bluuebunny/crossref_metadata_2025 huggingface dataset:
Early supplementation with zinc proteinate does not change rectal microbiota but increases growth performance by improving antioxidant capacity and plasma zinc concentration in preweaned dairy calves
Authors: Liu Junhao , Yu Xin , Ma Fengtao , Wo Yeqianli , Jin Yuhang , Hashem Nesrein M. , Sun Peng
Published: September 2023

The present study evaluated the effects of early supplementation with zinc proteinate (ZnP) or zinc oxide (ZnO) for 2 weeks on the growth performance, redox status, plasma trace element concentrations, and rectal microbiota of preweaned dairy calves. A total of 60 newborn healthy female Holstein dairy calves, with initial body weight (BW): 41.33 ± 0.62 kg, were randomly allocated to 5 groups of 12 each: a control group (CON); three groups supplemented with 261 (L-ZnP), 523 (M-ZnP), and 784 (H-ZnP) mg/day ZnP, equivalent to 40, 80, and 120 mg/day zinc, respectively; and one group supplemented with 232 mg/day ZnO, equivalent to 180 mg/day zinc (ZnO). Zinc supplements were administered on days 1–14, and the calves were followed up until day 70. Zinc supplementation increased total dry matter intake (DMI) and starter DMI compared with the CON group (p < 0.01). The final BW, average daily gain, and feed efficiency were higher in the M-ZnP, H-ZnP, and ZnO groups (p < 0.05). The incidence of diarrhea on days 1–28 was reduced by zinc administration (p < 0.01), whereas the incidence on days 29–56 was lower in the M-ZnP and ZnO groups (p < 0.05). Serum glutathione peroxidase activity, total antioxidant capacity, immunoglobulin G and plasma zinc concentrations were increased linearly (p < 0.05), while the serum concentration of malondialdehyde was decreased linearly (p < 0.01), as the dose of ZnP increased. ZnP yielding 80 mg/day zinc had similar effects as ZnO yielding 180 mg/day zinc, except that final BW was higher in the ZnO group (p < 0.05). At the phylum level, ZnO decreased the relative abundance of Firmicutes while increasing the abundance of Bacteroidetes (p < 0.05). At the genus level, ZnO increased the relative abundances of Prevotella, Subdoligranulum, and Odoribacter (p < 0.05). These findings indicated that early supplementation with ZnP did not affect the rectal microbiota of preweaned dairy calves but increased their growth performance, antioxidant capacity, and plasma zinc concentration. In summary, ZnP is an organic zinc source with greater bioavailability than ZnO for preweaned dairy calves. Early dietary supplementation with ZnP yielding 80 mg/day zinc is recommended.
Intravenous lipid emulsion for the treatment of poisonings in 313 dogs and 100 cats (2016–2020)
Authors: Markert Carina , Heilmann Romy Monika , Kiwitz Dschaniena , Doerfelt René
Published: September 2023

Introduction

The aim of this retrospective study was to analyze the effect and potential adverse effects of intravenous lipid emulsion (ILE) in poisoned dogs and cats over a 5 years period.

Methods

Medical records of 313 dogs and 100 cats receiving ILE between 2016–2020 were analyzed for suspected toxicant, clinical signs, ILE dosages and frequency, the effect and adverse effects of ILE, and patient outcome.

Results

Dogs and cats were poisoned with mostly unidentified toxicants (48%), rodenticides (8%), recreational drugs and nuts (7% each) and other toxicants. Clinical signs included neurologic deficits (63%), cardiovascular signs (29%), thermoregulation (21%) or gastrointestinal abnormalities (17%). Treatment with ILE was initiated within a median of 6.0 h (1.0–91.0 h) after poisoning. Dogs and cats received a total amount of median 8.0 mL/kg (1.5–66.6 mL/kg) and 15.8 mL/kg (1.8–69.4 mL/kg) ILE, respectively. A positive effect was observed in 74% of the patients, whereas clinical signs worsened in 4% of the patients after ILE administration. No subjective effect was detected in 22% of the patients. Suspected or possible adverse effects of ILE occurred in 6% of the patients, including neurological signs (temporarily reduced consciousness and ataxia), bradycardia, hyperthermia, vomiting, diarrhea, respiratory distress, worsening of the general behavior, facial swelling, and thrombophlebitis. The overall survival rate was 96%. One dog who potentially experienced adverse events was euthanized.

Conclusion

ILE treatment was successful in most patients but can be associated with adverse effects. Administration of ILE should be carefully selected on an individual basis after weighing the possible benefits against potential adverse effects.
Determinants of Public Institutions Competitiveness: Case Study of the Republic of Moldova
Authors: Bîrcă Alic , Sandu Christiana Brigitte , Matveiciuc Igor
Published: September 2023

This study analyzes the determinant factors contributing to the competitiveness of public institutions. To reach the aim of the study, we have identified seven determinant factors: employee development, employee performance, organizational communication, work organization, digitalization of activities, reduction in bureaucracy, and strategic management. For each of the factors, we formulated 35 items that influence, to a higher or lower degree, the competitiveness of public institutions. To validate the results, we designed and applied a questionnaire to employees of public institutions. The study included 1042 individuals who provided valid responses. To process the data, the confirmatory factor analysis was performed using the STATA and SmartPLS software. The novelty of this study lies in the multidimensional analysis of the competitiveness of public institutions, carried out using multiple determinant factors. Our research findings could be used by decision-makers for enhancing institutional strategies designed to grow competitiveness.
Research on Cutting Angle Design Optimization of Rubber Cutter Based on Discrete Element Method
Authors: Zhang Heng , Wen Zhentuo , Chen Yaya , Liu Junxiao , Liu Hongxin , Zhang Zhifu , Zhang Xirui
Published: September 2023

