bluuebunny/crossref_metadata_2025 huggingface dataset:
Passive and Active Training Control of an Omnidirectional Mobile Exoskeleton Robot for Lower Limb Rehabilitation
Authors: Yu Suyang , Liu Congcong , Ye Changlong , Fu Rongtian
Published: May 2024

As important auxiliary equipment, rehabilitation robots are widely used in rehabilitation treatment and daily life assistance. The rehabilitation robot proposed in this paper is mainly composed of an omnidirectional mobile platform module, a lower limb exoskeleton module, and a support module. According to the characteristics of the robot’s omnidirectional mobility and good stiffness, the overall kinematic model of the robot is established using the analytical method. Passive and active training control strategies for an omnidirectional mobile lower limb exoskeleton robot are proposed. The passive training mode facilitates the realization of the goal of walking guidance and assistance to the human lower limb. The active training mode can realize the cooperative movement between the robot and the human through the admittance controller and the tension sensor and enhance the active participation of the patient. In the simulation experiment, a set of optimal admittance parameters was obtained, and the parameters were substituted into the controller for the prototype experiment. The experimental results show that the admittance-controlled rehabilitation robot can perceive the patient’s motion intention and realize the two walking training modes. In summary, the passive and active training control strategies based on admittance control proposed in this paper achieve the expected purpose and effectively improve the patient’s active rehabilitation willingness and rehabilitation effect.
Design and Experiment of Toggle Lever-Type Potato Picker
Authors: Lu Kailiang , Xie Shengshi , Gai Xiuzhi , Ji Xinjie
Published: May 2024

To address the issues of significant soil blockage and high potato damage rates in current potato picking machines, this study developed a toggle lever-type potato picker designed to minimize potato damage and improve operational efficiency. Design calculations were performed for the picker components, and kinematic analyses were conducted for the toggle lever. Single-factor experiments were carried out to determine the variation in performance parameters of the potato picker under different experimental conditions. Discrete element simulations were performed to measure the peak soil height before the pick-up shovel and the peak force on potatoes during the pick-up process. A Box–Behnken response surface experiment was conducted using toggle lever speed, machine forward speed, and shovel angle as experiments factors. Subsequently, an analysis of variance was performed, and a mathematical regression model was established based on the experiments results. The findings revealed that at a toggle lever speed of 50 r/min, machine forward speed of 0.9 m/s, and shovel angle of 19°; the potato leakage rate was 2.32%, and the potato damage rate was 2.72%, thereby meeting the requirements stipulated by potato mechanized picking technology regulations.
Temporal and Spatial Variation of Agricultural and Pastoral Production in the Eastern Section of the Agro-Pastoral Transitional Zone in Northern China
Authors: Zhang Yajing , Hao Ruifang , Qin Yu
Published: May 2024

The agro-pastoral transitional zone in northern China is an important agricultural and pastoral production base. This study focuses on the eastern section of the agro-pastoral transitional zone in northern China. Combined with spatio-temporal analysis, stepwise regression, and gray relation analysis, we analyzed the average annual growth rate, spatio-temporal changes, and influencing factors of agricultural and pastoral production in the study area during 2000–2020. The results show that, in the past 20 years, the agricultural and pastoral production of the 50 municipal districts and counties has significantly changed, among which the agricultural production of 38 municipal districts and counties has shown an extremely significant increase. Generally, the growth rate of agricultural production is higher than that of pastoral production. Agricultural and pastoral production in the study area is influenced by socio-economic and land use/cover factors, with an average correlation degree of 0.79 and 0.88, respectively. Climate change affects agricultural production in agricultural counties, with a correlation degree of 0.85. The results of this research provide valuable insights into understanding the long-term temporal and spatial changes in agricultural and pastoral production and help to develop sound agriculture and pastoral management practices in the eastern section of the agro-pastoral transitional zone in Northern China.
Study on the Effects of Different Light Supply Modes on the Development and Extracellular Enzyme Activity of Ganoderma lucidum
Authors: Liu Yihan , Luo Yuan , Guo Wenzhong , Zhang Xin , Zheng Wengang , Chen Xiaoli
Published: May 2024

