bluuebunny/crossref_metadata_2025 huggingface dataset:
An Integrated UWB-IMU-Vision Framework for Autonomous Approaching and Landing of UAVs
Authors: Dong Xin , Gao Yuzhe , Guo Jinglong , Zuo Shiyu , Xiang Jinwu , Li Daochun , Tu Zhan
Published: December 2022

Unmanned Aerial Vehicles (UAVs) autonomous approaching and landing on mobile platforms always play an important role in various application scenarios. Such a complicated autonomous task requires an integrated multi-sensor system to guarantee environmental adaptability in contrast to using each sensor individually. Multi-sensor fusion perception demonstrates great feasibility to compensate for adverse visual events, undesired vibrations of inertia sensors, and satellite positioning loss. In this paper, a UAV autonomous landing scheme based on multi-sensor fusion is proposed. In particular, Ultra Wide-Band (UWB) sensor, Inertial Measurement Unit (IMU), and vision feedback are integrated to guide the UAV to approach and land on a moving object. In the approaching stage, a UWB-IMU-based sensor fusion algorithm is proposed to provide relative position estimation of vehicles with real time and high consistency. Such a sensor integration addresses the open challenge of inaccurate satellite positioning when the UAV is near the ground. It can also be extended to satellite-denied environmental applications. When the landing platform is detected by the onboard camera, the UAV performs autonomous landing. In the landing stage, the vision sensor is involved. With the visual feedback, a deep-learning-based detector and local pose estimator are enabled when the UAV approaches the landing platform. To validate the feasibility of the proposed autonomous landing scheme, both simulation and real-world experiments in extensive scenes are performed. As a result, the proposed landing scheme can land successfully with adequate accuracy in most common scenarios.
Relative Dynamics and Modern Control Strategies for Rendezvous in Libration Point Orbits
Authors: Cuevas del Valle Sergio , Urrutxua Hodei , Solano-López Pablo , Gutierrez-Ramon Roger , Sugihara Ahmed Kiyoshi
Published: December 2022

Deep space missions are recently gaining increasing interest from space agencies and industry, their maximum exponent being the establishment of a permanent station in cis-lunar orbit within this decade. To that end, autonomous rendezvous and docking in multi-body dynamical environments have been defined as crucial technologies to expand and maintain human space activities beyond near Earth orbit. Based on analytical and numerical formulations of the relative dynamics in the Circular Restricted Three Body Problem (CR3BP), a family of optimal, linear and nonlinear, continuous and impulsive, guidance and control techniques are developed for the design of end-to-end rendezvous trajectories between co-orbiting spacecraft in this multi-body dynamical environment. To this end, several modern control techniques are effectively designed and adapted to this problem, with particular emphasis on the design of low cost rendezvous manoeuvres. Finally, the designed hybrid rendezvous strategies, combining both discrete and continuous control techniques, are effectively tested and validated under several start-to-end deep space testbench mission scenarios, where their performance is compared and quantitatively assessed with a set of performance indices.
Direct and Endophytic Effects of Fungal Entomopathogens for Sustainable Aphid Control: A Review
Authors: Francis Frederic , Fingu-Mabola Junior Corneille , Ben Fekih Ibtissem
Published: December 2022

Entomopathogenic fungi (EPF) are cosmopolitan species of great interest in pest management due to their ability to cause epizooty in soil-dwelling and aboveground insects. Besides their direct effect against a wide host range of serious agricultural insect pests, such as aphids, a major emphasis has been placed on investigating the impact of EPF with endophytic traits (EIPF) on aboveground tripartite interactions between host plants, herbivores and beneficial insects. However, despite their valuable role in biocontrol processes, there is still more to explore about their diverse potential as ecofriendly biological control agents. Herein, we provide an overview of the meaningful role and faced challenges following the use of EPF and EIPF to control aphids.
Physiological and Biochemical Changes in Vegetable and Field Crops under Drought, Salinity and Weeds Stresses: Control Strategies and Management
Authors: Abdelaal Khaled , Alsubeie Moodi Saham , Hafez Yaser , Emeran Amero , Moghanm Farahat , Okasha Salah , Omara Reda , Basahi Mohammed A. , Darwish Doaa Bahaa Eldin , Ibrahim Mohamed F. M. , El-Yazied Ahmed Abou , Rashwan Emadeldeen Ahmed , Elkelish Amr , Mady Mohamed Ahmed , Ibraheem Farag
Published: December 2022

