bluuebunny/crossref_metadata_2025 huggingface dataset:
Coverage and Representativeness of Passive Surveillance Components for Cattle and Swine in The Netherlands
Authors: Vredenberg Imke , van Schaik Gerdien , van der Poel Wim H. M. , Stegeman Arjan
Published: November 2022

Common aims of animal health surveillance systems are the timely detection of emerging diseases and health status monitoring. This study aimed to evaluate the coverage and representativeness of passive surveillance components for cattle and swine in the Netherlands from 2015–2019. The passive surveillance components consisted of a telephone helpdesk for veterinary advice and diagnostic and postmortem facilities. Spatial analysis showed heterogeneity (range in RR = 0.26–5.37) of participation across the Netherlands. Generalized linear mixed models showed that distance to the diagnostic facility and farm density were associated with the number of contacts of farmers with the helpdesk and postmortem examination. The contact rate of veterinary practices was associated with their number of clients, ranging in RR from 0.39 to 1.59. We concluded that the evaluation indicated differences in coverage of the passive surveillance components across regions, farms and veterinary practices. Due to the absence of emerging infections in the study period, we were unable to estimate the consequences of the observed differences for the early detection of disease. Nevertheless, regions and veterinary practices with low participation in passive surveillance might be a risk for early detection, and consequently, further understanding of the motivation to participate in passive surveillance components is needed.
Detection and Identification of Avian Reovirus in Young Geese (Anser anser domestica) in Poland
Authors: Nowak Tomasz , Kwiecinski Adam , Kwiecinski Piotr , Tomczyk Grzegorz , Wodz Karolina
Published: November 2022

Avian reovirus (ARV) is a cause of infections of broiler and turkey flocks, as well as waterfowl birds. This case report describes a reovirus detection in a fattening goose flock. GRV-infected geese suffer from severe arthritis, tenosynovitis, pericarditis, depressed growth, or runting-stunting syndrome (RSS), malabsorption syndrome, and respiratory and enteric diseases. GRV (goose reovirus) caused pathological lesions in various organs and joints, especially in the liver and spleen. GRV infection causes splenic necrosis, which induces immunosuppression, predisposing geese to infection with other pathogens, which could worsen the disease and lead to death. Our results showed that GRV was detected via RT-PCR and isolated in SPF (Specific Pathogen Free) embryos. This is the first report of the involvement of reovirus in arthritis, and the generalized infection of young geese in Poland, resulting in pathological changes in internal organs and sudden death. This study also provides new information about the GRV, a disease that is little known and underestimated.
MicroRNA Expression Variation in Female Dog (Canis familiaris) Reproductive Organs with Age and Presence of Uteropathy
Authors: Kim Eun Pyo , Kim Chae Young , Heo Min Young , Kim Sang Wha , Kim Geon A.
Published: November 2022

While aging is associated with microRNA (miRNA) expression, little is known about its role in the aging of dog reproductive organs. We examined miRNA expression in ovaries, oviducts, and uteri from young and old dogs and dogs with uteropathy to elucidate miRNA’s role in aging. The ovaries, oviducts, and uteri of 18 dogs (Canis familiaris)—young (8.5 ± 1.9 months old), old (78.2 ± 29.0 months old), and those with uteropathy (104.4 ± 15.1 months old)—were collected for miRNA expression examination. Total RNA samples were extracted, reverse-transcribed to cDNA, and real-time PCR analysis was also performed. In ovaries, miR-708 and miR-151 levels were significantly higher in old dogs than in young dogs, and only let-7a, let-7b, let-7c, miR125b, and miR26a were significantly upregulated in dogs with uteropathy. In the oviducts and uteri of old dogs, miR-140, miR-30d, miR-23a, miR-10a, miR-125a, miR-221, and miR-29a were upregulated. Realtime quantitative PCR revealed that targeted mRNA was similarly regulated to miRNA. These results suggest that miRNAs of reproductive organs in dogs may be biological markers for aging and reproductive diseases and could be used for mediating aging.
Assessment of Genetic Diversity and Conservation in South African Indigenous Goat Ecotypes: A Review
Authors: Magoro Aletta Matshidiso , Mtileni Bohani , Hadebe Khanyisile , Zwane Avhashoni
Published: November 2022

Goats were amongst the first livestock to be domesticated more than 10,000 years ago for their meat, milk, skin, and fiber. They were introduced to Southern Africa by migrating nations from Central Africa to the south. Due to local adaptation to the different agro-ecological zones and selection, indigenous goats are identified as ecotypes within the indigenous veld goat breed. Their ability to thrive in a resource-limited production system and in challenging environmental conditions makes them valuable animal resources for small-scale and emerging farmers. They play important roles in household agriculture and cultural activities as well as in poverty alleviation. Studies have described the phenotypic and genetic variations in indigenous goats, targeting the major goat-producing regions and the breeds of South Africa. In turn, information is restricted to certain breeds and regions, and the experimental design is often not adequate to inform the conservation status and priorities in changing environments. Advances in genomics technologies have availed more opportunities for the assessment of the biodiversity, demographic histories, and detection regions associated with local adaptation. These technologies are essential for breeding and conservation strategies for sustainable production for food security. This review focuses on the status of indigenous goats in South Africa and the application of genomics technologies for characterization, with emphasis on prioritization for conservation and sustainable utilization.
An Assessment of Starch Content and Gelatinization in Traditional and Non-Traditional Dog Food Formulations
Authors: Perry Erin Beth , Valach Alyssa Ann , Fenton Jesse Marie , Moore George E.
Published: November 2022

