bluuebunny/crossref_metadata_2025 huggingface dataset:
Heterogeneity of Urban and Rural Areas in Association of Fringe Benefits and Depression: A Cross-Sectional Study
Authors: Luo Tianwen , Yan Chaoyang , Zhang Xiang
Published: January 2022

Background

Fringe benefits are an important social support in the work scenario, but empirical research on their effect on the mental health of employees is lacking. This study aims to analyse the relationship between different fringe benefits and depression in urban and rural areas.

Methods

Chi-square analysis was used to describe the distribution differences of individual characteristics between urban and rural areas in depression groups. Logistic regression was used to further estimate the relationship between fringe benefits and depression between urban and rural areas.

Results

People with free lunch in urban areas are less likely to suffer from depression. People with food subsidies in rural areas are also less likely to suffer from depression. The abnormal result is people with housing subsidies in rural areas are more likely to be depressed. The effects of job type and contract on depression were different between urban and rural areas.

Conclusions

Employers in urban areas should focus on providing free lunch and the quality of lunch, whereas in rural areas, catering subsidies may be a more appropriate way to improve the mental health of employees. The psychological status of rural workers who receive housing subsidies and have contracts also needs attention.
Analysis of the Impact of External Debt on Health in an Emerging Asian Economy: Does FDI Matter?
Authors: Ma Yechi , Hu Mengyun , Zafar Quratulain
Published: January 2022

In this study, our main objective is to find the impact of FDI and external debt on health outcomes in emerging Asian economies from 1991 to 2019. To that end, we have collected data for seven economies: Bangladesh, Malaysia, Philippines, Thailand, Sri Lanka, China, and India. We have relied on the panel ARDL (PARDL) method for empirical analysis. The study's findings confirmed that the debt has increased infant mortality and decreased life expectancy in emerging Asian economies in the long run. On the other side, the FDI causes infant mortality to fall and life expectancy to rise in the long run in emerging Asian economies. Similarly, the health expenditures also reduced the infant mortality rate, though the impact is insignificant, and improved the life expectancy in emerging Asian economies. The causal analysis confirmed the two-way causality between health expenditure, infant mortality, and health expenditure and debt.
Irrigating Solutions and Activation Methods Used in Clinical Endodontics: A Systematic Review
Authors: Tonini Riccardo , Salvadori Matteo , Audino Elisabetta , Sauro Salvatore , Garo Maria Luisa , Salgarello Stefano
Published: January 2022

Background

Ex vivo and in vitro studies have demonstrated the effectiveness of some irrigation protocols in reducing the bacterial load in the root canal system. However, standardized protocols have not yet been defined for the real clinical context due to many irrigation procedures available.

Objective

To evaluate the clinical endodontic protocols and limitations of irrigating solutions in the disinfection of the root canal system in patients with apical periodontitis.

Methods

PubMed, Scopus, Embase, Web of Science, and Cochrane databases were searched for randomized controlled trials (RCT) published until January 2021. Hand searching was also performed. Studies focused on evaluating the effectiveness of irrigating solutions and/or irrigation activation methods in reducing the bacterial load in the root canal system were considered. The Cochrane risk-of-bias tool for randomized trials (RoB2) was used to assess the quality of the studies.

Results

Four hundred and twenty eight published articles were identified. After removing the duplicate studies and analyzing full texts, seven RCTs were selected. Two studies compared pure NaOCl with some combination of NaOCl with HEDP and MTAD. Two studies analyzed the antibacterial efficacy of NaOCl and chlorhexidine (CHX). Three studies compared conventional needle irrigation with different irrigation activation methods (PUI, XP-endo finisher, F-file activator, EndoVac activator). The review attained a satisfactory methodology. The main results of each included study were described.

Discussion

Activation methods provide significantly higher biofilm reduction than conventional needle irrigation methods. Combinations of NaOCl with different chelating agents were ineffective in terms of antimicrobial, but it could potentially increase the risk of irrigant extrusion. However, the irrigating protocols were not carefully detailed, especially those regarding the irrigants application time or total volume. The existing literature lacks high-quality studies. The level of evidence is moderate.

Conclusions

The available data is too heterogeneous to compare and identify the superiority of specific valuable irrigation protocols in each clinical context. Application time, volume, and activation methods should be standardized to determine the optimal irrigating procedures to reduce the bacterial load and ensure higher predictability of the endodontic treatment.

Systematic Review Registration

(https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=218555), PROSPERO registration: CRD42020218555.
Performance Characterization of Dosimeters Based on Radiation-Hard Silicon Diodes in Gamma Radiation Processing
Authors: Bueno C. C. , Camargo F. , Gonçalves J. A. C. , Pascoalino K. , Mangiarotti A. , Tuominen E. , Härkönen J.
Published: January 2022

