bluuebunny/crossref_metadata_2025 huggingface dataset:
Dissecting the importance and origin of circulating myokines in gastric cancer cachexia
Authors: Sierzega Marek , Drabik Anna , Sanak Marek , Chrzan Robert , Richter Piotr
Published: October 2024

Background

Some experimental data suggest that myokines may play an important role in developing cancer-associated cachexia (CAC), but their relevance in humans remains poorly explored. In our study, we tested the hypothesis that circulating myokines are associated with the pathogenesis of CAC in a model population of gastric cancer.

Methods

A group of 171 treatment naïve patients with adenocarcinoma of the stomach were prospectively examined. Cachexia was defined as weight loss >5% or weight loss >2% with either BMI <20 kg/m2 or sarcopenia. A panel of 19 myokines was measured in portal and peripheral blood as well as tumour tissue and surrounding gastric mucosa. Moreover, a serum proteomic signature of cachexia was identified by a label-free quantitative proteomics with a nano LC-MS/MS system and stored in a ProteomeXchange database (PXD049334).

Results

One hundred (58%) patients were diagnosed with CAC. The concentrations of fatty acid-binding protein 3 (FABP3), follistatin-like 1 protein (FSTL−1), interleukin 6 (IL 6), and interleukin 8 (IL 8) were significantly higher in the peripheral blood of cachectic subjects, while leptin levels were lower. Of all the evaluated myokines, tumour tissues showed higher expression levels only for IL-15 and myostatin. However, the analysis of paired samples failed to demonstrate a decreasing concentration gradient between the portal and peripheral blood for any of the myokines, evidencing against their release by the primary tumour. Proteomic analysis identified 28 proteins upregulated and 24 downregulated in the peripheral blood of patients with cachexia. Differentially expressed proteins and 5 myokines with increased serum levels generated a significant protein-protein interaction network.

Conclusions

Our study provides clinical evidence that some myokines are involved in the pathogenesis of cachexia and are well integrated into the regulatory network of circulating blood proteins identified among cachectic patients with gastric cancer.
MicroRNA binding site variants–new potential markers of primary osteoporosis in men and women
Authors: Yalaev Bulat , Deev Roman , Tyurin Anton , Salakhov Ramil , Smirnov Kirill , Eremkina Anna , Mokrysheva Natalia , Minniakhmetov Ildar , Khusainova Rita
Published: October 2024

Introduction

The identification of significant DNA markers of primary osteoporosis may gain new insights by studying genome regions involved in mechanisms of epigenetic regulation through interactions with microRNAs.

Methods

The authors searched for associations of polymorphic variants of microRNA binding sites of mRNA target genes and polymorphic loci of microRNA genes with primary osteoporosis in a cohort of women and men from the Volga-Ural region of Russia (N = 1.177).

Results

Using case-control association analysis, the authors found that rs1061947 (COL1A1), rs10793442 (ZNF239), rs6854081 (FGF2), and rs11614913 (miR-196a) were associated with osteoporotic fractures; rs5854 (MMP1) and rs2910164 (miR-146a) were associated with low bone mineral density; and rs10098470 (TPD52), rs11540149 (VDR), rs1042673 (SOX9), rs1054204 (SPARC), and rs1712 (FBXO5) were markers of both fractures and low bone mineral density. Among the identified associations, ethno specific trends were found, as well as sex-specific associations. Prognostic models were developed, among which the model for predicting osteoporosis in general in women (Area Under Curve = 0.909) achieved the highest level of predictive value. Thus, the potential role of polymorphic variants of microRNA binding sites in the development of primary osteoporosis in men and women from the Volga-Ural region of Russia was demonstrated.
Ocean warming enhances the competitive advantage of Ulva prolifera over a golden tide alga, Sargassum horneri under eutrophication
Authors: Wu Hailong , Zhang Jiankai , Li He , Li Sufang , Pan Chen , Yi Lefei , Xu Juntian , He Peimin
Published: October 2024

Recent years have seen the Ulva green tide and Sargassum golden tide become commonplace in the coastal waters of China. However, little is known on how the combination of ocean warming and eutrophication would affect the interaction of green and golden tides. In this study, we cultured the green tide alga Ulva prolifera and the golden tide alga Sargassum horneri under different temperatures (5, 10, 15, 20, 25, and 30°C) and two nutrient concentrations (Low nutrient, LN: 5 μM-nitrate and 0.5 μM-phosphate; High nutrient, HN: 500 μM-N and 50 μM-P) in both monoculture and coculture systems to investigate the physiological responses and their competitive relationships. In monocultures, the growth of U. prolifera and S. horneri, along with pigment concentrations and photosynthesis, increased with rising temperature, reaching a plateau at 15 - 25°C. However, when the temperature increased to 30°C, the growth of U. prolifera and S. horneri decreased abruptly, with S. horneri even suffering death. In coculture, the growth of both U. prolifera and S. horneri was inhibited compared to the monoculture, with the greatest decline observed in S. horneri at 25°C under two nutrient conditions. Our results show that U. prolifera would outcompete S. horneri under high temperature in coculture, suggesting that ocean warming would enhance the competitive advantage of green tide over golden tide under eutrophication in the future.
Simultaneous use of convection and radiation heat transfer for Iranian pistachio drying using catalytic heater - numerical and experimental study
Authors: Ebrahimpour Vahid , Esmailpour Kazem
Published: October 2024

