bluuebunny/crossref_metadata_2025 huggingface dataset:
The Value of Open Data in HCI: A Case Report from Mobile Text Entry Research
Authors: Komninos Andreas
Published: August 2022

For many years, HCI research has been known to suffer from a replication crisis, due to the lack of openly available datasets and accompanying code. Recent research has identified several barriers that prevent the wider sharing of primary research materials in HCI, but such material does, in fact, exist. Interested in the field of mobile text entry research, and largely hindered by the lack of access to participants due to the COVID-19 pandemic, the exploration of a recently published open gaze and touch dataset became an appealing prospect. This paper demonstrates the numerous problems and the extent of required effort related to understanding, sanitising and utilising open data in order to produce meaningful outcomes from it, through a detailed account of working with this dataset. Despite these issues, the paper demonstrates the value of open data as a means to produce novel contributions, without the need for additional new data (in this case, an unsupervised learning pipeline for the robust detection of gaze clusters in vertically distinct areas of interest). Framing the experience of this case study under a dataset lifecycle model intended for ML open data, a set of useful guidelines for researchers wishing to exploit open data is derived. A set of recommendations is also proposed, about the handling of papers accompanied by data, by conferences and journals in the future, Finally, the paper proposes a set of actions for the mobile text entry community, in order to facilitate data sharing across its members.
Association of rs738409 Polymorphism in Adiponutrin Gene with Liver Steatosis and Atherosclerosis Risk Factors in Greek Children and Adolescents
Authors: Stasinou Eleanna , Emmanouilidou-Fotoulaki Elpida , Kavga Maria , Sotiriadou Fotini , Lambropoulos Alexandros F. , Fotoulaki Maria , Papadopoulou-Legbelou Kyriaki
Published: August 2022

Non-alcoholic fatty liver disease (NAFLD) shares several risk factors with atherosclerosis, as it is associated with components of the metabolic syndrome. However, genetic variations have also been linked to the risk of NAFLD, such as adiponutrin/patatin-like phospholipase domain-containing the protein 3 (PNPLA3) rs738409 polymorphism. The aim of the study was to determine the associations of thePNPLA3 rs738409 polymorphism with NAFLD and atherosclerosis risk factors in children and adolescents from northern Greece. A total of 91 children/adolescents who followed a Mediterranean eating pattern with no particular restrictions were studied. They were divided into three subgroups, according to their body mass index (BMI) and the presence or absence of liver disease. Diagnosis of NAFLD was based on a liver ultrasound, while the distribution of the PNPLA3 rs738409 polymorphism was investigated in all the participants. From the components of metabolic syndrome, only BMI, waist circumference, blood pressure, and the homeostasis model of insulin resistance (HOMA-IR) differed significantly between groups. The rs738409 polymorphism was significantly associated with BMI and NAFLD, while lipid values had no significant association with either NAFLD or gene polymorphism. This study shows that in Greekchildren, there is a significant association between the rs738409polymorphism in the PNPLA3 gene and hepatic steatosis, regardless of bodyweight.
Water-Soluble Vitamins and Trace Elements Losses during On-Line Hemodiafiltration
Authors: Bévier Alban , Novel-Catin Etienne , Blond Emilie , Pelletier Solenne , Parant Francois , Koppe Laetitia , Fouque Denis
Published: August 2022

Maintenance hemodialysis induces water-soluble vitamins and trace elements losses, which is why recommendations regarding potential supplementation were provided, but mainly based on conventional hemodialysis. This study′s aim was to measure the water–soluble vitamins and trace element losses during one on-line post-dilution hemodiafiltration (HDF) session. Thirty-nine patients under maintenance HDF were enrolled. We used the Theraflux® sampler (Theradial Corp., Orvault, France) to analyze the full session dialysate mass transfer. Blood and dialysate samples were collected before and after one HDF session to measure B1, B2, B6, B9, B12, C vitamins, zinc, and selenium concentrations. Values significantly decreased for B1 (20.2%), B2 (13%), B6 (25.4%), B9 (32.6%), C (66.6%) and selenium (6.7%). No significant differences were found for vitamin B12 and zinc. The dialysate losses per session were 1.12 ± 0.88 mg for vitamin B1, 0.28 ± 0.30 mg for B2, 0.33 ± 0.09 mg for B6, 0.3 ± 0.18 mg for B9, 147.5 ± 145.50 mg for C and 25.75 ± 6.91 mg for zinc. Vitamin B12 and selenium were under detection values. In conclusion, during a standard 4hr-HDF session, we found important losses for vitamin B1, B6, B9, C and zinc, suggesting the need for regular monitoring of plasma levels and systematic supplementation of these compounds.
Rheological Properties and Stability of Thickeners for Clinical Use
Authors: Calmarza-Chueca Fernando , Sánchez-Gimeno Ana Cristina , Raso-Pueyo Javier , Arbones-Mainar José Miguel , Caverni-Muñoz Alberto , Sanz-Arque Alejandro , Sanz-Paris Alejandro
Published: August 2022