Edible fungi have certain photo-sensitivity during the mushroom emergence stage, but there have been few relevant studies on the responses of Ganoderma lucidum to different light irradiation conditions. Ganoderma lucidum were planted in an environmentally controllable mushroom room with different light supply modes that were, respectively, continuous white light (CK), red light (R), green light (G), blue light (B), and intermittent red light (R-), green light (G-), and blue light (B-), with a total light intensity of 15 μmol·m−2·s−1 and a light/dark (L/D) period of 12 h/12 h for each treatment. The interval in intermittent light treatments was 30 min. The optimal light supply mode suitable for the growth of Ganoderma lucidum was explored by analyzing the characteristics, nutritional quality, and extracellular enzyme activity in mushrooms exposed to different light treatments. The results showed that red light (whether in continuous or intermittent supply modes) inhibited the fruiting body differentiation of Ganoderma lucidum, showing delayed differentiation or complete undifferentiation. The highest stipe length and pileus diameter of fruiting bodies were detected under G- treatment, which were, respectively, increased by 71.3% and 3.2% relative to the control. The highest weight of fruiting bodies was detected under G treatment, which was significantly increased by 21.4% compared to the control (p < 0.05). Intermittent light mode seemed to be more conducive to the size development of the fruiting body, while continuous light mode was beneficial for increasing the weight. The highest contents of crude protein and total triterpenes in pileus were detected under G treatment (significantly 14.9% and 28.1% higher than the control, respectively), while that of the crude polysaccharide was detected under G- treatment (significantly 35.7% higher than the control) (p < 0.05). The highest activities of extracellular enzymes such as cellulase, hemicellulase, laccase, lignin peroxidase, and amylase were detected in fruiting bodies subjected to G treatment, which were significantly increased by 11.9%~30.7% in the pileus and 9.5%~44.5% in the stipe. Green light might increase the weight and nutrient accumulation in the pileus of Ganoderma lucidum via up-regulating the extracellular enzyme activities. This study provides an effective light supply strategy for regulating the light environment in the industrial production of Ganoderma lucidum.
Design and Experiment of Flexible Threshing Device with Variable Stiffness for Corn
Authors: Niu Lin , Zha Zehao , Yang Haoran , Ma Jie , He Qinghao , Wang Yanan , Cui Yipeng , Li Xiang , Geng Duanyang
Published: May 2024

In order to solve the problem of the high damage rate of corn with a high moisture content in the Huanghuaihai region, according to the mechanical characteristics of corn in the Huanghuaihai region, we designed a flexible threshing device with a threshing rasp bar and variable stiffness spring as the buffer carrier, and the elements of the device were nail teeth and a flexible threshing rasp bar, which could be replaced freely. The experiment was based on the threshing rotor speed, threshing gap, and spring stiffness as the influencing factors, with the grain breakage rate and the unthreshed rate as an indicator of three-factor three-level experiments, and in October in Zibo through bench experiments, to determine the best parameter combinations. When the spring compression stiffness was 20.83 N/mm, the rotor speed was 375 r/min, and the gap of the concave plate was 45 mm, the grain breakage rate of the corn ear was 4.7%, and the unthreshed rate was 0.48%, which is in line with the relevant national standards.
MicroRNA164 Regulates Perennial Ryegrass (Lolium perenne L.) Adaptation to Changing Light Intensity
Authors: Zhang Liyun , Huang Xin , Liu Yanrong , Ma Ning , Li Dayong , Hu Qiannan , Zhang Wanjun , Wang Kehua
Published: May 2024

Plants especially need to adapt to all different light environments (shade, high light, etc.) due to the essential role of light in plant life. Either shade or high-light microenvironmental conditions are common for cool-season turfgrasses, such as perennial ryegrass (Lolium perenne L.). In order to study how a plant highly conserves microRNA, miR164-affected perennial ryegrass were studied under different light intensities. OsmiR164a-overexpression (OE164), target mimicry OsmiR164a (MIM164), and CRES-T (chimeric repressor gene-silencing technology) OsNAC60 (NAC60) transgenic plants and wild-type (WT) plants were evaluated in both field (shade and full sun) and growth chamber conditions (low, medium, and high PAR at 100, 400, and 1200 µmol s−1 m−2). Morphological and physiological analysis showed miR164 could fine-tune perennial ryegrass adaptation to changing light intensity, possibly via the regulation of target genes, such as NAC60. Overall, OE164 and NAC60 plants were similar to each other and more sensitive to high light, particularly under the field condition, demonstrated by smaller size and much poorer grass quality; MIM164 performed more like WT plants than either the OE164 or NAC60 plants. This study indicates the potential of genetic manipulation of miR164 and/or its targeted genes for turfgrass adaptation to changing light environments, and future research to further investigate the molecular mechanism beneath would be warranted.
Assessing Net Irrigation Needs in Maize–Wheat Rotation Farmlands on the North China Plain: Implications for Future Climate Scenarios
Authors: Wu Yujin , Leng Pei , Ren Chao
Published: May 2024

Assessment of agricultural water requirements under future climate projections has received increasing attention in recent decades. The agriculture pattern of the semi-arid North China Plain is a maize–wheat rotation system in which sufficient irrigation is required to maintain production. In this study, the effects of future climate scenarios on the net irrigation requirement of the maize–wheat rotation system were assessed using the Food and Agriculture Organization crop growth model—AquaCrop. First, the baseline net irrigation requirement over the study region was obtained through AquaCrop simulation under ERA5-Land reanalysis from 2011 to 2020. In addition, the AquaCrop model was used to predict irrigation requirements in future scenarios (2021–2050) under the extreme-emission scenario of the Shared Socioeconomic Pathway SSP 5-8.5 (SSP 5-8.5). Finally, the predicted irrigation amount for maize and wheat during the period 2021–2050 under SSP 5-8.5 was compared with the baseline to assess the interannual change in irrigation water requirement. Results reveal significant agreement between the AquaCrop-derived daily soil moisture (SM) and a reference SM product with unbiased root mean square differences of 0.03 m3/m3 and 0.04 m3/m3 over maize and wheat, respectively. Furthermore, the median net irrigation requirement is expected to increase by approximately 107 mm (21%) to guarantee optimum yield.
Effects of a Novel Consensus Bacterial 6-Phytase Variant on Growth Performance and Bone Ash of Broilers Fed Complex Diets Highly Deficient in Minerals, Digestible Amino Acids and Energy through 42 Days of Age
Authors: Sobotik Eric B. , House Gabrielle M. , Stiewert Austin M. , Bello Abiodun , Dersjant-Li Yueming , Marchal Leon , Archer Gregory S.
Published: May 2024