Starch gelatinization in pet food may be affected by moisture, retention time, and ingredients used. Starch gelatinization has been associated with changes in digestibility but is not well studied using non-traditional ingredients in canine diets. The objective of this research was to examine differences in starch content and gelatinization associated with changes in ingredient profile (traditional vs. non-traditional) and nutrient content requirements associated with differing life stages. Traditional diets (n = 10) utilizing protein sources including chicken, chicken by-product meal, meat and bone meal and plant-based ingredients including rice, barley, oats, and corn were examined in comparison with non-traditional diets (n = 10) utilizing protein sources including alligator, buffalo, venison, kangaroo, squid, quail, rabbit, and salmon along with plant-based ingredients including tapioca, chickpeas, lentils, potato, and pumpkin. Total starch and gelatinized starch (as percent of total diet) were measured with variation due to ingredient type assessed using Student’s t-test in SAS 9.4. Significance was set at p < 0.05. Total starch (as a percent of diet) was higher in traditional diets compared to non-traditional diets formulated for maintenance (p < 0.0032) or all life stages (p < 0.0128). However, starch gelatinization as a proportion of total starch was lower in traditional diets formulated for maintenance (p < 0.0165) and all life stages (p < 0.0220). Total starch and gelatinized starch had a strong negative correlation (r = −0.78; p < 0.01) in diets utilizing traditional ingredients. These novel data reveal important differences between starch content and gelatinization and may impact selection of various ingredient types by pet food manufacturers.
A Comparison of Intra-Articular Blood Cell Secretome and Blood Cell Secretome with Triamcinolone Acetonide in Dogs with Osteoarthritis: A Crossover Study
Authors: Alves J. C. , Santos Ana , Jorge Patrícia , Carreira L. Miguel
Published: November 2022

Osteoarthritis (OA) is a growing welfare problem for dogs and a challenge to manage for the clinician, and most therapeutic options aim to control pain. In a randomized, double-blinded, placebo-controlled, 2-way, 2-period crossover study, we aimed to evaluate the use of Blood Cell Secretome (BCS) administrated intra-articularly, with or without the combination with triamcinolone, in dogs with bilateral hip OA. BCS is an acellular orthobiologic containing anti-inflammatory and anabolic proteins produced from the patient’s own blood through extended coagulation in a defined environment. Fifteen dogs were initially assigned to a BCS group (BCSG, n = 5), a triamcinolone group (TG, n = 5), or a combination group (BCS+TG, n = 5). All had bilateral hip OA. After a 180-day follow-up, the crossover was performed with BCSG (n = 7) and BCS+TG (n = 7). BCSG received a single intra-articular administration of 3 mL of Blood Cell Secretome, and BCS+TG received BCS plus 0.5 mL of triamcinolone acetonide (40 mg/mL). The volume in BCSG was corrected to 3.5 mL with saline. In all patients, both hips were treated. For treatment follow-up, a copy of the Canine Brief Pain Inventory (divided into pain interference score—PIS and Pain Severity Score—PSS), Liverpool Osteoarthritis in Dogs (LOAD), and Canine Orthopedic Index (COI, divided into function, gait, stiffness, and quality of life) was completed on days 0, 8, 15, 30, 60, 90, 120, 150, and 180. Results were analyzed with the Mann–Whitney U test, effect size, and Kaplan–Meier estimators, followed by the log-rank test. p was set at <0.05. Patients of the sample had a mean age of 9.6 ± 2.9 years and a body weight of 29.2 ± 3.9 kg. Seven hips were classified as severe osteoarthritis, and eight were classified as moderate. No differences were found between groups at T0. Significant differences were observed in PSS scores at +8d, with BCS+TG exhibiting better results. PIS, PSS, LOAD, stiffness, and function scores were also lower in BCS+TG from +15 to +60d. The two groups showed similar improvements from +90 to +120d. Kaplan–Meier estimators showed that dogs in BCS+TG showed clinically-important differences for longer, despite a positive result in BCSG. The intra-articular administration of BCS alone was able to improve the overall condition of OA patients. Its combined use with triamcinolone acetonide lead to a faster and longer-lasting improvement in pain scores.
Performance, Egg Quality, and Yolk Antioxidant Capacity of the Laying Quail in Response to Dietary Choline Levels
Authors: Olgun Osman , Gül Esra Tuğçe , Kılınç Gözde , Yıldız Alpönder , Çolak Abdullah , Sarmiento-García Ainhoa
Published: November 2022

