bluuebunny/crossref_metadata_2025 huggingface dataset:
Explainable deep learning model for automatic mulberry leaf disease classification
Authors: Nahiduzzaman Md. , Chowdhury Muhammad E. H. , Salam Abdus , Nahid Emama , Ahmed Faruque , Al-Emadi Nasser , Ayari Mohamed Arselene , Khandakar Amith , Haider Julfikar
Published: September 2023

Mulberry leaves feed Bombyx mori silkworms to generate silk thread. Diseases that affect mulberry leaves have reduced crop and silk yields in sericulture, which produces 90% of the world’s raw silk. Manual leaf disease identification is tedious and error-prone. Computer vision can categorize leaf diseases early and overcome the challenges of manual identification. No mulberry leaf deep learning (DL) models have been reported. Therefore, in this study, two types of leaf diseases: leaf rust and leaf spot, with disease-free leaves, were collected from two regions of Bangladesh. Sericulture experts annotated the leaf images. The images were pre-processed, and 6,000 synthetic images were generated using typical image augmentation methods from the original 764 training images. Additional 218 and 109 images were employed for testing and validation respectively. In addition, a unique lightweight parallel depth-wise separable CNN model, PDS-CNN was developed by applying depth-wise separable convolutional layers to reduce parameters, layers, and size while boosting classification performance. Finally, the explainable capability of PDS-CNN is obtained through the use of SHapley Additive exPlanations (SHAP) evaluated by a sericulture specialist. The proposed PDS-CNN outperforms well-known deep transfer learning models, achieving an optimistic accuracy of 95.05 ± 2.86% for three-class classifications and 96.06 ± 3.01% for binary classifications with only 0.53 million parameters, 8 layers, and a size of 6.3 megabytes. Furthermore, when compared with other well-known transfer models, the proposed model identified mulberry leaf diseases with higher accuracy, fewer factors, fewer layers, and lower overall size. The visually expressive SHAP explanation images validate the models’ findings aligning with the predictions made the sericulture specialist. Based on these findings, it is possible to conclude that the explainable AI (XAI)-based PDS-CNN can provide sericulture specialists with an effective tool for accurately categorizing mulberry leaves.
Psychopathological factors and personality dimensions on dysfunctional eating behaviors in a sample of individuals with obesity
Authors: Attanasio Margherita , Giuliani Antonio , Romano Lucia , Laidò Cristina , Di Poggiovalle Gilda , Le Donne Ilenia , Di Fonzo Valentina , Tiberti Sergio , Valenti Marco , Mazza Monica
Published: September 2023

Introduction

Obesity and eating disorders are considered to be part of a broad spectrum of disorders associated with weight issues and maladaptive eating styles. Several studies show that psychopathological and personality characteristics contribute to the development and maintenance of obesity and dysfunctional eating behaviors, showing a bidirectional relationship. The purpose of this study was to understand the role of psychopathological factors and personality dimensions on dysfunctional eating behaviors in a sample of individuals with obesity.

Methods

The study was conducted with 96 individuals with obesity (31 males and 65 females) who underwent psychological assessment. The instruments administered included the Cognitive Behavioral Assessment 2.0 - Primary Scales, the Minnesota Multiphasic Personality Inventory-2, and the Eating Disorder Inventory. Relationships between dysfunctional eating behaviors and personality and psychopathological factors were explored through mediation analysis.

Results and discussion

Our results showed that difficulties related to impulse control and behavior, along with negative and dysphoric emotions, may be associated with difficulties in eating behavior. Mediation analysis showed that the combination of depressive and obsessive-compulsive symptomatology may exacerbate or contribute to the occurrence of eating disorders. These psychopathological aspects should be taken into account during the assessment of patients who decide to undergo bariatric surgery and should be targets of specific psychological interventions.
Studying perceptual bias in favor of the from-above Necker cube perspective in a goal-directed behavior
Authors: Kuc Alexander , Maksimenko Vladimir , Savosenkov Andrey , Grigorev Nikita , Grubov Vadim , Badarin Artem , Kazantsev Victor , Gordleeva Susanna , Hramov Alexander
Published: September 2023