This paper focuses on obtaining fundamental data for optimizing the design of intelligent equipment for cutting natural rubber and its key components. It uses natural rubber bark as the research subject and employs specific experimental apparatus to measure the physical properties and contact coefficients of the rubber bark. The discrete element method, along with the Hertz–Mindlin model featuring bonding contacts, are employed to create a discrete element model of natural rubber bark. Parameters are calibrated, and model validation is performed. Subsequently, a one-factor simulation test is conducted to assess various cutting angles of the rubber cutter knife. A secondary Fourier fitting is applied to fit the curve to the average shear force values obtained from the simulation. The results indicate that the lowest average shear force, at 84.345 N, occurs within the range of cutting angles between 25° and 30°. The corresponding optimal cutting angle is 29.294°, suggesting that cutting with low resistance can be achieved at this angle, leading to reduced power consumption. Following a statistical analysis of field rubber-cutting tests conducted in a forest setting, it was found that the average power consumption for rubber-cutting operations under the optimal cutting angle is 0.96 W·h. Additionally, the volume of rubber discharged in the initial 5 min period is 6.53 mL. These findings hold significant importance for guiding the optimization and enhancement of the design of intelligent equipment for cutting natural rubber and its key components.
Analysis of Influencing Factors on the Willingness and Behavioral Consistency of Chinese Consumers to Purchase Tea via E-Commerce Platforms
Authors: Xie Kexiao , Lin Dongkai , Zhu Weihan , Ma Yongqiang , Qiu Jiaxiong , Chen Youcheng , Chen Zhidan
Published: September 2023

Tea is a global economic crop. In the traditional sales model, the quality of tea is difficult to judge via external clues, and it basically relies on consumers to taste and experience it firsthand. However, currently, most e-commerce platforms can only provide consumers with product information and cannot provide experiential services, which strengthens consumers’ purchasing concerns and makes it difficult for them to take practical actions even if they have the desire to purchase tea online. Therefore, this article is based on a questionnaire survey of consumers in China, the world’s largest tea producing and selling country, using unordered multi classification logistic analysis data and calculating the marginal effect proportion of consistency occurrence. Through data analysis, it is shown that there is a serious inconsistency between consumers’ willingness and behavior in choosing online tea purchases. However, under the influence of some internal and external factors, there will also be positive changes; for example, the level of education, online shopping age, familiarity with tea, convenience, product diversification, online evaluation, and other variables will increase the motivation for consumers to convert their purchase intention into actual behavior. In addition, increasing the level of variables such as age, cultural association, cultural experience, convenience, information reliability, award-winning status, familiarity with tea, product diversity, online evaluation, and service attitude in online shopping can enhance consumers’ willingness to shop online and reduce extreme situations where there is neither intention nor behavior. This study provides evidence from a consumer perspective to enhance the efficiency of tea e-commerce marketing and proposes countermeasures and suggestions based on the research results, which could also provide ideas for marketing strategies for tea or other similar agricultural products.
Design and Implementation of Internet of Things (IoT) Platform Targeted for Smallholder Farmers: From Nepal Perspective
Authors: Lamsal Ritu Raj , Karthikeyan P. , Otero Pablo , Ariza Alfonso
Published: September 2023

Nepal, a lower-middle-income country in South Asia, predominantly features smallholder farming communities operating on modest land holdings. These smallholders often adhere to traditional farming methods, relying on familial labor, which has become increasingly inefficient in contemporary agricultural landscapes. To enhance their productivity and efficiency, smallholder farmers require affordable and accessible Internet of Things (IoT)-based systems. However, the prevailing IoT solutions in the market primarily cater to large-scale commercial enterprises, rendering them unsuitable for the specific needs and constraints faced by smallholder farmers. In response to this gap, we have introduced a cost-effective, customizable, scalable, and dependable IoT platform tailored expressly for smallholder farmers. This platform empowers them to visualize, monitor, and control real-time data pertaining to their crops, livestock, and other agricultural assets. To ascertain the efficacy and suitability of our proposed platform, we conducted a comparative analysis with existing counterparts such as Blynk IoT and ThingSpeak IoT, evaluating their respective features and application services against standard requirements. Additionally, we subjected our platform to rigorous server load testing, assessing crucial performance parameters including throughput, response time, user capacity, and data sampling rates. Over an observation period spanning an average of 339 days, our platform successfully processed and stored a substantial volume of data, encompassing 817,633 sensor messages, averaging 2412 messages per day, with a cumulative storage size of 14,238.28 KB. Extrapolating from these results, it is noteworthy that an A0 instance with 20 GB of cloud space can adequately accommodate 200 users at a rate of 100 MB per user, which is adequate for the smallholder needs. Furthermore, the purposed platform was deployed inside a polyhouse to perform off-season grafting of citrus plants. The achieved success rate of 84% closely approached the success rate of 90–95% observed during on-season grafting. These empirical findings, coupled with the extensive data gathered during our research, underscore the reliability and performance of our proposed IoT platform for smallholder farmers.
Soil Microbial Community Responses to Cyanobacteria versus Traditional Organic Fertilizers
Authors: Afkairin Antisar , Stromberger Mary , Storteboom Heather , Wickham Allison , Sterle David G. , Davis Jessica G.
Published: September 2023