The current study determined the ideal dose of choline in the diet of laying quails based on egg development, egg quality, and antioxidant capacity. A total of 120 female quails (244.7 ± 10.38 g) were randomly assigned to 6 experimental groups with 5 replicates of 4 quails each. In the 10-week trial, treatment diets were formed by adding 6 choline chloride−60% concentrations providing 1500 (control), 2000, 2500, 3000, 3500, and 4000 mg/kg of choline. The feed intake of quails was quadratically affected (p < 0.05) by the choline level of the diet, in other developmental parameters, and by egg quality among these treatments. The feed intake was reduced to 2500 and 3000 mg/kg levels of choline in the diet compared to the control group. Free radical scavenging capacity (DPPH) of the yolk increased linearly (p < 0.001) with dietary choline levels. In contrast, the thiobarbituric acid reactive substances (TBARS) value decreased as dietary choline levels increased, except for 4000 mg/kg levels. Based on the findings of the current study, 1500 mg/kg of dietary choline is adequate to maintain performance parameters and egg quality in laying quails. However, to increase egg antioxidant capacity, in terms of the DPPH value, the dietary choline dose needs to be increased to 3500 mg/kg.
Seasonal Trophic Ecology and Diet Shift in the Common Sole Solea solea in the Central Adriatic Sea
Authors: Fanelli Emanuela , Principato Elena , Monfardini Eleonora , Da Ros Zaira , Scarcella Giuseppe , Santojanni Alberto , Colella Sabrina
Published: November 2022

The common sole, Solea solea, is one the most important commercial species in Europe and, within the Mediterranean, the Adriatic basin is the most crucial area for its production. Although the species is overexploited in the basin, data on its trophic ecology are fragmentary, even though this is one of the most important features within the Ecosystem Approach to Fishery. Here, we analysed temporal variations in the feeding ecology of the species by using an integrated approach of stomach contents and stable isotope analyses coupled with the analysis of some condition indices such as the gonadosomatic and the hepatosomatic indices. Changes in diet and trophic level across the years in adult females were clearly linked to the different energetic requirements facing reproduction. Temporal changes throughout the year were mainly related to changes in food availability. This study confirms the opportunistic behaviour of this benthophagous species and its role as a mesopredator, opening new perspectives for further investigations on the effects of the overexploitation of this important fishery resource on the marine trophic web.
Wild Chimpanzee Welfare: A Focus on Nutrition, Foraging and Health to Inform Great Ape Welfare in the Wild and in Captivity
Authors: Gerstner Katie F. , Pruetz Jill D.
Published: November 2022

Adequate nutrition is essential for individual well-being, survival and reproductive fitness. Yet, in wild animals, including great apes, scoring nutrition or health comes with many challenges. Here, we have two aims: first, broadly review the scientific literature regarding nutritional data on wild chimpanzee foods to get a better understanding what nutrients foods comprise of, and second, highlight important findings on wild chimpanzee nutrition and welfare pertaining to diet. We discuss variation in macro and micronutrients in food items consumed and their role in chimpanzee health across chimpanzee subspecies from multiple study sites. We found a lack of information pertaining to nutritional consumption rates of daily diets. Second, we call for a fresh, in-depth discussion on wild chimpanzee welfare issues is of foremost importance to inform conservation projects and particularly settings where humans and chimpanzees may interact, because such conversation can reveal how specific or general welfare measures can (a) inform our knowledge of an individual’s, group’s, and population’s welfare, (b) provide additional measures from the study of wild chimpanzee ecology that can guide the welfare of captive chimpanzees, and (c) can enable comparative study of welfare across wild populations. A summary of the current literature on approaches to measuring wild chimpanzee health and welfare status, to our knowledge, has yet to be done.
Epidemiology, Outcomes and Tolerability of Protracted Treatment of Nontuberculous Mycobacterial Infections at a Community Teaching Hospital in the Southeastern United States
Authors: Tsai Yuwei Vivian , Derrick Caroline , Yunusa Ismaeel , Weissman Sharon , Al-Hasan Majdi N. , Justo Julie Ann , Bookstaver Paul Brandon
Published: November 2022

Nontuberculous mycobacterial (NTM) infections present a treatment challenge for clinicians and patients. There are limited data about current susceptibility patterns and treatment outcomes in U.S. adults. This was a 10-year, single-center, retrospective, observational cohort study of adults with a positive NTM culture and clinical suspicion of infection between 1 January 2010 and 30 June 2020. The primary objective was to identify predictors for favorable treatment outcomes. Key secondary objectives were characterization of NTM epidemiology, susceptibility profiles, and safety and tolerability of treatment, including the proportion of subjects with an antimicrobial change and the reasons for the change. Of 250 subjects diagnosed with NTM infection, the most prevalent NTM isolates were Mycobacterium avium intracellulare complex (66.8%) followed by Mycobacterium abscessus (17.6%). Antimicrobial susceptibility data were available for 52.4% of the cohort (45.8% slow growers; 54.2% rapid growers). Only 88 (35%) subjects received treatment with evaluable clinical outcomes. The proportion of subjects with a favorable outcome was 61.4%. More subjects in the unfavorable outcome group experienced a change in antimicrobial therapy (73.5% vs. 51.9%, p = 0.043). The most common reason for antimicrobial change was adverse drug events (n = 36, 67.9%). In the regression model, private insurance was associated with a favorable outcome, whereas having multiple antimicrobial changes was associated with an unfavorable outcome. The complexity of NTM treatment and high incidence of medication-related issues suggest the necessity of interdisciplinary collaboration to improve overall treatment outcomes in NTM infections.
Biocide-Resistant Escherichia coli ST540 Co-Harboring ESBL, dfrA14 Confers QnrS-Dependent Plasmid-Mediated Quinolone Resistance
Authors: Bharathi Srinivasan Vijaya , Rajamohan Govindan
Published: November 2022