When viewing a completely ambiguous image, different interpretations can switch involuntarily due to internal top-down processing. In the case of the Necker cube, an entirely ambiguous stimulus, observers often display a bias in perceptual switching between two interpretations based on their perspectives: one with a from-above perspective (FA) and the other with a from-below perspective (FB). Typically, observers exhibit a priori top-down bias in favor of the FA interpretation, which may stem from a statistical tendency in everyday life where we more frequently observe objects from above. However, it remains unclear whether this perceptual bias persists when individuals voluntarily decide on the Necker cube's interpretation in goal-directed behavior, and the impact of ambiguity in this context is not well-understood. In our study, we instructed observers to voluntarily identify the orientation of a Necker cube while manipulating its ambiguity from low (LA) to high (HA). Our investigation aimed to test two hypotheses: (i) whether the perspective (FA or FB) would result in a bias in response time, and (ii) whether this bias would depend on the level of stimulus ambiguity. Additionally, we analyzed electroencephalogram (EEG) signals to identify potential biomarkers that could explain the observed perceptual bias. The behavioral results confirmed a perceptual bias in favor of the from-above perspective, as indicated by shorter response times. However, this bias diminished for stimuli with high ambiguity. For the LA stimuli, the occipital theta-band power consistently exceeded the frontal theta-band power throughout most of the decision-making time. In contrast, for the HA stimuli, the frontal theta-band power started to exceed the occipital theta-band power during the 0.3-s period preceding the decision. We propose that occipital theta-band power reflects evidence accumulation, while frontal theta-band power reflects its evaluation and decision-making processes. For the FB perspective, occipital theta-band power exhibited higher values and dominated over a longer duration, leading to an overall increase in response time. These results suggest that more information and more time are needed to encode stimuli with a FB perspective, as this template is less common for the observers compared to the template for a cube with a FA perspective.
The association between socioeconomic status and health-related quality of life among young and middle-aged maintenance hemodialysis patients: multiple mediation modeling
Authors: Mai Qingxin , Xu Siyi , Hu Jingyi , Sun Xiaoming , Chen Gangyi , Ma Zhen , Song Yang , Wang Chao
Published: September 2023

Objective

To explore the relationship between socioeconomic status (SES), illness perception, social functioning, and health-related quality of life (HRQoL) of young and middle-aged maintenance hemodialysis (MHD) patients and the internal mechanism of action.

Design

A multicenter cross-sectional study.

Methods

An aggregate of 332 young and middle-aged MHD patients were enrolled from hemodialysis centers in four general hospitals in Guangzhou, Guangdong, China, from June to December 2022. The questionnaires used included one for general demographic data, the Brief Illness Perception Questionnaire (BIPQ), Social Dysfunction Screening Scale (SDSS), and the 12-item Short Form Health Survey (SF-12).

Results

Both SES and HRQoL were negatively correlated with illness perception and social functioning, respectively. SES was positively correlated with HRQoL. Illness perception was positively correlated with social functioning. The indirect effects of illness perception and social functioning on the relationship between SES and HRQoL were 0.33 and 0.31, making up 41.06% and 38.91% of the sum. The chain indirect effect of illness perception and social functioning was 0.10, making up 12.59% of the total effect, while gender did not play a moderating role.

Conclusion

Illness perception and social functioning may independently and accumulatively mediate the association between SES and HRQoL. Nurses should consider developing individual intervention program for young and middle-aged MHD patients with low SES, focusing on establishing targeted counseling and health education strategies corresponding to illness perception and social functioning to help patients improve their HRQoL.
Harnessing behavioral psychology to encourage individuals' adoption of pollinator conservation behaviors
Authors: Fair Conor G. , Braman S. Kris
Published: September 2023

The economic and ecological importance of pollinators and the increasingly evident decline of their populations have drawn concern from scientists, governments, and individuals alike. While research has focused on the ecological causes and solutions to pollinator declines, it is less understood how to motivate actual behavior changes to help conserve pollinators. Behavioral psychologists have developed many theories to explain how human behavioral drivers affect the adoption of pro-environmental behaviors such as recycling and other sustainability actions. A comprehensive model incorporating norm activation theory, the new ecological paradigm, values-belief-norm theory, and the theory of planned behavior suggests various psychological determinants that drive changes in pro-environmental behaviors. A survey was constructed using Qualtrics software to measure and analyze >1,500 individuals' responses to questions designed to test the relationships between different types of pollinator conservation behaviors and the sociopsychological determinants of an individual's intention to perform said behaviors. Previous behaviors, issue awareness, and positive attitudes toward pollinators consistently predict increased intention to perform pollinator conservation behaviors, which supports related research on pro-environmental behaviors. Other determinants, such as ascription of responsibility and perceived behavioral control, had positive effects on the intention to perform some of the tested pollinator conservation behaviors. Understanding these relationships could help improve efforts to educate and increase the adoption of these pollinator conservation behaviors. Finally, many determinants had mixed and fewer significant relationships with the intention to perform conservation behaviors, which suggests the need for revisions to the specific wording of the survey tools and additional testing of these psychological determinants.
Divergent perspectives about water security: hydrosocial transformations in the metropolitan region of Montevideo (Uruguay)
Authors: Dias Tadeu Natalia , Trimble Micaela , Lázaro Marila , Venturini Paula , Venegas Mauricio
Published: September 2023

The Montevideo Metropolis, where more than half of Uruguay's population resides, is supplied with water from the Santa Lucía River (SLR), which faces increasing problems of water quality and quantity. In 2020, in the context of national government political changes, a hydraulic project (called Neptuno) involving the construction of a purification plant using water from the Río de la Plata estuary (close to the SLR basin), was proposed by a consortium of private companies. The aim of this paper is to analyze the arguments to support and oppose the Neptuno Project, as well as the hydrosocial transformations promoted by it in the SLR basin, including the scalar strategies adopted. Primary and secondary data (interviews, participant observation, and document analysis) were triangulated. Coalitions pro and against the greater involvement of the private sector with water supply services were identified. Our research shows that diverse perspectives of water security, related to different hydrosocial projects, reflect opposed interests and divergent objectives in a context of disputes within asymmetrical power relationships. This has been reactivating the coalition of the historic conflict against the privatization processes that preceded the constitutional reform in Uruguay in 2004. This coalition, against the Neptuno project, carried out a “jump scale,” taking the issue from the local to the national scale.
PRIME: a probabilistic neural network approach to solar wind propagation from L1
Authors: O’Brien Connor , Walsh Brian M. , Zou Ying , Tasnim Samira , Zhang Huaming , Sibeck David Gary
Published: September 2023

