bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimentation and 2D Fluid Flow Simulation over an External Gear Pump
Authors: Adake Dhananjay G , Dhote Nihal D , Khond Mohan P 
Published: October 2023

Abstract
In this work, the investigation’s goal is to conduct experiments and simulations on the existing gear pump test rig setup. The various parameters are set and observed in the first section of the investigation. Calculations are done using these numbers to obtain the other testing results. Another section simulates 2-D fluid flow over an external gear pump and contrasts the findings of the experiment with the flow rate and efficiency at various discharge pressures. This study provides a clear understanding of the external gear pump’s numerical analysis as well as its actual analysis. For each discharge pressure at the end, a prediction of pressure at various locations within the pump’s fluid domain was made.
In Cabin Driver Monitoring and Alerting System For Passenger cars using Machine Learning.
Authors: Suryavanshi Shrirang , Ladhwe Raju , Joshi Omkar 
Published: October 2023

Abstract
The primary causes of road accidents are driver errors. Such as excessive speeding, driver distraction, and driver sleepiness. Diver sleepiness and distraction can be controlled by implementing advanced technology such as an in-cabin driver monitoring system. This is a technological solution that uses a machine learning algorithm to improve road safety. This paper describes a new real-time driver monitoring and alerting system that solely monitors driver Sleepiness, diver distraction, and seatbelt wearing status in order to prevent road accidents. It employs the YOLOv5 deep learning algorithm to detect various types of distraction and For seatbelt wearing status and computer vision’s cvzone framework is used to detect sleepiness using 3D facial landmarking. In this system, The camera is mounted in the centre of the vehicle’s dashboard for data collection and real-time implementation. The Raspberry Pi 3b module is used for the Realtime implementation. According to the findings of this study, the system is capable of real-time implementation, and the machine learning model used in the study achieves an accuracy of more than 90%.
A Deep Learning model for driver drowsiness detection in extremely low-light conditions
Authors: Anoop P P , Deivanathan R 
Published: October 2023

Abstract
Accidents occurring at night account for a significant percentage when compared to those that happen during the daytime. One of the leading causes of such accidents is driver drowsiness, which could result from inadequate sleep or exhaustion. Continuous monitoring of the facial expressions of the driver can detect signs of drowsiness, and an alarm system can alert the driver and prevent potential accidents. Various research studies have been conducted in this area. However, the low lighting conditions at night make it challenging to obtain detailed images, making it difficult to apply the proposed models effectively. This paper presents an effective model for detecting driver drowsiness using deep learning techniques. The study utilizes AlexNet as a classifier and attains an impressive accuracy of 98.3% after hyperparameter tuning.
Recent development of LIF diagnostics in ASIPP
Authors: Yip Chi-Shung , Jiang Di , Jin Chenyao , Zhang Wei 
Published: October 2023

Abstract
In this article, recent research progress of laser induced fluorescence (LIF) diagnostics in ASIPP is reviewed. The fundamental goal of ASIPP's effort on the LIF diagnostics is to develop a working velocity distribution function (VDF) diagnostic to monitor helium ash removal in burning plasmas. Real-time monitoring of helium ash VDF requires consideration in radiation safety, measurement response time, and compatibility of tokamak operation, as well as ion/neutral VDFs with a temperature at possibly >20 eV. These considerations, almost unique to large-scale instruments or specifically to tokamak plasmas, require renewed research and development (R&D) efforts in optical design, automation, and expansion of laser functionality for the LIF diagnostics that were often not considered in conventional applications of the LIF diagnostics. To this end, ASIPP invested a series of research effort into the development of LIF techniques. Signal evaluation has been performed on a diagnostics-test device (LTS), and the obtained signal strength has been extrapolated to tokamak edge and divertor relevant environments with promising results. The extrapolations compared the available solid angle and plasma density between the test device and the design scenario where the LIF diagnostics will potentially be implemented in a tokamak edge and divertor plasma. The estimation neglects the higher density of energetic electrons in the edge and divertor regions, making it a conservative assessment. Automated post-DAQ processing of LIF signals using both “conventional” methods and an AI-augmented method were also explored. Both approaches yielded usable results, but the AI-trained method showed a faster response, which is advantageous for real-time plasma diagnostics. Basic mechanisms of LIF diagnostics were also explored. Specifically, the limitations of lock-in modulation was demonstrated to determine the limitation of time-resolved measurements using such methods. De-modulation and degradation of the LIF signal occurred as the modulation frequency exceeded 1/10th of the fluorescence frequency. This finding sets a practical limit of the modulation frequency up to which we can benefit from lock-in amplification. These published works along with other unpublished progress will be thoroughly discussed in this article to illustrate ASIPP's effort towards the implementation of LIF diagnostics in future tokamak devices and to promote the application of LIF diagnostics in other fields of research.
Carbon dioxide release from retrogressive thaw slumps in Siberia
Authors: Beer C , Runge A , Grosse G , Hugelius G , Knoblauch C 
Published: October 2023