An experiment was conducted to evaluate the effects of increasing the dose of a novel consensus bacterial 6-phytase variant expressed in Trichoderma reesei (PhyG) in broilers fed complex diets highly deficient in minerals, dig AA, and energy. Diets were a nutrient-adequate control (PC); a nutrient-reduced control (NC) formulated with a reduction in available P (avP) by 0.199%, Ca by 0.21%, crude protein by 0.72–1.03%, dig Lys by 0.064–0.084%, Na by 0.047%, and ME by 87.8 kcal/kg, respectively; and NC supplemented with PhyG at 500, 1000, and 2000 FTU/kg feed. BW was decreased and FCR increased in the NC vs. PC, while the PhyG treatments were similar to the PC. Carcass yield and bone ash were also maintained with PhyG supplementation. Phytase provided economic benefit on a feed cost per kg of weight basis for 1 to 35 d; the cost reductions equated to USD 0.006, 0.016, and 0.02/kg BWG at 500, 1000, and 2000 FTU/kg. In conclusion, this trial demonstrated that supplementation with a novel consensus phytase variant in diets highly deficient in minerals, dig AA, and energy maintained growth performance and provided economic benefit, with production benefits being maximized at inclusion levels of 2000 FTU/kg.
Diet Drives Gut Bacterial Diversity of Wild and Semi-Captive Common Cranes (Grus grus)
Authors: Wu Hong , Wu Nan , Liu Xinchen , Zhang Lei , Zhao Dapeng
Published: May 2024

The gut microbiota of wild animals can regulate host physical health to adapt to the environment. High-throughput sequencing from fecal samples was used to analyze the gut microbiota communities in common cranes (Grus grus) without harming them. Herein, we compared the fecal microbiome of fifteen G. grus in Tianjin Tuanbo Bird Natural Reserve (wild group) and six G. grus sampled from Beijing Wildlife Park (semi-captive group) in China, using 16S amplicon sequencing and bioinformatic analysis. The results showed that microbiota diversity and composition varied in different groups, suggesting that the gut microbiota was interactively influenced by diet and the environment. A total of 38 phyla and 776 genera were analyzed in this study. The dominant phyla of the G. grus were Firmicutes and Proteobacteria. Meanwhile, the microbiota richness of the semi-captive group was higher than the wild group. Data on beta diversity highlighted significant differences based on different dietary compositions. Zea mays, Glycine max, and Phragmites australia showed a significant correlation with intestinal bacteria of G. grus. This study provides a comprehensive analysis of diet and microbiomes in semi-captive and wild G. grus living in different environments, thus helping us to evaluate the influence on animal microbiomes and improve conservation efforts for this species.
Analysis of the Quality and Chemical Composition of Double-Yolked Eggs Compared to Those of a Normal Structure
Authors: Drabik Kamil , Wengerska Karolina , Kasperek Kornel , Knaga Sebastian , Batkowska Justyna
Published: May 2024

The study material consisted of 360 eggs from a reproductive flock of meat-type hens; 240 were double-yolked eggs and 120 were single-yolked as a control group. The eggs were numbered individually and then analysed for their quality in terms of characteristics of the whole egg (weight, shape index, specific gravity), shell (colour, strength, weight, density), albumen (pH, height, weight, Haugh units) and yolk (colour, weight, shape index, pH). During the analyses, yolks were sampled for analyses including basic composition, fatty acid profile (by gas chromatography) and fatty acid indices. It was found that double-yolked eggs differed significantly from single-yolked ones in terms of weight, proportion of individual elements in the egg weight, total protein content in the yolks as well as in terms of the fatty acid profile and their indices both due to the presence or absence of two yolks and in the context of the individual yolks analysed. The results indicate the possibility of using double-yolked eggs as table eggs due to the absence of negative effects stemming from being double-yolked and the increased content of biologically important components such as fatty acids.
Regulation of Inflammatory Responses of Cow Mammary Epithelial Cells through MAPK Signaling Pathways of IL-17A Cytokines
Authors: Zhang Kai , Zhang Min , Su Hong , Zhao Feifei , Wang Daqing , Zhang Yuanyuan , Cao Guifang , Zhang Yong
Published: May 2024