Introduction: For the last several decades, continuous monitoring of the solar wind has been carried out by spacecraft at the first Earth-Sun Lagrange point (L1). Due to computational expense or model limitations, those data often must be propagated to some point closer to the Earth in order to be usable by those studying the interaction between Earth’s magnetosphere and the solar wind. The current most widely used tool to propagate measurements from L1 (roughly 235 RE upstream) to Earth is the planar propagation method, which includes a number of known limitations. Motivated by these limitations, this study introduces a new algorithm called the Probabilistic Regressor for Input to the Magnetosphere Estimation (PRIME).

Methods: PRIME is based on a novel probabilistic recurrent neural network architecture, and is capable of incorporating solar wind time history from L1 monitors to generate predictions of near-Earth solar wind as well as estimate uncertainties for those predictions.

Results: A statistical validation shows PRIME’s predictions better match MMS magnetic field and plasma measurements just upstream of the bow shock than measurements from Wind propagated to MMS with a minimum variance analysis-based planar propagation technique. PRIME’s continuous rank probability score (CRPS) is 0.214σ on average across all parameters, compared to the minimum variance algorithm’s CRPS of 0.350σ. PRIME’s performance improvement over minimum variance is dramatic in plasma parameters, with an improvement in CRPS from 2.155 cm−3 to 0.850 cm−3 in number density and 16.15 km/s to 9.226 km/s in flow velocity VX GSE.

Discussion: Case studies of particularly difficult to predict or extreme conditions are presented to illustrate the benefits and limitations of PRIME. PRIME’s uncertainties are shown to provide reasonably reliable predictions of the probability of particular solar wind conditions occurring.

Conclusion: PRIME offers a simple solution to common limitations of solar wind propagation algorithms by generating accurate predictions of the solar wind at Earth with physically meaningful uncertainties attached.
The Mechanism of Drug Carryover in Feed Manufacturing as a Function of Drug Properties and Equipment Design—A Brief Review
Authors: Akoto Esther Y. , Maier Dirk E.
Published: September 2023

This paper thoroughly reviews the mechanism of veterinary drug carryover in feed manufacturing facilities, factors resulting in varying concentrations of drug carryover in processing equipment, the impact of chemical and physical properties of drugs, and the effect of equipment type and design. The Google Scholar database (from 1998 to 2023) was searched with words and phrases such as drug carryover, feed manufacturing, equipment cleaning and validation, food allergen control, sources of drug carryover, and process parameters in drug carryover. Some papers were from the Iowa State University Library database and PubMed. Drug carryover is a function of ingredients, nature of drugs, equipment type, process parameters, and cleaning procedures. The gaps are the lack of commercial feed mills data on the role and interaction of nanomaterials, molasses, equipment type, and process parameters in drug carryover in animal feed. Modification of process parameters, e.g., airflow in bucket elevators and the interaction of feed ingredients, composition, equipment type, and design, need to be investigated in the commercial setting to address drug carryover. Rhetorically, can big data facilitate the standardization of cleaning procedures at feed mills? The findings can result in drug carryover prevention/control in animal feed and animal-based human food.
Surveillance of Multidrug-Resistant Pathogens in Neonatal Intensive Care Units of Palermo, Italy, during SARS-CoV-2 Pandemic
Authors: Graziano Giorgio , Notarbartolo Veronica , Priano Walter , Maida Carmelo Massimo , Insinga Vincenzo , Rinaudo Grazia , Russo Arianna , Palermo Roberta , Vitale Francesco , Giuffrè Mario
Published: September 2023

Background: Antimicrobial resistance (AMR) is a topic of concern, especially in high-level care departments like neonatal intensive care units (NICUs). The systematic use of an “active” epidemiological surveillance system allows us to observe and analyze any changes in microbial distribution, limiting the risk of healthcare-associated infection (HAI) development. Methods: We have conducted a longitudinal observational study in the five NICUs of Palermo, comparing the “pre-pandemic period” (March 2014–February 2020) with the “pandemic” one (March 2020–February 2022). The primary aim of the study was to evaluate the cumulative prevalence of carriage from multi-drug resistant (MDR) bacteria in the cumulative NICUs (NICU C). Results: During the “pre-pandemic period”, 9407 swabs were collected (4707 rectal, 4700 nasal); on the contrary, during the “pandemic period”, a total of 2687 swabs were collected (1345 rectal, 1342 nasal). A statistically significant decrease in MDR-Gram-negative bacteria (GNB) carriage prevalence was detected during the pandemic. At the same time, there was a general worsening of the carriage of carbapenemase-forming MDR-GNB (CARBA-R+) and methicillin-resistant Staphylococcus aureus (MRSA) during the pandemic period. A significant reduction in methicillin-susceptible Staphylococcus aureus (MSSA) carriage was detected too. Conclusions: The surveillance of MDRO carriage in NICUs is fundamental for limiting the social and economic burden of HAIs.
Sequential or Combination Treatments as Rescue Therapies in Immunocompromised Patients with Persistent SARS-CoV-2 Infection in the Omicron Era: A Case Series
Authors: Longo Bianca Maria , Venuti Francesco , Gaviraghi Alberto , Lupia Tommaso , Ranzani Fabio Antonino , Pepe Andrea , Ponzetta Laura , Vita Davide , Allice Tiziano , Gregorc Vanesa , Frascione Pio Manlio Mirko , De Rosa Francesco Giuseppe , Calcagno Andrea , Bonora Stefano
Published: September 2023