Emerging sequence types of pathogenic bacteria have a dual ability to acquire resistance islands/determinants, and remain renitent towards disinfection practices; therefore, they are considered “critical risk factors” that contribute significantly to the global problem of antimicrobial resistance. Multidrug-resistant Escherichia coli was isolated, its genome sequenced, and its susceptibilities characterized, in order to understand the genetic basis of its antimicrobial resistance.The draft genome sequencing of E. coli ECU32, was performed with Illumina NextSeq 500, and annotated using a RAST server. The antibiotic resistome, genomic island, insertion sequences, and prophages were analyzed using bioinformatics tools. Subsequently, analyses including antibiotic susceptibility testing, E-test, bacterial growth, survival, and efflux inhibition assays were performed.The draft genome of E. coli ECU32 was 4.7 Mb in size, the contigs were 107, and the G+C content was 50.8%. The genome comprised 4658 genes, 4543 CDS, 4384 coding genes, 115 RNA genes, 88 tRNAs, and 3 CRISPR arrays. The resistome characterization of ST540 E. coli ECU32 revealed the presence of ESBL, APH(6)-Id, APH(3′)-IIa, dfrA14, and QnrS1, with broad-spectrum multidrug and biocide resistance. Comparative genome sequence analysis revealed the presence of transporter and several virulence genes. Efflux activity and growth inhibition assays, which were performed with efflux substrates in the presence of inhibitor PAβN, exhibited significant reduced growth relative to its control.This study discusses the genotypic and phenotypic characterization of the biocide-tolerant multidrug-resistant E. coli O9:H30 strain, highlighting the contributory role of qnrS-dependent plasmid-mediated quinolone resistance, in addition to innate enzymatic modes of multidrug resistance mechanisms.
Redox Properties, Bioactivity and Health Effects of Indicaxanthin, a Bioavailable Phytochemical from Opuntia ficus indica, L.: A Critical Review of Accumulated Evidence and Perspectives
Authors: Attanzio Alessandro , Restivo Ignazio , Tutone Marco , Tesoriere Luisa , Allegra Mario , Livrea Maria A.
Published: November 2022

Phytochemicals from plant foods are considered essential to human health. Known for their role in the adaptation of plants to their environment, these compounds can induce adaptive responses in cells, many of which are directed at maintaining the redox tone. Indicaxanthin is a long-known betalain pigment found in the genus Opuntia of cactus pear and highly concentrated in the edible fruits of O. ficus indica, L. whose bioactivity has been overlooked until recently. This review summarizes studies conducted so far in vitro and in vivo, most of which have been performed in our laboratory. The chemical and physicochemical characteristics of Indicaxanthin are reflected in the molecule’s reducing properties and antioxidant effects and help explain its ability to interact with membranes, modulate redox-regulated cellular pathways, and possibly bind to protein molecules. Measurement of bioavailability in volunteers has been key to exploring its bioactivity; amounts consistent with dietary intake, or plasma concentration after dietary consumption of cactus pear fruit, have been used in experimental setups mimicking physiological or pathophysiological conditions, in cells and in animals, finally suggesting pharmacological potential and relevance of Indicaxanthin as a nutraceutical. In reporting experimental results, this review also aimed to raise questions and seek insights for further basic research and health promotion applications.
Berberine Regulation of Cellular Oxidative Stress, Apoptosis and Autophagy by Modulation of m6A mRNA Methylation through Targeting the Camk1db/ERK Pathway in Zebrafish-Hepatocytes
Authors: Zhang Meijuan , Liu Jin , Yu Chengbing , Tang Shangshang , Jiang Guangzhen , Zhang Jing , Zhang Hongcai , Xu Jianxiong , Xu Weina
Published: November 2022

Berberine (BBR) ameliorates cellular oxidative stress, apoptosis and autophagy induced by lipid metabolism disorder, however, the molecular mechanism associated with it is not well known. To study the mechanism, we started with m6A methylation modification to investigate its role in lipid deposition zebrafish hepatocytes (ZFL). The results showed that BBR could change the cellular m6A RNA methylation level, increase m6A levels of Camk1db gene transcript and alter Camk1db gene mRNA expression. Via knockdown of the Camk1db gene, Camk1db could promote cellular ERK phosphorylation levels. Berberine regulated the expression level of Camk1db mRNA by altering the M6A RNA methylation of the Camk1db gene, which further affected the synthesis of calmodulin-dependent protein kinase and activated ERK signaling pathway resulting in changes in downstream physiological indicators including ROS production, cell proliferation, apoptosis and autophagy. In conclusion, berberine could regulate cellular oxidative stress, apoptosis and autophagy by mediating Camk1db m6A methylation through the targeting of the Camk1db/ERK pathway in zebrafish-hepatocyte.
Nrf2 Regulates Oxidative Stress and Its Role in Cerebral Ischemic Stroke
Authors: Wang Lei , Zhang Xu , Xiong Xiaoxing , Zhu Hua , Chen Ran , Zhang Shudi , Chen Gang , Jian Zhihong
Published: November 2022

