bluuebunny/crossref_metadata_2025 huggingface dataset:
The Association of Socio-Economic Factors and Indigenous Crops on the Food Security Status of Farming Households in KwaZulu-Natal Province
Authors: Shelembe Nomfundo , Hlatshwayo Simphiwe Innocentia , Modi Albert , Mabhaudhi Tafadzwanashe , Ngidi Mjabuliseni Simon Cloapas
Published: March 2024

Indigenous crops have been proposed as part of a solution for household food security and sustainable farming systems. However, they have been overlooked and underutilised by households and farmers despite their potential contribution to household food security. The objective of this paper was to determine the association of socio-economic factors and indigenous crops with the household food security of farming households. About 260 farming households were selected using a simple random sampling procedure. The food security status was measured through the use of the Household Food Insecurity Access Scale (HFIAS). The Chi-square test and extended ordered probit regression model assessed the relationship of socio-economic factors and indigenous crops with household food security status. The results from the HFIAS showed that farming households were largely in the mildly and moderately food-insecure categories, with 34.2% and 36.2% of the sampled farmers found in these categories, respectively. The Chi-square test showed a statistically significant relationship between food security status and socio-economic factors. Young men and everyone were perceived to be the ones likely to consume indigenous crops. Consumption of indigenous crops was perceived to be associated with food security. The results also showed that farming experience is likely to positively contribute to the food security status of the farming households. Selling indigenous crops in a formal market is perceived to be associated with food security compared to selling in an informal market. This study concludes that consuming indigenous crops is likely associated with improved food security. Identifying an appropriate market for sales of indigenous crops is imperative. Government, extension officers, and nutritionists must conduct training workshops to encourage households to grow, market and buy indigenous crops. Government and policymakers need to include indigenous crops in the national food and nutrition security policy and create formal markets for indigenous crops.
Effects of Different Spray Adjuvants on the Permeation of Dinotefuran in Rice Leaves
Authors: Xu Guangchun , Yan Dongdong , Fang Wensheng , Xu Dejin , Xu Lu , Wang Qiuxia , Cao Aocheng
Published: March 2024

This study investigated the efficacy of three spray adjuvants (Coerce, Wetcit, and Silwet408) in enhancing dinotefuran permeation in rice leaves. Different concentrations of these adjuvants were tested using an external standard method. The rice leaf surface was analyzed by using the van Oss–Chaudhury–Good method to establish a link between surface free energy (SFE) and dinotefuran permeation. All of the adjuvants effectively increased dinotefuran permeation in rice leaves, with the highest permeation of 8.496 mg/kg achieved using Wetcit at 1000 mg/L. The SFE of the rice leaf surface was determined to be 29.28 mJ/m2. A notable correlation was observed between the energy difference (the SFE of the pesticide liquid versus the SFE of the rice leaf surface) and permeation. Various fitting methods, including linear, exponential, logarithmic, polynomial, and power methods, were applied. Polynomial fitting demonstrated the highest coefficient of determination (R2 > 0.9000). The relationship between the permeation (y) and energy difference (Δγ) conformed to the polynomial equation y = aΔγ2 + bΔγ + c, where a, b, and c are constants. This model provides a predictive tool for the optimal dosage of spray adjuvants according to target plant characteristics, enhancing the understanding of the interaction between pests and pesticides.
Sustainability in Food Production: A High-Efficiency Offshore Greenhouse
Authors: Barreca Francesco
Published: March 2024

The world’s population is expected to increase by nearly two billion in the next 30 years; the population will increase from 8 billion to 9.7 billion by 2050 and could peak at 10.4 billion by the mid-2080s. The extreme weather triggered by global climate change has severely hit crop yields in open-field cultivation and led to an increase in food prices. Furthermore, in the last few years, emergency events such as the COVID-19 pandemic, wars/conflicts, and economic downturns have conditioned agricultural production and food security around the world. Greenhouses could be efficient cultivation systems because they enable food production in a sustainable way, limiting contact between pollutants and plants and optimizing the use of water, energy, and soil. This paper proposes a novel dome-soilless greenhouse concept for tomato cultivation in the Mediterranean area. The proposed greenhouse is fixed on a sea platform to take advantage of the seawater cooling environment and to integrate water consumption into a hydroponic system. In order to evaluate the best covering solution material to adopt, a few thermal and photometric characteristics of greenhouse covering materials were evaluated using a simplified method. A dynamic simulation was carried out to compare the proposed seawater cooling system with a conventional cooling tower in terms of the electric energy spent to maintain the inside temperature range at 13–25 °C across all seasons in the year. The proposed heating, ventilation, and air conditioning (HVAC) system allowed a total annual energy saving of more than 10%. The energy saved was a result of the better cooling performance of the seawater heat exchange that allowed energy saving of about 14% on cooling. The comparison between the model characterised by a 6 mm polycarbonate coupled with UbiGro film and a seawater cooling system, and the model including a 6 mm polycarbonate coupled with a clarix blue film covering and a tower cooling system highlighted energy saving of about 20%. The obtained results indicate possible future directions for offshore greenhouses to carry out independent production together with the integration of photovoltaic modules, water treatment plants, and smart remote-control systems.
Inversion of Soil Salinity in the Irrigated Region along the Southern Bank of the Yellow River Using UAV Multispectral Remote Sensing
Authors: Wang Yuxuan , Qu Zhongyi , Yang Wei , Chen Xi , Qiao Tian
Published: March 2024