This study presents a comprehensive investigation into the simultaneous use of convection and radiation heat transfer for Iranian pistachio drying using a catalytic heater. Both experimental and numerical analyses were conducted to evaluate the performance of the proposed system. The experimental setup involved a catalytic infrared heater, which provided a consistent temperature of approximately 370 K within the drying chamber. The results indicated that the drying time was reduced by 40% compared to traditional hot air drying methods, with an average moisture reduction rate of 0.8% per minute. The numerical analysis, conducted using computational fluid dynamics (CFD) simulations, supported the experimental findings, showing a uniform temperature distribution across the pistachios and efficient heat transfer. The catalytic heater demonstrated a combustion efficiency of 98%, with CO emissions below 10 ppm and zero NOx emissions, highlighting its environmental benefits. Overall, the combined experimental and numerical results confirmed that the proposed catalytic heater system not only enhances drying efficiency but also significantly reduces energy consumption and greenhouse gas emissions compared to conventional drying methods.
Basal metabolic rate mediates the causal relationship between gut microbiota and osteoarthritis: a two-step bidirectional Mendelian randomization study
Authors: Li Jiachen , Liang Jianhui , Liu Yang , Sun Weichao , Sun Wei
Published: October 2024

Background

The relationship between gut microbiota and osteoarthritis (OA) occurrence remains unclear. Existing research needs to clearly understand how basal metabolic rate (BMR) regulates this relationship. Therefore, using a two-step bidirectional Mendelian Randomization approach, our study aims to investigate whether BMR levels mediate the causal relationship between gut microbiota and OA.

Methods

In this study, we examined publicly available summary statistics from Genome-Wide Association Studies (GWAS) to determine the correlation between gut microbiota and OA. The analysis included one primary dataset and two secondary datasets. Initially, a two-step, two-sample, and reverse MR analysis was performed to identify the causal relationship between gut microbiota and OA. Subsequently, a two-step MR analysis revealed that the relationship between microbiota and OA is mediated by BMR. Sensitivity analyses confirmed the robustness of the study results.

Results

In our analysis of the primary dataset, we discovered a positive correlation between three taxa and the outcome of OA, and eight taxa exhibited a negative correlation with the OA outcome. Through comparisons with the secondary dataset and multiple testing corrections, we found a negative association between the class Actinobacteria (OR=0.992886277, p-value = 0.003) and the likelihood of OA occurrence. Notably, knee osteoarthritis (KOA) and hip osteoarthritis (HOA) had a strong negative correlation (OR = 0.927237553/0.892581219). Our analysis suggests that BMR significantly mediates the causal pathway from Actinobacteria to OA, with a mediated effect of 2.59%. Additionally, BMR mediates 3.98% of the impact in the path from the order Bifidobacteriales and the family Bifidobacteriaceae to OA. Besides these findings, our reverse analysis did not indicate any significant effect of OA on gut microbiota or BMR.

Conclusion

Our research results indicate that an increase in the abundance of specific gut microbial taxa is associated with a reduced incidence of OA, and BMR levels mediate this causal relationship. Further large-scale randomized controlled trials are necessary to validate the causal impact of gut microbiota on the risk of OA. This study provides new insights into the potential prevention of OA by modulating the gut microbiota.
Large-scale prediction of outer-membrane multiheme cytochromes uncovers hidden diversity of electroactive bacteria and underlying pathways
Authors: Garber Arkadiy I. , Nealson Kenneth H. , Merino Nancy
Published: October 2024

Multi-heme cytochromes (MHCs), together with accessory proteins like porins and periplasmic cytochromes, enable microbes to transport electrons between the cytoplasmic membrane and extracellular substrates (e.g., minerals, electrodes, other cells). Extracellular electron transfer (EET) has been described in multiple systems; yet, the broad phylogenetic and mechanistic diversity of these pathways is less clear. One commonality in EET-capable systems is the involvement of MHCs, in the form of porin-cytochrome complexes, pili-like cytochrome polymers, and lipid-anchored extracellular cytochromes. Here, we put forth MHCscan—a software tool for identifying MHCs and identifying potential EET capability. Using MHCscan, we scanned ~60,000 bacterial and 2,000 archaeal assemblies, and identify a diversity of MHCs, many of which represent enzymes with no known function, and many found within organisms not previously known to be electroactive. In total, our scan identified ~1,400 unique enzymes, each encoding more than 10 heme-binding motifs. In our analysis, we also find evidence for modularity and flexibility in MHC-dependent EET pathways, and suggest that MHCs may be far more common than previously recognized, with many facets yet to be discovered. We present MHCscan as a lightweight and user-friendly software tool that is freely available: https://github.com/Arkadiy-Garber/MHCscan.
Comprehensive data optimization and risk prediction framework: machine learning methods for inflammatory bowel disease prediction based on the human gut microbiome data
Authors: Peng Yan , Liu Yue , Liu Yifei , Wang Jie
Published: October 2024