Cerebral ischemic stroke is characterized by acute ischemia in a certain part of the brain, which leads to brain cells necrosis, apoptosis, ferroptosis, pyroptosis, etc. At present, there are limited effective clinical treatments for cerebral ischemic stroke, and the recovery of cerebral blood circulation will lead to cerebral ischemia-reperfusion injury (CIRI). Cerebral ischemic stroke involves many pathological processes such as oxidative stress, inflammation, and mitochondrial dysfunction. Nuclear factor erythroid 2-related factor 2 (Nrf2), as one of the most critical antioxidant transcription factors in cells, can coordinate various cytoprotective factors to inhibit oxidative stress. Targeting Nrf2 is considered as a potential strategy to prevent and treat cerebral ischemia injury. During cerebral ischemia, Nrf2 participates in signaling pathways such as Keap1, PI3K/AKT, MAPK, NF-κB, and HO-1, and then alleviates cerebral ischemia injury or CIRI by inhibiting oxidative stress, anti-inflammation, maintaining mitochondrial homeostasis, protecting the blood–brain barrier, and inhibiting ferroptosis. In this review, we have discussed the structure of Nrf2, the mechanisms of Nrf2 in cerebral ischemic stroke, the related research on the treatment of cerebral ischemia through the Nrf2 signaling pathway in recent years, and expounded the important role and future potential of the Nrf2 pathway in cerebral ischemic stroke.
Observing Meteorological Tides: Fifteen Years of Statistics in the Port of La Spezia (Italy)
Authors: Soldani Maurizio , Faggioni Osvaldo
Published: November 2022

Sea level changes in coastal areas significantly influence port activities (e.g., the safety of navigation). Along Italian coastlines, sea level variations are mainly due to astronomical tides (well known, due to gravitational attraction between Earth, Moon and Sun); however, during the last fifteen years, a high number of “anomalous” tides has been observed: the study of the phenomenon has allowed to attribute its cause to variations in atmospheric pressure (the so-called meteorological tides: sea level drops when atmospheric pressure increases and vice versa); the statistical analysis of acquired data made it possible to evaluate the hydrobarometric transfer factor (a local parameter which represents the correlation between atmospheric pressure changes and consequent sea level variations): it was found that it is usually much larger within gulfs or port basins than offshore areas, where a pressure change of 1 hPa results in a sea level variation of about 1 cm; the statistical analysis described in the following, and aimed at correctly estimating the hydrobarometric transfer factor in harbors, can play a fundamental role in optimizing the management of port waters: its results allow to forecast meteorological tides and therefore future sea level (and depth) variations in a given port basin. The results of the study conducted in the port of La Spezia (North Western Italy) are presented here, together with possible applications on port activities and harbor water management.
Frequency-Domain Lifting-Line Aerodynamic Modelling for Wing Aeroelasticity
Authors: Giansante Riccardo , Bernardini Giovanni , Gennaretti Massimo
Published: November 2022

A frequency-domain lifting-line solution algorithm for the prediction of the unsteady aerodynamics of wings is presented. The Biot–Savart law is applied to determine the normalwash generated by the wake vorticity distribution, whereas steady and unsteady airfoil theories (Glauert’s and Theodorsen’s, respectively) are used to evaluate the sectional aerodynamic loads, namely the lift and pitching moment. The wake vorticity released at the trailing edge derives from the bound circulation through the Kutta condition and is convected downstream with the velocity of the undisturbed flow. The local bound circulation is obtained by the application of the Kutta–Joukowski theorem, extended to unsteady flows. Assuming a bending and torsion wing, this paper provides the aerodynamic matrix of the transfer functions, relating the generalised aerodynamic loads to the Lagrangian coordinates of the elastic deformation. Its rational approximation yields a reduced-order state-space aerodynamic model suitable for an aeroelastic stability analysis and control purposes. The numerical investigation examines the influence of both the wake shed/trailed vorticity modelling and different approximations of the Kutta–Joukowski theorem for unsteady flows on the aerodynamic transfer functions given by the developed frequency-domain lifting-line solver. The accuracy of the solver is assessed by comparison with the predictions obtained by a three-dimensional boundary-element-method solver for potential flows. It is shown that, at least for the frequency range considered, regardless of the approximation of the Kutta–Joukowski theorem applied, the formulation based on the Theodorsen theory provides predictions that are in very good agreement with the results from the boundary element method for a slender wing. This agreement worsens as the wing aspect ratio decreases. A lower level of accuracy is obtained by the application of the sectional loads given by the Glauert theory. In this case, the predictions are more sensitive to the approximation used to express the Kutta–Joukowski theorem for unsteady flows.
Two-View Mammogram Synthesis from Single-View Data Using Generative Adversarial Networks
Authors: Yamazaki Asumi , Ishida Takayuki
Published: November 2022

While two-view mammography taking both mediolateral-oblique (MLO) and cranio-caudual (CC) views is the current standard method of examination in breast cancer screening, single-view mammography is still being performed in some countries on women of specific ages. The rate of cancer detection is lower with single-view mammography than for two-view mammography, due to the lack of available image information. The goal of this work is to improve single-view mammography’s ability to detect breast cancer by providing two-view mammograms from single projections. The synthesis of novel-view images from single-view data has recently been achieved using generative adversarial networks (GANs). Here, we apply complete representation GAN (CR-GAN), a novel-view image synthesis model, aiming to produce CC-view mammograms from MLO views. Additionally, we incorporate two adaptations—the progressive growing (PG) technique and feature matching loss—into CR-GAN. Our results show that use of the PG technique reduces the training time, while the synthesized image quality is improved when using feature matching loss, compared with the method using only CR-GAN. Using the proposed method with the two adaptations, CC views similar to real views are successfully synthesized for some cases, but not all cases; in particular, image synthesis is rarely successful when calcifications are present. Even though the image resolution and quality are still far from clinically acceptable levels, our findings establish a foundation for further improvements in clinical applications. As the first report applying novel-view synthesis in medical imaging, this work contributes by offering a methodology for two-view mammogram synthesis.
Improving Lignocellulosic and Non-Lignocellulosic Biomass Characteristics through Torrefaction Process
Authors: Ivanovski Maja , Urbancl Danijela , Petrovič Aleksandra , Stergar Janja , Goričanec Darko , Simonič Marjana
Published: November 2022

