: November 2021

With the majority of U.S. adults not meeting recommended vegetable intakes and well-documented racial and ethnic disparities in fruit and vegetable consumption, various approaches to increase vegetable consumption have been implemented. Gardening is one approach that has been associated with increased vegetable consumption in various subpopulations; however, limited national data exist examining this relationship. Since vegetable acquisition is a necessary antecedent to increased vegetable consumption, this study examines if garden access is associated with vegetable acquisition among adults in a nationally representative sample of U.S. households. Data come from the National Food Acquisition and Purchasing Survey (FAPS), a survey of 4826 US households. Descriptive analysis and modified Poisson regressions were performed to examine associations between household garden access and vegetable acquisition amongst the total population and by race. Results indicate that for foods for at-home consumption, respondents with their own garden had a 30% greater prevalence (PR: 1.30, 95% CI: 1.01, 1.64) of acquiring enough vegetables to meet USDA recommendations compared to respondents in households without access to any gardens. Among Black respondents, those with access to their own garden had over two times increased prevalence (PR: 2.35, 95% CI: 1.10, 5.01) of acquiring enough vegetables to meet recommended consumption amounts, compared to Black respondents without any access to a garden. No relationships between garden access and vegetable acquisition were observed for White or Asian respondents. This information may contribute to the body of evidence on strategies for increasing vegetable consumption among U.S. adults.
Housing and Health: Here We Go Again
Authors: Capasso Lorenzo , D’Alessandro Daniela
Published: November 2021

Housing is one of the major determinants of human health and the current COVID-19 pandemic has highlighted its relevance. The authors summarize the main issues, including dimensional standards, indoor air quality, safety, accessibility, neighborhoods, and area characteristics. The authors propose an operating scheme in order to implement actions to improve residential wellbeing on a local, national, and international level.
Mental Health of PhD Students at Polish Universities—Before the COVID-19 Outbreak
Authors: Kowalczyk Mateusz , Karbownik Michał Seweryn , Kowalczyk Edward , Sienkiewicz Monika , Talarowska Monika
Published: November 2021

Background: A group particularly exposed to the occurrence of disorders in the sphere of the psyche are young people with a newly developing personality structure and a sense of identity. In the available literature there are few reports describing the mental health of doctoral students—a group that is affected by a particular group of stressors. The aim of the research was to assess the mental health of PhD students at Polish universities. Material and Methods: The Polish adaptation of the GHQ Questionnaire-28, developed by David Goldberg et al. was used in the research. PhD students from all universities associated in the National Representation of Doctoral Students were invited to take part in the research. A total of 576 completed questionnaires were received. Results: It was found that depression is statistically more frequent in doctoral students who are not in any relationship with another person; anxiety/insomnia is more common in women than men and less frequently in doctoral students of general than in technical universities. Conclusions: (1) More than half of the surveyed students complain about the deterioration of mental health. The most commonly reported symptom groups are anxiety and insomnia, followed by social dysfunctions and somatic symptoms. (2) Depression is statistically more common in people who are not in any relationship with another person and anxiety and insomnia are statistically more common in women than in men and statistically less frequent in doctoral students of general universities than technical universities. (3) In view of the presented results, educating young adults in the field of self-awareness in the field of mental health seems to be particularly important.
Genomic Regions Associated with Fusarium Wilt Resistance in Flax
Authors: Kanapin Alexander , Bankin Mikhail , Rozhmina Tatyana , Samsonova Anastasia , Samsonova Maria
Published: November 2021