Over the past decade, the prevalence of inflammatory bowel disease (IBD) has significantly increased, making early detection crucial for improving patient survival rates. Medical research suggests that changes in the human gut microbiome are closely linked to IBD onset, playing a critical role in its prediction. However, the current gut microbiome data often exhibit missing values and high dimensionality, posing challenges to the accuracy of predictive algorithms. To address these issues, we proposed the comprehensive data optimization and risk prediction framework (CDORPF), an ensemble learning framework designed to predict IBD risk based on the human gut microbiome, aiding early diagnosis. The framework comprised two main components: data optimization and risk prediction. The data optimization module first employed triple optimization imputation (TOI) to impute missing data while preserving the biological characteristics of the microbiome. It then utilized importance-weighted variational autoencoder (IWVAE) to reduce redundant information from the high-dimensional microbiome data. This process resulted in a complete, low-dimensional representation of the data, laying the foundation for improved algorithm efficiency and accuracy. In the risk prediction module, the optimized data was classified using a random forest (RF) model, and hyperparameters were globally optimized using improved aquila optimizer (IAO), which incorporated multiple strategies. Experimental results on IBD-related gut microbiome datasets showed that the proposed framework achieved classification accuracy, recall, and F1 scores exceeding 0.9, outperforming comparison models and serving as a valuable tool for predicting IBD onset risk.
Semantic segmentation-based detection algorithm for challenging cryo-electron microscopy RNP samples
Authors: Vargas J. , Modrego A. , Canabal H. , Martin-Benito J.
Published: October 2024

In this study, we present a novel and robust methodology for the automatic detection of influenza A virus ribonucleoproteins (RNPs) in single-particle cryo-electron microscopy (cryo-EM) images. Utilizing a U-net architecture—a type of convolutional neural network renowned for its efficiency in biomedical image segmentation—our approach is based on a pretraining phase with a dataset annotated through visual inspection. This dataset facilitates the precise identification of filamentous RNPs, including the localization of the filaments and their terminal coordinates. A key feature of our method is the application of semantic segmentation techniques, enabling the automated categorization of micrograph pixels into distinct classifications of particle and background. This deep learning strategy allows to robustly detect these intricate particles, a crucial step in achieving high-resolution reconstructions in cryo-EM studies. To encourage collaborative advancements in the field, we have made our routines, the pretrained U-net model, and the training dataset publicly accessible. The reproducibility and accessibility of these resources aim to facilitate further research and validation in the realm of cryo-EM image analysis.
Hemoglobin α-derived peptides VD-hemopressin (α) and RVD-hemopressin (α) are involved in electroacupuncture inhibition of chronic pain
Authors: Yuan Xiaocui , Guo Yixiao , Yi Huiyuan , Hou Xuemei , Zhao Yulong , Wang Yuying , Jia Hong , Baba Sani Sa’idu , Li Man , Huo Fuquan
Published: October 2024

Introduction

Knee osteoarthritis (KOA) is a chronic degenerative bone metabolic disease that primarily affects older adults, leading to chronic pain and disability that affect patients’ daily activities. Electroacupuncture (EA) is a commonly used method for the treatment of chronic pain in clinical practice. Previous studies indicate that the endocannabinoid system is involved in EA analgesia, but whether endocannabinopeptide VD-hemopressin (α) and RVD-hemopressin (α) derived from hemoglobin chains are involved in EA analgesia is unclear.

Methods

RNA-seq technology was used to screen which genes involved in EA analgesia. The expression of hemoglobin α chain and 26S proteasome were determined by Western blotting. The level of VD-hemopressin (α) and RVD-hemopressin (α) were measured by UPLC-MS/MS. Microinjection VD-Hemopressin (α), RVD-Hemopressin (α) and 26S proteasome inhibitor MG-132 into vlPAG, then observe mechanical and thermal pain thresholds.

Results

Therefore, we used RNA-seq to obtain differentially expressed genes Hba-a1 and Hba-a2 involved in EA analgesia in the periaqueductal gray (PAG), which were translated into the hemoglobin α chain. EA significantly increased the expression of the hemoglobin α chain and the level of hemopressin (α) and RVD-hemopressin (α). Microinjection of VD-hemopressin (α) and RVD-hemopressin (α) into the ventrolateral periaqueductal gray (vlPAG) mimicked the analgesic effect of EA, while CB1 receptor antagonist AM251 reversed this effect. EA significantly increased the expression of 26S proteasome in KOA mice. Microinjection of 26S proteasome inhibitor MG132 before EA prevented both the anti-allodynic effect and upregulation of the concentration of RVD-hemopressin (α) by EA treatment and upregulated the expression of the hemoglobin α chain.