Soil salinization is a global issue confronting humanity, imposing significant constraints on agricultural production in the irrigated regions along the southern bank of the Yellow River. This, in turn, leads to the degradation of the ecological environment and inadequate grain yields. Hence, it is essential to explore the magnitude and spatial patterns of soil salinization to promote efficient and sustainable agricultural development. This study carried out a two-year surface soil sampling experiment encompassing the periods before spring irrigation and the budding, flowering, and maturity stages of sunflower fields in the irrigated area along the southern bank of the Yellow River. It employed deep learning in conjunction with multispectral remote sensing conducted by UAV to estimate soil salinity levels in the sunflower fields. Following the identification of sensitive spectral variables through correlation analysis, we proceeded to model and compare the accuracy and stability of various models, including the deep learning Transformer model, traditional machine learning BP neural network (BPNN), random forest model (RF), and partial least squares regression model (PLSR). The findings indicate that the precision of soil salinity content (SSC) retrieval in saline–alkali land can be significantly enhanced by incorporating the RE band of UAV data. Four SSC inversion models were developed using the most suitable spectral variables, resulting in precise soil salinity inversion. The model order based on accuracy and stability was Transformer > BPNN > RF > PLSR. Notably, the Transformer model achieved a prediction accuracy exceeding 0.8 for both the training and test datasets, as indicated by R2 values. The precision order of the soil salinity inversion model in each period is as follows: before spring irrigation > budding period > maturity period > flowering stages. Additionally, the accuracy is higher in the bare soil stage compared to the crop cover stage. The Transformer model exhibited RMSE and R2 values of 2.41 g kg−1 and 0.84 on the test datasets, with the salt inversion results aligning closely with field-measured data. The results showed that the Transformer deep learning model integrated with RE band data significantly enhances the precision and efficiency of soil salinity inversion within the irrigated regions along the south bank of the Yellow River.
Artificial Neural Networks to Predict Electrical Conductivity of Groundwater for Irrigation Management: Case of Campo de Cartagena (Murcia, Spain)
Authors: Mateo Luis F. , Más-López M. Isabel , García-del-Toro Eva M. , García-Salgado Sara , Quijano M. Ángeles
Published: March 2024

Groundwater is a crucial water resource, particularly in regions with intensive agriculture and a semi-arid climate, such as Campo de Cartagena (Murcia, Spain). Groundwater salinity in the area can be attributed to hydrogeological characteristics, irrigation return water, or even marine intrusion and communication between aquifers. The management of these waters is essential to maintain sustainable agriculture in the area. Therefore, two groundwater salinity prediction models were developed, a backpropagation artificial neural network (ANN) model and a multiple linear regression (MLR) model, based on EC (electrical conductivity) data obtained from official information sources. The data used were the bicarbonate, calcium, chloride, magnesium, nitrate, potassium, sodium, and sulphate concentrations, as well as EC, pH, and temperature, of 495 water samples from 38 sampling stations between 2000 and 2023. Variables with the least influence on the model were discarded in a previous statistical analysis. Based on seven evaluation metrics (RMSE, MAE, R2, MPE, MBE, SSE, and AARD), the ANN model showed a sligntly better accuracy in predicting EC compared to the MLR model. As a result, the ANN model, together with crop tolerance to EC, may be an effective tool for groundwater irrigation management in these areas.
Are Supervised Learning Methods Suitable for Estimating Crop Water Consumption under Optimal and Deficit Irrigation?
Authors: Yamaç Sevim Seda , Kurtuluş Bedri , Memon Azhar M. , Alomair Gadir , Todorovic Mladen
Published: March 2024

This study examined the performance of random forest (RF), support vector machine (SVM) and adaptive boosting (AB) machine learning models used to estimate daily potato crop evapotranspiration adjusted (ETc-adj) under full irrigation (I100), 50% of full irrigation supply (I50) and rainfed cultivation (I0). Five scenarios of weather, crop and soil data availability were considered: (S1) reference evapotranspiration and precipitation, (S2) S1 and crop coefficient, (S3) S2, the fraction of total available water and root depth, (S4) S2 and total soil available water, and (S5) S3 and total soil available water. The performance of machine learning models was compared with the standard FAO56 calculation procedure. The most accurate ETc-adj estimates were observed with AB4 for I100, RF3 for I50 and AB5 for I0 with coefficients of determination (R2) of 0.992, 0.816 and 0.922, slopes of 1.004, 0.999 and 0.972, modelling efficiencies (EF) of 0.992, 0.815 and 0.917, mean absolute errors (MAE) of 0.125, 0.405 and 0.241 mm day−1, root mean square errors (RMSE) of 0.171, 0.579 and 0.359 mm day−1 and mean squared errors (MSE) of 0.029, 0.335 and 0.129 mm day−1, respectively. The AB model is suggested for ETc-adj prediction under I100 and I0 conditions, while the RF model is recommended under the I50 condition.
Testing Biochar’s Ability to Moderate Extremely Acidic Soils in Tea-Growing Areas
Authors: Ghorbani Mohammad , Amirahmadi Elnaz , Bernas Jaroslav , Konvalina Petr
Published: March 2024