Modern flax cultivars are susceptible to many diseases; arguably, the most economically damaging of these is the Fusarium wilt fungal disease. Over the past decades international flax breeding initiatives resulted in the development of resistant cultivars. However, much remains to be learned about the mechanisms of resistance to Fusarium infection in flax. As a first step to uncover the genetic factors associated with resistance to Fusarium wilt disease, we performed a genome-wide association study (GWAS) using 297 accessions from the collection of the Federal Research Centre of the Bast Fiber Crops, Torzhok, Russia. These genotypes were infected with a highly pathogenic Fusarium oxysporum f.sp. lini MI39 strain; the wilt symptoms were documented in the course of three successive years. Six different single-locus models implemented in GAPIT3 R package were applied to a selected subset of 72,526 SNPs. A total of 15 QTNs (Quantitative Trait Nucleotides) were detected during at least two years of observation, while eight QTNs were found during all three years of the experiment. Of these, ten QTNs occupied a region of 640 Kb at the start of chromosome 1, while the remaining QTNs mapped to chromosomes 8, 11 and 13. All stable QTNs demonstrate a statistically significant allelic effect across 3 years of the experiment. Importantly, several QTNs spanned regions that harbored genes involved in the pathogen recognition and plant immunity response, including the KIP1-like protein (Lus10025717) and NBS-LRR protein (Lus10025852). Our results provide novel insights into the genetic architecture of flax resistance to Fusarium wilt and pinpoint potential candidate genes for further in-depth studies.
Lactoferrin Ameliorates Dry Eye Disease Potentially through Enhancement of Short-Chain Fatty Acid Production by Gut Microbiota in Mice
Authors: Connell Samuel , Kawashima Motoko , Nakamura Shigeru , Imada Toshihiro , Yamamoto Hiromitsu , Tsubota Kazuo , Fukuda Shinji
Published: November 2021

Lactoferrin is a glycoprotein found at high concentrations within exocrine secretions, including tears. Low levels of lactoferrin have been implicated in the loss of tear secretion and ageing. Furthermore, lactoferrin possesses a range of functionalities, including anti-inflammatory properties and the ability to modulate the gut microbiota. Expanding evidence demonstrates a crucial role of the gut microbiota in immune regulation and development. The specific composition of bacterial species of the gut has a profound influence on local and systemic inflammation, leading to a protective capacity against a number of inflammatory diseases, potentially by the induction of regulatory immune cells. In this study, we demonstrated that oral administration of lactoferrin maintains tear secretion in a restraint and desiccating stress induced mouse model of dry eye disease. Furthermore, we revealed that lactoferrin induces the reduction of inflammatory cytokines, modulates gut microbiota, and induces short-chain fatty acid production. Whereas, the antibiotic vancomycin abrogates the effects of lactoferrin on dry eye disease and significantly reduces short-chain fatty acid concentrations. Therefore, this protective effect of LF against a mice model of DED may be explained by our observations of an altered gut microbiota and an enhanced production of immunomodulatory short-chain fatty acids.
Molecular Mechanisms of Possible Action of Phenolic Compounds in COVID-19 Protection and Prevention
Authors: Gligorijevic Nikola , Radomirovic Mirjana , Nedic Olgica , Stojadinovic Marija , Khulal Urmila , Stanic-Vucinic Dragana , Cirkovic Velickovic Tanja
Published: November 2021

The worldwide outbreak of COVID-19 was caused by a pathogenic virus called Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Therapies against SARS-CoV-2 target the virus or human cells or the immune system. However, therapies based on specific antibodies, such as vaccines and monoclonal antibodies, may become inefficient enough when the virus changes its antigenicity due to mutations. Polyphenols are the major class of bioactive compounds in nature, exerting diverse health effects based on their direct antioxidant activity and their effects in the modulation of intracellular signaling. There are currently numerous clinical trials investigating the effects of polyphenols in prophylaxis and the treatment of COVID-19, from symptomatic, via moderate and severe COVID-19 treatment, to anti-fibrotic treatment in discharged COVID-19 patients. Antiviral activities of polyphenols and their impact on immune system modulation could serve as a solid basis for developing polyphenol-based natural approaches for preventing and treating COVID-19.
The Genetic, Environmental, and Immunopathological Complexity of Autoantibody-Negative Rheumatoid Arthritis
Authors: De Stefano Ludovico , D’Onofrio Bernardo , Manzo Antonio , Montecucco Carlomaurizio , Bugatti Serena
Published: November 2021

