bluuebunny/crossref_metadata_2025 huggingface dataset:
Growth Parameters, Yield and Grain Quality of Different Winter Wheat Cultivars Using Strip Tillage in Relation to the Intensity of Post-Harvest Soil Cultivation
Authors: Różewicz Marcin , Grabiński Jerzy , Wyzińska Marta
Published: December 2024

The research has been undertaken to determine whether it is worthwhile to do a post-tillage on stubble before applying strip-till or whether tillage operations such as tillage and stubble ploughing should be performed. Therefore, ploughed tillage + strip tillage (PT), stubble discing + strip tillage (SD) and strip tillage (ST) operations were evaluated on three genetically distant winter wheat cultivars, including Formacja, Metronom and Desamo. A three-year field experiment was conducted from 2018 to 2021 at the Agricultural Experimental Station Kepa-Osiny in Pulawy, Poland. The experiment design was a split-block design with four repetitions of every treatment. The results showed that the cultivars differed in dry matter growth. However, no differences were found between the cultivar and post-harvest tillage method in terms of dry matter, plant height, and flag leaf area. Grain yield per ear was the main factor of yield variation across the cultivar and tillage systems. The extent of tillage only in the case of previously performed ploughing had an effect on the thousand grain weight. On the other hand, the omission of post-harvest tillage (ST) had a positive effect on the sedimentation index value. In terms of wheat grain yield, plough tillage (PT) proved to be the most advantageous, while reducing the intensity of tillage caused a systematic decrease in yield by 6% in the SD treatment and 9% in the ST treatment, respectively. Other quality parameters (gluten quantity, gluten index, falling number) did not depend on the applied tillage range. The response of cultivars to the applied cultivation methods was generally similar. Due to the beneficial effect of reducing the scope of cultivation on the environment, a small reduction in yield and no negative impact on the quality characteristics of grain, it is recommended to use strip-till cultivation without prior post-harvest cultivation. The results provide new insights into the growth of different winter wheat cultivars and the postharvest tillage applied, and they can be used in the future to validate existing wheat growth models.
Precipitation Controls Topsoil Nutrient Buildup in Arid and Semiarid Ecosystems
Authors: Medina-Roldán Eduardo , Wang Meixin , Miyasaka Takafumi , Pan Yueming , Li Xiang , Liu Bing , Qu Hao
Published: December 2024

Soil nutrient buildup is a key process in nutrient-poor arid and semiarid regions. However, our knowledge of the factors that control soil nutrient buildup in these systems is still limited. An experiment was set up and carried out for five and a half years in order to investigate how precipitation and other site factors control soil nutrient buildup. Topsoil carbon (C), nitrogen (N), phosphorus (P), and potassium (K) derived from litter (soil nutrient buildup) were tracked twice a year at two sites differing in terms of climate and soils (Urat: arid and Naiman: semiarid, both in Inner Mongolia). Precipitation was manipulated at both sites to include seven precipitation levels: three reduced levels (−20, −40, and −60% with respect to the background), background (control), and three enhanced levels (+20, +40, and +60% with respect to the background). The dynamic buildup (i.e., amount of nutrients released among consecutive samplings) for all nutrients was controlled by precipitation (nonlinearly), site effects (lower buildup at the site dominated by aeolian pedogenesis), and seasonality (higher under warm conditions). However, the considered nutrients differed in the factor that most determined their buildup. Through studying the concurrent dynamics of litter decomposition and soil nutrient buildup, we can foresee that changes in precipitation and land degradation are most likely to affect the soil nutrient pools in these ecosystems.
Chemotactic Responses of Oscheius myriophilus to Mollusk Mucus
Authors: Laznik Žiga , Trdan Stanislav , Šavli Klara
Published: December 2024

Terrestrial slugs and snails can significantly harm agriculture. Due to environmental concerns associated with chemical molluscicides, biological control methods are increasingly being explored. Oscheius myriophilus (Poinar, 1986), a nematode species recently discovered in association with Arion vulgaris Moquin-Tandon, 1855, holds promise as a biocontrol agent for gastropod pests. In this study, we investigated the chemotactic response and motility of O. myriophilus when exposed to the mucus of five mollusk species: Helix pomatia Linnaeus, 1758, Cernuella virgata (Da Costa, 1778), Deroceras reticulatum Müller, 1774, A. vulgaris, and Tandonia budapestensis Hazay, 1880. Our experiments were conducted at two temperatures (20 °C and 25 °C) to assess how environmental conditions influence nematode behavior. The results demonstrated that the chemoattractiveness of mollusk mucus to O. myriophilus was significantly influenced by both the species of mollusk and the temperature. Overall, nematode motility was higher at 20 °C than at 25 °C, indicating that lower temperatures may enhance the activity of O. myriophilus. Among the tested mollusk species, C. virgata mucus consistently attracted the highest number of nematodes, especially at the lower temperature. Our findings indicate that the chemotactic response of O. myriophilus to mollusk mucus may have potential for the targeted biocontrol of pest mollusks. While C. virgata demonstrated strong attractant potential at the tested temperatures, particularly under cooler conditions (20 °C), further research is needed to confirm whether this represents a consistent temperature-related effect. Future studies should aim to identify the specific chemical cues in mollusk mucus that trigger nematode attraction and examine how these signals interact with a broader range of environmental variables, including temperature, to influence nematode behavior.
Analysis of Future Drought Risk and Wheat Meteorological Disaster in Ningxia (Northwest China) Based on CMIP6 and SPEI
Authors: Li Xinlong , Tan Junli , Wang Xina , Shang Qian , Li Hao , Li Xuefang
Published: December 2024

