bluuebunny/crossref_metadata_2025 huggingface dataset:
Specificity and integration of meaning in self-defining memories of breast cancer survivors: clinical reflections to promote a narrative identity integration
Authors: Martino Maria Luisa , Sebri Valeria , Singer Jefferson , Madow Katie , Giudice Alice Viola , Mazzoni Davide , Freda Maria Francesca , Pravettoni Gabriella
Published: August 2024

Potential traumatic events, such as breast cancer, can influence autobiographical memory (AM), interrupting the continuity of narrative identity. AM is based on a hierarchical search across different levels of specificity that are indexed from top to bottom when a memory is retrieved. In the breast cancer field, non-specific AMs are an observed clinical phenomenon. In particular, breast cancer survivors report issues related to self-defining memories (SDMs), specific and significant AMs that evoke strong emotions and sensory details at the time of memory. SDMs are linked to life goals and facilitate adaptation to critical experiences, preserving the continuity of identity. This study explored the narrative identity integration process of breast cancer survivors, analyzing themes, specificity, and integrative meaning in SDMs. Ten women participated in an online group support program centered on the integration of AMs linked to the cancer journey. Participants were asked to assess their body image perceptions, filling out an online survey three times, in which they had to report three SDMs each time. A reflexive thematic analysis of the SDMs identified three main themes: the onset of breast cancer; the labeling of negative emotions, and changes in the body. The results indicated inhibited retrieval of specific episodes, fostering a progressive failure in memory characterization and the concurrent meaning-making process. Participants struggled with connecting the memories to insights regarding their self and life, as well as relating the memories to external conditions and other individuals. Further studies might examine the impact of these difficulties on the psychological adjustment of BC long-term survivors. They could also explore cognitive reconstruction by reframing the memories and re-evaluating their traumatic meanings.
Transcranial alternating current stimulation for neuropsychiatric disorders: a systematic review of treatment parameters and outcomes
Authors: Gholamali Nezhad Fatemeh , Martin Josh , Tassone Vanessa K. , Swiderski Alyssa , Demchenko Ilya , Khan Somieya , Chaudhry Hamzah E. , Palmisano Annalisa , Santarnecchi Emiliano , Bhat Venkat
Published: August 2024

Background

Transcranial alternating current stimulation (tACS) alters cortical excitability with low-intensity alternating current and thereby modulates aberrant brain oscillations. Despite the recent increase in studies investigating the feasibility and efficacy of tACS in treating neuropsychiatric disorders, its mechanisms, as well as optimal stimulation parameters, are not fully understood.

Objectives

This systematic review aimed to compile human research on tACS for neuropsychiatric disorders to delineate typical treatment parameters for these conditions and evaluate its outcomes.

Methods

A search for published studies and unpublished registered clinical trials was conducted through OVID (MEDLINE, PsycINFO, and Embase), ClinicalTrials.gov, and the International Clinical Trials Registry Platform. Studies utilizing tACS to treat neuropsychiatric disorders in a clinical trial setting were included.

Results

In total, 783 published studies and 373 clinical trials were screened; 53 published studies and 70 clinical trials were included. Published studies demonstrated a low risk of bias, as assessed by the Joanna Briggs Institute Critical Appraisal Tools. Neurocognitive, psychotic, and depressive disorders were the most common disorders treated with tACS. Both published studies (58.5%) and registered clinical trials (52%) most commonly utilized gamma frequency bands and tACS was typically administered at an intensity of 2 mA peak-to-peak, once daily for 20 or fewer sessions. Although the targeted brain locations and tACS montages varied across studies based on the outcome measures and specific pathophysiology of the disorders, the dorsolateral prefrontal cortex (DLPFC) was the most common target in both published studies (30.2%) and registered clinical trials (25.6%). Across studies that published results on tACS outcome measures, tACS resulted in enhanced symptoms and/or improvements in overall psychopathology for neurocognitive (all 11 studies), psychotic (11 out of 14 studies), and depressive (7 out of 8 studies) disorders. Additionally, 17 studies reported alterations in the power spectrum of the electroencephalogram around the entrained frequency band at the targeted locations following tACS.

Conclusion

Behavioral and cognitive symptoms have been positively impacted by tACS. The most consistent changes were reported in cognitive symptoms following gamma-tACS over the DLPFC. However, the paucity of neuroimaging studies for each neuropsychiatric condition highlights the necessity for replication studies employing biomarker- and mechanism-centric approaches.
The impact of exercise intervention on social interaction in children with autism: a network meta-analysis
Authors: Hou Yaoqi , Song Zhuo , Deng Jiaqi , Song Xiangqin
Published: August 2024

Background

Extensive research has documented the positive impacts of physical activity on children and adolescents with Autism Spectrum Disorders (ASD). However, the specific benefits of various sports on the social functioning of children with ASD remain ambiguous. This study aims to employ a network meta-analysis to investigate the effects of different sports on the social functioning of children and adolescents with ASD and to establish a ranking of their effectiveness.

Methods

This study conducted a comprehensive online search across Web of Science, PubMed, Cochrane, and Embase databases for randomized controlled trials and quasi-experimental studies focusing on social functioning outcomes. Data were synthesized using a Bayesian framework.