The aim of this study is to explore the mechanism of IL-17A infection in the development of bacterial mastitis in dairy cows. In this study, RT-qPCR and ELISA were used to measure the promoting effect of IL-17A on the generation of pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) and chemokine (IL-8). In addition, Western blot (WB) was applied to measure the influences of IL-17A on the inflammation-related ERK and p38 proteins in the MAPK pathways. The results show that under the stimulation of LPS on cow mammary epithelial cells (CMECs), cytokines IL-1β, IL-6, IL-8, TNF-α, and IL-17A will exhibit significantly increased expression levels (p < 0.05). With inhibited endogenous expression of IL-17A, cytokines IL-1β, IL-6, IL-8, and TNF-α will present reduced genetic expression (p < 0.01), with reduced phosphorylation levels of ERK and p38 proteins in the MAPK signaling pathways (p < 0.001). Upon the exogenous addition of the IL-17A cytokine, the genetic expression of cytokines IL-1β, IL-6, IL-8, and TNF-α will increase (p < 0.05), with increased phosphorylation levels of the ERK and p38 proteins in the MAPK signaling pathways (p < 0.001). These results indicate that under the stimulation of CMECs with LPS, IL-17A can be expressed together with relevant inflammatory cytokines. Meanwhile, the inflammatory responses of mammary epithelial cells are directly proportional to the expression levels of IL-17A inhibited alone or exogenously added. In summary, this study shows that IL-17A could be used as an important indicator for assessing the bacterial infections of mammary glands, indicating that IL-17A could be regarded as one potential therapeutic target for mastitis.
Functional Analysis of Oligoadenylate Synthetase in the Emu (Dromaius novaehollandiae)
Authors: Sato Keisuke , Nakamura Teppei , Morimatsu Masami , Agui Takashi
Published: May 2024

2′-5′-oligoadenylate synthetase (OAS) is one of the proteins that act as a defense mechanism against foreign RNA in cells. OAS has two functions: an antiviral effect against a wide range of virus species via the OAS/RNase L pathway with synthesized oligoadenylates and inhibition of viral replication specific to viruses of the genus Flavivirus, which is independent of enzymatic activity. Several birds have been reported to possess only one type of OAS family member, OASL, which has both enzymatic activity and inhibitory effects on flaviviral replication. However, the ostrich has two types of OASs, OAS1 and OASL, which show different functions—enzymatic and anti-flaviviral activities, respectively. In this study, emu OASs were cloned to investigate their sequence and function and elucidate the role of OASs in emus. The cloning results showed that emus had OAS1 and OASL, suggesting that emu OASs were more closely related to ostrich than to other birds. Functional investigations showed that emu OAS1 and OASL had enzymatic and anti-flaviviral activities, respectively, similar to those of the ostrich. Emus and ostriches are evolutionarily different from most birds and may be more closely related to mammalian OAS diversity.
Shy and Bold Fish Have the Same Preference for Light Color Selection
Authors: Zou Qingqing , Li Weiwei , Zhang Chaoshuo , Bao Jianghui , Lyu Huafei , Duan Ming
Published: May 2024

Personality, which matters for animal welfare, demonstrates behavioral differences. Light is one of the most important factors in aquaculture. However, how fish personality affects light color selection is unclear. In this study, we tested the personality of yellow catfish Pelteobagrus fulvidraco juveniles and then quantified the selective behaviors of different personalities under six light colors: violet (410–420 nm), yellow (580–590 nm), green (550–560 nm), red (620–630 nm), blue (470–480 nm), and white. The results showed that juveniles preferred the yellow and green light over the other colors of light, probably due to different reasons. The average cumulative dwell time in yellow (32.81 ± 5.22%), green (21.81 ± 3.58%), and red (26.36 ± 4.89%) lights was significantly longer than the other light colors, and the average visit frequency in green light (32.00 ± 4.93%) was the most. Juveniles had the longest total moved distance in green light. Moreover, the results demonstrated that shy and bold individuals had the same preference for the green light. Bold individuals could find the preferred light colors rapidly and make quick decisions for light color selection. After identifying the preferred light colors, bold individuals reduced the frequency of exploration. This study provides a theoretical basis for the welfare of juvenile yellow catfish in aquaculture.
Report on a Milking Mule: Milk Qualitative Characteristics during Lactation
Authors: Martini Mina , Degl’Innocenti Andrea , Altomonte Iolanda , Sodi Irene , Bocci Carlotta , Fanelli Diana , Moroni Rebecca , Panzani Duccio , Camillo Francesco , Salari Federica
Published: May 2024

Despite their inability to reproduce naturally, mules can host embryos and be surrogate dams. The aim of this investigation was to increase our knowledge of the qualitative composition of mule’s milk and its variations throughout the whole lactation period—namely, from 6 h after foaling to 180 days in milk (DIM). Milk was obtained from a mule dam that had foaled after receiving a mule embryo transfer. For each sample, the gross, mineral, and fatty acid composition was evaluated. The average quality of the mule milk was as follows: protein 1.97 g 100 mL−1, fat 0.90 g 100 mL−1, and ash 0.39 g 100 mL−1. Saturated fatty acids made up, on average, 50.00 g 100 g−1 of fat. Monounsaturated and polyunsaturated fatty acids made up half of the total fatty acid content (31.80 g 100 g−1 and 18.2 g 100 g−1 of fat, respectively). Linoleic acid and linolenic acid were the main polyunsaturated fatty acids in the milk. The milk composition changed throughout lactation. Dry matter, protein, fat, and ash decreased significantly from early lactation (6 h to 14 DIM). The n3 polyunsaturated fatty acids decreased at the end of lactation. The changes in milk composition throughout lactation are probably due to adaptations to the growth requirements of the foal.
The microRNA Let-7f Induces Senescence and Exacerbates Oxidative Stress in Retinal Pigment Epithelial Cells
Authors: Ortiz Christina , Tahiri Houda , Yang Chun , Gilbert Claudia , Fortin Carl , Hardy Pierre
Published: May 2024

