bluuebunny/crossref_metadata_2025 huggingface dataset:
Rhizospheric Bacillus spp. Exhibit Miticidal Efficacy against Oligonychus coffeae (Acari: Tetranychidae) of Tea
Authors: Bora Popy , Gogoi Sukanya , Deshpande Mukund Vinayak , Garg Pankaj , Bhuyan Rana P. , Altaf Nilofar , Saha Nikita , Borah Sapna Mayuri , Phukon Mousumi , Tanti Nabajit , Saikia Bishal , Ahmed Shenaz Sultana , Borah Sanjib Ranjan , Dutta Ashish , Sarmah Bidyut Kumar
Published: November 2023

Oligonychus coffeae (Acari: Tetranychidae), popularly known as red spider mite (RSM) is one of the major pests of commercial tea (Camellia sinensis (L.) O. Kuntze) plantation world over. Many attempts have been made in the past to control this devastating pest using a variety of microbial bioagents, however, area-wise field success is very limited. We carried out an in vitro study to explore the potential of rhizospheric Bacillus spp. (B. amyloliquefaciens BAC1, B. subtilis LB22, and B. velezensis AB22) against O. coffeae through adulticidal and ovicidal activity. The 100% adult and egg mortality was observed with bacterial suspension (1 × 109 CFU/mL) by B. velezensis AB22, showing the lowest LC50 values for both adults and eggs of O. coffeae, i.e., 0.28 × 105 and 0.29 × 105, respectively. The study also throws some insights into the underlying mechanism through electron microscopy study and identification of some putative pesticidal metabolites from all the species. The three Bacillus species were observed to have four commonly secreted putative bioactive secondary metabolites, brevianamide A, heptadecanoic acid, thiolutin, and versimide responsible for their bio-efficacy against O. coffeae. The outcome of our study provides a strong possibility of introducing Bacillus spp. as a biological miticide and developing synthetic metabolites mimicking the mechanistic pathway involved in microbial bioefficacy.
Association of Gut Microbiota with Age-Related Macular Degeneration and Glaucoma: A Bidirectional Mendelian Randomization Study
Authors: Li Chen , Lu Peirong
Published: November 2023

The objective of this study was to examine the correlation between gut microbiota and both age-related macular degeneration (AMD) and glaucoma. Mendelian randomization studies were conducted utilizing the data sourced from the genome-wide association study (GWAS) database for the gut microbiome, AMD, and glaucoma. Single nucleotide polymorphism (SNP) estimates were summarized through five Mendelian randomization (MR) methods. We utilized Cochran’s Q statistic to evaluate the heterogeneity of the instrumental variables (IVs). Additionally, we employed a “leave-one-out” approach to verify the stability of our findings. Inverse variance weighted (IVW) suggests that Eubacterium (oxidoreducens group) and Parabacteroides had a protective effect on AMD. Both weighted median and IVW suggest that Lachnospiraceae (NK4A136 group) and Ruminococcaceae (UCG009) had a protective effect on AMD. However, both weighted median and IVW suggest that Dorea had a risk effect on AMD. Similarly, The IVW of Eubacterium (ventriosum group) showed a risk effect on AMD. The weighted median of Eubacterium (nodatum group), Lachnospiraceae (NC2004 group), and Roseburia had a risk effect on glaucoma. IVW suggested that Ruminococcaceae (UCG004) had a risk effect on glaucoma. Reverse MR analysis found a causal link between Eubacterium (nodatum group) and glaucoma. No causal relationships were found between AMD or glaucoma and the other mentioned bacterial groups. No significant heterogeneity or evidence of horizontal pleiotropy was detected. This study found that certain gut bacteria had protective effects on AMD, while others may be risk factors for AMD or glaucoma. Likewise, reverse MR found that glaucoma led to an increased abundance of certain gut bacteria. Further trials are needed to clarify the specific mechanisms involved.
The Heat about Cultured Meat in Poland: A Cross-Sectional Acceptance Study
Authors: Sikora Dominika , Rzymski Piotr
Published: November 2023

Cultured meat, produced by culturing animal cells in vitro, is gaining increasing interest. The first products obtained using this technology were authorized for human consumption in Singapore and the United States, and more are likely to follow in other parts of the world. Therefore, it is important to assess the attitudes toward such meat in various populations and understand the grounds for its acceptance and rejection. The present cross-sectional online study of adult Poles (n = 1553) aimed to evaluate knowledge of cultured meat, the main reasons and fears associated with its production and consumption, and willingness to buy it and factors influencing such willingness. Most respondents (63%) were familiar with the concept of cultured meat, and 54% declared to purchase it when available. However, concerns over safety were expressed by individuals accepting (39%) and rejecting (49%) such meat. The main motivations for choosing it included limiting animal suffering (76%) and environmental impacts of meat consumption (67%), although over half of responders willing to buy these products were driven by curiosity (58%). Multiple logistic regression revealed that odds (OR; 95%CI) for accepting cultured meat were significantly increased for adults aged 18–40 (1.8; 1.2–2.7); women (1.8; 1.2–2.7); meat eaters (8.7; 5.6–13.6); individuals convinced that animal farming adversely affects the climate (7.6; 3.1–18.3), surface waters (3.1; 1.2–8.1), and air quality (3.0; 1.2–7.6); those familiar with cultured meat concept (4.2, 2.2–8.4); and those revealing high openness to experience (1.7; 1.2–2.4). The results highlight that the Polish population may be moderately ready to accept cultured meat and identify the groups resistant to accepting it. Well-designed and transparent promotion of these products is required to increase the general public’s understanding of the potential benefits and challenges of cultured meat technology.
Adherence to Vitamin D Supplementation during Infancy—A Single Pediatric Primary Practice Retrospective Study
Authors: Vucak Jerko , Matijevic Jeronim , Pivac Ivan , Markic Josko
Published: November 2023

