bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial Correlation Network Structure of and Factors Influencing Technological Progress in Citrus-Producing Regions in China
Authors: Gu Yumeng , Qi Chunjie , He Yu , Liu Fuxing , Luo Beige
Published: November 2023

In this study, the transcendental logarithmic cost function model was used to measure the rate of technological progress in seven major mandarin-producing regions and seven major tangerine-producing regions in China from 2006 to 2021. The modified gravity model was used to establish spatial correlation networks. The social network analysis method was used to analyze the characteristics of the overall network structure and the individual network structure of the spatial correlation networks of citrus-production technology progress, and the quadratic assignment procedure was used to analyze the factors influencing the spatial network. The results show the production of Chinese mandarins and tangerines is in the stage of technological progress in general, but the rate of progress is slowing down gradually, and the rate of mandarin-production technology progress is higher than that of tangerine-production technology progress. In terms of the overall network structure characteristics, the spatial networks of technological progress related to Chinese mandarin and tangerine production are becoming increasingly dense and complex, with obvious spatial spillover effects, but the network structure is relatively loose, and the polarization of the tangerine network is more serious. In terms of individual network structure characteristics, the relatively economically developed eastern regions have a higher status in terms of the spatial correlation network and a stronger role in controlling and dominating the resource elements needed for citrus-production technology progress. Education, informatization, economic development, innovation support, and financial support are important factors influencing the formation of the spatial association network of citrus-production technology progress in China.
Evaluation of Alternative-Design Cotton Gin Lint Cleaning Machines on Fiber Length Uniformity Index
Authors: Armijo Carlos B. , Delhom Christopher D. , Whitelock Derek P. , Tumuluru Jaya Shankar , Yeater Kathleen M. , Blake Cody D. , Rowe Chandler , Wanjura John D. , Sui Ruixiu , Holt Gregory A. , Martin Vikki B. , Kothari Neha
Published: November 2023

Developing cotton ginning methods that improve fiber length uniformity index to levels that are compatible with newer and more efficient spinning technologies would expand market share and increase the demand for cotton products and give U.S. cotton a competitive edge to synthetic fibers. Older studies on lint cleaning machines showed that the most widely used feed mechanism that places fiber on the cleaning cylinder damages the fiber and reduces uniformity. The present study evaluates how conventional and experimental feed mechanisms affect uniformity. The lint cleaners were used with both saw and roller gin stands. Four diverse cotton cultivars from the Far West, Southwest, and Mid-South were used in the test. Statistical analysis used a random effects modeling approach which included constructing a 95% confidence interval for each ginning treatment around the predicted mean for the fiber property of interest, and then examining which treatments overlap (for comparison). Results show that the micro-saw gin with the direct-feed lint cleaner had the best uniformity at 85.8%. Prior research has shown that roller ginning is consistently higher in uniformity than any type of saw ginning. In this study, the roller ginning treatments had uniformities of 85.3 and 85.6%, so it is encouraging that the saw gin stand with the direct-feed lint cleaner had very high uniformity. This suggests that it may be beneficial to place fiber directly onto the lint cleaning saw without changing direction. Additionally, the saw gin-coupled lint cleaner had a uniformity of 84.3% which is also a respectable level of uniformity. These results indicate that the direct-feed lint cleaner and coupled lint cleaner warrant further testing under better controlled conditions.
Antioxidant Capacity in Two Different Cultivars of Ripe and Unripe Peaches Utilizing the Cloud-Point Extraction Method
Authors: Giovanoudis Ioannis , Athanasiadis Vassilis , Chatzimitakos Theodoros , Kalompatsios Dimitrios , Mantiniotou Martha , Bozinou Eleni , Gortzi Olga , Nanos George D. , Lalas Stavros I.
Published: November 2023

In this study, the objective was to ascertain the optimal extraction method for the recovery of polyphenols from two peach cultivars, namely ‘Andross’ and ‘Everts’, at unripe and ripe stages. Two extraction techniques were explored: conventional extraction and cloud-point extraction (CPE), utilizing various solvents, including water, ethanol, 60% ethanol, and the surfactant Tween 80. Moreover, the conditions of CPE (such as pH, ionic strength, surfactant concentration, etc.) were optimized. To elucidate the antioxidant activity of the extracts, the total polyphenol content (TPC), the ferric-reducing antioxidant power (FRAP) assay, and the DPPH antiradical scavenging were measured. Our findings indicate that CPE is a superior method for polyphenol recovery. Unripe fruits had more antioxidants than ripe ones. Unripe ‘Andross’ fruit has a TPC of 1465.32 mg gallic acid equivalents per kilogram (mg GAE/kg). FRAP and DPPH levels were 7.33 and 5.12 mmol ascorbic acid equivalents (AAE/kg), respectively. With a TPC of 1714.53 mg GAE/kg, the unripe fruit from the ‘Everts’ cultivar has even more antioxidant capacity. Additionally, its FRAP and DPPH values were increased at 8.57 and 6.08 mmol AAE/kg, respectively. These findings underscore the efficacy of CPE as a preferred method for polyphenol extraction while also highlighting the enhanced antioxidant potential of unripe peaches, particularly in the ‘Everts’ cultivar.
Dynamic of Phenolic Compounds in Guadua angustifolia Kunth under Chemical, Organic, and Biological Fertilization
Authors: Sánchez-Matiz Juan José , Lozano-Puentes Hair Santiago , Villamarín-Raad David A. , Díaz-Gallo Sergio A. , Díaz-Ariza Lucía Ana
Published: November 2023