This study aims to investigate the role of microRNA let-7f in the dysfunction and degeneration of retinal pigment epithelium (RPE) cells through the induction of senescence and oxidative stress. Furthermore, we explore whether let-7f inhibition can protect these cells against sodium iodate (SI)-induced oxidative stress. Oxidative stress and let-7f expression are reciprocally regulated in retinal pigment epithelial cells. Overexpression of let-7f in ARPE-19 cells induced oxidative stress as demonstrated by increased reactive oxygen species (ROS) production as well as senescence. Inhibition of let-7f successfully protected RPE cells from the detrimental effects induced by SI. In addition, let-7f overexpression induced RPE cellular dysfunction by diminishing their migratory capabilities and reducing the phagocytosis of porcine photoreceptor outer segments (POS). Results were further confirmed in vivo by intravitreal injections of SI and let-7f antagomir in C57BL/6 mice. Our results provide strong evidence that let-7f is implicated in the dysfunction of RPE cells through the induction of senescence and oxidative injury. These findings may help to uncover novel and relevant processes in the pathogenesis of dry AMD.
High-Resolution Estimation of Soil Saturated Hydraulic Conductivity via Upscaling and Karhunen–Loève Expansion within DREAM(ZS)
Authors: Xia Yang , Li Na
Published: May 2024

Quantification of the soil hydraulic conductivity is key to the study of water flow and solute transport in unsaturated soils. Rapid advances in measurement technology have provided a large number of observations at different scales, offering unprecedented opportunities and challenges for the estimation of hydraulic parameters. This paper proposes an inverse estimation method for downscaling of observations on coarse scales to estimate hydraulic parameters on high-resolution scales. Due to the significant spatial heterogeneity, the inversion faces the problems of dynamics-based integration of data at different scales, model uncertainty due to hundreds and thousands of parameters, and computational consumption due to the large number of forward simulations. To overcome these problems, this paper uses an efficient Bayesian optimization DREAM(ZS) as an inverse framework, and incorporates an analytical upscaling method and Karhunen–Loève (KL) expansion to infer finer-scale saturated hydraulic conductivity distribution conditioned on coarse-scale measurements. The efficient upscaling method is used to link measurements and hydraulic parameters at different scales, and Karhunen–Loève (KL) expansion is incorporated to greatly reduce the dimension of the parameter to be estimated. To further improve the efficiency of the inversion, a locally one-dimensional (LOD) algorithm is used to solve the multidimensional water flow model at coarse scales. The proposed inverse model is applied in a series of numerical experiments to demonstrate its applicability and effectiveness under different flow boundary conditions, different levels of ratio between coarse- and fine-scale grids, different densities of observation points, and different degrees of statistic heterogeneity of soil mediums.
An Adaptive Security Framework for Internet of Things Networks Leveraging SDN and Machine Learning
Authors: Hamarsheh Ala
Published: May 2024

The Internet of Things (IoT) is expanding rapidly with billions of connected devices worldwide, necessitating robust security solutions to protect these systems. This paper proposes a comprehensive and adaptive security framework called Enhanced Secure Channel Authentication using random forests and software-defined networking (SCAFFOLD), tailored for IoT environments. The framework establishes secure communication channels between IoT nodes using software-defined networking (SDN) and machine learning techniques. The key components include encrypted channels using session keys, continuous traffic monitoring by the SDN controller, ensemble machine-learning for attack detection, precision mitigation via SDN reconfiguration, and periodic reauthentication for freshness. A mathematical model formally defines the protocol. Performance evaluations via extensive simulations demonstrate Enhanced SCAFFOLD’s ability to reliably detect and rapidly mitigate various attacks with minimal latency and energy consumption overheads across diverse IoT network scenarios and traffic patterns. The multidimensional approach combining encryption, intelligent threat detection, surgical response, and incremental hardening provides defense-in-depth to safeguard availability, integrity, and privacy within modern IoT systems while preserving quality of service.
Combining Balancing Dataset and SentenceTransformers to Improve Short Answer Grading Performance
Authors: Wijanto Maresha Caroline , Yong Hwan-Seung
Published: May 2024

Short-answer questions can encourage students to express their understanding. However, these answers can vary widely, leading to subjective assessments. Automatic short answer grading (ASAG) has become an important field of research. Recent studies have demonstrated a good performance using computationally expensive models. Additionally, available datasets are often unbalanced in terms of quantity. This research attempts to combine a simpler SentenceTransformers model with a balanced dataset, using prompt engineering in GPT to generate new sentences. Our recommended model also tries to fine-tune several hyperparameters to achieve optimal results. The research results show that the relatively small-sized all-distilroberta-v1 model can achieve a Pearson correlation value of 0.9586. The RMSE, F1-score, and accuracy score also provide better performances. This model is combined with the fine-tuning of hyperparameters, such as the use of gradient checkpointing, the split-size ratio for testing and training data, and the pre-processing steps. The best result is obtained when the new generated dataset from the GPT data augmentation is implemented. The newly generated dataset from GPT data augmentation achieves a cosine similarity score of 0.8 for the correct category. When applied to other datasets, our proposed method also shows an improved performance. Therefore, we conclude that a relatively small-sized model combined with the fine-tuning of the appropriate hyperparameters and a balanced dataset can provide performance results that surpass other models that require larger resources and are computationally expensive.
Optimal Concordant Tests
Authors: Chen Zhongxue
Published: May 2024