The risk of vitamin D deficiency is high in infants. Therefore, potential vitamin D deficiency should be prophylactically treated with vitamin D supplementation. Achieving good adherence to recommended prophylactic regimens is the goal of every primary pediatrician. The aim of this paper was to establish whether Croatian infants receive recommended prophylactic doses of vitamin D regularly. We analyzed the prescription rate of vitamin D preparation during the first year of life in one pediatric primary practice. Our research has shown, for the first time in Croatia, that there is low treatment adherence. Only 7.6% of infants received the recommended doses of vitamin D. The percentage of infants in the moderately irregular adherence group was 19.3%. There was no statistical difference regarding urban or rural place of living or parents’ educational level. Based on these findings, a comprehensive public health campaign is needed to improve adherence to vitamin D supplementation during infancy. Also, further studies on larger samples and on a national level are warranted.
Novel Coumarin Derivatives as Potential Urease Inhibitors for Kidney Stone Prevention and Antiulcer Therapy: From Synthesis to In Vivo Evaluation
Authors: Shahzadi Kiran , Bukhari Syed Majid , Zaidi Asma , Wani Tanveer A. , Jan Muhammad Saeed , Zargar Seema , Rashid Umer , Farooq Umar , Khushal Aneela , Khan Sara
Published: November 2023

The presence of ammonium ions in urine, along with basic pH in the presence of urease-producing bacteria, promotes the production of struvite stones. This causes renal malfunction, which is manifested by symptoms such as fever, nausea, vomiting, and blood in the urine. The involvement of urease in stone formation makes it a good target for finding urease enzyme inhibitors, which have the potential to be developed as lead drugs against kidney stones in the future. The documented ethnopharmacology of coumarin 2-one against bacterial, fungal and viral strains encouraged us to synthesize new derivatives of coumarins by reacting aromatic aldehydes with 4-aminocoumarin. The synthesized compounds (2a to 11a) were evaluated for their antimicrobial, in vitro, and in silico properties against the urease enzyme. The study also covers in vivo determination of the synthesized compounds with respect to different types of induced ulcers. The molecular docking study along with extended MD simulations (100 ns each) and MMPBSA study confirmed the potential inhibitory candidates as evident from computed ∆Gbind (3a = −11.62 and 5a = −12.08 Kcal/mol) against the urease enzyme. The in silico analyses were augmented by an enzymatic assay, which revealed that compounds 3a and 5a had strong inhibitory action, with IC50 of 0.412 µM (64.0% inhibition) and 0.322 µM (77.7% inhibition), respectively, compared to standard (Thiourea) with 82% inhibition at 0.14 µM. Moreover, the most active compound, 5a, was further tested in vivo for antiulcer activity by different types of induced ulcers, including pyloric ligation-, ethanol-, aspirin-, and histamine-induced ulcers. Compound 5a effectively reduced gastric acidity, lipid peroxidation, and ulceration in a rat model while also inhibiting gastric ATPase activity, which makes it a promising candidate for ulcer treatment. As a result of the current research, 3a and 5a may be used as new molecules for developing potent urease inhibitors. Additionally, the compound 3a showed antibacterial activity against Staphylococcus aureus and Salmonella typhimurium, with zones of inhibition of 41 ± 0.9 mm and 35 ± 0.9 mm, respectively. Compound 7a showed antibacterial activity against Staphylococcus aureus and Salmonella typhimurium, with zones of inhibition of 30 ± 0.8 mm and 42 ± 0.8 mm, respectively. These results prove that the synthesized compounds also possess good antibacterial potential against Gram-positive and Gram-negative bacterial strains.
Integrated Assessment of Pb(II) and Cu(II) Metal Ion Phytotoxicity on Medicago sativa L., Triticum aestivum L., and Zea mays L. Plants: Insights into Germination Inhibition, Seedling Development, and Ecosystem Health
Authors: Vasilachi-Mitoseru Ionela-Catalina , Stoleru Vasile , Gavrilescu Maria
Published: November 2023