This study explores the impact of diverse organic fertilizers, including a non-traditional cyanobacteria-based alternative, on soil microbial communities in varying soil types and depths. The research aims to elucidate the effects of these fertilizers on soil microorganisms in certified organic cucumber (Cucumis sativus) field and peach (Prunus persica) orchard settings. Fertilizers were applied either on the soil surface or banded 5 cm below the soil surface, and microbial ester-linked fatty acids (EL-FAMEs) were analyzed in collected soils. Notably, cyanobacteria and Neptune hydrolyzed fish emulsion fertilizers induced significant alterations in the microbial communities of cucumber plots, enhancing microbial biomass and favoring the proliferation of Gram-negative bacteria, Gram-positive bacteria, and actinomycetes compared to other treatments. In the peach orchard, fertilizer choice differentially impacted microbial communities, especially in the first year and at greater soil depths. Notably, the supplementation of poultry manure with cyanobacteria fertilizer resulted in augmented microbial biomass and relative fungal and arbuscular mycorrhizal fungal abundances compared to poultry manure alone. These shifts have promising implications for organic vegetable and fruit cultivation. The study further underscores the potential of cyanobacteria-based fertilizers to reduce reliance on traditional options and minimize manure application, promoting self-sufficiency and benefiting soil microorganisms, plant growth, and the ecosystem. Thus, the research emphasizes the importance of exploring and adopting cyanobacteria-based fertilizers to bolster sustainable agricultural practices.
Does Sodium Nitroprusside Alleviate Water Deficit Stress in Impatiens walleriana Shoots Grown In Vitro?
Authors: Đurić Marija , Trifunović-Momčilov Milana , Milošević Snežana , Marković Marija , Radulović Olga , Subotić Angelina , Uzelac Branka
Published: September 2023

Impatiens walleriana is a decorative horticultural plant species. Commercial production requires that the plants be brought to market, often accompanied by reduced water content during transport. Drought significantly affects metabolic processes in plants. The effects of polyethylene glycol (PEG)-induced water deficit on shoots of I. walleriana were investigated using different mechanisms at the biochemical level. In addition, the potential water deficit-ameliorating effect of sodium nitroprusside (SNP) was tested. Shoots of I. walleriana were initially grown on MS media supplemented with SNP (50, 100 and 250 μM). After pre-treatments, shoots were further transferred to media supplemented with PEG8000 (3%) and/or SNP (50, 100 and 250 μM). Water deficit conditions increased proline, photosynthetic pigments, malondialdehyde (MDA), H2O2, total phenolic content and antioxidant activity. In addition, PEG-induced water deficit increased superoxide dismutase (SOD) and peroxidase (POX) activities but decreased catalase (CAT) activity. SNP did not significantly affect photosynthetic pigments and total phenolic content but increased proline accumulation, MDA and H2O2 content, especially when applied simultaneously with PEG. Moreover, none of the investigated SNP pretreatments significantly altered the activities of SOD, POX, and CAT in I. walleriana. The results indicate that exogenous application of SNP effectively alleviated water deficit stress in shoots of I. walleriana grown in vitro.
Bedding Management for Suppressing Particulate Matter in Cage-Free Hen Houses
Authors: Bist Ramesh Bahadur , Regmi Prafulla , Karcher Darrin , Guo Yangyang , Singh Amit Kumar , Ritz Casey W. , Kim Woo Kyun , Jones Deana R. , Chai Lilong
Published: September 2023

Cage-free (CF) layer houses tend to have high particulate matter (PM) levels because of bedding/litter floor and the birds’ activities, such as perching, dustbathing, and foraging on it. It has been reported that optimizing bedding management can potentially suppress PM levels in CF houses. The objectives of this study were to (1) test the effect of the top application of new bedding materials (BMs) on PM levels and (2) compare different BM PM reduction efficiencies. Small flake shavings (SFS), large flake shavings (LFS), and aspen wood chips (AWC) were top-dressed on the surface of the original litter (33-week-old litter) evenly in each of the BM treatment rooms at 20% volume of the original litter floor. The initial litter depths in the control, SFS, LFS, and AWC rooms were 4.6 ± 0.6, 4.8 ± 0.8 cm, 4.8 ± 0.8 cm, and 4.6 ± 0.9 cm, respectively. One room was used as a control without adding new BM. The results indicate that the top application of new bedding suppressed PM levels in all treatment rooms (p < 0.01). The PM2.5 reductions in the SFS, AWC, and LFS treatment rooms were 36.5%, 34.6%, and 28.9% greater than in the control room, respectively. The mitigation efficiencies were different between PM sizes. For instance, PM2.5, PM10, and TSP in the SFS room were lower than in the control room by 36.5%, 39.4%, and 38.7%, respectively. For litter quality, the moisture content was 18.0 ± 2.8, 20.0 ± 3.1, 20.6 ± 2.4, and 19.7 ± 4.2% in the control, SFS, LFS, and AWC rooms, respectively. Treatment rooms with 20% new BM had 10% higher litter moisture than the control room. The findings of this study reveal that the top application of new bedding on old litter is a potential strategy for reducing PM generation in CF houses. Further studies are warranted, such as regarding the effect of different ratios of new bedding on PM reduction, cost analysis, and verification tests in commercial CF houses.
Comparison of System of Rice Intensification Applications and Alternatives in India: Agronomic, Economic, Environmental, Energy, and Other Effects
Authors: Kumar Rapolu Mahender , Chintalapati Padmavathi , Rathod Santosha , Vidhan Singh Tapeshwar , Kuchi Surekha , Mannava Prasad Babu B. B. , Latha Patharath Chandran , Somasekhar Nethi , Bandumula Nirmala , Madamsetty Srinivas Prasad , Prasad J. V. N. S. , Vijayakumar Shanmugam , Srinivas Dayyala , Sreedevi Banugu , Tuti Mangal Deep , Arun Melekote Nagabhushan , Sailaja Banda , Sundaram Raman Meenakshi
Published: September 2023