Weeds are one of the most damaging biotic stresses in crop production, and drought and salinity are considered the most serious abiotic stresses. These factors harmfully affect growth and development in several vegetable and field crops by causing harmful effects on physiological and biochemical characteristics such as water uptake, photosynthesis, relative water content, electrolyte leakage, and antioxidant compounds linked with oxidative stress and the accumulation of reactive oxygen species (ROS). These oxidative stress-related components affect most physiological and biochemical characteristics in plants under natural conditions and environmental stresses, especially weed infestation, salinity, and drought stress. ROS such as superoxide (O2•−), hydrogen peroxide (H2O2), peroxyl radical (ROO•), and singlet oxygen (1O2) are very important molecules produced naturally as by-products of metabolic processes in chloroplasts, mitochondria, peroxisomes, and the apoplast. Under stress conditions such as weed infestation, drought and salinity, the morphological and yield characteristics of stressed plants are negatively affected; however, superoxide (O2•−) and hydrogen peroxide (H2O2) are significantly increased. The negative impact of weeds can be mitigated with integrated controls which include herbicides, allelopathy, and crop rotation as well as the different methods for weed control. The defense system in various crops mainly depends on both enzymatic and nonenzymatic antioxidants. The enzymatic antioxidants include superoxide dismutase, glutathione reductase, and catalase; nonenzymatic antioxidants include ascorbic acid, carotenoids, α-Tocopherols, proline, glutathione, phenolics, and flavonoids. These antioxidant components can scavenge various ROS under several stresses, particularly weeds, drought and salinity. In this review, our objective is to shed light on integrated weeds management and plant tolerance to salinity and drought stresses associated with the ROS and the induction of antioxidant components to increase plant growth and yield in the vegetable and field crops.
Does the 10-Year Fishing Ban Compensation Policy in the Yangtze River Basin Improve the Livelihoods of Fishing Households? Evidence from Ma’anshan City, China
Authors: He Yufeng , Chen Tinggui
Published: December 2022

The implementation of the 10-year fishing ban compensation policy in the Yangtze River basin is the first practice of the river ecological compensation project in China, which has a milestone value to protect China’s ecological sustainability and boost green development. Based on the survey data of 212 retired fishing households in Ma’anshan city, this paper constructs a livelihood capital evaluation system, coupled with coordination model and mobility matrix to analyze the policy effect on participants’ livelihood from the changes of livelihood capital amounts on structure and mobility. The key results are threefold. (1) Policy implementation has significantly raised retired households’ livelihood capital index; (2) The households livelihood capital coupling coordination degree has significantly improved, and the capital structure has transitioned from imbalanced to coordinated; and (3) Households’ livelihood capital exhibits a high mobility, and the gap between rich and poor has been narrowed. This paper theoretically contributes to the research on ecological compensation by providing a more comprehensive perspective of policy effect analysis, and it can also provide a micro level empirical basis for policymakers to optimize the follow-up fishing ban policy.
Edge-Compatible Deep Learning Models for Detection of Pest Outbreaks in Viticulture
Authors: Gonçalves João , Silva Eduardo , Faria Pedro , Nogueira Telmo , Ferreira Ana , Carlos Cristina , Rosado Luís
Published: December 2022

The direct effect of global warming on viticulture is already apparent, with unexpected pests and diseases as one of the most concerning consequences. Deploying sticky traps on grape plantations to attract key insects has been the backbone of conventional pest management programs. However, they are time-consuming processes for winegrowers, conducted through visual inspection via the manual identification and counting of key insects. Additionally, winegrowers usually lack taxonomy expertise for accurate species identification. This paper explores the usage of deep learning on the edge to identify and quantify pest counts automatically. Different mobile devices were used to acquire a dataset of yellow sticky and delta traps, consisting of 168 images with 8966 key insects manually annotated by experienced taxonomy specialists. Five different deep learning models suitable to run locally on mobile devices were selected, trained, and benchmarked to detect five different insect species. Model-centric, data-centric, and deployment-centric strategies were explored to improve and fine-tune the considered models, where they were tested on low-end and high-end mobile devices. The SSD ResNet50 model proved to be the most suitable architecture for deployment on edge devices, with accuracies per class ranging from 82% to 99%, the F1 score ranging from 58% to 84%, and inference speeds per trap image of 19.4 s and 62.7 s for high-end and low-end smartphones, respectively. These results demonstrate the potential of the approach proposed to be integrated into a mobile-based solution for vineyard pest monitoring by providing automated detection and the counting of key vector insects to winegrowers and taxonomy specialists.
Predicted Soil Greenhouse Gas Emissions from Climate × Management Interactions in Temperate Grassland
Authors: Barneze Arlete S. , Abdalla Mohamed , Whitaker Jeanette , McNamara Niall P. , Ostle Nicholas J.
Published: December 2022

Grassland management practices and their interactions with climatic variables have significant impacts on soil greenhouse gas (GHG) emissions. Mathematical models can be used to simulate the impacts of management and potential changes in climate beyond the temporal extent of short-term field experiments. In this study, field measurements of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) emissions from grassland soils were used to test and validate the DNDC (DeNitrification-DeComposition) model. The model was then applied to predict changes in GHG emissions due to interactions between climate warming and grassland management in a 30-year simulation. Sensitivity analysis showed that the DNDC model was susceptible to changes in temperature, rainfall, soil carbon and N-fertiliser rate for predicting N2O and CO2 emissions, but not for net CH4 emissions. Validation of the model suggests that N2O emissions were well described by N-fertilised treatments (relative variation of 2%), while non-fertilised treatments showed higher variations between measured and simulated values (relative variation of 26%). CO2 emissions (plant and soil respiration) were well described by the model prior to hay meadow cutting but afterwards measured emissions were higher than those simulated. Emissions of CH4 were on average negative and largely negligible for both simulated and measured values. Long-term scenario projections suggest that net GHG emissions would increase over time under all treatments and interactions. Overall, this study confirms that GHG emissions from intensively managed, fertilised grasslands are at greater risk of being amplified through climate warming, and represent a greater risk of climate feedbacks.
Effects of Grazing Intensity on the Carbon, Nitrogen and Phosphorus Content, Stoichiometry and Storage of Plant Functional Groups in a Meadow Steppe
Authors: Wang Miao , Zhang Chu , Chen Sisi , Zhang Yu , Li Yingxin , Xin Xiaoping , Wang Xiaoli , Yan Ruirui
Published: December 2022