Differences in clinical presentation, response to treatment, and long-term outcomes between autoantibody-positive and -negative rheumatoid arthritis (RA) highlight the need for a better comprehension of the immunopathogenic events underlying the two disease subtypes. Whilst the drivers and perpetuators of autoimmunity in autoantibody-positive RA have started to be disclosed, autoantibody-negative RA remains puzzling, also due its wide phenotypic heterogeneity and its possible misdiagnosis. Genetic susceptibility appears to mostly rely on class I HLA genes and a number of yet unidentified non-HLA loci. On the background of such variable genetic predisposition, multiple exogeneous, endogenous, and stochastic factors, some of which are not shared with autoantibody-positive RA, contribute to the onset of the inflammatory cascade. In a proportion of the patients, the immunopathology of synovitis, at least in the initial stages, appears largely myeloid driven, with abundant production of proinflammatory cytokines and only minor involvement of cells of the adaptive immune system. Better understanding of the complexity of autoantibody-negative RA is still needed in order to open new avenues for targeted intervention and improve clinical outcomes.
Proteomics of Cryptococcus neoformans: From the Lab to the Clinic
Authors: Muselius Ben , Durand Shay-Lynn , Geddes-McAlister Jennifer
Published: November 2021

Fungal pathogens cause an array of diseases by targeting both immunocompromised and immunocompetent hosts. Fungi overcome our current arsenal of antifungals through the emergence and evolution of resistance. In particular, the human fungal pathogen, Cryptococcus neoformans is found ubiquitously within the environment and causes severe disease in immunocompromised individuals around the globe with limited treatment options available. To uncover fundamental knowledge about this fungal pathogen, as well as investigate new detection and treatment strategies, mass spectrometry-based proteomics provides a plethora of tools and applications, as well as bioinformatics platforms. In this review, we highlight proteomics approaches within the laboratory to investigate changes in the cellular proteome, secretome, and extracellular vesicles. We also explore regulation by post-translational modifications and the impact of protein–protein interactions. Further, we present the development and comprehensive assessment of murine models of cryptococcal infection, which provide valuable tools to define the dynamic relationship between the host and pathogen during disease. Finally, we explore recent quantitative proteomics studies that begin to extrapolate the findings from the bench to the clinic for improved methods of fungal detection and monitoring. Such studies support a framework for personalized medical approaches to eradicate diseases caused by C. neoformans.
Distinct and Overlapping Functions of Miscanthus sinensis MYB Transcription Factors SCM1 and MYB103 in Lignin Biosynthesis
Authors: Golfier Philippe , Ermakova Olga , Unda Faride , Murphy Emily K. , Xie Jianbo , He Feng , Zhang Wan , Lohmann Jan U. , Mansfield Shawn D. , Rausch Thomas , Wolf Sebastian
Published: November 2021

Cell wall recalcitrance is a major constraint for the exploitation of lignocellulosic biomass as a renewable resource for energy and bio-based products. Transcriptional regulators of the lignin biosynthetic pathway represent promising targets for tailoring lignin content and composition in plant secondary cell walls. However, knowledge about the transcriptional regulation of lignin biosynthesis in lignocellulosic feedstocks, such as Miscanthus, is limited. In Miscanthus leaves, MsSCM1 and MsMYB103 are expressed at growth stages associated with lignification. The ectopic expression of MsSCM1 and MsMYB103 in N. benthamiana leaves was sufficient to trigger secondary cell wall deposition with distinct sugar and lignin compositions. Moreover, RNA-seq analysis revealed that the transcriptional responses to MsSCM1 and MsMYB103 overexpression showed an extensive overlap with the response to the NAC master transcription factor MsSND1, but were distinct from each other, underscoring the inherent complexity of secondary cell wall formation. Furthermore, conserved and previously described promoter elements as well as novel and specific motifs could be identified from the target genes of the three transcription factors. Together, MsSCM1 and MsMYB103 represent interesting targets for manipulations of lignin content and composition in Miscanthus towards a tailored biomass.
Ultraviolet Treatment of Titanium to Enhance Adhesion and Retention of Oral Mucosa Connective Tissue and Fibroblasts
Authors: Ikeda Takayuki , Ueno Takeshi , Saruta Juri , Hirota Makoto , Park Wonhee , Ogawa Takahiro
Published: November 2021

