bluuebunny/crossref_metadata_2025 huggingface dataset:
Biological management of coffee wilt disease (Fusarium xylarioides) using antagonistic Trichoderma isolates
Authors: Mulatu Afrasa , Megersa Negussie , Teferi Demelash , Alemu Tesfaye , Vetukuri Ramesh Raju
Published: March 2023

Coffee wilt disease (CWD) is a serious threat to the food security of small-scale farmers in Ethiopia, causing significant reductions in coffee yield. Currently, there are no effective control measures available against the causative agent of CWD, Fusarium xylarioides. The main objective of this study was therefore to develop, formulate, and evaluate a range of biofungicides against F. xylarioides, derived from Trichoderma species and tested under in vitro, greenhouse, and field conditions. In total, 175 Trichoderma isolates were screened as microbial biocontrol agents against F. xylarioides. The efficacy of two biofungicide formulations, wettable powder and water dispensable granules, were tested on the susceptible Geisha coffee variety in three different agro-ecological zones in southwestern Ethiopia over three years. The greenhouse experiments were set up using a complete block design, while in the field a randomized complete block design was used, with twice yearly applications of biofungicide. The test pathogen spore suspension was applied to the coffee seedlings by soil drenching, and the subsequent incidence and severity of CWD evaluated annually. The mycelial growth inhibition profiles of the Trichoderma isolates against F. xylarioides ranged from 44.5% to 84.8%. In vitro experiments revealed that T. asperelloides AU71, T. asperellum AU131 and T. longibrachiatum AU158 reduced the mycelial growth of F. xylarioides by over 80%. The greenhouse study indicated that wettable powder (WP) of T. asperellum AU131 had the highest biocontrol efficacy (84.3%), followed by T. longibrachiatum AU158 (77.9%) and T. asperelloides AU71 (71.2%); they also had a significant positive impact on plant growth. The pathogen-treated control plants had a disease severity index of 100% across all the field experiments, and of 76.7% in the greenhouse experiments. In comparison to untreated controls, the annual and cumulative disease incidence over the three years of the study period varied from 46.2 to 90%, 51.6 to 84.5%, and 58.2 to 91%, at the Teppi, Gera and Jimma field experimental locations. Overall, the greenhouse and field experiments and in vitro assays support the biocontrol potential of Trichoderma isolates, and T. asperellum AU131 and T. longibrachiatum AU158 in particular are recommended for the management of CWD under field conditions.
Comparative analyses of functional traits based on metabolome and economic traits variation of Bletilla striata: Contribution of intercropping
Authors: Deng Pengfei , Yin Ruoyong , Wang Huiling , Chen Leiru , Cao Xiaoqing , Xu Xiaoniu
Published: March 2023

The intercropping practice has been regarded as a practical land-use selection to improve the management benefits of Bletilla striata plantations. The reports about the variety of economic and functional traits of Bletilla pseudobulb under intercropping systems were limited. The present study investigated the variation of economic and functional traits of Bletilla pseudobulb under different intercropping systems (the deep-rooted intercropping system: B. striata - Cyclocarya paliurus, CB; and the shallow-rooted intercropping system: B. striata - Phyllostachys edulis, PB). The functional traits were analyzed through non-targeted metabolomics based on GC-MS. The results indicated that the PB intercropping system significantly decreased the yield of Bletilla pseudobulb while significantly increasing the total phenol and flavonoids compared with the control (CK). However, there were no significant differences in all economic traits between CB and CK. The functional traits among CB, PB, and CK were separated and exhibited significant differences. Under different intercropping systems, B. striata may adopt different functional strategies in response to interspecific competition. The functional node metabolites (D-galactose, cellobiose, raffinose, D-fructose, maltose, and D-ribose) were up-regulated in CB, while the functional node metabolites (L-valine, L-leucine, L-isoleucine, methionine, L-lysine, serine, D-glucose, cellobiose, trehalose, maltose, D-ribose, palatinose, raffinose, xylobiose, L-rhamnose, melezitose, and maltotriose) were up-regulated in PB. The correlation between economic and functional traits depends on the degree of environmental stress. Artificial neural network models (ANNs) accurately predicted the variation in economic traits via the combination of functional node metabolites in PB. The correlation analysis of environmental factors indicated that Ns (including TN, NH4+-, and NO3--), SRI (solar radiation intensity), and SOC were the main factors that affected the economic traits (yield, total phenol, and total flavonoids). TN, SRI, and SOC were the main factors affecting the functional traits of the Bletilla pseudobulb. These findings strengthen our understanding of the variation of economic and functional traits of Bletilla pseudobulb under intercropping and clarify the main limiting environmental factors under B. striata intercropping systems.
Severity assessment of wheat stripe rust based on machine learning
Authors: Jiang Qian , Wang Hongli , Wang Haiguang
Published: March 2023

Introduction

The accurate severity assessment of wheat stripe rust is the basis for the pathogen-host interaction phenotyping, disease prediction, and disease control measure making.