The dosimetric response of silicon diodes produced with distinct engineering technologies, Magnetic Czochralski (MCz), and standard Float Zone (Fz), has been investigated, aiming at their use for online dosimeters in gamma radiation processing applications. The p+-n-n+ junction diodes, 300 µm thick with an active area of 25 mm2, are operated as online radiation dosimeters in the short-circuit current mode. In this case, the key dosimetric quantity is the dose rate, which is correlated with the output current from the diode subjected to radiation. Thus, the dose is obtained offline by the integration of the corresponding current signal. The irradiations are performed with an industrial Gammacell 60Co facility at 2.3–2.44 kGy/h covering doses up to 275 kGy. Under continuous irradiation, both diodes delivered current signals whose intensities decreased with accumulated doses. Mitigation of this decay has been accomplished by pre-irradiating the devices to 700 kGy. Polynomial functions best represent the dose responses for either pristine or preirradiated diodes. The relevant dosimetric parameters as response stability, charge sensitivity, and repeatability of current signals (<5%) reveal the better performance of the MCz diode. It is important to note that the whole dataset fully complies with the international standard protocols for routine dosimeters in radiation processing dosimetry. Regarding radiation damage, which in unbiased diodes manifests primarily in the decay of current sensitivity, the results also showed greater tolerance of the MCz diode. Based on these studies, large availability, and better cost-effectiveness, it is possible to endorse the potential use of MCz devices as online routine dosimeters in radiation processing applications. However, the data reproducibility with the accumulated dose, the dose lifespan, and the effect of the irradiation conditions (e.g., temperature, relative humidity, and dose fractionating) remain to be investigated. Works in this direction are currently in progress.
Growing Opportunities for Equitable, Interdisciplinary Undergraduate Food Systems Education: A Review of Food Systems Education at Land-Grant Institutions and Development of Open-Access Materials
Authors: Belarmino Emily H. , Kolodinsky Jane , Ammerman Alice S. , Connor Volpe Leah , Brown Covington , Jilcott Pitts Stephanie B. , Hanson Karla L. , Sitaker Marilyn , Wang Weiwei , McGuirt Jared T. , Carfagno Michelle , Hunsinger Emily , Seguin-Fowler Rebecca A.
Published: January 2022

Post-secondary coursework related to agriculture and the food supply has been at the core of the United States' land-grant system for more than 150 years. However, as the complexity of food systems has grown, so too have critiques that the education provided in these programs is too narrow to adequately prepare graduates to address pressing food systems issues. In response, some higher education institutions have developed degrees in food systems. To support development of this burgeoning field, we created, tested, and refined four evidence-informed, interdisciplinary, equity-oriented, open-access teaching modules. These modules are based on our experience conducting a multi-site, multi-year transdisciplinary investigation of subsidized, or “cost-offset”, community supported agriculture and a survey asking instructors at land-grant institutions (n = 66) about topic offerings and current unmet needs for instructional materials. Our collaboration illuminated the potential and challenges of food systems research; underscored the value of transdisciplinary research teams; and identified several equity-oriented topics related to the design, implementation, and evaluation of local food initiatives suitable for advancing sustainable foods systems education. Instructors reported that the most helpful teaching aids would be case studies, lesson plans with active learning components, and reference lists with relevant peer-reviewed publications. The final modules seek to shed light on the complexity of food systems projects and build knowledge, vocabularies, and skills across disciplines engaged with food systems. Per instructor-defined needs, each module features a case study, active-learning activities, and references. We anticipate that the adaptable modules will be suitable for a wide range of students and courses.
Serum Lactate Level in Early Stage Is Associated With Acute Kidney Injury in Traumatic Brain Injury Patients
Authors: Wang Ruoran , Wang Shaobo , Zhang Jing , He Min , Xu Jianguo
Published: January 2022

Background

Acute kidney injury (AKI) is a common complication in the clinical practice of managing patients with traumatic brain injury (TBI). Avoiding the development of AKI is beneficial for the prognosis of patients with TBI. We designed this study to testify whether serum lactate could be used as a predictive marker of AKI in patients with TBI.

Materials and Methods

In total, 243 patients with TBI admitted to our hospital were included in this study. Univariate and multivariate logistic regression analyses were utilized to analyze the association between lactate and AKI. The receiver operating characteristic (ROC) curves were drawn to verify the predictive value of lactate and the logistic model.

Results

Acute kidney injury group had higher age (p = 0.016), serum creatinine (p < 0.001), lactate (p < 0.001), and lower Glasgow Coma Scale (GCS; p = 0.021) than non-AKI group. Multivariate logistic regression showed that age [odds ratio (OR) = 1.026, p = 0.022], serum creatinine (OR = 1.020, p = 0.010), lactate (OR = 1.227, p = 0.031), fresh frozen plasma (FFP) transfusion (OR = 2.421, p = 0.045), and platelet transfusion (OR = 5.502, p = 0.044) were risk factors of AKI in patients with TBI. The area under the ROC curve (AUC) values of single lactate and predictive model were 0.740 and 0.807, respectively.