Biochar as a by-product of the carbonization of biomass has an inherent potential to modify acidic soils due to its alkaline nature. To explore the mechanism and effectiveness of biochar, a case study was conducted on severely acidic soils from six fields under tea cultivation in a subtropical zone, comparing rice husk biochars, in three rates (B5, B10, B15 t ha−1), and CaCO3 as conventional liming practice. The results showed increases in pH of 71.5%, 52.7%, 30.6%, and 29.7% in B15, B10, B5, and CaCO3-treated soils compared to the control. On average, B15 and B10 treatments resulted in the highest organic matter with 12.3% and 9.7%, respectively. B15, B10, B5, and CaCO3 caused increases of 196.6%, 173.4%, 129.7%, and 100.9% in base saturation compared to the control, respectively. Also, after the application of B15, B10, and B5 treatments, the effective cation exchange capacity increased by 191.4%, 112.1%, and 39.5%; however, the application of CaCO3 resulted in a 20.1% decrease. Overall, applying biochar on acidic soils provides adequate negative charges due to its well-extended specific surface area and pore volume, which cause the absorption of additional Al+, resulting in ameliorating soil pH. The application of proper biochar could notably be more effective in improving acidic soils than conventional practices such as the overuse of CaCO3. In this regard, evaluating various biochars in terms of feedstock, pyrolysis conditions, and modification scenarios merits in-depth research in future studies.
Forced Handling Decreases Emotionality but Does Not Improve Young Horses’ Responses toward Humans and their Adaptability to Stress
Authors: Pereira-Figueiredo Inês , Rosa Ilda , Sancho Sanchez Consuelo
Published: March 2024

Horses are often still exposed to stressful or inadequate conditions and difficult relationships with humans, despite growing concerns about animal welfare. In the present study, we investigated the impact of different approaches of short-term handling sessions on young Lusitanian horses raised on a high-breed farm, specifically on their later adaptability to humans and stressful environments. Thirty-one foals (3 months old ± 15 days), from both sexes, were separated into three groups, one submitted to 3 consecutive days of handling sessions (Int-H), another to one handling session each month for 3 months (Month-H), and one left undisturbed (control). At 8 months old ± 15 days, all foals were evaluated during behavioral tests (restraint in a stock and forced-person test). Evaluations were based on behavioral observations and physiological assessments. The handled foals (Int-H and Month-H) reacted less to being isolated and restrained and better tolerated human contact and veterinary procedures than the control ones. The handled foals displayed less evasive and negative behaviors toward human approach, but also sought less human contact and did not interact, regardless of the handling timeframe. All animals displayed signs of stress when restrained in the stock, with increased neutrophil counts and CHCM levels in the blood, and no differences in metabolic (CK and LDH) and other hematological parameters. The neutrophil–lymphocyte ratio was significantly higher (p < 0.05) in handled foals than in control ones, suggesting low standards of welfare. Our data suggest that early forced handling decreases fearfulness in new environments; however, it does not improve the horses’ relationship with humans, and it decreases welfare.
The Metabolic Pathway of Bile Secretion Is Vulnerable to Salmonella enterica Exposure in Porcine Intestinal Epithelial Cells
Authors: Cai Jiajia , Chen Xiaolei , Xu Chao , Zhu Xiaoyang , Wang Haifei , Wu Shenglong , Cai Demin , Fan Hairui
Published: March 2024

Pigs can be colonized with Salmonella enterica and become established carriers. However, the mechanisms of the host’s response to Salmonella enterica infection are largely unclear. This study was constructed with the Salmonella enterica infection model in vitro using porcine intestinal epithelial cells (IPEC-J2). Transcriptome profiling of IPEC-J2 cells was carried out to characterize the effect of Salmonella enterica infection and lipopolysaccharide (LPS) treatment, in which LPS-induced inflammation was a positive control. At first, Salmonella enterica infection increased the cell apoptosis rate and induced an inflammation response in IPEC-J2. Then, the up-regulated genes were enriched in metabolic pathways, such as those for bile secretion and mineral absorption, while down-regulated genes were enriched in immune-related pathways, such as the Toll-like receptor signaling and p53 signaling pathways. Moreover, we found 368 up-regulated genes and 101 down-regulated genes in common. Then, an integrative analysis of the transcriptomic profile under Salmonella enterica infection and LPS treatment was conducted, and eight up-regulated genes and one down-regulated gene were detected. Among them, AQP8 is one critical gene of the bile secretion pathway, and its mRNA and protein expression were increased significantly under Salmonella enterica infection and LPS treatment. Thus, the AQP8 gene and bile secretion pathway may be important in IPEC-J2 cells under Salmonella enterica infection or LPS treatment.
Equine Asthma Does Not Affect Circulating Myostatin Concentrations in Horses
Authors: Kowalik Sylwester , O’reilly Maisie , Niedźwiedź Artur , Kędzierski Witold
Published: March 2024