Peri-implantitis is an unsolved but critical problem with dental implants. It is postulated that creating a seal of gingival soft tissue around the implant neck is key to preventing peri-implantitis. The objective of this study was to determine the effect of UV surface treatment of titanium disks on the adhesion strength and retention time of oral connective tissues as well as on the adherence of mucosal fibroblasts. Titanium disks with a smooth machined surface were prepared and treated with UV light for 15 min. Keratinized mucosal tissue sections (3 × 3 mm) from rat palates were incubated for 24 h on the titanium disks. The adhered tissue sections were then mechanically detached by agitating the culture dishes. The tissue sections remained adherent for significantly longer (15.5 h) on the UV-treated disks than on the untreated control disks (7.5 h). A total of 94% of the tissue sections were adherent for 5 h or longer on the UV-treated disks, whereas only 50% of the sections remained on the control disks for 5 h. The adhesion strength of the tissue sections to the titanium disks, as measured by tensile testing, was six times greater after UV treatment. In the culture studies, mucosal fibroblasts extracted from rat palates were attached to titanium disks by incubating for 24, 48, or 96 h. The number of attached cells was consistently 15–30% greater on the UV-treated disks than on the control disks. The cells were then subjected to mechanical or chemical (trypsinization) detachment. After mechanical detachment, the residual cell rates on the UV-treated surfaces after 24 and 48 h of incubation were 35% and 25% higher, respectively, than those on the control surfaces. The remaining rate after chemical detachment was 74% on the control surface and 88% on the UV-treated surface for the cells cultured for 48 h. These trends were also confirmed in mouse embryonic fibroblasts, with an intense expression of vinculin, a focal adhesion protein, on the UV-treated disks even after detachment. The UV-treated titanium was superhydrophilic, whereas the control titanium was hydrophobic. X-ray photoelectron spectroscopy (XPS) chemical analysis revealed that the amount of carbon at the surface was significantly reduced after UV treatment, while the amount of TiOH molecules was increased. These ex vivo and in vitro results indicate that the UV treatment of titanium increases the adhesion and retention of oral mucosa connective tissue as a result of increased resistance of constituent fibroblasts against exogenous detachment, both mechanically and chemically, as well as UV-induced physicochemical changes of the titanium surface.
The Effectiveness in Activating M-Type K+ Current Produced by Solifenacin ([(3R)-1-azabicyclo[2.2.2]octan-3-yl] (1S)-1-phenyl-3,4-dihydro-1H-isoquinoline-2-carboxylate): Independent of Its Antimuscarinic Action
Authors: Cho Hsin-Yen , Chuang Tzu-Hsien , Wu Sheng-Nan
Published: November 2021

Solifenacin (Vesicare®, SOL), known to be a member of isoquinolines, is a muscarinic antagonist that has anticholinergic effect, and it has been beneficial in treating urinary incontinence and neurogenic detrusor overactivity. However, the information regarding the effects of SOL on membrane ionic currents is largely uncertain, despite its clinically wide use in patients with those disorders. In this study, the whole-cell current recordings revealed that upon membrane depolarization in pituitary GH3 cells, the exposure to SOL concentration-dependently increased the amplitude of M-type K+ current (IK(M)) with effective EC50 value of 0.34 μM. The activation time constant of IK(M) was concurrently shortened in the SOL presence, hence yielding the KD value of 0.55 μM based on minimal reaction scheme. As cells were exposed to SOL, the steady-state activation curve of IK(M) was shifted along the voltage axis to the left with no change in the gating charge of the current. Upon an isosceles-triangular ramp pulse, the hysteretic area of IK(M) was increased by adding SOL. As cells were continually exposed to SOL, further application of acetylcholine (1 μM) failed to modify SOL-stimulated IK(M); however, subsequent addition of thyrotropin releasing hormone (TRH, 1 μM) was able to counteract SOL-induced increase in IK(M) amplitude. In cell-attached single-channel current recordings, bath addition of SOL led to an increase in the activity of M-type K+ (KM) channels with no change in the single channel conductance; the mean open time of the channel became lengthened. In whole-cell current-clamp recordings, the SOL application reduced the firing of action potentials (APs) in GH3 cells; however, either subsequent addition of TRH or linopirdine was able to reverse SOL-mediated decrease in AP firing. In hippocampal mHippoE-14 neurons, the IK(M) was also stimulated by adding SOL. Altogether, findings from this study disclosed for the first time the effectiveness of SOL in interacting with KM channels and hence in stimulating IK(M) in electrically excitable cells, and this noticeable action appears to be independent of its antagonistic activity on the canonical binding to muscarinic receptors expressed in GH3 or mHippoE-14 cells.
Cold Rolling Texture Prediction Using Finite Element Simulation with Zooming Analysis
Authors: Wang Honghao , Ding Sheng , Taylor Tom , Yanagimoto Jun
Published: November 2021