Results

Sixteen relevant studies encompassing 560 participants were included. According to Cohen’s classification, mini-basketball (SMD = 0.84, 95% CI: 0.46, 1.20), SPARK (SMD = 0.88, 95% CI: 0.06, 1.70), and Karate (SMD = 1.10, 95% CI: 0.27, 2.00) demonstrated high effect sizes, with Karate identified as the most effective intervention. Conversely, Combined Exercise and Nei Yang Gong interventions exhibited the least significant effects, falling below small effect sizes.

Conclusion

Physical activity interventions have been shown to enhance social functioning in children and adolescents with ASD to varying extents, with Karate emerging as the most efficacious.
Prevalence of mild cognitive impairment and its association with malnutrition in older Chinese adults in the community
Authors: Wang Ling-ying , Hu Zi-yi , Chen Hong-xiu , Zhou Chun-fen , Hu Xiu-ying
Published: August 2024

Objective

This study aims to characterize the prevalence and associated factors of cognitive impairment in older adults within Chinese community settings.

Background

Research exploring the interrelation between malnutrition and cognitive impairment in the older adult community-dwelling population is scarce. The impact of nutritional status on cognitive function in aging adults has not been definitively established.

Methods

A cross-sectional survey was conducted in one urban and one rural community in Chengdu, China, from October 2022 to March 2023. The sample included 706 older adults. Logistic regression was utilized to determine independent risk factors for mild cognitive impairment (MCI).

Results

The study found a significant prevalence of MCI at 32.0% among the older adult population. Among those suffering from malnutrition, 55.6% were affected by MCI. The logistic regression analysis indicated that malnutrition risk (OR = 2.192, 95% CI 1.431 to 3.357, p < 0.001), rural residence (OR = 1.475, 95% CI 1.003 to 2.170, p = 0.048), age (70–79 years old; OR = 2.425, 95% CI 1.611 to 3.651, p < 0.001; ≥80 years old: OR = 4.773, 95% CI 2.571 to 8.859, p < 0.001), male (OR = 1.584, 95% CI 1.085 to 2.313, p = 0.017), middle education level (OR = 0.986, 95% CI 1.627 to 5.482, p < 0.001), and ADL dependence (OR = 1.810, 95% CI 1.158 to 2.827, p = 0.009) were significantly associated with the occurrence of MCI.

Conclusion

The findings indicate a widespread occurrence of MCI in community-dwelling older Chinese adults. The association between malnutrition, as measured by the Mini Nutritional Assessment-Short Form (MNA-SF), and cognitive decline is evident. Older adult individuals with nutritional risk, advancing age, rural residence, male gender, moderate education, and ADL dependency are at increased likelihood of developing MCI. Longitudinal research is needed to clarify the temporal relationships between MCI, demographic factors, and whether improvements in nutritional status or ADL can reduce the incidence of MCI in this population.
Strategies and bottlenecks to tackle infodemic in public health: a scoping review
Authors: Gentili Andrea , Villani Leonardo , Osti Tommaso , Corona Valerio Flavio , Gris Angelica Val , Zaino Andrea , Bonacquisti Michele , De Maio Lucia , Solimene Vincenzo , Gualano Maria Rosaria , Favaretti Carlo , Ricciardi Walter , Cascini Fidelia
Published: August 2024

Background

The World Health Organization defines “infodemic” as the phenomenon of an uncontrolled spread of information in digital and physical environments during a disease outbreak, causing confusion and risk-taking behaviors that can harm health. The aim of this scoping review is to examine international evidence and identify strategies and bottlenecks to tackle health-related fake news.

Methods

We performed a scoping review of the literature from 1 January 2018 to 26 January 2023 on PubMed, Web of Science, and Scopus electronic databases. We also performed a search of grey literature on institutional websites. The research question has been defined according to the PCC (population, concept, and context) mnemonic for constructing research questions in scoping reviews.

Results

The overall research in the scientific databases yielded a total of 5,516 records. After removing duplicates, and screening the titles, abstracts, and full texts, we included 21 articles from scientific literature. Moreover, 5 documents were retrieved from institutional websites. Based on their content, we decided to group recommendations and bottlenecks into five different and well-defined areas of intervention, which we called strategies: “foster proper communication through the collaboration between science and social media companies and users,” “institutional and regulatory interventions,” “check and debunking,” “increase health literacy,” and “surveillance and monitoring through new digital tools.”

Conclusion

The multidisciplinary creation of standardized toolkits that collect recommendations from the literature and institutions can provide a valid solution to limit the infodemic, increasing the health education of both citizens and health professionals, providing the knowledge to recognize fake news, as well as supporting the creation and validation of AI tools aimed at prebunking and debunking.
Astroglial CD38 impairs hippocampal synaptic plasticity after global cerebral ischemia
Authors: Burch Amelia M. , Haas Ami , Orfila James E. , Tiemeier Erika , Gamboa Cassidy De Anda , Chalmers Nicholas , Quillinan Nidia , Herson Paco S.
Published: August 2024