Studies on the impacts of grazing on carbon, nitrogen, and phosphorus stoichiometry and storage are crucial for better understanding the nutrient cycles of grasslands ecosystems. Using a controlled grazing experimental platform in a meadow steppe ecosystem, the effects of different stocking rates (0.00, 0.23, 0.34, 0.46, 0.69, and 0.92 AU ha−1) on the carbon, nitrogen, and phosphorus contents of plant functional groups were explored. The major results were: (1) The carbon content of Gramineae Barnhart was significantly reduced by grazing intensity (p < 0.05), and the organic carbon content of Cyperaceae Rotundus was significantly higher than that of the other groups; the total nitrogen content of Cyperaceae and other groups and total phosphorus contents of Gramineae, Leguminosae Sp., Cyperaceae, and other groups all increased significantly with increasing grazing intensity (p < 0.05). (2) The carbon, nitrogen, and phosphorus storage amounts of Gramineae, Leguminosae, and Ranunculaceae L. decreased significantly with increasing grazing intensity. Heavy grazing reduced the carbon, nitrogen, and phosphorus storage amounts of Cyperaceae and other groups, while the carbon, nitrogen, and phosphorus storage amounts of Compositae were the largest under moderate grazing. (3) The nitrogen content of each functional group was highly significantly negatively correlated with the C/N ratio, and the phosphorus content was highly significantly negatively correlated with the C/P ratio. Grazing and foraging affected the growth of the different functional groups, which in turn affected their carbon, nitrogen, and phosphorus content, stoichiometry, and storage. Moderate grazing improved the nutrient utilization efficiency of grassland and is beneficial for promoting sustainable grassland development.
The Expanded and Diversified Calmodulin-Binding Protein 60 (CBP60) Family in Rice (Oryza sativa L.) Is Conserved in Defense Responses against Pathogens
Authors: Kumari Diksha , Prasad Bishun Deo , Sahni Sangita , Nonhebel Heather M. , Krishna Priti
Published: December 2022

Plant disease management is key to sustainable production of staple food crops. Calcium (Ca2+) signal and phytohormones play critical roles in regulating plant defense responses against pathogens. The Ca2+ signals are sensed, decoded and transduced by calmodulin and other Ca2+ -binding proteins, followed by interaction with and modulation of activities of target proteins such as calmodulin-binding proteins (CBPs). Members of the Arabidopsis CBP60 gene family, AtCBP60g and AtSARD1, have emerged as major regulators of immune responses. In this study, we identified a 15 member CBP60 gene family in rice (Oryza sativa) of which OsCBP60g-3, OsCBP60g-4, OsCBP60a and OsSARD-like1 genes were consistently upregulated in rice seedlings in response to infection with both fungal (Magnaporthe oryzae) and bacterial (Xanthomonas oryzae) pathogens as well as by salicylic acid (SA). OsCBP60g-4 and OsCBP60g-3 were induced maximally by SA and brassinosteroid (BR), respectively, and OsCBP60g-4 was expressed at 3-fold higher levels in the M. oryzae resistant rice genotype (IC-346004) as compared to the susceptible rice genotype (Rajendra Kasturi). The considerable expansion of the immunity clade and the up-regulation of several OsCBP60 genes in response to pathogens and defense hormones supports the importance of further investigating OsCBP60 genes as targets for increasing disease resistance in rice.
Winter Wheat Seeding Decisions for Improved Grain Yield and Yield Components
Authors: Aula Lawrence , Easterly Amanda C. , Creech Cody F.
Published: December 2022

The continual re-evaluation of agronomic practices is necessary to improve crop performance and sustainability of the production of winter wheat (Triticum aestivum L.), particularly as genetics and climate conditions change. Recommendations made about winter wheat planting dates, spacing, variety, and seed rates under normal climatic conditions may not be suitable in current times with more climate variability. Our experiment investigated the effect of planting date (early, historic-optimum, and late), row spacing (19 and 25 cm), variety (Goodstreak, Robidoux, and Wesley), and seed rate (1.8, 2.1, 2.3, 2.4, 2.6, 2.8, 3.1, and 3.4 M seeds ha−1) on winter wheat grain yield and yield components. The seeding rate was nested within row spacing in nested-factorial design. A nested-factorial treatment design was used with testing at several locations in Nebraska across two years. Variety had a substantial effect on winter wheat grain yield (p < 0.05). Variety also had a substantial interaction effect with planting date and row spacing 50% of the time (p ≤ 0.01). At Hemingford, for example, Wesley planted at 19 cm had 5.9% more yield when compared to Robidoux planted at 19 cm (5.5 Mg ha−1). Similarly, biomass was influenced by variety across sites (p < 0.01), but a substantial interaction effect also occurred between planting date and variety at two of the three sites. Narrow row spacing (19 cm) led to significantly more tillers (6.9 M ha−1) when planted with Goodstreak at two of the sites. While planting date by itself did not affect any of the responses evaluated, this research highlights the importance of comprehensive and holistic approaches to wheat production in the High Plains.
Impacts of Climate Change on the Mean and Variance of Indica and Japonica Rice Yield in China
Authors: Zhang Lijuan , Wang Jinxia , Sun Tianhe , Wang Xialin
Published: December 2022