Conclusion

Serum lactate level in the early phase is associated with AKI in patients with TBI. Lactate is valuable for clinicians to evaluate the probability of AKI in patients with TBI.
Establishment and Analysis of an Individualized Immune-Related Gene Signature for the Prognosis of Gastric Cancer
Authors: Li Mengying , Cao Wei , Huang Bingqian , Zhu Zhipeng , Chen Yaxin , Zhang Jiawei , Cao Guodong , Chen Bo
Published: January 2022

A growing number of studies have shown that immunity plays an important clinical role in the process of gastric cancer (GC). The purpose of this study was to explore the function of differentially expressed immune-related genes (DEIRGs) of GC, and construct a gene signature to predict the overall survival (OS) of patients. Gene expression profiles and clinical data of GC patients were downloaded from TCGA and GEO databases. Combined with immune-related genes (IRGs) downloaded from the ImmPort database, 357 DEIRGs in GC tissues and adjacent tissues were identified. Based on the analysis of Lasso and Cox in the training set, a prognostic risk scoring model consisting of 9 (RBP7, DES, CCR1, PNOC, SPP1, VIP, TNFRSF12A, TUBB3, PRKCG) DEIRGs was obtained. Functional analysis revealed that model genes may participate in the formation and development of tumor cells by affecting the function of cell gap junction intercellular communication (GJJC). According to the model score, the samples were divided into high-risk and low-risk groups. In multivariate Cox regression analysis, the risk score was an independent prognostic factor (HR = 1.674, 95% CI = 1.470–1.907, P < 0.001). Survival analysis showed that the OS of high-risk GC patients was significantly lower than that of low-risk GC patients (P < 0.001). The area under the receiver operating characteristic curve (ROC) of the model was greater than other clinical indicators when verified in various data sets, confirming that the prediction model has a reliable accuracy. In conclusion, this study has explored the biological functions of DEIRGs in GC and discovered novel gene targets for the treatment of GC. The constructed prognostic gene signature is helpful for clinicians to determine the prognosis of GC patients and formulate personalized treatment plans.
A Virulent Trueperella pyogenes Isolate, Which Causes Severe Bronchoconstriction in Porcine Precision-Cut Lung Slices
Authors: Qin Lei , Meng Fandan , He Haijuan , Yang Yong-Bo , Wang Gang , Tang Yan-Dong , Sun Mingxia , Zhang Wenlong , Cai Xuehui , Wang Shujie
Published: January 2022

Trueperella pyogenes causes disease in cattle, sheep, goats and swine, and is involved occasionally in human disease worldwide. Most reports implicating T. pyogenes have been associated with clinical cases, whereas no report has focused on pathogenicity of T. pyogenes in mouse models or precision-cut lung slice (PCLS) cultures from swine. Here, we isolated and identified a virulent, β-hemolytic, multidrug-resistant T. pyogenes strain named 20121, which harbors the virulence marker genes fimA, fimE, nanH, nanP and plo. It was found to be highly resistant to erythromycin, azithromycin and medemycin. Strain 20121 was pathogenic in mouse infection models, displaying pulmonary congestion and inflammatory cell infiltration, partial degeneration in epithelial cells of the tracheal and bronchiolar mucosa, a small amount of inflammatory cell infiltration in the submucosa, and bacteria (>104 CFU/g) in the lung. Importantly, we used T. pyogenes 20121 to infect porcine precision-cut lung slices (PCLS) cultures for the first time, where it caused severe bronchoconstriction. Furthermore, dexamethasone showed its ability to relieve bronchoconstriction in PCLS caused by T. pyogenes 20121, highlighting dexamethasone may assist antibiotic treatment for clinical T. pyogenes infection. This is the first report of T. pyogenes used to infect and cause bronchoconstriction in porcine PCLS. Our results suggest that porcine PCLS cultures as a valuable 3D organ model for the study of T. pyogenes infection and treatment in vitro.
No Cell Left behind: Automated, Stochastic, Physics-Based Tracking of Every Cell in a Dense, Growing Colony
Authors: Pham Huy , Shehada Emile R. , Stahlheber Shawna , Pandey Kushagra , Hayes Wayne B.
Published: January 2022

Motivation: Precise tracking of individual cells—especially tracking the family lineage, for example in a developing embryo—has widespread applications in biology and medicine. Due to significant noise in microscope images, existing methods have difficulty precisely tracking cell activities. These difficulties often require human intervention to resolve. Humans are helpful because our brain naturally and automatically builds a simulation “model” of any scene that we observe. Because we understand simple truths about the world—for example cells can move and divide, but they cannot instantaneously move vast distances—this model “in our heads” helps us to severely constrain the possible interpretations of what we see, allowing us to easily distinguish signal from noise, and track the motion of cells even in the presence of extreme levels of noise that would completely confound existing automated methods. Results: Here, we mimic the ability of the human brain by building an explicit computer simulation model of the scene. Our simulated cells are programmed to allow movement and cell division consistent with reality. At each video frame, we stochastically generate millions of nearby “Universes” and evolve them stochastically to the next frame. We then find and fit the best universes to reality by minimizing the residual between the real image frame and a synthetic image of the simulation. The rule-based simulation puts extremely stringent constraints on possible interpretations of the data, allowing our system to perform far better than existing methods even in the presense of extreme levels of image noise. We demonstrate the viability of this method by accurately tracking every cell in a colony that grows from 4 to over 300 individuals, doing about as well as a human can in the difficult task of tracking cell lineages.
Variation of Osculating Orbit Elements Using Low-Thrust Photonic Laser Propulsion in the Two-Body Problem
Authors: Hsiao Fu-Yuen
Published: January 2022