Methods

To realize the rapid and accurate severity assessment of the disease, the severity assessment methods of the disease were investigated based on machine learning in this study. Based on the actual percentages of the lesion areas in the areas of the corresponding whole single diseased wheat leaves of each severity class of the disease, obtained after the image segmentation operations on the acquired single diseased wheat leaf images and the pixel statistics operations on the segmented images by using image processing software, under two conditions of considering healthy single wheat leaves or not, the training and testing sets were constructed by using two modeling ratios of 4:1 and 3:2, respectively. Then, based on the training sets, two unsupervised learning methods including K-means clustering algorithm and spectral clustering and three supervised learning methods including support vector machine, random forest, and K-nearest neighbor were used to build severity assessment models of the disease, respectively.

Results

Regardless of whether the healthy wheat leaves were considered or not, when the modeling ratios were 4:1 and 3:2, satisfactory assessment performances on the training and testing sets can be achieved by using the optimal models based on unsupervised learning and those based on supervised learning. In particular, the assessment performances obtained by using the optimal random forest models were the best, with the accuracies, precisions, recalls, and F1 scores for all the severity classes of the training and testing sets equal to 100.00% and the overall accuracies of the training and testing sets equal to 100.00%.

Discussion

The simple, rapid, and easy-to-operate severity assessment methods based on machine learning were provided for wheat stripe rust in this study. This study provides a basis for the automatic severity assessment of wheat stripe rust based on image processing technology, and provides a reference for the severity assessments of other plant diseases.
Chemometric-guided chemical marker selection: A case study of the heat-clearing herb Scrophularia ningpoensis
Authors: Wang Lung-Shuo , Chen Po-Jen , Cheng Wen-Chi , Chang Yu-Chia , El-Shazly Mohamed , Chen Lo-Yun , Peng Bo-Rong , Su Chun-Han , Yen Pei-Tzu , Hwang Tsong-Long , Lai Kuei-Hung
Published: March 2023

The selection of medicinal plants’ chemical markers focuses on bioactivity as the primary goal, followed by the nature of secondary metabolites, their stability, and availability. However, herbal medicines are valued for their complex and holistic pharmacological effects. A correct chemical marker can be carefully selected by a systematic clarification of their chemical-biological relationships. In the current study, the multi-informative molecular networking (MIMN) approach was employed to construct the anti-inflammatory metabolomic pattern of a heat-clearing herb, Scrophularia ningpoensis Hemsl. (S. ningpoensis). The MIMN molecular families characterized by cinnamic acid glycosides showed a higher bioactivity score compared with the other two major chemical classes (iridoid glycosides and iridoid-cinnamic acid glycosides). The Global Natural Product Social Molecular Networking (GNPS) and Reaxys database were used to assist in the putative annotation of eighteen metabolites from the bioactive and non-bioactive molecular families. The anti-inflammatory validation step was based on the detection of reactive oxygen species (ROS) generation by activated human neutrophils. All compounds from the bioactive MIMN molecular families dose-dependently inhibited the total ROS generation promoted by fMLF (IC50: 0.04–0.42 μM), while the compounds from non-bioactive MIMN clusters did not show any significant anti-inflammatory effect. The ROS-dependent anti-inflammatory activity of these cinnamic acid glycosides was attributed to their oxygen radical scavenging ability. The most abundant cinnamic acid glycoside, angoroside C (IC50: 0.34 μM) was suggested to be selected as a chemical marker for S. ningpoensis. In this study, the MIMN platform was applied to assist in the chemical marker selection of S. ningpoensis. The correct selection of markers will aid in the compilation and revision of herbal monographs and pharmacopeias resulting in the precise analysis and classification of medicinal plants on a scientific basis.
Development and validation of the leadership learning agility scale
Authors: Bouland-van Dam Sophie I. M. , Oostrom Janneke K. , Jansen Paul G. W.
Published: March 2023

Introduction

Learning agility is key in the selection and development of future leaders. However, prior research has failed to clearly conceptualize learning agility and to empirically clarify its dimensions.

Method

We developed the Leadership Learning Agility Scale (LLAS) by using a combination of both deductive and inductive approaches and established scale development and validation procedures. We administered the LLAS among three independent samples of workers and leaders (N = 907;N = 196;N = 219).

Results

Our results indicate that our 18-item LLAS measures the willingness to learn from social experiences, and the drive to apply those lessons in new and challenging leadership roles, and comprises a Developing Leadership, Seeking Feedback, and Developing Systematically dimension. Furthermore, the LLAS showed adequate internal consistency. Leadership learning agility was positively related to achievement motivation, extraversion, and conscientiousness but unrelated to openness to experience.

Discussion

We provided a new scale to measure leadership learning agility that can be applied in both research and practitioner settings.
Functional Neurologic Disorders, disorders to be managed by neurologists, or are neurologists wandering in a dangerous field with inadequate resources?
Authors: Onofrj Marco , Ajdinaj Paola , Digiovanni Anna , Malek Naveed , Martinotti Giovanni , Ferro Filippo Maria , Russo Mirella , Thomas Astrid , Sensi Stefano Luca
Published: March 2023