Environmental pollution with heavy metals has become a problem of major interest due to the harmful effects of metal ions that constantly evolve and generate serious threats to both the environment and human health through the food chain. Recognizing the imperative need for toxicological assessments, this study revolves around elucidating the effects of Pb(II) and Cu(II) ions on three plant species; namely, Medicago sativa L., Triticum aestivum L., and Zea mays L. These particular species were selected due to their suitability for controlled laboratory cultivation, their potential resistance to heavy metal exposure, and their potential contributions to phytoremediation strategies. The comprehensive phytotoxicity assessments conducted covered a spectrum of critical parameters, encompassing germination inhibition, seedling development, and broader considerations regarding ecosystem health. The key metrics under scrutiny included the germination rate, the relative growth of root and stem lengths, the growth inhibition index, and the tolerance index. These accurately designed experiments involved subjecting the seeds of these plants to an array of concentrations of PbCl2 and CuCl2 solutions, enabling an exhaustive evaluation of the phytotoxic potential of these metal ions and their intricate repercussions on these plant species. Overall, this study provides valuable insights into the diverse and dynamic responses of different plant species to Pb(II) and Cu(II) metal ions, shedding light on their adaptability and resilience in metal-contaminated environments. These findings have important implications for understanding plant–metal interactions and devising phytoremediation strategies in contaminated ecosystems.
Smart Indicator Film Based on Sodium Alginate/Polyvinyl Alcohol/TiO2 Containing Purple Garlic Peel Extract for Visual Monitoring of Beef Freshness
Authors: Jiang Kai , Li Jiang , Brennan Margaret , Brennan Charles , Chen Haiyan , Qin Yuyue , Yuan Mingwei
Published: November 2023

The aim of this study was to prepare a novel pH-sensitive smart film based on the addition of purple garlic peel extract (PGE) and TiO2 nanoparticles in a sodium alginate (SA)/polyvinyl alcohol (PVA) matrix to monitor the freshness of beef. FT-IR spectroscopy revealed the formation of stronger interaction forces between PVA/SA, PGE, and TiO2 nanoparticles, which showed good compatibility. In addition, the addition of PGE improved the tensile strength and elongation at break of the composite film, especially in different pH environments, and the color response was obvious. The addition of 1% TiO2 nanoparticles significantly improved the mechanical properties of the film, as well as the light barrier properties of the film. PGE could effectively be uniformly dispersed into the composite film, but it also had a certain slow-release effect on the release of PGE. PGE had high sensitivity under different pH conditions with rich color changes, and the color showed a clear color change from red to yellow-green when the pH increased from 1 to 14. The same change was observed when it was added to the film. In particular, by applying this film to the process of beef preservation, we judged the freshness of beef by monitoring the changes in the TVB-N value and pH value during the storage process of beef and found that the film showed obvious color changes during the storage process of beef, from blue (indicating freshness) to red (indicating non-freshness), and finally to yellow-green (indicating deterioration), which indicated that the color change of the film and the freshness of the beef maintained a highly consistent.
Application of Data-Driven Methods for Heating Ventilation and Air Conditioning Systems
Authors: Guo Yabin , Liu Yaxin , Wang Zhanwei , Hu Yunpeng
Published: November 2023

At present, with the continuous global energy crisis, buildings, as a significant factor in energy consumption, have significant importance in achieving the energy-saving operation of buildings [...]
Analysis and Modeling of the Onion Peeling Process in the Blowing Compressed Air Method
Authors: Woźniak Paweł , Bieńczak Agata , Nosal Stanisław , Piepiórka-Stepuk Joanna , Sterczyńska Monika
Published: November 2023

This paper presents the relationship between the efficiency of the process of onion peeling and the amount of waste generated in the process. The research was carried out on a pilot test stand for onion peeling. The process variables were the value of the compressed air pressure (p) and the value of the flow opening time through the control valve (t). The experiment took into account the influence of the onion diameter (d0) and its hardness (H). The obtained results were subjected to statistical analysis. Standard deviations were of the percentage loss of onion mass in the form of the peel removed in the onion peeling process in relation to the obtained average values. Tukey’s multiple comparison test was performed in order to identify the importance of individual process variables on the final effect of onion peeling. This was the basis for the development of a predictive model in the form of a non-linear regression Mp = f(p,t,d0,H), which is a mathematical description of the onion peeling process. Finally, the response surface area of the relationship between analyzed variables was determined. The results of research show that the peeling efficiency of the onion and waste of peel mass depend on the compressed air pressure. Extending the onion blowing time does not improve the process efficiency, while the hardness and size of the onion are irrelevant to the process.
Vision Transformer-Based Ensemble Learning for Hyperspectral Image Classification
Authors: Liu Jun , Guo Haoran , He Yile , Li Huali
Published: November 2023

Hyperspectral image (HSI) classification, due to its characteristic combination of images and spectra, has important applications in various fields through pixel-level image classification. The fusion of spatial–spectral features is a topic of great interest in the context of hyperspectral image classification, which typically requires selecting a larger spatial neighborhood window, potentially leading to overlaps between training and testing samples. Vision Transformer (ViTs), with their powerful global modeling abilities, have had a significant impact in the field of computer vision through various variants. In this study, an ensemble learning framework for HSI classification is proposed by integrating multiple variants of ViTs, achieving high-precision pixel-level classification. Firstly, the spatial shuffle operation was introduced to preprocess the training samples for HSI classification. By randomly shuffling operations using smaller spatial neighborhood windows, a greater potential spatial distribution of pixels can be described. Then, the training samples were transformed from a 3D cube to a 2D image, and a learning framework was built by integrating seven ViT variants. Finally, a two-level ensemble strategy was employed to achieve pixel-level classification based on the results of multiple ViT variants. Our experimental results demonstrate that the proposed ensemble learning framework achieves stable and significantly high classification accuracy on multiple publicly available HSI datasets. The proposed method also shows notable classification performance with varying numbers of training samples. Moreover, herein, it is proven that the spatial shuffle operation plays a crucial role in improving classification accuracy. By introducing superior individual classifiers, the proposed ensemble framework is expected to achieve even better classification performance.
Regional Contribution and Attribution of the Interannual Variation of Net Primary Production in the Yellow River Basin, China
Authors: Cao Yue , Li Huiwen , Liu Yali , Zhang Yifan , Jiang Yingkun , Dai Wenting , Shen Minxia , Guo Xiao , Qi Weining , Li Lu , Li Jianjun
Published: November 2023

