bluuebunny/crossref_metadata_2025 huggingface dataset:
Epidemiology of companion animal AMR in the United States of America: filling a gap in the one health approach
Authors: Sobkowich Kurtis E. , Weese J. Scott , Poljak Zvonimir , Plum Andy , Szlosek Donald , Bernardo Theresa M.
Published: June 2023

Introduction

Antimicrobial resistance (AMR) is a global health concern that affects all aspects of the One Health Triad, including human, animal, and environmental health. Companion animals, such as cats and dogs, may contribute to the spread of AMR through their close contact with humans and the frequent prescription of antimicrobials. However, research on AMR in companion animals is limited, and there are few surveillance measures in place to monitor the spread of resistant pathogens in the United States.

Methods

This study aims to explore the practicality of using data from commercial laboratory antimicrobial susceptibility testing (AST) services for epidemiological analyses of AMR in companion animals in the United States.

Results

The study analyzed 25,147,300 individual AST results from cats and dogs submitted to a large commercial diagnostic laboratory in the United States between 2019 and 2021, and found that resistance to certain antimicrobials was common in both E. coli and S. pseudintermedius strains.

Conclusion

There has been a paucity of information regarding AMR in companion animals in comparison to human, environmental and other animal species. Commercial AST datasets may prove beneficial in providing more representation to companion animals within the One Health framework for AMR.
Synchronous and metachronous multiple primary cancers in melanoma survivors: a gender perspective
Authors: Guzzinati Stefano , Buja Alessandra , Grotto Giulia , Zorzi Manuel , Manfredi Mariagiovanna , Bovo Eleonora , Del Fiore Paolo , Tropea Saveria , Dall’Olmo Luigi , Rossi Carlo R. , Mocellin Simone , Rugge Massimo
Published: June 2023

Background

Long-term survivors of cutaneous malignant melanoma (CMM) risk subsequent malignancies due to both host-related and environmental risk factors. This retrospective population-based study differentially assesses the risk of synchronous and metachronous cancers in a cohort of CMM survivors stratified by sex.

Methods

The cohort study (1999–2018) included 9,726 CMM survivors (M = 4,873, F = 4,853) recorded by the cancer registry of all 5,000,000 residents in the Italian Veneto Region. By excluding subsequent CMM and non-CMM skin cancers, the incidence of synchronous and metachronous malignancies was calculated according to sex and tumor site, standardizing for age and calendar year. The Standardized Incidence Ratio (SIR) was calculated as the ratio between the number of subsequent cancers among CMM survivors and the expected number of malignancies among the regional population.

Results

Irrespective of the site, the SIR for synchronous cancers increased in both sexes (SIR = 1.90 in males and 1.73 in females). Both sexes also demonstrated an excess risk for synchronous kidney/urinary tract malignancies (SIR = 6.99 in males and 12.11 in females), and women had an increased risk of synchronous breast cancer (SIR = 1.69). CMM male survivors featured a higher risk of metachronous thyroid (SIR = 3.51, 95% CI [1.87, 6.01]), and prostate (SIR = 1.35, 95% CI [1.12, 1.61]) malignancies. Among females, metachronous cancers featured higher SIR values than expected: kidney/urinary tract (SIR = 2.27, 95% CI [1.29, 3.68]), non-Hodgkin’s lymphoma (SIR = 2.06, 95% CI [1.24, 3.21]), and breast (SIR = 1.46, 95% CI [1.22, 1.74]). Females had an overall increased risk of metachronous cancers in the first 5 years after CMM diagnosis (SIR = 1.54 at 6–11 months and 1.37 at 1–5 years).

Conclusion

Among CMM survivors, the risk of metachronous non-skin cancers is higher than in the general population and differs significantly by sex. These results encourage sex-tailored interventions for metachronous secondary cancer prevention.
Sketching the vision of the Web of Debates
Authors: Bikakis Antonis , Flouris Giorgos , Patkos Theodore , Plexousakis Dimitris
Published: June 2023

The exchange of comments, opinions, and arguments in blogs, forums, social media, wikis, and review websites has transformed the Web into a modern agora, a virtual place where all types of debates take place. This wealth of information remains mostly unexploited: due to its textual form, such information is difficult to automatically process and analyse in order to validate, evaluate, compare, combine with other types of information and make it actionable. Recent research in Machine Learning, Natural Language Processing, and Computational Argumentation has provided some solutions, which still cannot fully capture important aspects of online debates, such as various forms of unsound reasoning, arguments that do not follow a standard structure, information that is not explicitly expressed, and non-logical argumentation methods. Tackling these challenges would give immense added-value, as it would allow searching for, navigating through and analyzing online opinions and arguments, obtaining a better picture of the various debates for a well-intentioned user. Ultimately, it may lead to increased participation of Web users in democratic, dialogical interchange of arguments, more informed decisions by professionals and decision-makers, as well as to an easier identification of biased, misleading, or deceptive arguments. This paper presents the vision of the Web of Debates, a more human-centered version of the Web, which aims to unlock the potential of the abundance of argumentative information that currently exists online, offering its users a new generation of argument-based web services and tools that are tailored to their real needs.
Intentional practice: a common language, approach and set of methods to design, adapt and implement contextualised wellbeing solutions
Authors: Raymond Ivan J.
Published: June 2023