The adaptation of liquids for patients with dysphagia requires precision and individualization in the viscosities used. We describe the variations of viscosity in water at different concentrations and evolution over time of the three compositions of commercial thickeners that are on the market (starch, starch with gums, and gum). By increasing the concentration in water, the viscosity of gum-based thickeners increases linearly, but it did not reach pudding texture, whereas the viscosity of the starch-based thickeners (alone or mixed with gums) rapidly reaches very thick textures. We modeled the viscosity at different concentrations of the four thickeners using regression analysis (R2 > 0.9). We analyzed viscosity changes after 6 h of preparation. The viscosity of gum-based thickeners increased by a maximum of 6.5% after 6 h of preparation, while starch-based thickeners increased by up to 43%. These findings are important for correct handling and prescription. Gum-based thickeners have a predictable linear behavior with the formula we present, reaching nectar and honey-like textures with less quantity of thickener, and are stable over time. In contrast, starch thickeners have an exponential behavior which is difficult to handle, they reach pudding-like viscosity, and are not stable over time.
Serum Folate Related to Five Measurements of Obesity and High-Sensitivity C-Reactive Protein in Korean Adults
Authors: Lee Mee-Ri , Jung Sung Min
Published: August 2022

This study investigated the effects of folic acid on obesity and high-sensitivity C-reactive protein (CRP) levels. Using data from the Korea National Health and Nutrition Examination Survey (KNHANES VII 2016–2018), 6394 adults (aged 19–80 years) who met the study criteria were identified and divided into young, middle-aged, and older adult groups. The analysis assessed associations using logistic regression for complex samples. Obesity was measured using body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), a body shape index (ABSI), and body roundness index (BRI). The odds ratio (OR) of obesity based on BMI were statistically significant for young adults and older participants with low levels of folic acid compared to those with high levels (OR: 1.33 and 1.58, respectively). The OR of obesity based on BMI, WC, WHtR, ABSI, and BRI was significant with low levels of folic acid in middle-aged individuals (OR: 1.36, 1.32, 1.41, 1.29, and 1.47, respectively). Low folate levels were related to higher high-sensitivity CRP levels in middle-aged patients. In conclusion, folate level showed a significant inverse association with obesity and inflammatory biomarkers, especially in the middle-aged group. Further longitudinal or randomized controlled trials are needed to confirm and expand our results.
Prevalence of Swine Gastrointestinal Parasites in Two Free-Range Farms from Nord-West Region of Romania
Authors: Băieş Mihai-Horia , Boros Zsolt , Gherman Călin Mircea , Spînu Marina , Mathe Attila , Pataky Stefan , Lefkaditis Menelaos , Cozma Vasile
Published: August 2022

Parasitic diseases cause significant economic losses in swine, including free-range swine farms, the number of which in Romania has increased in the last decades. The current study aimed to identify the parasitic profile of swine raised on two free-range (low-input) farms from Transylvania. Nine hundred sixty samples collected from weaners, fatteners, and sows were investigated by flotation, centrifugal sedimentation, modified Ziehl-Neelsen stained fecal smear, modified Blagg technique, and oocyst/egg cultures. The number of oocysts (OPG), cysts (CPG), and eggs (EPG) were counted per gram of fecal matter. The examination revealed parasitic infections with Balantidium coli, Eimeria spp., Ascaris suum, Trichuris suis, Oesophagostomum spp., Strongyloides ransomi and Cryptosporidium spp. Prevalence (P) and the mean intensity (MI) of the infections varied according to age, swine category, farm, and season. The overall prevalence in both free-range farms according to the age category was 63.2%—Eimeria spp., 70.31%—B. coli, 9.38%—Oesophagostomum spp., 3.75% S. ransomi, and 18.12% Cryptosporidium spp. in weaners. In fatteners Eimeria spp. revealed a prevalence of 50.93%, B. coli—72.5 %, A. suum—63.13%, T. suis—39.06%, and in sows Eimeria spp.—39.06%, B. coli—62.19%, A. suum—34.06%, Oesophagostomum spp.—27.19%, S. ransomi—1.56% and Cryptosporidium spp.—9.38%. The study revealed statistically significant (p < 0.05) differences between age groups, seasons, and farms for all diagnosed parasites. Further research is required to better understand the epidemiology of these infections in swine from Transylvania.
Correction: Mysore et al. A Broad-Based Mosquito Yeast Interfering RNA Pesticide Targeting Rbfox1 Represses Notch Signaling and Kills Both Larvae and Adult Mosquitoes. Pathogens 2021, 10, 1251
Authors: Mysore Keshava , Sun Longhua , Hapairai Limb K. , Wang Chien-Wei , Roethele Joseph B. , Igiede Jessica , Scheel Max P. , Scheel Nicholas D. , Li Ping , Wei Na , Severson David W. , Duman-Scheel Molly
Published: August 2022

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Serological Assessment of Ascaris suum Exposure in Greek Pig Farms and Associated Risk Factors Including Lawsonia intracellularis
Authors: Tassis Panagiotis , Symeonidou Isaia , Gelasakis Athanasios I. , Kargaridis Michalis , Aretis George , Arsenopoulos Konstantinos V. , Tzika Eleni , Papadopoulos Elias
Published: August 2022