Guadua angustifolia produces phenolic compounds, and this production may be influenced by the application of chemical, organic, and biological fertilizers. Currently, the effect of such fertilizers on the synthesis dynamics of this group of metabolites in bamboo is unknown. In this study, the total phenolic content (TPC) and total flavonoid content (TFC) in the leaves of plants fertilized with diammonium phosphate (DAP) and humus in combination with the biofertilizers Promofort®, Azospirillum brasilense, Pseudomonas fluorescens, and Stenotrophomonas sp. were determined using colorimetric techniques across three sampling events (four, five, and seven months after planting). Additionally, an approximation of the bacterial profile of G. angustifolia roots was performed using the DGGE-PCR fingerprint technique. Through repeated measures ANOVA (rmANOVA), it was determined that there is no statistically significant three-way interaction between humus or DAP application, biological fertilizers, and time for either TPC or TFC. However, there were interactions between the sampling event and the application of biological fertilizers for both TPC and TFC, with the latter being promoted by the application of Promofort®. Finally, NMDS analyses and heatmaps with hierarchical clustering showed that the composition and abundance of OTUs in the bacterial profile varied with fertilization type and increased over time.
Genome-Wide Association Study for Yield and Yield-Related Traits in Chinese Spring Wheat
Authors: Tian Yousheng , Liu Pengpeng , Cui Fengjuan , Xu Hongjun , Han Xinnian , Nie Yingbin , Kong Dezhen , Sang Wei , Li Weihua
Published: November 2023

Wheat (Triticum aestivum L.) is one of the important grain crops that fulfill global food security requirements. Understanding the genetic basis of wheat yield and related traits is crucial for increasing yield through marker-assisted selection (MAS). In this study, a phenotypic analysis was conducted on the yield and related traits of 192 Chinese spring wheat genotypes in six field environments. Based on the 90K wheat SNP iSelect assay, a genome-wide association study (GWAS) identified 84 stable and significantly associated signals at 50 loci for 8 out of the 10 analyzed traits. These traits included grain yield (1), plant height (6), spike length (21), productive spikelet rate (12), kernel number per spikelet (1), kernel number per main spike (2), thousand kernel weight (5), and test weight (2). Seventy-one stable SNP markers were mapped to annotated genes, with 51 of them located in the coding sequences (CDSs) of 47 explanatory genes. Haplotype analysis revealed three blocks on chromosome 5A and two blocks on chromosome 5D associated with plant height (PH). Varieties with different haplotypes at these loci displayed a significant difference in plant height. The performance of traits was improved by increasing the number of superior alleles for productive spikelet rate and spike length. These results provided prospective alleles for controlling yield and yield composition in wheat breeding. These alleles could be used for marker-assisted selection to improve wheat yield.
Optimizing the Growth of Silage Maize by Adjusting Planting Density and Nitrogen Application Rate Based on Farmers’ Conventional Planting Habits
Authors: Qian Yinsen , Ma Quan , Ren Zhen , Zhu Guanglong , Zhu Xinkai , Zhou Guisheng
Published: November 2023

Silage maize is cultivated due to its high nutritional value as a forage. China’s recent agricultural policy promotes the popularization and cultivation of silage maize. The production of silage maize is affected by planting density and nitrogen application. Based on investigating the planting habits of local farmers, we adjusted the planting density and nitrogen application rate to optimize the growth of silage maize. This study was conducted to investigate the effects of planting density (65,000 plant ha−1 (D1), 80,000 plant ha−1 (D2), and 95,000 plant ha−1 (D3)) and nitrogen rate (150 kg ha−1 (N1), 230 kg ha−1 (N2), and 310 kg ha−1 (N3)) on growth, yield, and quality of silage maize using a two-factor random block design. Planting density and nitrogen fertilizer significantly affected plant height, stem diameter, leaf area index, crude protein, neutral detergent fiber, acid detergent fiber, and starch of silage maize. In summary, the combination of a planting density of 80,000 plants ha−1 and a nitrogen application rate of 310 kg ha−1 produced a higher crude protein and starch yield and better palatability and quality; this result can aid silage maize growth.
Refinement of Animal Experiments: Replacing Traumatic Methods of Laboratory Animal Marking with Non-Invasive Alternatives
Authors: Klabukov Ilya , Shestakova Victoria , Krasilnikova Olga , Smirnova Anna , Abramova Olga , Baranovskii Denis , Atiakshin Dmitri , Kostin Andrey A. , Shegay Peter , Kaprin Andrey D.
Published: November 2023