Reducing the “science-to-practice” gap has gained significant attention across multi-disciplinary settings, including school psychology and student wellbeing, trauma-informed practice, community and human services, and clinically focused health care. There has been increasing calls for complexity and contextualisation to be integrated within the implementation science literature. This includes the design and implementation of interventions spanning “systems” (whole-of-community capacity building initiatives), “programs” (e.g., evidence-based programs, clinical interventions) and “moment-to-moment” support or care. The latter includes responses and communication designed to deliver specific learning, growth or wellbeing outcomes, as personalised to an individual's presenting needs and context (e.g., trauma-informed practice). Collectively, this paper refers to these interventions as “wellbeing solutions”. While the implementation science literature offers a range of theories, models and approaches to reduce the science-to-practice gap in wellbeing solution design and implementation, they do not operationalise interventions into the “moment”, in a manner that honours both complexity and contextualisation. Furthermore, the literature's language and content is largely targeted towards scientific or professional audiences. This paper makes the argument that both best-practice science, and the frameworks that underpin their implementation, need to be “sticky”, practical and visible for both scientific and non-scientific knowledge users. In response to these points, this paper introduces “intentional practice” as a common language, approach and set of methods, founded upon non-scientific language, to guide the design, adaptation and implementation of both simple and complex wellbeing solutions. It offers a bridge between scientists and knowledge users in the translation, refinement and contextualisation of interventions designed to deliver clinical, wellbeing, growth, therapeutic and behavioural outcomes. A definitional, contextual and applied overview of intentional practice is provided, including its purported application across educational, wellbeing, cross-cultural, clinical, therapeutic, programmatic and community capacity building contexts.
The resilience of short food supply chains during the COVID-19 pandemic: a case study of a direct purchasing network
Authors: Ušča Maija , Tisenkopfs Talis
Published: June 2023

Introduction

The COVID-19 pandemic has presented challenges to global food supply chains. Since the beginning of the pandemic researchers have studied various food supply chain issues influenced by the COVID-19 crisis, including impacts on consumer behavior, and logistical and organizational changes to food supply chains. Despite the proliferation of studies on food supply chains during the pandemic, only a few researchers have focused on short food supply chains and their resilience. Therefore, the aim of this study was to explore the resilience of short food supply chains during the COVID-19 pandemic using a direct purchasing (DP) network as a case study. The study considered three research questions. (1) How has the functioning of the DP network changed during the COVID-19 pandemic? (2) What role do resilience elements (i.e., readiness to shocks, responsiveness to disruption, and recovery from the crisis) play in the short food supply chain response to the COVID-19 crisis? (3) Which innovations in the short food supply chain would further the recovery process, and thus resilience, after the crisis?

Methods

This article presents a case study of a direct organic food purchasing network in Latvia. The analysis of economic data regarding the dynamics of organic product demand and supply in the DP network was supplemented with an analysis of qualitative data gathered through semi-structured in-depth interviews with representatives of three groups of DP network participants: consumers, producers, and DP network organizers.

Results and discussion

From the consumer and producer experiences, the DP network was a flexible short food chain that could adapt quickly in a crisis. While the number of DP distribution points and total number of purchases decreased during the pandemic, a statistically significant increase in the number of product units sold compared to the pre-COVID-19 period was observed. From the perspective of food chain resilience elements, the reactive strategies of the DP network as a short food supply chain were highlighted. During the COVID-19 pandemic, the organizational and product innovations introduced in the DP network played a key role in enhancing the resilience of the short supply chain in the context of the wider food system.
The future of charitable alternative food networks in the UK: an investigation into current challenges and opportunities for foodbanks and community markets
Authors: Nayak Rounaq , Hartwell Heather
Published: June 2023

This study examines the potential of charitable alternative food networks (ANFs), specifically community markets, as a complimentary solution to existing food aid efforts in response to food insecurity. While foodbanks play a crucial role in providing emergency food aid, they often face challenges in terms of supply shortages, limited food variety, and perpetuating dependency on food aid. Moreover, foodbanks may only offer temporary relief without addressing the root cause of food insecurity. Community markets, on the other hand, adopt a social economy approach and aim to empower local communities by providing affordable food options to all community members. These markets operate on a different business model than foodbanks and offer additional vouchers for those who cannot afford to purchase food. Community markets also focus on promoting social and economic goals and often provide additional services and activities within the community centers. By assessing the perspectives of beneficiaries of foodbanks and community markets, the paper examines the dimensions of food security (availability, access, utilization, and stability) in the context of both charitable AFNs and highlights the potential of community markets and foodbanks to address these dimensions. While there is ongoing debate about categorizing food aid programmes as AFNs, both share the goal of reducing food insecurity and promoting sustainable and equitable food systems. Ultimately the paper argues that community markets offer a more sustainable and empowering approach to addressing food insecurity by addressing its underlying causes and promoting community resilience.
A practical guide for the generation of model-based virtual clinical trials
Authors: Craig Morgan , Gevertz Jana L. , Kareva Irina , Wilkie Kathleen P.
Published: June 2023