In arid areas, droughts caused by climate change seriously impact wheat production. Therefore, research on spatial and temporal variability of dry and hot wind events and drought risk under different development patterns of future climate can provide a reference for wheat cultivation planning in the study area. Based on meteorological data under three scenarios of the CMIP6 (Sixth International Coupled Model Comparison Program) shared socio-economic path (SSP), we introduced wheat dry hot wind discrimination criteria and calculated the Standardized Precipitation–Evapotranspiration Index (SPEI). Future temperature changes within the Ningxia Province were consistent, increasing at a rate of 0.037, 0.15 and 0.45 °C·(10 a−1) under SSP126, 245 and 585 scenarios, respectively. Simultaneously, average annual precipitation would increase by 17.77, 38.73 and 32.12 mm, respectively. Dry hot wind frequency differed spatially, being higher in northern Ningxia and western Ningxia, and lower in southern Ningxia and eastern Ningxia. During the wheat growing period, there is an obvious increasing drought risk trend under the SSP585 model in May, and the possibility of drought risk in the middle period was highest under the SSP126 model. In June, SPEI was generally higher than in May, and the risk of alternating drought and flood was greater under the SSP585 model, while near-medium drought risk was lower under the SSP126 and SSP245 models. The influence of DHW (dry and hot wind) on wheat yield will increase with the increase of warming level. However, when DHW occurs, effective irrigation can mitigate the harm. Irrigation water can be sourced from various channels, including rainfall, diversion, and groundwater. These results provide scientific reference for sustainable agricultural production, drought risk and wheat meteorological disaster forecast in inland arid areas affected by climate change.
Optimizing Cryopreservation Protocols for Coffea racemosa and Coffea liberica: Impact of Moisture Content and Packaging on Seed Viability
Authors: Coelho Stefania Vilas Boas , Rosa Sttela Dellyzete Veiga Franco da , Padilha Lilian , Assis Janaina Guarieiro Ribeiro de , Vilela Ana Luiza de Oliveira , Ferreira Ana Maria Oliveira , Guerreiro Filho Oliveiro , Braghini Masako Toma
Published: December 2024

Cryopreservation protocols have not yet been defined for seeds of some Coffea species due to their high sensitivity to desiccation and to ultra-low temperatures, factors that lead to low seed survival rates after warming. This reduced rate occurs due to several factors that compromise cellular integrity during the steps of the process. In this study, we evaluated the effect of moisture content and the types of packaging on the cryopreservation of Coffea racemosa and Coffea liberica var dewevrei seeds. For that purpose, seeds were dried to moisture contents of 18, 20, and 25% (dry basis—db) for C. racemosa and to contents of 20, 25, 30, and 35% for C. liberica. The seeds were then packed in mesh bags, Falcon tubes, and triple-laminated aluminum foil pouches before being directly immersed in liquid nitrogen. Physiological and biochemical analyses were performed on the seeds. There was interaction between moisture content and the packaging of the seeds of the species. Drying the seeds to a 20% moisture content and packing them in triple-laminated aluminum foil pouches provided the best cryopreservation protocol among those studied, with survival rates of 79 and 8% for C. racemosa and C. liberica, respectively.
Correction: Smolik, B.; Sędzik-Wójcikowska, M. Examining Nicotinamide Application Methods in Alleviating Lead-Induced Stress in Spring Barley. Agronomy 2024, 14, 1314
Authors: Smolik Beata , Sędzik-Wójcikowska Maja
Published: December 2024

In the original publication [...]
Recent Technological Advancements for Identifying and Exploiting Novel Sources of Pest and Disease Resistance for Peanut Improvement
Authors: Biswal Akshaya Kumar , Ozias-Akins Peggy , Holbrook Carl Corley
Published: December 2024

Peanut, also known as groundnut (Arachis hypogaea L.), is an important oilseed and food crop globally, contributing significantly to the economy and food security. However, its productivity is often hampered by pests and diseases. Traditional breeding methods have been used to develop resistant cultivars, but these are often time-consuming and labor-intensive. Recent technological advancements have revolutionized the identification of novel resistance sources and the development of resistant peanut cultivars. This review explores the latest techniques and approaches used in peanut breeding for pest and disease resistance, focusing on the identification of resistance loci and their incorporation into peanut using marker-assisted selection (MAS) and genomic tools. Next-generation sequencing (NGS) technologies, bioinformatics pipelines, comparative genomics, and transcriptomics have helped identify a plethora of candidate genes involved in pest resistance. However, peanut lags behind other cereal crops in terms of phenomics and precision genetic techniques for their functional validation. In conclusion, recent technological advancements have significantly improved the efficiency and precision of peanut breeding for pest and disease resistance and hold great promise for developing durable and sustainable resistance in peanut cultivars, ultimately benefiting peanut farmers and consumers globally.
Estimation of Harvest Time Based on Cumulative Temperatures to Produce High-Quality Cherry Tomatoes in a Plant Factory
Authors: Rachma Dannisa Fathiya , Munyanont Maitree , Maeda Kazuya , Lu Na , Takagaki Michiko
Published: December 2024

