bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Collagen Types, Bacterial Strains and Storage Duration on the Quality of Probiotic Fermented Sheep’s Milk
Authors: Szopa Kamil , Znamirowska-Piotrowska Agata , Szajnar Katarzyna , Pawlos Małgorzata
Published: May 2022

Collagen has become popular in dietary supplements, beverages and sports nutrition products. Therefore, the aim of this study was to evaluate the possibility of using various doses of collagen and collagen hydrolysate to produce probiotic sheep’s milk fermented with Lactobacillus acidophilus, Lacticaseibacillus casei, Lacticaseibacillus paracasei and Lacticaseibacillus rhamnosus. The effects of storage time, type and dose of collagen, and different probiotic bacteria on the physicochemical, organoleptic and microbiological properties of fermented sheep’s milk at 1 and 21 days of refrigerated storage were investigated. The addition of collagen to sheep’s milk increased the pH value after fermentation and reduced the lactic acid contents of fermented milk compared to control samples. After fermentation, the number of probiotic bacteria cells was higher than 8 log cfu g−1. In sheep’s milk fermented by L. acidophilus and L. casei, good survival of bacteria during storage was observed, and there was no effect of collagen dose on the growth and survival of both strains. The addition of collagen, both in the form of hydrolysate and bovine collagen, resulted in darkening of the color of the milk and increased the sweet taste intensity of the fermented sheep’s milk. However, the addition of hydrolysate was effective in reducing syneresis in each milk sample compared to its control counterpart.
Nanostructured Biomaterials for Tissue Repair and Anti-Infection
Authors: Qiu Jiajun , Liu Xuanyong
Published: May 2022

Biomaterials play a vital role in regenerative medicine, aiming to regenerate and replace lost/dysfunctional tissues [...]
Comprehensive Transcriptional Profiling and Mouse Phenotyping Reveals Dispensable Role for Adipose Tissue Selective Long Noncoding RNA Gm15551
Authors: Engelhard Christoph Andreas , Huang Chien , Khani Sajjad , Kasparek Petr , Prochazka Jan , Rozman Jan , Reguera David Pajuelo , Sedlacek Radislav , Kornfeld Jan-Wilhelm
Published: May 2022

Cold and nutrient-activated brown adipose tissue (BAT) is capable of increasing systemic energy expenditure via the uncoupled respiration and secretion of endocrine factors, thereby protecting mice against diet-induced obesity and improving insulin response and glucose tolerance in men. Long non-coding RNAs (lncRNAs) have recently been identified as fine-tuning regulators of cellular function. While certain lncRNAs have been functionally characterised in adipose tissue, their overall contribution in the activation of BAT remains elusive. We identified lncRNAs correlating to interscapular brown adipose tissue (iBAT) function in a high fat diet (HFD) and cold stressed mice. We focused on Gm15551, which has an adipose tissue specific expression profile, is highly upregulated during adipogenesis, and downregulated by β-adrenergic activation in mature adipocytes. Although we performed comprehensive transcriptional and adipocyte physiology profiling in vitro and in vivo, we could not detect an effect of gain or loss of function of Gm15551.
Antimicrobial Resistance and Molecular Epidemiology of Staphylococcus aureus from Hunters and Hunting Dogs
Authors: Silva Vanessa , Caniça Manuela , Manageiro Vera , Vieira-Pinto Madalena , Pereira José Eduardo , Maltez Luís , Poeta Patrícia , Igrejas Gilberto
Published: May 2022

Several studies have showed that a dog-to-human transmission of Staphylococcus aureus occurs. Hunting dogs do not have as much contact with their owners as dogs that live in the same household as the owners; however, these dogs have contact with their owners during hunting activities as well as when hunting game; therefore, we aimed to isolate S. aureus from hunters and their hunting dogs to investigate a possible S. aureus transmission. Nose and mouth samples were collected from 30 hunters and their 78 hunting dogs for staphylococcal isolation. The species identification was performed using MALDI-TOF. The antimicrobial susceptibility profiles were accessed using the Kirby–Bauer method and respective antimicrobial resistance genes were investigated by PCR. Multilocus sequence typing (MLST) and spa- and agr-typing was performed in all S. aureus isolates. S. aureus were detected in 10 (30%) human samples and in 11 (15.4%) dog samples of which 11 and 5 were methicillin-resistant S. aureus (MRSA). Other staphylococci were identified, particularly, S. pseudintermedius. Most S. aureus isolates were resistant to penicillin, erythromycin, and tetracycline. Evidence of a possible transmission of S. aureus between human and dogs was detected in three hunters and their dogs. S. aureus isolates were ascribed to 10 STs and 9 spa-types. A moderate colonization of S. aureus in hunting dogs and their owners was detected in this study. A few dog-to-dog and dog-to-human possible transmissions were identified.
Wild Bird Densities and Landscape Variables Predict Spatial Patterns in HPAI Outbreak Risk across The Netherlands
Authors: Schreuder Janneke , de Knegt Henrik J. , Velkers Francisca C. , Elbers Armin R. W. , Stahl Julia , Slaterus Roy , Stegeman J. Arjan , de Boer Willem F.
Published: May 2022

