bluuebunny/crossref_metadata_2025 huggingface dataset:
Biodetection of an odor signature in white-tailed deer associated with infection by chronic wasting disease prions
Authors: Golden Glen J. , Ramirez Elizabeth A. , Stevens Hayley N. , Bourbois Jennifer , Grove Daniel M. , Bowen Richard A. , DeLiberto Thomas J. , Kimball Bruce A.
Published: August 2024

Chronic wasting disease (CWD) has become a major concern among those involved in managing wild and captive cervid populations. CWD is a fatal, highly transmissible spongiform encephalopathy caused by an abnormally folded protein, called a prion. Prions are present in a number of tissues, including feces and urine in CWD infected animals, suggesting multiple modes of transmission, including animal-to-animal, environmental, and by fomite. CWD management is complicated by the lack of practical, non-invasive, live-animal screening tests. Recently, there has been a focus on how the volatile odors of feces and urine can be used to discriminate between infected and noninfected animals in several different species. Such a tool may prove useful in identifying potentially infected live animals, carcasses, urine, feces, and contaminated environments. Toward this goal, dogs were trained to detect and discriminate CWD infected individuals from non-infected deer in a laboratory setting. Dogs were tested with novel panels of fecal samples demonstrating the dogs’ ability to generalize a learned odor profile to novel odor samples based on infection status. Additionally, dogs were transitioned from alerting to fecal samples to an odor profile that consisted of CWD infection status with a different odor background using different sections of gastrointestinal tracts. These results indicated that canine biodetectors can discriminate the specific odors emitted from the feces of non-infected versus CWD infected white-tailed deer as well as generalizing the learned response to other tissues collected from infected individuals. These findings suggest that the health status of wild and farmed cervids can be evaluated non-invasively for CWD infection via monitoring of volatile metabolites thereby providing an effective tool for rapid CWD surveillance.
Artificial intelligence-assisted metastasis and prognosis model for patients with nodular melanoma
Authors: Xu Chan , Yu Xiaoyu , Ding Zhendong , Fang Caixia , Gao Murong , Liu Wencai , Liu Xiaozhu , Yin Chengliang , Gu Renjun , Liu Lu , Li Wenle , Wu Shi-Nan , Cao Bei
Published: August 2024

Objective

The objective of this study was to identify the risk factors that influence metastasis and prognosis in patients with nodular melanoma (NM), as well as to develop and validate a prognostic model using artificial intelligence (AI) algorithms.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was queried for 4,727 patients with NM based on the inclusion/exclusion criteria. Their clinicopathological characteristics were retrospectively reviewed, and logistic regression analysis was utilized to identify risk factors for metastasis. This was followed by employing Multilayer Perceptron (MLP), Adaptive Boosting (AB), Bagging (BAG), logistic regression (LR), Gradient Boosting Machine (GBM), and eXtreme Gradient Boosting (XGB) algorithms to develop metastasis models. The performance of the six models was evaluated and compared, leading to the selection and visualization of the optimal model. Through integrating the prognostic factors of Cox regression analysis with the optimal models, the prognostic prediction model was constructed, validated, and assessed.

Results

Logistic regression analyses identified that marital status, gender, primary site, surgery, radiation, chemotherapy, system management, and N stage were all independent risk factors for NM metastasis. MLP emerged as the optimal model among the six models (AUC = 0.932, F1 = 0.855, Accuracy = 0.856, Sensitivity = 0.878), and the corresponding network calculator (https://shimunana-nm-distant-m-nm-m-distant-8z8k54.streamlit.app/) was developed. The following were examined as independent prognostic factors: MLP, age, marital status, sequence number, laterality, surgery, radiation, chemotherapy, system management, T stage, and N stage. System management and surgery emerged as protective factors (HR < 1). To predict 1-, 3-, and 5-year overall survival (OS), a nomogram was created. The validation results demonstrated that the model exhibited good discrimination and consistency, as well as high clinical usefulness.

Conclusion

The developed prediction model more effectively reflects the prognosis of patients with NM and differentiates between the risk level of patients, serving as a useful supplement to the classical American Joint Committee on Cancer (AJCC) staging system and offering a reference for clinically stratified individualized treatment and prognosis prediction. Furthermore, the model enables clinicians to quantify the risk of metastasis in NM patients, assess patient survival, and administer precise treatments.
Seroprevalence and risk factors for SARS-CoV-2 infection in middle-sized cities of Burkina Faso: A descriptive cross-sectional study
Authors: Sana Adama , Djemaï Elodie , De Vreyer Philippe , Thivillon Thomas , Badolo Hermann , Berthé Abdramane , Kania Dramane
Published: August 2024

Background

Since March 2020, COVID-19 has evolved from a localized outbreak to a global pandemic. We assessed the seroprevalence of COVID-19 in three towns in the Centre Sud region of Burkina Faso.

Methods

A population-based cross-sectional survey was conducted in three middle-sized cities in Burkina Faso’s Centre Sud region, from June to July 2021. Subjects aged 16 or over at the time of the survey were considered for this seroprevalence study. The Biosynex COVID-19 BSS rapid test was used to detect immunoglobulin G (IgG) and immunoglobulin M (IgM) against SARS-CoV-2. A standardized questionnaire was also administered to collect additional information.