Harvest time is one of the key factors for obtaining high-quality cherry tomatoes. This parameter depends on environmental conditions and tomato variety. In plant factories with artificial lighting (PFALs), it is possible to control environmental conditions to enhance tomato production and quality. Since the ripening status of tomato fruit is correlated with cumulative temperature (CT), and the temperature inside PFALs can be easily controlled, CT could be used as an alternative method to predict tomato harvest time. In this study, three experiments were conducted to determine the optimal CT for harvesting high-quality cherry tomatoes in a PFAL. The experiments aimed to (1) evaluate the yield and quality of cherry tomatoes as affected by different harvest times based on CT (ranging from 900 to 1400 °C), (2) comparatively evaluate the yield and quality of cherry tomatoes that were still on the plant and off the plant (in storage) based on the same CT levels (i.e., 1100, 1200, and 1300 °C), and (3) investigate the fruit-cracking percentage during the ripening stage based on CT levels. The results showed that the fruit harvested at lower CTs exhibited higher hardness values, while those harvested at higher CTs had a higher sugar content. The on-the-plant treatment resulted in a higher yield and sugar content compared with the off-the-plant treatment, indicating that harvesting tomatoes early would come at the expense of a certain yield and sweetness. Moreover, the fruit-cracking percentage tended to increase with increasing CT, possibly due to the fast fruit growth rate and increased internal turgor pressure. These results indicated that producers can use CT as an index to predict the harvest time, thereby optimizing profits in cherry tomato production.
Saccharomyces Cerevisiae Diet Supplementation Affects Nutrient Digestibility and Milk and Mozzarella Cheese Yield in Dairy Buffalo Cows During the Transition
Authors: Zicarelli Fabio , Vianello Remus Costantin , Masiello Isabella , Musco Nadia , Iommelli Piera , Wanapat Metha , Lotito Daria , Lombardi Pietro , Grossi Micaela , Infascelli Federico , Tudisco Raffaella
Published: December 2024

The aim of the trial was to evaluate the influence of diet supplementation with Saccharomyces cerevisiae on nutrient digestibility and milk and mozzarella cheese yield in buffalo cows during the transition period. Twenty buffalo cows in the last month of pregnancy were equally divided into two groups (control, C, and treated, T) homogeneous for parity and milk yield at the previous lactation. The diet of group T was supplemented with 100 g/head/day of a product containing Saccharomyces cerevisiae (Sc 47- CNCM I-4407) for 4 weeks before and after calving. Dry matter intake and the body condition score were not affected by the dietary treatment. In contrast, organic matter, protein, NDF, and ADF digestibility significantly (p < 0.01) increased. Group T showed a higher milk yield (kg 10.5 vs. 9.2, p < 0.05) but lower milk fat (g/kg 76.0 vs. 80.1, p < 0.05). The buffalo standard milk (FPCM = 740 kcal) yield was higher in the treated group (kg 16.8 vs. 15.0, p < 0.05), whereas the mozzarella cheese yield was not affected by the treatment (p > 0.05). These findings indicate that supplementation of the diet of buffaloes with Saccharomyces cerevisiae during the transition period results in notable enhancements in nutrient digestibility and milk yield. These outcomes are worthy of further investigation.
Fertility of the European Brown Hare Across Plain, Hill and Mountain Environments in the Italian Peninsula
Authors: Freschi Pierangelo , Cosentino Carlo , Mallia Egidio , Trocchi Valter
Published: December 2024

This study examines the reproductive performance of the European brown hare in Italy, focusing on four hunting districts in Basilicata (A1, A2) and Emilia–Romagna (A3, A4) and using the number of endometrial scars as a fertility indicator. Fertility, measured as the number of scars during the entire reproductive period, was highest in A1 (11.50 ± 1.64) and A4 (11.43 ± 1.01), followed by A3 (9.56 ± 1.09) and A2 (6.08 ± 1.34). Significant differences were found when comparing the mountain area (A2) with A4 (p < 0.01) and with A1 and A3 (p < 0.05). Regarding the overall monthly number of scars per individual across the four study areas, the highest value (3.16 ± 0.18) was observed in May, followed by March (2.74 ± 0.18), April (2.67 ± 0.20), June (2.57 ± 0.20), February (2.53 ± 0.34), July (2.40 ± 0.22), and August (2.19 ± 0.31). A correlation analysis identified a weak yet statistically significant positive relationship (r = 0.532; p = 0.036) between the Kerner Oceanity Index (with values of 16.87, 15.00, 8.45, and 11.11 in A1, A2, A3, and A4, respectively) and the number of scars per pregnancy across the four study areas. Understanding species’ reproductive dynamics is vital for assessing habitat suitability and creating strategies to sustain hare populations and their ecosystem roles.
Evaluation of the Effect of Adipokinetic Hormone/Corazonin-Related Peptide (ACP) on Ovarian Development in the Mud Crab, Scylla paramamosain
Authors: Tan Wenting , Tang Yiwei , Liu Fang , Lu Li , Liu An , Ye Haihui
Published: December 2024