In this study, three locally available biomasses, namely miscanthus, hops, sewage sludge, and additionally, their mixtures, were subjected to the torrefaction process to improve their fuel properties. The torrefaction process was conducted at 250–350 °C and 10–60 min in a nitrogen (N2) environment. The torrefaction temperature and time were studied to evaluate the selected biomass materials; furthermore, heating values, mass and energy yields, enhancement factors, torrefaction severity indexes (TSI), and energy-mass co-benefit indexes (EMCI) were calculated. In addition, thermogravimetric (TGA) and Fourier transform infrared analyses (FTIR) were performed to characterize raw and torrefied biomass under the most stringent conditions (350 °C and 60 min). The results showed that with increasing torrefaction temperature and duration, mass and energy yields decreased, and heating values (HHVs) increased for all studied biomasses. The results of the TSI and EMCI indexes showed that the optimum torrefaction conditions were as follows: 260 °C and 10 min for pure miscanthus and hops, whilst this could not be confirmed for the sewage sludge. Furthermore, the combination of sewage sludge and the above-mentioned types of lignocellulosic biomass exhibited better fuel properties than sewage sludge alone.
Modelling and Mapping of Soil Erosion Susceptibility of Murree, Sub-Himalayas Using GIS and RS-Based Models
Authors: Islam Fakhrul , Ahmad Muhammad Nasar , Janjuhah Hammad Tariq , Ullah Matee , Islam Ijaz Ul , Kontakiotis George , Skilodimou Hariklia D. , Bathrellos George D.
Published: November 2022

Soil erosion is one of Pakistan’s most serious environmental threats. This study used geospatial modelling to identify the distinct zones susceptible to soil erosion in Murree, Pakistan. Using a machine learning technique in the Google Earth engine (GEE) and Google Earth, we identified 1250 soil erosion events. The inventory (dependent variable) was separated into two datasets, one for training (70%) and one for testing (30%). Elevation, slope, aspect, curvature, stream, precipitation, LULC, lithology, soil, NDVI, and distance to road were prepared in ArcGIS and considered as independent variables in the current research. GIS and RS-based models such as WOE, FR, and IV were used to assess the relationship between both variables and produce soil erosion susceptibility maps. Finally, the Area Under Curve (AUC) approach was used to confirm the research results. According to the validation data, the SRC for WOE, FR, and IV were 88%, 91%, and 87%, respectively. The present study’s validation results show that the PRC for WOE, FR, and IV are 92%, 94%, and 90%, respectively. Based on the AUC validation approach, we determined that the FR model had the highest accuracy when compared to the other two techniques, the WOE and IV models. The current analysis and final susceptibility maps of soil erosion could be useful for decision-makers in the future to prevent soil erosion and its negative repercussions.
Development of an Ensembled Meta-Deep Learning Model for Semantic Road-Scene Segmentation in an Unstructured Environment
Authors: Sivanandham Sangavi , Gunaseelan Dharani Bai
Published: November 2022

Road scene segmentation is an integral part of the Intelligent Transport System (ITS) for precise interpretation of the environment and safer vehicle navigation. Traditional segmentation methods have faced difficulties in meeting the requirements of unstructured and complex image segmentation. Therefore, the Deep-Neural Network (DNN) plays a significant role in effectively segmenting images with multiple classes in an unstructured environment. In this work, semantic segmentation models such as U-net, LinkNet, FPN, and PSPNet are updated to use classification networks such as VGG19, Resnet50, Efficientb7, MobilenetV2, and Inception V3 as pre-trained backbone architectures, and the performance of each updated model is compared with the unstructured Indian Driving-Lite (IDD-Lite) dataset. In order to improve segmentation performance, a stacking ensemble approach is proposed to combine the predictions of a semantic segmentation model across different backbone architectures using a simple grid search method. Thus, four ensemble models are formed and analyzed on the IDD-Lite dataset. The two metrics Intersection over Union (IoU or Jaccard index) and Dice coefficient (F1 score) are used to assess the segmentation performance of each ensemble model. The results show that an ensemble of U-net with different backbone architectures is more efficient than other ensemble models. This model has achieved 73.12% and 76.67%, respectively, in IoU and F1 scores.
Application of Design of Experimental Methods in Theoretical Analysis of the Gas-Delayed Blowback Operation Firearm Action
Authors: Morawski Mateusz , Fikus Bartosz , Woźniak Ryszard , Trębiński Radosław
Published: November 2022