Highly pathogenic avian influenza viruses’ (HPAIVs) transmission from wild birds to poultry occurs globally, threatening animal and public health. To predict the HPAI outbreak risk in relation to wild bird densities and land cover variables, we performed a case-control study of 26 HPAI outbreaks (cases) on Dutch poultry farms, each matched with four comparable controls. We trained machine learning classifiers to predict outbreak risk with predictors analyzed at different spatial scales. Of the 20 best explaining predictors, 17 consisted of densities of water-associated bird species, 2 of birds of prey, and 1 represented the surrounding landscape, i.e., agricultural cover. The spatial distribution of mallard (Anas platyrhynchos) contributed most to risk prediction, followed by mute swan (Cygnus olor), common kestrel (Falco tinnunculus) and brant goose (Branta bernicla). The model successfully distinguished cases from controls, with an area under the receiver operating characteristic curve of 0.92, indicating accurate prediction of HPAI outbreak risk despite the limited numbers of cases. Different classification algorithms led to similar predictions, demonstrating robustness of the risk maps. These analyses and risk maps facilitate insights into the role of wild bird species and support prioritization of areas for surveillance, biosecurity measures and establishments of new poultry farms to reduce HPAI outbreak risks.
Immunogenicity Analysis of the Recombinant Plasmodium falciparum Surface-Related Antigen in Mice
Authors: Yu Jia-Li , Liu Qing-Yang , Yang Bo , Sun Yi-Fan , Wang Ya-Ju , Jiang Jian , Wang Bo , Cheng Yang , Wang Qiu-Bo
Published: May 2022

Plasmodium falciparum, mainly distributed in tropical and subtropical regions of the world, has received widespread attention owing to its severity. As a novel protein, P. falciparum surface-related antigen (PfSRA) has the structural and functional characteristics to be considered as a malaria vaccine candidate; however, limited information is available on its immunogenicity. Here, we expressed three fragments of recombinant PfSRA in an Escherichia coli system and further analyzed its immunogenicity. The results showed that rPfSRA-immunized mice produced specific antibodies with high endpoint titers (1:10,000 to 1:5,120,000) and affinity antibodies (i.e., rPfSRA-F1a (97.70%), rPfSRA-F2a (69.62%), and rPfSRA-F3a (91.87%)). In addition, the sera of immunized mice recognized both the native PfSRA and recombinant PfSRA, the rPfSRA antibodies inhibited the invasion of P. falciparum into the erythrocytes, and they were dose-dependent in vitro. This study confirmed PfSRA could be immunogenic, especially the F1a at the conserved region N-terminal and provided further support for it as a vaccine candidate against P.falciparum.
Possible Association between Selected Tick-Borne Pathogen Prevalence and Rhipicephalus sanguineus sensu lato Infestation in Dogs from Juarez City (Chihuahua), Northwest Mexico–US Border
Authors: Beristain-Ruiz Diana , Garza-Hernández Javier , Figueroa-Millán Julio , Lira-Amaya José , Quezada-Casasola Andrés , Ordoñez-López Susana , Laredo-Tiscareño Stephanie , Alvarado-Robles Beatriz , Castillo-Luna Oliver , Floriano-López Adriana , Hernández-Triana Luis , Martínez-Ibáñez Francisco , Rivera-Barreno Ramón , Rodríguez-Alarcón Carlos
Published: May 2022

Tick-borne bacterial pathogens (TBBPs) show a worldwide distribution and represent a great impact on public health. The brown dog tick (Rhipicephalus sanguineus) is a vector of several pathogens that affect dogs and sometimes humans as well. In addition, TBBPs represent a diagnostic challenge and imply financial resources and medical treatment for long periods of time. In the present study, R. sanguineus s. l. was identified as the main tick species naturally parasitizing dogs that inhabit. Juárez City, Chihuahua, in the Paso del Norte region, Mexico–US Border, representing 99.8% of the cases. Additionally, an end-point PCR was performed to search for whether pathogens in R. sanguineus s. l. can transmit in DNA extracted from ticks and dog blood samples. This is the first molecular detection of Rickettsia rickettsi infecting domestic dogs in Mexico; however, other pathogens were also identified, such as Ehrlichia canis and Anaplasma platys in both ticks and dog blood samples, while Anaplasma phagocytophilum was identified only in dog blood samples. Moreover, co-detection in tick pools and co-infection in the analyzed dog blood samples could be found. Similarly, this research showed that dogs were found mostly parasitized by adult female ticks, increasing the possibility of transmission of E. canis.
The Multifaceted Manifestations of Multisystem Inflammatory Syndrome during the SARS-CoV-2 Pandemic
Authors: Pérez-Gómez Héctor Raúl , Morfín-Otero Rayo , González-Díaz Esteban , Esparza-Ahumada Sergio , León-Garnica Gerardo , Rodríguez-Noriega Eduardo
Published: May 2022