The overall goal of this study was to examine the impacts of climate change on the mean and variance of rice yields in China by using historical climate and crop data. An econometric model was established to estimate Just–Pope stochastic production functions and identify the potential impacts of climate change on the mean and variance of rice yields by type, keeping other factors constant. Based on the estimated production functions, the contribution rate of climatic factors to rice yield was then assessed by conducting the growth accounting of yields over the past 30 years. The results showed that both the mean rice yield and the yield variability were influenced by changes in the mean climate conditions and climatic variance. In the future, the impacts of climate change on rice yields will depend on local regions’ present climatic conditions. The results have implications for improving the adaptation capacity of rice production.
Analysis of Weed Communities in Solar Farms Located in Tropical Areas—The Case of Malaysia
Authors: Ya’acob Mohammad Effendy , Lu Li , Nobilly Frisco , Che’Ya Nik Norasma , Aziz Ammar Abdul , Dupraz Christian , Yahya Muhammad Syafiq , Atikah Sharifah Nur , Mamun Mohammad Abdullah Al.
Published: December 2022

Weed management in large-scale solar photovoltaic (LSS-PV) farms has become a great concern to the solar industry due to scarcity of labour and the ever-increasing price of pesticides, which opens up possibilities for integrated farming, also known as agrivoltaics. Improper weed control may have multiple negative impacts such as permanent shading of the module surface, pest housing which damages communication cables, and even bush fires. The shaded PV modules can be heated up to extreme temperatures, causing costly burn-out damage. Critical information on the types of weeds on solar farms, especially in Malaysia, has not been established to support the concept of weed management. Thus, with this study, detailed composition of the weed community was obtained via quadrat sampling between solar PV modules, near ground equipment, near perimeter fencing, and directly underneath the PV modules. Weed-control measures via high-quality weedmat installation under solar PV arrays have been implemented where this approach can be considered effective on solar farms based on the existing PV structure height and equipment constraints plus the increasing cost for labour and agricultural inputs. This work underlines the proposed Agrivoltaic for Large Scale Solar (Agrivoltaic4LSS) program to complement the solar industry in Malaysia towards an agrivoltaic, eco-friendly approach to weed management.
Genetic Diversity Analysis and Core Collection Construction of the Actinidia chinensis Complex (Kiwifruit) Based on SSR Markers
Authors: Hu Guangming , Jiang Quan , Wang Zhi , Li Zuozhou , Liao Wenyue , Shen Dandan , Zhong Caihong
Published: December 2022

Kiwifruit belonging to the Actinidiaceae family is a perennial, dioecious vine called ‘the king of fruits’ due to its considerably nutritious and sweet characteristics. A. chinensis complex, including two main groups, A. chinensis var. chinensis and A. chinensis var. deliciosa, is a major component of Actinidia due to their huge economic value and the high degree of development and utilization. Wild resources are widely distributed in China, but are under serious threat due to extreme environments and destroyed habitats. Thus, it is of great significance for the conservation of kiwifruit resources and the sustainable development of the kiwifruit industry to evaluate the genetic diversity of existing genetic resources and to systematically construct a core collection of the A. chinensis complex. In this study, 40 high polymorphism microsatellites markers were used to investigate all accessions from the A. chinensis complex. A total of 888 alleles were marked with 22.2 alleles in each locus. The expected heterozygosity was 0.846, the observed heterozygosity was 0.622, the polymorphism information content was 0.835, and the Shannon information index was 2.369. Among these loci, the observed heterozygosity of 38 loci was lower than expected. The inbreeding coefficient was 0.257, which indicates that frequent hybridization occurred between close relatives. Analyses of molecular variance showed that genetic variations mainly came from the population. Finally, a core collection containing 93 accessions was constructed. The bank not only perfectly represented the genetic diversity of the original population, but also had excellent potential for development and utilization. Our research provides a crucial reference for the future conservation, germplasm identification, and genetic breeding of kiwifruit.
Alleviation of Cr(VI) Toxicity and Improve Phytostabilization Potential of Vigna radiata Using a Novel Cr(VI) Reducing Multi-Stress-Tolerant Plant Growth Promoting Rhizobacterial Strain Bacillus flexus M2
Authors: Srinivas Ravi Manoj , Karthik Chinnannan , Padikasan Indra Arulselvi , Ma Ying
Published: December 2022