In recent years, some neurologists reconsidered their approach to Medically Unexplained Symptoms and proposed Functional Neurologic Disorders (FND) as a new entity, claiming that neurology could offer alternative treatment options to the psychotherapies provided in psychiatry settings. FNDs, for this purpose, should include only the disorders listed as Conversion from the Somatic Symptom and Related Disorders (SSRD) group. The present review analyzes the rationale of this position and challenges the arguments provided for its support. The review also discusses the systematization of these disorders as provided by public health systems. It outlines risks stemming from economic support and public funding uncertainty, given their negligible epidemiological dimensions resulting from the parcellation of SSRD. The review underlines the unresolved issue of Factitious Disorders, which are in the same SSRD category of the international classification but are, nonetheless, overlooked by the theoretical proponents of the FND entity. Comorbidity with other psychiatric disorders is also analyzed. We propose a model that supports the continuum between different SSRD conditions, including Factitious Disorders. The model is based on the emergence of feigned death reflex and deception from frontal lobe dysfunction. Finally, the paper summarizes the wealth of historical psychiatric and psychodynamic approaches and critical reviews. The study also puts in context the categorization and interpretation efforts provided by the most eminent researchers of the past century.
Cancer risks from cosmic radiation exposure in flight: A review
Authors: Scheibler Christopher , Toprani Sneh M. , Mordukhovich Irina , Schaefer Matthew , Staffa Steven , Nagel Zachary D. , McNeely Eileen
Published: March 2023

Aircrew (consisting of flight attendants, pilots, or flight engineers/navigators) are exposed to cosmic ionizing radiation (CIR) at flight altitude, which originates from solar activity and galactic sources. These exposures accumulate over time and are considerably higher for aircrew compared to the general population, and even higher compared to U.S. radiation workers. Many epidemiological studies on aircrew have observed higher rates of specific cancers compared to the general population. Despite high levels of CIR exposure and elevated rates of cancer in aircrew, a causal link between CIR and cancer has yet to be established. Many challenges still exist in effectively studying this relationship, not the least of which is evaluating CIR exposure separately from the constellation of factors that occur as part of the flight environment. This review concentrates on cancer incidence and mortality observed among aircrew in epidemiologic studies in relation to CIR exposure and limitation trends observed across the literature. The aim of this review is to provide an updated comprehensive summary of the literature that will support future research by identifying epidemiological challenges and highlighting existing increased cancer concerns in an occupation where CIR exposure is anticipated to increase in the future.
Incidence and predictors of hyperglycemic emergencies among adult diabetic patients in Bahir Dar city public hospitals, Northwest Ethiopia, 2021: A multicenter retrospective follow-up study
Authors: Abate Melsew Dagne , Semachew Ayele , Emishaw Solomon , Meseret Fentahun , Azmeraw Molla , Algaw Dawit , Temesgen Dessie , Feleke Sefineh Fenta , Nuru Ahmed , Abate Makda , Bantie Berihun , Andualem Atsedemariam
Published: March 2023

Background

Diabetic ketoacidosis and hyperglycemic hyperosmolar syndrome are the two commonly known life-threatening hyperglycemic emergencies of diabetes mellitus. Despite the growing hyperglycemic emergency impact among adult patients with diabetes, its incidence and predictors have not been well studied in Ethiopia. Thus, this study aimed to assess the incidence and predictors of hyperglycemic emergencies among adult patients with diabetes.

Method

A retrospective follow-up study design was conducted among a randomly selected sample of 453 adult patients with diabetes. Data were entered into EPI data version 4.6 and analyzed using STATA version 14.0. A Cox-proportional hazard regression model was fitted to identify the independent predictors of hyperglycemic emergencies, and variables having a p < 0.05 in the multivariable model were considered statistically significant.

Result

Among the total adult patients with diabetes included in the study, 147 (32.45%) developed hyperglycemic emergencies. Hence, the overall incidence of hyperglycemic emergencies was 14.6 per 100 person-years observation. The incidence of diabetic ketoacidosis was 12.5 per 100 person-years (35.6 and 6.3 among T1DM and T2DM, respectively). The incidence of the hyperglycemic hyperosmolar syndrome was 2.1 per 100 person-years (0.9 and 2.4 among T1DM and T2DM, respectively). The overall median free survival time was 53.85 months. Type 1 diabetes mellitus [AHR = 2.75, 95% CI (1.68, 4.51)], diabetes duration of ≥ 3 years [AHR = 0.33, 95% CI (0.21, 0.50)], recent acute illness [AHR = 2.99, 95% CI (2.03, 4.43)], presence of comorbidity [AHR = 2.36, 95% CI (1.53, 3.63)], poor glycemic control [AHR = 3.47, 95% CI (2.17, 5.56)], history of medication non-compliance [AHR = 1.85,95% CI (1.24, 2.76)], follow-up frequency of 2–3 months [AHR = 1.79,95% CI (1.06, 3.01)], and without community health insurance [AHR = 1.63, 95% CI (1.14, 2.35)] were significant predictors of hyperglycemic emergencies.

Conclusion

The incidence of hyperglycemic emergencies was high. Therefore, giving greater attention to patients with identified predictors could decrease the occurrence of hyperglycemic emergencies and related public health and economic impacts.
Local health department engagement with workplaces during the COVID-19 pandemic—Examining barriers of and facilitators to outbreak investigation and mitigation
Authors: Bonney Tessa , Grant Michael P.
Published: March 2023

Objectives

To document local health department (LHD) COVID-19 prevention or mitigation activities at workplaces in the United States and identify facilitators for and barriers to these efforts.

Methods

We conducted a web-based, cross-sectional national probability survey of United States LHDs (n = 181 unweighted; n = 2,284 weighted) from January to March 2022, collecting information about worker complaints, surveillance, investigations, relationships and interactions with employers/businesses, and LHD capacity.