The novel coronavirus SARS-CoV-2, which has similarities to the 2002–2003 severe acute respiratory syndrome coronavirus known as SARS-CoV-1, causes the infectious disease designated COVID-19 by the World Health Organization (Coronavirus Disease 2019). Although the first reports indicated that activity of the virus is centered in the lungs, it was soon acknowledged that SARS-CoV-2 causes a multisystem disease. Indeed, this new pathogen causes a variety of syndromes, including asymptomatic disease; mild disease; moderate disease; a severe form that requires hospitalization, intensive care, and mechanical ventilation; multisystem inflammatory disease; and a condition called long COVID or postacute sequelae of SARS-CoV-2 infection. Some of these syndromes resemble previously described disorders, including those with no confirmed etiology, such as Kawasaki disease. After recognition of a distinct multisystem inflammatory syndrome in children, followed by a similar syndrome in adults, various multisystem syndromes occurring during the pandemic associated or related to SARS-CoV-2 began to be identified. A typical pattern of cytokine and chemokine dysregulation occurs in these complex syndromes; however, the disorders have distinct immunological determinants that may help to differentiate them. This review discusses the origins of the different trajectories of the inflammatory syndromes related to SARS-CoV-2 infection.
The Politician: Action and Creation in the Practical Ontology of Gilles Deleuze
Authors: Ferreyra Julian
Published: May 2022

This paper addresses an action that, from a Deleuzian perspective, is capable of modifying the despairing current social situation in which we are immersed, through the creation of political Ideas. Even though Deleuze conceives social Ideas as vast civilizing structures, we propose to bring into the political domain the logic of other acts of creation, such as the artistic or the philosophical, where the monumental coexists with minor figures that are nonetheless capable of introducing novelty into the world. The politician is the figure of those who are capable of having an Idea that allows to break the habits that perpetuate the current situation, and gives consistency to the intensive forms of life that continually create and dissolve themselves in the flow of becoming. Thus, macro- and micro-politics do not oppose each other, but offer in their immanence an alternative to social nihilism.
Instantaneous Photocarrier Transport at the Interface in Perovskite Solar Cells to Generate Photovoltage
Authors: Mochizuki Toshimitsu , Kawayama Iwao , Tonouchi Masayoshi , Nishihara Yoshihiko , Chikamatsu Msayuki , Yoshida Yuji , Takato Hidetaka
Published: May 2022

The instantaneous photocarrier transport of perovskite solar cells was evaluated by assessing laser-induced terahertz (THz) emission to understand carrier dynamics in perovskite solar cells. The waveform of laser-induced THz radiation from an interface between the TiO2 electron transport layer and perovskite active layer of an n-i-p perovskite solar cell with varying external bias was measured using THz-time domain spectroscopy. The amplitude of the THz radiation decreased with increasing reverse bias voltage. The waveform of the THz radiation was inverted at a strong reverse bias. The measured bias voltage dependence suggests that the transient current generated at the interface between perovskite and TiO2 owing to the higher mobility of electrons than that of holes, namely the photo-Dember effect, is the dominant source of THz radiation and the destructive contribution of the interfacial electric field inverts the transient current when a reverse bias causes a strong interfacial electric field. The significant contribution of the interfacial electric field has not been previously reported in perovskite thin films and is unique to solar cells. We believe that band bending at interfaces in perovskite solar cells will be determined from the THz emission with proper modeling.
State-of-the-Art Technologies in Piezoelectric Deformable Mirror Design
Authors: Toporovsky Vladimir , Kudryashov Alexis , Skvortsov Arkadiy , Rukosuev Alexey , Samarkin Vadim , Galaktionov Ilya
Published: May 2022

In this work, two advanced technologies were applied for manufacturing a bimorph wavefront corrector: laser ablation, to vaporize conductive silver coating from piezoceramic surface, and parallel-gap resistance microwelding, to provide a reliable electrical contact between the piezodisk surface silver electrodes and copper wires. A step-by-step guide for bimorph mirror production is presented, together with the ‘bottlenecks’. Optimization of the laser ablation technique was carried out using an Nd:YAG laser with an output power of 4 W and a frequency of 20 kHz. A comparison of the ultrasonic welding and parallel-gap resistance microwelding methods was performed. The tensile strength in the first case was in the range of 0.2…0.25 N for the system ‘copper wire–silver coating’. The use of resistance welding made it possible to increase the value of this parameter for the same contact pair by almost two times (0.45…0.5 N).
Foliar Diseases and the Associated Fungi in Rice Cultivated in Kenya
Authors: Nganga Everlyne M. , Kyallo Martina , Orwa Philemon , Rotich Felix , Gichuhi Emily , Kimani John M. , Mwongera David , Waweru Bernice , Sikuku Phoebe , Musyimi David M. , Mutiga Samuel K. , Ziyomo Cathrine , Murori Rosemary , Wasilwa Lusike , Correll James C. , Talbot Nicholas J.
Published: May 2022