In meta-analyses, unlike model-based methods, such as fixed- or random-effect models, the p-value combining methods are distribution-free and robust. How to appropriately and powerfully combine p-values obtained from various sources remains an important but challenging topic in statistical inference. For cases where all or a majority of the individual alternative hypotheses have the same but unknown direction, concordant tests based on one-sided p-values can substantially improve the detecting power. However, there exists no test that is uniformly most powerful; therefore, figuring out how to choose a robust and powerful test to combine one-sided p-values for a given data set is desirable. In this paper, we propose and study a class of gamma distribution-based concordant tests. Those concordant tests are optimal under specific conditions. An asymptotically optimal concordant test is also studied. The excellent performances of the proposed tests were demonstrated through a numeric simulation study and real data example.
Identification of Urban Building Functions Based on Points of Interest and Spatial Relationships between Geographic Entities
Authors: Wei Yi , Luo Guowei , Yu Lu , Huang Zhenhui
Published: May 2024

Knowing the functions of buildings is valuable in urban planning and management. For example, it can be used for the assessment of urban planning implementation and the fine-tuning of community governance. At large scales, determining building functions can be time-consuming and laborious. While point of interest (POI) data can be used to identify urban building functions, it is prone to missing values. The present study proposes combining POIs with the spatial relationships between geographic entities and geographic information systems (GIS) to improve the accuracy of urban building function identification. First, the POIs are reclassified according to building functions. Second, the spatial relationships among road networks, buildings and POIs are analysed, and the frequency density ratios of POI types are calculated to identify the functions of buildings that contain POIs. Finally, buildings that do not contain POIs are identified by calculating the spatial similarity between unrecognised buildings and recognised buildings within the same road network mesh. The method can identify buildings with singular residential, commercial, office, and public services functions, as well as seven mixed functions, with an accuracy, recall, and F1 value of 90.28%, 97.52%, and 93.76%, respectively. Public service buildings and residential buildings have the highest identification precision, while the identification precision of mixed commercial and public service buildings and mixed residential and public service buildings are the lowest. An experiment demonstrates the effectiveness of the method. The results indicate that the spatial relationships between entities can compensate for missing POI data.
Aluminum-Based Plasmonic Photodetector for Sensing Applications
Authors: Lyaschuk Yurii , Indutnyi Ivan , Myn’ko Viktor , Romanyuk Volodymyr , Mamontova Iryna , Redko Roman , Dusheyko Mykhailo , Savchuk Yelizaveta , Tochkovyi Vasyl , Shtykalo Oleksandr , Kuznetsova Daria , Mamykin Sergii
Published: May 2024

Plasmonic sensors have great potential for widespread usage. However, the prohibitive cost of noble metals restrains the wider adoption of these devices. The aim of our study is to develop a cost-effective Al-based alternative to common noble metal-based plasmonic detectors. We considered a structure consisting of an n-type doped Si wafer with a shallow p-n junction and an overlying Al grating with a trapezoidal groove profile. The RCWA (rigorous coupled-wave analysis) method was used to numerically calculate the distribution of absorbed light energy in the plasmonic detector layers and to optimize the grating parameters. Based on the simulation results, experimental samples of plasmonic photodetectors with optimal grating parameters (period—633 nm, relief depth—50 nm, groove filling factor—0.36, and thickness of the intermediate Al layer—14 nm) were manufactured, and their properties were studied. For these samples, we obtained a polarization sensitivity value of Ip/Is = 8, an FWHM of the resonance in the photocurrent spectrum ranging from 50 to 100 nm, a sensitivity at the resonance maximum of Iph = 0.04–0.06 A/W, and an angular half-width of photocurrent resonance of Δθ = 5°, which are comparable to noble metal-based analogs. Our results may be used for creating cost-effective high-sensitivity plasmonic sensors.
Syn2Real Detection in the Sky: Generation and Adaptation of Synthetic Aerial Ship Images
Authors: Wu Yaoyuan , Guo Weijie , Tan Zhuoyue , Zhao Yifei , Zhu Quanxing , Wu Liaoni , Guo Zhiming
Published: May 2024

Object detection in computer vision requires a sufficient amount of training data to produce an accurate and general model. However, aerial images are difficult to acquire, so the collection of aerial image datasets is a priority issue. Building on the existing research on image generation, the goal of this work is to create synthetic aerial image datasets that can be used to solve the problem of insufficient data. We generated three independent datasets for ship detection using engine and generative model. These synthetic datasets are rich in virtual scenes, ship categories, weather conditions, and other features. Moreover, we implemented domain-adaptive algorithms to address the issue of domain shift from synthetic data to real data. To investigate the application of synthetic datasets, we validated the synthetic data using six different object detection algorithms and three existing real-world, ship detection datasets. The experimental results demonstrate that the methods for generating synthetic aerial image datasets can complete the insufficient data in aerial remote sensing. Additionally, domain-adaptive algorithms could further mitigate the discrepancy from synthetic data to real data, highlighting the potential and value of synthetic data in aerial image recognition and comprehension tasks in the real world.
Automatic Optimization System for Heat Source Layout of Multi-Chip Components Based on Multi-Software Integration
Authors: Huang Xingxing , Hu Jiangcheng , Ge Yan , Guo Liang , Han Kang , Zhang Jiahong
Published: May 2024