(1) Background: The number of horses suffering from chronic respiratory diseases, resembling human asthma, is increasing but there is still a lack of reliable and accurate methods to detect these disorders. Numerous studies have found elevated plasma concentrations of one of the myokines, namely, myostatin (MSTN), in people suffering from severe asthma. MSTN normally inhibits myoblast proliferation and differentiation through autocrine or paracrine signals. Therefore, given the pathogenesis of asthma, we hypothesize that MSTN could be a useful biomarker of equine asthma. Thus, this study aimed to compare the concentration of MSTN in the blood plasma of fully healthy and asthmatic horses. (2) Methods: A total of 61 horses were clinically examined to confirm or exclude the occurrence of equine asthma, including bronchoalveolar lavage (BAL) fluid cytology performed on 49 horses. This study included three groups of horses, two of which were clinically healthy, and one of which was asthmatic. (3) Results: The mean circulatory MSTN concentration determined using the ELISA method in asthmatic horses was significantly higher than that in clinically healthy young Thoroughbred racehorses (p < 0.05), but it did not differ as compared to the group of healthy, adult leisure horses. (4) Conclusions: The obtained results did not unambiguously support our original hypothesis that MSTM may be a reliable marker for the early diagnosis of equine asthma. To the best of the authors’ knowledge, this is the first study to analyze the plasma MSTN concentration in equine asthma patients, and therefore further studies are needed to confirm our novel findings.
Bovine Colostrum Supplementation in Rabbit Diet Modulates Gene Expression of Cytokines, Gut–Vascular Barrier, and Red-Ox-Related Molecules in the Gut Wall
Authors: Riva Federica , Draghi Susanna , Inglesi Alessia , Filipe Joel , Cremonesi Paola , Lavazza Antonio , Cavadini Patrizia , Vigo Daniele , Agradi Stella , Menchetti Laura , Di Giancamillo Alessia , Aidos Lucia , Modina Silvia Clotilde , Fehri Nour Elhouda , Pastorelli Grazia , Serra Valentina , Balzaretti Claudia Maria , Castrica Marta , Severgnini Marco , Brecchia Gabriele , Curone Giulio
Published: March 2024

Rabbits, pivotal in the EU as livestock, pets, and experimental animals, face bacterial infection challenges, prompting a quest for alternatives to curb antibiotic resistance. Bovine colostrum (BC), rich in immunoregulatory compounds, antimicrobial peptides, and growth factors, is explored for disease treatment and prevention. This study assesses BC diet supplementation effects on rabbit intestines, examining gene expression. Thirty female New Zealand White rabbits at weaning (35 days) were divided into three experimental groups: control (commercial feed), 2.5% BC, and 5% BC. The diets were administered until slaughtering (81 days). BC-upregulated genes in the jejunum included IL-8, TGF-β, and CTNN-β1 at 5% BC, while PLVAP at 2.5% BC. Antioxidant-related genes (SOD1, GSR) were downregulated in the cecum and colon with 2.5% BC. BC 5% promoted IL-8 in the jejunum, fostering inflammation and immune cell migration. It also induced genes regulating inflammatory responses (TGF-β) and gastrointestinal permeability (CTNN-β1). BC 5% enhanced antioxidant activity in the cecum and colon, but no significant impact on anti-myxo antibody production was observed. These results suggest that BC has significant effects on the rabbit gastrointestinal tract’s inflammatory and antioxidant response, but further research is required to fully understand its histological and physiological impact.
Link Prediction Based on Feature Mapping and Bi-Directional Convolution
Authors: Feng Ping , Zhang Xin , Wu Hang , Wang Yunyi , Yang Ziqian , Ouyang Dantong
Published: March 2024

A considerable amount of research on link prediction has recently been driven by missing relationships between knowledge graph entities and the problem of the incompleteness of knowledge graphs. Some recent studies have shown that convolutional neural networks based on knowledge embeddings are highly expressive and have good performance in link prediction. However, we found that the convolutional neural network (CNN)-based models do not handle the link between relations and entities well. For this reason, this paper proposes a link prediction model (LPM) based on feature mapping and bi-directional convolution. For the modeling of the task, an encoding layer–mapping layer–decoding layer structure is used. Among these layers, the encoding layer adopts a graph attention network to encode multi-hop triad information and obtains richer encoding of entities and relationships. The mapping layer can realize the mapping transformation between entities and relations and project the entity encoding in the space of relation encoding to capture the subtle connection between entities and relations. The decoding layer adopts bidirectional convolution to merge and decode the triples in a sequential inverse order, which makes the decoding layer model more advantageous in prediction. In addition, the decoding layer also adopts the r-drop training method to effectively reduce the distribution error generated by training between models and enhance the robustness of the model. Our experiments demonstrated the effectiveness of mapping relations, bidirectional convolution, and r-drop, and the accuracy of the proposed model showed significant improvements for each evaluation metric on two datasets, WN18RR and FB15k-237.
Effects of Various Foot Wedges on Thigh Muscle Activity during Squatting in Healthy Adults: A Systematic Review and Meta-Analysis
Authors: Ghasemi Mohammadhossein , Gholami-Borujeni Behnam , Briem Kristín
Published: March 2024