Cold rolling is widely employed in the manufacturing industry for the production of metal plates. In the cold rolling process, the thickness reduction of the metal plate under the recrystallization temperature generates severe anisotropy; this influences the subsequent forming processes. Therefore, the generation and prediction of metal plate anisotropy during cold rolling is a highly interesting research topic involving upstream studies of sheet metal forming. In this study, using the finite element method with zooming analysis, we established an efficient elastic–plastic analysis method to predict the metal plate texture after cold rolling. This method for cold rolling texture prediction was confirmed by comparing the experimental and simulation results of cold rolling for an S45C plate with a body-centered cubic lattice. Further, the numerical analysis method proposed in this study can contribute to the study of anisotropy as an alternative to experimental approaches.
Experimental Study on Single Corner Cold Bending Mechanical Response of Laminated of PVB Interlayer Tempered Glass Panes and the Coupling Effect with Load
Authors: Zhang Xide , Zhou Wei , Xu Mingcai
Published: November 2021

The cold bending method is a type of curved glass curtain wall construction method that has been used in practical engineering for a short time. It has the advantages of simple operation, high efficiency and low cost. However, the mechanical response and properties of glass panes caused by cold bending have not been solved effectively. To study the mechanical response and the properties of cold formed laminated tempered glass panes after applying with a wind load, cold bending and load tests of 9 laminated tempered glass panes were conducted by the orthogonal experimental design method. The effects of cold bending curvature, glass pane thickness and interlayer thickness were considered. In this paper, the response law of cold bending stress to the curvature and the relationship among the influencing factors were analyzed. The variation process of stress, the deflection of cold-formed glass panes under uniform load and the characteristics affected by cold-formed stress and deformation were studied. The results show that the cold bending stress is distributed in a saddle shape, and the curvature has the greatest influence on the cold bending stress, followed by the thickness of the glass panes. The influence of the interlayer thickness is small. The maximum stress appears near the corner of the short side direction adjacent to the cold bending corner. The cold bending stress increases linearly with increasing cold bending curvature. The cold bending stress and deformation have little effect on the change process of the later stage load effect.
Informing Stewardship Measures in Canadian Food Animal Species through Integrated Reporting of Antimicrobial Use and Antimicrobial Resistance Surveillance Data—Part I, Methodology Development
Authors: Agunos Agnes , Gow Sheryl P. , Deckert Anne E. , Kuiper Grace , Léger David F.
Published: November 2021

This study explores methodologies for the data integration of antimicrobial use (AMU) and antimicrobial resistance (AMR) results within and across three food animal species, surveyed at the farm-level by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS). The approach builds upon existing CIPARS methodology and principles from other AMU and AMR surveillance systems. Species level data integration involved: (1) standard CIPARS descriptive and temporal analysis of AMU/AMR, (2) synthesis of results, (3) selection of AMU and AMR outcomes for integration, (4) selection of candidate AMU indicators to enable comparisons of AMU levels between species and simultaneous assessment of AMU and AMR trends, (5) exploration of analytic options for studying associations between AMU and AMR, and (6) interpretation and visualization. The multi-species integration was also completed using the above approach. In addition, summarized reporting of internationally-recognized indicators of AMR (i.e., AMR adjusted for animal biomass) and AMU (mg/population correction unit, mg/kg animal biomass) is explored. It is envisaged that this approach for species and multi-species AMU–AMR data integration will be applied to the annual CIPARS farm-level data and progressively developed over time to inform AMU–AMR integrated surveillance best practices for further enhancement of AMU stewardship actions.
Monitoring Illegal Tree Cutting through Ultra-Low-Power Smart IoT Devices
Authors: Andreadis Alessandro , Giambene Giovanni , Zambon Riccardo
Published: November 2021