This paper presents an automatic optimization system for the heat source layout of multi-chip modules, referred to as IOS. The system aims to optimize the heat source layout of multi-chip modules through the integration of multiple software tools. The IOS utilizes an optimization algorithm, WINDOW DOS, and other methods to achieve this goal. Initially, two optimization strategies are introduced which are utilized in conjunction with the Non-dominated Sorting Genetic Algorithm-II(NSGA-II). Subsequently, a simplified thermal model of the multi-chip module is applied to the IOS. The automatic optimization module is then used to optimize the heat source layout. In the end, we simulated and analyzed the application results. The simulation analysis reveals that when the temperature extreme value index is optimized, the PCB board’s transient temperature range falls within [343.14 K, 344.09 K]. Similarly, when the temperature homogeneity index is optimized, the PCB board’s transient temperature range falls within [343.39 K, 344.21 K]. Comparing these results with the experience layout, the temperature difference is reduced by 76.36% and 79.60%, respectively. The optimization results demonstrate that the IOS has a significant impact, offering remarkable optimization effects, low cost, high efficiency, and a more uniform temperature distribution. These findings indicate that the IOS holds promising potential for applications and provides value in optimizing the heat source layout of multi-chip modules.
Effect of Acute Consumption of Crackers Enriched with Grape Seed Flour or Barley Flour with Added β-Glucan on Biomarkers of Postprandial Glycemia, Lipidemia, and Oxidative Stress: A Crossover Study
Authors: Chatziharalambous Despina , Papagianni Olga , Potsaki Panagiota , Almpounioti Kalliopi , Koutelidakis Antonios E.
Published: May 2024

Background: Grape seed polyphenol bioactivity is linked to reduced risk of metabolic syndrome, type 2 diabetes, obesity, and coronary heart disease development. Furthermore, regular consumption of β-glucan is associated with decreased lipidemic and glycemic profiles. The aim was to investigate the acute effect of crackers enriched with either 10% grape seed flour or 40% barley flour with added β-glucan along with a high-fat and high-carbohydrate meal on biomarkers of postprandial glycemia, lipidemia, and oxidative stress. Methods: In a randomized, three-arm crossover design study, 12 healthy subjects were assigned to consume breakfast consisting of bread, butter, and 250 mL water along with crackers containing either (a) wheat flour, (b) 10% grape seed flour, or (c) 40% barley flour enriched with β-glucan. Blood samples were drawn immediately before and 30, 90, and 180 min after the meal. Total antioxidant capacity was measured in plasma with the FRAP method. Total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, and uric acid were measured in serum. Results: Tested markers did not differ between the intervention groups at baseline, 30, 90, and 180 min (p ≥ 0.05) post-prandially. Conclusions: Enriched cracker consumption did not significantly affect the selected markers at the postprandial state, although better serum glucose and lipid levels, similar to baseline values, were maintained.
Tidal Range Barrage Design and Construction
Authors: Vandercruyssen David , Baker Simon , Howard David , Aggidis George
Published: May 2024

The west coast of Great Britain has the potential for barrages to create tidal range reservoirs that both facilitate electricity generation and prevent flooding from sea level rise. Seawater flows into and out of the reservoir, or impoundment, through turbines and sluices. The impounded water follows the natural tidal sequence but with a delay which creates a head between the two bodies of water. Traditional designs for barrages use earth embankments, with impermeable cores and rockfill protection. More recently, breakwaters and jetties have been constructed using precast concrete vertical caissons. A novel design using horizontal precast caissons is described and evaluated. Wave forces are estimated using Goda’s method for a vertical breakwater to assess their impact on stability and ground-bearing pressures. The stability of the barrage is checked for hydrostatic and wave forces. The volumes of materials and relative costs are presented. Precast caissons are found to be viable financially and should be both quicker and easier to construct and install. The horizontal caissons show advantages over the vertical type, and although untried, they should be easier to construct than submerged tube tunnels. Further work is needed to validate the design, including dynamic modelling and detailed construction assessment to confirm the cost rates.
DBCW-YOLO: A Modified YOLOv5 for the Detection of Steel Surface Defects
Authors: Han Jianfeng , Cui Guoqing , Li Zhiwei , Zhao Jingxuan
Published: May 2024