Chromium (Cr) is a toxic heavy metal discharged into the environment through various anthropogenic sources, which affects soil properties and fertility. Hence, an effective soil restoration strategy is the need of the hour. In this study, a potent Cr(VI)-reducing strain M2 was isolated from the rhizosphere of Zea mays L. grown in leather industrial effluent contaminated sites and identified as Bacillus flexus through 16S rDNA sequencing. Strain M2 exhibited strong tolerance to multi-stresses such as temperature (up to 45 °C), pH (up to 9.0), Sodium chloride (NaCl) (up to 7%) and PEG 6000 (up to 50%) and showed strong Cr(VI) reduction with the presence of multi-stresses. The interaction of Cr(VI) with strain M2 was elucidated through various instrumentation analyses. Fourier Transform Infra-red (FTIR) Spectroscopy analysis confirmed that Cr(VI) exposures induce significant changes in the cell-surface functional groups. Raman spectrum and Transmission Electron Microscopy–Energy Dispersive X-ray spectroscopy (TEM-EDX) analysis confirmed the bio-reduction of Cr(VI) to Cr(III) and their intracellular localization as Cr(III). Further, strain M2 produced a significant quantity of Indole acetic acid (IAA), ammonia, and exopolysaccharide (EPS) and showed positive results for various plant-growth-promoting activities with the presence of Cr(VI). In greenhouse experiments, the strain M2 inoculation progressively increased the plant growth parameters and stabilized the antioxidant system of Vigna radiata under Cr stress. However, Cr(VI) exposure decreased the growth parameters and increased the level of proline content, Hydrogen peroxide (H2O2) accumulation, and antioxidant enzymes expression in V. radiata. Interestingly, strain M2 inoculation significantly reduced the accumulation of Cr in root and shoot of V. radiata when compared to the uninoculated Cr(VI) treatment. Hence, this study confirms that rhizobacterial inoculation markedly reduced the negative impact of Cr toxicity and improved V. radiata growth even in harsh environments by stabilizing the mobility of Cr in the rhizosphere.
Effects of Bismuth Exposure on the Human Kidney—A Systematic Review
Authors: Pelepenko Lauter E. , Janini Ana Cristina P. , Gomes Brenda P. F. A. , de-Jesus-Soares Adriana , Marciano Marina A.
Published: December 2022

The effects of bismuth toxicity on the kidney—the main organ responsible for blood filtration—were systematically reviewed. This review was motivated by availability of several sources of bismuth in contact with humans including environmental, medications, dental materials, and cosmetics, potentially leading to kidney filtration of this chemical. No previous studies have systematically reviewed the literature considering this association. A total of 22 studies with a total of 46 individuals met the inclusion criteria, 19 being case reports with only one patient enrolled. The included studies publication dates ranged from 1961 to 2021 and the countries of publication were the United States of America, United Kingdom, Germany, Turkey, Switzerland, and Canada. Bismuth sources affecting the kidneys were uniquely reported as from medical purposes and mostly associated to overdoses with several symptoms, apparently with dose-dependent consequences. Patient history of renal impairment seemed to affect the outcome of the case. Several therapies were conducted following bismuth intoxication, and few studies performed renal biopsies describing its histological findings. It is crucial to reconsider the nephrotoxicity of bismuth compounds, mainly in patients with previous history of renal impairment.
Development and Psychometric Evaluation of the Antibiotic Knowledge and Consumption Tool (AKCT)
Authors: Hasan Sanah , Sulieman Hana , Babi Husam , Bloukh Samir
Published: December 2022

Knowledge of antibiotics and awareness of microbial resistance are essential for appropriate antibiotic consumption. This study aimed to develop and validate a measure of antibiotic knowledge and consumption (AKCT) and to make it available in the Arabic language and context. The tool was developed and applied on individuals ≥ 18 years, with mastery of Arabic or English. Exploratory factor analysis using principal-component analysis tested the psychometric properties of the items. AKCT scores were compared with the Infectious Numeracy Test (INT) scores to establish convergent validity. Cronbach’s α > 0.7 measured reliability. Three hundred-eighty-six participants completed the questionnaire, achieving a 95.3% response rate. Five components were retained after factor analysis: Side-effects and resistance, Access to antibiotics, Recovery after use, Antibiotics use indications, and Body response. Cronbach’s α = 0.85. The mean ± SD of AKCT = 9.82 ± 3.85 (range = 7–20); lowest scores were related to “Side-effects and resistance” (2.32 ± 2.00, max = 7) and “Antibiotic use indications” (1.61 ± 1.29, max = 5). Scores on the AKCT and INT positively correlated. The AKCT is a valuable, valid, and reliable tool developed for measurement of antibiotic knowledge and consumption behaviors to identify specific areas needing improvements; hence, targeted interventions are devised.
Evaluation of Different Strategies to Improve the Management of Helicobacter pylori Infection at the Primary Care Level: Training Sessions Increase Prescription Appropriateness of Treatment Regimens
Authors: Alfaro Enrique , Martínez-Domínguez Samuel J. , Laredo Viviana , Lanas Ángel , Sostres Carlos
Published: December 2022

Helicobacter pylori infection (H. pylori) is mainly managed at the primary care level. Our group previously performed a study demonstrating that providing specific counselling (SC) to primary care practitioners (PCPs) who requested a urea breath test (UBT) improved treatment management but not indications for H. pylori tests. SC was given in the form of a personal letter addressed to PCPs with UBT results which contained information about accepted UBT indications and a Helicobacter pylori treatment algorithm. The purpose of the present study was to evaluate the effect of training sessions (TS) on UBT indications, antibiotic prescriptions and eradication rates. This was a quasi-experimental study performed at primary care centres (PCCs). Phase I included 399 patients diagnosed with H. pylori infection after providing SC to PCPs. Phase II included 400 H. pylori-positive patients after giving TS to PCPs who had already received SC (100 from PCCs with TS and 300 from PCCs without TS). An improved trend in the appropriate indication of H. pylori diagnosis was observed between Phase I and PCCs with TS in Phase II (57.5% vs. 67%; p = 0.06). TS improved appropriate prescriptions in PCCs with TS compared to PCCs that only received SC in Phase I and II (94% vs. 75.3%, p = 0.01; 94% vs. 85.6%, p = 0.04, respectively). Eradication rates showed no differences between groups. In conclusion, training sessions after specific counselling improved antibiotic prescription appropriateness but not eradication rates.
Analysis of Tonsil Tissues from Patients Diagnosed with Chronic Tonsillitis—Microbiological Profile, Biofilm-Forming Capacity and Histology
Authors: Kostić Marina , Ivanov Marija , Babić Snežana Sanković , Tepavčević Zvezdana , Radanović Oliver , Soković Marina , Ćirić Ana
Published: December 2022