Results

Overall, 94% LHD respondents reported investigating workplace-linked COVID-19 cases; however, 47% reported insufficient capacity to effectively receive, investigate and respond to COVID-19-related workplace safety complaints. Prior relationships with jurisdiction employers and LHD personnel with formal occupational health and safety (OHS) training were predictors of proactive outreach to prevent COVID-19 spread in workplaces (p < 0.01 and p < 0.001). LHD size predicted OHS personnel and sufficient financial resources to support workplace investigation and mitigation activities (p < 0.001).

Conclusions

Differences in LHD capacity to effectively respond to communicable disease spread in workplaces may exacerbate health disparities, especially between rural and urban settings. Improving LHD OHS capacity, especially in smaller jurisdictions, could facilitate effective prevention and mitigation of workplace communicable disease spread.
Soft robotics towards sustainable development goals and climate actions
Authors: Giordano Goffredo , Murali Babu Saravana Prashanth , Mazzolai Barbara
Published: March 2023

Soft robotics technology can aid in achieving United Nations’ Sustainable Development Goals (SDGs) and the Paris Climate Agreement through development of autonomous, environmentally responsible machines powered by renewable energy. By utilizing soft robotics, we can mitigate the detrimental effects of climate change on human society and the natural world through fostering adaptation, restoration, and remediation. Moreover, the implementation of soft robotics can lead to groundbreaking discoveries in material science, biology, control systems, energy efficiency, and sustainable manufacturing processes. However, to achieve these goals, we need further improvements in understanding biological principles at the basis of embodied and physical intelligence, environment-friendly materials, and energy-saving strategies to design and manufacture self-piloting and field-ready soft robots. This paper provides insights on how soft robotics can address the pressing issue of environmental sustainability. Sustainable manufacturing of soft robots at a large scale, exploring the potential of biodegradable and bioinspired materials, and integrating onboard renewable energy sources to promote autonomy and intelligence are some of the urgent challenges of this field that we discuss in this paper. Specifically, we will present field-ready soft robots that address targeted productive applications in urban farming, healthcare, land and ocean preservation, disaster remediation, and clean and affordable energy, thus supporting some of the SDGs. By embracing soft robotics as a solution, we can concretely support economic growth and sustainable industry, drive solutions for environment protection and clean energy, and improve overall health and well-being.
Co-implementation of conservation tillage and herbicides reduces weed and nematode infestation and enhances the productivity of direct-seeded rice in North-western Indo-Gangetic Plains
Authors: Raj Rishi , Das T. K. , Pankaj  , Banerjee Tirthankar , Ghosh A. , Bhattacharyya Ranjan , Chakraborty Debashis , Prasad Shiv , Babu Subhash , Kumar Vikash , Sen Suman , Ghosh Sonaka
Published: March 2023

Direct-seeded rice (DSR) can be a resource-efficient alternative to puddled transplanted rice (PTR), but weeds and nematodes pose severe challenges. Conservation agriculture (CA)-based DSR may inhibit/influence weeds/nematodes, which can be further intensified by adopting better weed control. Hence, this experiment was undertaken. Five CA-based DSR practices involving zero tillage, residue retention, brown manuring, and superimposed with four weed control/herbicide options were compared with PTR in a split-plot design replicated three times. All DSRs encountered more weeds and plant parasitic nematodes (PPNs) than PTR. Root-knot nematodes (RKN) infested five among 14 weeds present in rice and was first time found inDinebra retroflexa. A CA-based zero till (ZT)DSR+ mungbean residue – ZT wheat + rice residue – ZT mungbean+wheat residue system reduced weeds significantly. It reduced RKN galls inEchinochloa colona, Echinochloa crusgalli, and rice plants by 72, 58, and 56%, respectively. In soil too, RKN and other PPNs, namely,Tylenchorhynchus brevilineatusandPratylenchus thorneiwere reduced by 39%, 32%, and 26%, respectively, which gave a 6.3–22.7% higher yield in this CA practice than other DSRs. Pyrazosulfuron-ethyl, cyhalofop-butyl, and bispyribac-Na applied sequentially reduced weeds and PPNs, increased rice yield by 176.1%, and were at below detectable levels in soil, rice grains, and straw, and were safe for rotational crops. The above ZT-based triple cropping with residue supplemented with herbicides through better weed and nematode control would be an alternative to PTR in the North-wester Indo-Gangetic Plains of India and in similar agroecologies of the tropics/sub-tropics. This study would help farmers and policymakers to design integrated weed and nematode management modules using tillage, crop residue, and herbicides/pesticides for higher DSR yield and income.
One-stage tracheostomy during surgery reduced early pulmonary infection and mechanical ventilation length in complete CSCI patients
Authors: Sun Lin , Feng Haoyu , Mei Jun , Wang Zhiqiang , Deng Chen , Qin Zhixin , Lv Junqiao
Published: March 2023

Objective

Complete cervical spinal cord injury (CSCI) is a devastating injury that usually requires surgical treatment. Tracheostomy is an important supportive therapy for these patients. To evaluate the effectiveness of early one-stage tracheostomy during surgery compared with necessary tracheostomy after surgery, and to identify clinical factors for one-stage tracheostomy during surgery in complete cervical spinal cord injury.

Design

Data from 41 patients with complete CSCI treated with surgery were retrospectively analyzed.