Discussion

Our data suggest that EA upregulated the concentration of VD-hemopressin (α) and RVD-hemopressin (α) through enhancement of the hemoglobin α chain degradation by 26S proteasome in the PAG, then activated the CB1 receptor, thereby exerting inhibition of chronic pain in a mouse model of KOA. These results provide new insights into the EA analgesic mechanisms and reveal possible targets for EA treatment of chronic pain.
Feature diffusion reconstruction mechanism network for crop spike head detection
Authors: Ming Rui , Gong Qian , Yang Chen , Luo Haibo , Song Cancan , Zhou Zhiyan
Published: October 2024

Introduction

Monitoring crop spike growth using low-altitude remote sensing images is essential for precision agriculture, as it enables accurate crop health assessment and yield estimation. Despite the advancements in deep learning-based visual recognition, existing crop spike detection methods struggle to balance computational efficiency with accuracy in complex multi-scale environments, particularly on resource-constrained low-altitude remote sensing platforms.

Methods

To address this gap, we propose FDRMNet, a novel feature diffusion reconstruction mechanism network designed to accurately detect crop spikes in challenging scenarios. The core innovation of FDRMNet lies in its multi-scale feature focus reconstruction and lightweight parameter-sharing detection head, which can effectively improve the computational efficiency of the model while enhancing the model's ability to perceive spike shape and texture.FDRMNet introduces a Multi-Scale Feature Focus Reconstruction module that integrates feature information across different scales and employs various convolutional kernels to capture global context effectively. Additionally, an Attention-Enhanced Feature Fusion Module is developed to improve the interaction between different feature map positions, leveraging adaptive average pooling and convolution operations to enhance the model's focus on critical features. To ensure suitability for low-altitude platforms with limited computational resources, we incorporate a Lightweight Parameter Sharing Detection Head, which reduces the model's parameter count by sharing weights across convolutional layers.

Results

According to the evaluation experiments on the global wheat head detection dataset and diverse rice panicle detection dataset, FDRMNet outperforms other state-of-the-art methods with mAP@.5 of 94.23%, 75.13% and R2 value of 0.969, 0.963 between predicted values and ground truth values. In addition, the model's frames per second and parameters in the two datasets are 227.27,288 and 6.8M, respectively, which maintains the top three position among all the compared algorithms.

Discussion

Extensive qualitative and quantitative experiments demonstrate that FDRMNet significantly outperforms existing methods in spike detection and counting tasks, achieving higher detection accuracy with lower computational complexity.The results underscore the model's superior practicality and generalization capability in real-world applications. This research contributes a highly efficient and computationally effective solution for crop spike detection, offering substantial benefits to precision agriculture practices.
Comparing performances of different statistical models and multiple threshold methods in a nested association mapping population of wheat
Authors: Sandhu Karansher S. , Burke Adrienne B. , Merrick Lance F. , Pumphrey Michael O. , Carter Arron H.
Published: October 2024

Nested association mapping (NAM) populations emerged as a multi-parental strategy that combines the high statistical power of biparental linkage mapping with greater allelic richness of association mapping. Several statistical models have been developed for marker-trait associations (MTAs) in genome-wide association studies (GWAS), which ranges from simple to increasingly complex models. These statistical models vary in their performance for detecting real association with the avoidance of false positives and false negatives. Furthermore, significant threshold methods play an equally important role for controlling spurious associations. In this study, we compared the performance of seven different statistical models ranging from single to multi-locus models on eight different simulated traits with varied genetic architecture for a NAM population of spring wheat (Triticum aestivum L.). The best identified model was further used to identify MTAs for 11 different agronomic and spectral reflectance traits, which were collected on the NAM population between 2014 and 2016. The “Bayesian information and linkage disequilibrium iteratively nested keyway (BLINK)” model performed better than all other models observed based on QQ plots and detection of real association in a simulated data set. The results from model comparison suggest that BLINK controls both false positives and false negatives under the different genetic architecture of simulated traits. Comparison of multiple significant threshold methods suggests that Bonferroni correction performed superior for controlling false positives and false negatives and complements the performance of GWAS models. BLINK identified 45 MTAs using Bonferroni correction of 0.05 for 11 different phenotypic traits in the NAM population. This study helps identify the best statistical model and significant threshold method for performing association analysis in subsequent NAM population studies.
Mindfulness-based relapse prevention targeting psychological craving and trait mindfulness in young Chinese women with methamphetamine dependence: a randomized controlled trial
Authors: Liu Xuan , Zhang Yidan , Cheng Hongxin , Dong Honglin , You Yuting , Wu Yuxi , Yang Chunli , Jing Lushi
Published: October 2024

Methods

We recruited 58 MA-dependent young adult females from a compulsory isolation drug rehabilitation center in Sichuan Province and randomly divided them into an MBRP group (n = 29) and a control group (n = 29) according to their degree of psychological craving. The MBRP group received 2 hours of MBRP training twice a week for 4 weeks, alongside routine treatment at the drug rehabilitation center. Meanwhile, the control group solely received routine treatment at the drug rehabilitation center without any additional interventions. The assessment was conducted before and immediately after the intervention, with the Compulsive Drug Use Scale (OCDUS) used to assess craving and the Five-Factor Mindfulness Scale (FFMQ) used to assess trait mindfulness. Also, a “mental feedback monitoring balance” instrument was used to assess concentration and relaxation during some training sessions. This randomized trial was conducted to evaluate the effectiveness of decreasing psychological craving and increasing trait mindfulness.