The effects of nematodes and bacteria on intestinal health are of primary importance in modern swine production. The aim of the present study was to assess the seropositivity status of Ascaris suum infection in fatteners in intensive swine farms in Greece and address possible risk factors, including Lawsonia intracellularis as a predisposing factor to swine ascariosis. In total, 360 blood serum samples from pigs in the late fattening period, from 24 Greek swine farrow-to-finish farms (15 samples/farm) were collected and tested with Svanovir® A. suum antibody ELISA and Ileitis antibody ELISA. The results demonstrated 34.4% seropositive samples for A. suum and 42.2% for L. intracellularis. The analysis of predisposing risk factors suggested that the frequency of application of anthelminthic treatment to sows more than two times per year was significantly associated with the lower likelihood of A. suum infection, whereas a greater likelihood of A. suum infection was observed in pigs with concurrent L. intracellularis exposure. The results highlight the importance of proper anthelminthic metaphylaxis of the breeding stock, as well as the likely outcome of concurrent exposure to two intestinal pathogens in pigs, implying a possible association between intestinal nematodes and bacteria in swine.
An Evaluation of the Drug Permeability Properties of Human Cadaveric In Situ Tympanic and Round Window Membranes
Authors: Veit Joachim , Birru Bhaskar , Wang Yong , Singh Ruby , Arrigali Elizabeth , Park Ryan , Miller Briggs , Firpo Matthew , Park Albert , Serban Monica
Published: August 2022

It is estimated that hearing loss currently affects more than 1.5 billion people, or approximately 20% of the global population; however, presently, there are no Food and Drug Administration-approved therapeutics or prophylactics for this condition. While continued research on the development of otoprotective drugs to target this clear unmet need is an obvious path, there are numerous challenges to translating promising therapeutic candidates into human clinical testing. The screening of promising drug candidates relies exclusively on preclinical models. Current models do not permit the rapid high-throughput screening of promising drug candidates, and their relevance to clinical scenarios is often ambiguous. With the current study, we seek to understand the drug permeability properties of the cadaveric tympanic and round window membranes with the goal of generating knowledge that could inform the design and/or evaluation of in vitro organotypic models. The development of such models could enable the early high-throughput screening of topical therapeutic candidates and should address some of the limitations of currently used animal models.
A Peptide Inhibitor of the Human Cytomegalovirus Core Nuclear Egress Complex
Authors: Alkhashrom Sewar , Kicuntod Jintawee , Stillger Katharina , Lützenburg Tamara , Anzenhofer Christian , Neundorf Ines , Marschall Manfred , Eichler Jutta
Published: August 2022

The replication of human cytomegalovirus (HCMV) involves a process termed nuclear egress, which enables translocation of newly formed viral capsids from the nucleus into the cytoplasm. The HCMV core nuclear egress complex (core NEC), a heterodimer of viral proteins pUL50 and pUL53, is therefore considered a promising target for new antiviral drugs. We have recently shown that a 29-mer peptide presenting an N-terminal alpha-helical hook-like segment of pUL53, through which pUL53 interacts with pUL50, binds to pUL50 with high affinity, and inhibits the pUL50–pUL53 interaction in vitro. Here, we show that this peptide is also able to interfere with HCMV infection of cells, as well as with core NEC formation in HCMV-infected cells. As the target of the peptide, i.e., the pUL50–pUL53 interaction, is localized at the inner nuclear membrane of the cell, the peptide had to be equipped with translocation moieties that facilitate peptide uptake into the cell and the nucleus, respectively. For the resulting fusion peptide (NLS-CPP-Hook), specific cellular and nuclear uptake into HFF cells, as well as inhibition of infection with HCMV, could be demonstrated, further substantiating the HCMV core NEC as a potential antiviral target.
Predicting Throughput and Melt Temperature in Pharmaceutical Hot Melt Extrusion
Authors: Gottschalk Tobias , Özbay Cihangir , Feuerbach Tim , Thommes Markus
Published: August 2022

Even though hot melt extrusion (HME) is a commonly applied process in the pharmaceutical area, determination of the optimal process parameters is demanding. The goal of this study was to find a rational approach for predetermining suitable extrusion parameters, with a focus on material temperature and throughput. A two-step optimization procedure, called scale-independent optimization strategy (SIOS), was applied and developed further, including the use of an autogenic extrusion mode. Three different polymers (Plasdone S-630, Soluplus, and Eudragit EPO) were considered, and different optimal process parameters were assessed. The maximum barrel load was dependent on the polymers’ bulk density and the extruder size. The melt temperature was influenced by the screw speed and the rheological behavior of the polymer. The melt viscosity depended mainly on the screw speed and was self-adjusted in the autogenic extrusion. A new approach, called SIOS 2.0, was suggested for calculating the extrusion process parameters (screw speed, melt temperature and throughput) based on the material data and a few extrusion experiments.
Mesoporous Nanoparticles for Diagnosis and Treatment of Liver Cancer in the Era of Precise Medicine
Authors: Wu Han , Wang Ming-Da , Zhu Jia-Qi , Li Zhen-Li , Wang Wan-Yin , Gu Li-Hui , Shen Feng , Yang Tian
Published: August 2022