Initial evaluations of the System of Rice Intensification in India and elsewhere focused mainly on its impacts on yield and income, and usually covered just one or two seasons. Researchers at the ICAR-Indian Institute of Rice Research have conducted a more comprehensive evaluation of SRI methods over six years (six wet and six dry seasons), comparing them with three alternatives: modified, partially mechanized SRI (MSRI) to reduce labor requirements; direct-seeded rice (DSR) as an alternative method for growing rice; and conventional transplanting of rice with flooding of fields (CTF). Grain yield with SRI methods was found to be about 50% higher than with CTF (6.35 t ha−1 vs. 4.27 t ha−1), while the MSRI yield was essentially the same (6.34 t ha−1), 16% more than with DSR (5.45 t ha−1). Water productivity with SRI methods was 5.32–6.85 kg ha-mm−1, followed by 4.14–5.72 kg ha-mm−1 for MSRI, 5.06–5.11 kg ha-mm−1 for DSR, and 3.52–4.56 kg ha-mm−1 for CTF. In comparison with CTF, SRI methods significantly enhanced soil microbial populations over time: bacteria by 12%, fungi by 8%, and actinomycetes by 20%. Biological activity in the rhizosphere was also higher as indicated by 8.5% greater dehydrogenase and 16% more FDA enzymes in soil under SRI management. Similarly, an indicator of soil organic matter, glucosidase activity, was 78% higher compared to CTF. SRI enhanced the relative abundance of beneficial microbial-feeding nematodes by 7.5% compared to CTF, while that of plant-pathogenic nematodes was 7.5% lower under SRI. Relative to conventional methods, SRI management reduced GHG emissions by 21%, while DSR reduced them by 23%, and MSRI by 13%, compared to standard rice-growing practice. Economic analysis showed both gross and net economic returns to be higher with SRI than with the other management systems evaluated. While the six-year study documented many advantages of SRI crop management, it also showed that MSRI is a promising adaptation that provides similar benefits but with lower labor requirements.
Assessing PREDICTA®B as a Potential Disease Risk Management Decision Tool for Sorghum Charcoal Rot Based on Disease Levels, Lodging, and Associated Yield Loss
Authors: Adorada Dante L.
Published: September 2023

Charcoal rot, caused by Macrophomina phaseolina (Mp), is the most common and the most important root and stalk rot disease of sorghum. Survey data for sorghum charcoal rot disease and pathogen loads were analysed to assess the potential of PREDICTA®B as a disease risk management decision tool. The pathogen, at sowing and pre-harvest, was found to be strongly correlated. The results showed a strong quadratic relationship between the incidence of charcoal rot and the percent of lodging, supporting the notion that charcoal rot is one of the causative agents in sorghum lodging. An Mp load of 2.5 k copies per gram of soil on a log10 scale was established as an indicator of the high incidence of charcoal rot, and its associated risk of serious lodging can be used as a management decision tool. Rainfall and location were also shown to influence lodging rates. Some varieties of sorghum were found to be less susceptible to charcoal rot than others. This study found that disease incidence was a better predictor of damage than the disease rating index. As set by PREDICTA®B, at low or non-detectable levels of Mp, the risk of disease is low. With high levels of Mp, the incidence and severity of disease depend on the susceptibility of the variety and the conduciveness of the environment. High levels of Mp do not mean that disease will occur, but that there is a high risk if the conditions are favourable for disease development. While this study has provided much useful information, it has highlighted the need for further data collection to be able to develop reliable disease risk categories based on test results and its associated yield loss.
Optimizing Irrigation and Nitrogen Regimes in Rice Plants Can Contribute to Achieving Sustainable Rice Productivity
Authors: Gu Junfei
Published: September 2023

Ensuring Food security is increasingly challenging each year as the global population is projected to be 9 [...]
The Study of Structural Optimization on Hydraulic Performance and Anti-Clogging Performance of Labyrinth Drip Irrigation Emitters
Authors: Xu Tianyu , Bao Sanlin , Li Zonglei , Yu Qiuyue , Zheng Ennan
Published: September 2023