Squatting is a common movement in daily activities, athletic training, rehabilitation programs, and even in the workplace. Identifying the effects of various foot wedges on thigh muscle activity during squatting can help specialists in terms of rehabilitation, injury prevention, physical preparation, and occupational optimization. In this study, systematic literature searches in six electronic databases (Cochrane Library, PubMed, Google Scholar, Web of Science, ScienceDirect, and Scopus) were conducted up to December 2023. Fifteen studies met the inclusion criteria (total n = 269 subjects). The results showed that posterior wedges significantly increased the overall activity of thigh muscles (p < 0.001, 12 studies). No significant change was observed for anterior (p = 0.730, six studies), medial (p = 0.169; three studies), and lateral wedges (p = 0.989, two studies). Compared with a non-wedge condition, the activity of the vastus medialis (p < 0.001, eight studies) was significantly higher using a posterior wedge during squatting, as was the activity of the rectus femoris (p = 0.021, five studies) using the anterior wedge. It seems that thigh muscle activation is modifiable with a change in footwear design, which may be useful during sports training, rehabilitation, or daily work routines.
Room Impulse Response Dataset of a Recording Studio with Variable Wall Paneling Measured Using a 32-Channel Spherical Microphone Array and a B-Format Microphone Array
Authors: Chesworth Grace , Bastine Amy , Abhayapala Thushara
Published: March 2024

This paper introduces RSoANU, a dataset of real multichannel room impulse responses (RIRs) obtained in a recording studio. Compared to the current publicly available datasets, RSoANU distinguishes itself by featuring RIRs captured using both a 32-channel spherical microphone array (mh acoustics em32 Eigenmike) and a B-format soundfield microphone array (Rode NT-SF1). The studio incorporates variable wall panels in felt and wood options, with measurements conducted for two configurations: all panels set to wood or felt. Three source positions that emulate typical performance locations were considered. RIRs were collected over a planar receiver grid spanning the room, with the microphone array centered at a height of 1.7 m. The paper includes an analysis of acoustic parameters derived from the dataset, revealing notable distinctions between felt and wood panel environments. Felt panels exhibit faster decay, higher clarity, and superior definition in mid-to-high frequencies. The analysis across the receiver grid emphasizes the impact of room geometry and source–receiver positions on reverberation time and clarity. The study also notes spatial variations in parameters obtained from the two microphone arrays, suggesting potential for future research into their specific capabilities for room acoustic characterization.
Finite Element Analysis of Load-Bearing Characteristics and Design Method for New Composite-Anchor Uplift Piles
Authors: Jiang Jiaqi , Mao Zongyuan , Chen Lihong , Wu Yongkang
Published: March 2024

This paper introduces a new type of uplift pile known as the composite-anchor pile, which employs a composite anchor composed of steel strands, grouting materials, and steel pipes as the main reinforcement. This paper extensively analyzes this pile’s load-bearing capacity and deformation characteristics through full-scale field tests and three-dimensional finite element numerical simulations. The results show that the composite-anchor pile has a more even distribution of stress, and its endurance and mechanics performance are better than others. Furthermore, this study utilizes a three-dimensional finite element refined model that has been validated using on-site test results to examine the influence of key parameters, such as the pile diameter, the number of composite-anchor cables, and the diameter of steel strands, on the load-bearing capacity of uplift piles. Building upon these findings, this paper introduces a calculating method to determine the bearing capacity of composite-anchor piles, thereby addressing the existing gap in this field.
A Segmented Calculation Method for Friction Force in Long-Distance Box Jacking Considering the Effect of Lubricant
Authors: Zhang Yunlong , Zhang Peng , Liu Kaixin , Xu Tianshuo , Xu Yong , Mei Jiahao
Published: March 2024

In box jacking, injecting lubricant around the box is an essential method to reduce excessive friction forces caused by the interaction between the box and soil. This method introduces complexity to factors controlling the friction forces, such as the pipe-soil contact state, earth pressure, and friction coefficient. In particular, during long-distance construction, different lubricant conditions come into play. These intricate scenarios hinder the accurate estimation and control of friction force throughout the entire construction period. This study analyzed the variation patterns of frictional resistance based on monitoring data from two actual cases. The lubricant condition changes during the long-distance jacking process were categorized, the effect of lubricant actions on factors controlling friction force in each segment was discussed, and a new method for calculating friction forces by partitioning the long-distance box jacking was proposed. This approach aims to enhance the prediction accuracy and was compared with the results obtained from existing models. The rationality of the new model was further validated by combining numerical simulation results with field data. The results indicate that the proposed segmented calculation model demonstrates better prediction accuracy when facing variations in actual construction conditions. It can serve as a reference for the process design and construction control of long-distance box jacking.
Effectiveness of a Nutrition Education Program for Patients with Type 2 Diabetes Mellitus
Authors: Gortzi Olga , Dimopoulou Maria , Androutsos Odysseas , Vraka Anna , Gousia Helen , Bargiota Alexandra
Published: March 2024