Mathematical modeling has made significant contributions to drug design, development, and optimization. Virtual clinical trials that integrate mathematical models to explore patient heterogeneity and its impact on a variety of therapeutic questions have recently risen in popularity. Here, we outline best practices for creating virtual patients from mathematical models to ultimately implement and execute a virtual clinical trial. In this practical guide, we discuss and provide examples of model design, parameter estimation, parameter sensitivity, model identifiability, and virtual patient cohort creation. Our goal is to help researchers adopt these approaches to further the use of virtual population-based analysis and virtual clinical trials.
Numerical Investigation of Effect of Structural Parameters on the Performance of a Combustion-Driven Sparkjet Actuator
Authors: Chen Hai , Zhou Yan , Luo Zhenbing , Cheng Pan
Published: June 2023

With the aim of increasing the momentum jet and obtaining better environmental adaptability, this study designs a new type of actuator combining a sparkjet actuator and a combustion-driven actuator. Numerical simulation shows that the combustion-driven sparkjet actuator has a higher velocity and mass rate compared to the sparkjet actuator when the length and orifice diameter are 6.5 mm and 1.3 mm, respectively, while the saturation work frequency is almost the same. A parameter study shows that as the volume increases, the pressure, orifice velocity, and mass rate of the combustion-driven sparkjet actuator increase. By contrast, the saturation work frequency decreases. Moreover, as the orifice diameter decreases, the orifice peak velocity, temperature, and pressure increase, whereas the mass flow rate and saturation work frequency decrease.
Hybrid Visual Servo Control of a Robotic Manipulator for Cherry Tomato Harvesting
Authors: Li Yi-Rong , Lien Wei-Yuan , Huang Zhi-Hong , Chen Chun-Ta
Published: June 2023

This paper aims to develop a visual servo control of a robotic manipulator for cherry tomato harvesting. In the robotic manipulator, an RGB-depth camera was mounted to the end effector to acquire the poses of the target cherry tomatoes in space. The eye-in-hand-based visual servo controller guides the end effector to implement eye–hand coordination to harvest the target cherry tomatoes, in which a hybrid visual servo control method (HVSC) with the fuzzy dynamic control parameters was proposed by combining position-based visual servo (PBVS) control and image-based visual servo (IBVS) control for the tradeoff of both performances. In addition, a novel cutting and clipping integrated mechanism was designed to pick the target cherry tomatoes. The proposed tomato-harvesting robotic manipulator with HVSC was validated and evaluated in a laboratory testbed based on harvesting implementation. The results show that the developed robotic manipulator using HVSC has an average harvesting time of 9.40 s/per and an average harvesting success rate of 96.25% in picking cherry tomatoes.
Impact of Allelic Variation in Maturity Genes E1–E4 on Soybean Adaptation to Central and West Siberian Regions of Russia
Authors: Perfil’ev Roman , Shcherban Andrey , Potapov Dmitriy , Maksimenko Konstantin , Kiryukhin Sergey , Gurinovich Sergey , Panarina Veronika , Polyudina Revmira , Salina Elena
Published: June 2023

Four maturity genes, namely, E1, E2, E3 and E4, have been found to play major roles in controlling the flowering and maturity time of soybean. Which genotypes of E1–E4 genes provide effective adaptation to the varied conditions of Russia are unknown. To clarify this issue, we have studied the allele variation in soybean E1–E4 genes in terms of both flowering and maturity time under the natural day-length conditions of Central Russia and Western Siberia in a collection of 176 soybean accessions, including 142 Russian and 34 foreign accessions. As a result, a high frequency of previously determined E1–E4 alleles has been identified. The field experiment showed that genotypes with all recessive alleles from e1-nl/e2/e3/e4 and e1-as/e2/e3/e4 provide the effective adaptation of soybean to the mentioned conditions. Cultivars with these genotypes are considered to be most suitable for cultivation in Central Russia and Western Siberia.
Effects of Future Climate Change on Spring Maize Yield and Water Use Efficiency under Film Mulching with Different Materials in the LOESS Plateau Region of China
Authors: Wang Bingfan , Li Zhaoyang , Liu Zihan , Pang Jinwen , Zhang Peng , Jia Zhikuan
Published: June 2023

Background: Traditional polyethylene film mulching is widely used in the Loess Plateau region of China to improve crop yields. However, whether long-term polyethylene film mulching can continue to ensure crop yield under future climate change conditions is questionable. First, we conducted a four-year field experiment to calibrate and validate the biogeochemical DeNitrification–DeComposition (DNDC) model. Then, based on the calibrated and validated model, we evaluated the spring maize yield and water use efficiency under different film mulching methods (no mulching, traditional polyethylene film mulching, and biodegradable film mulching) in the Loess Plateau region. Results: The temperature and rainfall in the Loess Plateau region are predicted to increase in the future (2021–2100) under four scenarios due to higher CO2 concentrations. Through 252 simulation results, we found that future climate change will have positive impacts under no mulching, traditional polyethylene film mulching, and degradable film mulching conditions. The yield increase will be greater with no mulching, but in the future, film mulching will continue to reduce crop yields. Additionally, the crop yield reduction under traditional polyethylene film mulching is greater. A sensitivity analysis indicated that rainfall will have a major effect on yield, and polyethylene film mulching will reduce the sensitivity of the yield to rainfall. As the rainfall increases, the differences between the yield and water use efficiency under ordinary plastic film and degradable film will become smaller. In the later period with a warmer and wetter climate under the SSP585 scenario, the water use efficiency will be higher under degradable film than traditional polyethylene film mulching. Conclusion: It can be seen that degradable film is more adaptable to the warmer and wetter climate in the future.
Realtime Picking Point Decision Algorithm of Trellis Grape for High-Speed Robotic Cut-and-Catch Harvesting
Authors: Xu Zhujie , Liu Jizhan , Wang Jie , Cai Lianjiang , Jin Yucheng , Zhao Shengyi , Xie Binbin
Published: June 2023