Prolonged SARS-CoV-2 infections are widely described in immunosuppressed patients, but safe and effective treatment strategies are lacking. We aimed to outline our approach to treating persistent COVID-19 in patients with immunosuppression from different causes. In this case series, we retrospectively enrolled all immunosuppressed patients with persistent SARS-CoV-2 infections treated at our centers between March 2022 and February 2023. Patients received different sequential or combination regimens, including antivirals (remdesivir, nirmatrelvir/ritonavir, or molnupiravir) and/or monoclonal antibodies (mAbs) (tixagevimab/cilgavimab or sotrovimab). The main outcome was a complete virological response (negative SARS-CoV-2 RT-PCR on nasopharyngeal swabs) at the end of treatment. Fifteen patients were included as follows: eleven (11/15; 73%) with hematological disease and four (4/15; 27%) with recently diagnosed HIV/AIDS infection. Six patients (6/15; 40%) received a single antiviral course, four patients (4/15; 27%) received an antiviral and mAbs sequentially, and two patients (13%) received three lines of treatment (a sequence of three antivirals or two antivirals and mAbs). A combination of two antivirals or one antiviral plus mAbs was administered in three cases (3/15, 20%). One patient died while still positive for SARS-CoV-2, while fourteen (14/15; 93%) tested negative within 16 days after the end of treatment. The median time to negativization since the last treatment was 2.5 days. Both sequential and combination regimens used in this study demonstrated high efficacy and safety in the high-risk group of immunosuppressed patients.
Compensation of the Distorted WDM Signals by Symmetric Dispersion Map with Nonuniform Zero-Crossing Place of Accumulated Dispersion in Midway-OPC System
Authors: Chung Jae-Pil , Lee Seong-Real
Published: September 2023

The nonlinear Kerr effect and chromatic dispersion are the fundamental causes of optical signal degradation in single-mode fiber (SMF) and erbium-doped fiber-amplification (EDFA)-based wavelength division multiplexing (WDM) transmission. Dispersion management combined with a midway optical phase conjugator among the technologies for compensating for such optical signal distortion is known to not be limited by the modulation format and multiplexing technology. Optimization of the dispersion map can partially alleviate the capacity and maximum transmission distance limitations of the SMF and EDFA system. In this paper, we propose various types of symmetric dispersion maps in which the position of zero-crossing place of the cumulative dispersion is not constant, and analyze the effect of each dispersion map configuration on 40 Gb/s × 24-channel WDM signal distortion compensation. When designed with the residual dispersion per span (RDPS) around 400 ps/nm, it is confirmed that most of the proposed dispersion maps are more effective in compensating the distorted WDM signal than conventional dispersion map. In particular, we confirm that, among the proposed dispersion maps, the dispersion map in which the RDPS is designed uniformly for all fiber spans can increase the power margin of WDM channel and expand the range of the total residual dispersion in the dispersion-managed link.
Treadmill Deck Performance Optimization Design Based on Muscle Activity during Running
Authors: Wang Zeng , Wang Xiancheng , Li Ruidong
Published: September 2023

In previous research on treadmills, the main focus has been on comparing the physiological differences induced by running on treadmill decks and other exercise surfaces, with relatively little research on the mechanical properties of treadmill decks. Reducing sports injuries is a common desire of runners, which may be closely related to muscle activity. Obviously, the mechanical properties of the treadmill play an important role in this process. Muscle activity was evaluated based on a mass-spring-damper (MSD) model that provides a simulated signal of the ground reaction forces (GRF) and vibration of the lower-limb soft tissues (LLST) during the landing of the human body during running. We improved the original human motion model by considering the stiffness and damping effect of the treadmill deck. In addition, based on the theory of muscle activity regulation, the dimensionless objective function is established, and the particle swarm optimization algorithm is used to find the best range of treadmill deck parameters under pre- and post-fatigue conditions. The results show that the hardness of the treadmill deck can affect the regulation of muscle activity. Based on this, the parameters of the specific safe area of the treadmill deck are obtained, and the size of the safe area after fatigue is significantly reduced compared to that before fatigue. By studying the physiological effects of the mechanical properties of the treadmill deck on runners, the research results are expected to provide references for the design of treadmill deck parameters and reduce the risk of runners’ sports injuries, which has practical application value for treadmill design and runners’ health.
Study on the Influence of Surface Integrity on Hydrogen Permeation Resistance of Hydrogen Production Reactor Materials
Authors: Leng Zhiyi , Zhang Shengfang , Wang Wenzhe , Gu Hongtao , Yin Jian , Wang Ziguang , Liu Yu
Published: September 2023