Diabetes is a metabolic disease that is a major health problem globally. Dietary interventions contribute to the management of the disease and the improvement in patients’ quality of life. The aim of the present study was to assess the effects of a nutrition and lifestyle education intervention on a sample of patients with diabetes. The duration of the intervention was 3 months, and it focused on the promotion of the Mediterranean diet through information pamphlets, diet plans and healthy lifestyle guidelines, which were provided in addition to patients’ standard medical treatment. Patients were enrolled in the outpatient clinic of the University Hospital of Larissa (Greece). Anthropometric and biochemical parameters were recorded at baseline and follow-up using standardized equipment and methods. The intervention improved patients’ body mass index, body composition, fasting glucose, postprandial glucose, triglycerides, HDL/LDL cholesterol and cholesterol. For smoking status, alcohol consumption and physical activity categorization, physical activity improved but not the other two indices. The results of this study show that patient education should be provided according to the nutritional recommendations for T2DM plus a more individually structured intervention. It is therefore necessary to direct the attention of doctors to the need for continuous and detailed discussions with patients in relation to both the standards of a healthy diet and the benefits it brings. Patients, for their part, need to commit to following an appropriate, healthy diet.
A Study on the Emotional Tendency of Aquatic Product Quality and Safety Texts Based on Emotional Dictionaries and Deep Learning
Authors: Tong Xingxing , Chen Ming , Feng Guofu
Published: March 2024

The issue of aquatic product quality and safety has gradually become a focal point of societal concern. Analyzing textual comments from people about aquatic products aids in promptly understanding the current sentiment landscape regarding the quality and safety of aquatic products. To address the challenge of the polysemy of modern network buzzwords in word vector representation, we construct a custom sentiment lexicon and employ the Roberta-wwm-ext model to extract semantic feature representations from comment texts. Subsequently, the obtained semantic features of words are put into a bidirectional LSTM model for sentiment classification. This paper validates the effectiveness of the proposed model in the sentiment analysis of aquatic product quality and safety texts by constructing two datasets, one for salmon and one for shrimp, sourced from comments on JD.com. Multiple comparative experiments were conducted to assess the performance of the model on these datasets. The experimental results demonstrate significant achievements using the proposed model, achieving a classification accuracy of 95.49%. This represents a notable improvement of 6.42 percentage points compared to using Word2Vec and a 2.06 percentage point improvement compared to using BERT as the word embedding model. Furthermore, it outperforms LSTM by 2.22 percentage points and textCNN by 2.86 percentage points in terms of semantic extraction models. The outstanding effectiveness of the proposed method is strongly validated by these results. It provides more accurate technical support for calculating the concentration of negative emotions using a risk assessment system in public opinion related to quality and safety.
Correlations between SSQ Scores and ECG Data during Virtual Reality Walking by Display Type
Authors: Choi Mi-Hyun , Kang Kyu-Young , Lee Tae-Hoon , Choi Jin-Seung
Published: March 2024

To encourage the application of virtual reality (VR) in physical rehabilitation, this study analyzed the occurrence of motion sickness when walking on a treadmill in virtual straight paths presented on two types of displays (screen and head-mounted displays (HMDs)) at a constant speed of 3.6 km/h. The simulator sickness questionnaire (SSQ) scores, which indicate motion sickness, were collected from the participants. In addition, the heart rate (HR) and heart rate variability (HRV; RMSSD and LF/HF ratio) were measured from electrocardiogram data. The correlations between the SSQ scores and HR and HRV were examined to identify a reliable variable for evaluating motion sickness. The SSQ scores were used to classify the data into the motion-sickness and no-motion-sickness groups. The data were classified into the motion-sickness group if a minimum difference of 15 points existed between the walking and baseline phases when using the screen and HMD; otherwise, the data were classified into the no-motion-sickness group. The HR and LF/HF ratio were higher, whereas the RMSSD was lower in the motion-sickness group. Moreover, within the motion-sickness group, the reduction in RMSSD and increase in HR and LF/HF ratio were greater with the HMD than with the screen. Regression analysis was performed on the HR, HRV, and SSQ scores to differentiate between the motion-sickness and no-motion-sickness groups. The regression analysis results showed a high negative correlation between the SSQ score and RMSSD. The results of this study can assist in controlling the occurrence of motion sickness in VR-based applications.
Enhancing CT Segmentation Security against Adversarial Attack: Most Activated Filter Approach
Authors: Lee Woonghee , Kim Younghoon
Published: March 2024

This study introduces a deep-learning-based framework for detecting adversarial attacks in CT image segmentation within medical imaging. The proposed methodology includes analyzing features from various layers, particularly focusing on the first layer, and utilizing a convolutional layer-based model with specialized training. The framework is engineered to differentiate between tampered adversarial samples and authentic or noise-altered images, focusing on attack methods predominantly utilized in the medical sector. A significant aspect of the approach is employing a random forest algorithm as a binary classifier to detect attacks. This method has shown efficacy in identifying genuine samples and reducing false positives due to Gaussian noise. The contributions of this work include robust attack detection, layer-specific feature analysis, comprehensive evaluations, physician-friendly visualizations, and distinguishing between adversarial attacks and noise. This research enhances the security and reliability of CT image analysis in diagnostics.
Low-Cost Data-Driven Robot Collision Localization Using a Sparse Modular Point Matrix
Authors: Lin Haoyu , Quan Pengkun , Liang Zhuo , Wei Dongbo , Di Shichun
Published: March 2024