We conducted a survey to assess the occurrence and severity of rice blast and brown spot diseases on popular cultivars grown in the Busia, Kirinyaga, and Kisumu counties of Kenya in 2019. Working with agricultural extension workers within rice production areas, we interviewed farmers (n = 89) regarding their preferred cultivars and their awareness of blast disease, as this was the major focus of our research. We scored the symptoms of blast and brown spot and assessed the lodging, plant height, and maturity of the crops (days after planting). Furthermore, we collected leaf and neck tissues for the assessment of the prevailing fungal populations. We used specific DNA primers to screen for the prevalence of the causal pathogens of blast, Magnaporthe oryzae, and brown spot, Cochliobolus miyabeanus, on asymptomatic and symptomatic leaf samples. We also conducted fungal isolations and PCR-sequencing to identify the fungal species in these tissues. Busia and Kisumu had a higher diversity of cultivars compared to Kirinyaga. The aromatic Pishori (NIBAM 11) was preferred and widely grown for commercial purposes in Kirinyaga, where 86% of Kenyan rice is produced. NIBAM108 (IR2793-80-1) and BW196 (NIBAM 109) were moderately resistant to blast, while NIBAM110 (ITA310) and Vietnam were susceptible. All the cultivars were susceptible to brown spot except for KEH10005 (Arize Tej Gold), a commercial hybrid cultivar. We also identified diverse pathogenic and non-pathogenic fungi, with a high incidence of Nigrospora oryzae, in the rice fields of Kirinyaga. There was a marginal correlation between disease severity/incidence and the occurrence of causal pathogens. This study provides evidence of the need to strengthen pathogen surveillance through retraining agricultural extension agents and to breed for blast and brown spot resistance in popular rice cultivars in Kenya.
Defining the Collapse Point in Colloidal Unimolecular Polymer (CUP) Formation
Authors: Zore Ashish , Geng Peng , Zhang Yuwei , Van De Mark Michael R.
Published: May 2022

Colloidal unimolecular polymer (CUP) particles were made using polymers with different ratios of hydrophobic and hydrophilic monomers via a self-organization process known as water reduction. The water-reduction process and the collapse of the polymer chain to form a CUP were tracked using viscosity measurements as a function of composition. A vibration viscometer, which allowed for viscosity measurement as the water was being added during the water-reduction process, was utilized. The protocol was optimized and tested for factors such as temperature control, loss of material, measurement stability while stirring, and changes in the solution volume with the addition of water. The resulting viscosity curve provided the composition of Tetrahydrofuran (THF)/water mixture that triggers the collapse of a polymer chain into a particle. Hansen as well as dielectric parameters were related to the polymer composition and percentage v/v of THF/water mixture at the collapse point. It was observed that the collapse of the polymer chain occurred when the water/THF composition was at a water volume of between 53.8 to 59.3% in the solvent mixture.
Modification of Orange Bagasse with Reactive Extrusion to Obtain Cellulose-Based Materials
Authors: Mantovan Janaina , Yamashita Fábio , Mali Suzana
Published: May 2022

Orange bagasse (OB) could be considered a sustainable, renewable, and low-cost biomass for the extraction of cellulose. In this context, reactive extrusion can be considered an excellent, eco-friendly, alternative process for the extraction of cellulose from lignocellulosic materials. Thus, the present study aimed to obtain cellulose-based materials with a reactive extrusion process and also to investigate the impact of pectin on the delignification process. Two groups of samples (OB and depectinizated OB) were submitted to extrusion with sulfuric acid or sodium hydroxide in one-step processes. The cellulose content of extruded materials was highly affected by pectin content in the raw material; the thermal profile (TGA curves) and crystallinity also changed. The cellulose content of modified materials ranged from 18.8% to 58.4%, with a process yield of 30.6% to 79.2%. The alkaline reagent provided the highest cellulose content among all extrusion treatments tested, mainly for OB without pectin. The extrusion process was considered an efficient and promising process for extracting cellulose from citrus residue. Materials produced in this study can be used as sources of cellulose fiber for various products and processes, such as in the food industry, fermentation substrates, or refined applications after subsequent treatments.
Risk Classification of Shale Gas Gathering and Transportation Pipelines Running through High Consequence Areas
Authors: Chen Kun , Shi Nan , Lei Zhenjie , Chen Xu , Qin Wei , Wei Xin , Liu Shanghao
Published: May 2022

Shale gas gathering and transportation pipeline poses significant risk due to special geographical conditions and different climatic conditions in high consequence areas such as Sichuan and Chongqing. The risks become critical as gas pipelines run through high consequence areas such as hospital, market, and scenic areas. This study presents a risk classification method for the pipelines running through high consequence areas. The proposed method considers different failure scenarios including third-party damage, corrosion, design and construction defects, mis-operation, and natural disasters. The method uses subjective and objective data from different sources. To minimize the subjectivity and data uncertainty, an improved fuzzy analytic hierarchy process was used to process data. The estimated risk is used to classify different risk zones. After the failure of shale gas pipelines in HCAs, in order to reduce the adverse impact of emergencies, personnel should immediately organize an evacuation to a safe area, focusing on the diagnosis and analysis of risk factors that are more likely to lead to pipeline leakage. The developed classes are verified using field data. The study observes that risk levels classified using the proposed method provide realistic assessments of hazard zoning. Risk zoning will help develop effective risk management strategies.
Nonlinear Dynamic Process Monitoring Based on Two-Step Dynamic Local Kernel Principal Component Analysis
Authors: Fang Hairong , Tao Wenhua , Lu Shan , Lou Zhijiang , Wang Yonghui , Xue Yuanfei
Published: May 2022

Nonlinearity may cause a model deviation problem, and hence, it is a challenging problem for process monitoring. To handle this issue, local kernel principal component analysis was proposed, and it achieved a satisfactory performance in static process monitoring. For a dynamic process, the expectation value of each variable changes over time, and hence, it cannot be replaced with a constant value. As such, the local data structure in the local kernel principal component analysis is wrong, which causes the model deviation problem. In this paper, we propose a new two-step dynamic local kernel principal component analysis, which extracts the static components in the process data and then analyzes them by local kernel principal component analysis. As such, the two-step dynamic local kernel principal component analysis can handle the nonlinearity and the dynamic features simultaneously.
Multi-Criteria Decision Making to Detect Multiple Moving Targets in Radar Using Digital Codes
Authors: Alotaibi Majid
Published: May 2022