Results

At baseline, there were no significant differences in total or dimension scores for FFMQ or OCDUS between the two groups (all P > 0.05). After the intervention, the repeated measures ANOVA showed a significant time main effect on changes in observing, non-judging, and non-reacting scores (all P < 0.05), and a significant interaction effect between time and group on both FFMQ total score and OCDUS score (P < 0.01 or P < 0.05). Mental feedback monitoring indicated significant improvement in concentration and relaxation after breath meditation exercises (P < 0.05 or P < 0.001). Additionally, the MBRP group showed improved relaxation during the body scan exercise (P < 0.01).

Conclusion

MBRP training can improve the trait mindfulness of MA addicts and reduce psychological cravings effectively.
Post-implementation knowledge retention of stroke: the lasting influence of FAST Heroes
Authors: Orologa Emilia , Baskini Maria , Tsakpounidou Kalliopi , Keramydas Christos , Proios Hariklia
Published: October 2024

Background

FAST Heroes is a kindergarten-based educational program that teaches young children and their extended families (parents, grandparents), the main stroke symptoms (Face, Arm, and Speech), and the timely and appropriate steps in the event of a suspected stroke (Time). However, post-campaign knowledge retention remains a challenge.

Aims

The purpose of the current study was to investigate whether and to what extent grandparents’ stroke knowledge is maintained 44 months after the initial implementation of the program.

Methods

Forty-five participants engaged in the present study (35 women, 10 men; 72.8§5.3) and completed an adapted version of the FAST Heroes Stroke Preparedness Questionnaire via phone calls.

Results

Compared to immediately post-program implementation, respondents were still able to recall arm weakness (OR = 1.63; p = 0.246) and slurred speech (OR = 2.02; p = 0.075) as main stroke symptoms. A decrease was observed in recalling facial drooping (OR = 0.44; p = 0.042). Reporting of the appropriate course of action, was found to be increased (OR = 4.17; p < 0.001). Respondents remembered the emergency number to call, i.e., 112 (OR = 0.97; p = 0.947).

Conclusion

The results showed that awareness regarding the common signs of a stroke and the importance of promptly contacting emergency services following a stroke, in the population group mostly affected by stroke, is retained. Exploring knowledge preservation in a greater sample size is warranted.
Determining the acceptance of e-mental health interventions in elite athletes using the unified theory of acceptance and use of technology
Authors: Geiger Sheila , Aufderlandwehr Julia , Esser Anna Julia , Schadendorf Theresa , Muehlbauer Thomas , Skoda Eva-Maria , Teufel Martin , Bäuerle Alexander
Published: October 2024

Background

Elite athletes are exposed to many different sport-specific stressors that may put them at particular risk for mental health symptoms and disorders. E-mental health interventions could be a feasible option to support elite athletes in need. The aim of the present study was to assess the acceptance of e-mental health interventions among elite athletes and explore its underlying drivers and barriers.

Materials and methods

A cross-sectional study was conducted with N = 382 elite athletes. Of these, N = 275 (71.99%, 167 females) were included in the statistical analyses. The impact of various sociodemographic, sport-related and medical characteristics on acceptance was assessed. EHealth-related data and acceptance of e-mental health interventions were examined using a modified assessment based on the Unified Theory of Acceptance and Use of Technology (UTAUT).

Results

Overall, the acceptance of e-mental health interventions in elite athletes can be classified as high (M = 3.69 SD = 0.97). In the UTAUT regression model sex, financial situation, depression symptoms, digital confidence, digital overload as well as the UTAUT predictors performance expectancy, effort expectancy, and social influence predicted acceptance significantly.

Conclusions

The UTAUT model has proven to be a valuable instrument in predicting of acceptance of e-mental health interventions in elite athletes. Given the strong association between acceptance and future use, new interventions should focus on the explored factors to establish effective e-mental health interventions for elite athletes.
Data-Driven Model-Free Adaptive Containment Control for Uncertain Rehabilitation Exoskeleton Robots with Input Constraints
Authors: Pei Xinglong , Fang Xiaoke , Wen Liqun , Zhang Yan , Wang Jianhui
Published: October 2024

This paper presents a data-driven model-free adaptive containment control (MFACC) scheme for uncertain rehabilitation exoskeleton robots, where the robotic exoskeleton dynamics are uncertain with saturation constraints. To handle uncertainties of the robotic dynamics, a model-free adaptive control (MFAC) strategy is established by linearizing the robotic exoskeleton dynamics into an equivalent data model. Considering the integral additive effect of the traditional MFAC method, an improved MFAC controller is designed in this paper. Since actuators with saturation constraints constantly affect the safety of patients during rehabilitation training, we construct a new criterion function with active constraints for the critical function of the MFAC algorithm and adopt the Hildreth quadratic programming algorithm to find the constrained optimal solution to overcome this limitation. The proposed MFACC scheme is rigorously proven by the compression mapping method to demonstrate model-free stability. Finally, the proposed control scheme is verified to be effective by simulation studies of the robotic SimMechanics model.
Programmable Hydrogel-Based Soft Robotics via Encoded Building Block Design
Authors: Pruksawan Sirawit , Chua Zhan Au , Chong Yi Ting , Wang FuKe
Published: October 2024