Primary liver cancer is the seventh-most-common cancer worldwide and the fourth-leading cause of cancer mortality. In the current era of precision medicine, the diagnosis and management of liver cancer are full of challenges and prospects. Mesoporous nanoparticles are often designed as specific carriers of drugs and imaging agents because of their special morphology and physical and chemical properties. In recent years, the design of the elemental composition and morphology of mesoporous nanoparticles have greatly improved their drug-loading efficiency, biocompatibility and biodegradability. Especially in the field of primary liver cancer, mesoporous nanoparticles have been modified as highly tumor-specific imaging contrast agents and targeting therapeutic medicine. Various generations of complexes and structures have been determined for the complicated clinical management requirements. In this review, we summarize these advanced mesoporous designs in the different diagnostic and therapeutic fields of liver cancer and discuss the relevant advantages and disadvantages of transforming applications. By comparing the material properties, drug-delivery characteristics and application methods of different kinds of mesoporous materials in liver cancer, we try to help determine the most suitable drug carriers and information media for future clinical trials. We hope to improve the fabrication of biomedical mesoporous nanoparticles and provide direct evidence for specific cancer management.
A Novel Treatment: Effects of Nano-Sized and Micro-Sized Al2O3 on Steel Surface for the Shear Strength of Epoxy–Steel Single-Lap Joints
Authors: Wang Wanru , Wang Zhen , Guo Rui , Xian Guijun
Published: August 2022

Traditional steel surface treatment (e.g., sand blasting, or silane treatment) was regarded as an effective method to improve the bonding strength of steel–epoxy single-lap joints. In the present study, a new steel surface treatment method was developed. With this method, the steel surfaces were treated with suspensions of nano-sized and micro-sized Al2O3 particles in ethanol/water mixture using the dip-coating method. Both Al2O3 particle sizes were previously treated or not treated with silane. Single-lap shear tests of the steel–epoxy bonds were conducted to compare the effects of the treating methods. According to the testing results, the highest increase in the bonding strength (by 51.8%) was found for the steel coated with the suspension of silane treated nano-Al2O3 particles. Scanning electron microscopy (SEM) analysis and energy dispersive spectrometer (EDS) analysis indicates that the nano-Al2O3 particles were clearly attached to the treated steel surfaces. Moreover, the steel surface with the silane-treated nano-Al2O3 particles was found to clearly enhance the contact angle between the steel and epoxy resin. The fracture morphology analysis of the single-lap shear testing specimen shows that the bonding between the steel and adhesive changed from steel–epoxy interfacial failure to cohesive failure when the steel surfaces were treated with the nano-Al2O3 particles suspension. The developed steel surface treatment method with the suspension of nano-particles proves to be effective and reliable in enhancing the bonding strength of the steel-to-epoxy adhesives.
Efficient Retention and Alpha Spectroscopy of Actinides from Aqueous Solutions Using a Combination of Water-Soluble Star-like Polymers and Ultrafiltration Membranes
Authors: Bliznyuk Valery N. , Kutsevol Nataliya V. , Kuziv Yuliia I. , Husson Scott M. , DeVol Timothy A.
Published: August 2022

We explored two approaches to recover uranium and plutonium from aqueous solutions at pH 4 and pH 7 using water-soluble star-like polyacrylamide polymers with a dextran core. In the first approach, a solution comprising a neutral or ionomer polymer was mixed with a radionuclide solution to form polymer–metal complexes that were then retained by ultrafiltration (UF) membranes under applied pressure. The same polymers were first deposited on the membrane in the second approach using pressure-driven flow. The applied polymers had an overall diameter of gyration of 120 nm, which exceeded the nominal diameter of the UF membrane pores. The polymers showed a high affinity to uranyl but could also be used to extract Pu from neutral or near-neutral pH solutions. Direct-flow single-step filtration and alpha spectrometry demonstrated that the UF membranes containing star-like copolymers could recover 99% of U and up to 60% of Pu from deionized water after filtering 15 mL solutions containing 25 ppm and 33 ppb of the actinides, correspondingly. The sorption capacity of the polymers for uranium could be measured as 1mg U per mg of the polymer after six subsequent filtration steps. Alpha spectroscopy of the deposited actinides revealed peculiarities of the structural organization of polymers and their complexes with U or Pu, depending on the approach. Though both approaches were efficient, the second approach (deposition of the polymer on the membrane followed by filtration) has an additional advantage of protecting the membrane pores from capillary collapse by filling them with the polymer chains. Therefore, these polymer-modified membranes could be used either in continuous or multi-step filtration process with drying after each step without deterioration of their sorption characteristics.
Hyaluronic Acid: A Review of the Drug Delivery Capabilities of This Naturally Occurring Polysaccharide
Authors: Buckley Ciara , Murphy Emma J. , Montgomery Therese R. , Major Ian
Published: August 2022

The inclusion of physiologically active molecules into a naturally occurring polymer matrix can improve the degradation, absorption, and release profile of the drug, thus boosting the therapeutic impact and potentially even reducing the frequency of administration. The human body produces significant amounts of polysaccharide hyaluronic acid, which boasts exceptional biocompatibility, biodegradability, and one-of-a-kind physicochemical features. In this review, we will examine the clinical trials currently utilizing hyaluronic acid and address the bright future of this versatile polymer, as well as summarize the numerous applications of hyaluronic acid in drug delivery and immunomodulation.
Development of Embroidery-Type Pressure Sensor Dependent on Interdigitated Capacitive Method
Authors: Truong TranThuyNga , Kim Ji-Seon , Kim Jooyong
Published: August 2022