Reliable methods for identifying rodents play an important role in ensuring the success of preclinical studies. However, animal identification remains a trivial laboratory routine that is not often discussed, despite the fact that more than 6 million rodents are used in animal studies each year. Currently, there are extensive regulations in place to ensure adequate anesthesia and to reduce animal suffering during experiments. At the same time, not enough attention is paid to the comfort of rodents during routine identification procedures, which can be painful and cause some complications. In order to achieve the highest ethical standards in laboratory research, we must minimize animal discomfort during the identification phase. In this article, we discuss traumatic methods of identification and describe several painless methods for marking in long-term experimental studies. The use of non-traumatic and non-invasive methods requires the renewal of marks as they fade and additional handling of the rodents. Laboratory personnel must be trained in stress-minimizing handling techniques to make mark renewal less stressful.
Multiparametric Comparison of Two TTA-Based Surgical Techniques in Dogs with Cranial Cruciate Ligament Tears
Authors: Figueirinhas Pedro , Gonzalo-Orden José Manuel , Rodriguez Oliver , Regueiro-Purriños Marta , Prada Ivan , Vilar José Manuel , Rodríguez-Altónaga José
Published: November 2023

Tearing of the cranial cruciate ligament causes hindlimb lameness in dogs. Different surgical procedures have been proposed to treat this condition. In this study, two different TTA-based techniques and implants were compared. A total of 30 dogs were separated into two groups according to the technique and implant used (Porous TTA® or Model Xgen®). The aim of the study was to assess whether one of these techniques has better functional recovery of the joint, better bone consolidation after the osteotomy procedure and fewer osteoarthritic changes. We compared both groups up to 3 months after surgery. No significant differences were found in any of the assessed parameters. Thus, both procedures were found to be equally effective and safe.
Mechanisms of Digestive Enzyme Response to Acute Salinity Stress in Juvenile Yellowfin Tuna (Thunnus albacares)
Authors: Zhang Ninglu , Yang Rui , Fu Zhengyi , Yu Gang , Ma Zhenhua
Published: November 2023

This study investigates the effect of a sudden change in salinity for 48 h on the digestive enzyme activity of juvenile yellowfin tuna. The treatment included a control salinity of 32‰ in natural seawater and an experimental salinity of 29‰. Acute stress experiments were carried out on 72 juvenile yellowfin tuna (646.52 ± 66.32 g) for 48 h to determine changes in digestive enzyme activity in different intestinal sections over time (0 h, 12 h, 24 h, 48 h). The activities of pepsin, trypsin, α-amylase, lipase, and chymotrypsin in the digestive organs (stomach, foregut, and pyloric ceca) of juvenile yellowfin tuna were measured. Pepsin and pancreatic protease in the experimental group were significantly lower than in the control group (p < 0.05). α-amylase showed a fluctuating trend of decreasing and then increasing, and its activity trend was pyloric ceca > foregut > stomach. The lipase activity of gastric tissues decreased at the beginning and then increased, reaching a minimum at 24 h (2.74 ± 1.99 U·g protein−1). The change of lipase in the pyloric ceca and foregut was increasing and then decreasing. The lipase activity trend was pyloric ceca > foregut > stomach. The chymotrypsin showed a decreasing and increasing trend and then stabilized at 48 h with a pattern of pyloric ceca > foregut > stomach. Similarly, the gut villi morphology was not significantly altered in the acutely salinity-stressed compared to the non-salinity-stressed. This study suggests that salinity may change the digestive function of juvenile yellowfin tuna, thereby affecting fish feeding, growth, and development. On the contrary, yellowfin tuna is highly adapted to 29‰ salinity. However, excessive stress may negatively affect digestive enzyme activity and reduce fish digestibility. This study may provide a scientific basis for a coastal aquaculture water environment for yellowfin tuna farming, which may guide the development and cultivation of aquaculture.
Validity and Repeatability Characteristics of a Non-Invasive, Infrared-Based Method Estimating Plasma Indocyanine Green Decay in Healthy Dogs
Authors: Honkavaara Juhana , Grobelna Agnieszka , Restitutti Flavia , Kallio-Kujala Ira , Raekallio Marja , Spillmann Thomas
Published: November 2023

Plasma clearance of indocyanine green (ICG-CL) is an invasive method to evaluate liver dysfunction. We aimed to investigate the practicality of a noninvasive, transcutaneous, infrared-based method estimating the disappearance rate of indocyanine green (ICG-PDR). In a randomized, cross-over study, both ICG-CL and ICG-PDR were determined in eight healthy dogs while conscious and when sedated with medetomidine and medetomidine–vatinoxan. ICG-PDR was further repeated in six of the dogs to assess its repeatability. Differences were tested with repeated-measures analysis of variance and post hoc t-tests with Bonferroni corrections, while associations were evaluated by both Spearman and Pearson correlation analyses. Furthermore, repeatability was assessed by examining calculated coefficients of variation (CV). A significant decrease in ICG-CL was observed in dogs sedated with medetomidine, while no difference between conscious and sedated states was detected with ICG-PDR. Overall, correlations between ICG-CL and ICG-PDR were poor, as was the intrasubject repeatability of ICG-PDR in conscious dogs with CV consistently above 20%. While some of the results may be explained by poor signal quality for the non-invasive method, we conclude that in healthy dogs ICG-PDR performed poorly.
Situation Analysis and Recommendations for the Biosecurity Status of Dairy Farms in Punjab, India: A Cross-Sectional Survey
Authors: Dhaka Pankaj , Chantziaras Ilias , Vijay Deepthi , Singh Manmeet , Bedi Jasbir Singh , Caekebeke Nele , Dewulf Jeroen
Published: November 2023