Results

A total of 2449 eligible participants (age ≥ 16 years) were identified. Serological tests for COVID-19 were performed in 2155 individuals, of which 2143 valid tests were retained and analyzed. Out of the entire sample, 246 positive tests were observed, corresponding to a prevalence of 11.48%. Prevalence was 9.35% (58 cases) in Kombissiri, 12.86% (80 cases) in Manga and 11.99% (108 cases) in Pô. By gender, 13.37% of women (164 cases) tested positive, and 8.95% of men (82 cases). Women accounted for 66.67% of all positive test subjects. The results from the multivariate analysis show a significantly higher seroprevalence in women (p = 0.007), people over 55 years old (p = 0.004), overweight people (p = 0.026) and those with drinking water sources at home (p = 0.013).

Conclusions

The results of this study show that the COVID-19 virus also circulates in the population of middle-sized cities in Burkina Faso, far more than officially reported by the information service of the government of Burkina Faso, given the lack of systematic testing in the general population in the country. The study also highlighted the greater vulnerability of women, older and overweight individuals to the epidemic. The preventive measures put in place to fight the pandemic must take these different factors into account.
Visual sequence encoding is modulated by music schematic structure and familiarity
Authors: Ren Yiren , Leslie Grace , Brown Thackery
Published: August 2024

Music is omnipresent in daily life and may interact with critical cognitive processes including memory. Despite music’s presence during diverse daily activities including studying, commuting, or working, existing literature has yielded mixed results as to whether music improves or impairs memory for information experienced in parallel. To elucidate how music memory and its predictive structure modulate the encoding of novel information, we developed a cross-modal sequence learning task during which participants acquired sequences of abstract shapes accompanied with paired music. Our goal was to investigate whether familiar and structurally regular music could provide a “temporal schema” (rooted in the organized and hierarchical structure of music) to enhance the acquisition of parallel temporally-ordered visual information. Results revealed a complex interplay between music familiarity and music structural regularity in learning paired visual sequences. Notably, compared to a control condition, listening to well-learned, regularly-structured music (music with high predictability) significantly facilitated visual sequence encoding, yielding quicker learning and retrieval speed. Conversely, learned but irregular music (where music memory violated musical syntax) significantly impaired sequence encoding. While those findings supported our mechanistic framework, intriguingly, unlearned irregular music–characterized by the lowest predictability–also demonstrated memory enhancement. In conclusion, this study demonstrates that concurrent music can modulate visual sequence learning, and the effect varies depending on the interaction between both music familiarity and regularity, offering insights into potential applications for enhancing human memory.
Rehabilitation outcomes of bird-building collision victims in the Northeastern United States
Authors: Kornreich Ar , Partridge Dustin , Youngblood Mason , Parkins Kaitlyn
Published: August 2024

Building collisions are a leading threat to wild birds; however, only those that are found dead or fatally wounded are included in current mortality estimates, with injured or stunned birds largely assumed to survive long-term. Avian building collision victims are often brought to wildlife rehabilitators for care, with the hopes they can be released and resume their natural lives. We examined the wildlife rehabilitation records of over 3,100 building collisions with 152 different avian species collected across multiple seasons to identify patterns of survival and release among patients. The number of admissions varied by season; fall migration had the highest number of cases and winter had the least number of cases, and summer having the lowest release proportion and winter having the highest. The most common reported injury was head trauma and concussion. Our logistic and Poisson models found that mass had a strong positive effect on release probability, and the season of summer had a strong negative effect on release probability. Mass and winter had a strong positive effect on treatment time, and age and the seasons of fall and winter had a strong negative effect on treatment time in these models. Ultimately, about 60% of patients died in care, either by succumbing to their injuries or by euthanasia. Patients that were released remained in care for longer than patients that died. This study reports different data than carcass studies and views bird-building collisions from the perspective of surviving victims to explore longer-term effects of these collisions on mortality. Increased communication and collaboration between wildlife rehabilitators and conservation researchers is recommended to better understand building collisions and how to respond to this leading threat to wild birds. These findings, along with our estimate of delayed mortality, suggest that overall collision mortality estimates based on carcass collection far exceed one billion birds in the U.S. each year.
VMseg: Using spatial variance to automatically segment retinal non-perfusion on OCT-angiography
Authors: LE BOITE Hugo , COUTURIER Aude , TADAYONI Ramin , LAMARD Mathieu , QUELLEC Gwenolé
Published: August 2024

Background and objectives

To develop and test VMseg, a new image processing algorithm performing automatic segmentation of retinal non-perfusion in widefield OCT-Angiography images, in order to estimate the non-perfusion index in diabetic patients.