Many studies have been conducted to develop electronic skin (e-skin) and flexible wearable textiles which transform into actual “skin”, using different approaches. Moreover, many reports have investigated self-healing materials, multifunctional sensors, etc. This study presents a systematic approach to embroidery pressure sensors dependent on interdigitated capacitors (IDCs), for applications surrounding intelligent wearable devices, robots, and e-skins. The method proposed a broad range of highly sensitive pressure sensors based on porous Ecoflex, carbon nanotubes (CNTs), and interdigitated electrodes. Firstly, characterizations of ICDs embroidering on a cotton fabric using silver conductive thread are evaluated by a precision LCR meter throughout the frequency range from 1 kHz to 300 kHz. The effect of thread density on the performance of embroidered sensors is included. Secondly, the 16451B dielectric test fixture from Keysight is utilized to evaluate the composite samples’ dielectric constant accurately. The effect of frequency on sensor performance was evaluated to consider the influence of the dielectric constant as a function of the capacitance change. This study shows that the lower the frequency, the higher the sensitivity, but at the same time, it also leads to instability in the sensor’s operation. Thirdly, assessing the volume fraction of CNTs on composites’ properties is enclosed. The presence of volume portion CNTs upgrades the bond strength of composites and further develops sensor deformability. Finally, the presented sensor can accomplish excellent performance with an ultra-high sensitivity of 0.24 kPa−1 in low pressure (<25 kPa) as well as a wide detection range from 1 to 1000 kPa, which is appropriate for general tactile pressure rages. In order to achieve high sensor performance, factors such as density, frequency, fabric substrate, and the structure of the dielectric layer need to be carefully evaluated.
Cur Homo Deus? A Catholic Response to a Posthumanist Narrative
Authors: Rugani Marc V.
Published: August 2022

Yuval Noah Harari’s book Homo Deus has popularized and promoted the case for a posthumanist reading of universal history in the 21st century. Among the features of his narrative are atheism, a deterministic rejection of free will, and a hedonistic theory of value. Passing the seventieth anniversary of Humani Generis, Pius XII’s call for “seriousness, moderation and measure” when weighing and judging the conclusions of human science, including theories of evolution, remains relevant. With special attention to Anselm of Canterbury’s aptly titled Cur Deus Homo, this essay will identify and respond to several misrepresentations of key Christian doctrines which, when corrected, undermine the reliability of Harari’s narrative history and speculations. Rather than conceding Harari’s posthumanist conclusion that humanity’s path to divinity is a global, social agenda of biological and technological upgrade, I counterargue that Christian soteriology better responds to the deepest longings in human dissatisfaction through notions of grace and love manifest in the doctrines of incarnation and divine satisfaction.
GeoDLS: A Deep Learning-Based Corn Disease Tracking and Location System Using RTK Geolocated UAS Imagery
Authors: Ahmad Aanis , Aggarwal Varun , Saraswat Dharmendra , El Gamal Aly , Johal Gurmukh S.
Published: August 2022

Deep learning-based solutions for precision agriculture have recently achieved promising results. Deep learning has been used to identify crop diseases at the initial stages of disease development in an effort to create effective disease management systems. However, the use of deep learning and unmanned aerial system (UAS) imagery to track the spread of diseases, identify diseased regions within cornfields, and notify users with actionable information remains a research gap. Therefore, in this study, high-resolution, UAS-acquired, real-time kinematic (RTK) geotagged, RGB imagery at an altitude of 12 m above ground level (AGL) was used to develop the Geo Disease Location System (GeoDLS), a deep learning-based system for tracking diseased regions in corn fields. UAS images (resolution 8192 × 5460 pixels) were acquired in cornfields located at Purdue University’s Agronomy Center for Research and Education (ACRE), using a DJI Matrice 300 RTK UAS mounted with a 45-megapixel DJI Zenmuse P1 camera during corn stages V14 to R4. A dataset of 5076 images was created by splitting the UAS-acquired images using tile and simple linear iterative clustering (SLIC) segmentation. For tile segmentation, the images were split into tiles of sizes 250 × 250 pixels, 500 × 500 pixels, and 1000 × 1000 pixels, resulting in 1804, 1112, and 570 image tiles, respectively. For SLIC segmentation, 865 and 725 superpixel images were obtained using compactness (m) values of 5 and 10, respectively. Five deep neural network architectures, VGG16, ResNet50, InceptionV3, DenseNet169, and Xception, were trained to identify diseased, healthy, and background regions in corn fields. DenseNet169 identified diseased, healthy, and background regions with the highest testing accuracy of 100.00% when trained on images of tile size 1000 × 1000 pixels. Using a sliding window approach, the trained DenseNet169 model was then used to calculate the percentage of diseased regions present within each UAS image. Finally, the RTK geolocation information for each image was used to update users with the location of diseased regions with an accuracy of within 2 cm through a web application, a smartphone application, and email notifications. The GeoDLS could be a potential tool for an automated disease management system to track the spread of crop diseases, identify diseased regions, and provide actionable information to the users.
Detecting Spatial Communities in Vehicle Movements by Combining Multi-Level Merging and Consensus Clustering
Authors: Liu Qiliang , Hou Zhaoyi , Yang Jie
Published: August 2022