The core component of a properly functioning drip irrigation system is the drip irrigation emitter. Irrigation water containing impurities and sand particles can easily lead to clogging of the drip irrigation emitter, reducing the efficiency of the drip irrigation system. In this paper, orthogonal tests were used to optimize the flow channel structure, combined with the computational fluid dynamics–discrete element method (CFD-DEM) to analyze the flow index and sand particle motion characteristics. Clear water tests and short-cycle anticlogging tests were used to validate the results of the numerical simulation, and the relationship between the hydraulic performance and anti-clogging performance was revealed via linear regression. The results showed that the structural parameters of drip irrigation emitters were important factors affecting the flow index and sand movement characteristics. The order from largest to smallest was the turning angle, amount of interdental reference, flow channel depth, flow channel width, and width of the top base. The sand passage rate and the percentage decrease in velocity can be used as important indicators of anti-clogging performance, and there was a negative correlation between the two indicators. The flow channel with a 65° turning angle had the lowest flow index, and the sand passage rate can reach up to 91.48%; the reason was that the main flow region velocity was higher, the vortex region and the sand energy loss were small, which was not easy to clog. The equation for the relationship between flow index and sand passage rate was a negative correlation for drip irrigation emitters between a 65° and 75° turning angle. The drip irrigation emitter with a 65° turning angle had better hydraulic performance and anti-clogging performance.
Comparative Analysis of Different UAV Swarm Control Methods on Unmanned Farms
Authors: Ming Rui , Jiang Rui , Luo Haibo , Lai Taotao , Guo Ente , Zhou Zhiyan
Published: September 2023

Unmanned farms employ a variety of sensors, automated systems, and data analysis techniques to enable fully automated and intelligent management. This not only heightens agricultural production efficiency but also reduces the costs associated with human resources. As integral components of unmanned farms’ automation systems, agricultural UAVs have been widely adopted across various operational stages due to their precision, high efficiency, environmental sustainability, and simplicity of operation. However, present-day technological advancement levels and relevant policy regulations pose significant restrictions on UAVs in terms of payload and endurance, leading to diminished task efficiency when a single UAV is deployed over large areas. Accordingly, this paper aggregates and analyzes research pertaining to UAV swarms from databases such as Google Scholar, ScienceDirect, Scopus, IEEE Xplorer, and Wiley over the past decade. An initial overview presents the current control methods for UAV swarms, incorporating a summary and analysis of the features, merits, and drawbacks of diverse control techniques. Subsequently, drawing from the four main stages of agricultural production (cultivation, planting, management, and harvesting), we evaluate the application of UAV swarms in each stage and provide an overview of the most advanced UAV swarm technologies utilized therein. Finally, we scrutinize and analyze the challenges and concerns associated with UAV swarm applications on unmanned farms and provide forward-looking insights into the future developmental trajectory of UAV swarm technology in unmanned farming, with the objective of bolstering swarm performance, scalability, and adoption rates in such settings.
Diversity Analysis and Biocontrol Potential of Cultivatable Terrestrial Bacterial Streptomyces in Southern China
Authors: Zhou Lifeng , Pei Fan , Pu Wangling , Zhang Chuang , Chen Fei , Hu Yuechen , Chen Jie , Lin Haiping , Zhou Xudong
Published: September 2023

Streptomyces are filamentous bacteria that are extensively present in soil, play an important role in carbon cycling, and produce a large number of highly valuable secondary metabolites. In this study, total number of 411 isolates of Streptomyces were collected from ecologically similar habitats from 13 provinces in Southern China. They were clustered into 96 operational taxonomic units including eight potentially new species based on their 16S rDNA sequences. Phylogenetic analysis disclosed that the isolates with similar geographical distributions clustered together. Beta diversity of Streptomyces showed it manifests in a latitudinal diversity gradient (R2 = 0.3828, p = 0.0113). The beta diversity did not change significantly with geographic distance, and this could be due to the large longitudinal and relatively smaller latitudinal sampling range, as the phylogenetic clustering of regions with higher annual average temperature was analyzed with the nearest taxon index (R = −0.23, p = 0.045). Result of the Streptomyces biogeography evaluation shows the diversity of the genus is controlled by many of the same processes. Bioassay results disclosed that there were 27 isolates strongly antagonistic to plant pathogenic fungi and 71 isolates with strong nematocidal activity against pine wood nematode. Our results provide significant insights into the diversity and biocontrol potential of cultivatable Streptomyces in Southern China.
Reduction in N2O Emissions and Improvement in Nitrifier and Denitrifier Communities through Bamboo-Biochar-Based Fertilization in Pomelo Orchard Soil
Authors: Li Qinghua , Zhao Lin , Wang Fei , Chen Hongmei , Qian Xiaojie
Published: September 2023