Hydrogen permeation reduces a material’s properties and increases the risk of brittle fracture, which causes a potential safety hazard. A workpiece’s hydrogen permeation resistance could be improved by improving its surface integrity through surface processing. This paper studies low-alloy steel’s surface integrity and its hydrogen permeation resistance in a hydrogen production reactor, using the electrochemical cathodic hydrogen-charging method to carry out electrochemical hydrogen-charging experiments. After the specimens were pretreated using different surface-grinding methods and shot peening pressure strengthening, they were hydrogen-charged on a self-designed and built electrolytic hydrogen charging platform. Before and after hydrogen charging, the specimens’ section hardness and tensile strength were tested, and the fracture morphology of the specimens was observed. The influence laws of surface roughness and surface residual compressive stress on the distribution of material hardness along the depth, the variation in material hardness, the fracture morphology, and the decline in the tensile properties of the low-alloy steel specimens after 5 h of hydrogen charging were analyzed. The reasons for the influence of surface integrity indexes on the hydrogen permeation resistance of the specimens were also analyzed. Based on the experimental results, a series of mechanical processing parameters were proposed to improve the material’s permeation resistance, which provides a theoretical and practical basis for the processing of materials with high surface integrity and hydrogen permeation resistance. Through the experiments, it was found that the hydrogen permeation resistance of the Ra 0.17 μm surface roughness specimen was the best of all specimens with different surface roughness values, and its hydrogen embrittlement sensitivity index was 20.96%. The specimen had the best hydrogen permeation resistance under 336 MPa surface residual compress stress, and its hydrogen embrittlement sensitivity index was 16.45%.
Enhancing Nutrition and Palatability: The Development of Cooked Sausages with Protein Hydrolysate from Secondary Raw Materials for the Elderly
Authors: Tultabayeva Tamara , Tokysheva Gulzhan , Zhakupova Gulmira , Konysbaeva Damilya , Mukhtarkhanova Rauan , Matibayeva Ainur , Mukhametov Almas , Zamaratskaia Galia , Makangali Kadyrzhan
Published: September 2023

Currently, there is an increase in the use of preparations from collagen-containing raw materials in the production of meat products. The high functional and technological properties of such preparations make it possible to significantly improve the rheological properties of food products, as well as organoleptic indicators, and enrich meat products with dietary fibers. The aim of this study was to study the effect of an emulsion of 5% protein hydrolysate and 1% purslane powder on herodietic boiled sausages for the elderly. The results showed that the experimental samples of boiled sausages contained 15.44% protein, 6.6% fat, 4.2% carbohydrates and 71.1% moisture; this shows that boiled sausage with the addition of protein hydrolysate contains optimal chemical composition for dietary nutrition, a certain moisture index confirms the excellent consistency of boiled sausage. The change in the peroxide number was studied for 7 days. The results showed that the peroxide number did not change significantly from 2.0 meq/kg to 4.6 meq/kg. Thus, the addition of purslane with antioxidant properties helps to slow down the oxidation of fats and thereby increases the shelf life of boiled herodietic sausage. The results of the study of color characteristics showed stable color formation, which was influenced by an emulsion of collagen and purslane. It was found that products using emulsions from collagen-containing raw materials are characterized by a higher concentration of tyrosine due to the action of proteolytic enzymes (pepsin and trypsin)—from 728.1 mcg/mL (during the first three hours of hydrolysis) to 392.5 mcg/mL (during 6 h of hydrolysis)—which indicates a higher degree of protein digestibility these products. Thus, the addition of an emulsion of 5% protein hydrolysate and 1% purslane powder can be recommended for the production of boiled sausages with improved nutritional and taste properties.
Prediction of Sensor Data in a Greenhouse for Cultivation of Paprika Plants Using a Stacking Ensemble for Smart Farms
Authors: Han Seok-Ho , Mutahira Husna , Jang Hoon-Seok
Published: September 2023

Ensuring food security has become of paramount importance due to the rising global population. In particular, the agriculture sector in South Korea faces several challenges such as an aging farming population and a decline in the labor force. These issues have led to the recognition of smart farms as a potential solution. In South Korea, the smart farm is divided into three generations. The first generation primarily concentrates on monitoring and controlling precise cultivation environments by leveraging information and communication technologies (ICT). This is aimed at enhancing convenience for farmers. Moving on to the second generation, it takes advantage of big data and artificial intelligence (AI) to achieve improved productivity. This is achieved through precise cultivation management and automated control of various farming processes. The most advanced level is the 3rd generation, which represents an intelligent robotic farm. In this stage, the entire farming process is autonomously managed without the need for human intervention. This is made possible through energy management systems and the use of robots for various farm operations. However, in the current Korean context, the adoption of smart farms is primarily limited to the first generation, resulting in the limited utilization of advanced technologies such as AI, big data, and cloud computing. Therefore, this research aims to develop the second generation of smart farms within the first generation smart farm environment. To accomplish this, data was collected from nine sensors spanning the period between 20 June to 30 September. Following that, we conducted kernel density estimation analysis, data analysis, and correlation heatmap analysis based on the collected data. Subsequently, we utilized LSTM, BI-LSTM, and GRU as base models to construct a stacking ensemble model. To assess the performance of the proposed model based on the analyzed results, we utilized LSTM, BI-LSTM, and GRU as the existing models. As a result, the stacking ensemble model outperformed LSTM, BI-LSTM, and GRU in all performance metrics for predicting one of the sensor data variables, air temperature. However, this study collected nine sensor data over a relatively short period of three months. Therefore, there is a limitation in terms of considering the long-term data collection and analysis that accounts for the unique seasonal characteristics of Korea. Additionally, the challenge of including various environmental factors influencing crops beyond the nine sensors and conducting experiments in diverse cultivation environments with different crops for model generalization remains. In the future, we plan to address these limitations by extending the data collection period, acquiring diverse additional sensor data, and conducting further research that considers various environmental variables.
Enhancing Early Dementia Detection: A Machine Learning Approach Leveraging Cognitive and Neuroimaging Features for Optimal Predictive Performance
Authors: Irfan Muhammad , Shahrestani Seyed , Elkhodr Mahmoud
Published: September 2023