A mathematical model of the gas-delayed blowback operation firearm action is presented in the paper. Mathematical equations and relations describing the action of this automatic weapon system are shown. Results of theoretical calculations are analyzed from the point of view of the influence of system (weapon) parameters (factors) on braking the recoiling assembly movement. In the analysis of computer simulation results, the design of experimental methods are used. The significance of the effects of individual parameters on output characteristics are estimated. This enables us to eliminate insignificant parameters and to assess the character of the dependence on significant parameters. The obtained results serve as a basis for the design of a new laboratory stand and for planning experiments which significantly reduce the time and cost of experimental tests. The stand will be used for a detailed verification and validation of the proposed model.
Failure Propagation Controlling for Frangible Composite Canister Design
Authors: Smarrazzo Aniello , Guida Michele , Marulo Francesco , Coppola Massimo , Molitierno Raffaele
Published: November 2022

The complexity in predicting the damage initiation and failure propagation controlling in composite structures is challenging. The focus of this paper is to design a potential component for new ship gunnels to make the composite canister affordable in structural applications by using a damage tolerant design approach. The design of a new tailgate configuration was investigated, taking into account the correct fragmentation of the structure to ensure a clear ejection while reducing the weight of the panels by exploiting the properties of the composite material. The complex geometry of the tailgate, the high impulse load, the energy transferred to the tailgate during missile impact, and how to safely break large panel flaps are elements that characterize the sizing of the composite component to meet the stringent ejection requirements in the life cycle of a missile during takeoff. The numerical simulations were performed using the LS/Dyna code and its explicit formulation was contemplated to take into account the geometrical, contact, and material non linearities.
Adaptive Robust Admittance Control of Robots Using Duality Principle-Based Impedance Selection
Authors: Sun Tairen , Wang Zekai , He Chen , Yang Lihong
Published: November 2022

The performance of robot admittance control depends heavily on environmental dynamics, the desired impedance selection, and control input. In this study, an adaptive robust admittance control strategy is proposed for robot–environment interaction. The environmental impedance is estimated using an adaptive law with projection modification to guarantee that the impedance estimator is constrained in a predefined set. Then, the desired robot stiffness and damping are determined based on the duality principle. To obtain the desired impedance dynamics, an adaptive robust admittance controller based on time-delay estimation is designed for the robot to track the admittance trajectory with the prescribed performance. Simulations are conducted to show the effectiveness of the environmental impedance estimation and the proposed adaptive robust admittance control.
Working Condition Recognition of a Mineral Flotation Process Using the DSFF-DenseNet-DT
Authors: Liu Hongchang , He Mingfang , Cai Weiwei , Zhou Guoxiong , Wang Yanfeng , Li Liujun
Published: November 2022

The commonly used working condition recognition method in the mineral flotation process is based on shallow features of flotation froth images. However, the shallow features of flotation froth images frequently have an excessive amount of redundant and noisy information, which has an impact on the recognition effect and prevents the flotation process from being effectively optimized. Therefore, a working condition recognition method for the mineral flotation process based on a deep and shallow feature fusion densely connected network decision tree (DSFF-DenseNet-DT) is proposed in this paper. Firstly, the color texture distribution (CTD) and size distribution (SD) of a flotation froth image obtained in advance are approximated by the nonparametric kernel density estimation method, and a set of kernel function weights is obtained to represent the color texture and size features, while the deep features of the flotation froth image are extracted through the densely connected network (DenseNet). Secondly, a two-stage feature fusion method based on a stacked autoencoder after Concat (Cat-SAE) is proposed to fuse and reduce the dimensionality of the extracted shallow features and deep features so as to maximize the comprehensive description of the features and eliminate redundant and noisy information. Finally, the feature vectors after fusion dimensionality reduction are fed into the densely connected network decision tree (DenseNet-DT) for working condition recognition. Multiple experiments employing self-built industrial datasets reveal that the suggested method’s average recognition accuracy, precision, recall and F1 score reach 92.67%, 93.9%, 94.2% and 0.94, respectively. These results demonstrate the proposed method’s usefulness.
Automatic Brix Measurement for Watermelon Breeding
Authors: Huang Jingjing , Zou Ting , Hu Heming , Xiao Xu , Wang Zhiwei , Li Ming , Dai Sihui
Published: November 2022

Sweetness or sugar content, represented by soluble solids contents (SSC), is a vital quality trait in watermelon breeding which can be assessed by the refractive index method. However, sampling watermelon juice out of the pulp is a process that is both labor-intensive and error-prone. In this study, we developed an automatic SSC measurement system for watermelon breeding to improve efficiency and decrease costs. First, we built an automatic cutting system to cut watermelons into precise halves, in which a laser rangefinder is used to measure the distance from the upper surface of the watermelon to itself, and thus, the diameter is estimated. The experiments showed a high correlation between the estimated diameters and the ground truths, with and . Then, we built an automatic Brix measurement system to obtain the Brix data from a central point on the watermelon’s section, where an image analysis procedure is applied to locate the testing point. This is then transformed to the camera coordination system, and a refractometer is driven by a 3-axis robotic arm to reach the testing point. Brix measurement experiments were conducted using three vertical gaps and four lateral gaps between the probe of the refractometer and the pulp. The result showed that the best parameters were a vertical gap of 4 mm and a lateral gap of 2 mm. The average accuracy reached 98.74%, which indicates that this study has the potential to support watermelon breeding research.
Real-Time Filtering Non-Intentional Bid Request on Demand-Side Platform
Authors: Nguyen Thi-Thanh-An , Ha Duy-An , Zhu Wen-Yuan , Yuan Shyan-Ming
Published: November 2022