Farmland soil is an important source of the greenhouse gas nitrous oxide (N2O), and soil nitrification and denitrification are key processes affecting N2O production. In this study, the acidic soil of a pomelo orchard was used to investigate the effects of a bamboo-biochar-based fertilizer (BB) on soil N2O emissions and nitrifier and denitrifier communities. In this study, five treatments, namely, CK (no urea and BB), N (0.72 g·kg−1 urea), 5BB+N (0.72 g·kg−1 urea plus 5 g·kg−1 BB), 10BB+N (0.72 g·kg−1 urea plus 10 g·kg−1 BB), and 20BB+N (0.72 g·kg−1 urea plus 20 g·kg−1 BB) were applied to the acidic soil of a pomelo orchard. The nitrification (AOA-amoA, AOB-amoA) and denitrification (nirS, nirK, nosZ) gene copy numbers were analyzed by qPCR, and their community diversities were determined by Illumina MiSeq sequencing. The results showed that N treatment significantly promoted soil N2O emissions compared with CK, while all BB+N treatments significantly inhibited soil N2O emissions compared with N treatment. BB fertilizer promoted soil nitrification, alleviated the adverse effects from N fertilizer inputs on the AOA-amoA gene copy numbers and community diversity, and restored the AOA-amoA diversity to the initial level. BB had a strong effect on Crenarchaeota (AOA-amoA) and Nitrosospira (AOB-amoA). BB significantly promoted the denitrification gene copy numbers; increased nirS and nirK community diversity; particularly affected the relative abundance of denitrifiers such as Nonomuraea (nirS), Proteobacteria (nirK), and Rhodanobacter (nosZ); and, finally, reduced N2O emissions.
Wing Shape Variation between Terrestrial and Coastal Populations of the Invasive Box Tree Moth, Cydalima perspectalis, in Croatia
Authors: Lemic Darija , Viric Gasparic Helena , Majcenic Patricija , Pajač Živković Ivana , Bjeliš Mario , Suazo Manuel J. , Correa Margarita , Hernández Jordan , Benítez Hugo A.
Published: September 2023

The box tree moth (Cydalima perspectalis Walker, 1859; Lepidoptera: Crambidae) is an invasive species naturally distributed in Asia. The caterpillars in all developmental stages cause damage through defoliation of plants, and ultimately the death of the plant itself may occur. It is possible to recognize this species by its silk barriers and threads, and in the case of an intense attack, the entire plant will be covered with them. In Europe, this species’ presence was first recorded in 2007 in Germany and the Netherlands, and it is now widely distributed. In Croatia, its existence was first recorded in 2012, in Istria, while substantial damages were recorded in 2013. This work aimed to determine the morphological variability of C. perspectalis from Croatia and assess its invasive character, the possibility of flight, and the risk of further spread. The methods of geometric morphometrics were used as the analysis of wing shape. A total of 269 moths from different locations in Croatia were collected, the upper wings of males and females were analyzed using 14 landmarks. Significant differences in wing shapes between terrestrial and coastal populations were found, as well as subtle wing shape sexual dimorphism. The implications of this variability in species invasiveness and capacity of spread are discussed in this paper. We also extrapolate the usefulness of our results and suggest strategies for predicting and managing invasive species.
Mucormycosis in a Severe Trauma Patient Treated with a Combination of Systemic Posaconazole and Topical Amphotericin B—Case Report
Authors: Keller Filip , Antoni Helena , Minarcikova Petra , Hrdy Ondrej , Gal Roman
Published: September 2023

Mucormycosis is an opportunistic infection affecting mainly immunocompromised hosts. Infection in immunocompetent patients is rare, but may occur typically in trauma or burn victims. We report on a previously healthy young man suffering devastating trauma from an agricultural accident with the subsequent development of a multifocal mucormycosis. Diagnosis was achieved by cultures obtained from non-healing wounds, some of them even covered by a macroscopic mold formation. Specific treatment was initiated soon after the preliminary results indicated mucormycosis. Aggressive surgical therapy, with concomitant use of systemic posaconazole and topical amphotericin B in a combination treatment, led to the elimination of the fungal infection. The remaining deep tissue defects were consequently reconstructed by a muscle flap and skin graft autotransplantation with a good overall outcome, which would not have been possible without the complete remission of mucormycosis. This case study presents the successful use of a combination treatment with systemic posaconazole and topical amphotericin B and underlines the importance of timely and aggressive surgical therapy.
Boswellia Essential Oil: Natural Antioxidant as an Effective Antimicrobial and Anti-Inflammatory Agent
Authors: Obiștioiu Diana , Hulea Anca , Cocan Ileana , Alexa Ersilia , Negrea Monica , Popescu Iuliana , Herman Viorel , Imbrea Ilinca Merima , Heghedus-Mindru Gabriel , Suleiman Mukhtar Adeiza , Radulov Isidora , Imbrea Florin
Published: September 2023