This study investigated the variation of the osculating orbit elements of a spacecraft propelled by photonic laser propulsion (PLP) under the two-body problem assumption. The PLP thrusting system can produce continuous and constant thrust. This paper first reviewed its basics and then studied its influences on the variation of osculating orbit elements given a small PLP thrust. Gauss’s equations, perturbation theory, and normalization were introduced to investigate this problem. Our work approached the problem by studying the influences of small planar and out-of-plane PLP thrusts, respectively. Bounds on the variation of orbit elements were derived, and a sufficient condition that traps the mission spacecraft in the vicinity of the mother ship was also found. Numerical simulations are also presented to verify our results, including the bounds and the sufficient conditions. The results obtained in this paper are directly applicable to the usage of PLP thrust, a new type of thrusting system, in the future, and are potentially helpful to various space missions, especially interplanetary travel.
Acknowledgment to Reviewers of AgriEngineering in 2021
Authors:   AgriEngineering Editorial Office
Published: January 2022

Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Effects of Nitrogen plus Sulfur Fertilization and Seeding Density on Yield, Rheological Parameters, and Asparagine Content in Old Varieties of Common Wheat (Triticum aestivum L.)
Authors: Soofizada Quadratullah , Pescatore Antonio , Guerrini Lorenzo , Fabbri Carolina , Mancini Marco , Orlandini Simone , Napoli Marco
Published: January 2022

Numerous epidemiological studies have highlighted the positive effects on health of wholegrain bakery products made from ‘old’ common wheat (Triticum aestivum L.) varieties. However, ‘old’ common wheat varieties display poor rheological properties, and there is limited information on its free asparagine (ASN) content, the main precursor to acrylamide during the baking process. This paper evaluates the effects of two seeding density levels (SD: 200 and 350 seed m−2), three nitrogen levels (NL: 35, 80 and 135 kg N ha−1), and two sulfur levels (SL: 0 and 6.4 kg S ha−1) towards improving the grain yield (GY), rheological characteristics, and ASN content of 14 ‘old’ common wheat varieties. SL and SD treatments significantly increased GY without decreasing the protein content (PC), while NL significantly increased the PC without affecting GY. The dough strength (W) increased significantly with increasing SL and NL but was significantly reduced with increasing SD. ASN significantly increased by 111% as NL increased from 35 to 135 kg ha−1, while ASN significantly decreased by 85.1% with the SL treatment. The findings show that 135 kg N ha−1 combined with 6.4 kg S ha−1 can improve the technical performance of ‘old’ wheat wholegrain flours while maintaining the ASN as low as possible.
The Nitrogen Fixation and Yielding of Pea in Different Soil Tillage Systems
Authors: Faligowska Agnieszka , Kalembasa Stanisław , Kalembasa Dorota , Panasiewicz Katarzyna , Szymańska Grażyna , Ratajczak Karolina , Skrzypczak Grzegorz
Published: January 2022

The field experiment was carried out in 2013 and 2014 as part of a long-term experiment to test the influence of different soil tillage systems (conventional, reduced, direct sowing) on (a) the yield of summer pea (Pisum sativum L.) and (b) the amount of biologically reduced atmospheric nitrogen (N), which was determined using the 15N dilution method (ID15N). Spring barley was used as a reference plant. Climatic conditions did not have a significant influence on the yield of pea seeds (mean value 4.56 t ha−1), post-harvest residues (3.76 t ha−1) and total biomass (8.33 t ha−1). Soil tillage system was found to have a significant impact on all components of the pea yield in years of experiment, with the highest average seed yield values observed with the conventional system (5.19 t ha−1) and significantly lower values observed with reduced tillage (4.34 t ha−1) and direct sowing (4.17 t ha−1). The content of total N was greatest in the pea biomass that was harvested in the conventional system (202 kg ha−1) and lowest with direct sowing (155 kg ha−1). Nitrogen accumulated in the pea seeds from three sources: atmosphere (mean value 35.2%), fertilizers (6.8%) and soil (57.9%), equating to 48.6, 9.9, and 85.4 kg ha−1, respectively. Soil tillage system was found to have a significant impact on the amount of N that was fixed from the atmosphere by the peas: 17.7% in conventional tillage, 37.9 in reduced system and 50.2% in direct sowing, which equates to a harvested seed yield of 28.9, 52.0 and 64.4 kg ha−1, respectively. In the post-harvest residues, the amount of N fixed from the atmosphere by the pea crop was also modified by the soil tillage system in range: 20.2% in conventional tillage and 32.6% in direct sowing (which equates to 7.4 and 8.5 kg N ha−1, respectively), but the difference was not significant.
Benchmark of Deep Learning and a Proposed HSV Colour Space Models for the Detection and Classification of Greenhouse Tomato
Authors: Moreira Germano , Magalhães Sandro Augusto , Pinho Tatiana , dos Santos Filipe Neves , Cunha Mário
Published: January 2022

The harvesting operation is a recurring task in the production of any crop, thus making it an excellent candidate for automation. In protected horticulture, one of the crops with high added value is tomatoes. However, its robotic harvesting is still far from maturity. That said, the development of an accurate fruit detection system is a crucial step towards achieving fully automated robotic harvesting. Deep Learning (DL) and detection frameworks like Single Shot MultiBox Detector (SSD) or You Only Look Once (YOLO) are more robust and accurate alternatives with better response to highly complex scenarios. The use of DL can be easily used to detect tomatoes, but when their classification is intended, the task becomes harsh, demanding a huge amount of data. Therefore, this paper proposes the use of DL models (SSD MobileNet v2 and YOLOv4) to efficiently detect the tomatoes and compare those systems with a proposed histogram-based HSV colour space model to classify each tomato and determine its ripening stage, through two image datasets acquired. Regarding detection, both models obtained promising results, with the YOLOv4 model standing out with an F1-Score of 85.81%. For classification task the YOLOv4 was again the best model with an Macro F1-Score of 74.16%. The HSV colour space model outperformed the SSD MobileNet v2 model, obtaining results similar to the YOLOv4 model, with a Balanced Accuracy of 68.10%.
Soil Water Content Directly Affects Bud Burst Rate in Single-Node Cuttings of Perennial Plants
Authors: Signorelli Santiago , Dewi Juwita R. , Considine Michael J.
Published: January 2022