Participants and interventions

Ten patients (24.4%) underwent one-stage tracheostomy during surgery, thirteen (31.7%) underwent tracheostomy when necessary after surgery, and eighteen (43.9%) did not have a tracheostomy.

Main results

One-stage tracheostomy during surgery significantly reduced the development of pneumonia at 7 days after tracheostomy (p = 0.025), increased the PaO2 (p < 0.05), and decreased the length of mechanical ventilation (p = 0.005), length of stay (LOS) in the intensive care unit (ICU) (p = 0.002), hospital LOS (p = 0.01) and hospitalization expenses compared with necessary tracheostomy after surgery (p = 0.037). A high neurological level of injury (NLI) (NLI C5 and above), a high PaCO2 in the blood gas analysis before tracheostomy, severe breathing difficulty, and excessive pulmonary secretions were the statistically significant factors for one-stage tracheostomy during surgery in the complete CSCI patients, but no independent clinical factor was found.

Conclusions

In conclusion, one-stage tracheostomy during surgery reduced the number of early pulmonary infections and the length of mechanical ventilation, ICU LOS, hospital LOS and hospitalization expenses, and one-stage tracheostomy should be considered when managing complete CSCI patients by surgical treatment.
Advances in eggshell membrane separation and solubilization technologies
Authors: Han Chunhao , Chen Yifan , Shi Lei , Chen Hui , Li Lanhui , Ning Zhonghua , Zeng Dan , Wang Dehe
Published: March 2023

Eggshell membranes (ESM) contain 90% protein, 3% lipids, 2% sugars, and small amounts of minerals such as calcium and magnesium. Of the 90% of proteins present, 472 proteins species have been identified. ESM provide the initial mineralization platform for eggshell formation, and can be used for to produce adsorbents, cosmetics, and medical products because of their special physical structure and chemical composition. The special physical structure of the eggshell membrane, with disulfide bonds between and within the protein molecules and the cross-linking of lysine-derived and heterochain chains between the eggshell membrane, makes the membrane very difficult to dissolve, with a maximum solubility rate of only 62%. Also, the insolubility of ESM limits its development and use also any related research. Based on the physical structure and chemical composition of the eggshell membrane, this paper reviews the latest research on eggshell membrane separation and membrane protein solubilization to provide a reference for promoting the separation, dissolution, and rational development and use of the avian eggshell membrane.
Impacts of commingling preconditioned and auction-derived beef calves on bovine respiratory disease related morbidity, mortality, and weight gain
Authors: Mijar Sanjaya , van der Meer Frank , Pajor Ed , Hodder Abigail , Louden Julia Morgan , Thompson Sean , Orsel Karin
Published: March 2023

Introduction

Stressors predisposing to bovine respiratory disease (BRD) upon arrival in the feedlot, include the ranch to feedlot transition and mixing cattle from multiple sources. Preconditioning (PC) reduces multiple stressors, but commingling PC and auction-derived (AD) calves in a feedlot may increase BRD risk. Our objective was to evaluate PC calf performance over the first 40 days in the feedlot and determine impacts of commingling with varying proportions of AD calves (25, 50, and 75%).

Methods

Calves were either preconditioned at one ranch (n = 250) or mixed-source and bought from a local auction (n = 250). At arrival, calves were assigned into 1 of 5 pens: 100 PC, 75 PC, 50 PC, 25 PC, and 0 PC, reflecting the percentage of PC calves in a 100-head pen.

Results

Over 40 days, morbidity in pen 100 PC was lower compared to 0 PC (24 vs. 50%, P < 0.001) and varied in commingled pens, being highest (63%) in 25 PC and least (21%) in 50 PC (P < 0.05). There were 3 AD deaths in 0 PC and 2 deaths in 25 PC. The AD calves in 0 PC were 3 times more likely to get BRD than PC calves in 100 PC; however, AD calves gained 0.49 kg/d more than PC calves (P < 0.0001). Ignoring pen placement, AD calves were 2.76 times more likely to get BRD but gained 0.27 kg/d more than PC calves (P < 0.0001). Commingling did not affect morbidity of PC (P = 0.5) or AD calves (P = 0.96), implying commingling did not affect health. Calves in 25 PC were 3.39 times more likely to get BRD than those in the 100 PC (P < 0.001). Furthermore, 25 PC calves gained the most (1.08 kg/d), followed by 50 PC (0.62 kg/d) and 75 PC (0.61 kg/d), compared to 100 PC (P < 0.05). Calf weight at arrival modified ADG (P < 0.05).