Dementia, including Alzheimer’s Disease (AD), is a complex condition, and early detection remains a formidable challenge due to limited patient records and uncertainty in identifying relevant features. This paper proposes a machine learning approach to address this issue, utilizing cognitive and neuroimaging features for training predictive models. This study highlighted the viability of cognitive test scores in dementia detection—a procedure that offers the advantage of simplicity. The AdaBoost Ensemble model, trained on cognitive features, displayed a robust performance with an accuracy rate of approximately 83%. Notably, this model surpassed benchmark models such as the Artificial Neural Network, Support Vector Machine, and Naïve Bayes. This study underscores the potential of cognitive tests and machine learning for early dementia detection.
A Numerical Simulation Study on DC Positive Corona Discharge Characteristics at the Conductor’s Tip Defect
Authors: Wang Shenghui , Mai Jiamin , Wang Lihong
Published: September 2023

For investigating the relationship between the surface corona discharge of a DC wire and other influencing factors, a hybrid numerical model based on a fluid-chemical reaction was proposed to simulate the discharge process at the tip defect of the wire. Under different defect geometries and gas pressures achieved via simulation, the microscopic process of the reaction and movement of electrons and heavy particles during a positive corona discharge was studied, and characteristic parameters such as corona inception voltage and discharge current were analyzed. Furthermore, through the corona cage test, for a specific electrode configuration, corona inception voltages under different pressures were compared and verified, which showed that the model was reasonable. The results showed that the maximum electron density of the streamer head was about 1 × 1020 m−3, the rise time of the pulse current was about 10 ns, and the decay time was about 300–500 ns. The corona inception voltage decreased with an increase in the tip height and decreases in the tip curvature radius, conductor radius, and background air pressure; the amplitude of the pulse current increased with increases in the wire radius and curvature radius of the defect tip and decreases in tip height and background air pressure. The experimental results are consistent with the simulation results, which verifies the reasonability of the model.
Study of the Rheological Characteristics of Sediment-Gelling Compositions for Limiting Water Inflows
Authors: Moldabayeva Gulnaz Z. , Efendiyev Galib M. , Kozlovskiy Artem L. , Tuzelbayeva Sholpan R. , Imansakipova Zemfira B.
Published: September 2023

In view of the poor knowledge of the applicability of sediment-gelling compositions (SGCs) in waterproofing the bottom-hole zone of wells, work in this area of research is one of the most promising in waterproofing today. The key goal of this work is to study the prospect of using SGCs for waterproofing as well as to calculate the rheological characteristics of the proposed SGCs depending on variations in the components of their composition (alkali and polymer). In the course of our studies, it was found that the key factors influencing the rheological characteristics of SGCs are not only the variation in the ratio in the composition of alkali and polymer but also the degree of salinity of the formation water, which must be taken into account when developing waterproofing. During this research, it was found that due to the absence of calcium and magnesium ions in fresh water, the proposed polymers have good solubility (the exponent in the rheological model is equal to or close to unity), which leads to an increase in the viscosity of solutions. The dependence of changes in the rheological constants of SGCs on such parameters as temperature and alkali concentration have been established. It was determined that an increase in the solution temperature leads to an increase in the rheological constant n from 0.8 to 0.92 (at a polymer concentration of 0.05 and a NaOH concentration of 0.1), while a variation in the NaOH alkali concentration from 0.1 to 0.75 leads to similar changes in one measured temperature range. The results obtained can be used in the future to evaluate the use of SGCs to create barrier waterproofing in the bottom-hole zone of wells during oil production.
An Innovative Strategy Based on Secure Element for Cyber–Physical Authentication in Safety-Critical Manufacturing Supply Chain
Authors: Gómez-Marín Ernesto , Senni Valerio , Parrilla Luis , Tejero López Jose L. , Castillo Encarnación , Martintoni Davide
Published: September 2023