Chronic tonsillitis (CT) is a global health issue which can impair patient’s quality of life and has an important socioeconomic impact due to the nonrational use of antibiotics, increased antimicrobial resistance and frequent need for surgical treatment. In order to isolate and identify the causing agents of CT, a total of 79 postoperative palatine and adenoid tissue samples were obtained from the ENT Clinic, KBC Zvezdara, Belgrade, Serbia. Culture identification was performed by MALDI-TOF MS and the Staphylococcus aureus isolates were tested for biofilm forming capability and antibiotic susceptibility. Additionally, a histological examination of palatine and adenoid tissue was performed in order to detect the presence of CT-causing bacteria. The slight majority of participants were females with median age of 28 years for adult patients (group I) and 6 years for children (group II). Analysis of the incidence of bacteria isolated from tissue samples in both groups showed the highest prevalence of S. aureus, Streptococcus oralis and Streptococcus parasanquinis. In addition to interfollicular hyperplasia, colonies of species S. aureus were detected in histological material. The presence of biofilm might be the reason for the recurrence of infection. Therefore, searching for a new treatment of CT is of great importance.
Antibiotic Resistance of Enterococcus spp. Isolated from the Urine of Patients Hospitalized in the University Hospital in North-Central Poland, 2016–2021
Authors: Kraszewska Zuzanna , Skowron Krzysztof , Kwiecińska-Piróg Joanna , Grudlewska-Buda Katarzyna , Przekwas Jana , Wiktorczyk-Kapischke Natalia , Wałecka-Zacharska Ewa , Gospodarek-Komkowska Eugenia
Published: December 2022

Urinary Tract Infections (UTIs) are common outpatient and inpatient infections, often treated with empirical therapy. Enterococcus spp. is responsible for about 10% of UTIs. This study aimed to determine the necessity of changing the empirical treatment of UTIs caused by Enterococcus spp. The evaluation was performed for 542 Enterococcus strains isolated from urine samples in the years 2016–2021. We identified three Enterococcus species that were found: E. faecalis (389, 71.8%), E. faecium (151, 27.8%) and E. gallinarum (2, 0.4%). E. faecalis was the dominant species every year. Among E. faecalis, the most prevalent was resistance to norfloxacin (51.4%). Almost all E. faecium strains (150, 99.3%) were resistant to beta-lactams and norfloxacin. Eighty-three strains (55.0%) were resistant to vancomycin and 72 (47.7%) to teicoplanin. E. faecium strains showed a significantly higher percentage of resistance mechanisms GRE (Glicopeptide-Resistant Enterococcus) (72, 48.7%) and VRE (Vancomycin-Resistant Enterococcus) (11, 7.3%), while only five strains of E. feacalis showed a VRE mechanism (1.3%). In the therapy of E. faecalis UTIs, ampicillin and imipenem still remain effective. However, the above-mentioned antibiotics, as well as fluoroquinolones, are not recommended in the treatment of UTIs of E. faecium etiology.
Awareness of Antibiotics and Antibiotic Resistance in a Rural District of Ha Nam Province, Vietnam: A Cross-Sectional Survey
Authors: Ulaya Godwin , Nguyen Tu Cam Thi , Vu Bich Ngoc Thi , Dang Duc Anh , Nguyen Hien Anh Thi , Tran Hoang Huy , Tran Huong Kieu Thi , Reeve Matthew , Pham Quynh Dieu , Trinh Tung Son , van Doorn H. Rogier , Lewycka Sonia
Published: December 2022

Low awareness of antibiotics and antibiotic resistance may lead to inappropriate antibiotic use and contribute to the problem of antibiotic resistance. This study explored levels and determinants of antibiotic awareness in a rural community in northern Vietnam, through a cross-sectional survey of 324 households in one commune of Ha Nam Province. Awareness and knowledge of antibiotics and antibiotic resistance and determinants were evaluated using structured questionnaires. Most respondents (232/323 (71.8%)) had heard of antibiotics, but fewer could name any antibiotic (68/323 (21.1%)) or had heard of antibiotic resistance (57/322 (17.7%)). In adjusted regression models, antibiotic awareness was lower among those who lived further from health facilities (Odds Ratio (OR): 0.08; 95% Confidence Interval (CI): 0.04–0.19) but higher among those who used interpersonal sources for health information (OR: 4.06; 95% CI: 1.32–12.46). Antibiotic resistance awareness was lower among those who used private providers or pharmacies as their usual health facility (OR: 0.14; 95% CI: 0.05–0.44) but higher among those with medical insurance (OR: 3.70; 95% CI: 1.06–12.96) and those with high media use frequency (OR: 9.54; 95% CI: 2.39–38.07). Awareness of Antimicrobial Resistance (AMR) was also higher among those who sought health information from official sources (OR: 3.88; 95% CI: 1.01–14.86) or had overall high levels of health information seeking (OR: 12.85; 95% CI: 1.63–101.1). In conclusion, communication interventions need to target frequently used media platforms, such as television, as well as key health information providers, such as health workers, as channels for increasing knowledge and changing community antibiotic use behaviour.
Repurposing Disulfiram as an Antimicrobial Agent in Topical Infections
Authors: Lajarin-Reinares Maria , Pena-Rodríguez Eloy , Cañellas-Santos Mariona , Rosell-Vives Elisabet , Cortés Pilar , Casas Montserrat Llagostera , Calvo Maria Àngels , Fernandez-Campos Francisco
Published: December 2022