Discussion

In conclusion, PC calves had lower morbidity over the first 40 days, irrespective of commingling. With larger variations in arrival weight, there was no advantage of PC for ADG in the first 40 days. The unknown weaning strategies and comparable arrival weights of AD calves may have contributed to greater ADG in AD calves.
Understanding the background and clinical significance of the WHO, WOAH, and EMA classifications of antimicrobials to mitigate antimicrobial resistance
Authors: Gehring Ronette , Mochel Jonathan P. , Schmerold Ivo
Published: March 2023

In Europe, the classification systems of the WHO, WOAH (founded as OIE), and EMA are the prevailing standard documents guiding the prudent use of antibiotic substances. While the WHO document “Critically important antimicrobials for human medicine” eponymously focusses on the use in humans, the other two documents, “OIE List of Antimicrobial Agents of Veterinary Importance” and “EMA Categorization of antibiotics for use in animals,” concentrate exclusively on the prudent use of antibiotics in animals. One common purpose of these classification systems is to provide guidance in making sound decisions on the choice of antibiotics for treating humans as well as animals. Although the latest editions of these compendia refer to one another and bear a clear resemblance at the category levels, some of the substances are grouped into unequal classes. This review illustrates the specific perspectives of the three categorization systems under consideration. The arguments raised for different classifications between the WHO and the EMA are exemplified for amoxicillins without beta-lactamase inhibitors, macrolides, sulfonamides, and colistin. For the daily clinical use of antibiotics, veterinarians should consider the EMA document, and, under tentative circumstances, consult the OIE list.
Visual Speech Recognition for Kannada Language Using VGG16 Convolutional Neural Network
Authors: Rudregowda Shashidhar , Patil Kulkarni Sudarshan , H L Gururaj , Ravi Vinayakumar , Krichen Moez
Published: March 2023

Visual speech recognition (VSR) is a method of reading speech by noticing the lip actions of the narrators. Visual speech significantly depends on the visual features derived from the image sequences. Visual speech recognition is a stimulating process that poses various challenging tasks to human machine-based procedures. VSR methods clarify the tasks by using machine learning. Visual speech helps people who are hearing impaired, laryngeal patients, and are in a noisy environment. In this research, authors developed our dataset for the Kannada Language. The dataset contained five words, which are Avanu, Bagge, Bari, Guruthu, Helida, and these words are randomly chosen. The average duration of each video is 1 s to 1.2 s. The machine learning method is used for feature extraction and classification. Here, authors applied VGG16 Convolution Neural Network for our custom dataset, and relu activation function is used to get an accuracy of 91.90% and the recommended system confirms the effectiveness of the system. The proposed output is compared with HCNN, ResNet-LSTM, Bi-LSTM, and GLCM-ANN, and evidenced the effectiveness of the recommended system.
Distributed Model Predictive Control with Particle Swarm Optimizer for Collision-Free Trajectory Tracking of MWMR Formation
Authors: Zhang Tian , Zhang Xiangyin
Published: March 2023

The distributed model predictive control (DMPC) strategy with particle swarm optimization (PSO) is applied to solve the collision-free trajectory tracking problem for the mecanum-wheeled mobile robot (MWMR) formation. Under the leader–follower framework, the predictive model is established considering the kinematics and dynamics of the MWMR with the uncertainties and external disturbances. Based on the information from itself and its neighbors, each MWMR is assigned its own finite-horizon optimal control problem, of which the objective/cost function consists of formation maintenance, trajectory tracking, and collision avoidance terms, and the control inputs of each MWMR are computed synchronously in a distributed manner. PSO serves as the fast and effective optimizer to find feasible solutions to these finite-horizon optimal control problems. Further, the feedback emendation is implemented using a double closed-loop compensator to efficiently inhibit the influence of unknown dynamics in real time. The stability of the proposed distributed formation control approach is strictly analyzed. Numerical simulations confirmed the robustness and effectiveness of the control approach in obstacle environments.
RAMSEES: A Model of the Atmospheric Radiative Environment Based on Geant4 Simulation of Extensive Air Shower
Authors: Cintas Hugo , Wrobel Frédéric , Ruffenach Marine , Herrera Damien , Saigné Frédéric , Varotsou Athina , Bezerra Françoise , Mekki Julien
Published: March 2023

The device downscaling of electronic components has given rise to the need to consider specific failures in onboard airplane electronics. Single Event Effects (SEE) are a kind of failures that occur due to radiation in the atmosphere. For the purpose of ensuring onboard electronic reliability, there is a clear need for new tools to predict the SEE rate, at both avionic altitudes and at ground level. In this work, we develop a new tool: RAMSEES (Radiation Atmospheric Model for SEE Simulation), which simulates the atmospheric radiative environment induced by cosmic rays. This multiscale and multi-physics phenomenon is simulated using the Geant4 toolkit, allowing the creation of a database to characterize the radiation environment in the atmosphere as a function of altitude. We show the need to simulate very high-energy particles such as 100 TeV space protons, because they are the main contributor of radiation at avionic altitudes as well as at ground level. Our approach shows a good agreement with the experimental data, the standards, and other models, and it also points out some discrepancies, especially below 18 km of altitude. RAMSEES can be the basis of the estimation of the SEE rate from ground level to the stratosphere, at any given position and time.
A Machine Learning and Feature Engineering Approach for the Prediction of the Uncontrolled Re-Entry of Space Objects
Authors: Salmaso Francesco , Trisolini Mirko , Colombo Camilla
Published: March 2023