Methods

We included diabetic patients with severe non-proliferative or proliferative diabetic retinopathy. We acquired images using the PlexElite 9000 OCT-A device with a photomontage of 5 images of size 12 x 12 mm. We then developed VMseg, a Python algorithm for non-perfusion detection, which binarizes a variance map calculated through convolution and morphological operations. We used 70% of our data set (development set) to fine-tune the algorithm parameters (convolution and morphological parameters, binarization thresholds) and evaluated the algorithm performance on the remaining 30% (test set). The obtained automatic segmentations were compared to a ground truth corresponding to manual segmentation from a retina expert and the inference processing time was estimated.

Results

We included 51 eyes of 30 patients (27 severe non-proliferative, 24 proliferative diabetic retinopathy). Using the optimal parameters found on the development set to tune the algorithm, the mean dice for the test set was 0.683 (sd = 0.175). We found a higher dice coefficient for images with a higher area of retinal non-perfusion (rs = 0.722, p < 10−4). There was a strong correlation (rs = 0.877, p < 10−4) between VMseg estimated non-perfusion indexes and indexes estimated using the ground truth segmentation. The Bland-Altman plot revealed that 3 eyes (5.9%) were significantly under-segmented by VMseg.

Conclusion

We developed VMseg, an automatic algorithm for retinal non-perfusion segmentation on 12 x 12 mm OCT-A widefield photomontages. This simple algorithm was fast at inference time, segmented images in full-resolution and for the OCT-A format, was accurate enough for automatic estimation of retinal non-perfusion index in diabetic patients with diabetic retinopathy.
Local resource availability drives habitat use by a threatened avian granivore in savanna woodlands
Authors: van Osta John M. , Dreis Brad , Grogan Laura F. , Castley J. Guy
Published: August 2024

Conserving threatened species relies on an understanding of their habitat requirements. This is especially relevant for granivorous birds, whose habitat use and movement patterns are intricately linked to the spatial and temporal availability of resources such as food and water. In this study, we investigated the habitat use, home range and daily activity patterns of the Endangered Southern Black-throated Finch (SBTF; Poephila cincta cincta) within a 75,000 ha savanna woodland study area in northeastern Australia. This semi-arid region is one of the key remaining strongholds for the species and is characterised by substantially different habitat and climatic conditions than areas where previous research on this species has been undertaken. We radio tracked 142 SBTF using both manual tracking and an array of 27 automated radio towers, which revealed a strong preference for eucalypt-dominated grassy woodland communities. The preference for these habitats also increased with decreasing distance to permanent water. While SBTF occupied large home ranges, individual SBTF were largely sedentary during the radio tracking period (21.8, range = 0.83–120 days), with few landscape-scale movements of more than 4.5 km. Daily foraging activity of SBTF exhibited bimodal peaks in the early morning and late afternoon, while other activities were greatest from the late morning to the early afternoon. Compared to other estrildid finches, our research suggests that SBTF track resources at a local scale across a large home range. We postulate that in times of resource scarcity SBTF may use dietary diversification, instead of landscape or regional-scale nomadic movements, to meet their resource needs. The species’ movement patterns underscore the importance of local scale habitat management to facilitate resource availability throughout the year. Furthermore, our research helps target monitoring designs for granivorous birds that focus on the species’ diurnal activity patterns.
Study examining the significant role of intellectual property protection in driving radical technological innovation among national research project teams, employing PLS-SEM and ANN modeling
Authors: Chen Wei , Yin Jianhui , Tian Ye , Shang Haixu , Li Yuan
Published: August 2024

This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspective. This study utilizes a sample of 336 national research project team members from various Chinese universities, research institutes, and corporations to analyze the theoretical model. Additionally, a two-stage hybrid partial least squares structural equation modeling (PLS-SEM) approach, combined with artificial neural network techniques (ANN), is employed to evaluate the hypotheses. The empirical findings of this study reveal a positive association between the intensity of IPP and RTI within national research project teams. Research and development investment intensity (R&DII) is identified as the primary predictor, while integrated leadership (IL) and group potential (GP) play crucial moderating roles. These groundbreaking findings extend the scope of innovation-driven and AMO theories, providing a proactive model for national research project teams to propose improvements to the IPP system, ultimately enhancing the realization of RTI.
Mixbiotic society measures: Assessment of community well-going as living system
Authors: Kato Takeshi , Miyakoshi Jyunichi , Matsumura Tadayuki , Mine Ryuji , Mizuno Hiroyuki , Deguchi Yasuo
Published: August 2024