Cardiac arrest-induced global cerebral ischemia (GCI) results in profound cognitive impairment in survivors. Our prior work demonstrated persistent disruption of long-term potentiation (LTP) in hippocampal CA1 neurons, correlating with learning and memory deficits in a rodent model of cardiac arrest/cardiopulmonary resuscitation (CA/CPR). Delayed inhibition of the Ca2+-permeable TRPM2 ion channel restored LTP post-CA/CPR, yet the mechanisms upstream of TRPM2 activation remain elusive. This study investigates CD38 as a potential regulator of TRPM2, highlighting a novel target to reverse hippocampal synaptic plasticity deficits after ischemia. We observe elevated levels of CD38 in activated astrocytes in the CA1 region of the hippocampus 7 days following CA/CPR in both male and female mice. Delayed inhibition of CD38 reverses hippocampal synaptic plasticity impairments at subacute timepoints after CA/CPR, phenocopying TRPM2 restoration of LTP. Our previous findings demonstrated that TRPM2 inhibition reverses the CA/CPR-induced enhancement of GABAA receptor (GABAAR) clustering, which contribute to ongoing LTP deficits. We, therefore, assessed the effect of CD38 on GABAergic inhibitory potentiation and find that inhibition of CD38 reverses GABAAR clustering in a TRPM2-dependent manner. In this study, we identify astroglial CD38 as a potential target and upstream regulator of the TRPM2 channel, offering a promising approach to restore hippocampal synaptic plasticity impairments following GCI through modulation of GABAergic signaling.
Solar empowerment in agriculture: investigating photovoltaic energy’s impact on efficiency among wheat farmers
Authors: Khan Nawab , Xu Xuanguo , Ahsan Faiza
Published: August 2024

Persistent electricity shortages in Pakistan, causing prolonged grid power load shedding, have adversely impacted various sectors, notably agriculture and the livelihoods of rural farmers. Literature suggests that adopting photovoltaic solar energy can mitigate these issues. This research aims to measure the impact of photovoltaic solar energy on the technical efficiency of food productivity in Khyber Pakhtunkhwa, Pakistan, applying data from 580 respondents. Addressing self-selective bias through ESR and stochastic frontier production function model is utilized to assess technical efficiency. The findings of this study reveal that farmers using solar energy experience a significant improvement in technical efficiency, with 15.8 percent of them achieving a 7.643 percent increase, after accounting for self-selection bias. Furthermore, the positive effects are more pronounced among larger farms and those with greater farming experience. This study underscores the importance of evidence-based approaches in implementing solar energy solutions, highlighting their potential to foster sustainability and equitable development at the grassroots level. The research culminates with policy recommendations that underscore the importance of promoting the photovoltaic solar energy use among farmers to improve food security and increase agricultural productivity.
A retrospective study of tracheal collapse in small-breed dogs: 110 cases (2022–2024)
Authors: Kim Mi-Rae , Kim Se-Hoon , Ryu Min-Ok , Youn Hwa-Young , Choi Ji-Hye , Seo Kyoung-Won
Published: August 2024

Background

The grade of tracheal collapse (TC) is assessed by the diameter of the narrowed lumen. However, studies on the relationship between TC grade and clinical symptom severity are lacking.

Objectives

To investigate the clinical characteristics of small-breed dogs diagnosed with TC and determine if fluoroscopic grading correlates with cough severity.

Methods

We retrospectively reviewed medical records from 2022 to 2024. TC diagnosis was confirmed using fluoroscopic examination. Multiple linear regression was employed to investigate factors influencing cough severity, with a significance level set at p < 0.05.

Results

A total of 132 dogs with TC were identified, of which 22 were excluded. The final cohort consisted of 110 dogs, aged between 2–19 years, with no significant sex differences. The majority (97.2%) of dogs had a BCS of ≥4. Among the top four breeds (Maltese, Pomeranian, Poodle, and Chihuahua), the most severe collapse was observed in the carinal region. The grade of collapse on fluoroscopy was mostly related to high BCS (p < 0.007) and low body weight (p < 0.001). However, interestingly, fluoroscopic findings of collapse location and grade did not correlate with cough severity (p = 0.350). Notably, clinical symptoms improved in 86.6% of cases following interventions such as weight reduction, environmental changes, and pharmacotherapy.

Conclusions and clinical relevance

In small-breed dogs, the severity of cough was not associated with the region or grade of TC diagnosed by fluoroscopy.
Comparing feces collection methods for evaluating the apparent digestibility coefficient of brewers’ spent yeast in juvenile Atlantic salmon (Salmo salar)
Authors: Orellana Paola , Márquez Lorenzo , Ortloff Alexander , Ruiz Joceline , Dantagnan Patricio , Hernández Adrián J.
Published: August 2024