In this study, we identified Sp-ACP and its putative receptor from the mud crab S. paramamosain and explored its potential role in ovarian development. RT-PCR results suggested Sp-ACP was extensively expressed in nervous tissues, the ovary, the middle gut, and the Y-organ, while Sp-ACPR was highly expressed in the ovary. The expression level of Sp-ACP in the ovary, eyestalk, and cerebral ganglia gradually increased during ovarian development, whereas its receptor exhibited an opposite expression pattern in the ovary. Immunofluorescence revealed that ACP was specifically localized in the follicle cells of the ovary. In vitro experiments showed that the expression of vitellogenin receptor (Sp-VgR) in the ovary was significantly increased by 4 and 6 h incubation of Sp-ACP (10 nM). In addition, 12 h injection of Sp-ACP significantly induced the levels of Sp-Vg in the hepatopancreas and Sp-VgR in the ovary, and hemolymph 17β-estradiol titer. Finally, it demonstrated that prolonged injection of Sp-ACP significantly increased the level of Vg and VgR expression, hemolymph 17β-estradiol titer, GSI, and the oocyte diameter. In conclusion, our results suggested that ACP is involved in the regulation of ovarian development of S. paramamosain, likely by inducing hepatopancreas Sp-Vg expression through estradiol and promoting the uptake of Vg by oocytes.
Automating an Encoder–Decoder Incorporated Ensemble Model: Semantic Segmentation Workflow on Low-Contrast Underwater Images
Authors: Bektaş Jale
Published: December 2024

Numerous methods have been proposed for semantic segmentation and the state-of-the-art part is likely to be incorporated by deep learning-based methods which show a salient performance. This study addresses the challenge of semantic segmentation in low-contrast imbalanced underwater images. Moreover, it employs nine model fusions as a downstream workflow task using encoder–decoder architectures with Dice Loss and Focal Loss training focusing on the imbalance data. Afterwards, the most effective two encoder–decoder fusion models, Res34+Unet and VGG19+FPN, by 0.592%, 0.590% mIoU on average and by 0.510%, 0.491% F1-score yielded better performance, respectively, than other models. Using a weight-optimization algorithm, the ensemble model with recreated IoU results improves the accuracy for both the Res34+Unet and the VGG19+FPN models, by 0.652% mIoU on average which is 6%. The ensemble model combines the model performances of independent models by considering their superior inference accuracy on a per-class basis separately and improves the model performances by emphasizing the better one on a per-class basis.
Non-Destructive Evaluation of Reinforced Concrete Structures with Magnetic Flux Leakage and Eddy Current Methods—Comparative Analysis
Authors: Frankowski Paweł Karol , Majzner Piotr , Mąka Marcin , Stawicki Tomasz
Published: December 2024

This article evaluates two essential non-destructive electromagnetic techniques, magnetic flux leakage (MFL) and eddy current (EC) methods, and their effectiveness in assessing the basic parameters of reinforced concrete (RC). The study compares both systems’ hardware and software components, emphasizing the adaptations implemented to tailor the methods for evaluating RC structures. Subsequently, the measurement results are analyzed, and association rules are extracted to demonstrate the relationships between variations in the physical parameters of the tested structure and the features of the measured waveforms. Finally, similar identification models are implemented, and the obtained identification results are compared. The paper documents and details all phases of this research. The findings indicate that while the operational principles of both methods are similar, the techniques differ significantly in terms of their measurement systems’ complexity and usability. The eddy current (EC) method exhibits superior spatial resolution, whereas the magnetic method is more straightforward and offers a greater effective range and favorable association rules. Consequently, it is recommended that both techniques be utilized for different structures and in varying contexts. The techniques’ advantages, disadvantages, and limitations are discussed in this work and supported by the measurement results.
Evaluation of Pressure Effect on Accelerated Aging Tests of Polymer-Insulated Aircraft Wires
Authors: Bas-Calopa Pau , Riba Jordi-Roger , Moreno-Eguilaz Manuel
Published: December 2024

Most current international standards for qualifying polymer-insulated wires for aircraft applications rely on degradation tests conducted under standard pressure conditions. However, some wires are used in unpressurized areas and therefore need to withstand low-pressure conditions. In the technical literature, there is a shortage of data on this topic. This article focuses on accelerated wet arc tracking tests of insulated wires and evaluates three methods that assess the performance of surface discharges generated during degradation, based on the light emitted, under different pressure conditions in the range of 100 kPa–16 kPa. The experimental results presented in this paper show that the sensitivity of the proposed methods increases with atmospheric pressure, allowing a better quantification of the degradation effects at higher pressures. These results can also help to gain experience and understanding in how commercial optoelectronic sensors can be used to assess the insulation condition by analyzing the light generated by the surface discharges.
Consistent Vertical Federated Deep Learning Using Task-Driven Features to Construct Integrated IoT Services
Authors: Oh Soyeon , Lee Minsoo
Published: December 2024