The use of single-node cuttings of shoots as explants to study bud dormancy and its physiology under controlled conditions is a common practice in grapevine (Vitis vinifera L.) or other perennial plant research. In particular, this method has been extensively used to understand the effect of different chemicals on bud dormancy and bud burst. However, the soil water content in those experiments is usually not reported and its relevance is often neglected. Here, we observed that an unevenly distributed soil water content in a tray containing multiple explants results in an uneven pattern of bud burst within the same treatment. Thus, we hypothesised that soil water content can dramatically affect bud burst. To investigate this, we first established that fresh single-node cuttings were able to transport water into the buds. We then tested the rate of bud burst at different water treatments (35%, 55%, 70%, 85%, and 100% of field capacity; FC). We observed a clear dependence of bud burst on water, in which, at very low levels of water, bud burst does not occur; after 35% FC, bud burst rate increases with water content until around 85% FC; and, from 85% FC, bud burst rate becomes independent of water content. These data highlight the critical importance of monitoring soil water content in any bud burst assay in perennials. Finally, we provide a detailed protocol for determining and controlling field capacity and other soil water content indicators.
Antibiotic Discovery and Resistance: The Chase and the Race
Authors: Iskandar Katia , Murugaiyan Jayaseelan , Hammoudi Halat Dalal , Hage Said El , Chibabhai Vindana , Adukkadukkam Saranya , Roques Christine , Molinier Laurent , Salameh Pascale , Van Dongen Maarten
Published: January 2022

The history of antimicrobial resistance (AMR) evolution and the diversity of the environmental resistome indicate that AMR is an ancient natural phenomenon. Acquired resistance is a public health concern influenced by the anthropogenic use of antibiotics, leading to the selection of resistant genes. Data show that AMR is spreading globally at different rates, outpacing all efforts to mitigate this crisis. The search for new antibiotic classes is one of the key strategies in the fight against AMR. Since the 1980s, newly marketed antibiotics were either modifications or improvements of known molecules. The World Health Organization (WHO) describes the current pipeline as bleak, and warns about the scarcity of new leads. A quantitative and qualitative analysis of the pre-clinical and clinical pipeline indicates that few antibiotics may reach the market in a few years, predominantly not those that fit the innovative requirements to tackle the challenging spread of AMR. Diversity and innovation are the mainstays to cope with the rapid evolution of AMR. The discovery and development of antibiotics must address resistance to old and novel antibiotics. Here, we review the history and challenges of antibiotics discovery and describe different innovative new leads mechanisms expected to replenish the pipeline, while maintaining a promising possibility to shift the chase and the race between the spread of AMR, preserving antibiotic effectiveness, and meeting innovative leads requirements.
Oral Vancomycin Prophylaxis for Primary and Secondary Prevention of Clostridioides difficile Infection in Patients Treated with Systemic Antibiotic Therapy: A Systematic Review, Meta-Analysis and Trial Sequential Analysis
Authors: Maraolo Alberto Enrico , Mazzitelli Maria , Zappulo Emanuela , Scotto Riccardo , Granata Guido , Andini Roberto , Durante-Mangoni Emanuele , Petrosillo Nicola , Gentile Ivan
Published: January 2022

Background: Clostridioides difficile infection (CDI) is associated with substantial morbidity and mortality as well as high propensity of recurrence. Systemic antibiotic therapy (SAT) represents the top inciting factor of CDI, both primary and recurrent (rCDI). Among the many strategies aimed to prevent CDI in high-risk subjects undergoing SAT, oral vancomycin prophylaxis (OVP) appears promising under a cost-effectiveness perspective. Methods: A systematic review with meta-analysis and trial sequential analysis (TSA) of studies assessing the efficacy and the safety of OVP to prevent primary CDI and rCDI in persons undergoing SAT was carried out. PubMed and EMBASE were searched until 30 September 2021. The protocol was pre-registered on PROSPERO (CRD42019145543). Results: Eleven studies met the inclusion criteria, only one being a randomized controlled trial (RCT). Overall, 929 subjects received OVP and 2011 represented the comparator group (no active prophylaxis). OVP exerted a strong protective effect for CDI occurrence: odds ratio 0.14, 95% confidence interval 0.04–0.38. Moderate heterogeneity was observed: I2 54%. This effect was confirmed throughout several subgroup analyses, including prevention of primary CDI versus rCDI. TSA results pointed at the conclusive nature of the evidence. Results were robust to a variety of sensitivity and quantitative bias analyses, although the underlying evidence was deemed as low quality. No differences between the two groups were highlighted regarding the onset of vancomycin-resistant Enterococcus infections. Conclusions: OVP appears to be an efficacious option for prevention of CDI in high-risk subjects undergoing SAT. Nevertheless, additional data from RCTs are needed to establish OVP as good clinical practice and define optimal dosage and duration.
Up-To-Date Analysis of the Extraction Methods for Anthocyanins: Principles of the Techniques, Optimization, Technical Progress, and Industrial Application
Authors: Tena Noelia , Asuero Agustin G.
Published: January 2022