Abstract
Thawing of ice-rich permafrost soils in sloped terrain can lead to activation of retrogressive thaw slumps (RTSs) which make organic matter available for decomposition that has been frozen for centuries to millennia. Recent studies show that the area affected by RTSs increased in the last two decades across the pan-Arctic. Combining a model of soil carbon dynamics with remotely sensed spatial details of thaw slump area and a soil carbon database, we show that RTSs in Siberia turned a previous quasi-neutral ecosystem into a strong source of carbon dioxide of 367 ± 213 gC m-1 a-1. On a global scale, recent CO2 emissions from Siberian thaw slumps of 0.42 ± 0.22 Tg carbon per year are negligible so far. However, depending on the future evolution of permafrost thaw and hence thaw slump-affected area, such hillslope processes can transition permafrost landscapes to become a major source of additional CO2 release into the atmosphere.
Serengeti–Masai Mara ecosystem dynamics inferred from rainfall extremes
Authors: Mtewele Zacharia Florence , Jia Gensuo , Xu Xiyan 
Published: October 2023

Abstract
The Serengeti–Masai Mara Ecosystem (SMME) is an iconic ecological and biodiversity resource in East Africa with a spectacular great animal migration feature. Environmental shocks like droughts, floods, and land degradation threaten the SMME’s ecological functioning. However, the spatiotemporal ecosystem dynamics during climate extremes are inadequately examined. Here we quantified water availability and vegetation changes during extreme wet (EWE) and dry (EDE) events over the SMME for wet and dry seasons in 1982–2020. We derived extreme events from seasonal mean precipitation anomaly exceeding standard deviation and applied composite and correlation techniques to assess their dynamics with animal populations and migration prospects. Wet season EWE increases vegetative and moist conditions over southern SMME, suggesting elongating migrants’ occupancy compared to normal periods and delayed northward migration. Wet season EDE significantly suppresses these features, heightening ecosystem competition and survival threats, proposing an earlier northward migration. Dry season EWE increases vegetation and water availability over northern SMME, prompting the late southward migration. Dry season EDE significantly reduces vegetation and water availability over northern SMME, suggesting an early southward migration towards regions with more vegetation and increased water availability. The SMME also experiences multiple EDE occurring in consecutive seasons, prolonging dry conditions that aggregate wildlife survival threats. Notably, two EDE prevailed consecutively from the 1993 dry season to the 1994 wet season, coupled with a population decline of wildebeest (1.2–0.9 million), buffalo (40–20 thousand), and lion (1.3–0.9 thousand). We also note a reversal from more EDE to EWE during the study period. Prevalent EWE can lessen wet and vegetative conditions distribution gradient, which is imperative for the functioning of the SMME migratory ecosystem. Our study unveiled hotspot areas of extremes-driven ecosystem changes for the sustainable SMME migratory functioning essential for framing meaningful conservation management policies under climate change.
Integrability and BRST invariance from BF topological theory
Authors: Restuccia A , Sotomayor A 
Published: October 2023

AbstractWe consider the Becchi, Rouet, Stora and Tyutin (BRST) invariant effective action of the non-abelian BF topological theory in two dimensions with gauge groupSl(2,R). By considering different gauge fixing conditions, the zero-curvature field equation gives rise to several well known integrable equations. We prove that each integrable equation together with the associated ghost field evolution equation, obtained from the BF theory, is a BRST invariant system with an infinite sequence of BRST invariant conserved quantities. We construct explicitly the systems and the BRST transformation laws for the Korteweg-de Vries (KdV) sequence (including the KdV, mKdV and CKdV equations) and Harry Dym integrable equation.
Concerning the direction of the Aharonov–Bohm deflection
Authors: Boyer Timothy H 
Published: October 2023