By training a multivariate deep learning model distributed across existing IoT services using vertical federated learning, expanded services could be constructed cost-effectively while preserving the independent data architecture of each service. Previously, we proposed a design approach for vertical federated learning considering IoT domain characteristics. Also, our previous method, designed leveraging our approach, achieved improved performance, especially in IoT domains, compared to other representative vertical federated learning mechanisms. However, our previous method was difficult to apply in real-world scenarios because its mechanism consisted of several options. In this paper, we propose a new vertical federated learning method, TT-VFDL-ST (Task-driven Transferred Vertical Federated Deep Learning using Self-Transfer partial training), a consistent single mechanism even in various real-world scenarios. The proposed method is also designed based on our previous design approach. However, the difference is that it leverages a newly proposed self-transfer partial training mechanism. The self-transfer partial training mechanism improved the MSE and accuracy of TT-VFDL-ST by 0.00262 and 12.08% on average compared to existing mechanisms. In addition, MSE and accuracy improved by up to 0.00290 and 5.08% compared to various options of our previous method. By applying the self-transfer partial training mechanism, TT-VFDL-ST could be used as a key solution to construct real-world-integrated IoT services.
Ultrasound-Assisted Enzymatic Extraction and Physicochemical Properties of Soluble Dietary Fiber from Soy Sauce Residue
Authors: Zhang Lili , Song Juncheng , Liu Qi , Liu Feng , Li Xiangyang
Published: December 2024

There are millions of tons of fresh soy sauce residue (SSR) by-products created by China’s soy sauce industry every year. Most of the SSR is directly discarded; this not only wastes resources, but also pollutes the environment. As it is rich in dietary fiber, which is beneficial to human health, skimmed SSR was used as a raw material to obtain soluble dietary fiber (SDF) in this study. Firstly, the process of ultrasonic-assisted enzymatic extraction of SDF was optimized through single factor experiments and a response surface test. The extraction rate of the SDF from SSR reached 76.8 ± 0.8% under the optimum extracting conditions of a cellulase/hemicellulase (w/w) 1/1 mixture, an enzyme addition amount of 5.7%, a material–liquid ratio (w/v) of 1/20 g/mL, and a reaction time of 30 min. Then, the physicochemical properties of the SDF extracted using enzymatic and chemical methods were compared; we found that the SDF obtained through ultrasound-assisted enzymatic extraction had a much better appearance and physicochemical properties than that extracted by acid or alkali, with a lighter color, higher extraction rate, higher water-holding capacity, higher oil-holding capacity, higher swelling capacity, and solubility. The microstructure was more uniform and porous. This study will provide theoretical guidance and technical support for the recycling and utilization of SSR, which is beneficial for improving its economic value.
The Effect of the Cultivar and Process Parameters on Quality and Biologically Active Compounds Content in Impregnated Carrot Tissue
Authors: Radziejewska-Kubzdela Elżbieta , Biegańska-Marecik Róża , Szadzińska Justyna , Spiżewski Tomasz , Gapiński Bartosz , Kowiel Angelika , Mierzwa Dominik
Published: December 2024

Vacuum impregnation (VI) allows soluble solids to be introduced into the porous matrix of a food material, modifying the composition of the tissue to facilitate further processing. The purpose of this research was to analyze the influence of pressure on the effectiveness of VI on a low porous material that is difficult to impregnate. Two cultivars of carrot (Baltimore F1 and Komarno) were subjected to VI at 5 and 30 kPa in a ternary solution of ascorbic acid (0.5%), citric acid (0.5%), and sucrose (8%) under isotonic conditions. The products were analyzed in terms of ascorbic acid content, degree of impregnation, and changes in structure, texture, color, antioxidant activity, phenolic content, carotenoids, and structure-forming compounds. Increases in vitamin C content (after VI) depended on the process conditions and ranged from 900% to 1300% in relation to the raw material. It was also observed that the extended impregnation time at a pressure of 5 kPa produced slices that were also impregnated in parenchyma area. The increased levels of polyphenolic compounds found in the saturated product may suggest that de novo synthesis under the influence of physiological stress had occurred.
Joint Design of Transmitter Precoding and Optical Intelligent Reflecting Surface Configuration for Photon-Counting MIMO Systems Under Poisson Shot Noise
Authors: Wang Jian , Zhou Xiaolin , Li Fanghua , Chen Yongkang , Cai Chaoyi , Xu Haoze
Published: December 2024

Intelligent reflecting surfaces (IRSs) have emerged as a promising technology to enhance link reliability in a cost-effective manner, especially for line-of-sight (LOS) link blocking caused by obstacles. In this paper, we investigate an IRS-assisted single-cell photon-counting communication system in the presence of building shadows, where one IRS is deployed to assist the communication between a multi-antenna base station (BS) and multiple single-antenna users. Photon counting has been widely adopted in sixth-generation (6G) optical communications due to its exceptional detection capability for low-power optical signals. However, the correlation between signal and noise complicates analyses. To this end, we first derive the channel gain of the IRS-assisted MIMO system, followed by the derivation of the mean square error (MSE) of the system using probabilistic methods. Given the constraints of the transmit power and IRS configuration, we propose an optimization problem aimed at minimizing the MSE of the system. Next, we present an alternating optimization (AO) algorithm that transforms the original problem into two convex subproblems and analyze its convergence and complexity. Finally, numerical results demonstrate that the IRS-assisted scheme significantly reduces the MSE and bit error rate (BER) of the system, outperforming other baseline schemes.
Two-Stage Genetic Algorithm for Optimization Logistics Network for Groupage Delivery
Authors: Malashin Ivan P. , Tynchenko Vadim S. , Masich Igor S. , Sukhanov Denis A. , Ageev Daniel A. , Nelyub Vladimir A. , Gantimurov Andrei P. , Borodulin Alexey S.
Published: December 2024