Nowadays, food industries are concerned about satisfying legal requirements related to waste policy and environmental protection. In addition, they take steps to ensure food safety and quality products that have high nutritional properties. Anthocyanins are considered high added-value compounds due to their sensory qualities, colors, and nutritional properties; they are considered bioactive ingredients. They are found in high concentrations in many by-products across the food industry. Thus, the non-conventional extraction techniques presented here are useful in satisfying the current food industry requirements. However, selecting more convenient extraction techniques is not easy. Multiple factors are implicated in the decision. In this review, we compile the most recent applications (since 2015) used to extract anthocyanins from different natural matrices, via conventional and non-conventional extraction techniques. We analyze the main advantages and disadvantages of anthocyanin extraction techniques from different natural matrices and discuss the selection criteria for sustainability of the processes. We present an up-to-date analysis of the principles of the techniques and an optimization of the extraction conditions, technical progress, and industrial applications. Finally, we provide a critical comparison between these techniques and some recommendations, to select and optimize the techniques for industrial applications.
Functions of Redox Signaling in Pollen Development and Stress Response
Authors: Xie Dong-Ling , Zheng Xue-Lian , Zhou Can-Yu , Kanwar Mukesh Kumar , Zhou Jie
Published: January 2022

Cellular redox homeostasis is crucial for normal plant growth and development. Each developmental stage of plants has a specific redox mode and is maintained by various environmental cues, oxidants, and antioxidants. Reactive oxygen species (ROS) and reactive nitrogen species are the chief oxidants in plant cells and participate in cell signal transduction and redox balance. The production and removal of oxidants are in a dynamic balance, which is necessary for plant growth. Especially during reproductive development, pollen development depends on ROS-mediated tapetal programmed cell death to provide nutrients and other essential substances. The deviation of the redox state in any period will lead to microspore abortion and pollen sterility. Meanwhile, pollens are highly sensitive to environmental stress, in particular to cell oxidative burst due to its peculiar structure and function. In this regard, plants have evolved a series of complex mechanisms to deal with redox imbalance and oxidative stress damage. This review summarizes the functions of the main redox components in different stages of pollen development, and highlights various redox protection mechanisms of pollen in response to environmental stimuli. In continuation, we also discuss the potential applications of plant growth regulators and antioxidants for improving pollen vigor and fertility in sustaining better agriculture practices.
Probiotic Bacillus Alleviates Oxidative Stress-Induced Liver Injury by Modulating Gut-Liver Axis in a Rat Model
Authors: Wu Yanping , Wang Baikui , Tang Li , Zhou Yuanhao , Wang Qi , Gong Li , Ni Jiajia , Li Weifen
Published: January 2022

Emerging evidence suggests a key role of gut microbiota in maintaining liver functions through modulating the gut–liver axis. In this study, we investigated whether microbiota alteration mediated by probiotic Bacillus was involved in alleviating oxidative stress- induced liver injury. Sprague–Dawley rats were orally administered Bacillus SC06 or SC08 for a 24-day period and thereafter intraperitoneally injected diquat (DQ) to induce oxidative stress. Results showed that Bacillus, particularly SC06 significantly inhibited hepatic injuries, as evidenced by the alleviated damaged liver structure, the decreased levels of ALT, AST, ALP and LDH, and the suppressed mitochondrial dysfunction. SC06 pretreatment markedly enhanced the liver antioxidant capacity by decreasing MDA and p47, and increasing T-AOC, SOD and HO-1.16S rRNA sequencing analysis revealed that DQ significantly changed the diversities and composition of gut microbiota, whereas Bacillus pretreatments could attenuate gut dysbiosis. Pearson’s correlation analysis showed that AST and MDA exerted a positive correlation with the opportunistic pathogenic genera and species (Escherichia and Shigella), and negatively correlated with the potential probiotics (Lactobacillus), while SOD exerted a reverse trend. The microbial metagenomic analysis demonstrated that Bacillus, particularly SC06 markedly suppress the metabolic pathways such as carbohydrate metabolism, lipid metabolism, amino acid metabolism and metabolism of cofactors and vitamins. Furthermore, SC06 decreased the gene abundance of the pathways mediating bacterial replication, secretion and pathogenicity. Taken together, Bacillus SC06 alleviates oxidative stress-induced liver injuries via optimizing the composition, metabolic pathways and pathogenic replication and secretion of gut microbiota. These findings elucidate the mechanisms of probiotics in alleviating oxidative stress and provide a promising strategy for preventing liver diseases by targeting gut microbiota.
Melatonin as a Smart Protector of Pregnancy in Dairy Cows
Authors: Dirandeh Essa , Ansari-Pirsaraei Zarbakht , Thatcher William
Published: January 2022