Technological advancement in battlefield and surveillance applications switch the radar investigators to put more effort into it, numerous theories and models have been proposed to improve the process of target detection in Doppler tolerant radar. However, still, more effort is needed towards the minimization of the noise below the radar threshold limit to accurately detect the target. In this paper, a digital coding technique is being discussed to mitigate the noise and to create clear windows for desired target detection. Moreover, multi-criteria of digital code combinations are developed using discrete mathematics and all designed codes have been tested to investigate various target detection properties such as the auto-correlation, cross-correlation properties, and ambiguity function using mat-lab to optimize and enhance the static and moving target in presence of the Doppler in a multi-target environment.
Computer-Aided Depth Video Stream Masking Framework for Human Body Segmentation in Depth Sensor Images
Authors: Ryselis Karolis , Blažauskas Tomas , Damaševičius Robertas , Maskeliūnas Rytis
Published: May 2022

The identification of human activities from videos is important for many applications. For such a task, three-dimensional (3D) depth images or image sequences (videos) can be used, which represent the positioning information of the objects in a 3D scene obtained from depth sensors. This paper presents a framework to create foreground–background masks from depth images for human body segmentation. The framework can be used to speed up the manual depth image annotation process with no semantics known beforehand and can apply segmentation using a performant algorithm while the user only adjusts the parameters, or corrects the automatic segmentation results, or gives it hints by drawing a boundary of the desired object. The approach has been tested using two different datasets with a human in a real-world closed environment. The solution has provided promising results in terms of reducing the manual segmentation time from the perspective of the processing time as well as the human input time.
1.2 V Differential Difference Transconductance Amplifier and Its Application in Mixed-Mode Universal Filter
Authors: Kumngern Montree , Suksaibul Pichai , Khateb Fabian , Kulej Tomasz
Published: May 2022

This paper presents a new mixed-mode universal filter based on a differential difference transconductance amplifier (DDTA). Unlike the conventional transconductance amplifier (TA), this DDTA has both advantages of the TA and the differential difference amplifier (DDA). The proposed filter can offer four-mode operations of second-order transfer functions into a single topology, namely, voltage-mode (VM), current-mode (CM), transadmittance-mode (TAM), and transimpedance-mode (TIM) transfer functions. Each operation mode offers five standard filtering responses; therefore, at least twenty filtering transfer functions can be obtained. For the filtering transfer functions, the matching conditions for the input and passive component are absent. The natural frequency and the quality factor can be set orthogonally and electronically controlled. The performance of the proposed topology was evaluated by PSPICE simulator using the 0.18 µm CMOS technology from the Taiwan Semiconductor Manufacturing Company (TSMC). The voltage supply was 1.2 V and the power dissipation of the DDTA was 66 µW. The workability of the filter was confirmed through experimental test by DDTA-based LM13600 discrete-component integrated circuits.
Portable Deep Learning-Driven Ion-Sensitive Field-Effect Transistor Scheme for Measurement of Carbaryl Pesticide
Authors: Houngkamhang Nongluck , Phasukkit Pattarapong
Published: May 2022

This research proposes a multiple-input deep learning-driven ion-sensitive field-effect transistor (ISFET) scheme to predict the concentrations of carbaryl pesticide. In the study, the carbaryl concentrations are varied between 1 × 10−7–1 × 10−3 M, and the temperatures of solutions between 20–35 °C. To validate the multiple-input deep learning regression model, the proposed ISFET scheme is deployed onsite (a field test) to measure pesticide concentrations in the carbaryl-spiked vegetable extract. The advantage of this research lies in the use of a deep learning algorithm with an ISFET sensor to effectively predict the pesticide concentrations, in addition to improving the prediction accuracy. The results demonstrate the very high predictive ability of the proposed ISFET scheme, given an MSE, MAE, and R2 of 0.007%, 0.016%, and 0.992, respectively. The proposed multiple-input deep learning regression model with signal compensation is applicable to a wide range of solution temperatures which is convenient for onsite measurement. Essentially, the proposed multiple-input deep learning regression model could be adopted as an effective alternative to the conventional statistics-based regression to predict pesticide concentrations.
Formation Control of Automated Guided Vehicles in the Presence of Packet Loss
Authors: Sedghi Leila , John Jobish , Noor-A-Rahim Md , Pesch Dirk
Published: May 2022

This paper presents the formation tracking problem for non-holonomic automated guided vehicles. Specifically, we focus on a decentralized leader–follower approach using linear quadratic regulator control. We study the impact of communication packet loss—containing the position of the leader—on the performance of the presented formation control scheme. The simulation results indicate that packet loss degrades the formation control performance. In order to improve the control performance under packet loss, we propose the use of a long short-term memory neural network to predict the position of the leader by the followers in the event of packet loss. The proposed scheme is compared with two other prediction methods, namely, memory consensus protocol and gated recurrent unit. The simulation results demonstrate the efficiency of the long short-term memory in packet loss compensation in comparison with memory consensus protocol and gated recurrent unit.
Prediction Techniques on FPGA for Latency Reduction on Tactile Internet
Authors: Silva Sérgio N. , da Silva Lucileide M. D. , Dias Leonardo A. , Fernandes Marcelo A. C.
Published: May 2022