Antimicrobial drugs applied topically offer several advantages. However, the widespread use of antibiotics has led to increasing antimicrobial resistance. One interesting approach in the drug discovery process is drug repurposing. Disulfiram, which was originally approved as an anti-alcoholism drug, offers an attractive alternative to treat topical multidrug resistance bacteria in skin human infections. This study aimed to evaluate the biopharmaceutical characteristics of the drug and the effects arising from its topical application in detail. Microdilution susceptibility testing showed antibacterial activity against Gram-positive bacteria Staphylococcus aureus and Streptococcus pyogenes. Dermal absorption revealed no permeation in pig skin. The quantification of the drug retained in pig skin demonstrated concentrations in the stratum corneum and epidermis, enough to treat skin infections. Moreover, in vitro cytotoxicity and micro-array analyses were performed to better understand the mechanism of action and revealed the importance of the drug as a metal ion chelator. Together, our findings suggest that disulfiram has the potential to be repurposed as an effective antibiotic to treat superficial human skin infections.
Variability of Mycobacterium avium Complex Isolates Drug Susceptibility Testing by Broth Microdilution
Authors: Zimenkov Danila
Published: December 2022

Non-tuberculous mycobacteria are widely distributed in environments and are capable of infecting humans, particularly those with a compromised immune system. The most prevalent species that cause nontuberculous mycobacterial lung diseases are slow-growing bacteria from the Mycobacterium avium complex (MAC), mainly M. avium or M. intracellulare. The key treatment of MAC infections includes macrolides, ethambutol, and rifampicin; however, the therapy outcomes are unsatisfactory. Phenotypic drug susceptibility testing is a conditional recommendation prior to treatment, and critical concentrations for clarithromycin, amikacin, moxifloxacin, and linezolid have been established. In this review, data from studies on the determination of MIC of clinical isolates using the broth microdilution method were summarized. A significant variation in the MIC distributions from different studies was found. The main reasons could impact the findings: insufficient reproducibility of the phenotypic testing and variation in species lineages identified in different laboratories, which could have various intrinsic susceptibility to drugs. For most of the drugs analyzed, the MICs are too high, which could undermine the treatment efficiency. Further improvement of treatment outcomes demands the validation of microbiological resistance criteria together with the identification of molecular mechanisms of resistance.
A Real-Time Automated System for Monitoring Individual Feed Intake and Body Weight of Group-Housed Young Chickens
Authors: Peng Yuping , Zeng Zhixiong , Lv Enli , He Xinyuan , Zeng Boyang , Wu Fan , Guo Jiaming , Li Ziwei
Published: December 2022

The feeding behavior of poultry at a young age is very likely to determine the final growth of the chicken, and can also reflect the feeding status and the health status. It is also of great significance for breeding. This paper describes the development and testing of a real-time automated system and a single passage for monitoring the individual feed intake and body weight of poultry. This system integrates an automatic feeding mechanism, an RFID reading module, a weight scale, a feed scale, and a drop weighting scale. The system uses analog circuits and digital filtering to improve the weighing accuracy, and directly measures the amount of feed falling to the ground using a high-precision weighing scale. Through the sequential opening and closing of a sliding door, group-housed chickens are separated so that the young ones are fed individually. As a result of the experiment, we learned that a young chicken grows at a rate of about 8.88 g/day, and the food conversion rate (FCR) is about 4.4, which proves that this system matches the single passage and can accurately monitor the body weight change and feeding behavior of young chickens.
Performance Metric Development to Measure Overall Vehicle Effectiveness in Mining Transportation
Authors: Hia Selamat Walmanto , Singgih Moses Laksono , Gurning Raja Oloan Saut
Published: December 2022

Several performance metrics to measure the effectiveness of manufacturing equipment have been studied, and one of the most used is overall equipment effectiveness (OEE). However, its application and development in the road transportation sector remains little studied. The purpose of this paper is to establish a new metric derived from OEE to measure the overall effectiveness of coal mining transportation and apply this metric to actual operation. This study employed in-depth interviews and Delphi techniques to explore the specific metrics. Three rounds of Delphi involving mining experts, academia, and consultants identified six potential metrics to measure coal mining transportation operations that contributed to a new metric to measure mining transportation overall vehicle effectiveness. This paper also discusses a case study of how this newly developed metric was tested and applied to the actual operation of the truck fleet at a coal-hauling company in Indonesia. According to the case study, this metric accommodated the important factors in coal mining transportation operations and reflected operational performance. This study contributes to measuring the effectiveness of coal-hauling transportation by providing an effective metric that will help the managerial team make better decisions for process improvement.
A Fast Training Method of a Fabric Hand-Feel Panel under Industry Conditions, and Its Conformity with Other Human and Instrumental Approaches
Authors: Dabolina Inga , Abu-Rous Mohammad , Lapkovska Eva
Published: December 2022