For high-speed robotic cut-and-catch harvesting, efficient trellis grape recognition and picking point positioning are crucial factors. In this study, a new method for the rapid positioning of picking points based on synchronous inference for multi-grapes was proposed. Firstly, a three-dimensional region of interest for a finite number of grapes was constructed according to the “eye to hand” configuration. Then, a feature-enhanced recognition deep learning model called YOLO v4-SE combined with multi-channel inputs of RGB and depth images was put forward to identify occluded or overlapping grapes and synchronously infer picking points upwards of the prediction boxes of the multi-grapes imaged completely in the three-dimensional region of interest (ROI). Finally, the accuracy of each dimension of the picking points was corrected, and the global continuous picking sequence was planned in the three-dimensional ROI. The recognition experiment in the field showed that YOLO v4-SE has good detection performance in various samples with different interference. The positioning experiment, using a different number of grape bunches from the field, demonstrated that the average recognition success rate is 97% and the average positioning success rate is 93.5%; the average recognition time is 0.0864 s; and the average positioning time is 0.0842 s. The average positioning errors of the x, y, and z directions are 2.598, 2.012, and 1.378 mm, respectively. The average positioning error of the Euclidean distance between the true picking point and the predicted picking point is 7.69 mm. In field synchronous harvesting experiments with different fruiting densities, the average recognition success rate is 97%; the average positioning success rate is 93.606%; and the average picking success rate is 92.78%. The average picking speed is 6.18 s×bunch−1, which meets the harvesting requirements for high-speed cut-and-catch harvesting robots. This method is promising for overcoming time-consuming harvesting caused by the problematic positioning of the grape stem.
Selected Nutrition and Management Strategies in Suckling Pigs to Improve Post-Weaning Outcomes
Authors: Arnaud Elisa A. , Gardiner Gillian E. , Lawlor Peadar G.
Published: June 2023

Weaning is a critical period in a pig’s life. Piglets are confronted with abrupt changes to their physical and social environment, as well as management and nutritional changes. Weaning has always been associated with a growth check and is frequently accompanied by post-weaning diarrhoea in piglets. However, rapid increases in litter size in the last decade have increased within-litter piglet weight variation, with piglets now generally lighter at weaning, making the challenges associated with weaning even greater. Many interventions can be employed during the suckling period to ease the weaning transition for piglets. Pre-weaning strategies such as supervised farrowing (assistance with suckling and oxytocin provision), the provision of pain relief to sows around farrowing, split-suckling, early oral supplementation with glucose, bovine colostrum, faecal microbiota transplantation, feed additives and solid and liquid creep feeding (milk and liquid feed) have all been investigated. The objective of these strategies is to stimulate earlier maturation of the digestive tract, improve immunity, reduce latency to the first feed post-weaning and increase early post-weaning feed intake and growth. This review focuses in particular on: (1) pain relief provision to sows around farrowing, (2)split-suckling of piglets, (3) pre-weaning provision of supplementary milk and/or liquid feed, (4) other strategies to stimulate earlier enzyme production (e.g., enzyme supplementation), (5) other nutritional strategies to promote improved gut structure and function (e.g., L-glutamine supplementation), and (6) other strategies to modulate gut microbiota (e.g., probiotics and prebiotics). Correctly implementing these strategies can, not only increase post-weaning growth and reduce mortality, but also maximise lifetime growth in pigs.
Would You Detour with Me? Association between Functional Breed Selection and Social Learning in Dogs Sheds Light on Elements of Dog–Human Cooperation
Authors: Dobos Petra , Pongrácz Péter
Published: June 2023

Interspecific social learning is a main synchronizing mechanism that enables dogs to adapt to the anthropogenic niche. It is not known whether dogs in general possess the capacity of learning from humans or whether more recent selective events have affected their ability to learn from humans. We hypothesized that cooperative and independent working dog breeds may behave differently in a social learning task. Dogs (N = 78 from 16 cooperative and 18 independent breeds) had to detour a transparent, V-shaped wire mesh fence. The experiment consisted of three one-minute-long trials. The control condition did not include a demonstration. In the demonstration condition, the experimenter placed a reward in the inside corner by walking around the fence. Cooperative dogs reached the target significantly faster, while independent dogs did not detour faster in trials 2 and 3 after the human demonstration. Detour latencies were not associated with the keeping conditions and training level of the subjects. As we assembled both test groups from several genetically distantly related breeds, we can exclude the explanation that higher cooperativity emerged only in particular clades of dogs; instead, functional selection for particular working tasks could enhance capacities that affect a wide range of socio-cognitive traits in dogs.
Species Composition of Parasitic Mites of the Subfamily Picobiinae (Acariformes: Syringophilidae) Associated with African Barbets (Piciformes: Lybiidae)
Authors: Sikora Bozena , Mahamoud-Issa Mathieu , Unsoeld Markus , Hromada Martin , Skoracki Maciej
Published: June 2023