Hydrogels have revolutionized the field of soft robotics with their ability to provide dynamic and programmable responses to different stimuli, enabling the fabrication of highly adaptable and flexible robots. This continual development holds significant promise for applications in biomedical devices, active implants, and sensors due to the biocompatibility of hydrogels. Actuation in hydrogel-based soft robotics relies on variations in material properties, structural design, or a combination of both to generate desired movements and behaviors. While such traditional approaches enable hydrogel actuation, they often rely on complex material design, bringing challenges to hydrogel fabrication and hindering practical use. Therefore, this work seeks to present a simplified and versatile approach for fabricating programmable single-component hydrogel-based soft robotics using an encoded building block design concept and 3D printing. A series of structural building blocks have been designed to achieve various actuation characteristics, including the direction, degree, and kinetics of actuation. By assembling these building blocks into various configurations, a broader range of actuation responses can be encoded, allowing for the fabrication of versatile, programmable soft robotics using a single uniform material through vat photopolymerization 3D printing. This approach enables adaptation to a wide range of applications, providing highly customizable encoding designs.
Thrust Model and Trajectory Design of an Interplanetary CubeSat with a Hybrid Propulsion System
Authors: Quarta Alessandro A.
Published: October 2024

This paper analyzes the performance of an interplanetary CubeSat equipped with a hybrid propulsion system (HPS), which combines two different types of thrusters in the same deep space vehicle, in a heliocentric transfer between two assigned (Keplerian) orbits. More precisely, the propulsion system of the CubeSat considered in this work consists of a combination of a (low-performance) photonic solar sail and a more conventional solar electric thruster. In particular, the characteristics of the solar electric thruster are modeled using a recent mathematical approach that describes the performance of the miniaturized engine that will be installed on board the proposed ESA’s M-ARGO CubeSat. The latter will hopefully be the first interplanetary CubeSat to complete a heliocentric transfer towards a near-Earth asteroid using its own propulsion system. In order to simplify the design of the CubeSat attitude control subsystem, we assume that the orientation of the photonic solar sail is kept Sun-facing, i.e., the sail reference plane is perpendicular to the Sun-CubeSat line. That specific condition can be obtained, passively, by using an appropriate design of the shape of the sail reflective surface. The performance of an HPS-based CubeSat is analyzed by optimizing the transfer trajectory in a three-dimensional heliocentric transfer between two closed orbits of given characteristics. In particular, the CubeSat transfer towards the near-Earth asteroid 99942 Apophis is studied in detail.
Female and Migrant Entrepreneurship in SOS Children’s Villages in the Lambayeque Region, Peru
Authors: Vidal-Taboada Silvia Lourdes , Fernández-Miranda Marina , Vásquez-Caballero Luis Alberto
Published: October 2024

This quantitative research analyzes the entrepreneurial competencies of in-migrant women in the Children’s Village of the Lambayeque Region. With a sample of 79 women, 39 Peruvian and 40 Venezuelan, online surveys and observation forms were operated for 18 months (2021–2022). Using a Likert scale of 55 questions and nine dimensions, competencies such as opportunity seeking, risk anticipation, persistence, self-exertion, and more were assessed. Data were analyzed using correlations, ANOVA, logistic regression, and principal component analysis (PCA). The results revealed significant differences between nationalities, with Venezuelan women having higher competencies. The study identified two principal components that explain 57.663% of the total variance, representing initiative and quality, as well as control and responsibility. These findings suggest the need for specific training programs to strengthen the entrepreneurial competencies of these women. The inductive methodology and quantitative analysis provided a clear vision of entrepreneurial competencies, contributing to the improvement of support and training programs.
Research and Experimentation on Sparse–Dense Interphase Curved-Tooth Sorghum Threshing Technology
Authors: Ma Jie , He Qinghao , Geng Duanyang , Niu Lin , Cui Yipeng , Yu Qiming , Yin Jianning , Wang Yang , Ni Lei
Published: October 2024

The high-speed development of the liquor industry brings sorghum demand, which is increasingly strong at the moment. Still, its harvesting mechanization level is low, and with the design of a longitudinal flow sparse and dense curved-teeth sorghum threshing technology, the harvester’s work quality is improved by the reduction of seed impurities. This article describes the working principle of the harvester, the overall distribution of threshing elements, and force analysis of the threshing aspects to determine the structure of the threshing elements. The orthogonal test was carried out, with a sparse–dense interphase threshing drum as the research object, selecting operating speed, threshing element bending angle, and threshing element mounting angle as the test factors, with the entrainment loss rate and the net threshing rate as the assessment indexes for the three-factor, three-level test, and the use of Design-Expert to establish a mathematical regression model between the factors and the two indicators, resulting in the following optimized parameters: when the operating speed is 1.0 m·s−1, the bending angle of the threshing element is 80°, and the mounting angle of the threshing element is 45°, the loss rate of entrainment is 1.89%, and the net threshing rate is 95.53%. The machine’s design indexes are in line with relevant national standards and can meet the demand for mechanized harvesting of sorghum.
Chinese Bayberry Detection in an Orchard Environment Based on an Improved YOLOv7-Tiny Model
Authors: Chen Zhenlei , Qian Mengbo , Zhang Xiaobin , Zhu Jianxi
Published: October 2024