Farm biosecurity is an important herd management strategy to assure infection prevention and animal health. The present study aimed to evaluate the implementation of biosecurity measures on dairy farms in Punjab, India, using the standardized Biocheck.UGent™ scoring system. Convenience sampling was used to select 94 dairy farms, comprising both cattle and buffaloes, with a mean herd size of 74.8 animals. The study found that the mean external and internal biosecurity scores for the selected dairy farms were 45.4% and 43.7%, respectively. Among the subcategories, the highest external biosecurity score was observed for ‘vermin control and other animals’ (63%), and the highest internal biosecurity score was observed for ‘adult cattle management’ (76.6%). Whereas the lowest score for external biosecurity was observed for ‘purchase and reproduction’ (30.6%), and the lowest score for internal biosecurity was observed for ‘health management’ (33.6%). The overall mean biosecurity score of the present study was 44.8%, which was lower than the overall mean global score of 52%. The correlation analysis indicated a positive correlation between herd size and overall biosecurity scores, indicating that larger farms had, on average, higher biosecurity scores. Based on these results, it can be concluded that the implementation of biosecurity measures on dairy farms in Punjab needs improvement, especially in the subcategories of ‘purchase and reproduction’ and ‘health management’. Further research to identify the factors influencing the implementation of biosecurity measures on dairy farms in the region is recommended.
Conventional Feed-Grade or Slow-Release Coated Urea as Sources of Dietary Nitrogen for Fattening Lambs
Authors: Saro Cristina , Degeneffe Miguel Alonso , Andrés Sonia , Mateo Javier , Caro Irma , López-Ferreras Lorena , Horst Egon Henrique , López Secundino , Giráldez Francisco Javier
Published: November 2023

Twenty-two Assaf male lambs (29.2 ± 0.9 kg live weight and 89 ± 0.2 days of age), distributed in two experimental groups, were used to evaluate the use of either feed-grade conventional urea (Control diet; n = 11) or slow-release urea (SRU diet; n = 11) as sources of dietary nitrogen on animal performance, ruminal fermentation, blood acid-base status, plasmatic metabolic profile, and carcass and meat quality. Animals were housed individually and fed ad libitum. At the end of the fattening period (day 70), the animals were slaughtered to compare the fermentation patterns in ruminal digesta and to evaluate the carcass and meat characteristics. No statistically significant differences (p > 0.05) were observed between treatments in the dry matter intake, final live weight, average daily gain, and feed conversion rate. Regarding the ruminal fermentation parameters, the molar proportion of propionic acid was higher (p < 0.05) and that of butyric acid was lower (p < 0.05) with the SRU than with the Control diet. There were no significant differences (p > 0.05) between experimental treatments in the blood acid-base status and biochemical profile, except for the concentration of urea in plasma, which was significantly (p < 0. 05) greater in SRU than in Control lambs. No statistically significant differences were observed between treatments (p > 0.05) in the carcass and meat characteristics. In conclusion, the use of slow-release urea as a replacement for feed-grade conventional urea in the diet of Assaf fattening lambs, under the experimental conditions of this study, did not improve animal performance and increased the feeding costs.
New Anti-RSV Nucleoprotein Monoclonal Antibody Pairs Discovered Using Rabbit Phage Display Technology
Authors: Baurand Pierre-Emmanuel , Balland Jérémy , Galli Emilia , Eklin Suvi , Bruley Rémy , Ringenbach Laurence
Published: November 2023

Human respiratory syncytial virus (hRSV) is one of the major contagious viruses and causes complicated respiratory issues, especially in young children. The sensitive and fast detection of hRSV is critical for taking the most effective actions. In the present study, rabbit antibodies against the hRSV nucleoprotein (NP) were developed using phage display technology. A female rabbit was immunized with an hRSV strain A2 recombinant NP. A Fab library was built and sorted during two successive panning rounds for strain B and the A2 NP (recombinant preparations), respectively. The choice of candidates was performed using ELISA on the two NP strains. The obtained library was 3 × 106 cfu/mL, with an insertion rate of >95%. The two panning rounds permitted an enrichment factor of 100. ELISA screening allowed us to obtain 28 NP-specific Fab candidates. Among them, 10 retained candidates were reformatted into rabbit full IgG; thereafter, pairing tests on the recombinant strains and native lysate samples were performed. After the pairing tests on the recombinant strains, 53 pairs were identified. Eleven pairs were identified as being able to detect RSVs from native lysates. This work presents new high-potential monoclonal antibodies mAbs (mAbs), which would benefit from lateral flow testing data with patient materials.
The Phenolic Composition, Antioxidant Activity and Microflora of Wild Elderberry in Asturias (Northern Spain): An Untapped Resource of Great Interest
Authors: Rodríguez Madrera Roberto , Pando Bedriñana Rosa
Published: November 2023