In this study, we conducted a parasitological investigation of the quill mite fauna of the subfamily Picobiinae (Acariformes: Prostigmata: Syringophilidae) associated with African barbets (Aves: Piciformes: Lybiidae). We examined twenty-seven host species, representing 57% of the forty-seven known host species in the family Lybiidae, belonging to seven genera (70% of the ten genera in the family). Our research revealed that ten host species were infested by three species of picobiine mites belonging to the genus Tanopicobia: (1) Tanopicobia hallae Sikora and Skoracki, sp. n., from three species of the genus Lybius and two species of the genus Tricholaema, (2) Tanopicobia stactolaema Sikora and Skoracki, sp. n., from two species of the genus Stactolaema, and (3) Tanopicobia trachyphoni Skoracki et al., 2020, collected from three host species of the genus Trachyphonus. Our findings demonstrate that birds belonging to the family Lybiidae have a specific parasite fauna consisting exclusively of mites of the genus Tanopicobia; this mite genus is apparently restricted to African barbets.
Evaluation of the Genetic Diversity, Population Structure and Selection Signatures of Three Native Chinese Pig Populations
Authors: Zhong Ziqi , Wang Ziyi , Xie Xinfeng , Tian Shuaishuai , Wang Feifan , Wang Qishan , Ni Shiheng , Pan Yuchun , Xiao Qian
Published: June 2023

Indigenous pig populations in Hainan Province live in tropical climate conditions and a relatively closed geographical environment, which has contributed to the formation of some excellent characteristics, such as heat tolerance, strong disease resistance and excellent meat quality. Over the past few decades, the number of these pig populations has decreased sharply, largely due to a decrease in growth rate and poor lean meat percentage. For effective conservation of these genetic resources (such as heat tolerance, meat quality and disease resistance), the whole-genome sequencing data of 78 individuals from 3 native Chinese pig populations, including Wuzhishan (WZS), Tunchang (TC) and Dingan (DA), were obtained using a 150 bp paired-end platform, and 25 individuals from two foreign breeds, including Landrace (LR) and Large White (LW), were downloaded from a public database. A total of 28,384,282 SNPs were identified, of which 27,134,233 SNPs were identified in native Chinese pig populations. Both genetic diversity statistics and linkage disequilibrium (LD) analysis indicated that indigenous pig populations displayed high genetic diversity. The result of population structure implied the uniqueness of each native Chinese pig population. The selection signatures were detected between indigenous pig populations and foreign breeds by using the population differentiation index (FST) method. A total of 359 candidate genes were identified, and some genes may affect characteristics such as immunity (IL-2, IL-21 and ZFYVE16), adaptability (APBA1), reproduction (FGF2, RNF17, ADAD1 and HIPK4), meat quality (ABCA1, ADIG, TLE4 and IRX5), and heat tolerance (VPS13A, HSPA4). Overall, the findings of this study will provide some valuable insights for the future breeding, conservation and utilization of these three Chinese indigenous pig populations.
Clinical Features and Outcomes of VAP Due to Multidrug-Resistant Klebsiella spp.: A Retrospective Study Comparing Monobacterial and Polybacterial Episodes
Authors: Adukauskiene Dalia , Ciginskiene Ausra , Adukauskaite Agne , Koulenti Despoina , Rello Jordi
Published: June 2023

VAP due to multidrug-resistant (MDR) bacteria is a frequent infection among patients in ICUs. Patient characteristics and mortality in mono- and polybacterial cases of VAP may differ. A single-centre, retrospective 3-year study was conducted in the four ICUs of a Lithuanian referral university hospital, aiming to compare both the clinical features and the 60-day ICU all-cause mortality of monobacterial and polybacterial MDR Klebsiella spp. VAP episodes. Of the 86 MDR Klebsiella spp. VAP episodes analyzed, 50 (58.1%) were polybacterial. The 60-day mortality was higher (p < 0.05) in polybacterial episodes: overall (50.0 vs. 27.8%), in the sub-group with less-severe disease (SOFA < 8) at VAP onset (45.5 vs. 15.0%), even with appropriate treatment (41.7 vs. 12.5%), and the sub-group of extended drug-resistant (XDR) Klebsiella spp. (46.4 vs. 17.6%). The ICU mortality (44.0 vs. 22.5%) was also higher in the polybacterial episodes. The monobacterial MDR Klebsiella spp. VAP was associated (p < 0.05) with prior hospitalization (61.1 vs. 40.0%), diabetes mellitus (30.6 vs. 5.8%), obesity (30.6 vs. 4.7%), prior antibiotic therapy (77.8 vs. 52.0%), prior treatment with cephalosporins (66.7 vs. 36.0%), and SOFA cardiovascular ≥ 3 (44.4 vs. 10.0%) at VAP onset. Patients with polybacterial VAP were more likely (p < 0.05) to be comatose (22.2 vs. 52.0%) and had a higher SAPS II score (median [IQR] 45.0 [35.25–51.1] vs. 50.0 [40.5–60.75]) at VAP onset. Polybacterial MDR Klebsiella spp. VAP had distinct demographic and clinical characteristics compared to monobacterial, and was associated with poorer outcomes.
The Research Status, Potential Hazards and Toxicological Mechanisms of Fluoroquinolone Antibiotics in the Environment
Authors: Du Jia , Liu Qinghua , Pan Ying , Xu Shaodan , Li Huanxuan , Tang Junhong
Published: June 2023