The precise detection of Chinese bayberry locations using object detection technology is a crucial step to achieve unmanned harvesting of these berries. Because of the small size and easy occlusion of bayberry fruit, the existing detection algorithms have low recognition accuracy for such objects. In order to realize the fast and accurate recognition of bayberry in fruit trees, and then guide the robotic arm to carry out accurate fruit harvesting, this paper proposes a detection algorithm based on an improved YOLOv7-tiny model. The model introduces partial convolution (PConv), a SimAM attention mechanism and SIoU into YOLOv7-tiny, which enables the model to improve the feature extraction capability of the target without adding extra parameters. Experimental results on a self-built Chinese bayberry dataset demonstrate that the improved algorithm achieved a recall rate of 97.6% and a model size of only 9.0 MB. Meanwhile, the precision of the improved model is 88.1%, which is 26%, 2.7%, 4.7%, 6.5%, and 4.7% higher than that of Faster R-CNN, YOLOv3-tiny, YOLOv5-m, YOLOv6-n, and YOLOv7-tiny, respectively. In addition, the proposed model was tested under natural conditions with the five models mentioned above, and the results showed that the proposed model can more effectively reduce the rates of misdetections and omissions in bayberry recognition. Finally, the improved algorithm was deployed on a mobile harvesting robot for field harvesting experiments, and the practicability of the algorithm was further verified.
Risk Mitigation in Environmental Conservation for Potato Production in Cisangkuy Sub-Watershed, Bandung Regency, West Java, Indonesia
Authors: Syamsiyah Nur , Qanti Sara Ratna , Rochdiani Dini
Published: October 2024

Potatoes are a crop that thrives in highland areas, and Bandung Regency is one of the major potato production centers in West Java. This production center is located in an environmentally focused village development area within the Cisangkuy Sub-Watershed of Bandung Regency. The purpose of this study is to identify risks arising from various risk sources and to formulate risk control strategies for potato production in this region. The method used is the house of risk (HOR) method. In farming activities, farmers must comply with environmental regulations. However, many farmers are still unaware of the importance of environmental sustainability, particularly in their use of chemicals. To actively engage in environmental management efforts, it is crucial to understand the characteristics of potato farmers in Bandung Regency, especially those located in the development area of environmentally focused villages within the Cisangkuy Sub-Watershed. The results of this study identified 33 risk events. The risk event with the highest impact is waterlogged plants (E10), with an impact value of 8.9. Based on the Pareto diagram, 16 priority risk sources need to be addressed. The most significant risk source identified is the use of uncertified seeds (A29). To mitigate risks in potato production, 21 preventive actions (PAs) have been proposed. One of the most effective strategies is for farmers to purchase seed potatoes directly from Balitsa (PA1), with an effectiveness ratio (ETD) of 4372. Another recommended strategy is to purchase certified seeds from other breeders (PA2). These strategies are prioritized to reduce the risks faced by potato farmers.
Mapping PM2.5 Sources and Emission Management Options for Bishkek, Kyrgyzstan
Authors: Guttikunda Sarath K. , Zlatev Vasil B. , Dammalapati Sai Krishna , Sahoo Kirtan C.
Published: October 2024

Harsh winters, aging infrastructure, and the demand for modern amenities are major factors contributing to the deteriorating air quality in Bishkek. The city meets its winter heating energy needs through coal combustion at the central heating plant, heat-only boilers, and in situ heating equipment, while diesel and petrol fuel its transportation. Additional pollution sources include 30 km2 of industrial area, 16 large open combustion brick kilns, a vehicle fleet with an average age of more than 10 years, 7.5 km2 of quarries, and a landfill. The annual PM2.5 emission load for the airshed is approximately 5500 tons, resulting in an annual average concentration of 48 μg/m3. Wintertime daily averages range from 200 to 300 μg/m3. The meteorological and pollution modeling was conducted using a WRF–CAMx system to evaluate PM2.5 source contributions and to support scenario analysis. Proposed emissions management policies include shifting to clean fuels like gas and electricity for heating, restricting secondhand vehicle imports while promoting newer standard vehicles, enhancing public transport with newer buses, doubling waste collection efficiency, improving landfill management, encouraging greening, and maintaining road infrastructure to control dust emissions. Implementing these measures is expected to reduce PM2.5 levels by 50–70% in the mid- to long-term. A comprehensive plan for Bishkek should expand the ambient monitoring network with reference-grade and low-cost sensors to track air quality management progress and enhance public awareness.
Procedural Sedation and Analgesia in an Australian Emergency Department: Results of the First 3 Months of a Procedural Sedation Registry
Authors: Tran Viet , Whitfield James , Askaroff Natasha , Barrington Giles
Published: October 2024