This study explored the optimization of groupage intercity delivery using a two-stage genetic algorithm (GA) framework, developed with the BaumEvA Python library. The primary objective was to minimize the transportation costs by strategically positioning regional branch warehouses within a logistics network. In the first stage, the GA selected optimal branch warehouse locations from a set of candidate cities. The second stage addressed the vehicle routing problem (VRP) by employing a combinatorial GA to optimize the delivery routes. The GA framework was designed to minimize the total costs associated with intercity and last-mile deliveries, factoring in warehouse locations, truck routes, and vehicle types for last-mile fulfillment while ensuring capacity constraints are adhered to. By solving both line haul and last-mile delivery subproblems, this solution adjusted variables related to warehouse placement, cargo volumes, truck routing, and vehicle selection. The integration of such optimization techniques into the logistics workflow allowed for streamlined operations and reduced costs.
A Hybrid Deep Learning Approach for Multi-Class Cyberbullying Classification Using Multi-Modal Social Media Data
Authors: Tabassum Israt , Nunavath Vimala
Published: December 2024

Cyberbullying involves the use of social media platforms to harm or humiliate people online. Victims may resort to self-harm due to the abuse they experience on these platforms, where users can remain anonymous and spread malicious content. This highlights an urgent need for efficient systems to identify and classify cyberbullying. Many researchers have approached this problem using various methods such as binary and multi-class classification, focusing on text, image, or multi-modal data. While deep learning has advanced cyberbullying detection and classification, the multi-class classification of cyberbullying using multi-modal data, such as memes, remains underexplored. This paper addresses this gap by proposing several multi-modal hybrid deep learning models, such as LSTM+ResNet, LSTM+CNN, LSTM+ViT, GRU+ResNet, GRU+CNN, GRU+ViT, BERT+ResNet, BERT+CNN, BERT+ViT, DistilBERT+ResNet, DistilBERT+CNN, DistilBERT+ViT, RoBERTa+ResNet, RoBERTa+CNN, and RoBERTa+ViT, for classifying multi-classes of cyberbullying. The proposed model incorporates a late fusion process, combining the LSTM, GRU, BERT, DistilBERT, and RoBERTa models for text extraction and the ResNet, CNN, and ViT models for image extraction. These models are trained on two datasets: a private dataset, collected from various social media platforms, and a public dataset, obtained from previously published research. Our experimental results demonstrate that the RoBERTa+ViT model achieves an accuracy of 99.20% and an F1-score of 0.992 on the public dataset, and an accuracy of 96.10% and an F1-score of 0.959 on the private dataset when compared with other hybrid models.
Impact of the STFT Window Size on Classification of Grain-Oriented Electrical Steels from Barkhausen Noise Time–Frequency Spectrograms via Deep CNNs
Authors: Maciusowicz Michal , Psuj Grzegorz
Published: December 2024

The Magnetic Barkhausen Noise (MBN) is a non-destructive testing method, which, due to its high sensitivity to changes in the microstructure of the material, is increasingly being applied with success as a tool for evaluation of magnetic material state and properties. However, it is no less difficult to analyze the measurement signals and their correct interpretation due to the complex, non-deterministic and stochastic nature of the Barkhausen phenomenon. Depending on the material to be examined, a signal with different characteristics can be observed. Frequently, a signal with multi-phase Barkhausen activity characteristics is obtained, like in the case of grain-oriented electrical steels. Due to the increased computational capabilities of computers, more and more advanced signal analysis methods are being used and artificial intelligence is being involved as well. Recently, the time–frequency (TF) approach for MBN signal analysis was introduced and discussed in several papers, where short-time Fourier Transform (STFT) found frequent application with promising results. Due to the automation of the search for diagnostic patterns, the stage of selecting transformation parameters becomes extremely important in the process of preparing training data for evaluation algorithms. This paper investigates the influence of the STFT computational window size on the material state evaluation results obtained using convolutional neural network (CNN). The studies were performed for MBN signals obtained from grain-oriented electrical steel with anisotropic properties. The carried out work made it possible to draw connections on the importance of the choice of the window during the implementation of CNN network training.
Monitoring and Prediction of Land Surface Phenology Using Satellite Earth Observations—A Brief Review
Authors: Gašparović Mateo , Pilaš Ivan , Radočaj Dorijan , Dobrinić Dino
Published: December 2024

Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, and forest and agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the advancement of LSP research, enabling global and continuous monitoring of vegetation cycles. This review provides a brief overview of key EO satellite missions, including the advanced very-high resolution radiometer (AVHRR), moderate resolution imaging spectroradiometer (MODIS), and the Landsat program, which have played an important role in capturing LSP dynamics at various spatial and temporal scales. Recent advancements in machine learning techniques have further enhanced LSP prediction capabilities, offering promising approaches for short-term prediction of vegetation phenology and cropland suitability assessment. Data cubes, which organize multidimensional EO data, provide an innovative framework for enhancing LSP analyses by integrating diverse data sources and simplifying data access and processing. This brief review highlights the potential of satellite-based monitoring, machine learning models, and data cube infrastructure for advancing LSP research and provides insights into current trends, challenges, and future directions.
Sintering with Sodium Carbonate and Leaching of Wolframite Cakes
Authors: Baimbetov Bolotpay , Tazhiyev Yeleussiz , Yeleuliyeva Akmaral , Moldabayeva Gulnara , Dauletbakova Adelya , Yakob Yelena , Taimassova Akbota
Published: December 2024

Focuses on the processing of tungsten raw materials through various operations, including sintering, leaching, purification, and the production of technical tungstic acid. Modern research aims to enhance these processes, particularly the sintering of wolframite concentrates with alkali metal compounds and the leaching of concentrates and cakes. Experiments revealed that reactions between tungsten minerals and sodium carbonate from Akchatau ores commence at temperatures above 520–550 °C, intensifying between 750 and 850 °C. The concentrates were sintered at 750, 800, and 850 °C with a sodium carbonate excess coefficient of 1.05 to 1.2 to evaluate the effect on sodium tungstate extraction. Water leaching was conducted under a probabilistic–deterministic experimental design, analyzing five factors at four levels. Tungsten extraction was assessed based on solution density and the composition of the insoluble residue. Data processing established polynomial trends for tungsten trioxide extraction, and a material balance for sinter leaching was calculated from experiments using 100 g samples with a liquid-to-solid ratio of 2:1. The findings can be applied to improve tungsten processing technologies.
A Country Risk Assessment from the Perspective of Cybersecurity in Local Entities
Authors: Sanchez-Zurdo Javier , San-Martín Jose
Published: December 2024

The number of vulnerabilities identified annually has increased substantially, thereby raising the risks associated with online services. The implementation of cybersecurity management measures in accordance with the European NIS2 Directive is optional at the local authority level. This study analyzes the external perimeter of nearly 7000 municipalities and proposes a simplified security framework that provides a comprehensive view of security across regions. A complete data set was assembled on the Technological and Competence profiles of all municipalities in Spain over a two-year period. The data were gathered from the external perimeter in relation to security, availability and SEO posture areas. A survey was conducted to determine the level of concern among citizens regarding cybersecurity issues in online municipal services, with 188 respondents. Some regions were identified as exhibiting particularly high and homogeneous levels of security. In contrast, other regions were found to be below the expected level. The presence of supra-local entities, such as the “Diputaciones”, has been demonstrated to facilitate the harmonization of regional security, while simultaneously reducing technological fragmentation and operational expenditure.
Application of Machine Learning for Estimating the Physical Parameters of Three-Dimensional Fractures
Authors: Akmal Fadhillah , Nurcahya Ardian , Alexandra Aldenia , Yulita Intan Nurma , Kristanto Dedy , Dharmawan Irwan Ary
Published: December 2024

Hydrocarbon production in the reservoir depends on fluid flow through its porous media, such as fractures and their physical parameters, which affect the analysis of the reservoir’s physical properties. The fracture’s physical parameters can be measured conventionally by laboratory analysis or using numerical approaches such as simulations with the Lattice Boltzmann method. However, these methods are time-consuming and resource-intensive; therefore, this research explores the application of machine learning as an alternative method to predict the physical parameters of fractures such as permeability, surface roughness, and mean aperture. Synthetic three-dimensional digital fracture data that resemble real rock fractures were used to train the machine learning models. These included two convolutional neural networks (CNNs) designed and implemented in this research—which are referred to as CNN-1 and CNN-2—as well as three pre-trained models—including DenseNet201, VGG16, and Xception. The models were then evaluated using the R2 and mean absolute percentage error (MAPE). CNN-2 was the best model for accurately predicting the three fracture physical parameters but experienced a drop in performance when tested on real rock fractures.
Investigation of Effects of Feed Rate and Cutting-Edge Angle Variation on Surface Roughness in External Cylindrical Turning Process of Ms58 Brass Material
Authors: Ateş Ergun , Serbest Nefise
Published: December 2024

The Ms58 brass material was machined dry by the lathe’s external cylindrical surface turning method. Three different feeds (0.155, 0.088, and 0.028 mm/rev), 3 different cutting-edge angles (70°, 80°, and 90°), and three-spindle speeds (480, 630, and 1250 rpm) were used in machining experiments. The depth of the cut value was taken as a 0.5 mm constant. The effects of these different parameters on surface roughness values were investigated. For each surface roughness value measured from parts machined with other parameters, measurements were made five times, the largest and smallest values were discarded, and the average of the remaining 3 values was taken. This rigorous process of data collection ensured the reliability of the results. Graphs were prepared and examined with working parameters and surface roughness values. As a result, it was determined that the surface roughness value decreased with the decrease in feed and the increase in another parameter, the “cutting-edge angle” of the tool. When external cylindrical surface turning was performed with the experimental parameters of 480 rpm, a large cutting-edge angle of 90°, and a depth of cut of 0.5 mm within this study plan, the lowest average surface roughness was obtained as 1.228 µm.
H∞ Consistency of T-S Fuzzy Supply Chain System Based on Trust Mechanism
Authors: Huang Yong , Li Qingkui
Published: December 2024