In the context of automatic charging for electric vehicles, collision localization for the end-effector of robots not only serves as a crucial visual complement but also provides essential foundations for subsequent response design. In this scenario, data-driven collision localization methods are considered an ideal choice. However, due to the typically high demands on the data scale associated with such methods, they may significantly increase the construction cost of models. To mitigate this issue to some extent, in this paper, we propose a novel approach for robot collision localization based on a sparse modular point matrix (SMPM) in the context of automatic charging for electric vehicles. This method, building upon the use of collision point matrix templates, strategically introduces sparsity to the sub-regions of the templates, aiming to reduce the scale of data collection. Additionally, we delve into the exploration of data-driven models adapted to SMPMs. We design a feature extractor that combines a convolutional neural network (CNN) with an echo state network (ESN) to perform adaptive feature extraction on collision vibration signals. Simultaneously, by incorporating a support vector machine (SVM) as a classifier, the model is capable of accurately estimating the specific region in which the collision occurs. The experimental results demonstrate that the proposed collision localization method maintains a collision localization accuracy of 91.27% and a collision localization RMSE of 1.46 mm, despite a 48.15% reduction in data scale.
Frequency-Dependent Contrast Enhancement for Conductive and Non-Conductive Materials in Electrical Impedance Tomography
Authors: Nguyen Diep Quoc Tuan , Huynh Hoang Nhut , Cao Dinh Minh Quan , Huynh Thanh Ven , Tran Anh Tu , Tran Trung Nghia
Published: March 2024

This research investigates the critical role of frequency selection in Electrical Impedance Tomography (EIT), a non-invasive imaging technique that reconstructs internal conductivity distributions through injected electrical currents. Empirical frequency selection is paramount to maximizing the fidelity and specificity of EIT images. The study explores the impact of distinct frequency ranges—low, medium, and high—on image contrast and clarity, particularly focusing on differentiating conductive materials from non-conductive materials. The findings reveal distinct empirical frequency bands for enhancing the respective contrasts: 15–38 kHz for conductive materials (copper) and 45–75 kHz for non-conductive materials (acrylic resin). These insights shed light on the frequency-dependent nature of material contrast in EIT images, guiding the selection of empirical operating ranges for various target materials. This research paves the way for improved sensitivity and broader applicability of EIT in diverse areas.
Influence of Implant Number on Peri-Implant and Posterior Edentulous Area Strains in Mandibular Overdentures Retained by the New Ti–Zr (Roxolid®) Mini-Implants as Single-Units: In Vitro Study
Authors: Puljic Dario , Celebic Asja , Kovacic Ines , Petricevic Nikola
Published: March 2024

The new Ti–Zr (Roxolid®) mini-implants have not yet been fully researched. We analyzed peri-implant and posterior edentulous area microstrains during mandibular overdenture (OD) loading at different sites with different extents of forces when one-, two-, three-, or four- mini dental implants (MDIs) as single-units supported the respective ODs. The models were designed from cone beam computed tomography (CBCT) scans of an appropriate patient with narrow ridges. The mucosal thickness was 2 mm. Strain gauges were bonded on the vestibular and oral peri-implant sites, and in the distal edentulous area under the saddles. The loads were applied posteriorly bilaterally and unilaterally with 50, 100 and 150 N forces, and anteriorly with 50 and 100 N forces. Each loading was repeated 15 times. Statistical analysis included descriptive statistics, boxplots and the MANOVA. Higher forces induced higher peri-implant microstrains, as well as unilateral loadings, especially on the loaded side, in all models except the one-MDI model where anterior loads (100 N) elicited the highest peri-implant microstrain (1719.35 ± 76.0). The highest microstrains during unilateral posterior loading (right side) with 150 N force were registered from the right MDI in the two-MDI model (1836.64 ± 63.0). High microstrains were also recorded on the left side (1444.48 ± 54.6). By increasing the number of implants, peri-implant microstrains and those in the edentulous area decreased. In the three- and four-MDI models, higher microstrains were found in the posterior than in the anterior MDIs under posterior loadings. None of the recorded microstrains exceeded bone reparatory mechanisms, although precaution and additional research should be provided when only one or two MDIs support ODs.
Solution to a Conjecture on the Permanental Sum
Authors: Wu Tingzeng , Jiu Xueji
Published: March 2024

Let G be a graph with n vertices and m edges. A(G) and I denote, respectively, the adjacency matrix of G and an n by n identity matrix. For a graph G, the permanent of matrix (I+A(G)) is called the permanental sum of G. In this paper, we give a relation between the Hosoya index and the permanental sum of G. This implies that the computational complexity of the permanental sum is NP-complete. Furthermore, we characterize the graphs with the minimum permanental sum among all graphs of n vertices and m edges, where n+3≤m≤2n−3.
Allometric Growth Pattern and Hunger Tolerance of Hemibarbus maculatus Bleeker Larvae
Authors: Xie Min , Wang Pengpeng , Deng Qi , Liu Si , Zhang Zhou , Wu Hao , Xiang Jing , Zhou Jie , Yang Xin , Song Rui , Li Shaoming , Xie Zhonggui
Published: March 2024