Brewer’s spent yeast (BSY), derived from Saccharomyces cerevisiae used in beer production, is a valuable protein source for aquafeeds. Estimations of apparent digestibility coefficients (ADC) for nutrients in BSY are crucial for its inclusion in aquafeeds. ADC estimations for Saccharomyces cerevisiae protein in rainbow are hardly comparable from a methodological point of view, whereas the ADC estimations for BSY protein in Atlantic salmon are only based on stripped feces, which are known to produce underestimations. Therefore, new determinations of ADC of BSY nutrients are necessary for the inclusion of this ingredient in practical diets for salmonids. This study is focused on determining unbiased ADC values for protein and energy from BSY in juvenile Salmo salar. To reduce systematic biases, fecal samples were collected using stripping and decantation methods, which are known to produce under-and overestimations, respectively. 780 fish (25.16 ± 4.88 g) were stocked in six tanks. A reference diet (50% protein, 20% lipid, 1% Cr2O3) was provided to three tanks, and a test diet (70,30 reference diet to BSY) to the other three. ADC for BSY protein was 84.70 ± 1.04% (decantation) and 70.50 ± 4.03% (stripping). For gross energy, stripped feces yielded an ADC of 52.04 ± 5.30%, while decantation resulted in 63.80 ± 1.17%. Thus, ADC estimates were taken as the average of the stripping-value and the decantation-value, resulting in 77.6% for BSY crude protein, which is appreciably higher than previously measured values in S. salar fed undisrupted S. cerevisiae, and in 57.9% for gross energy.
Modeling Bibb Lettuce Nitrogen Uptake and Biomass Productivity in Vertical Hydroponic Agriculture
Authors: Sharkey Andrew , Altman Asher , Cohen Abigail R. , Groh Teagan , Igou Thomas K. S. , Ferrarezi Rhuanito Soranz , Chen Yongsheng
Published: August 2024

Global fertilizer production and mismanagement significantly contribute to many harmful environmental impacts, revealing the need for a greater understanding of crop growth and nutrient uptake, which can be used to optimize fertilizer management. This study experimentally adapts first-principles microbial modeling techniques to the hydroponic cultivation of Bibb lettuce (Lactuca sativa) under nitrogen-limited conditions. Monod and Michaelis–Menten’s approaches are applied to predict biomass productivity and nutrient uptake and to evaluate the feasibility of reclaimed wastewater as a nutrient source of nitrogen. Experimental and modeling results reveal significantly different kinetic saturation constants (Ks = 1.331 and Km = 17.887 mg L−1) and a corresponding cell yield strongly dependent on nutrient concentration, producing visually and compositionally distinct tissue between treatments receiving ≤26.2 and ≥41.7 mgN L−1. The resulting Monod model overestimates dry mass predictions during low nutrient conditions, and the collective results support the development of a dynamic Monod curve that is temporally dependent during the plants’ lifecycle. Despite this shortcoming, these results support the feasibility of reclaiming nitrogen from wastewater in hydroponic agriculture, expecting to produce lesser biomass lettuce exhibiting healthy tissue. Furthermore, this study provides a mathematical foundation for agricultural simulations and nutrient management.
Augmented Reality Applied to Identify Aromatic Herbs Using Mobile Devices
Authors: Lopes William Aparecido Celestino , Fernandes João Carlos Lopes , Antunes Samira Nascimento , Fernandes Marcelo Eloy , Nääs Irenilza de Alencar , Vendrametto Oduvaldo , Okano Marcelo Tsuguio
Published: August 2024

Correctly identifying and classifying food is decisive in food safety. The food sector is constantly evolving, and one of the technologies that stands out is augmented reality (AR). During practical studies at Companhia de Entreposto e Armazéns Gerais de São Paulo (CEAGESP), responsible for the largest food storage in South America, difficulties were identified in classifying aromatic herbs due to the large number of species. The project aimed to create an innovative AR application called ARomaticLens to solve the challenges associated with identifying and classifying aromatic herbs using the design science research (DSR) methodology. The research was divided into five stages according to the DSR methodology, from surveying the problem situation at CEAGESP to validating the application through practical tests and an experience questionnaire carried out by CEAGESP specialists. The result of the study presented 100% accuracy in identifying the 18 types of aromatic herbs studied when associated with the application’s local database without the use of an Internet connection, in addition to a score of 8 on a scale of 0 to 10 in terms of the usability of the interface as rated by users. The advantage of the applied method is that the app can be used offline.
Machine-Learning Microclimate Forecasting for Adaptive Equipment Control via Web Integration in Open-Ventilated Greenhouses
Authors: Thwin Kyaw Maung Maung , Horanont Teerayut , Phatrapornnant Teera
Published: August 2024

Open-ventilated greenhouses have reasonable setup costs and low operational costs for growers, which is crucial and most appealing for this research. These attributes fit developing nations like Thailand and other tropical regions. It is challenging to control the equipment intended to obtain an ideal microclimate. This research was conducted in an actual greenhouse setting for data collection and experiments, with a proposed system for adaptive equipment control via web integration. Also, the proposed multivariate multistep LSTM was forecasted over 1 h and cooperated with sensor data. Additional sensors, like a leaf wetness sensor and a CO2 sensor, were installed for detecting plant-level precision for vaporization, rather than greenhouse-level. The proposed system can optimize the indoor temperature within 34.5 to 36 °C with a 39 to 40 °C outdoor temperature. Also, humidity was still at the ideal level of 68 to 70%; more precisely, the wetness value was below 300 throughout the experiment. The model accuracy achieved a sufficient RMSE (0.49) and R2 (0.9788). This proposed system architecture and MM-LSTM model has potential as one dimension of a fully smart greenhouse system development in open-ventilated greenhouse settings in tropical regions and Southeast Asian nations for a better yield rate and less human interaction.
Odor Dilution Assessment for Explosive Detection
Authors: Huff Dillon E. , Cantu Ariela , Kane Sarah A. , Fernandez Lauren S. , Cañas-Carrell Jaclyn E. , Hall Nathaniel J. , Prada-Tiedemann Paola A.
Published: August 2024