The objective of this study is the characterization of the phenolic profile and antioxidant activity of elderberries (Sambucus nigra L.) from a collection of 79 wild specimens in northern Spain to assess variations in the species at the local level and evaluate its interest as a source of biocompounds. Also, a first study was carried out on the microflora present in this fruit, providing information relevant to its commercial exploitation. Moreover, the phenolic composition, antioxidant capacity and microbial composition in overripe fruits were determined, seeking a better use for this currently wasted resource. A wide variability in levels of phenolics was detected. Elderberries showed high antioxidant activity related to a high cyanidin derivative content, making them of interest to industry. Microflorae were present in very variable concentration ranges, so their levels should be monitored in those applications that require strict control. Overripe fruits are of interest as a source of anthocyanidins, since their concentration and antioxidant capacity remain after the optimal ripening period, promoting sustainability and a better use of natural resources. The database generated is of particular interest for further breeding trials based on the phenolic profile and antioxidant activity of the samples.
Tocotrienols Provide Radioprotection to Multiple Organ Systems through Complementary Mechanisms of Antioxidant and Signaling Effects
Authors: Shrum Stephen A. , Nukala Ujwani , Shrimali Shivangi , Pineda Edith Nathalie , Krager Kimberly J. , Thakkar Shraddha , Jones Darin E. , Pathak Rupak , Breen Philip J. , Aykin-Burns Nukhet , Compadre Cesar M.
Published: November 2023

Tocotrienols have powerful radioprotective properties in multiple organ systems and are promising candidates for development as clinically effective radiation countermeasures. To facilitate their development as clinical radiation countermeasures, it is crucial to understand the mechanisms behind their powerful multi-organ radioprotective properties. In this context, their antioxidant effects are recognized for directly preventing oxidative damage to cellular biomolecules from ionizing radiation. However, there is a growing body of evidence indicating that the radioprotective mechanism of action for tocotrienols extends beyond their antioxidant properties. This raises a new pharmacological paradigm that tocotrienols are uniquely efficacious radioprotectors due to a synergistic combination of antioxidant and other signaling effects. In this review, we have covered the wide range of multi-organ radioprotective effects observed for tocotrienols and the mechanisms underlying it. These radioprotective effects for tocotrienols can be characterized as (1) direct cytoprotective effects, characteristic of the classic antioxidant properties, and (2) other effects that modulate a wide array of critical signaling factors involved in radiation injury.
Investigation of the Application of Complex Function Theory in Underground Mine Design: A Case Study
Authors: Tan Lihai , Peng Huaide , Si Xuefeng , Lin Qibin
Published: November 2023

This study, with the engineering background of the design of a stope involving a sublevel mining method in a certain underground metal mine, explored the application of stress-solving methods based on the complex variable function theory in actual engineering. Three mathematical calculation models based on the functions of a complex variable were established. Through triangle interpolation, mapping functions of a plane with a roadway section and a plane with the stope section were determined. An improved Schwarz alternating method was adopted to study the stability of the roadway and the influence of an adjacent roadway from the perspective of the stress field. In addition, in light of the distribution characteristics of a gangue in the stope, the design parameters of a pillar were optimized, with the pillar’s optimal dimensions determined. The results showed that when the magnitudes of two far-field principal stresses in the rock mass are relatively close, the distribution of the surrounding rock stress around the roadway is more uniform, and tensile stress is less likely to occur. The excavation of a neighboring roadway exacerbates to some extent the side stress of the other roadway, especially the compressive stress concentration on the side closer to the neighboring roadway. However, when the distance between the two roadways is significantly larger than the roadway size, this effect is not pronounced. In the engineering case studied in this research, the thickness of the pillar is approximately linearly positively correlated with the safety factor of the pillar approximately linearly negatively correlated with the recovery rate. Overall, this research explored the application of the complex variable function theory in an underground mine design, demonstrating its accuracy and practicality.
The Simulation of Dielectric Barrier Discharge for Breakdown Voltage in Starch Modification
Authors: Chankuson Pitchasak , Chumsri Paramee , Plodkaew Apinun
Published: November 2023

This paper presents the simulation results for dielectric barrier discharge (DBD) at atmospheric pressure in argon gas for different relative permittivity, granule shape, thickness layer, and granule diameter measurements for starch on the breakdown voltage. DBD is commonly utilized to generate cold plasma for starch modification. The electric field was computed using COMSOL Multiphysics 5.3a software. The breakdown voltage was calculated employing Paschen’s law for this electric field. The voltage was found according to the breakdown criterion for gap distance 0.2–1.0 cm, and then the Paschen curve could be plotted. The results show that the top electrode of the plasma system may be replaced with the parallel plate electrode by a mesh electrode with a bigger mesh size to achieve a lower breakdown voltage. In addition, increasing the relative permittivity and decreasing the thickness layer can reduce the applied voltage for plasma formation. When compared to the sphere and ellipsoid shapes, starch with a polyhedral granule shape requires a significantly lower voltage for breakdown. The starch granule diameter does not affect the breakdown voltage. These findings can be utilized to determine the optimal breakdown voltage for each type of starch modification, contributing to the construction of a high-efficiency plasma production system for starch modification.
A Hybrid Architectural Model for Monitoring Production Performance in the Plastic Injection Molding Process
Authors: Luisi Gerardo , Di Pasquale Valentina , Pietronudo Maria Cristina , Riemma Stefano , Ferretti Marco
Published: November 2023