The continuously growing number of objects orbiting around the Earth is expected to be accompanied by an increasing frequency of objects re-entering the Earth’s atmosphere. Many of these re-entries will be uncontrolled, making their prediction challenging and subject to several uncertainties. Traditionally, re-entry predictions are based on the propagation of the object’s dynamics using state-of-the-art modelling techniques for the forces acting on the object. However, modelling errors, particularly related to the prediction of atmospheric drag, may result in poor prediction accuracies. In this context, we explored the possibility of performing a paradigm shift, from a physics-based approach to a data-driven approach. To this aim, we present the development of a deep learning model for the re-entry prediction of uncontrolled objects in Low Earth Orbit (LEO). The model is based on a modified version of the Sequence-to-Sequence architecture and is trained on the average altitude profile as derived from a set of Two-Line Element (TLE) data of over 400 bodies. The novelty of the work consists in introducing in the deep learning model, alongside the average altitude, and three new input features: a drag-like coefficient (B*), the average solar index, and the area-to-mass ratio of the object. The developed model was tested on a set of objects studied in the Inter-Agency Space Debris Coordination Committee (IADC) campaigns. The results show that the best performances are obtained on bodies characterised by the same drag-like coefficient and eccentricity distribution as the training set.
Functional Hazard Assessment of a Modular Re-Configurable Morphing Wing Using Taguchi and Finite Element Methodologies
Authors: Mahmood Faisal , Hashemi Seyed M. , Alighanbari Hekmat
Published: March 2023

Growing concerns over the CO2 footprint due the exponential demand of the aviation industry, along with the requirements for high aerodynamic performance, cost saving, and manoeuvrability during different phases of a flight, pave the path towards adaptable wing design. Morphing wing design encompasses most, if not all, of the flight condition variations, and can respond interactively. However, functional failure of the morphing wing might bring devastating impacts on the passengers, crew, and/or aircraft. In the present work, the dynamic characteristics of a re-configurable modular morphing wing developed in-house by a research group at the Toronto Metropolitan University, are investigated from the perspective of a functional hazard assessment (FHA). This modular morphing wing, developed based on the idea of a parallel robot, consists of a number of structural elements connected to each other and to the wing ribs through eye-bolt joints. Timoshenko’s bending beam theory, in conjunction with the finite element method (FEM), is exploited to model the structural members. Possible hazards, assumed here to be the structural failure of the beam components, have been identified and their failure conditions are assessed. Numerical simulations have been presented to show the impact of various combinations of the identified hazards on the vibration signature of the morphing wing in unmorphed and morphed configurations. Identification of changes in the wing’s vibration signature is a vital component in the fail-safe structural and aeroelastic design of an aircraft. The present study is geared towards the structural response of the system in the absence of any aerodynamic loads.
Transcriptome Sequencing Reveals Key Genes for Sunflower Unsaturated Fatty Acid Synthesis
Authors: Huang Qixiu , Xiang Lijun , Zhang Li , Maimaiti Yushanjiang , Luo Wenfang , Lei Zhonghua
Published: March 2023

Sunflower (Helianthus annuus L.) is an important oil crop with rich nutrients, and genetically engineered breeding has become an important way to improve its quality. In this study, five varieties of oilseed sunflower were analyzed for fatty acid (FA) content. The seed embryos of one of the high oleic acid (OA) varieties were transcriptome sequenced at different stages. The results showed that OA synthesis dominated the unsaturated fatty acid (UFA) synthesis pathways in seed embryos. Substantially differentially expressed genes were detected at various post-flowering stages. Specifically, the up-regulated gene numbers were highest at 10 d after flowering, while most genes were down-regulated at 20 d after flowering. The enriched genes were rather consistent with almost all experimental groups exhibiting enrichment to the FAD2 gene. The expression of FAD2 was highly negatively correlated with the expressions of FAD6, FAD3, and FAD7. During seed embryo development, the expression level of FAD2 was highly negatively correlated with the final OA content and was highly positively correlated with the final linoleic acid (LA) content. This suggests that the FAD2 is a key enzyme catalyzing the OA to LA conversion.
Leaf Extracts of Miconia albicans (Sw.) Triana (Melastomataceae) Prevent the Feeding and Oviposition of Plutella xylostella (Linnaeus, 1758) (Lepidoptera: Plutellidae)
Authors: Padial Isabella Maria Pompeu Monteiro , Souza Silvana Aparecida de , Malaquias José Bruno , Cardoso Claudia Andrea Lima , Pachú Jéssica Karina da Silva , Fioratti Claudemir Antonio Garcia , Mussury Rosilda Mara
Published: March 2023

Sustainability in food production is an increasingly discussed issue nowadays; therefore, demands for research that can reduce production costs and ensure the quality and autonomy of production are relevant, with attention to the use of plants due to their importance in biodiversity. Thus, the objective of this research was to evaluate the bioactivity, feeding preference, and oviposition preference of Miconia albicans botanical extracts at concentrations of 1%, 5%, and 10% against Plutella xylostella. We observed reduced larval duration, larval survival, female hatching success, and repellence of oviposition and feeding for all concentrations. For higher concentrations, the extracts showed a larval mortality rate of 58%, a feeding reduction of 82%, and an oviposition reduction of 94%, showing potential for pest control. Phytochemical analyses identified phenolic compounds, flavonoids, and tannins, which are substances with repellent and larvicidal properties. This is the first report on the phytosanitary potential of M. albicans, showing that the plant has both lethal and sublethal effects on P. xylostella.
Factors Influencing Farm-Land Value in the Czech Republic
Authors: Prochazka Petr , Maitah Mansoor , Mullen Kevin J. , Honig Vladimir , Soukupova Jana , Zamkova Martina , Rojik Stanislav , Smutka Lubos , Cabelkova Inna , Hinke Jana , Dvorak Marek , Sanova Petra
Published: March 2023