Net primary production (NPP) serves as a crucial indicator of the ecosystem’s capacity to capture atmospheric CO2. Gaining insights into the dynamics of NPP and its driving mechanisms is pivotal for optimizing ecosystem carbon sink resource management. Since the implementation of the Grain-for-Green Program (GFGP) in 1999, the Yellow River Basin (YRB) has been one of the most significant areas for ecological restoration in China. However, our knowledge regarding the interannual variability (IAV) of NPP and the underlying driving forces in this region remains incomplete. In this study, we utilized a light use efficiency model to assess the spatiotemporal dynamics, IAV, and driving factors of NPP in the YRB during the period from 1999 to 2018. Our findings revealed that the average annual NPP in the YRB approximated 189.81 Tg C. Over the study duration, NPP significantly increased in 79.63% of the basin with an overall increasing rate of 6.76 g C m−2 yr−1. The most prominent increase was observed in the key GFGP implementation area, predominantly in the semi-humid region. Notably, the middle altitude region (1–1.5 km), semi-humid region, and grassland emerged as the primary contributors to the basin’s total vegetation carbon sequestration. However, it is worth emphasizing that there was substantial IAV in the temporal trends of NPP, with the semi-humid region being the most influential contributor (62.66%) to the overall NPP IAV in the YRB. Further analysis of the driving mechanisms unveiled precipitation as the primary driver of NPP IAV in the YRB with a contribution of 62.9%, followed by temperature (23.07%) and radiation (14.03%). Overall, this study deepened our understanding of the IAV and driving mechanisms of NPP in the YRB under ecological restoration, and provided scientific support for optimizing the management of regional carbon sequestration resources.
Anomaly Detection in the Production Process of Stamping Progressive Dies Using the Shape- and Size-Adaptive Descriptors
Authors: Ma Liang , Meng Fanwu
Published: November 2023

In the production process of progressive die stamping, anomaly detection is essential for ensuring the safety of expensive dies and the continuous stability of the production process. Early monitoring processes involve manually inspecting the quality of post-production products to infer whether there are anomalies in the production process, or using some sensors to monitor some state signals during the production process. However, the former is an extremely tedious and time-consuming task, and the latter cannot provide warnings before anomalies occur. Both methods can only detect anomalies after they have occurred, which usually means that damage to the die has already been caused. In this paper, we propose a machine-vision-based method for real-time anomaly detection in the production of progressive die stamping. This method can detect anomalies before they cause actual damage to the mold, thereby stopping the machine and protecting the mold and machine. In the proposed method, a whole continuous motion scene cycle is decomposed into a standard background template library, and the potential anomaly regions in the image to be detected are determined according to the difference from the background template library. Finally, the shape- and size-adaptive descriptors of these regions and corresponding reference regions are extracted and compared to determine the actual anomaly regions. The experimental results indicate that this method can achieve reasonable accuracy in the detection of anomalies in the production process of stamping progressive dies. The experimental results demonstrate that this method not only achieves satisfactory accuracy in anomaly detection during the production of progressive die stamping, but also attains competitive performance levels when compared with methods based on deep learning. Furthermore, it requires simpler preliminary preparations and does not necessitate the adoption of the deep learning paradigm.
A Real-Time Energy Response Correction Method for Cs3Cu2I5:Tl Scintillating Dosimeter
Authors: Li Jiaming , Zhang Leilei , Wang Jiaqi , Su Hengyi , Wang Zungang , Li Zhiyuan
Published: November 2023

The uneven energy response of radiation detectors severely limits the accuracy of the dose rate meter used for radiation protection. Currently widely used in dose rate meters as a physical method of setting shielding compensation, the energy response correction error of the detector at different energies is mostly between 15 and 25%. This work designs a real-time correction method for energy response based on a novel Cs3Cu2I5:Tl scintillation detector to improve the accuracy of the dose rate meter used for radiation protection. The technique utilizes the idea of pulse amplitude weighting (PAW) to segment the pulse amplitude histogram. This detector achieves an almost constant energy response after our correction. The experimental results show that compared to 137Cs γ rays, the maximum error of the response is 8.26% in the photon energy ranging from 33 keV to 1.25 MeV, which is much better than ±30% of the recommended IEC 61526:2010, verifying the feasibility of PAW.
Effect of Foot Orthoses on Angular Velocity of Feet
Authors: Florenciano Restoy Juan Luis , Solé-Casals Jordi , Borràs-Boix Xantal
Published: November 2023