Monitoring production systems is a key element for identifying waste and production efficiency, and for this purpose, the calculation of the Key Performance Indicator (KPI) Overall Equipment Effectiveness (OEE) is validly recognized in the scientific literature. The collection and analysis of the cause of the interruption of the plants is particularly useful in this sense. The use of Internet of Things (IoT) technology in order to automate data collection for the purpose of calculating the OEE and the causes of interruption is effective. Furthermore, the existing literature lacks research studies that aim to improve the data quality of important process data that cannot be collected automatically. This study proposes the use of IoT technologies to request targeted and intelligent information inputs from the operators directly involved in the process, improving the completeness and accuracy of the information through the real-time and smart combination of manual and automated data. The Business Process Model and Notation (BPMN) methodology was used to analyze and redesign the collection data process and define the architectural model with a deep knowledge of the specific process. The proposed architecture, designed for application to a plastic injection molding production line, comprises several elements: the telemetry of the injection molding machine, an intervention request system, an intervention tracking system, and a human–system interface. Furthermore, a dashboard was developed using the Power BI software, 2.122.746.0 version, to analyze the information collected. Reducing the randomness of manual data makes it possible to direct production efficiency efforts more effectively, helping to reduce waste and production costs. Reducing production costs appears to be strongly linked to reducing environmental impacts, and future studies will be able to quantify the benefits obtained from the solution in terms of environmental impact.
A Comprehensive Survey of Machine Learning Methodologies with Emphasis in Water Resources Management
Authors: Drogkoula Maria , Kokkinos Konstantinos , Samaras Nicholas
Published: November 2023

This paper offers a comprehensive overview of machine learning (ML) methodologies and algorithms, highlighting their practical applications in the critical domain of water resource management. Environmental issues, such as climate change and ecosystem destruction, pose significant threats to humanity and the planet. Addressing these challenges necessitates sustainable resource management and increased efficiency. Artificial intelligence (AI) and ML technologies present promising solutions in this regard. By harnessing AI and ML, we can collect and analyze vast amounts of data from diverse sources, such as remote sensing, smart sensors, and social media. This enables real-time monitoring and decision making in water resource management. AI applications, including irrigation optimization, water quality monitoring, flood forecasting, and water demand forecasting, enhance agricultural practices, water distribution models, and decision making in desalination plants. Furthermore, AI facilitates data integration, supports decision-making processes, and enhances overall water management sustainability. However, the wider adoption of AI in water resource management faces challenges, such as data heterogeneity, stakeholder education, and high costs. To provide an overview of ML applications in water resource management, this research focuses on core fundamentals, major applications (prediction, clustering, and reinforcement learning), and ongoing issues to offer new insights. More specifically, after the in-depth illustration of the ML algorithmic taxonomy, we provide a comparative mapping of all ML methodologies to specific water management tasks. At the same time, we include a tabulation of such research works along with some concrete, yet compact, descriptions of their objectives at hand. By leveraging ML tools, we can develop sustainable water resource management plans and address the world’s water supply concerns effectively.
The Effect of Vibrations from Racing Cars on the Human Body in FORMULA STUDENT Races
Authors: Itu Calin , Sorin Vlase
Published: November 2023

During car races, strong vibrations appear in the chassis of the vehicle, due to the high power created by the engine which are then transmitted and, therefore, affect the driver’s condition. The study of these vibrations is a subject frequently addressed by researchers, analyzing the influence of different parameters on the forces to which the pilot’s body or certain sensitive body parts are subjected. In this paper, we analyze the particular case of a racing car made to meet safety requirements in the event of an accident. For the analysis of the forced vibrations induced by the running track, the finite element method was used. This method proved to be a useful and stable modeling and analysis method, validated by practical applications. A standard-equipped racing car with a mannequin inside was studied. Once the natural frequencies of the structure were determined, the response of some points of the mannequin’s body to the movement caused by the running track or the engine was analyzed. Modeling and discretization were performed using well-known classical procedures. The obtained results revealed the parameters that can negatively influence the body of the mannequin which were communicated to the design team. The conclusion of this study is a racing car that was successfully used in Formula Student competitions.
Assessment for Alzheimer’s Disease Advancement Using Classification Models with Rules
Authors: Thabtah Fadi , Peebles David
Published: November 2023