Tactile Internet (TI) is a new internet paradigm that enables sending touch interaction information and other stimuli, which will lead to new human-to-machine applications. However, TI applications require very low latency between devices, as the system’s latency can result from the communication channel, processing power of local devices, and the complexity of the data processing techniques, among others. Therefore, this work proposes using dedicated hardware-based reconfigurable computing to reduce the latency of prediction techniques applied to TI. Finally, we demonstrate that prediction techniques developed on field-programmable gate array (FPGA) can minimize the impacts caused by delays and loss of information. To validate our proposal, we present a comparison between software and hardware implementations and analyze synthesis results regarding hardware area occupation, throughput, and power consumption. Furthermore, comparisons with state-of-the-art works are presented, showing a significant reduction in power consumption of ≈1300× and reaching speedup rates of up to ≈52×.
Linear Laser Scanning Measurement Method Tracking by a Binocular Vision
Authors: Wu Chunyan , Yang Li , Luo Zai , Jiang Wensong
Published: May 2022

The 3D scanning of a freeform structure relies on the laser probe and the localization system. The localization system, determining the effect of the point cloud reconstruction, will generate positioning errors when the laser probe works in complex paths with a fast speed. To reduce the errors, in this paper, a linear laser scanning measurement method is proposed based on binocular vision calibration. A simple and effective eight-point positioning marker attached to the scanner is proposed to complete the positioning and tracking procedure. Based on this, the method of marked point detection based on image moment and the principle of global coordinate system calibration are introduced in detail. According to the invariance principle of space distance, the corresponding points matching method between different coordinate systems is designed. The experimental results show that the binocular vision system can complete localization under different light intensities and complex environments, and that the repeated translation error of the binocular vision system is less than 0.22 mm, while the rotation error is less than 0.15°. The repeated error of the measurement system is less than 0.36 mm, which can meet the requirements of the 3D shape measurement of the complex workpiece.
Research on Dual-Frequency Electromagnetic False Alarm Interference Effect of a Typical Radar
Authors: Du Xue , Wei Guanghui , Zhao Kai , Zhao Hongze , Lyu Xuxu
Published: May 2022

In order to master the position variation rule of radar false alarm signal under continuous wave (CW) electromagnetic interference and reveal the mechanism of CW on radar, taking a certain type of stepping frequency radar as the research object, theoretical analysis of the imaging mechanism of radar CW electromagnetic interference false alarm signals from the perspective of time-frequency decoupling and receiver signal processing. Secondly, electromagnetic interference injection method is used to test the single-frequency and dual-frequency electromagnetic interference effect of the tested equipment. The results show that under the single frequency CW electromagnetic interference, the sensitive bandwidth of false alarm signal is about ±75 MHz, and the position of false alarm signal irregularity changes. Under the in-band dual-frequency CW electromagnetic interference, the position of non-intermodulation false alarm signal is similar to that of single frequency. However, the distance difference of two non-intermodulation false alarm signals is regular. In addition, the positions of the second-order intermodulation false alarm signals of the tested radar are also regular, and its position changes with the change of the second-order intermodulation frequency difference.
CBGRU: A Detection Method of Smart Contract Vulnerability Based on a Hybrid Model
Authors: Zhang Lejun , Chen Weijie , Wang Weizheng , Jin Zilong , Zhao Chunhui , Cai Zhennao , Chen Huiling
Published: May 2022

In the context of the rapid development of blockchain technology, smart contracts have also been widely used in the Internet of Things, finance, healthcare, and other fields. There has been an explosion in the number of smart contracts, and at the same time, the security of smart contracts has received widespread attention because of the financial losses caused by smart contract vulnerabilities. Existing analysis tools can detect many smart contract security vulnerabilities, but because they rely too heavily on hard rules defined by experts when detecting smart contract vulnerabilities, the time to perform the detection increases significantly as the complexity of the smart contract increases. In the present study, we propose a novel hybrid deep learning model named CBGRU that strategically combines different word embedding (Word2Vec, FastText) with different deep learning methods (LSTM, GRU, BiLSTM, CNN, BiGRU). The model extracts features through different deep learning models and combine these features for smart contract vulnerability detection. On the currently publicly available dataset SmartBugs Dataset-Wild, we demonstrate that the CBGRU hybrid model has great smart contract vulnerability detection performance through a series of experiments. By comparing the performance of the proposed model with that of past studies, the CBGRU model has better smart contract vulnerability detection performance.
Virtual Breathalyzer: Towards the Detection of Intoxication Using Motion Sensors of Commercial Wearable Devices
Authors: Nassi Ben , Shams Jacob , Rokach Lior , Elovici Yuval
Published: May 2022