While real-time bidding brings a huge profit for online businesses, it also becomes a potential target for malicious purposes. In real-time bidding, the bid request traffic could be classified into two kinds: intentional and non-intentional. Intentional bid requests come from ordinal web users while non-intentional bid requests come from abnormal web users. From the perspective of a demand-side platform (DSP), the budget of advertisers should be used as effectively as possible by limiting non-intentional traffic. Therefore, it is essential to classify and predict these two kinds of bid request traffic. In this research, we propose a real-time filtering bid requests (RFBR) model to predict whether an incoming bid request is intentional or non-intentional from the DSP’s viewpoint. Our model is built on three stages. In the first stage, we analyzed all potential attributes in the bid request scheme and figured out the relations between abnormal behaviors and their attributes; in the second stage, a classification model was built to classify normal and abnormal audiences by the extracted features and self-defined thresholds; in the third stage, a RFBR model was built to classify intentional and non-intentional bid requests. The experimental result shows that our system can effectively classify incoming bid requests.
Fuzzy Neural Network Dynamic Inverse Control Strategy for Quadrotor UAV Based on Atmospheric Turbulence
Authors: Yang Zhibo , Cheng Ben , Lv Chengxing , Wang Yanqian , Lu Peng
Published: November 2022

Quadrotor UAV is vulnerable to external interference, which affects search and rescue. In this paper, a fuzzy neural network dynamic inverse controller (FNN-DIC) is designed to eliminate the instability of the attitude angle caused by atmospheric turbulence. Considering the complexity of atmospheric turbulence, the component model of atmospheric turbulence is obtained firstly based on the Dryden model, using Gaussian white noise as a random input signal and a designed shaping filter. Combined with the Newton-Euler equation, a nonlinear dynamic model for the quadrotor UAV with atmospheric disturbance is established. While the traditional nonlinear dynamic inverse cancels the nonlinearity of the controlled object, it relies on precise mathematical models. The fuzzy neural network can adaptively compensate for the inaccurate part of the model and the inverse error of the model caused by the external disturbance, and the stability of the control system is strictly proved by using the Lyapunov function. The experiments are carried out on the simulation platform, and the results show that the FNN method can ensure that the quadrotor UAV can still fly smoothly against strong disturbances, and that robustness of the system is significantly improved.
Impact and Stability of Mandibular Setback after Intraoral Vertical Ramus Osteotomy
Authors: Dobriyan Alex , Akerman Eyal , Yoffe Tal , Blinder Daneilla , Tessler Idit , Gecel Nir Abraham , Mesika Mor , Yahalom Ran
Published: November 2022

(1) Background: The purpose of this study was to evaluate stability and complications following mandibular setback using intraoral vertical ramus osteotomy (IVRO) and provide an assessment of IMF (Inter-maxillary Fixation) compliance. (2) Methods: This is a retrospective cohort study. It included a total of 39 patients who underwent 78 IVRO for the treatment of mandibular prognathism between 2005 and 2021 at Sheba Medical Center. Radiographic and clinical examinations were performed preoperatively (T0), 3 days post-surgery (T1) and 8 months post-surgery (T2). Measurements of dental and skeletal stability, as well as neurosensory disturbances and TMJ dysfunctions, were statistically analyzed. (3) Results: The mean mandibular setback was 5.6 mm. A relapse of less than 2 mm was observed at T2. A short-term neurological disturbance was reported in 38.46% of the 39 patients, and 17.94% of them showed full recovery by T2. In 21 patients who underwent IVRO without genioplasty, only 14.28% reported long-term sensory disturbance. In addition, when a vertical osteotomy was performed, neurological damage was 174% higher as compared to oblique osteotomy. The IMF compliance rate for the 6 weeks postoperatively was 100%. (4) Conclusions: IVRO is still a relevant and valid technique for the treatment of mandibular prognathism that provides stable results with minimal complications rate.
A Military Object Detection Model of UAV Reconnaissance Image and Feature Visualization
Authors: Liu Huanhua , Yu Yonghao , Liu Shengzong , Wang Wei
Published: November 2022

Military object detection from Unmanned Aerial Vehicle (UAV) reconnaissance images faces challenges, including lack of image data, images with poor quality, and small objects. In this work, we simulate UAV low-altitude reconnaissance and construct the UAV reconnaissance image tank database UAVT-3. Then, we improve YOLOv5 and propose UAVT-YOLOv5 for object detection of UAV images. First, data augmentation of blurred images is introduced to improve the accuracy of fog and motion-blurred images. Secondly, a large-scale feature map together with multi-scale feedback is added to improve the recognition ability of small objects. Thirdly, we optimize the loss function by increasing the loss penalty of small objects and classes with fewer samples. Finally, the anchor boxes are optimized by clustering the ground truth object box of UAVT-3. The feature visualization technique Class Action Mapping (CAM) is introduced to explore the mechanisms of the proposed model. The experimental results of the improved model evaluated on UAVT-3 show that the mAP reaches 99.2%, an increase of 2.1% compared with YOLOv5, the detection speed is 40 frames per second, and data augmentation of blurred images yields an mAP increase of 20.4% and 26.6% for fog and motion blur images detection. The class action maps show the discriminant region of the tanks is the turret for UAVT-YOLOv5.