Social isolation and fragmentation represent global challenges, with the former stemming from a lack of interaction and the latter from exclusive mobs—both rooted in communication issues. Addressing these challenges, the philosophical realm introduces the concept of the “mixbiotic society.” In this framework, individuals with diverse freedoms and values mix together in physical proximity with diverse mingling, recognizing their respective “fundamental incapacities” and uniting in solidarity. This study aims to provide novel measures to balance freedom and solidarity, specifically the intermediate between isolation and mobbing, within a mixbiotic society. To achieve this, we introduce simplified measures to evaluate dynamic communication patterns. These measures complement traditional social network analysis of static structures and conventional entropy-based assessments of dynamic patterns. Our specific hypothesis posits that the measures corresponding to four distinct phases are established by representing communication patterns as multidimensional vectors. These measures include the mean of Euclidean distance to quantify “mobism” for fragmentation, the relative distance change for “atomism” indicating isolation, and a composite measure derived from multiplying the mean and variance of cosine similarity for “mixism,” reflecting the well-going state of a mixbiotic society. Additionally, nearly negligible measures correspond to “nihilism.” Through the evaluation of seven real-society datasets (high school, primary school, workplace, village, conference, online community, and email), we demonstrate the utility of the “mixism” measure in assessing freedom and solidarity in society. These measures can be employed to typify communities on a radar chart and a communication trajectory graph. The superiority of the measures lies in their ability to evaluate dynamic patterns, ease of calculation, and easily interpretable meanings compared to conventional analyses. As a future development, alongside additional validation using diverse datasets, the mixbiotic society measures will be employed to analyze social issues and applied in the fields of digital democracy and platform cooperativism.
Optimizing young tennis players’ development: Exploring the impact of emerging technologies on training effectiveness and technical skills acquisition
Authors: Liu Sheng , Wu Chenxi , Xiao Shurong , Liu Yaxi , Song Yingdong
Published: August 2024

The research analyzed the effect of weekly training plans, physical training frequency, AI-powered coaching systems, virtual reality (VR) training environments, wearable sensors on developing technical tennis skills, with and personalized learning as a mediator. It adopted a quantitative survey method, using primary data from 374 young tennis players. The model fitness was evaluated using confirmatory factor analysis (CFA), while the hypotheses were evaluated using structural equation modeling (SEM). The model fitness was confirmed through CFA, demonstrating high fit indices: CFI = 0.924, TLI = 0.913, IFI = 0.924, RMSEA = 0.057, and SRMR = 0.041, indicating a robust model fit. Hypotheses testing revealed that physical training frequency (β = 0.198, p = 0.000), AI-powered coaching systems (β = 0.349, p = 0.000), virtual reality training environments (β = 0.476, p = 0.000), and wearable sensors (β = 0.171, p = 0.000) significantly influenced technical skills acquisition. In contrast, the weekly training plan (β = 0.024, p = 0.834) and personalized learning (β = -0.045, p = 0.81) did not have a significant effect. Mediation analysis revealed that personalized learning was not a significant mediator between training methods/technologies and acquiring technical abilities. The results revealed that physical training frequency, AI-powered coaching systems, virtual reality training environments, and wearable sensors significantly influenced technical skills acquisition. However, personalized learning did not have a significant mediation effect. The study recommended that young tennis players’ organizations and stakeholders consider investing in emerging technologies and training methods. Effective training should be given to coaches on effectively integrating emerging technologies into coaching regimens and practices.
Moderate-intensity physical activity reduces the role of serum PFAS on COPD: A cross-sectional analysis with NHANES data
Authors: Pan Manyi , Zou Yuxin , Wei Gang , Zhang Caoxu , Zhang Kai , Guo Huaqi , Xiong Weining
Published: August 2024

Background

Chronic obstructive pulmonary disease (COPD) has emerged as a leading cause of chronic disease morbidity and mortality globally, posing a substantial public health challenge. Perfluoroalkyl substances (PFAS) are synthetic chemicals known for their high stability and durability. Research has examined their potential link to decreased lung function. Physical activity (PA) has been identified as one of the primary modalities of the non-pharmacological treatment of COPD.

Methods

To investigate the relationship between PFAS and COPD, and whether physical activity could reduce the risk of COPD caused by PFAS exposure, we used data from the NHANES 2013–2018, a cross-sectional study. Logistic regression analysis was used to examine the associations between PFAS and COPD in adult populations, and their associations in different PA types.

Results

We finally included 4857 participants in the analysis, and found that Sm-PFOS (OR: 1.250), PFOA (OR: 1.398) and n-PFOA (OR: 1.354) were closely related to COPD; After stratified by gender, age and smoking, the results showed that Sm-PFOA (OR: 1.312) was related to COPD in female adult, and PFOA (OR: 1.398) and n-PFOA (OR: 1.354) were associated with COPD in male adults; The associations of Sm-PFOS (OR: 1.280), PFOA (OR: 1.481) and n-PFOA (OR: 1.424)with COPD tended to be stronger and more consistent in over 50 years old adults; Sm-PFOS was related to COPD in current smoker (OR: 1.408), and PFOA was related to COPD in former smoker (OR: 1.487); Besides, in moderate-intensity PA group, there were no associations of Sm-PFOS, PFOA and n-PFOA with COPD stratified by gender, age and smoking.