Forests play a fundamental role in preserving the environment and fighting global warming. Unfortunately, they are continuously reduced by human interventions such as deforestation, fires, etc. This paper proposes and evaluates a framework for automatically detecting illegal tree-cutting activity in forests through audio event classification. We envisage ultra-low-power tiny devices, embedding edge-computing microcontrollers and long-range wireless communication to cover vast areas in the forest. To reduce the energy footprint and resource consumption for effective and pervasive detection of illegal tree cutting, an efficient and accurate audio classification solution based on convolutional neural networks is proposed, designed specifically for resource-constrained wireless edge devices. With respect to previous works, the proposed system allows for recognizing a wider range of threats related to deforestation through a distributed and pervasive edge-computing technique. Different pre-processing techniques have been evaluated, focusing on a trade-off between classification accuracy with respect to computational resources, memory, and energy footprint. Furthermore, experimental long-range communication tests have been conducted in real environments. Data obtained from the experimental results show that the proposed solution can detect and notify tree-cutting events for efficient and cost-effective forest monitoring through smart IoT, with an accuracy of 85%.
Experimental FIA Methodology Using Clock and Control Signal Modifications under Power Supply and Temperature Variations
Authors: Potestad-Ordóñez Francisco Eugenio , Tena-Sánchez Erica , Mora-Gutiérrez José Miguel , Valencia-Barrero Manuel , Jiménez-Fernández Carlos Jesús
Published: November 2021

The security of cryptocircuits is determined not only for their mathematical formulation, but for their physical implementation. The so-called fault injection attacks, where an attacker inserts faults during the operation of the cipher to obtain a malfunction to reveal secret information, pose a serious threat for security. These attacks are also used by designers as a vehicle to detect security flaws and then protect the circuits against these kinds of attacks. In this paper, two different attack methodologies are presented based on inserting faults through the clock signal or the control signal. The optimization of the attacks is evaluated under supply voltage and temperature variation, experimentally determining the feasibility through the evaluation of different Trivium versions in 90 nm ASIC technology implementations, also considering different routing alternatives. The results show that it is possible to inject effective faults with both methodologies, improving fault efficiency if the power supply voltage decreases, which requires only half the frequency of the short pulse inserted into the clock signal to obtain a fault. The clock signal modification methodology can be extended to other NLFSR-based cryptocircuits and the control signal-based methodology can be applied to both block and stream ciphers.
Bandwidth-Based Wake-Up Radio Solution through IEEE 802.11 Technology
Authors: Lopez-Aguilera Elena , Garcia-Villegas Eduard
Published: November 2021

IEEE 802.11 consists of one of the most used wireless access technologies, which can be found in almost all consumer electronics devices available. Recently, Wake-up Radio (WuR) systems have emerged as a solution for energy-efficient communications. WuR mechanisms rely on using a secondary low-power radio interface that is always in the active operation mode and is in charge of switching the primary interface, used for main data exchange, from the power-saving state to the active mode. In this paper, we present a WuR solution based on IEEE 802.11 technology employing transmissions of legacy frames by an IEEE 802.11 standard-compliant transmitter during a Transmission Opportunity (TXOP) period. Unlike other proposals available in the literature, the WuR system presented in this paper exploits the PHY characteristics of modern IEEE 802.11 radios, where different signal bandwidths can be used on a per-packet basis. The proposal is validated through the Matlab software tool, and extensive simulation results are presented in a wide variety of scenario configurations. Moreover, insights are provided on the feasibility of the WuR proposal for its implementation in real hardware. Our approach allows the transmission of complex Wake-up Radio signals (i.e., including address field and other binary data) from legacy Wi-Fi devices (from IEEE 802.11n-2009 on), avoiding hardware or even firmware modifications intended to alter standard MAC/PHY behavior, and achieving a bit rate of up to 33 kbps.
Automated Quantification of Brittle Stars in Seabed Imagery Using Computer Vision Techniques
Authors: Buškus Kazimieras , Vaičiukynas Evaldas , Verikas Antanas , Medelytė Saulė , Šiaulys Andrius , Šaškov Aleksej
Published: November 2021