Czech farm-land had enjoyed considerable growth in value from 2008 to 2019. This paper identifies the main determinants of agricultural land prices variations and how these variations are influenced by urbanization, lease payments, and subsidies. These three factors were thoroughly examined for the existence of a unit root using the Augmented Dickey Fuller Test. The long-run relationship between farm-land value and these elements was estimated using the co-integration approach, specifically the Johansen procedure. The estimation confirms the existence of this long-run relationship. Short-run fluctuation in agricultural land prices is explained using the Error Correction Model. As the most important variable in the short-run performance of Czech agricultural land prices, the authors identified the influence of urbanization. This information could be used to help regulators avoid potential agricultural land value instabilities and volatility in the market and hence would contribute to sustainable land use.
A Critical Review of Biochar Application for the Remediation of Greenhouse Gas Emissions and Nutrient Loss in Rice Paddies: Characteristics, Mechanisms, and Future Recommendations
Authors: Chen Yonglin , Xu Mengqi , Yang Liyu , Jing Haonan , Mao Wenjian , Liu Jingbin , Zou Yuzheng , Wu Yuhong , Zhou Hang , Yang Wentao , Wu Pan
Published: March 2023

Greenhouse gas emissions (GHG) and nutrient loss are considered to be critical environmental issues facing rice field ecosystems. Biochars (BCs), as carbon-rich materials with porous structures, large specific surface areas, and enriched surface functional groups, have shown great potential for improving environmental problems in rice fields and increasing rice yields. However, thus far, we still lack an adequate summary and review of the performance characteristics of BCs and their environmental behavior in paddy soils. In this paper, we critically review the positive effects of BC application on the growth and yield of rice, nutrient loss reduction, and GHG reduction. Biomass type, pyrolysis temperature, and modification method are considered to be the key factors that determine the performance characteristics of BCs. The application of BCs could promote rice yield and mitigate CO2, N2O, and CH4 emissions by improving soil physicochemical properties and microbial communities, providing nutrient sources, and reducing nutrient losses. Finally, this paper illustrates the potential ecological risks of BC application on paddy fields, including the risks of inconclusive research results and secondary pollution. These shortcomings need to be addressed in future research to ensure the sustainability of BC application.
Conservation Tillage Improves Soil Quality and Crop Yield in Hungary
Authors: Kovács Gergő Péter , Simon Barbara , Balla István , Bozóki Boglárka , Dekemati Igor , Gyuricza Csaba , Percze Attila , Birkás Márta
Published: March 2023

This paper provides an overview of the progress of tillage in Hungary. The local and international impacts on the national practice are summarized, and some adoption of the conservation tillage results is presented concerning Hungary. The interest in conservation agriculture in Hungary dates back almost 120 years; however, any significant changes only occurred in the last 50 years. Interestingly, the factors of progress and restraint in tillage have appeared simultaneously over the years. Among the factors restraining tillage progress, the most retarding were the beliefs that have existed for many decades, as soil conservation was not considered nor was the need to mitigate climate-related hazards. Progress was driven by the commitment to soil protection, the opportunity to raise farming standards, and the need to mitigate climate-related threats. Since the average yield in Hungary was usually sufficient for the domestic need, the main objective of crop production was to avoid yield loss. Long-term experimental data and monitoring results were considered for this study. The impacts of new tillage solutions, elaborated in foreign countries, on tillage modernization were reviewed. The experiences and first results in no-till (direct drilling) and strip-tillage showed that difficulties can gradually be reduced through site-specific technology solutions. The need for subsoiling is not a matter of debate nowadays but rather the timing of operation and the investigation of the duration of the effects. Due to its complex advantages, tine tillage occupies an increasing rank among soil conservation systems. The area of ploughed soils has decreased; however, improved implementation is required.
Accurate Detection Algorithm of Citrus Psyllid Using the YOLOv5s-BC Model
Authors: Lyu Shilei , Ke Zunbai , Li Zhen , Xie Jiaxing , Zhou Xu , Liu Yuanyuan
Published: March 2023

Citrus psyllid is the main vector of Huanglongbing, and as such, it is responsible for huge economic losses across the citrus industry. The small size of this pest, difficulties in data acquisition, and the lack of target detection algorithms suitable for complex occlusion environments inhibit detection of the pest. The present paper describes the construction of a standard sample database of citrus psyllid in multi-focal lengths and out-of-focus states in the natural environment. By integrating the attention mechanism and optimizing the key module of BottleneckCSP, YOLOv5s-BC, we have created an accurate detection algorithm for small targets. Based on YOLOv5s, our algorithm incorporates an SE-Net channel attention module into the Backbone network and improves the detection of small targets by guiding the algorithm to the channel characteristics of small-target information. At the same time, the BottleneckCSP module in the neck network is improved, and extraction of multiple features of recognition targets is improved by the addition of a normalization layer and SiLU activation function. Experimental results based on a standard sample database show the recognition accuracy (intersection over union (IoU) = 0.5) of the YOLOv5s-BC algorithm for citrus psyllid to be 93.43%, 2.41% higher than that of traditional YOLOv5s. The accuracy and recall rates are also increased by 1.31% and 4.22%, respectively. These results confirm that the YOLOv5s-BC algorithm has good generalization ability in the natural context of citrus orchards, and it offers a new approach for the control of citrus psyllid.