Fluoroquinolone antibiotics are widely used in human and veterinary medicine and are ubiquitous in the environment worldwide. This paper recapitulates the occurrence, fate, and ecotoxicity of fluoroquinolone antibiotics in various environmental media. The toxicity effect is reviewed based on in vitro and in vivo experiments referring to many organisms, such as microorganisms, cells, higher plants, and land and aquatic animals. Furthermore, a comparison of the various toxicology mechanisms of fluoroquinolone antibiotic residues on environmental organisms is made. This study identifies gaps in the investigation of the toxic effects of fluoroquinolone antibiotics and mixtures of multiple fluoroquinolone antibiotics on target and nontarget organisms. The study of the process of natural transformation toward drug-resistant bacteria is also recognized as a knowledge gap. This review also details the combined toxicity effect of fluoroquinolone antibiotics and other chemicals on organisms and the adsorption capacity in various environmental matrices, and the scarcity of data on the ecological toxicology evaluation system of fluoroquinolone antibiotics is identified. The present study entails a critical review of the literature providing guidelines for the government to control the discharge of pollutants into the environment and formulate policy coordination. Future study work should focus on developing a standardized research methodology for fluoroquinolone antibiotics to guide enterprises in the design and production of drugs with high environmental biocompatibility.
Whole Genome Sequencing and Phenotypic Analysis of Antibiotic Resistance in Filifactor alocis Isolates
Authors: Romero-Martínez Rosa , Maher Anushiravan , Àlvarez Gerard , Figueiredo Rui , León Rubén , Arredondo Alexandre
Published: June 2023

There is scarce knowledge regarding the antimicrobial resistance profile of F. alocis. Therefore, the objective of this research was to assess antimicrobial resistance in recently obtained F. alocis clinical isolates and to identify the presence of antimicrobial resistance genes. Isolates were obtained from patients with periodontal or peri-implant diseases and confirmed by sequencing their 16S rRNA gene. Confirmed isolates had their genome sequenced by whole genome sequencing and their phenotypical resistance to nine antibiotics (amoxicillin clavulanate, amoxicillin, azithromycin, clindamycin, ciprofloxacin, doxycycline, minocycline, metronidazole, and tetracycline) tested by E-test strips. Antimicrobial resistance genes were detected in six of the eight isolates analyzed, of which five carried tet(32) and one erm(B). Overall, susceptibility to the nine antibiotics tested was high except for azithromycin in the isolate that carried erm(B). Moreover, susceptibility to tetracycline, doxycycline, and minocycline was lower in those isolates that carried tet(32). The genetic surroundings of the detected genes suggested their inclusion in mobile genetic elements that might be transferrable to other bacteria. These findings suggest that, despite showing high susceptibility to several antibiotics, F. alocis might obtain new antimicrobial resistance traits due to its acceptance of mobile genetic elements with antibiotic resistance genes in their genome.
Evaluation of Aztreonam and Ceftazidime/Avibactam Synergism against Klebsiella pneumoniae by MALDI-TOF MS
Authors: Wilhelm Camila Mörschbächer , Inamine Everton , Martins Andreza Francisco , Barth Afonso Luís
Published: June 2023

Introduction: Resistance to carbapenems due to the co-production of NDM and ESBL or NDM and KPC is increasing. Therefore, combined therapy with aztreonam (ATM) plus ceftazidime/avibactam (CZA) has been recommended. Then, it is necessary to develop and evaluate fast and simple methods to determine synergism in vitro in microbiology laboratories. Objective: To develop a method to determine the synergism of ATM and CZA by MALDI-TOF MS (SynMALDI). Method: Klebsiella pneumoniae (n = 22) isolates with blaNDM and/or blaKPC genes were tested. The time–kill curve assay was performed for four isolates (three positives for blaNDM and blaKPC and one positive for blaNDM only). For SynMALDI, each isolate was incubated for 3 h in 4 tubes containing brain–heart infusion broth with the following: (1) no antibiotic; (2) ATM at 64 mg/L; (3) CZA at 10/4 mg/L; and (4) ATM at 64 mg/L plus CZA at 10/4 mg/L. After incubation, the bacterial protein extract was analyzed by MALDI-TOF MS, and the relative growth (RG) was determined for each isolate, considering intensities of the peaks of the bacterium incubated with antibiotic (tubes 2, 3, and 4) to the same bacterium incubated without antibiotic (tube 1), as follows: RG = IntensityWith antibiotic/IntensityWithout antibiotic. The combination was determined as synergistic when there was an RG decrease of 0.3 in the antibiotic combination in relation to the RG of the most active antibiotic alone. Results: The combination of ATM plus CZA proved to be synergic by time–kill curve assay. All isolates tested with the SynMALDI method also presented synergism. Conclusions: Detection of synergism for ATM plus CZA combination can be determined by MALDI-TOF MS, providing fast results in order to improve patient treatment.
Unsupervised Method Based on Adversarial Domain Adaptation for Bearing Fault Diagnosis
Authors: Li Yao , Yang Rui , Wang Hongshu
Published: June 2023