Pre-diagnosis of common dementia conditions such as Alzheimer’s disease (AD) in the initial stages is crucial to help in early intervention, treatment plan design, disease management, and for providing quicker healthcare access. Current assessments are often stressful, invasive, and unavailable in most countries worldwide. In addition, many cognitive assessments are time-consuming and rarely cover all cognitive domains involved in dementia diagnosis. Therefore, the design and implementation of an intelligent method for dementia signs of progression from a few cognitive items in a manner that is accessible, easy, affordable, quick to perform, and does not require special and expensive resources is desirable. This paper investigates the issue of dementia progression by proposing a new classification algorithm called Alzheimer’s Disease Class Rules (AD-CR). The AD-CR algorithm learns models from the distinctive feature subsets that contain rules with low overlapping among their cognitive items yet are easily interpreted by clinicians during clinical assessment. An empirical evaluation of the Disease Neuroimaging Initiative data repository (ADNI) datasets shows that the AD-CR algorithm offers good performance (accuracy, sensitivity, etc.) when compared with other machine learning algorithms. The AD-CR algorithm was superior in comparison to the other algorithms overall since it reached a performance above 92%, 92.38% accuracy, 91.30% sensitivity, and 93.50% specificity when processing data subsets with cognitive and demographic attributes.
Parametric Optimization of a New Gear Pump Casing Based on Weight Using a Finite Element Method
Authors: Zharkevich Olga , Nikonova Tatyana , Gierz Łukasz , Berg Andrey , Berg Alexandra , Zhunuspekov Darkhan , Warguła Łukasz , Łykowski Wikotor , Fryczyński Ksawery
Published: November 2023

Reducing the weight of the structures and choosing the materials used in mechanical engineering is an important and pressing economic and environmental problem. The design of a gear pump is developed from the point of view of the geometry of the gears, as well as the casing. This paper tested a gear pump casing using the environment of the ABAQUS 2020 system in the field of statistical strength analysis using the finite element method. The tests were carried out on the pump body and the front and rear covers, which were made of three types of materials (cast iron, aluminum, and polycarbonate), at a pressure of 28 MPa. After loading, the maximum stresses in the aluminum casing (177 MPa), the cast iron casing (157 MPa), and the polycarbonate (200 MPa) were determined. The largest stress concentrators are the grooves at the bottom of the pump casing. Rounding the internal chamber of the casing with a radius of 4 mm made it possible to reduce stress in this zone by 10 MPa. The parametric optimization of the front and back covers of the gear pump made it possible to reduce the total weight of the aluminum structure by 14%, the cast iron by 12%, and the polycarbonate by 16%. The 3D models show areas of minimal stress where the size and weight of the structure could be reduced in the future using a comprehensive approach involving parametric and topological analysis.
Influence on Physical and Mechanical Properties of Concrete Using Crushed Hazelnut Shell
Authors: Gálvez Cartagena Nicole , Muñoz Araya Grissel , Yanez Sergio J. , González Sepúlveda Sandra , Pina Juan Carlos
Published: November 2023

Concrete production requires a significant amount of natural resources, with aggregates comprising between 55% and 80% of the total volume. However, the over-exploitation of natural aggregates has led to the exploration of alternative materials for use in concrete production. In this study, crushed hazelnut shells were investigated as a partial replacement for fine aggregate, addressing the problem of natural resource depletion and offering a second use for this important agricultural waste product available in Chile. Hazelnut shells were incorporated in percentages of 2.5%, 5%, and 10% by weight of sand for water/cement ratios of 0.4 and 0.5. The compressive strength at 7 and 28 days and bending strength at 28 days were determined, alongside physical properties such as the workability, temperature, air content, fresh density, and hardened density of the concrete. Our findings showed that replacing 2.5% of the fine aggregate with hazelnut shells led to a higher compressive strength at 28 days, exceeding the strength of the standard specimens by 9.5%, whereas replacing 5% of the fine aggregate led to the highest bending strength, exceeding the strength of the standard specimens by 3.5%. Moreover, the 0.4 w/c ratio consistently led to better results for both compressive and bending strength, with fewer and lower reductions in mechanical strength compared to the standard mixture. Our results suggest that concrete mixes with hazelnut shells as a replacement for fine aggregate at a percentage of up to 2.5% can be used in construction systems with a compression strength lower than 17 MPa, and mixtures with up to 10% hazelnut shell replacement can be used in structures with tensile bending stress requirements lower than 6 MPa. Overall, the use of hazelnut shells as a partial replacement for fine aggregate in concrete production presents an environmentally friendly and cost-effective solution for the construction industry.
Advancing Financial Forecasts: A Deep Dive into Memory Attention and Long-Distance Loss in Stock Price Predictions
Authors: Yang Shijie , Ding Yining , Xie Boyu , Guo Yingyi , Bai Xinyao , Qian Jundong , Gao Yunxuan , Wang Wuxiong , Ren Jinzheng
Published: November 2023