There is some uncertainty regarding how foot orthoses (FO) affect the biomechanics of the lower extremities during running in non-injured individuals. This study aims to describe the behavior of the angular velocity of the foot in the stride cycle measured with a low-sampling-rate IMU device commonly used by podiatrists. Specific objectives were to determine if there are differences in angular velocity between the right and left foot and to determine the effect of foot orthoses (FO) on the 3D angular velocity of the foot during running. The sample was composed of 40 male adults (age: 43.0 ± 13.8 years, weight: 72.0 ± 5.5 kg, and height: 175.5 ± 7.0 cm), who were healthy and without any locomotor system alterations at the time of the test. All subjects use FO on a regular basis. The results show that there are significant differences in the transverse plane between feet, with greater differences in the right foot. Significant differences between FO and non-FO conditions were observed in the frontal and transverse planes on the left foot and in the sagittal and transverse planes on the right foot. FO decreases the velocity of the foot in dorsi-plantar flexion and abduction and increases the velocity in inversion. The kinematic changes in foot velocity occur between 30% and 60% of the complete cycle, and the FO reduces the velocity in abduction and dorsi–plantar flexion and increases the velocity in inversion–eversion, which facilitates the transition to the oscillating leg and with it the displacement of the center of mass. Quantifying possible asymmetries and assessing the effect of foot orthoses may aid in improving running mechanics and preventing injuries in individuals.
Indoor Human Action Recognition Based on Dual Kinect V2 and Improved Ensemble Learning Method
Authors: Kan Ruixiang , Qiu Hongbing , Liu Xin , Zhang Peng , Wang Yan , Huang Mengxiang , Wang Mei
Published: November 2023

Indoor human action recognition, essential across various applications, faces significant challenges such as orientation constraints and identification limitations, particularly in systems reliant on non-contact devices. Self-occlusions and non-line of sight (NLOS) situations are important representatives among them. To address these challenges, this paper presents a novel system utilizing dual Kinect V2, enhanced by an advanced Transmission Control Protocol (TCP) and sophisticated ensemble learning techniques, tailor-made to handle self-occlusions and NLOS situations. Our main works are as follows: (1) a data-adaptive adjustment mechanism, anchored on localization outcomes, to mitigate self-occlusion in dynamic orientations; (2) the adoption of sophisticated ensemble learning techniques, including a Chirp acoustic signal identification method, based on an optimized fuzzy c-means-AdaBoost algorithm, for improving positioning accuracy in NLOS contexts; and (3) an amalgamation of the Random Forest model and bat algorithm, providing innovative action identification strategies for intricate scenarios. We conduct extensive experiments, and our results show that the proposed system augments human action recognition precision by a substantial 30.25%, surpassing the benchmarks set by current state-of-the-art works.
IoT Sensor Network for Wild-Animal Detection near Roads
Authors: Knyva Mindaugas , Gailius Darius , Balčiūnas Gintautas , Pratašius Darius , Kuzas Pranas , Kukanauskaitė Aistė
Published: November 2023

The monitoring and detection of wild animals is a significant topic for researchers who study the behavior, lifestyle, and environment of wild animals, as well as for people who encounter wildlife both in residential areas and near roads while traveling. An innovative wild-animal detection internet-of-things (IoT) sensor network running on harvested solar energy and detection methodology is described in this article. The sensor-networks node is implemented via the principle of an embedded system incorporating passive infrared sensors, a long-range (LoRa) module, and a solar panel for energy harvesting. For experimental purposes, a small IoT sensor network was implemented near the road. The network consists of eight nodes placed near the road with a distance of 50 m between nodes, a gateway for gathering detection data from the nodes, and a thermo-vision camera for verification of the received data.
Analysis of FRP-Strengthened Reinforced Concrete Beams Using Electromechanical Impedance Technique and Digital Image Correlation System
Authors: Perera Ricardo , Huerta María Consuelo , Baena Marta , Barris Cristina
Published: November 2023

Fiber-reinforced polymer (FRP) strengthening systems have been considered an effective technique to retrofit concrete structures, and their use nowadays is more and more extensive. Externally bonded reinforcement (EBR) and near-surface mounted (NSM) technologies are the two most widely recognized and applied FRP strengthening methods for enhancing structural performance worldwide. However, one of the main disadvantages of both approaches is a possible brittle failure mode provided by a sudden debonding of the FRP. Therefore, methodologies able to monitor the long-term efficiency of this kind of strengthening constitute a challenge to be overcome. In this work, two reinforced concrete (RC) specimens strengthened with FRP and subjected to increasing load tests were monitored. One specimen was strengthened using the EBR method, while for the other, the NSM technique was used. The multiple cracks emanating in both specimens in the static tests, as possible origins of a future debonding failure, were monitored using a piezoelectric (PZT)-transducer-based electromechanical impedance (EMI) technique and a digital image correlation (DIC) system. Clustering approaches based on impedance measurements of the healthy and damaged states of the specimens allowed us to suspect the occurrence of cracks and their growth. The strain profiles captured in the images of the DIC system allowed us to depict surface hair-line cracks and their propagation. The combined implementation of the two techniques to look for correlations during incremental bending tests was addressed in this study as a means of improving the prediction of early cracks and potentially anticipating the complete failure of the strengthened specimens.
A New Approach for Completing Missing Data Series in Pan Evaporation Using Multi-Meteorologic Phenomena
Authors: Dis Muhammet Omer
Published: November 2023