Canine olfaction is a highly developed sense and is utilized for the benefit of detection applications, ranging from medical diagnostics to homeland security and defense prevention strategies. Instrumental validation of odor delivery methods is key to standardize canine olfaction research to establish baseline data for explosive detection applications. Solid-phase microextraction gas chromatography (SPME/GC-MS) was used to validate the odor delivery of an olfactometer. Three explosive classes were used in this study: composition C-4 (C-4), trinitrotoluene (TNT), and ammonium nitrate (AN). Dynamic airflow sampling yielded the successful detection of previously reported target volatile organic compounds (VOCs): 2,3-dimethyl-2,3-dinitrobutane (DMNB) in C-4 and 2-ethylhexan-1-ol (2E1H) in ammonium nitrate and TNT across odor dilutions of 80%, 50%, 25%, 12%, and 3%. C-4 highlighted the most reliable detection from the olfactometer device, depicting a response decrease as a function of dilution factor of its key odor volatile DMNB across the entire range tested. TNT only portrayed 2-ethylhexan-1-ol as a detected odor volatile with a detection response as a function of dilution from 80% down to 12%. Comparatively, ammonium nitrate also depicted 2-ethylhexan-1-ol as an odor volatile in the dynamic airflow sampling but with detection only within the upper scale of the dilution range (80% and 50%). The results suggest the importance of monitoring odor delivery across different dilution ranges to provide quality control for explosive odor detection using dynamic airflow systems.
Sea Cucumber Viscera Processed by Protease Hydrolysis Combined with Cordyceps militaris Fermentation Protect Caco-2 Cells against Oxidative Damage via Enhancing Antioxidant Capacity, Activating Nrf2/HO-1 Pathway and Improving Cell Metabolism
Authors: Mi Rui , Fu Zhiyu , Jiang Jingwei , Gao Shan , Guan Xiaoyan , Wang Xuda , Zhou Zunchun
Published: August 2024

Excessive reactive oxygen species (ROS) may lead to oxidative damage and metabolic disorder. The pathogenesis of human bowel inflammation is closely related to oxidative damage of intestinal epithelial cells caused by ROS. This study aimed to explore the high-value utilization of the byproducts of sea cucumber in antioxidant food for colitis prevention. The technology of protease hydrolysis combined with Cordyceps militaris fermentation was used to obtain fermented sea cucumber viscera protease hydrolysates (FSVHs). The results revealed that FSVH could enhance antioxidant capacity and alleviate oxidative damage and apoptosis by activating the Nrf2/HO-1 pathway and triggering the self-protection immune mechanisms. Moreover, the FSVH supplementation could upregulate antioxidant-related metabolic pathways of Caco-2 cells such as glutathione metabolism, confirming the enhanced antioxidant capacity of damaged cells. In summary, FSVH could exert protective effects on Caco-2 cells in response to oxidative damage, providing a promising prospect for sea cucumber resource utilization and colitis prevention.
Image-to-Image Steganography with Josephus Permutation and Least Significant Bit (LSB) 3-3-2 Embedding
Authors: Yanuar Muhammad Rafly , MT Suryadi , Apriono Catur , Syawaludin Muhammad Firdaus
Published: August 2024

In digital image security, the Josephus permutation is widely used in cryptography to enhance randomness. However, its application in steganography is underexplored. This study introduces a novel method integrating the Josephus permutation into the LSB 3-3-2 embedding technique for image steganography. This approach improves the randomness of the keystream generated by the chaotic logistic map, addressing vulnerabilities in basic logistic maps susceptible to steganalysis. Our algorithm is tested on RGB images as secret data, presenting higher complexity compared to grayscale images used in previous studies. Comparative analysis shows that the proposed algorithm offers higher payload capacity while maintaining image quality, outperforming traditional LSB techniques. This research advances the field of image steganography by demonstrating the effectiveness of the Josephus permutation in creating more secure and robust steganographic images.
A Deep Learning Estimation for Probing Depth of Transient Electromagnetic Observation
Authors: Gan Lu , Tang Rongjiang , Li Fusheng , Shen Fengli
Published: August 2024

The probing depth of the transient electromagnetic method (TEM) refers to the depth range at which the underground conductivity changes can be effectively detected. It typically ranges from tens of meters to several kilometers and is influenced by factors such as instrument parameters and the conductivity of the subsurface structure. Rapid and accurate probing depth is useful for the selection of appropriate inversion parameters and improving survey accuracy. However, mainstream methods suffer from issues such as low computational precision, large uncertainties, or high computational requirements, making them unsuitable for processing massive airborne electromagnetic data. In this study, we propose a prediction model based on deep learning that can directly compute the probing depth from the TEM responses, and its effectiveness and accuracy are validated through synthetic models and field measurements. We compared the performance of classic deep learning models, including CNN, RESNET, and RNN, and found that RNN performed the best overall on both synthetic and field data. Furthermore, we apply this algorithm to deep learning-based ATEM inversion by constraining the one-dimensional resistivity model depths in the training set, to reduce the non-uniqueness of the inversion, accelerate the convergence, and improve its prediction accuracy.
Diagnosis of Pressure Ulcer Stage Using On-Device AI
Authors: Chang Yujee , Kim Jun Hyung , Shin Hyun Woo , Ha Changjin , Lee Seung Yeob , Go Taesik
Published: August 2024