Driving under the influence of alcohol is a widespread phenomenon in the US where it is considered a major cause of fatal accidents. In this research, we present Virtual Breathalyzer, a novel approach for detecting intoxication from the measurements obtained by the sensors of smartphones and wrist-worn devices. We formalize the problem of intoxication detection as the supervised machine learning task of binary classification (drunk or sober). In order to evaluate our approach, we conducted a field experiment and collected 60 free gait samples from 30 patrons of three bars using a Microsoft Band and Samsung Galaxy S4. We validated our results against an admissible breathalyzer used by the police. A system based on this concept successfully detected intoxication and achieved the following results: 0.97 AUC and 0.04 FPR, given a fixed TPR of 1.0. Our approach can be used to analyze the free gait of drinkers when they walk from the car to the bar and vice versa, using wearable devices which are ubiquitous and more widespread than admissible breathalyzers. This approach can be utilized to alert people, or even a connected car, and prevent people from driving under the influence of alcohol.
Early Detection of Grapevine (Vitis vinifera) Downy Mildew (Peronospora) and Diurnal Variations Using Thermal Imaging
Authors: Cohen Bar , Edan Yael , Levi Asher , Alchanatis Victor
Published: May 2022

Agricultural industry is facing a serious threat from plant diseases that cause production and economic losses. Early information on disease development can improve disease control using suitable management strategies. This study sought to detect downy mildew (Peronospora) on grapevine (Vitis vinifera) leaves at early stages of development using thermal imaging technology and to determine the best time during the day for image acquisition. In controlled experiments, 1587 thermal images of grapevines grown in a greenhouse were acquired around midday, before inoculation, 1, 2, 4, 5, 6, and 7 days after an inoculation. In addition, images of healthy and infected leaves were acquired at seven different times during the day between 7:00 a.m. and 4:30 p.m. Leaves were segmented using the active contour algorithm. Twelve features were derived from the leaf mask and from meteorological measurements. Stepwise logistic regression revealed five significant features used in five classification models. Performance was evaluated using K-folds cross-validation. The support vector machine model produced the best classification accuracy of 81.6%, F1 score of 77.5% and area under the curve (AUC) of 0.874. Acquiring images in the morning between 10:40 a.m. and 11:30 a.m. resulted in 80.7% accuracy, 80.5% F1 score, and 0.895 AUC.
Unmarried Adolescents’ Experiences of Using Reproductive and Maternal Health Services in Nigeria and Uganda: A Qualitative Study
Authors: Onukwugha Franklin , Agaba Peninah , Hayter Mark , Orton Bev
Published: May 2022

Adolescents’ access and use of reproductive and maternal health (RMH) services is a critical part of the global strategy for achieving the Sustainable Development Goals (SDGs). However, previous studies have shown that a complex range of factors, including restrictive policies and punitive laws, limit adolescents from accessing a full range of RMH services in Sub-Saharan Africa (SSA). Our study explores the experiences of unmarried adolescents’ access and use of RMH services in Nigeria and Uganda to understand the extent to which the diverse policy environment in both countries enables or hinders adolescents’ access to and use of RMH services. Our qualitative research design involved eight focus group discussions (FGDs) in Nigeria and in Uganda, 14 in-depth interviews, and eight FGDs among adolescents. The data were analysed thematically and organised according to the WHO’s five broad dimensions for assessing youth-friendly health services. Our findings show that RMH services were inequitably delivered in both countries. Adolescents were restricted from accessing services based on age and marital status. Being unmarried and having no partner, especially in Uganda, was a cause for discrimination during antenatal appointments. We also observed that the expectations of adolescents were not adequately met. Service providers tended to be impolite, judgemental, and unwilling to provide services, especially contraceptives, to younger and unmarried adolescents. Our findings suggest that the existence of a youth-friendly health policy does not translate into effective youth-friendly service provision. This underscores the need for further studies to understand the complexities surrounding this by using a realist evaluation method to examine how adolescent and youth-friendly health services can be designed to improve uptake of reproductive and maternal health services among adolescents in Sub-Saharan Africa.
An Overview of Indoor Positioning and Mapping Technology Standards
Authors: Deng Yuejin , Ai Haojun , Deng Zeyu , Gao Wenxiu , Shang Jianga
Published: May 2022

Technologies and systems for indoor positioning, mapping, and navigation (IPMN) have rapidly developed over the latest decade due to advanced radio and light communications, the internet of things, intelligent and smart devices, big data, and so forth. Thus, a group of surveys for IPMN technologies, systems, standards, and solutions can be found in literature. However, currently there is no proposed solution that can satisfy all indoor application requirements; one of the biggest challenges is lack of standardization, even though several IPMN standards have been published by different standard developing organizations (SDOs). Therefore, this paper aims to re-survey indoor positioning and mapping technologies, in particular, the existing standards related to these technologies and to present guidance in the field. As part of our work, we provide an IPMN standards system architecture consisting of concepts, terms, models, indoor positioning technologies, software and tools, applications, services and policies, and indoor mapping and modelling; and, we present IPMN standards developed for our projects in practice, such as multi-source fusion positioning data interfaces; seamless cooperative positioning service interfaces; content model for indoor mapping and navigation, and specification for digital indoor map products.
Repeated-Measures Analysis in the Context of Heteroscedastic Error Terms with Factors Having Both Fixed and Random Levels
Authors: Chaka Lyson , Njuho Peter
Published: May 2022