Conclusion

PFAS exposure may increase the risk of developing COPD, but regular moderate-intensity physical activity can protect individuals from evolving to the disease. However, longitudinal studies are needed to support these preliminary findings.
Unique features of KGN granulosa-like tumour cells in the regulation of steroidogenic and antioxidant genes
Authors: Tang Feng , Hummitzsch Katja , Rodgers Raymond J.
Published: August 2024

The ovarian KGN granulosa-like tumour cell line is commonly used as a model for human granulosa cells, especially since it produces steroid hormones. To explore this further, we identified genes that were differentially expressed by KGN cells compared to primary human granulosa cells using three public RNA sequence datasets. Of significance, we identified that the expression of the antioxidant gene TXNRD1 (thioredoxin reductase 1) was extremely high in KGN cells. This is ominous since cytochrome P450 enzymes leak electrons and produce reactive oxygen species during the biosynthesis of steroid hormones. Gene Ontology (GO) analysis identified steroid biosynthetic and cholesterol metabolic processes were more active in primary granulosa cells, whilst in KGN cells, DNA processing, chromosome segregation and kinetochore pathways were more prominent. Expression of cytochrome P450 cholesterol side-chain cleavage (CYP11A1) and cytochrome P450 aromatase (CYP19A1), which are important for the biosynthesis of the steroid hormones progesterone and oestrogen, plus their electron transport chain members (FDXR, FDX1, POR) were measured in cultured KGN cells. KGN cells were treated with 1 mM dibutyryl cAMP (dbcAMP) or 10 μM forskolin, with or without siRNA knockdown of TXNRD1. We also examined expression of antioxidant genes, H2O2 production by Amplex Red assay and DNA damage by γH2Ax staining. Significant increases in CYP11A1 and CYP19A1 were observed by either dbcAMP or forskolin treatments. However, no significant changes in H2O2 levels or DNA damage were found. Knockdown of expression of TXNRD1 by siRNA blocked the stimulation of expression of CYP11A1 and CYP19A1 by dbcAMP. Thus, with TXNRD1 playing such a pivotal role in steroidogenesis in the KGN cells and it being so highly overexpressed, we conclude that KGN cells might not be the most appropriate model of primary granulosa cells for studying the interplay between ovarian steroidogenesis, reactive oxygen species and antioxidants.
Association between metabolic score for insulin resistance and regression to normoglycemia from prediabetes in Chinese adults: A retrospective cohort study
Authors: Liu Xue-Hui , Xu Qiang , Zhang Lei , Liu Hong-Jun
Published: August 2024

Background

Metabolic score for insulin resistance (METS-IR) is a surrogate index to estimate insulin sensitivity. The aim of this study was to examine the association between METS-IR and regression to normoglycemia in Chinese adults with prediabetes.

Methods

A total of 15,415 Chinese adults with prediabetes defined by their fasting blood glucose were included in this retrospective study. The association between METS-IR and regression to normoglycemia from prediabetes was evaluated using the Cox proportional hazards regression model. A Cox proportional hazards regression with cubic spline function was performed to explore the nonlinear association between METS-IR and regression to normoglycemia. Kaplan-Meier curves was used to describe the probability of regression to normoglycemia from prediabetes.

Results

In multivariate Cox proportional hazards regression analyses, the increase in METS-IR was independently associated with a reduced probability of regression to normoglycemia from prediabetes (all p < 0.01 in models 1–3). A nonlinear association between METS-IR and the probability of regression to normoglycemia was observed, with an inflection point of 49.3. The hazard ratio on the left side of the inflection point was 0.965 (95% CI 0.953–0.976). Subgroup analyses demonstrated the robustness of our findings.

Conclusion

This study demonstrated a negative and nonlinear association between METS-IR and regression to normoglycemia in Chinese adults with prediabetes. When METS-IR is below 49.3, reducing METS-IR could significantly increase the probability of regression to normoglycemia from prediabetes.
Sex differences in intra-set kinematics and electromyography during different maximum repetition sets in the barbell back squat?
Authors: van den Tillaar Roland , Bao Fredriksen Andrea , Hegdahl Gundersen Andreas , Nygaard Falch Hallvard
Published: August 2024

Barbell squats are commonly utilized in resistance training for rehabilitation, daily living enhancement, and improving sports performance. The current study investigated the kinematic and electromyographic (EMG) parameters in the squat between sexes across different repetition ranges (1-, 3-, 6-, and 10-RM) among recreationally strength-trained subjects. A total of 26 subjects (13 men: age 25 ± 3.5 years, height 178.2 ± 5.8 cm, weight 82.3 ± 9.1 kg; 13 women: age 24 ± 4.1 years, height 165.4 ± 6.3 cm, weight 68.2 ± 8.7 kg) participated in the study. The level of significance was set at p<0.05. The findings revealed no sex-specific differences in average barbell velocity across repetition ranges. However, the 1-RM showed a significantly lower average velocity compared to the final repetition of other repetition ranges (p<0.001), with the last repetition at 10-RM revealing a significantly higher velocity (p<0.001). Women had greater maximal angular hip extension velocity in the final repetitions of the 6- and 10-RM (p≤0.035, ηp2≤0.20), while both sexes displayed lower maximal angular knee extension velocity in the final repetition of the 10-RM (p = 0.028, ηp2 = 0.15). Moreover, men had lower EMG amplitude in the rectus femoris (3- and 10-RM), soleus, and lateral vastus (10-RM) compared to women (p≥0.011, ηp2≥0.26). It was concluded that 10-RM differed greatly in kinematics and EMG, suggesting different fatigue mechanisms compared to other repetition ranges with heavier loads. Furthermore, sex differences in EMG and angular hip extension velocity might imply sex-specific fatiguing mechanisms during high-repetition squats. These considerations could be important when prescribing training programs.
Assessing Representativeness of the All of Us Type 2 Diabetes