Pressure ulcers are serious healthcare concerns, especially for the elderly with reduced mobility. Severe pressure ulcers are accompanied by pain, degrading patients’ quality of life. Thus, speedy and accurate detection and classification of pressure ulcers are vital for timely treatment. The conventional visual examination method requires professional expertise for diagnosing pressure ulcer severity but it is difficult for the lay carer in domiciliary settings. In this study, we present a mobile healthcare platform incorporated with a light-weight deep learning model to exactly detect pressure ulcer regions and classify pressure ulcers into six severities such as stage 1–4, deep tissue pressure injury, and unstageable. YOLOv8 models were trained and tested using 2800 annotated pressure ulcer images. Among the five tested YOLOv8 models, the YOLOv8m model exhibited promising detection performance with overall classification accuracy of 84.6% and a mAP@50 value of 90.8%. The mobile application (app) was also developed applying the trained YOLOv8m model. The mobile app returned the diagnostic result within a short time (≒3 s). Accordingly, the proposed on-device AI app can contribute to early diagnosis and systematic management of pressure ulcers.
Structure of Public Passenger Transport Lines in the Region of Prešov in Slovakia to Support the Development of an Integrated Transport System
Authors: Bulková Zdenka , Škorupa Milan , Kendra Martin , Gašparík Jozef , Zitrický Vladislav
Published: August 2024

In the framework of sustainable development, the most important goal in the transport sector is sustainable mobility. It is necessary to improve the quality of the means of transport and the organisation of their operation in transport systems in addition to the management systems, coordination, and integration of individual types of transport. The aim of this paper is to propose a complex system of public transport lines in the region to achieve an effective transport service, in accordance with the principles of sustainable mobility, supporting the development of an integrated transport system. This research presents a proposal for the public transport lines of the region of Prešov in Slovakia, which is currently connected to an integrated transport system (IDS Východ). The proposal is defined by the tracing and functions of the lines, the mode of transport and headways on individual lines, the necessary number of vehicles for the operation of individual lines, transfer times at relevant points and directions, and the border of the radius of attractive daily commuting to the centre of the region, as well as a rough timetable for each line. Using an analytical hierarchical process (AHP method), we determine the two most suitable variants of traffic services. The results indicate that based on the multicriteria evaluation of these variants using descriptors, it is possible to determine the optimal variant of the transport service of the region, which will be introduced into a functional integrated transport system.
An Improved Ant Colony Algorithm with Deep Reinforcement Learning for the Robust Multiobjective AGV Routing Problem in Assembly Workshops
Authors: Chen Yong , Chen Mingyu , Yu Feiyang , Lin Han , Yi Wenchao
Published: August 2024

Vehicle routing problems (VRPs) are challenging problems. Many variants of the VRP have been proposed. However, few studies on VRP have combined robustness and just-in-time (JIT) requirements with uncertainty. To solve the problem, this paper proposes the just-in-time-based robust multiobjective vehicle routing problem with time windows (JIT-RMOVRPTW) for the assembly workshop. Based on the conflict between uncertain time and JIT requirements, a JIT strategy was proposed. To measure the robustness of the solution, a metric was designed as the objective. Afterwards, a two-stage nondominated sorting ant colony algorithm with deep reinforcement learning (NSACOWDRL) was proposed. In stage I, ACO combines with NSGA-III to obtain the Pareto frontier. Based on the model, a pheromone update strategy and a transfer probability formula were designed. DDQN was introduced as a local search algorithm which trains networks through Pareto solutions to participate in probabilistic selection and nondominated sorting. In stage II, the Pareto frontier was quantified in feasibility by Monte Carlo simulation, and tested by diversity-robust selection based on uniformly distributed weights in the solution space to select robust Pareto solutions that take diversity into account. The effectiveness of NSACOWDRL was demonstrated through comparative experiments with other algorithms on instances. The impact of JIT strategy is analyzed and the effect of networks on the NSACOWDRL is further discussed.
Status and Challenges of Medical History Taking in Bangladesh and an Affordable Digital Solution to Tackle Them
Authors: Hossain Forhad , Bouh Mohamed Mehfoud , Rahman Md Moshiur , Shah Faiz , Mine Tsunenori , Islam Rafiqul , Nakashima Naoki , Ahmed Ashir
Published: August 2024

Capturing patients’ medical histories significantly influences clinical decisions. Errors in this process lead to clinical errors, which increase costs and dissatisfaction among physicians and patients. Physicians in developing countries are overloaded with patients and cannot always follow the proper history-taking procedure. The challenges have been acknowledged; however, a comprehensive understanding of the status and the remedies has remained unexplored. This paper aims to investigate the workload, history-taking challenges, and the willingness of the physicians to accept digital solutions. A cross-sectional online survey was conducted on 104 physicians across Bangladesh, featuring 22 questions regarding their professional environment, workload, digitization status of health records, challenges in history taking, and attitudes toward adopting digital solutions for managing patient histories; 92.67% of the physicians face high workloads, 88.46% struggle in medical history taking, and only 4.81% use digital medical records. About 70% struggle to complete the necessary history-taking steps, emphasizing the urgent need for solutions. A novel visualization system, the Smart Health Gantt Chart (SHGC), has been introduced for their instant feedback. A total of 93.27% of physicians expressed their willingness to use such a system. The proposed SHGC has the potential to enhance healthcare efficiency in developing nations, benefit physicians, and improve patient-centered care.
Modeling and Analysis of Monkeypox Outbreak Using a New Time Series Ensemble Technique
Authors: Cuba Wilfredo Meza , Huaman Alfaro Juan Carlos , Iftikhar Hasnain , López-Gonzales Javier Linkolk
Published: August 2024