The research aimed to determine the chemical composition, the antioxidant and anti-inflammatory activity as well as the antimicrobial activity against Gram-positive, Gram-negative and two fungal Candida ATCC strains of a commercial Boswellia essential oil (BEO) containing Boswellia carteri, Boswellia sacra, Boswellia papryfera, and Boswellia frereana. Additionally, molecular docking was carried out to show the molecular dynamics of the compounds identified from the essential oil against three bacterial protein targets and one fungal protein target. The major components identified by GC-MS (Gas Chromatography-Mass Spectrometry) were represented by α-pinene, followed by limonene. Evaluation of antioxidant activity using the DPPH (2,2-Diphenyl-1-Picrylhydrazyl) method showed high inhibition comparable to the synthetic antioxidant used as a control. Oxidative stability evaluation showed that BEO has the potential to inhibit primary and secondary oxidation products with almost the same efficacy as butylated hydroxyanisole (BHA). The use of BEO at a concentration of 500 ppm provided the best protection against secondary oxidation during 30 days of storage at room temperature, which was also evident in the peroxide value. Regarding the in vitro anti-inflammatory activity, the membrane lysis assay and the protein denaturation test revealed that even if the value of protection was lower than the value registered in the case of dexamethasone, the recommendation of using BEO as a protective agent stands, considering the lower side effects. Gram-positive bacteria proved more sensitive, while Pseudomonas aeruginosa presented different sensitivity, with higher MICs (minimal inhibitory concentration). Haemophilus influenzae demonstrated a MIC at 2% but with consecutive inhibitory values in a negative correlation with the increase in concentration, in contrast to E. coli, which demonstrated low inhibitory rates at high concentrations of BEO. The computational tools employed revealed interesting binding energies with compounds having low abundance. The interaction of these compounds and the proteins (tyrosyl-tRNA synthetase, DNA gyrase, peptide deformylase, 1,3-β-glucan synthase) predicts hydrogen bonds with amino acid residues, which are reported in the active sites of the proteins. Even so, compounds with low abundance in BEO could render the desired bioactive properties to the overall function of the oil sustained by physical factors such as storage and temperature. Interestingly, the findings from this study demonstrated the antioxidant and antimicrobial potential of Boswellia essential oil against food-related pathogens, thus making the oil a good candidate for usage in food, feed or food-safety-related products.
Antioxidant Polyphenols from Lespedeza bicolor Turcz. Honey: Anti-Inflammatory Effects on Lipopolysaccharide-Treated RAW 264.7 Macrophages
Authors: Ren Caijun , Li Qiangqiang , Luo Teng , Betti Mirko , Wang Miao , Qi Suzhen , Wu Liming , Zhao Liuwei
Published: September 2023

Although the honey produced by Lespedeza bicolor Turcz. is precious because of its medicinal value, its pharmacological mechanism is still unclear. Here, its anti-inflammatory and antioxidant functions on lipopolysaccharide (LPS)-treated murine RAW 264.7 macrophages were analyzed using targeted and non-targeted metabolomics. Results showed that twelve polyphenols were identified in L. bicolor honey using UHPLC-QQQ-MS/MS. L. bicolor honey extract could scavenge the free radicals DPPH• and ABTS+ and reduce Fe3+. Furthermore, pretreatment with L. bicolor honey extract significantly decreased NO production; suppressed the expression of COX-2, IL-10, TNF-α, and iNOS; and upregulated HO-1′s expression in the cells with LPS application. UHPLC-Q-TOF-MS/MS-based metabolomics results revealed that L. bicolor honey extract could protect against inflammatory damage caused by LPS through the reduced activation of sphingolipid metabolism and necroptosis pathways. These findings demonstrate that L. bicolor honey possesses excellent antioxidant and anti-inflammatory activities.
Bridging the Gap between Purpose-Driven Frameworks and Artificial General Intelligence
Authors: Duan Yucong
Published: September 2023

Artificial General Intelligence (AGI) has leaped forward in capabilities, offering applications that reach far beyond conventional machine learning systems [...]
Limit Equilibrium Models for Tunnel Face Stability in Composite Soft-Hard Strata
Authors: Zhang Xiao , Song Qilong , Yao Zhanhu , Su Dong , Zhang Yazhou , Li Qiang
Published: September 2023

The tunnel face stability in composite strata, commonly referred to as the soft upper and hard lower condition, is a critical challenge in tunnel construction. The soft–hard ratio (SA) strongly influences the limit support pressure as well as the failure mechanism experienced by a tunnel face. This study focused on the Xingye Tunnel project in the Xiangzhou District of Zhuhai City. By conducting numerical simulations, the impact of different SAs on the limit support pressure was investigated. Furthermore, a limit equilibrium model was established on the basis of the analysis of the results of numerical simulation. The findings were then compared and analyzed alongside those of relevant theoretical models. In the event of tunnel face instability of composite strata, the deformation tends to be concentrated mainly in the soft soil layer, with less noticeable deformation in the hard rock layer. The investigation of different SAs revealed a linear decrease in the limit support pressure ratio of the tunnel face in composite strata as SA decreases. The self-stability of the tunnel face was observed when SA ≤ 0.125. Moreover, the limit support pressure ratio predicted by the truncated log-spiral model (TLSM) exhibited a higher degree of agreement with the results of numerical simulation than those of other relevant models. The superiority of TLSM was mainly demonstrated in the range of SA = 0.25 to 1.0.
DDI-SSL: Drug–Drug Interaction Prediction Based on Substructure Signature Learning
Authors: Liang Yuan
Published: September 2023

Drug–drug interactions (DDIs) are entities composed of different chemical substructures (functional groups). In existing methods that predict drug–drug interactions based on the usage of substructures, each node is perceived as the epicenter of a sub-pattern, and adjacent nodes eventually become centers of similar substructures, resulting in redundancy. Furthermore, the significant differences in structure and properties among compounds can lead to unrelated pairings, making it difficult to integrate information. This heterogeneity negatively affects the prediction results. In response to these challenges, we propose a drug–drug interaction prediction method based on substructure signature learning (DDI-SSL). This method extracts useful information from local subgraphs surrounding drugs and effectively utilizes substructures to assist in predicting drug side effects. Additionally, a deep clustering algorithm is used to aggregate similar substructures, allowing any individual subgraph to be reconstructed using this set of global signatures. Furthermore, we developed a layer-independent collaborative attention mechanism to model the mutual influence between drugs, generating signal strength scores for each class of drugs to mitigate noise caused by heterogeneity. Finally, we evaluated DDI-SSL on a comprehensive dataset and demonstrated improved performance in DDI prediction compared to state-of-the-art methods.
Special Issue on the Geo-Environmental Problems Caused by Underground Construction
Authors: Bai Bing
Published: September 2023