The most crucial losses in the hydrological cycle occur due to evaporation (EP). As a result, the accurate attainment of this complex phenomenon is critical in studies on irrigation, efficiency in the basins, dams, continuous hydrometeorological simulations, flood frequency, and water budget analysis. However, EP data sets are expensive, difficult to sustainably measure, and scarce, also, predictions are challenging tasks due to the wide range of parameters involved in these processes. In this study, the data gaps are filled with Class A evaporation pan observations through building a new meteorological station during seasons with no gauge measurements available for a three-year time period. These observations demonstrate high correlations with the readings from the Meteorology Airport Station, with a PCC of 0.75. After the continuous EP time series was completed over Kahramanmaras, these values were retrieved non-linearly via an artificial intelligence model using multi-meteorological parameters. In the study, the simulation performance is evaluated with the help of eight different statistical metrics in addition to graphical representations. The evaluation reveals that, when compared to the other EP functions, using both temperature and wind-driven simulations has the highest correlation (PCC = 0.94) and NSCE (0.87), as well as the lowest bias (PBias = −1.65%, MAE = 1.27 mm d−1, RMSD = 1.6 mm d−1, CRMSE = 24%) relative to the gauge measurements, while they give the opposite results in the solely precipitation-based models (PCC = 0.42, NSCE = 0.17, PBias = −6.44%, MAE = 3.58 mm d−1, RMSD = 4.2 mm d−1, CRMSE = 62%). It has been clearly seen that the temperature parameter is the most essential factor, while precipitation alone may be insufficient in EP predictions; additionally, wind speed and relative humidity would improve the prediction performance in artificial intelligence techniques.
Assessment of the Implementation of Sustainable Stormwater Management Practices in Asian Countries
Authors: Seitzhan Orynbayev , Abdul Khadir Fatin Khalida , Bakyt Smailov , Ng Cheng Yee , Takaijudin Husna , Zawawi Noor Amila Wan , Alaloul Wesam Salah , Musarat Muhammad Ali
Published: November 2023

Numerous efforts have been undertaken by Asian countries to mitigate the adverse effects of urbanization on stormwater management. However, traditional stormwater systems have become overwhelmed due to extensive development, resulting in excessive runoff and frequent floods. As a result, it is crucial to urgently adopt sustainable stormwater management practices (SSMPs) to effectively control water quantity and quality. The goal of this study is to assess the viewpoints of stormwater practitioners regarding green roofs, rainwater harvesting systems (RHS), grass swales, rain garden/bioretention systems, and porous pavement using a SWOT analysis. This was accomplished by distributing questionnaires and evaluating previous studies. The survey showed that participants mostly agreed with the strengths, weaknesses, opportunities, and threats factors related to the chosen SSMPs. Overall, the respondents favoured the implementation of green roofs and grass swales. Further assessments were conducted on these practices in other aspects, confirming that green roofs are the most preferable SSMP for implementation in Asian countries.
Laboratory Experimental Study on the Pressure Relief Effect of Boreholes in Sandstone under High-Stress Conditions
Authors: Lu Xiaowei , Jiang Jingyu , Wang Wen , Cao Xuewen , Hong Lei
Published: November 2023

To study the effects of deep rock drilling pressure relief under high stress conditions in enhanced geothermal systems, two kinds of drilling pressure relief experiments were conducted on sandstone—the staged drilling of pressure relief holes before peak stress and one-time drilling. Pressure relief experiments were carried out on sandstone with two borehole methods of the stage-by-stage drilling and one-time drilling of pressure relief boreholes ahead of the experiments. FLAC3D was used to analyze the plastic zone evolution during drilling and the relationship between stress and plastic zone volume. The results reveal the pre-peak stress change characteristics and pressure relief features of non-prefabricated boreholes under high stress. The experiments show that the staged drilling of pressurized samples involves stages of rapid and gradual decreases in stress, with total relief amplitudes increasing but single-borehole relief decreasing with more holes. Under the same conditions, staged drilling has better relief effects and results in greater energy dissipation, indicating that incremental pre-peak pressure relief is beneficial for reducing the surrounding rock’s impact tendency and improving stability. The research results can provide good guidance and reference for the long-term stability analysis of borehole-containing rock and rock burst hazard control.
Risk Classification Assessment and Early Warning of Heavy Metal Contamination in Meat Products
Authors: Wang Zheng , Gao Yanping , Xu Xuemei , Dong Wei , Jiang Tongqiang
Published: November 2023