Identifying spatial communities in vehicle movements is vital for sensing human mobility patterns and urban structures. Spatial community detection has been proven to be an NP-Hard problem. Heuristic algorithms were widely used for detecting spatial communities. However, the spatial communities identified by existing heuristic algorithms are usually locally optimal and unstable. To alleviate these limitations, this study developed a hybrid heuristic algorithm by combining multi-level merging and consensus clustering. We first constructed a weighted spatially embedded network with road segments as vertices and the numbers of vehicle trips between the road segments as weights. Then, to jump out of the local optimum trap, a new multi-level merging approach, i.e., iterative local moving and global perturbation, was proposed to optimize the objective function (i.e., modularity) until a maximum of modularity was obtained. Finally, to obtain a representative and reliable spatial community structure, consensus clustering was performed to generate a more stable spatial community structure out of a set of community detection results. Experiments on Beijing taxi trajectory data show that the proposed method outperforms a state-of-the-art method, spatially constrained Leiden (Scleiden), because the proposed method can escape from the local optimum solutions and improve the stability of the identified spatial community structure. The spatial communities identified by the proposed method can reveal the polycentric structure and human mobility patterns in Beijing, which may provide useful references for human-centric urban planning.
An Intelligent Automated System for Detecting Malicious Vehicles in Intelligent Transportation Systems
Authors: Ashfaq Tehreem , Khalid Rabiya , Yahaya Adamu Sani , Aslam Sheraz , Azar Ahmad Taher , Alkhalifah Tamim , Tounsi Mohamed
Published: August 2022

The exponential growth of intelligent vehicles(IVs) development has resulted in a complex network. As the number of IVs in a network increases, so does the number of connections. As a result, a great deal of data is generated. This complexity leads to insecure communication, traffic congestion, security, and privacy issues in vehicular networks (VNs). In addition, detecting malicious IVs, data integration, and data validation are major issues in VNs that affect network performance. A blockchain-based model for secure communication and malicious IV detection is proposed to address the above issues. In addition, this system also addresses data integration and transaction validation using an encryption scheme for secure communication. A multi-chain concept separates the legitimate and malicious data into two chains: the Integrity chain (I-chain) and Fraud chain (F-chain). This multi-chain mechanism solves the storage problem and reduces the computing power. The integration of blockchain in the proposed model provides privacy, network security, transparency, and immutability. To address the storage issue, the InterPlanetary File System (IPFS) is integrated with Certificate Authority (CA). A reputation mechanism is introduced to detect malicious IVs in the network based on ratings. This reputation mechanism is also used to prevent Sybil attack. The evaluation of the proposed work is based on the cost of smart contracts and computation time. Furthermore, two attacker models are presented to prevent the selfish mining attack and the Sybil attack. Finally, a security analysis of the proposed smart contracts with their security vulnerabilities is also presented.
Nonlinear Propagation and Filamentation on 100 Meter Air Path of Femtosecond Beam Partitioned by Wire Mesh
Authors: Geints Yuri E. , Minina Olga V. , Geints Ilia Yu. , Seleznev Leonid V. , Pushkarev Dmitrii V. , Mokrousova Daria V. , Rizaev Georgy E. , Shipilo Daniil E. , Nikolaeva Irina A. , Kurilova Maria V. , Panov Nikolay A. , Kosareva Olga G. , Houard Aurélien , Couairon Arnaud , Ionin Andrey A. , Liu Weiwei
Published: August 2022

High-intensity (∼1 TW/cm2 and higher) region formed in the propagation of ∼60 GW, 90 fs Ti:Sapphire laser pulse on a ∼100 m path in air spans for several tens of meters and includes a plasma filament and a postfilament light channel. The intensity in this extended region is high enough to generate an infrared supercontinuum wing and to initiate laser-induced discharge in the gap between the electrodes. In the experiment and simulations, we delay the high-intensity region along the propagation direction by inserting metal-wire meshes with square cells at the laser system output. We identify the presence of a high-intensity region from the clean-spatial-mode distributions, appearance of the infrared supercontinuum wing, and occurrence of the laser-induced discharge. In the case of free propagation (without any meshes), the onset of the high-intensity zone is at 40–52 m from the laser system output with ∼30 m extension. Insertion of the mesh with 3 mm cells delays the beginning of the high-intensity region to 49–68 m with the same ∼30 m extension. A decrease in the cell size to 1 mm leads to both delay and shrinking of the high-intensity zone to 71–73 m and 6 m, respectively. Three-dimensional simulations in space confirm the mesh-induced delay of the high-intensity zone as the cell size decreases.
Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis
Authors: Vićentić Teodora , Rašljić Rafajilović Milena , Ilić Stefan D. , Koteska Bojana , Madevska Bogdanova Ana , Pašti Igor A. , Lehocki Fedor , Spasenović Marko
Published: August 2022

The HeartPy Python toolkit for analysis of noisy signals from heart rate measurements is an excellent tool to use in conjunction with novel wearable sensors. Nevertheless, most of the work to date has focused on applying the toolkit to data measured with commercially available sensors. We demonstrate the application of the HeartPy functions to data obtained with a novel graphene-based heartbeat sensor. We produce the sensor by laser-inducing graphene on a flexible polyimide substrate. Both graphene on the polyimide substrate and graphene transferred onto a PDMS substrate show piezoresistive behavior that can be utilized to measure human heartbeat by registering median cubital vein motion during blood pumping. We process electrical resistance data from the graphene sensor using HeartPy and demonstrate extraction of several heartbeat parameters, in agreement with measurements taken with independent reference sensors. We compare the quality of the heartbeat signal from graphene on different substrates, demonstrating that in all cases the device yields results consistent with reference sensors. Our work is a first demonstration of successful application of HeartPy to analysis of data from a sensor in development.
ICARUS—Very Low Power Satellite-Based IoT
Authors: Krondorf Marco , Bittner Steffen , Plettemeier Dirk , Knopp Andreas , Wikelski Martin
Published: August 2022