As the market environment becomes increasingly complex, the demands for supply chain performance and security are continuously rising. Consequently, it is crucial to consider the role of trust factors within the system. This paper introduces a trust mechanism in the interaction between supply and demand within supply chain logistics and information flow. The supply chain system, characterized by varying degrees of trust, is modeled as multiple subsystems using the T-S fuzzy model. The challenge of mitigating the bullwhip effect, which refers to the amplification of demand variability within the supply chain, is reformulated as an H∞ consistency problem. A productivity and distributed consistency protocol switching controller based on fuzzy rules is designed, providing sufficient conditions for the entire system to achieve consistency. The proposed method effectively suppresses the bullwhip effect and allows certain nodes in the system to be temporarily in an abnormal state. Finally, the method’s effectiveness is validated through simulation examples.
Precise Pre-Close Wind Volume Calculation for Aluminum Electrolysis Based on Unscented Kalman and Average Filters
Authors: Zhao Jiawei , Wang Mengfan , Hu Xue , Zhang Lixin
Published: December 2024

To improve the accuracy of calculating the aluminum electrolysis pre-close wind volume, this study focused on optimizing the two main factors that influence its magnitude: the aluminum output speed and the pre-close wind volume coefficient. First, the Unscented Kalman Filter (UKF) algorithm was used to estimate the aluminum output speed, and its application in real production was verified through simulation experiments. The results demonstrate that UKF provides more accurate speed estimates when handling the non-linear dynamic system of aluminum electrolysis. When there was a sudden change in speed, the UKF achieved a relative error of only 0.0373%, significantly lower than the 2.52% error of the traditional Kalman Filter (KF). At the same time, the UKF exhibited a shorter runtime in the simulation. Additionally, this research introduces a self-correction mechanism for the pre-close wind volume coefficient for the first time. By dynamically adjusting the parameter based on aluminum output deviations and applying the Average Filter (AF) to improve the compensation accuracy, the pre-close wind volume coefficient can be precisely calculated. The combination of these methods significantly enhances the accuracy and robustness of pre-close wind volume calculations, providing solid theoretical foundations and the technical support needed to achieve high-precision aluminum output control.
Switch Rail Reduction Value Deviation’s Impact on Wheel–Rail Dynamic Interaction and Its Efficient Identification Method: A Numerical and Experimental Study
Authors: Wang Pu , Ma Qiantao , Liu Ji , Xu Jingmang
Published: December 2024

Railway turnout is a critical railway infrastructure that guides trains in switching tracks. Over time, uneven rail wear can lead to switch rail reduction value (SRRV) deviation, a typical structural defect that compromises turnout functionality and jeopardizes train operation safety. Current SRRV deviation detection methods rely primarily on inefficient manual inspections, making it difficult to ensure operational safety. To address this issue, the study carried out a comprehensive investigation combining numerical and experimental analyses. First, a rigid–flexible coupled dynamics model of a vehicle-turnout system was developed to analyze the wheel–rail dynamic interaction forces and contact relationships under various SRRV deviation conditions. The results revealed that SRRV deviation significantly affects both wheel–rail interaction forces and the turnout structural irregularity wavelength. Thus, based on discrete wavelet transform (DWT), a wheel–rail force trend component was derived that can effectively analyze the turnout structural irregular wavelength, and the mapping relationship between SRRV deviation and the wheel–rail force trend component was then established. Finally, an efficient and accurate method for identifying SRRV deviation based on wheel–rail force trend component was proposed and validated using field-measured data from trains passing through turnouts. This study contributes to the timely detection of track defects, helping to prevent safety incidents during train operations.
Sirtuin 1 and Hormonal Regulations in Aging
Authors: Keremidarska-Markova Milena , Sazdova Iliyana , Mladenov Mitko , Pilicheva Bissera , Zagorchev Plamen , Gagov Hristo
Published: December 2024

Aging affects the structure and functions of all organs and systems in the organism. In the elderly, significant changes in hormonal levels are observed. These translate to a predisposition for chronic diseases, including cardiovascular, neurodegenerative, and metabolic disorders. Therefore, tremendous scientific effort is focused on investigating molecular mechanisms and drugs with the potential to reduce hormonal changes in old age and their impact. Sirtuin 1 (SIRT1), a member of the sirtuin family of deacetylases, has been extensively studied as a regulator of multiple pathways related to antioxidant properties, optimal immune response, and metabolism. SIRT1 plays a key role in regulating various hormonal pathways and maintaining homeostasis. In the present study, we review the interplay between SIRT1 and hormonal regulations, including the endocrine role of the hypothalamic–pituitary–thyroid, –adrenal, –gonadal, and –liver axes, of other endocrine glands, and of non-endocrine tissues in the aging organism. The application of natural SIRT1 activators, such as resveratrol, curcumin, paeonol, and Buyang Huanwu Decoction, for the treatment of aging and senescence is discussed. SIRT1 activators improve mitochondrial function, reduce oxidative stress, and promote longevity, but their clinical application is limited by low bioavailability and poor permeability across biological barriers. For this reason, advanced delivery strategies are being considered, including nose-to-brain drug delivery and nanotechnology-based formulations.