The experimental objective was to examine the role of melatonin and its pathways in the maintenance of pregnancy in lactating dairy cows. Blood samples were collected at days 0, 16 and 32 after timed AI from cows (n = 200) in order to consider plasma melatonin concentrations and to conduct AOPP (advanced oxidation products of proteins) and TBARS (thiobarbituric acid reactive substances) tests. Luminal endometrial cells were collected at day 16 using a Cytobrush in all cows to determine mRNA expressions of melatonin receptor 1 (MT1), mouse double minute 2 (MDM2), MDM2 binding protein (MTBP), BCL2-associated X, apoptosis Regulator (BAX), p53 upregulated modulator of apoptosis (PUMA, gene symbol BBC3), mucin 1 (MUC1) and leukemia inhibitory factor (LIF). Plasma concentrations of melatonin were significantly greater in pregnant cows diagnosed pregnant at day 16 who sustained pregnancy to day 32 compared to nonpregnant cows at day 16, or pregnant at day 16 and who lost embryos by days 32. Concentrations of AOPP and TBARS were greater in nonpregnant cows at day 16 or pregnant at day 16 and who lost embryos by days 32 compared to those diagnosed pregnant at day 16 and who sustained pregnancy to day 32. In pregnant cows, endometrial mRNA expressions of MDM2, MTBP, MTR1 and LIF were higher compared to pregnant–embryo-loss cows (p < 0.05). In contrast, mRNA expressions of BBC3 and MUC1 were greater at day 16 in pregnant–embryo-loss cows compared to pregnant cows (p < 0.05). In conclusion, melatonin status is a modulator of embryo well-being and maintenance of pregnancy in lactating dairy cows.
Combining LoRaWAN and NB-IoT for Edge-to-Cloud Low Power Connectivity Leveraging on Fog Computing
Authors: Peruzzi Giacomo , Pozzebon Alessandro
Published: January 2022

Low Power Wide Area Networks (LPWANs) play crucial roles in the implementation of low-power and low-cost wide area distributed systems. Currently, two enabling technologies are the main competitors within the connectivity field for the Internet of Things (IoT), primarily because of their scalability, wide range and low power features: Long Range Wide Area Network (LoRaWAN) and Narrowband IoT (NB-IoT). In this paper, a brand new network architecture is presented, which combines both aforementioned technologies. Such a network accounts for sensor nodes, multi-protocol gateways, an a cloud infrastructure. Sensor nodes may be alternatively provided with LoRaWAN or NB-IoT. Multi-protocol gateways can receive and demodulate LoRaWAN packets and upload them to the cloud via the Message Queue Telemetry Transport (MQTT) protocol over NB-IoT. The cloud is transparent with respect to the transmission technology, meaning that data are acquired and stored regardless of the exploited technique (i.e., LoRaWAN or NB-IoT). Indeed, sensor nodes using NB-IoT can send data to the cloud and can directly communicate with other NB-IoT nodes setting up a fog computing paradigm on peer-to-peer subnetworks. This approach may be crucial for the development of complex IoT infrastructures while providing high flexibility.
Model for the Simulation of the Time-Dependent State in RC Elements
Authors: Džolan Ante , Galić Mirela , Harapin Alen
Published: January 2022

The paper presents an upgrade of the previously developed model for nonlinear 3D analysis of concrete structures extended with the possibility of simulation of the long-term effects (shrinkage and creep) under long-term static load. The origin model is based on the so-called multi-surface principle with modified Rankin criterion for dominant tensile influences (appearance and development of cracks) and the modified Mohr-Coulomb criterion for dominant compressive states (yielding and cracking of concrete). The material behaviour is described with elementary material parameters (modulus of elasticity, Poisson’s coefficient and uniaxial compressive and tensile strength of concrete) by standard tests. Sufficient accuracy along with a simple and effective description of the very complex behaviour of reinforced concrete structures, make this model advantageous. Creep and shrinkage are based on the procedure given by the fib Model Code 2010 and extended with a special extension for non-linear creeping. Two simple examples show the capabilities of the model, while a good agreement between numerical and experimental results indicates that the developed model can well describe long-term effects in reinforced concrete structures, and that the model is appropriate for standard engineering practice.
Comparison Study of the PSO and SBPSO on Universal Robot Trajectory Planning
Authors: Kazim Issraa Jwad , Tan Yuegang , Li Ruiya
Published: January 2022

Industrial robots were modified over the years. The benefit of robots is making production systems more efficient. Most methods of controlling robots have some limitations, such as stopping the robots. The robot stops by various reasons, such as collisions. The goal of this study is to study the comparison of improving the Artificial Potential Field (APF) by the traditional Particle Swarm Optimization (PSO) algorithm and the Serendipity-Based PSO (SBPSO) algorithm to control the path of a universal robot UR5 with collision avoidance. Already, the metaheuristic algorithm kinds deal with a premature convergence. This paper presents a new approach, which depends on the concept of serendipity and premature convergence applied to the path of the universal manipulator UR5 and also compares it with traditional the PSO. The features of the SBPSO algorithm prototype are formalized in this paper using the concept of serendipity in two dimensions: intelligence and chance. The results showed that the SBPSO is more efficient and has better convergence behavior than the traditional PSO for controlling the trajectory planning of the UR5 manipulator with obstacle avoidance.
Benchmarking Socio-Economic Impacts of High-Speed Rail Networks Using K-Nearest Neighbour and Pearson’s Correlation Coefficient Techniques through Computational Model-Based Analysis
Authors: Rungskunroch Panrawee , Shen Zuo-Jun , Kaewunruen Sakdirat
Published: January 2022