The ICARUS (International Cooperation for Animal Research Using Space) satellite IoT system was launched in 2020 to observe the life of animals on Earth: their migratory routes, living conditions, and causes of death. These findings will aid species conservation, protect ecosystem services by animals, measure weather and climate, and help forecast the spread of infectious zoonotic diseases and possibly natural disasters. The aim of this article is to explain the system design of ICARUS. Essential components are ‘wearables for wildlife’, miniature on-animal sensors, quantifying the health of animals and the surrounding environment on the move, and transmitting artificially intelligent summaries of these data globally. We introduce a new class of Internet-of-things (IoT) waveforms—the random-access, very-low-power, wide-area networks (RA-vLPWANs) which enable uncoordinated multiple access at very-low-signal power and low-signal-to-noise ratios. RA-vLPWANs used in ICARUS solve the problems hampering conventional low-power wide area network (LPWAN) IoT systems when applied to space communications. Prominent LPWANs are LoRA, SigFox, MIOTY, ESSA, NB-IoT (5G), or SCADA. Hardware and antenna aspects in the ground and the space segment are given to explain practical system constraints.
FGL-GAN: Global-Local Mask Generative Adversarial Network for Flame Image Composition
Authors: Qin Kui , Hou Xinguo , Yan Zhengjun , Zhou Feng , Bu Leping
Published: August 2022

It is important to reduce the danger of collecting flame image data sets by compositing flame images by computer. In this paper, a Global-Local mask Generative Adversarial Network (FGL-GAN) is proposed to address the current status of low quality composite flame images. First, FGL-GAN adopts a hierarchical Global-Local generator structure, to locally render high-quality flame halo and reflection, while also maintaining a consistent global style. Second, FGL-GAN incorporates the fire mask as part of the input of the generation module, which improves the rendering quality of flame halo and reflection. A new data augmentation technique for flame image compositing is used in the network training process to reconstruct the background and reduce the influence of distractors on the network. Finally, FGL-GAN introduces the idea of contrastive learning to speed up network fitting and reduce blurriness in composite images. Comparative experiments show that the images composited by FGL-GAN have achieved better performance in qualitative and quantitative evaluation than mainstream GAN. Ablation study shows the effectiveness of the hierarchical Global-Local generator structure, fire mask, data augmentation, and MONCE loss of FGL-GAN. Therefore, a large number of new flame images can be composited by FGL-GAN, which can provide extensive test data for fire detection equipment, based on deep learning algorithms.
Reinforcement Learning Based Multipath QUIC Scheduler for Multimedia Streaming
Authors: Lee Seunghwa , Yoo Joon
Published: August 2022

With the recent advances in computing devices such as smartphones and laptops, most devices are equipped with multiple network interfaces such as cellular, Wi-Fi, and Ethernet. Multipath TCP (MPTCP) has been the de facto standard for utilizing multipaths, and Multipath QUIC (MPQUIC), which is an extension of the Quick UDP Internet Connections (QUIC) protocol, has become a promising replacement due to its various advantages. The multipath scheduler, which determines the path to which each packet should be transmitted, is a key function that affects the multipath transport performance. For example, the default minRTT scheduler typically achieves good throughput, while the redundant scheduler gains low latency. While the legacy schedulers may generally give a desirable performance in some environments, however, each application renders different requirements. For example, Web applications target low latency, while video streaming applications require low jitter and high video quality. In this paper, we propose a novel MPQUIC scheduler based on deep reinforcement learning using the Deep Q-Network (DQN) that enhances the quality of multimedia streaming. Our proposal first takes into account both delay and throughput as a reward for reinforcement learning to achieve a low video chunk download time. Second, we propose a chunk manager that informs the scheduler of the video chunk information, and we also tune the learning parameters to explore new random actions adequately. Finally, we implement our new scheduler on the Linux kernel and give results using the Mininet experiments. The evaluation results show that our proposal outperforms legacy schedulers by at least 20%.
Exercise Condition Sensing in Smart Leg Extension Machine
Authors: Shiao Yaojung , Hoang Thang
Published: August 2022

Skeletal muscles require fitness and rehsabilitation exercises to develop. This paper presents a method to observe and evaluate the conditions of muscle extension. Based on theories about the muscles and factors that affect them during leg contraction, an electromyography (EMG) sensor was used to capture EMG signals. The signals were applied by signal processing with the wavelet packet entropy method. Not only did the experiment follow fitness rules to obtain correct EMG signal of leg extension, but the combination of inertial measurement unit (IMU) sensor also verified the muscle state to distinguish the muscle between non-fatigue and fatigue. The results show the EMG changing in the non-fatigue, fatigue, and calf muscle conditions. Additionally, we created algorithms that can successfully sense a user’s muscle conditions during exercise in a leg extension machine, and an evaluation of condition sensing was also conducted. This study provides proof of concept that EMG signals for the sensing of muscle fatigue. Therefore, muscle conditions can be further monitored in exercise or rehabilitation exercise. With these results and experiences, the sensing methods can be extended to other smart exercise machines in the future.
Towards a Recommender System for In-Vehicle Antenna Placement in Harsh Propagation Environments
Authors: Kraus Daniel , Diwold Konrad , Pestana Jesús , Priller Peter , Leitgeb Erich
Published: August 2022