The coronavirus pandemic has raised concerns about the emergence of other viral infections, such as monkeypox, which has become a significant hazard to public health. Thus, this work proposes a novel time series ensemble technique for analyzing and forecasting the spread of monkeypox in the four highly infected countries with the monkeypox virus. This approach involved processing the first cumulative confirmed case time series to address variance stabilization, normalization, stationarity, and a nonlinear secular trend component. After that, five single time series models and three proposed ensemble models are used to estimate the filtered confirmed case time series. The accuracy of the models is evaluated using typical accuracy mean errors, graphical evaluation, and an equal forecasting accuracy statistical test. Based on the results, it is found that the proposed time series ensemble forecasting approach is an efficient and accurate way to forecast the cumulative confirmed cases for the top four countries in the world and the entire world. Using the best ensemble model, a forecast is made for the next 28 days (four weeks), which will help understand the spread of the disease and the associated risks. This information can prevent further spread and enable timely and effective treatment. Furthermore, the developed novel time series ensemble approach can be used to forecast other diseases in the future.
Fuzzy Evaluation Model for Critical Components of Machine Tools
Authors: Chen Kuen-Suan , Yao Kai-Chao , Cheng Chien-Hsin , Yu Chun-Min , Chang Chen-Hsu
Published: August 2024

The rapid progression of emerging technologies like the Internet of Things (IoT) and Big Data analytics for manufacturing has driven innovation across various industries worldwide. Production data are utilized to construct a model for quality evaluation and analysis applicable to components processed by machine tools, ensuring process quality for critical components and final product quality for the machine tools. Machine tool parts often encompass several quality characteristics concurrently, categorized into three types: smaller-the-better, larger-the-better, and nominal-the-better. In this paper, an evaluation index for the nominal-the-better quality characteristic was segmented into two single-sided Six Sigma quality indexes. Furthermore, the process quality of the entire component product was assessed by n single-sided Six Sigma quality indexes. According to numerous studies, machine tool manufacturers conventionally base their decisions on small sample sizes (n), considering timeliness and costs. However, this often leads to inconsistent evaluation results due to significant sampling errors. Therefore, this paper established fuzzy testing rules using the confidence intervals of the q single-sided Six Sigma quality indices, serving as the fuzzy quality evaluation model for components of machine tools.
Spatial Pattern of Host Tree Size, Rather than of Host Tree Itself, Affects the Infection Likelihood of a Fungal Stem Disease
Authors: Shi Yanli , Gao Xinbo , Jiang Yunxiao , Zhang Junsheng , Qi Feng-Hui , Jing Tian-Zhong
Published: August 2024

The spatial pattern of diseased forest trees is a product of the spatial pattern of host trees and the disease itself. Previous studies have focused on describing the spatial pattern of diseased host trees, and it remains largely unknown whether an antecedent spatial pattern of host/nonhost trees affects the infection pattern of a disease and how large the effect sizes of the spatial pattern of host/nonhost trees and host size are. The results from trivariate random labeling showed that the antecedent pattern of the host ash tree, Fraxinus mandshurica, but not of nonhost tree species, impacted the infection pattern of a stem fungal disease caused by Inonotus hispidus. To investigate the effect size of the spatial pattern of ash trees, we employed the SADIE (Spatial Analysis by Distance IndicEs) aggregation index and clustering index as predictors in the GLMs. Globally, the spatial pattern (vi index) of ash trees did not affect the infection likelihood of the focal tree; however, the spatial pattern of DBH (diameter at breast height) of ash trees significantly affected the infection likelihood of the focal tree. We sampled a series of circular plots with different radii to investigate the spatial pattern effect of host size on the infection likelihood of the focal tree locally. The results showed that the location (patch/gap) of the DBH of the focal tree, rather than that of the focal tree itself, significantly affected its infection likelihood in most plots of the investigated sizes. A meta-analysis was employed to settle the discrepancy between plots of different sizes, which led to results consistent with those of global studies. The results from meta-regression showed that plot size had no significant effects.
Halophila stipulacea: A Comprehensive Review of Its Phytochemical Composition and Pharmacological Activities
Authors: Chebaro Ziad , Mesmar Joelle Edward , Badran Adnan , Al-Sawalmih Ali , Maresca Marc , Baydoun Elias
Published: August 2024