Abstract
The interaction of a solenoid with a passing charged particle can be treated within classical or quantum physics. If charged particles pass around both sides of a solenoid, there is an experimentally-observed Aharonov–Bohm deflection of the double-slit particle interference pattern between charges passing on opposite sides. Such a deflection can be obtained by a classical force calculation. Although the magnitude of the angular deflection agrees between the classical force calculation and the quantum topological theory, the direction of the predicted deflection is opposite. Here we point out the simple basis for the direction of the deflection based upon classical electrodynamics and based upon quantum theory. Also, we mention some deflection analogs, both the electrostatic deflection of the particle interference pattern and the optical analog of the classical calculation. The deflection direction involves an experimental question which is addressed rarely if ever. In the deflection direction, there is a direct experimental confrontation connected with the long-standing controversy involving the interpretation of the Aharonov–Bohm phase shift.
Doing it all: Effects of Family Responsibilities and Marital Relationship Quality on Mothers’ Ambulatory Blood Pressure
Authors: Graff Tyler C , Birmingham Wendy C , Wadsworth Lori L , Hung Man 
Published: October 2023

AbstractBackgroundThe shared provider responsibility between married couples does not translate to equally shared division of childcare (CC) and household labor. While some marriages contain highly positive aspects, marriages may also simultaneously contain both positive and negative aspects. The negativity in these relationships can negate the positivity and could potentially lead to the detriment of mothers’ health.PurposeWe examined mothers’ ambulatory blood pressure (ABP) associated with their marital relationship quality and perceived equity with her spouse on CC and household tasks.MethodsWe investigate these associations using a mixed multilevel model analysis on a sample of 224 mothers in heterosexual marriages, all of whom had children under the age of 18 years currently living in the home.ResultsMothers’ perception of equity in the division of CC responsibilities contributed to lower ABP. Additionally, mothers in supportive marital relationships (low negativity and high positivity) had lower ABP than those in ambivalent relationships (both high negativity and positivity). There was a crossover interaction such that the effect of relationship quality on ABP was moderated by the perception of equity in the division of CC. For mothers who report doing all the CC, they had lower ABP if they had a supportive marital relationship compared with mothers in ambivalent relationships. Whereas mothers who report more equity in CC and have a supportive relationship have higher ABP compared with mothers in ambivalent relationships.ConclusionsThis study has implications related to dynamics within marital relationships. These results demonstrate important relational influences on mothers’ ABP.
Belief as Status: Premodern Islamic Law, Duties, and the Martyr Conundrum
Authors: Zulfiqar Adnan A 
Published: October 2023

Abstract
The normative universe of the premodern Islamic legal tradition revolves around duties. These duties are determined by an individual’s status both as an autonomous entity and as part of the collective. The duties one owes and those that one is owed, are primarily constructed around belief. Belief, and its absence, function as the primary vehicles for affirming or denying an individual’s place within the moral community. In the jurists discourse on warfare, during the fifth ah/eleventh ce and sixth ah/twelfth ce centuries, we find an illustrative example of how belief dictates the duties that must be performed. Who is obligated to fight, who must be fought, and what obligations are owed in death all depend, though not exclusively, on the belief status of the relevant actors. In the process jurists constructed status hierarchies based on belief and, as in the case of martyrs, negotiated a delicate balance between preserving the sacredness of belief status and accounting for the pragmatic requirements of the battlefield.
Religious Endowments in Ancient India and the Institutionalization of Brahmin Caste Status
Authors: Lubin Timothy 
Published: October 2023