The accurate tracking of every production step and related outcome in a supply chain is a stringent requirement in safety-critical sectors such as civil aviation. In such a framework, trusted traceability and accountability can be reliably and securely managed by means of blockchain-based solutions. Unfortunately, blockchain cannot guarantee the provenance and accuracy of the stored information. To overcome such a limitation, this paper proposes a secure solution to strongly rely on the tracking information of the physical assets in the supply chain. The proposed solution exploits Hardware Security Modules (HSMs) to provide required cryptographic primitives through a Near-Field Communication (NFC) connection. In our approach, each transfer of the assets is authenticated, verified, and recorded in the blockchain through the HSM. Transaction entries are signed, thus providing a guarantee of ownership and authenticity. The proposed infrastructure has been subject of an exhaustive security analysis and proved resilient against counterfeiting attempts, stakeholder repudiations, and misleading information.
A New Generative Model for Textual Descriptions of Medical Images Using Transformers Enhanced with Convolutional Neural Networks
Authors: Barreto Artur Gomes , de Oliveira Juliana Martins , Gois Francisco Nauber Bernardo , Cortez Paulo Cesar , de Albuquerque Victor Hugo Costa
Published: September 2023

The automatic generation of descriptions for medical images has sparked increasing interest in the healthcare field due to its potential to assist professionals in the interpretation and analysis of clinical exams. This study explores the development and evaluation of a generalist generative model for medical images. Gaps were identified in the literature, such as the lack of studies that explore the performance of specific models for medical description generation and the need for objective evaluation of the quality of generated descriptions. Additionally, there is a lack of model generalization to different image modalities and medical conditions. To address these issues, a methodological strategy was adopted, combining natural language processing and features extraction from medical images and feeding them into a generative model based on neural networks. The goal was to achieve model generalization across various image modalities and medical conditions. The results showed promising outcomes in the generation of descriptions, with an accuracy of 0.7628 and a BLEU-1 score of 0.5387. However, the quality of the generated descriptions may still be limited, exhibiting semantic errors or lacking relevant details. These limitations could be attributed to the availability and representativeness of the data, as well as the techniques used.
Esketamine Inhibits Cocaine-Seeking Behaviour Subsequent to Various Abstinence Conditions in Rats
Authors: Wydra Karolina , Witek Kacper , Suder Agata , Filip Małgorzata
Published: September 2023

Background: Cocaine use disorder (CUD) is a relapsing brain disease caused by a chronic drug intake that involves neural mechanisms and psychological processes, including depression. Preclinical and clinical studies have demonstrated the promise of pharmacological drugs in controlling the reinstatement of cocaine by targeting the N-methyl-D-aspartate (NMDA) receptor. Recent evidence has revealed that esketamine, a (S) enantiomer of ketamine, shows a high affinity to NMDA receptors and has been used in clinical trials to treat moderate-to-severe depression. Methods: In the present paper, we investigated the effects of esketamine in regulating cocaine-seeking behaviour induced through the use of cocaine (10 mg/kg) or the cocaine-associated conditioned cue after a short (10 days)-lasting period of drug abstinence with extinction training, home cage or enrichment environment conditions in male rats. Furthermore, we investigated the acute effects of esketamine on locomotor activity in drug-naïve animals. Results: Esketamine (2.5–10 mg/kg) administered peripherally attenuated the reinstatement induced with cocaine priming or the drug-associated conditioned cue after different conditions of abstinence. Conclusions: These results seem to support esketamine as a candidate for the pharmacological management of cocaine-seeking and relapse prevention; however, further preclinical and clinical research is needed to better clarify esketamine’s actions in CUD.
Eicosapentaenoic Acid Influences the Lipid Profile of an In Vitro Psoriatic Skin Model Produced with T Cells
Authors: Morin Sophie , Tremblay Andréa , Dumais Elizabeth , Julien Pierre , Flamand Nicolas , Pouliot Roxane
Published: September 2023

Psoriasis is a skin disease characterized by epidermal hyperplasia and an inappropriate activation of the adaptive immunity. A dysregulation of the skin’s lipid mediators is reported in the disease with a predominance of the inflammatory cascade derived from n-6 polyunsaturated fatty acids (n-6 PUFAs). Bioactive lipid mediators derived from arachidonic acid (AA) are involved in the inflammatory functions of T cells in psoriasis, whereas n-3 PUFAs’ derivatives are anti-inflammatory metabolites. Here, we sought to evaluate the influence of a supplementation of the culture media with eicosapentaenoic acid (EPA) on the lipid profile of a psoriatic skin model produced with polarized T cells. Healthy and psoriatic skin substitutes were produced following the auto-assembly technique. Psoriatic skin substitutes produced with or without T cells presented increased epidermal and dermal linolenic acid (LA) and AA levels. N-6 PUFA lipid mediators were strongly measured in psoriatic substitutes, namely, 13-hydroxyoctadecadienoic acid (13-HODE), prostaglandin E2 (PGE2) and 12-hydroxyeicosatetraenoic acid (12-HETE). The added EPA elevated the amounts of EPA, n-3 docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA) in the epidermal and dermal phospholipids. The EPA supplementation balanced the production of epidermal lipid mediators, with an increase in prostaglandin E3 (PGE3), 12-hydroxyeicosapentaenoic acid (12-HEPE) and N-eicosapentaenoyl-ethanolamine (EPEA) levels. These findings show that EPA modulates the lipid composition of psoriatic skin substitutes by encouraging the return to a cutaneous homeostatic state.
Chirality Matters: Fine-Tuning of Novel Monoamine Reuptake Inhibitors Selectivity through Manipulation of Stereochemistry
Authors: Kalaba Predrag , Pacher Katharina , Neill Philip John , Dragacevic Vladimir , Zehl Martin , Wackerlig Judith , Kirchhofer Michael , Sartori Simone B. , Gstach Hubert , Kouhnavardi Shima , Fabisikova Anna , Pillwein Matthias , Monje-Quiroga Francisco , Ebner Karl , Prado-Roller Alexander , Singewald Nicolas , Urban Ernst , Langer Thierry , Pifl Christian , Lubec Jana , Leban Johann Jakob , Lubec Gert
Published: September 2023