Under industrial daily business conditions, a heterogeneous group of employees with different backgrounds and activity fields was trained to function as a hand-feel panel to evaluate internal developments and optimizations, and to predict customer preferences in the main textile segments. Using sets of fabrics of typical constructions, different descriptors related to hand actions were elaborated and an evaluation method based on scaling, as well as ranking, was defined, based on AATCC 5-2006. Group performance was investigated by statistical concordance factors, by correlation with physical hand-feel assessment methods, and with a reference panel. Using a different fabric set, the panel’s ability to predict the average preferences of a larger consumer group was tested. Furthermore, the correlations of the system parameters of the different physical methods for the used fabrics were studied and discussed, showing the agreement and the disagreement aspects of the methods for the investigated fabrics.
Combining Biomechanical Features and Machine Learning Approaches to Identify Fencers’ Levels for Training Support
Authors: Aresta Simona , Bortone Ilaria , Bottiglione Francesco , Di Noia Tommaso , Di Sciascio Eugenio , Lofù Domenico , Musci Mariapia , Narducci Fedelucio , Pazienza Andrea , Sardone Rodolfo , Sorino Paolo
Published: December 2022

Nowadays, modern technology is widespread in sports; therefore, finding an excellent approach to extracting knowledge from data is necessary. Machine Learning (ML) algorithms can be beneficial in biomechanical data management because they can handle a large amount of data. A fencing lunge represents an exciting scenario since it necessitates neuromuscular coordination, strength, and proper execution to succeed in a competition. However, to investigate and analyze a sports movement, it is necessary to understand its nature and goal and to identify the factors that affect its performance. The present work aims to define the best model to screen élite and novice fencers to develop further a tool to support athletes’ and trainers’ activity. We conducted a cross-sectional study in a fencing club to collect anthropometric and biomechanical data from élite and novice fencers. Wearable sensors were used to collect biomechanical data, including a wireless inertial system and four surface electromyographic (sEMG) probes. Four different ML algorithms were trained for each dataset, and the most accurate was further trained with hyperparameter tuning. The best Machine Learning algorithm was Multilayer Perceptron (MLP), which had 96.0% accuracy and 90% precision, recall, and F1-score when predicting class novice (0); and 93% precision, recall, and F1-score when predicting class élite (1). Interestingly, the MLP model has a slightly higher capacity to recognize élite fencers than novices; this is important to determine which training planning and execution are the best to achieve good performances.
Advanced Analysis of Electroretinograms Based on Wavelet Scalogram Processing
Authors: Zhdanov Aleksei , Dolganov Anton , Zanca Dario , Borisov Vasilii , Ronkin Mikhail
Published: December 2022

The electroretinography (ERG) is a diagnostic test that measures the electrical activity of the retina in response to a light stimulus. The current ERG signal analysis uses four components, namely amplitude, and the latency of a-wave and b-wave. Nowadays, the international electrophysiology community established the standard for electroretinography in 2008. However, in terms of signal analysis, there were no major changes. ERG analysis is still based on a four-component evaluation. The article describes the ERG database, including the classification of signals via the advanced analysis of electroretinograms based on wavelet scalogram processing. To implement an extended analysis of the ERG, the parameters extracted from the wavelet scalogram of the signal were obtained using digital image processing and machine learning methods. Specifically, the study focused on the preprocessing of wavelet scalogram as images, and the extraction of connected components and thier evaluation. As a machine learning method, a decision tree was selected as one that incorporated feature selection. The study results show that the proposed algorithm more accurately implements the classification of adult electroretinogram signals by 19%, and pediatric signals by 20%, in comparison with the classical features of ERG. The promising use of ERG is presented using differential diagnostics, which may also be used in preclinical toxicology and experimental modeling. The problem of developing methods for electrophysiological signals analysis in ophthalmology is associated with the complex morphological structures of electrophysiological signal components.
Containerised Application Profiling and Classification Using Benchmarks
Authors: Psychas Alexandros , Dadamis Phivos , Kapsoulis Nikolaos , Litke Antonios , Varvarigou Theodora
Published: December 2022

Along with the rise of cloud and edge computing has come a plethora of solutions that regard the deployment and operation of different types of applications in such environments. Infrastructure as a service (IaaS) providers offer a number of different hardware solutions to facilitate the needs of the growing number of distributed applications. It is critical in this landscape to be able to navigate and discover the best-suited infrastructure solution for the applications, taking into account not only the cost of operation but also the quality of service (QoS) required for any given application. The proposed solution has two main research developments: (a) the creation and optimisation of multidimensional vectors that represent the hardware usage profiles of an application, and (b) the assimilation of a machine learning classification algorithm, in order to create a system that can create hardware-agnostic profiles of a vast variety of containerised applications in terms of nature and computational needs and classify them to known benchmarks. Given that benchmarks are widely used to evaluate a system’s hardware capabilities, having a system that can help select which benchmarks best correlate to a given application can help an IaaS provider make a more informed decision or recommendation on the hardware solution, not in a broad sense, but based on the needs of a specific application.