Cohort Using BRFSS State Data
Authors: Zheng Lijia , Li Chenyu , Becich Michael M. , Kravchenko Olga
Published: August 2024

This study investigates the representativeness of the 'All of Us' Type 2 Diabetes (T2DB) cohort by comparing it with the demographic diversity of the Behavioral Risk Factor Surveillance System (BRFSS) benchmark. We identified 33,587 individuals within the AoU cohort using established computational phenotypes, noting significant disparities in race-age distributions. The analysis underscores the need for enhanced data collection strategies and targeted recruitment to reduce biases and improve research validity.
Performance Evaluation of DGNSS Receiver for Dynamic Military Applications
Authors: Chasmai Moiz , Purohit Gagandeep , Barde Arun , Sandeep Sandeep , Kumar Prashant , Kamble Abhijit
Published: August 2024

In military applications, a highly accurate and precise navigation system is necessary for some ground-based combat system applications to navigate the vehicle and mark the location of the fuses and pickets laid by the mobile equipment. Few companies across the globe have developed expertise in manufacturing Global Navigation Satellite System (GNSS) receivers with Real Time Kinematics (RTK) capability along with integrated INS. On mobile equipment, it is not always possible to precisely place the Differential GNSS (DGNSS) antenna and GNSS receiver at the point for which the data needs to be marked. For such applications, lever arm calculation needs to be implemented. Also, due to uneven terrain conditions and slopes, the vehicle undulates up to 10o about its longitudinal and transverse axis. This dynamic condition induces considerable errors in the actual data. During the fuse laying process, there is also a continuous requirement for real-time location data in the GNSS-denied environment for a short period. INS was integrated with the GNSS receiver. We discuss test methodology for GNSS receiver performance evaluation. Experimentations were performed, taking into consideration these requirements. Data collected are also analyzed and discussed. Test results confirmed that the module is accurate with an accuracy of a few centimeters.
Terramechanics Models for Tracked Vehicle Terrain Interaction Analysis A Review
Authors: Chakravarthy Pogula Nikhil , Sharma Pankaj Kumar
Published: August 2024

Efficient manoeuvrability of off-road tracked vehicles such as military tanks and rovers is essential in ensuring the success of military/extra-terrestrial operations. To achieve this, in-depth research on vehicle-terrain interaction is crucial. This manuscript deals with reviewing the ways to study terramechanics viz. theoretical, empirical, and field tests, and proposing the merits and demerits of each method. Under the theoretical approach, empirical, numerical, and semi-empirical methods are discussed. Under the empirical approach, the method based onthe vehicle cone index for tracked and wheeled vehicles is discussed. Under the numerical approach, advantages and disadvantages of Finite Element Method (FEM) and Discrete Element Method (DEM) are discussed. Semi-empirical method, based upon a combination of the best features of numerical and empirical approaches discusses terrain response to normal repetitive loads and shear repetitive loads for tracked as well as wheeled vehicles. Pressure sinkage relationship for terrains at various loading conditions and shear stress displacement relationship for different terrains obtained through penetration and shear tests are discussed to determine the vehicle’s mobility parameters under a semi-empirical approach. Further, the Super element model, multi-body simulation model, and ride and cornering vibration model are discussed under computer simulation models. A detailed review of various models customized towards tracked vehicle-terrain interaction discussed in this manuscript helps the authors set up a laboratory for terramechanics at DIAT. Preliminary analysis along with conceptual design of the experimental setup is also discussed. In a nutshell, this paper attempts to summarize the research that has been carried out in the field of tracked vehicle-terrain inter action comprising of VCI, MMP, FEM, DEM, Super element model, Multibody technique, and Semi-empirical methods helping the authors to establish a laboratory of terramechanics for their M. Tech. program on Armament and Combat Vehicles at DIAT Pune.
Comparison of Filtering Techniques for Transfer Alignment of Air Launched Tactical Guided Weapons
Authors: Jain Sambhav Kumar , Jain Tapan K. , Srivastava Srikant , Shanker Saumya
Published: August 2024

The transfer alignment technique is very useful for the accurate initialization and calibration of gyroscopes and accelerometers of INS for air-launched tactical guided weapon systems. In the present war scenario, the initialization of INS should be accurate and rapid to launch the tactical weapon against air or land targets within the shortest available time. A lot of development has been carried out by researchers for INS transfer alignment in the field of state estimation. The study and method presented in the research are relevant to aerial launch vehicles. However, to meet present guidance requirements within less time for initializing weapons, more appropriate transfer alignment algorithms are needed. This paper discusses the relative performance of Kalman Filter (KF), Extended KF, and Unscented KF for aligning the weapon INS using the data from Master INS. New developments, limitations, applicability, and design methods for the Kalman filters, became a key component in the transfer alignment of air-launched tactical missiles. These methodologies are extensively utilized in Navigation and Control systems; therefore, this research work will be an informative and perfect guide to existing and potential readers.
FuzzyBandit An Autonomous Personalized Model Based on Contextual Multi Arm Bandits Using Explainable AI
Authors: Bansal Nipun , Bala Manju , Sharma Kapil
Published: August 2024