Risk classification assessment and early warning systems are indispensable tools and technologies in the realm of regulatory control. Evaluating and issuing early warnings regarding heavy metal contaminants in meat products play a pivotal role in ensuring public safety and maintaining societal stability. In this study, we focused on heavy metal pollutants such as lead, cadmium, chromium, and arsenic. We collected national inspection data for meat products from 20 provinces in 2020. Combining dietary structure data, toxicology information, and dietary exposure assessment methods, we constructed a risk assessment model for heavy metal contaminants in food. Furthermore, we employed an entropy weight-based analytic hierarchy process (AHP-EW) to classify the results of the risk assessment for heavy metal contaminants in food. This involved determining risk rating levels and thresholds. Finally, we constructed a multi-step food contaminant risk prediction model based on the Transformer framework. To validate the model’s performance, comparative assessments were conducted across 20 datasets using various models. The results clearly indicate that the Transformer model outperformed the others in 14 datasets, excelling in its ability to provide advanced warnings for heavy metal risks in meat products. This empowers relevant authorities to strengthen their regulatory oversight of meat products based on the procedures and models proposed in this study, ultimately enhancing the efficiency of food safety risk management.
Responses of In Vitro Strawberry Plants to Drought Stress under the Influence of Nano-Silicon Dioxide
Authors: Şener Sevinç , Sayğı Hülya , Duran Canan Nilay
Published: November 2023

The aim of the study is to determine the effectiveness of nano-silicon dioxide (NaSiO2) application on the tolerance of strawberry plants exposed to drought stress under in vitro conditions. Drought stress was induced with polyethylene glycol (PEG-6000). In the experiment, the effects of PEG 6000 concentrations (0, 4, 8%) and NaSiO2 concentrations (0, 50, 100 mg L−1) on in vitro strawberry plants were determined. Plants treated with PEG 6000 showed reduced vegetative growth parameters, but this decrease was reduced with NaSiO2 application. The addition of NaSiO2 enhanced shoot and leaf growth, SPAD index, and the leaf relative water content (LRWC) of in vitro strawberry plants. NaSiO2 at 50 mg L−1 induced the maximum shoot and root fresh weight (1.20 g, 1.24 g, respectively) and length (40.09 mm, 34.26 mm, respectively), leaves number (16.67 pieces/plant) and SPAD index 53.57 among 4% and 8% PEG applications. When the superoxide dismutase (SOD) and catalase (CAT) activities were examined, the results showed that the application of NaSiO2 enhanced drought stress tolerance by promoting certain antioxidant responses by increasing SOD and CAT activities under drought stress. Our results suggest that the application of NaSiO2 can help maintain the devastating impact of drought stress and markedly enhance all the examined parameters in the Albion strawberry cultivar under in vitro conditions.
Executive Overconfidence and Corporate Environmental, Social, and Governance Performance
Authors: Wang Yao , Han Yinyin , Du Qiuxuan , Hou Deshuai
Published: November 2023

ESG (environmental, social, and governance) has gained widespread recognition as a fundamental investment approach on a global scale. Demonstrating strong ESG performance has evolved into a vital strategic imperative for fostering sustainable corporate growth and bolstering competitiveness. Given their critical roles within companies, it is crucial for decision-makers to investigate the impact of executive overconfidence on ESG performance. Through an examination of Chinese A-share listed companies spanning the years 2009 to 2020, this research reveals a significant correlation between executive overconfidence and improved corporate ESG performance. Mechanism tests uncover that overconfident executives exhibit robust risk-taking abilities and a heightened drive to garner attention, both of which contribute to the enhancement of ESG performance. Heterogeneity analysis demonstrates that, in companies characterized by lower-quality accounting information, lower institutional shareholding ratios, ample cash flow, and increased government subsidies, the positive influence of executive overconfidence on ESG performance is even more pronounced. Furthermore, our investigation unveils that overconfident executives exert a positive impact on corporate ESG performance through three primary pathways: assuming responsibility for environmental protection (E), embracing social responsibility (S), and fortifying corporate governance (G). It is worth noting that this boost in ESG performance, in turn, translates into an enhancement of corporate value. Ultimately, this research contributes to a deeper understanding of the economic ramifications of executive overconfidence and enriches the body of knowledge pertaining to the mechanisms for enhancing ESG performance.
A Business Strategy Framework for Patent Pooling in the Solar Cell Supply Chain
Authors: Lee Shuo-Min , Chen Jen-Shyang , Hsu Chien-Lin , Chang Chi-Cheng
Published: November 2023

In the green energy sector, which includes the solar cell industry, effectively combining the patents of various manufacturers within the supply chain to collectively create sustainable patent market value is of paramount importance. This study aimed to establish a business strategy framework for project-based licensing through the analysis of solar cell patents and the integration of supply chain manufacturers’ patents, with the goal of collectively creating market value for patents in a sustainable manner. The research methodology included analysis of the literature and focus group discussions. The study began with an analysis of solar cell industry patents from the past decade using the WIPS Global Patent database to identify projects with the highest patent count. Subsequently, through the use of focus group discussions, the feasibility of a patent pool strategy within the supply chain was explored. Finally, a strategy framework was proposed for project-based patent pool licensing, focusing on the top 15 projects with the highest count of 5579 patents. The results indicate that adopting this strategy framework for supply chain manufacturer patents can result in higher commercial patent value.
Unraveling Digital Transformation in Banking: Evidence from Romania
Authors: Ionașcu Alina Elena , Gheorghiu Gabriela , Spătariu Elena Cerasela , Munteanu Irena , Grigorescu Adriana , Dănilă Alexandra
Published: November 2023