In the context of the rapid evolution of financial markets, the precise prediction of stock prices has become increasingly complex and challenging, influenced by a myriad of factors including macroeconomic indicators, company financial conditions, and market sentiment. A model integrating modern machine learning techniques has been introduced in this study, aimed at enhancing the accuracy of stock price prediction. To more effectively capture long-term dependencies in time series data, a novel memory attention module has been innovatively integrated and a unique long-distance loss function has been designed. Through a series of experimental validations, the effectiveness and superiority of this model in the realm of stock price prediction have been demonstrated, especially evident in the R2 evaluation metric, where an impressive score of 0.97 has been achieved. Furthermore, the purpose, methodology, data sources, and key results of this research have been elaborately detailed, aiming to provide fresh perspectives and tools for the field of stock price prediction and lay a solid foundation for future related studies. Overall, this research has not only enhanced the accuracy of stock price prediction but also made innovative contributions in terms of methodology and practical applications, bringing new thoughts and possibilities to the domain of financial analysis and prediction.
Implant Stability in Regenerated Bone
Authors: Caggiano Mario , Acerra Alfonso
Published: November 2023

Bone regeneration is a surgical therapy that is increasingly being used for implant placement in functional patient rehabilitation [...]
Digital Twin-Based Vibration Monitoring of Plant Factory Transplanting Machine
Authors: Chen Kaikang , Zhao Bo , Zhang Yanli , Zhou Liming , Niu Kang , Jin Xin , Xu Bingbing , Yuan Yanwei , Zheng Yongjun
Published: November 2023

In response to the problem of bowl seedling detachment caused by the shaking of the transplanting machine in plant factories, this paper proposes a physical entity monitoring method for the digital twin (DT) plant factory transplanting system. The method is used to analyze the vibration signals of the transplanting machine under different operating conditions and explore the optimal working conditions. Firstly, a demand analysis for the physical entity of the DT plant factory transplanting system is conducted, focusing on practical applications. Then, an optimal deployment plan is designed based on the axiomatic design (AD) theory. Subsequently, a comparative analysis of the operating conditions of the plant factory transplanting equipment is carried out using data-driven approaches. Finally, the optimal working condition parameters are determined by comparing the modal vibration power spectral density of the transplanting equipment under different operating conditions. The results show that the maximum amplitude occurs in the Z-axis, with a magnitude of 2.1 m/s2. By comparing the cloud maps, it is evident that the vibration trends in the Z-axis and X-axis above the transplanting robotic arm are more pronounced compared to the Y-axis. This indicates that under the operating condition of transplanting 3000 plants per hour, a high transplanting efficiency can be maintained, and the vibration signals in the XYZ-axis above the transplanting robotic arm are relatively smooth, making them suitable for transplanting operations. This study combines digital twin technology to analyze the vibration signals of the plant factory transplanting machine under different operating conditions and explore the optimal working conditions. Compared to traditional monitoring platforms, this method facilitates the real-time visualization of different operating conditions of the transplanting machine in a virtual mapping, providing a more intuitive reflection of the equipment operation status.
HAE: A Hybrid Cryptographic Algorithm for Blockchain Medical Scenario Applications
Authors: Chen Ziang , Gu Jiantao , Yan Hongcan
Published: November 2023

The integration of cryptographic algorithms like Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC) is pivotal in bolstering the core attributes of blockchain technology, especially in achieving decentralization, tamper resistance, and anonymization within the realm of medical applications. Despite their widespread utilization, the conventional AES and ECC face significant hurdles in security and efficiency when dealing with expansive medical data, posing a challenge to the effective preservation of patient privacy. In light of these challenges, this study introduces HAE (hybrid AES and ECC), an innovative hybrid cryptographic algorithm that ingeniously amalgamates the robustness of AES with the agility of ECC. HAE is designed to symmetrically encrypt original data with AES while employing ECC for the asymmetric encryption of the initial AES key. This strategy not only alleviates the complexities associated with AES key management but also enhances the algorithm’s security without compromising its efficiency. We provide an in-depth exposition of HAE’s deployment within a framework tailored for medical scenarios, offering empirical insights into its enhanced performance metrics. Our experimental outcomes underscore HAE’s exemplary security, time efficiency, and optimized resource consumption, affirming its potential as a breakthrough advancement for augmenting blockchain applications in the medical sector, heralding a new era of enhanced data security and privacy within this critical domain.
New Digital Technologies for Diagnosis and Rehabilitation of Neurodevelopmental Disorders
Authors: Borasio Francesca , Mascheretti Sara , Lorusso Maria Luisa
Published: November 2023

In recent years, partly due to the SARS-CoV-2 pandemic, the use of new technologies in clinical activity has increased [...]
High-Precision Manufacture and Alignment of Image Slicer Based on Thin Glass Bonding
Authors: Chen Peng , Xia Jingjing , Yu Jun , Li Kexin , Shen Zhengxiang , Wang Zhanshan
Published: November 2023

Integral field spectroscopy (IFS) is capable of simultaneously collecting two-dimensional high-resolution spatial image information and spectral information in a target field of view (FOV). The image slicer is the key element in IFS for segmenting the target FOV. Current micro-image slicer fabrication methods such as molecular assembling need strictly accurate control during sticking, which is time-consuming and expensive. In this study, we improved a direct-adhesive method for thin glass slicer manufacture and alignment. Thin glass is fabricated via single polishing and direct stitching to form a micro-image slicer. Based on charge coupled device (CCD) camera tests on parallel light, the manufacture accuracy for a six-channel image slicer reaches that of the molecular assembling scheme. This method can be applied to the fabrication of image slicers with different apertures.