In steel production, defect detection is crucial for preventing safety risks, and improving the accuracy of steel defect detection in industrial environments remains challenging due to the variable types of defects, cluttered backgrounds, low contrast, and noise interference. Therefore, this paper introduces a steel surface defect detection model, DBCW-YOLO, based on YOLOv5. Firstly, a new feature fusion strategy is proposed to optimize the feature map fusion pair model using the BiFPN method to fuse information at multiple scales, and CARAFE up-sampling is introduced to expand the sensory field of the network and make more effective use of the surrounding information. Secondly, the WIoU uses a dynamic non-monotonic focusing mechanism introduced in the loss function part to optimize the loss function and solve the problem of accuracy degradation due to sample inhomogeneity. This approach improves the learning ability of small target steel defects and accelerates network convergence. Finally, we use the dynamic heads in the network prediction phase. This improves the scale-aware, spatial-aware, and task-aware performance of the algorithm. Experimental results on the NEU-DET dataset show that the average detection accuracy is 81.1, which is about (YOLOv5) 6% higher than the original model and satisfies real-time detection. Therefore, DBCW-YOLO has good overall performance in the steel surface defect detection task.
RL-Based Sim2Real Enhancements for Autonomous Beach-Cleaning Agents
Authors: Quiroga Francisco , Hermosilla Gabriel , Varas German , Alonso Francisco , Schröder Karla
Published: May 2024

This paper explores the application of Deep Reinforcement Learning (DRL) and Sim2Real strategies to enhance the autonomy of beach-cleaning robots. Experiments demonstrate that DRL agents, initially refined in simulations, effectively transfer their navigation skills to real-world scenarios, achieving precise and efficient operation in complex natural environments. This method provides a scalable and effective solution for beach conservation, establishing a significant precedent for the use of autonomous robots in environmental management. The key advancements include the ability of robots to adhere to predefined routes and dynamically avoid obstacles. Additionally, a newly developed platform validates the Sim2Real strategy, proving its capability to bridge the gap between simulated training and practical application, thus offering a robust methodology for addressing real-life environmental challenges.
Optimization of Zinc Smelting Slag Melting Point Based on Catboost and Improved Snake Optimization Algorithm
Authors: Kong Yueping , Liu Ziyu
Published: May 2024

The regulation of the melting point of zinc smelting slag has an important impact on the subsequent smelting processes of the metal. In actual production, uncontrollable melting points may result in inconsistent product quality, which has a great negative impact on the smelter’s efficiency and environmental protection. However, the regulation mechanism of the melting point of the smelting slag is complex, with many influencing factors, and there is no recognized high-precision calculation method. In response to these challenges, this study introduces an innovative approach for optimizing the melting point of zinc smelting slag based on the improved Snake Optimization (ISO) algorithm. The melting point of zinc smelting slag is modeled using the Catboost algorithm, and the model parameters are optimized using the Tree-structured Parzen Estimator (TPE) to improve the accuracy of the model. Next, the ISO algorithm is employed to conduct optimization calculations, determining the optimal values of various production process parameters that minimize the melting point. The effectiveness of this approach was evaluated using diverse modeling algorithms and test functions, subsequently applied to optimize and validate actual production data from a smelter in Shaanxi, China. Statistical analyses reveal that the TPE-optimized Catboost model exhibits an R2 of 93.89%, an RMSE of 7.02 °C, an MAE of 6.19 °C, and an MRE of 7.88%, surpassing performance metrics of alternative algorithms. Regarding optimization efficacy, the proposed ISO algorithm achieves an average reduction of 65 °C in the melting point and demonstrates superior robustness compared to both actual production data and alternative algorithms.
D-Limonene: Promising and Sustainable Natural Bioactive Compound
Authors: Lin Haoran , Li Ziyu , Sun Yue , Zhang Yingyue , Wang Su , Zhang Qing , Cai Ting , Xiang Wenliang , Zeng Chaoyi , Tang Jie
Published: May 2024

The discovery of antibiotics and pesticides has greatly contributed to the social and economic development of human society but, due to the long-term irrational application, it has led to drug-resistant microorganisms, environmental damage, and other hazards, so the selection of alternative natural, safe, and non-hazardous bioactive substances is an effective solution for this problem. D-limonene is a bioactive compound widely present in various plant essential oils, exhibiting excellent broad-spectrum bioactivity and promising prospects for development and clinical application. This review provides a detailed overview of the biological activities of D-limonene, emphasizing its antimicrobial, anthelmintic, insecticidal, and medicinal potential. While nanoencapsulation technology shows promise in improving the physicochemical properties of D-limonene and enhancing its practical applications, it is also crucial to comprehensively evaluate the potential side effects of D-limonene before use.
Task-Driven Transferred Vertical Federated Deep Learning for Multivariate Internet of Things Time-Series Analysis
Authors: Oh Soyeon , Lee Minsoo
Published: May 2024

As big data technologies for IoT services develop, cross-service distributed learning techniques of multivariate deep learning models on IoT time-series data collected from various sources are becoming important. Vertical federated deep learning (VFDL) is used for cross-service distributed learning for multivariate IoT time-series deep learning models. Existing VFDL methods with reasonable performance require a large communication amount. On the other hand, existing communication-efficient VFDL methods have relatively low performance. We propose TT-VFDL-SIM, which can achieve improved performance over centralized training or existing VFDL methods in a communication-efficient manner. TT-VFDL-SIM derives partial tasks from the target task and applies transfer learning to them. In our task-driven transfer approach for the design of TT-VFDL-SIM, the SIM Partial Training mechanism contributes to performance improvement by introducing similar feature spaces in various ways. TT-VFDL-SIM was more communication-efficient than existing VFDL methods and achieved an average of 0.00153 improved MSE and 7.98% improved accuracy than centralized training or existing VFDL methods.