Geo-environmental disturbances refer to the significant changes in physical, mechanical, and even chemical properties of soils; are closely related to interrelated multi-physical field coupling systems of solid particles, water, and gas in the shallow stratum; and are caused by underground engineering construction [...]
Breast Cancer Prediction Based on Differential Privacy and Logistic Regression Optimization Model
Authors: Chen Hua , Wang Nan , Zhou Yuan , Mei Kehui , Tang Mengdi , Cai Guangxing
Published: September 2023

In order to improve the classification effect of the logistic regression (LR) model for breast cancer prediction, a new hybrid feature selection method is proposed to process the data, using the Pearson correlation test and the iterative random forest algorithm based on out-of-bag estimation (RF-OOB) to screen the optimal 17 features as inputs to the model. Secondly, the LR is optimized using the batch gradient descent (BGD-LR) algorithm to train the loss function of the model to minimize the loss. In order to protect the privacy of breast cancer patients, a differential privacy protection technology is added to the BGD-LR model, and an LR optimization model based on differential privacy with batch gradient descent (BDP-LR) is constructed. Finally, experiments are carried out on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. Meanwhile, accuracy, precision, recall, and F1-score are selected as the four main evaluation indicators. Moreover, the hyperparameters of each model are determined by the grid search method and the cross-validation method. The experimental results show that after hybrid feature selection, the optimal results of the four main evaluation indicators of the BGD-LR model are 0.9912, 1, 0.9886, and 0.9943, in which the accuracy, recall, and F1-scores are increased by 2.63%, 3.41%, and 1.76%, respectively. For the BDP-LR model, when the privacy budget ε is taken as 0.8, the classification performance and privacy protection effect of the model reach an effective balance. At the same time, the four main evaluation indicators of the model are 0.9721, 0.9975, 0.9664, and 0.9816, which are improved by 1.58%, 0.26%, 1.81%, and 1.07%, respectively. Comparative analysis shows that the models of BGD-LR and BDP-LR constructed in this paper perform better than other classification models.
Smart Education Systems Supported by ICT and AI
Authors: Aberšek Boris , Flogie Andrej
Published: September 2023

Contemporary society, the society of the future (Industry 4 [...]
AI Enhancements for Linguistic E-Learning System
Authors: Liu Jueting , Li Sicheng , Ren Chang , Lyu Yibo , Xu Tingting , Wang Zehua , Chen Wei
Published: September 2023

E-learning systems have been considerably developed after the COVID-19 pandemic. In our previous work, we developed a linguistic interactive E-learning system for phonetic transcription learning. In this paper, we propose three artificial-intelligence-based enhancements to this system from different aspects. Compared with the original system, the first enhancement is a disordered speech classification module; this module is driven by the MFCC-CNN model, which aims to distinguish disordered speech and nondisordered speech. The accuracy of the classification is about 83%. The second enhancement is a grapheme-to-phoneme converter. This converter is based on the transformer model and designed for teachers to better generate IPA words from the regular written text. Compared with other G2P models, our transformer-based G2P model provides outstanding PER and WER performance. The last part of this paper focuses on a Tacotron2-based IPA-to-speech synthesis system, this deep learning-based TTS system can help teacher generate high-quality speech sounds from IPA characters which significantly improve the functionality of our original system. All of these three enhancements are related to the phonetic transcription process. and this work not only provides a better experience for the users of this system but also explores the utilization of artificial intelligence technologies in the E-learning field and linguistic field.
Improving Low-Resource Chinese Named Entity Recognition Using Bidirectional Encoder Representation from Transformers and Lexicon Adapter
Authors: Dang Xiaochao , Wang Li , Dong Xiaohui , Li Fenfang , Deng Han
Published: September 2023

Due to their individual advantages, the integration of lexicon information and pre-trained models like BERT has been widely adopted in Chinese sequence labeling tasks. However, given their high demand for training data, efforts have been made to enhance their performance in low-resource scenarios. Currently, certain specialized domains, such as agriculture, the industrial sector, and the metallurgical industry, suffer from a scarcity of data. Consequently, there is a dearth of effective models for entity relationship recognition when faced with limited data availability. Inspired by this, we constructed a suitable small balanced dataset and proposed a based-domain-NER model. Firstly, we construct a domain-specific dictionary based on mine hoist equipment and fault text and generate a dictionary tree to obtain word vector information. Secondly, we use a Lexicon Adapter to obtain the vector information of the domain-specific dictionary feature words matched using the characters and calculate the weights between their word vectors, integrating position encoding to enhance the positional information of the word vectors. Finally, we incorporate word vector information into the feature extraction layer to enhance the boundary information of domain entities and mitigate the semantic loss problem caused via using only character feature representation. Experimental results on a manually annotated dataset of mine hoist fault texts show that this method outperforms BiLSTM, BiLSTM-CRF, BERT, BERT-BiLSTM-CRF, and LEBERT, effectively improving the accuracy of named entity recognition (NER) for mine hoist faults.