To clarify the allometric growth pattern and hunger tolerance of Hemibarbus maculatus Bleeker larvae, the morphological lengths of their functional organs were measured continuously and their primary feeding rates under a state of starvation were studied. A control group and starvation group were set up for this study, and 10 larvae were sampled from each group every day in order to study their allometric growth pattern and starvation tolerance. The results indicated that the Hemibarbus maculatus larvae opened their mouths for feeding at 4 days after hatching, and that the yolk sac disappeared completely at 11 days after hatching. The Hemibarbus maculatus larvae preferentially developed their heads, fins, and eyes, related to the functions of feeding, balancing, and swimming, in order to cope with complex environments. The growth inflection points for the head length, pectoral fin length, dorsal fin length, eye diameter, eye spacing, snout length, and body height were characterized by total lengths of 10.93 mm, 11.67 mm, 11.67 mm, 13.17 mm, 16.53 mm, 15.13 mm, and 15.13 mm, respectively. Prior to and following the inflection point, positive allometric growth was observed in all organs. After the inflection point, the dorsal fin continued to maintain positive allometric growth, while the others changed to isometric allometric growth. A growth inflection point was not observed for trunk length or the lengths of the tail and anal fins. The trunk length always maintained negative allometry, while the tail and anal fin lengths were reversed. The growth inflection point of the tail length was at a total length of 13.68 mm. Before and after the growth inflection point, negative and isometric allometric growths were observed, respectively. According to the relationship between the total length and number of days after hatching, the growth inflection point of the Hemibarbus maculatus larvae was concentrated at TL = 10.93–16.53 mm, which was observed 14–20 days after hatching. The point of no return for the Hemibarbus maculatus larvae was 12–13 days after hatching, and the ratio of days after hatching in the mixed trophic period to the endotrophic period was 1.75, indicating that the larvae had strong hunger tolerance. Therefore, when considering a water temperature of 22.66 ± 1.56 °C, 4–5 days after hatching is the best time to cultivate in the pond, and it should not be carried out later than 12 days after hatching.
Morphofunctional Alteration of Mesenteric Lymph Nodes in the Inflammation of the Abdominal Cavity
Authors: Abdreshov Serik N. , Demchenko Georgii A. , Yeshmukhanbet Anar N. , Yessenova Makpal A. , Mankibaeva Sandugash A. , Atanbaeva Gulshat K. , Kulbayeva Marzhan S.
Published: March 2024

This paper provides data regarding the ratios of the functional structures of lymph nodes after inflammation in the abdominal organs. Lymph systems, including lymph nodes, function as filters of tissues and tissue fluids and are places of origin and lymphocyte production for normal physiological functions. They display specific morphological and functional responses in reaction to endogenous and exogenous substances. The morphological pattern of the mesenteric lymph node in experimental rat groups reflects a decrease in its immune function due to the processes of inflammation in the abdominal cavity. These processes work together with the associated organs and their involvement in the abdominal lymph nodes, in which there are discharges of the structure of the paracortical zone under conditions of reduced lymphogenic processes, according to the decrease in the size of the paracortex and the ratios of lymphoid nodes with and without germinal centers. Histological and morphometric analyses show changes in the mesenteric lymph node. These analyses are characterized by changes in the cortical and medullary substances, while the proportion of the cortical structure decreases. We also noted an increase in the number of macrophages in the lymphoid nodes and cerebral sinus, as well as a decrease in the number of mature plasmocytes, the paracortex, and the pulp strands. These changes indicate immunosuppressive effects on the lymph node. Under the conditions of inflammation, the formation of a mixed immune response occurs.
Role of Insulin-like Growth Factor-1 Receptor in Tobacco Smoking-Associated Lung Cancer Development
Authors: Shahid Ayaz , Santos Shaira Gail , Lin Carol , Huang Ying
Published: March 2024

Cancer remains a significant global health concern, with lung cancer consistently leading as one of the most common malignancies. Genetic aberrations involving receptor tyrosine kinases (RTKs) are known to be associated with cancer initiation and development, but RTK involvement in smoking-associated lung cancer cases is not well understood. The Insulin-like Growth Factor 1 Receptor (IGF-1R) is a receptor that plays a critical role in lung cancer development. Its signaling pathway affects the growth and survival of cancer cells, and high expression is linked to poor prognosis and resistance to treatment. Several reports have shown that by activating IGF-1R, tobacco smoke-related carcinogens promote lung cancer and chemotherapy resistance. However, the relationship between IGF-1R and cancer is complex and can vary depending on the type of cancer. Ongoing investigations are focused on developing therapeutic strategies to target IGF-1R and overcome chemotherapy resistance. Overall, this review explores the intricate connections between tobacco smoke-specific carcinogens and the IGF-1R pathway in lung carcinogenesis. This review further highlights the challenges in using IGF-1R inhibitors as targeted therapy for lung cancer due to structural similarities with insulin receptors. Overcoming these obstacles may require a comprehensive approach combining IGF-1R inhibition with other selective agents for successful cancer treatment.