This research probes into the digital transformation shifts in Romania and sets them against a backdrop of certain EU countries. Its primary objective is to spotlight digitalization’s significance and assess its level of integration within the Romanian banking landscape. Our approach relies on a detailed examination of the adoption of digital banking instruments in Romania through correlation and ANOVA assessments. The ANOVA analysis of the DESI index and its associated dimensions reveals how Romania’s digital transformation stands in relation to other EU member states. Our findings emphasize the numerous advantages Romanian banks have garnered from increasingly embracing digital innovations and artificial technologies. These perks span from optimized operations and efficiency to enhanced customer experiences and a sharpened competitive advantage. The research indicates a strong positive correlation between a bank’s return on assets and its liquid assets to deposits and short-term funding ratios. This suggests that as digital integration deepens, there is a marked upturn in financial robustness. Additionally, the study sheds light on the perks of individuals adopting digital banking offerings and delves into factors that propel and impede the digital evolution in the banking arena. Overall, this paper presents valuable insights into Romania’s digital banking trajectory and the sector’s long-term viability.
Safety Constraint-Guided Reinforcement Learning with Linear Temporal Logic
Authors: Kwon Ryeonggu , Kwon Gihwon
Published: November 2023

In the context of reinforcement learning (RL), ensuring both safety and performance is crucial, especially in real-world scenarios where mistakes can lead to severe consequences. This study aims to address this challenge by integrating temporal logic constraints into RL algorithms, thereby providing a formal mechanism for safety verification. We employ a combination of theoretical and empirical methods, including the use of temporal logic for formal verification and extensive simulations to validate our approach. Our results demonstrate that the proposed method not only maintains high levels of safety but also achieves comparable performance to traditional RL algorithms. Importantly, our approach fills a critical gap in the existing literature by offering a solution that is both mathematically rigorous and empirically validated. The study concludes that the integration of temporal logic into RL offers a promising avenue for developing algorithms that are both safe and efficient. This work lays the foundation for future research aimed at generalizing this approach to various complex systems and applications.
Boosting Mouse Defense against Lethal Toxoplasma gondii Infection with Full-Length and Soluble SAG1 Recombinant Protein
Authors: Li Xiang , Yuan Wei , He Ting , Guo Ruiying , Du Xiuxian , He Yanhong , Li Xuan , El-Ashram Saeed , Al-Olayan Ebtesam M. , Yang Na , Sang Xiaoyu
Published: November 2023

Toxoplasmosis is a major worldwide protozoan zoonosis. The surface antigen 1 (SAG1) of Toxoplasma gondii (T. gondii) has always been recognized as an ideal vaccine candidate antigen. However, the intact and soluble SAG1 protein is usually difficult to acquire in vitro, which is unfavorable for employing the recombinant protein as a vaccine candidate antigen. In the present study, we obtained the full-length SAG1 recombinant protein in soluble form by Escherichia coli Transetta (DE3) cells under optimized expression conditions. The immunogenicity and protective ability of this recombinant protein against T. gondii acute infection were evaluated in a mouse model. Monitoring changes in serum antibody levels and types, the presence of cytokines, and the rate of lymphocyte proliferation in vaccinated mice were used to assess humoral and cellular immune responses. Additional assessments were performed to determine the protective potency of the recombinant protein in combating T. gondii RH tachyzoites. It was found that the titers of both IgG2a and IgG2b were considerably greater in the immunized mice compared to the titers of IgG1 and IgG3. The levels of Th1-type cytokines (IFN-γ, IL-12p70, IL-2, and TNF-α) and Th2-type cytokines (IL-10) significantly increased when splenocytes from immunological group mice were treated with T. gondii lysate antigen. Compared to the control group, a recombinant protein substantially increased the longevity of infected mice, with an average death time prolonged by 14.50 ± 0.34 days (p < 0.0001). These findings suggest that the full-length and soluble SAG1 recombinant protein produced potent immune responses in mice and could be a preferred subunit vaccine candidate for T. gondii, offering a feasible option for vaccination against acute toxoplasmosis.
Flood and Landslide Damage in a Mediterranean Region: Identification of Descriptive Rainfall Indices Using a 40-Year Historical Series
Authors: Petrucci Olga , Coscarelli Roberto
Published: November 2023

In the future, as a result of global warming, it is possible that rainfall could become more intense and frequent. This could lead to more frequent triggering of damaging phenomena such as floods and landslides (named as a whole damaging hydrogeological events, DHE), and, consequently, to the increase of their impacts on territories, especially in regions where uncontrolled urban sprawl represents a factor that can exacerbate the problem. The analysis of a large quantity of information about both triggering rainfall and triggered phenomena can help to comprehend relationships between triggering precipitation and its related impacts. In this paper, to facilitate the investigation of the relationships between large and complex datasets concerning both rainfall and rainfall-related damage, we propose an index-based approach, illustrated by its application to the Calabria region (Southern Italy). In particular, this manuscript presents some results from a preliminary investigation aimed at assessing the “better” index to describe DHE. Five rainfall indices (RIs) were tested and five composite rainfall indices (CRIs), combinations of two or more RIs, are proposed. We calculated the RIs and the CRIs by means of 1,300,000 daily data registered in the observation period 1980–2020. The CRIs showed the best relationships with the data of damaging hydrogeological events (DHEs). Particularly, better results were obtained with landslides data than with floods data, perhaps due to the hydraulic characteristics of the Calabria rivers, affected by flash floods mainly influenced by very intense hourly rainfall events.