Underwater video surveys play a significant role in marine benthic research. Usually, surveys are filmed in transects, which are stitched into 2D mosaic maps for further analysis. Due to the massive amount of video data and time-consuming analysis, the need for automatic image segmentation and quantitative evaluation arises. This paper investigates such techniques on annotated mosaic maps containing hundreds of instances of brittle stars. By harnessing a deep convolutional neural network with pre-trained weights and post-processing results with a common blob detection technique, we investigate the effectiveness and potential of such segment-and-count approach by assessing the segmentation and counting success. Discs could be recommended instead of full shape masks for brittle stars due to faster annotation among marker variants tested. Underwater image enhancement techniques could not improve segmentation results noticeably, but some might be useful for augmentation purposes.
CyberEye: New Eye-Tracking Interfaces for Assessment and Modulation of Cognitive Functions beyond the Brain
Authors: Lech Michał , Czyżewski Andrzej , Kucewicz Michał T.
Published: November 2021

The emergence of innovative neurotechnologies in global brain projects has accelerated research and clinical applications of BCIs beyond sensory and motor functions. Both invasive and noninvasive sensors are developed to interface with cognitive functions engaged in thinking, communication, or remembering. The detection of eye movements by a camera offers a particularly attractive external sensor for computer interfaces to monitor, assess, and control these higher brain functions without acquiring signals from the brain. Features of gaze position and pupil dilation can be effectively used to track our attention in healthy mental processes, to enable interaction in disorders of consciousness, or to even predict memory performance in various brain diseases. In this perspective article, we propose the term ‘CyberEye’ to encompass emerging cognitive applications of eye-tracking interfaces for neuroscience research, clinical practice, and the biomedical industry. As CyberEye technologies continue to develop, we expect BCIs to become less dependent on brain activities, to be less invasive, and to thus be more applicable.
Heat Balance Calculation and Energy Efficiency Analysis for Building Clusters Based on Psychrometric Chart
Authors: Yang Shihai , Su Huiling , Dou Xun , Chen Mingming , Huang Yixuan
Published: November 2021

How to perform accurate calculation of heat balance and quantitative analysis of energy efficiency for building clusters is an urgent problem to be solved to reduce building energy consumption and improve energy utilization efficiency. This article proposes a method for the heat balance calculation and energy efficiency analysis of building clusters based on enthalpy and humidity diagrams and applies it to the energy management of building clusters containing primary return air systems and heating pipe networks. Firstly, the basic structure and energy management principle of building clusters with a primary return air system and a heating pipe network were given, and the heat balance calculation and energy efficiency analysis method based on i-d diagram was proposed to realize the accurate calculation of heat load and the quantification of energy utilization. Secondly, the energy management model of the building cluster with a primary return air system and a heating pipe network was established to efficiently manage the indoor temperature and the heating schedule of ASHP, HN and HI. Finally, the proposed method was validated by calculation examples, and the results showed that the proposed method is beneficial for improving the energy economy and energy efficiency of building clusters.
An Efficient Content Store-Based Forwarding Scheme for Internet of Things
Authors: Dinh Ngoc-Thanh , Kim Younghan
Published: November 2021