Background: Procedural sedation and analgesia (PSA) is commonly performed in emergency departments (EDs) to reduce anxiety, discomfort, or pain during a procedure. The primary goal of PSA is to produce a state of relaxation and drowsiness without eliminating the patient’s protective reflexes. Despite the discovery of new techniques and medications to deliver PSA, there is a paucity of research evaluating PSA in EDs over the last decade. We aim to describe the current practice of PSA in an Australian tertiary mixed ED with 75,000 presentations per year. Methods: A retrospective study of the initial 3 months of a PSA registry, which was part of the Tasmanian Emergency Care Outcomes Registry, was analyzed; Results: All told, 80 consecutive cases were entered over a 3-month period, with pediatric patients (<14 years old) making up 35% of all cases. Joint reductions (17, 39%) and fracture reductions (13, 29%) were the most common indications for the adult population, whilst fracture reductions (9, 36%), laceration repairs (7, 28%), and other distressing procedures (7, 28%) were the most common indications in the pediatric cohort. Pharmacological approaches also differed between groups, with ketamine (25, 92%) preferred in the pediatric cohort whilst the combination of propofol and fentanyl (22, 42%) was preferred in the adult cohort. No adverse events were recorded in the pediatric cohort whilst 6 (8%) minor events occurred in the adult population, with no severe events occurring for either cohort. PSA also occurred more frequently at 0900–1000 and the incidence was reduced between 0000 and 0800. Conclusions: PSA is commonly performed in our tertiary mixed ED and is both safe and effective, with non-severe complication rates similar to those in the reported literature. Severe complications are rare and therefore a larger cohort will be required to assess this aspect. The approach to ED PSA is also different between pediatric and adult populations and therefore research needs to differentiate both populations.
Bison, Elk, and Other Captive Wildlife Species Humoral Immune Responses against SARS-CoV-2
Authors: Ardalan Mehrnaz , Cool Konner , Gaudreault Natasha N. , Bold Dashzeveg , Rojas Catherine , Mannix Anna , Seetahal Janine , Richt Juergen A. , Pogranichniy Roman M.
Published: October 2024

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, has been found to infect various domestic and wild animal species. In this study, convenience serum samples from 575 bison, 180 elk, and 147 samples from various wildlife species collected between 2020 and 2023 from several regions in the United States were analyzed for the presence of SARS-CoV-2-specific antibodies. Two commercial ELISA assays based on the inhibition of the SARS-CoV-2 receptor-binding domain (sVNT) or the nucleocapsid protein (N-ELISA) of SARS-CoV-2 were used. Positive samples from the sVNT were additionally evaluated using a conventional virus neutralization test (VNT). Our results indicated that 1.2% of bison, 2.2% of elk, and 4.1% of the other wildlife species serum samples were seropositive in the sVNT, whereas 4.2% of bison, 3.3% of elk, and 1.4% of the other captive wildlife species serum samples tested positive by the N-ELISA. Among the sVNT serum samples, two samples from bison, one sample from elk, and five serum samples from other wildlife species (one cheetah, one gorilla, two lions, and one hippopotamus) had neutralizing antibody titers in the VNT, indicating these species are susceptible to SARS-CoV-2 infection. These findings highlight the importance of broad surveillance efforts for the effective monitoring of SARS-CoV-2 in non-human hosts.
Validation of a Commercial ELISA Kit for Non-Invasive Measurement of Biologically Relevant Changes in Equine Cortisol Concentrations
Authors: Share Elizabeth R. , Mastellar Sara L. , Suagee-Bedore Jessica K. , Eastridge Maurice L.
Published: October 2024

The measurement of fecal cortisol/corticosterone metabolites (FCMs) is often used to quantify the stress response. The sampling method is relatively non-invasive, reduces concern for elevation of cortisol from the sampling method, and has been shown to measure cortisol more consistently without the daily diurnal rhythm observed in blood. Commercial ELISA (enzyme-linked immunoassay) kits offer benefits over previously validated immunoassay methods but lack validation. The objective of this study was to evaluate a commercial ELISA kit (Arbor AssaysTM DetectX® Cortisol ELISA kit, K003-H1, Ann Arbor, MI, USA) and provide analytical and biologic validation of equine fecal and plasma samples. Horses (4 male, 4 female, mean ± SD: 4 ± 5 yr) were transported for 15 min with limited physical and visual contact via a livestock trailer. Blood and fecal samples were collected pre- and post-transportation. Parallelism, accuracy, and precision tests were used to analytically validate this kit. Data were analyzed using PROC MIXED in SAS 9.4. Plasma cortisol concentrations increased in response to trailering (254.5 ± 26.4 nmol/L, 0 min post-transportation) compared to pre-transportation (142.8 ± 26.4 nmol/L). FCM concentrations increased 24 h post-trailering (10.8 ± 1.7 ng/g) when compared to pre-transportation (7.4 ± 1.7 ng/g). These data support that changes in FCMs can be observed 24 h post-stressor. In conclusion, the Arbor AssaysTM DetectX® Cortisol ELISA kit is a reliable, economic option for the measurement of biologically relevant changes in cortisol in equine plasma and FCMs.