This paper contributes to improving a bottleneck residual block-based feature extractor as a set of layers for transforming raw data into features for classification. This structure is utilized to avoid the issues of the deep learning network, such as overfitting problems and low computational efficiency caused by redundant computation, high dimensionality, and gradient vanishing. With this structure, a domain adversarial neural network (DANN), a domain adversarial unsupervised model, and a maximum classifier discrepancy (MCD), a domain adaptation model, have been applied to conduct a binary classification of fault diagnosis data. In addition, a pseudo-label is applied to MCD for comparison with the original one. In comparison, several popular models are selected for transferability estimation and analysis. The experimental results have shown that DANN and MCD with this improved feature extractor have achieved high classification accuracy, with 96.84% and 100%, respectively. Meanwhile, after using the pseudo-label semi-supervised learning, the average classification accuracy of the MCD model increased by 15%, increasing to 94.19%.
Analysis of Influencing Factors and Prevention of Coal Wall Deformation and Failure of Coal Wall in Caving Face with Large Mining Height: Case Study
Authors: Meng Guohao , Zhang Jixiong , Wang Chongjing , Zhou Nan , Li Meng
Published: June 2023

The coal walls in a caving face with a tall mining height are prone to rib spalling, which leads to the phased cessation of the mining of the working face, causes heavy losses, and endangers the safety of underground workers. In order to prevent serious rib spalling accidents of coal walls in fully mechanized caving faces with a large mining height and to improve the prediction of and ability to control rib spalling, a load-bearing mechanical model of the roof–coal wall–support system was established based on the moment-balance relationship. The expressions for the deformation and stress distribution in a coal wall were calculated. Then, the influences of key factors on the horizontal displacement of the coal wall were investigated. A numerical simulation model of the working face was established, and an orthogonal test design was introduced. On this basis, the influences of four factors: cutting height, breaking position of the main roof, support strength, and sidewall protecting force of the support on the horizontal displacement and volume of a plastic zone of coal wall, were analyzed. Moreover, their order of importance was ranked on the basis of sensitivity. Based on the engineering conditions and production practices in the Cuncaota II Coal Mine, key parameters for controlling and measures for preventing the rib spalling of the coal wall are proposed to guide practical actions.
In Situ Analysis of Curling Defects in Powder Bed Fusion of Polyamide by Simultaneous Application of Laser Profilometry and Thermal Imaging
Authors: Klamert Victor , Schiefermair Lukas , Bublin Mugdim , Otto Andreas
Published: June 2023

Additive manufacturing (AM) is one of the key technologies in the global manufacturing market within various application sectors. The unique capabilities of AM enable high structural and part complexity, low material waste, and benefits in productivity by reducing design cycles and time to market. Efficient real-time quality control is still an important challenge in AM. In this paper, a real-time and in situ approach for monitoring the process in powder bed fusion of polyamide (PBF-LB/P/PA12) is proposed using the simultaneous application of two individual sensors, enabling the overlay and direct comparison of independent output data. An industrial grade laser profilometer and a thermal infrared (IR) camera were successfully integrated into a commercial system for PBF-LB/P. Artificially created curling defects were induced in a reproducible way by the manipulation of process parameters. The radiometric data was evaluated and processed into 3D topology and profile measurements to highlight peaks and curling progression. The results measured using different powder bed conditions were contrasted with corresponding thermographic data to prove the thermal visibility of curling and the influence of inhomogeneous temperature distribution on geometrical powder surface defects. The experimental setup enables the measuring of the entire powder bed surface inside the machine, with no limitations to sub-areas. Results indicate the measurable presence of curling and related temperature influences. When curling reached maximum values, inverted warpage into the negative z-direction was detected at part center as a further effect. These results can be used for improving real-time quality control in AM.
Remaining Useful Life Prediction of Aircraft Turbofan Engine Based on Random Forest Feature Selection and Multi-Layer Perceptron
Authors: Wang Hairui , Li Dongwen , Li Dongjun , Liu Cuiqin , Yang Xiuqi , Zhu Guifu
Published: June 2023

The accurate prediction of the remaining useful life (RUL) of aircraft engines is crucial for improving engine safety and reducing maintenance costs. To tackle the complex issues of nonlinearity, high dimensionality, and difficult-to-model degradation processes in aircraft engine monitoring parameters, a new method for predicting the RUL of aircraft engines based on the random forest algorithm and a Bayes-optimized multilayer perceptron (MLP) was proposed here. First, the random forest algorithm was used to evaluate the importance of historical monitoring parameters of the engine, selecting the key features that significantly impact the engine’s lifetime operation cycle. Then, the single exponent smoothing (SES) algorithm was introduced for smoothing the extracted features to reduce the interference of original noise. Next, an MLP-based RUL prediction model was established using a neural network. The Bayes’ online parameter updating formula was used to solve the objective function and return the optimal parameters of the MLP training model and the minimum value of the evaluation index RMSE. Finally, the probability density function of the predicted RUL value of the aircraft engine was calculated to obtain the RUL prediction results.The effectiveness of the proposed method was verified and analyzed using the C-MAPSS dataset for turbofan engines. Experimental results show that, compared with several other methods, the RMSE of the proposed method in the FD001 test set decreases by 6.1%, demonstrating that the method can effectively improve the accuracy of RUL prediction for aircraft engines.
Changes in Body Mass and Movement Strategy Maintain Jump Height Immediately after Soccer Match
Authors: Spencer Ryan , Sindall Paul , Hammond Kelly M. , Atkins Steve J. , Quinn Mark , McMahon John J.
Published: June 2023