Not only have high-speed rail (HSR) services stimulated the economy of many countries, but they have also significantly uplifted quality of lives (QoL) of countless people. For many decades, the aspiration for HSR network development has dramatically risen, and HSR networks have inevitably become an icon of civilisation. However, only a few successful HSR networks globally can truly generate socio-economic impacts on their societies. This research aims to understand the impact of HSR networks on social and economic impacts and to provide recommendations for success. This study is the world’s first to examine the benefits of HSR across all community demographic groups, including young and elderly people. The findings will illustrate the QoL, economic, and educational elements’ advantages in explicit terms. It has established two interconnected models via Python to codify a novel customised model for socio-economic evaluation. ‘Pearson correlation coefficient’ and ‘K-Nearest Neighbour’ techniques are applied to bolster the reliability of the research findings. The outcomes have been reviewed by 30 international HSR specialists. The benchmarking exhibits that socio-economic impacts apparently occur across vast areas. The insight stemming from this benchmarking also offers policy implications and empirical data for long-term HSR improvement, assisting the government in developing new methods for sustainable communities.
An Approach to Diagnostics of Geomagnetically Induced Currents Based on Ground Magnetometers Data
Authors: Vorobev Andrei , Soloviev Anatoly , Pilipenko Vyacheslav , Vorobeva Gulnara , Sakharov Yaroslav
Published: January 2022

The geomagnetically induced currents (GICs) in extended grounded technological systems are driven by telluric electric fields induced by the rapid changes of the geomagnetic field. The paper is concerned with research on the approach to diagnostics of GIC in the power transmission lines in northwestern Russia based on data from IMAGE magnetometers. Based on the results of the statistical and correlation analysis of the objective function (the level of the GIC recorded at the Vykhodnoy transformer station) and geomagnetic data recorded by the nearby IMAGE magnetometers, the features that best characterize the target variable in a given region are distinguished. Using machine learning (ML) methods, the defined number of feature objects is used to develop the relationship for the GIC diagnostics. Evaluation of the coefficient of determination for a stack of various ML methods revealed that the regression approach and artificial neural networks (ANN) are the best solution for the problem under consideration. Verification tests have shown that ANN-based approach and regression methods provide nearly the same diagnostic accuracy for GIC (the mean square error 0.12 A2). However, ANN-based methods are less interpretable and require more computer resources.
Toxicological Profiling of Onion-Peel-Derived Mesoporous Carbon Nanospheres Using In Vivo Drosophila melanogaster Model
Authors: Bhat Vinay S. , Kudva Avinash Kundadka , Naik Harshitha Venkatesh , G. Reshmi , Raghu Shamprasad Varija , De Padova Paola , Hegde Gurumurthy
Published: January 2022

Toxicological profiling of the novel carbon materials has become imperative, owing to their wide applicability and potential health risks on exposure. In the current study, the toxicity of mesoporous carbon nanospheres synthesized from waste onion peel was investigated using the genetic animal model Drosophila melanogaster. The survival assays at different doses of carbon nanoparticles suggested their non-toxic effect for exposure for 25 days. Developmental and behavioral defects were not observed. The biochemical and metabolic parameters, such as total antioxidant capacity (TAC), protein level, triglyceride level, and glucose, were not significantly altered. The neurological toxicity as analyzed using acetylcholinesterase activity was also not altered significantly. Survival, behavior, and biochemical assays suggested that oral feeding of mesoporous carbon nanoparticles for 25 days did not elicit any significant toxicity effect in Drosophila melanogaster. Thus, mesoporous carbon nanoparticles synthesized from waste onion peel can be used as beneficial drug carriers in different disease models.
Integration of Improvement Strategies and Industry 4.0 Technologies in a Dynamic Evaluation Model for Target-Oriented Optimization
Authors: Gallego-García Sergio , Groten Marcel , Halstrick Johannes
Published: January 2022

Many improvement techniques, methods, and technologies have been the driver of the development of supply chain systems. However, many managers and companies are focused only on new technologies without considering a comprehensive evaluation, and therefore lacking a real need and purpose. As a result, practitioners are often confused with regard of how to integrate improvement strategies and new technologies, as well as how to evaluate their convenience. Thus, this research aims to develop a model for the assessment for each manufacturing capability. This assessment aims to enable a continuous business transformation aligned with organizational goals; thus, a dynamic maturity assessment is chosen. Based on this, the study seeks to provide an integration model for relevant improvement strategies and new technologies that can be applied to any organization. As a result, the paper develops a sequence model, the GUVEI-Model, for the application of Industry 4.0 related technologies for continuous improvement in five different clusters. Furthermore, the research develops an evaluation scheme of optimization alternatives. Based on this conceptual development, a simulation model is built for specific use cases, such as additive manufacturing or virtual reality. The results show how the use cases along the GUVEI-Model application improve relevant indicators significantly, with the first two steps, obtaining and using data, acting as enablers of the three subsequent optimization steps that allow the virtualization, expansion, and improvement of capabilities and a higher impact on the target indicators than the first two steps. Finally, a discussion is presented about the utility of digital twin models for dynamic maturity level assessment and for simulating project improvement impacts before, during, and after their implementation.