This paper presents a novel approach to improving wireless communications in harsh propagation environments to achieve higher overall reliability and durability of wireless battery powered sensor systems in the context of in-vehicle communication. The goal is to investigate the physical layer and establish an antenna recommendation system for a specific harsh environment, i.e., an engine compartment of a vehicle. We propose the usage of electromagnetic (EM) and ray tracing simulations as a computationally cost-effective method to establish such a recommendation system, which we test by means of an experimental testbed—or test environment—that consists of both a physical, as well as its identical simulation, model. A pool of antennas is evaluated to identify and verify antenna behavior and properties at specified positions in the harsh environment. We use a vector network analyzer (VNA) for accurate measurements and a received signal strength indicator (RSSI) for a first estimation of system performance. Our analysis of the experimental measurements and its EM simulation counterparts shows that both types of data lead to equivalent antenna recommendations at each of the defined positions and experimental conditions. This evaluation and verification process by measurements on an experimental testbed is important to validate the antenna recommendation process. Our results indicate that—with properly characterized antennas—such measurements can be substituted with EM simulations on an accurate EM model, which can contribute to dramatically speeding up the antenna positioning and selection process.
Highly Sensitive and Selective Surface Acoustic Wave Ammonia Sensor Operated at Room Temperature with a Polyacrylic Acid Sensing Layer
Authors: Wang Weiqiang , Guo Yuanjun , Xiong Wenkai , Fu Yongqing , Elmarakbi Ahmed , Zu Xiaotao
Published: August 2022

In this study, polyacrylic acid (PAA) films were deposited onto a quartz surface acoustic wave (SAW) resonator using a spin-coating technique for ammonia sensing operated at room temperature, and the sensing mechanisms and performance were systematically studied. The oxygen-containing functional groups on the surfaces of the PAA film make it sensitive and selective to ammonia molecules, even when tested at room temperature. The ammonia molecules adsorbed by the oxygen-containing functional groups of PAA (e.g., hydroxyl and epoxy groups) increase the membrane’s stiffness, which was identified as the primary mechanism leading to the positive frequency shifts. However, mass loading due to adsorption of ammonia molecules is not a major reason as it will result in a negative frequency shifts. When the PAA coated SAW sensor was exposed to ammonia with a low concentration of 500 ppb, it showed a positive frequency shift of 225 Hz, with both good repeatability and stability, as well as a good selectivity to ammonia compared with those to C2H5OH, H2, HCl, H2S, CO, NO2, NO, and CH3COCH3.
Key Success Factors for the Development of Innovative Antibiotic Replacement Products to Accelerate Growth in Broilers
Authors: Supchukun Kitti , Yata Teerapong , Israsena Na Ayudhya Praima , Angkanaporn Kris
Published: August 2022

The issue of drug-resistant bacteria and the ban on antibiotic growth has encouraged research into new additives for the broiler chicken industry, from the point of view of environmental, social, governance sustainability, and material sciences management. This study aimed to examine the newest innovative antibiotic replacement products using a mixed method of planning and development schemes. Firstly, the qualitative method was conducted to evaluate the voices of 15 key users to examine product composition through an engineering technique and the quality function deployment (QFD) method. A prototype was proposed, containing a combination of nutraceuticals, including medium-chain fatty acids, short-chain fatty acids, oregano essential oil, and sweet basil essential oil, delivered in drinking water and as a feed additive through nanostructure lipid carrier (NLC) technology. The quantitative research summarized the compositions in terms of improving the growth performance of poultry, based on 280 responses. By using confirmatory factor analysis (CFA), the key factors of a successful antibiotic replacement are that they should be standardized and must follow regulations, be perceived as easy to use, satisfy performance expectations, address industry concerns, be innovative, offer an appropriate product and physical characteristics to the farm, and be presented alongside sales opportunities and marketing. It is concluded that such a hybrid of product development and innovation will lead to novel and appropriate products in the marketplace.
The Extent of Occupational Health Hazard Impact on Workers: Documentary Evidence from National Occupational Disease Statistics and Selected South African Companies’ Voluntary Corporate Social Responsibility Disclosures
Authors: Rikhotso Oscar , Morodi Thabiso John , Masekameni Daniel Masilu
Published: August 2022

This paper explores the potential of Corporate Social Responsibility disclosures in providing alternative information on the extent of occupational health hazard impact on workers, by selected South African companies operating within the manufacturing and utilities sectors amidst an absent national occupational disease surveillance system. An online internet search was used to retrieve publicly available national occupational disease statistics published between 2001 and 2020, and Corporate Social Responsibility reports of selected South African case companies, published between 2015 and 2020. Content analysis was used to analyse the retrieved documents for both descriptive and numeric data. The collection and reporting of occupational disease data in South Africa is inconsistent. Corporate Social Responsibility disclosures related to occupational health metrics vary between companies. Occupational disease incidence was the least reported of the social aspects in Corporate Social Responsibility disclosures, and/or were reported as a single statistic or combined into occupational safety incidence rates in some instances, obfuscating the true extent of the impact caused by occupational health hazards on workers. Furthermore, noise-induced hearing loss remains the most prevalently reported occupational disease, in general. Corporate Social Responsibility reports point to occupational health hazards requiring regulatory intervention, whilst also providing an alternative information source for occupational disease statistics.