Halophila stipulacea (Forsskål and Niebuhr) Ascherson is a small marine seagrass that belongs to the Hydrocharitaceae family. It is native to the Red Sea, Persian Gulf, and Indian Ocean and has successfully invaded the Mediterranean and Caribbean Seas. This article summarizes the pharmacological activities and phytochemical content of H. stipulacea, along with its botanical and ecological characteristics. Studies have shown that H. stipulacea is rich in polyphenols and terpenoids. Additionally, it is rich in proteins, lipids, and carbohydrates, contributing to its nutritional value. Several biological activities are reported by this plant, including antimicrobial, antioxidant, anticancer, anti-inflammatory, anti-metabolic disorders, and anti-osteoclastogenic activities. Further research is needed to validate the efficacy and safety of this plant and to investigate the mechanisms of action underlying the observed effects.
Role of Inflammation and the NF-κB Signaling Pathway in Hirschsprung’s Disease
Authors: Elkrewi Enas Zoheer , Al Abdulqader Ahmad A. , Khasanov Rasul , Maas-Omlor Silke , Boettcher Michael , Wessel Lucas M. , Schäfer Karl-Herbert , Tapia-Laliena María Ángeles
Published: August 2024

Hirschsprung’s disease (HSCR, incidence 1/5000 live births) is caused by the failure of neural crest-derived precursors to migrate, survive, proliferate, or differentiate during the embryonic development of the Enteric Nervous System (ENS), which could be disrupted by many factors, including inflammatory processes. The NF-κB family controls several biological processes, including inflammation, neurogenesis, and cell migration. With the aim of studying the potential role of NF-κB in HSCR, we have analyzed the expression of the NF-κB main subunits and other NF-κB-related genes by RT-qPCR in HSCR tissue samples (sub-divided into ganglionic and aganglionic segments). We found decreased gene expression of the NF-κB main subunit RELA but also of NFKBIA, TNFA, TFGBR2, and ERBB3 in the pathologic distal aganglionic segments compared to the proximal ganglionic segments. Moreover, we could also confirm the lower protein expression of RelA/p65 in the aganglionic distal segments by immunofluorescence staining. Further, we show that the expression of RelA/p65 protein in the proximal segments concurs with lymphocyte infiltration in the bowel tissue, indicating a pro-inflammatory activation of p65 in the proximal ganglionic HSCR tissue in the patients analyzed. All in all, our findings suggest that the modulation of NF-κB signaling in the neuro-enteric system does obviously contribute to the pathological effects of HSCR.
Cladosporols and PPARγ: Same Gun, Same Bullet, More Targets
Authors: Rapuano Roberta , Mercuri Antonella , Dallavalle Sabrina , Moricca Salvatore , Lavecchia Antonio , Lupo Angelo
Published: August 2024

Several natural compounds have been found to act as PPARγ agonists, thus regulating numerous biological processes, including the metabolism of carbohydrates and lipids, cell proliferation and differentiation, angiogenesis, and inflammation. Recently, Cladosporols, secondary metabolites purified from the fungus Cladosporium tenuissimum, have been demonstrated to display an efficient ability to control cell proliferation in human colorectal and prostate cancer cells through a PPARγ-mediated modulation of gene expression. In addition, Cladosporols exhibited a strong anti-adipogenetic activity in 3T3-L1 murine preadipocytes, preventing their in vitro differentiation into mature adipocytes. These data interestingly point out that the interaction between Cladosporols and PPARγ, in the milieu of different cells or tissues, might generate a wide range of beneficial effects for the entire organism affected by diabetes, obesity, inflammation, and cancer. This review explores the molecular mechanisms by which the Cladosporol/PPARγ complex may simultaneously interfere with a dysregulated lipid metabolism and cancer promotion and progression, highlighting the potential therapeutic benefits of Cladosporols for human health.
Design and Proof of Concept of a Web-Based Questionnaire to Identify Patients at Risk for HIV and HCV Infection
Authors: García-Ruiz de Morales Alejandro G. , Vivancos María Jesús , Lázaro Jorge , Romero Hernández Beatriz , Mateos Beatriz , Pérez-Elías Pilar , Herrero Delgado Margarita , Villanova Cuadra Laura , Moreno Santiago , Martínez-Sanz Javier , Pérez-Elías María Jesús
Published: August 2024

Despite remarkable improvement in the human immunodeficiency virus (HIV) and hepatitis C virus (HCV) care continuum, the rate of late diagnosis of HIV and HCV in high-income countries remains unacceptably high. Testing relies mainly on primary care physicians’ identification of risk factors. We aimed to adapt an analogic to an online questionnaire to help HIV and HCV screening and perform a pilot study to assess its accuracy and acceptability. We used the Delphi method to adapt a previously validated analogical questionnaire to a user-friendly online tool. It aimed to identify participants who should be screened for HIV or HCV and those who should be referred for pre-exposure prophylaxis (PrEP). We then designed a proof-of-concept pilot study from July to October 2022 to test its feasibility and suitability for use on a larger scale and to assess its accuracy in identifying patients at risk for HIV or HCV or with indication for PrEP. The final questionnaire consisted of 37 questions. A total of 142 participants provided informed consent, and 102 completed the questionnaire: 41 random patients recruited at the primary care level, 10 participants recently diagnosed with HIV, 20 participants with HIV on follow-up, 21 participants from the PrEP program, and 10 patients diagnosed with HCV. The tool adequately indicated the need for testing in more than 98% of participants with confirmed HIV/HCV infections or in the PrEP program. Furthermore, it adequately assessed PrEP referral in 94% of participants already on PrEP or with known HIV infection. Participants were highly satisfied with the tool, and 98% of them recommended its use. A self-administered web-based tool to identify patients who should be tested for HIV or HCV or referred to PrEP could simplify patient selection and help reduce late diagnosis.