In the era of artificial cognizance, context-aware decision-making problems have attracted significant attention. Contextual bandit addresses these problems by solving the exploration versus exploitation dilemma faced to provide customized solutions as per the user’s liking. However, a high level of accountability is required, and there is a need to understand the underlying mechanism of the black box nature of the contextual bandit algorithms proposed in the literature. To overcome these shortcomings, an explainable AI (XAI) based FuzzyBandit model is proposed, which maximizes the cumulative reward by optimizing the decision at each trial based on the rewards received in previous observations and, at the same time, generates explanations for the decision made. The proposed model uses an adaptive neuro-fuzzy inference system (ANFIS) to address the vague nature of arm selection in contextual bandits and uses a feedback mechanism to adjust its parameters based on the relevance and diversity of the features to maximize reward generation. The FuzzyBandit model has also been empirically compared with the existing seven most popular art of literature models on four benchmark datasets over nine criteria, namely recall, specificity, precision, prevalence, F1 score, Matthews Correlation Coefficient (MCC), Fowlkes–Mallows index (FM), Critical Success Index (CSI) and accuracy.
A Novel & Efficient LR LSTM AIS Route Data Prediction for Longer Range
Authors: Raj Nitish , Kumar Prabhat
Published: August 2024

The growth of technology has enabled different industries to generate an excessive amount of data- one such industry being the maritime sector. Sophisticated sensory systems installed on various vessels generate information at a very large scale which can further be used in optimizing operational efficiency, improving safety standards, and aiding in the decision-making process. Researchers have henceforth identified statistical learning methods and machine learning techniques as potent tools for excavating useful insights from this copious amount of data available. This research evaluates how these algorithms work by focusing exclusively on the analysis of sensory data collected from vessels within the maritime domain. A comparison study has been conducted between statistical learning methods (which includes regression analysis, and time series analysis) vis-a-vis machine learning approaches. The major objective of this study was to determine the most effective method for detecting anomalies while simplifying marine operations and optimizing vessel behavior. The scope of the conducted analysis is restricted to the prediction of the next trajectory points. Accurate prediction of vessel positions plays a crucial role in maritime operations, enabling efficient route planning, collision avoidance, and maritime traffic management. In this article, the authors propose a combination model that combines the benefits of Linear Regression (LR) and Long Short-Term Memory (LSTM) techniques to anticipate vessel positions based on Automatic Identification System (AIS) data. The proposed model takes advantage of the interpretability of LR and the temporal dependencies collected by LSTM to capture temporal dependencies, which improve prediction accuracy and reveal the underlying links between vessel features and future positions.
The Effects of Oxidative Stress on RNA Editing with Insight into the Relationship Between Air Pollution and Alzheimer's Disease
Authors: Forbes Melanie
Published: August 2024

Human interactions with the environment today add pressure on the world’s resources and ecosystems, which in turn harm human health. Many anthropogenic environmental changes, including climate change, biodiversity loss, and pollution, have accelerated morbidity and mortality. Research across multiple countries have found correlations between anthropogenic air pollution exposure and neurological degeneration, particularly with Alzheimer’s disease (AD). RNA editing induced by oxidative stress is one possible mechanism in which air pollution increases the risk of AD. To study this further, RNA adenosine-to-inosine (A-to-I) alterations were analyzed to identify a mechanism linking air pollution to neurological degeneration. These alterations occur in RNA, most prevalently in the central nervous system (CNS). Adenosine deaminase acting on RNA (ADAR) enzymes mediate A-to-I alterations and are essential for mammalian development and survival. ADAR mediated alterations have been associated with AD and the A-to-I occurrence frequency may increase in polluted environments that trigger increased oxidative stress. To test this possibility, wildtype (WT) and ADAR knockout (adr-2(-) Caenorhabditis elegans in their first larval (L1) developmental stage were exposed to juglone solution for 0, 15, and 60 minute experimental settings. For the two worm strains, WT and adr-2(-), the 0 minute treatment was the control, the 15 minute treatment represented acute oxidative stress exposure, and the 60 minute treatment represented chronic exposure. RNA was extracted from both groups and quantitative Real Time PCR (qRT-PCR) was used to measure the expression of gst-4, an Alzheimer’s associated gene (sel-12), and adr-2 normalized to the expression of gpd-3, the housekeeping gene that corrected for systemic errors. The gst-4 gene expression confirmed that oxidative stress occurred. Lack of adr-2 gene significantly decreased sel-12 expression at acute exposure, but adr-2 gene expression in WT worms did not significantly change across treatments. It remains to be determined whether oxidative stress impacts RNA editing of target mRNAs. Future studies are needed to explore the role of adr-2 in promoting sel-12 expression.
Utilization of Sidoarjo Volcanic Mud as Heterogeneous Catalyst in Persulfate Oxidation Process
Authors: Nisrina Khairunnisa Faza , Adityosulindro Sandyanto , Direstiyani Lucky Caesar
Published: August 2024