The high structural similarity, especially in transmembrane regions, of dopamine, norepinephrine, and serotonin transporters, as well as the lack of all crystal structures of human isoforms, make the specific targeting of individual transporters rather challenging. Ligand design itself is also rather limited, as many chemists, fully aware of the synthetic and analytical challenges, tend to modify lead compounds in a way that reduces the number of chiral centers and hence limits the potential chemical space of synthetic ligands. We have previously shown that increasing molecular complexity by introducing additional chiral centers ultimately leads to more selective and potent dopamine reuptake inhibitors. Herein, we significantly extend our structure-activity relationship of dopamine transporter-selective ligands and further demonstrate how stereoisomers of defined absolute configuration may fine-tune and direct the activity towards distinct targets. From the pool of active compounds, using the examples of stereoisomers 7h and 8h, we further showcase how in vitro activity significantly differs in in vivo drug efficacy experiments, calling for proper validation of individual stereoisomers in animal studies. Furthermore, by generating a large library of compounds with defined absolute configurations, we lay the groundwork for computational chemists to further optimize and rationally design specific monoamine transporter reuptake inhibitors.
The Effects of an Osteoarthritic Joint Environment on ACL Damage and Degeneration: A Yucatan Miniature Pig Model
Authors: Schwartz Elias , Chang Kenny , Sun Changqi , Zhang Fei , Peng Guoxuan , Owens Brett , Wei Lei
Published: September 2023

Posttraumatic osteoarthritis (PTOA) arises secondary to joint injuries and is characteristically driven by inflammatory mediators. PTOA is often studied in the setting of ACL tears. However, a wide range of other injuries also lead to PTOA pathogenesis. The purpose of this study was to characterize the morphological changes in the uninjured ACL in a PTOA inflammatory environment. We retrospectively reviewed 14 ACLs from 13 Yucatan minipigs, 7 of which had undergone our modified intra-articular drilling (mIAD) procedure, which induced PTOA through inflammatory mediators. Seven ACLs were harvested from mIAD minipigs (PTOA) and seven ACLs from control minipigs with no cartilage degeneration (non-PTOA). ACL degeneration was evaluated using histological scoring systems. IL-1β, NF-κB, and TNF-α mRNA expression in the synovium was measured using qRT-PCR. PTOA minipigs demonstrated significant ACL degeneration, marked by a disorganized extracellular matrix, increased vascularity, and changes in cellular shape, density, and alignment. Furthermore, IL-1β, NF-κB, and TNF-α expression was elevated in the synovium of PTOA minipigs. These findings demonstrate the potential for ACL degeneration in a PTOA environment and emphasize the need for anti-inflammatory disease-modifying therapies following joint injury.
A Truncated Receptor TrkB Isoform (TrkB.T1) in Mechanisms of Genetically Determined Depressive-like Behavior of Mice
Authors: Alsalloum Marah , Ilchibaeva Tatiana , Tsybko Anton , Eremin Dmitry , Naumenko Vladimir
Published: September 2023

Depression is a mental disorder that significantly reduces quality of life, and the discovery of new drug targets is an urgent problem for modern neuroscience. Brain-derived neurotrophic factor (BDNF) and its receptors have been found to participate in mechanisms of depression and antidepressant drugs’ action. In this study, we focused on a less-studied truncated isoform of receptor TrkB: TrkB.T1. Initially, we noticed that the level of TrkB.T1 is low in the hippocampus of Antidepressant-Sensitive Cataleptics (ASC) mice, which are characterized by genetically determined depressive-like behavior in contrast to “normal” C57BL/6J mice. Next, overexpression of TrkB.T1 receptor in hippocampal neurons of ACS mice was induced to clarify the role of this receptor in mechanisms of depressive-like behavior. TrkB.T1 overexpression lowered BDNF protein concentration in the hippocampus. On the behavioral level, TrkB.T1 overexpression severely decreased aggression and enhanced social behavior. Additionally, this excess of receptor TrkB.T1 slightly promoted anxiety and depressive-like behavioral traits without affecting learning and memory. Our results show that this TrkB isoform participates in the control of aggression, anxiety, and depressive-like behavior and in the regulation of BDNF system functioning in ASC mice (genetically predisposed to depressive-like behavior). Considering our findings, we believe that hippocampal receptor TrkB.T1 can be a drug target for the correction of behavioral pathologies.