A countermovement jump (CMJ) performed on a force plate is commonly applied in soccer to quantify acute neuromuscular fatigue (NMF), which may manifest immediately following soccer match play. Jump height (JH) is the main outcome variable reported for this purpose; however, it is sensitive to alterations in movement strategy, which may act to mask JH and, therefore, mask any presence of NMF. Acute reductions in body mass (BM) during match play could also lead to the maintenance of JH, but this is yet to be explored. This study sought to explore soccer-match-induced alterations to JH, movement strategy, and BM to inform future variable selection for the study of acute NMF. Fourteen male English National League soccer players performed three CMJs on a dual-force plate system immediately before and after a competitive soccer match. Differences in jump height were non-significant and trivial (p = 0.924, g = 0.03) before and after soccer match play, but there was a large post-match decrease in BM (g = 1.66). Furthermore, moderate decreases in jump momentum (g = 0.56) and countermovement depth (g = 0.72) were noted. As JH was determined by the take-off velocity, reduced BM could have augmented it (less mass to accelerate); however, reduced countermovement depth seemingly counteracted this (less distance to attain velocity). It may, therefore, be beneficial to report these variables when monitoring acute NMF via the CMJ.
Data-Driven and Knowledge-Guided Heterogeneous Graphs and Temporal Convolution Networks for Flood Forecasting
Authors: Shao Pingping , Feng Jun , Wu Yirui , Wang Wenpeng , Lu Jiamin
Published: June 2023

Data-driven models have been successfully applied to flood prediction. However, the nonlinearity and uncertainty of the prediction process and the possible noise or outliers in the data set will lead to incorrect results. In addition, data-driven models are only trained from available datasets and do not involve scientific principles or laws during the model training process, which may lead to predictions that do not conform to physical laws. To this end, we propose a flood prediction method based on data-driven and knowledge-guided heterogeneous graphs and temporal convolutional networks (DK-HTAN). In the data preprocessing stage, a low-rank approximate decomposition algorithm based on a time tensor was designed to interpolate the input data. Adding an attention mechanism to the heterogeneous graph module is beneficial for introducing prior knowledge. A self-attention mechanism with temporal convolutional network was introduced to dynamically calculate spatiotemporal correlation characteristics of flood data. Finally, we propose physical mechanism constraints for flood processes, adjusted and optimized data-driven models, corrected predictions that did not conform to physical mechanisms, and quantified the uncertainty of predictions. The experimental results on the Qijiang River Basin dataset show that the model has good predictive performance in terms of interval prediction index (PI), RMSE, and MAPE.
Self-Training with Entropy-Based Mixup for Low-Resource Chest X-ray Classification
Authors: Park Minkyu , Kim Juntae
Published: June 2023

Deep learning-based medical image analysis technology has been developed to the extent that it shows an accuracy surpassing the ability of a human radiologist in some tasks. However, data labeling on medical images requires human experts and a great deal of time and expense. Moreover, medical image data usually have an imbalanced distribution for each disease. In particular, in multilabel classification, learning with a small number of labeled data causes overfitting problems. The model easily overfits the limited number of labeled data, while it still underfits the large amount of unlabeled data. In this study, we propose a method that combines entropy-based Mixup and self-training to improve the performance of data-imbalanced chest X-ray classification. The proposed method is to apply the Mixup algorithm to limited labeled data to alleviate the data imbalance problem and perform self-training that effectively utilizes the unlabeled data while iterating this process by replacing the teacher model with the student model. Experimental results in an environment with a limited number of labeled data and a large number of unlabeled data showed that the classification performance was improved by combining entropy-based Mixup and self-training.
Integrated Assessment of CO2-Induced Acidification Lethal and Sub-Lethal Effects on Tropical Mussels Perna perna
Authors: Souza Lorena da Silva , Bonnail Estefanía , de Almeida Duarte Luis Felipe , Cesar Augusto , Riba Inmaculada , Pereira Camilo Dias Seabra
Published: June 2023

Leakages of CO2 capture and storage systems from the seabed are able to cause significant adverse biological effects in marine species. Adult mussels were exposed to different CO2 enrichment scenarios (pH from 8.3 to 6.0) for 96 h, and endpoints (lysosomal membrane deterioration, lipid peroxidation and primary damages in DNA) were assessed. Mortality and reduced health status can occur after short exposure of the tropical mussel Perna perna to pH levels lower than 7.5. Results pointed out cytogenotoxic effects in the hemolymph and gills after 48 and 96 h of exposure, respectively. These findings should be considered when environmental monitoring approaches are performed in tropical marine areas employing CCS strategies.