Advanced Oxidation Processes (AOP), such as persulfate oxidation is a promising contaminant removal agent for treating wastewater. In this study, Sidoarjo volcanic mud (VM) was applied as heterogeneous catalyst to support the persulfate oxidation process for Congo Red (CR) dye removal. The Sidoarjo volcanic mud is known to have a high iron content, making it a potential catalyst in AOP. This study was conducted under conditions of pH 2, CR 50 mg/L, and catalyst dosage 0.5 g/L  and effective reaction volume of 300 mL. This experiment was conducted by comparing three types of catalysts: unmodified volcanic mud (UVM), impregnated volcanic mud (Fe-IVM), and calcined volcanic mud (CVM). The methods were carried out by comparing two methods, namely simultaneous and sequential. The obtained CR removal values for UVM, Fe-IVM, and CVM catalysts were 83.73%, 78.86%, 51.96% for simultaneous and 84.75%, 81.72%, and 87.69% for sequential method. Whereas the UVM catalyst has the highest CR removal value with a lower adsorption value of 16.89%. The production of sulfate radical analyzed by comparing the oxidation process of homogeneous and heterogeneous catalysts. It was shown that the application of VM catalyst as heterogeneous catalyst is very promising for dye removal in wastewater treatment.
Effectiveness Evaluation of Alternative Technologies Applied in Centralized Domestic Wastewater Treatment Systems
Authors: Mubarok Ahmad , Ernayati Widya , Sjaifuddin Sjaifuddin
Published: August 2024

The paper aims to determine the effectiveness of several alternative technologies that have been applied in centralized domestic wastewater management systems, especially in West Java and Banten provinces, in the removal of domestic wastewater pollutant parameters. The study was conducted in SPALD-Ts, including the Anaerobic Baffle Reactor (ABR) system, the Anobic Filter (AF) system, the combined ABR + AF system, and the Extended Aeration. The analysis was performed by sampling at the inlet and outlet points of the system for three consecutive years with sampling times from 2021 - 2023. The results of the research show that the efficiency of pollutant parameter separation based on the best technology in the separation of domestic wastewater pollutant parameters is the SPALDT extended aeration technology, where this technology can separate pollutant parameters up to an average of 88.25%, but in this technology requires more cost and periodic maintenance.
The Relationship of Surface Ozone Pollution with Meteorological Conditions in Determining Episode Periods
Authors: Ramadhan Taufik Rizki , Permadi Didin Agustian
Published: August 2024

Jakarta, the capital city of Indonesia, is located in a tropical region with abundant sunlight and high temperatures year-round. Ozone and particulate matter (PM) are critical parameters causing unhealthy air pollution. Meteorological data were obtained from the NASA Power website. This study aims to explore the relationship between ozone formation and meteorological factors in Jakarta. Ozone air quality data were measured using the Backman model 950A ozone Analyzer, which detects concentrations as low as 0.05 ppm, with measurements taken every 40 seconds. From January to October 2023, ozone concentrations increased during the dry months of May to October, with the highest hourly value recorded at 263 μg/m³. During this period, average temperatures ranged from 27-29°C, rainfall was 0.3-5.6 mm, wind speeds were 3.14-4.64 m/s, wind direction was 92-171 degrees, and air humidity was 74-82%. Significant episodes were identified on (i) May 5-9, (ii) July 12-15, (iii) September 6-7, (iv) September 13-14, (v) September 21-22, and (vi) October 29-30, 2023. Daily, monthly, and seasonal ozone variations aligned with meteorological conditions, showing higher concentrations during the dry months. Further studies, including photochemical modeling, are required to identify dominant factors causing high ozone concentrations during these episodes. Understanding NOx or VOC emission sensitivities is crucial for effective ozone abatement strategies in Jakarta.
Green Hospital Implementation in Dr. Cipto Mangunkusumo National Central Public Hospital
Authors: Dzikriyati Nadiva , Raharjo Mursid , Nurjazuli Nurjazuli , Subagyo Baji , Hashim Jamal Hisham
Published: August 2024

Every day, hospitals carry out various health services and administrative activities constantly, so therefore hospitals are expected to reduce negative impacts on the environment by creating green hospitals. Green hospitals are hospitals that are designed, built, renovated, operated, and maintained by considering health and environmental development principles. This research used qualitative and quantitative methods. The qualitative method used is a case study method in the form of in-depth exploration from various perspectives related to the uniqueness of the green hospital system based on evidence obtained at the research location.  The quantitative method was carried out using a descriptive method in the form of simple statistics to describe the extent of green hospital achievements at Cipto Mangunkusumo General Hospital. The types of data collected are primary data from observation and in-depth interviews and secondary data from document review results. Implementation of green hospital in RSUPN Dr. Cipto Mangunkusumo, from 93 indicators 84,9% or 79 indicators are accomplished in RSUPN Dr. Cipto Mangunkusumo. The indicators with the most presentation are location and landscape, hopitals’ structure, Water efficiency, food processing, and air quality with 100% percentage. And the indicator with the least presentation are energy efficiency with 64,3% percentage.