The design and analysis of experiments which involve factors each consisting of both fixed and random levels fit into linear mixed models. The assumed linear mixed-model design matrix takes either a full-rank or less-than-full-rank form. The complexity of the data structures of such experiments falls in the model-selection and parameter-estimation process. The fundamental consideration in the estimation process of linear models is the special case in which elements of the error vector are assumed equal and uncorrelated. However, different assumptions on the structure of the variance–covariance matrix of error vector in the estimation of parameters of a linear mixed model may be considered. We conceptualise a repeated-measures design with multiple between-subjects factors, in which each of these factors has both fixed and random levels. We focus on the construction of linear mixed-effects models, the estimation of variance components, and hypothesis testing in which the default covariance structure of homoscedastic error terms is not appropriate. We illustrate the proposed approach using longitudinal data fitted to a three-factor linear mixed-effects model. The novelty of this approach lies in the exploration of the fixed and random levels of the same factor and in the subsequent interaction effects of the fixed levels. In addition, we assess the differences between levels of the same factor and determine the proportion of the total variation accounted for by the random levels of the same factor.
Systemizing and Automating the Concept Development Process Based on Product Configuration and User Feedback: Case Study on Automating the Design Process of Creating Concepts for a Kitchen Stand Mixer
Authors: Nielsen Camilla S. , Arlitt Ryan M.
Published: May 2022

Optimizing the development and evaluation of concepts during the design of consumer products through, e.g., topology optimization, often excludes areas associated with user needs (e.g., usability). This paper reports on an exploratory study of developing a system which can create new product concepts based on users’ preferences, requirements, and a clearly defined product structure. The 3D model of the product (structured using top-down design and resilient modeling) was integrated with calculations of the performance of the user needs (performance indicators). Different designs were developed based on design of experiment analyses and optimization analyses of the 3D model of the product (a kitchen stand mixer). The outcome of the analyses was a range of concepts which scored differently in the performance indicators. The best designs (based on Pareto front) were evaluated by six potential customers. Half of the participants preferred the same design, suggesting that this tool can be used to develop a design which a specific customer segment prefers. The process of creating the model and using it for customer interviews contributed a set of qualitative findings to the literature on combining parametric design, customization, and systematic design with user needs.
Enlightening the Pathway of Phytoremediation: Ecophysiology and X-ray Fluorescence Visualization of Two Chilean Hardwoods Exposed to Excess Copper
Authors: Milla-Moreno Estefanía , Guy Robert Dean , Soolanayakanahally Raju Y.
Published: May 2022

In the present climate emergency due to global warming, we are urged to move away from fossil fuels and pursue a speedy conversion to renewable energy systems. Consequently, copper (Cu) will remain in high demand because it is a highly efficient conductor used in clean energy systems to generate power from solar, hydro, thermal and wind energy across the world. Chile is the global leader in copper production, but this position has resulted in Chile having several hundred tailing deposits. We grew two Chilean native hardwood species, quillay (Quillaja saponaria Molina) and espino (Vachellia caven (Molina) Seigler & Ebinger, under three increasing Cu levels (0, 50, and 100 µM) for 6 months in a greenhouse setting. We measured growth, photosynthetic performance and elemental contents of leaves and roots to further evaluate their potential for phytoremediation. Growth of quillay was unaffected by Cu treatment but growth of espino was enhanced, as was its photosynthetic performance, indicating that espino may have an unusually high requirement for copper. Excess Cu was mostly restricted to the roots of both species, where X-ray fluorescence (XRF) mapping indicated some tendency for Cu to accumulate in tissues outside the periderm. Calcium oxalate crystals were prominently visible in XRF images of both species. Nickel (but not Cu) showed a concurrent distribution pattern with these crystals.
Low-Dose Propranolol Prevents Functional Decline in Catecholamine-Induced Acute Heart Failure in Rats
Authors: Tsai Cheng-Ken , Chen Bo-Hau , Chen Hsin-Hung , Hsieh Rebecca Jen-Ling , Lee Jui-Chen , Chu Yi-Ting , Lu Wen-Hsien
Published: May 2022

Severe hyper-catecholaminergic states likely cause heart failure and cardiac fibrosis. While previous studies demonstrated the effects of beta-blockade in experimental models of single-catecholamine excess states, the detailed benefits of beta-blockade in more realistic models of hyper-adrenergic states are less clearly understood. In this study, we examined different therapeutic dosages and the effects of propranolol in rats with hyper-acute catecholamine-induced heart failure, and subsequent cardiopulmonary changes. Rats (n = 41) underwent a 6 h infusion of epinephrine and norepinephrine alone, with additional low-dose (1 mg/kg) or high-dose propranolol (10 mg/kg) at hour 1. Cardiac and pulmonary tissues were examined after 6 h. Catecholamine-only groups had the lowest survival rate. Higher doses of propranolol (15 mg/kg) caused similarly low survival rates and were not further analyzed. All low-dose propranolol rats survived, with a modest survival improvement in the high-dose propranolol groups. Left ventricular (LV) systolic pressure and LV end-diastolic pressure improved maximally with low-dose propranolol. Cardiac immunohistochemistry revealed an LV upregulation of FGF-23 in the catecholamine groups, and this improved in low-dose propranolol groups. These results suggest catecholamine-induced heart failure initiates early pre-fibrotic pathways through FGF-23 upregulation. Low-dose propranolol exerted cardio-preventative effects through FGF-23 downregulation and hemodynamic-parameter improvement in our model of hyper-acute catecholamine-induced heart failure.