One of the main advantages of information-centric networking (ICN) is that a requested piece of content can be retrieved from a content store (CS) at any intermediate node, instead of its original content producer. In existing ICN designs, nodes forward Interest packets mainly based on forwarding information base (FIB). FIB is constructed from name prefixes registered by content producers with a list of next hops to the name prefixes. The ICN forwarding engine uses those information to forward Interest packets towards corresponding content producers. CS information of a node is currently used only for checking the availability of cached content objects at the node and is not considered in the data plane of existing ICN forwarding mechanisms. This paper highlights the importance of CS information in an ICN forwarding mechanism and enables neighbor CS information in the data plane to improve the cache hit ratio and forwarding efficiency, especially for resource-constraint Internet of Things (IoT). We propose an efficient CS-based forwarding scheme for IoT. The proposed forwarding scheme exploits CS information of neighbors to find efficient routes to forward Interest packets toward nearby nodes with corresponding cached content. For that, we carefully design an efficient way for CS information sharing using counting bloom filter. We implement the proposed scheme and compare with state-of-the-art ICN forwarding schemes in IoT. Experimental results indicate that the proposed forwarding scheme achieves a significant improvement in terms of cache hit ratio, energy efficiency, content retrieval latency, and response rate.
Insect-Inspired Robots: Bridging Biological and Artificial Systems
Authors: Manoonpong Poramate , Patanè Luca , Xiong Xiaofeng , Brodoline Ilya , Dupeyroux Julien , Viollet Stéphane , Arena Paolo , Serres Julien R.
Published: November 2021

This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.
Video Desnowing and Deraining via Saliency and Dual Adaptive Spatiotemporal Filtering
Authors: Li Yongji , Wu Rui , Jia Zhenhong , Yang Jie , Kasabov Nikola
Published: November 2021

Outdoor vision sensing systems often struggle with poor weather conditions, such as snow and rain, which poses a great challenge to existing video desnowing and deraining methods. In this paper, we propose a novel video desnowing and deraining model that utilizes the salience information of moving objects to address this problem. First, we remove the snow and rain from the video by low-rank tensor decomposition, which makes full use of the spatial location information and the correlation between the three channels of the color video. Second, because existing algorithms often regard sparse snowflakes and rain streaks as moving objects, this paper injects salience information into moving object detection, which reduces the false alarms and missed alarms of moving objects. At the same time, feature point matching is used to mine the redundant information of moving objects in continuous frames, and a dual adaptive minimum filtering algorithm in the spatiotemporal domain is proposed by us to remove snow and rain in front of moving objects. Both qualitative and quantitative experimental results show that the proposed algorithm is more competitive than other state-of-the-art snow and rain removal methods.
Dynamic Bargain Game Theory in the Internet of Things for Data Trustworthiness
Authors: Sumathi Appasamy , Akila Muthuramalingam , Pérez de Prado Rocío , Wozniak Marcin , Divakarachari Parameshachari
Published: November 2021

Smart home and smart building systems based on the Internet of Things (IoT) in smart cities currently suffer from security issues. In particular, data trustworthiness and efficiency are two major concerns in Internet of Things (IoT)-based Wireless Sensor Networks (WSN). Various approaches, such as routing methods, intrusion detection, and path selection, have been applied to improve the security and efficiency of real-time networks. Path selection and malicious node discovery provide better solutions in terms of security and efficiency. This study proposed the Dynamic Bargaining Game (DBG) method for node selection and data transfer, to increase the data trustworthiness and efficiency. The data trustworthiness and efficiency are considered in the Pareto optimal solution to select the node, and the bargaining method assigns the disagreement measure to the nodes to eliminate the malicious nodes from the node selection. The DBG method performs the search process in a distributed manner that helps to find an effective solution for the dynamic networks. In this study, the data trustworthiness was measured based on the node used for data transmission and throughput was measured to analyze the efficiency. An SF attack was simulated in the network and the packet delivery ratio was measured to test the resilience of the DBG and existing methods. The results of the packet delivery ratio showed that the DBG method has higher resilience than the existing methods in a dynamic network. Moreover, for 100 nodes, the DBG method has higher data trustworthiness of 98% and throughput of 398 Mbps, whereas the existing fuzzy cross entropy method has data trustworthiness of 94% and a throughput of 334 Mbps.