Abstract
Giving to worthy recipients has been meritorious public piety in India at least since the Mauryan empire. Most consequential were grants in perpetuity of land or capital as a ‘religious foundation’ for monks or Brahmins, conferred by means of a charter (śāsana). Grants to Brahmins typically created or supported an agrahāra, a residential enclave with attached farmland and villages, on terms analogous to those of grants to Buddhist or Jaina mendicants or monasteries. In these records (attested since the beginning of the Common Era), rulers cede their claims to certain normal obligations of subjects, such as tax revenue, compulsory labor, and billeting or provisions for officers of the state, and they often give the beneficiaries authority over internal legal administration. This article examines the implications of the fiscal and juridical autonomy conferred in such grants in providing state recognition and institutional support of Brahmins’ sacred status as a religious profession and a privileged caste.
Decoding functional cell–cell communication events by multi-view graph learning on spatial transcriptomics
Authors: Li Haochen , Ma Tianxing , Hao Minsheng , Guo Wenbo , Gu Jin , Zhang Xuegong , Wei Lei 
Published: October 2023

Abstract
Cell–cell communication events (CEs) are mediated by multiple ligand–receptor (LR) pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding FCE-target gene relations is: important for understanding the mechanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating LR pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multi-view network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting trained models. We applied HoloNet on three Visium datasets of breast cancer and liver cancer. The results detangled the multiple factors of FCEs by revealing how LR signals and cell types affect specific biological processes, and specified FCE-induced effects in each single cell. We conducted simulation experiments and showed that HoloNet is more reliable on LR prioritization in comparison with existing methods. HoloNet is a powerful tool to illustrate cell–cell communication landscapes and reveal vital FCEs that shape cellular phenotypes. HoloNet is available as a Python package at https://github.com/lhc17/HoloNet.
Daily Oral HIV Pre-exposure Prophylaxis Among Young Men Who Have Sex With Men in the United States: Cost-saving at Generic Drug Price
Authors: Amick Alyssa K , Eskibozkurt G Ege , Hosek Sybil G , Flanagan Clare F , Landovitz Raphael J , Jin Elena Y , Wilson Craig M , Freedberg Kenneth A , Weinstein Milton C , Kazemian Pooyan , Paltiel A David , Ciaranello Andrea L , Neilan Anne M 
Published: October 2023

Abstract

Background
Adherence and retention concerns raise questions about the effectiveness and cost-effectiveness of oral HIV pre-exposure prophylaxis (PrEP) in young men who have sex with men (YMSM).

Methods
Using an adolescent-focused simulation model, we compared annual HIV screening alone with tenofovir disoproxil fumarate/emtricitabine–based oral PrEP with every 3-month HIV screening in YMSM (aged 15–24) at increased risk of HIV. Data derived from published sources included: age-stratified HIV incidence/100 person-years (PY) on- or off-PrEP (0.6–10.1 or 0.4–6.4), PrEP retention at 6 years (28%), transmissions by HIV RNA level (0.0–78.4/100PY) and annual costs of antiretroviral therapy ($32 000–69 000), HIV care ($3100–34 600), and PrEP program/generic drug ($900/360). Outcomes included transmissions (percent of cohort infected), quality-adjusted life-years (QALYs), costs ($), and incremental cost-effectiveness ratios ($/QALY). We explored the sensitivity of findings to variation in HIV incidence and drug prices.

Results
Compared with annual screening alone, PrEP would increase QALYs (9.58 to 9.67), reduce new infections (37% to 30%), and decrease costs (by $5000) over 10 years. PrEP would remain cost-saving for HIV incidence off-PrEP ≥5.1/100PY or annual PrEP price ≤$1200. Over a lifetime horizon, PrEP would be cost-saving for HIV incidence off-PrEP ≥1.0/100PY, across all retention assumptions examined. PrEP would not be cost-effective at HIV incidence ≤0.1/100PY, regardless of drug price, due to programmatic costs.

Conclusions
In US YMSM at increased risk of HIV, generic oral PrEP and every-3-month screening would be cost-saving compared with annual screening alone, even with high discontinuation and low adherence, over a range of HIV incidences.
Febrile Phase Soluble Urokinase Plasminogen Activator Receptor and Olfactomedin 4 as Prognostic Biomarkers for Severe Dengue in Adults
Authors: Teo Andrew , Le Chau Thuy Tien , Tan Trevor , Chia Po Ying , Yeo Tsin Wen 
Published: October 2023

Abstract

Background
Dengue cases continue to rise and can overwhelm healthcare systems during outbreaks. In dengue, neutrophil mediators, soluble urokinase plasminogen activator receptor (suPAR) and olfactomedin 4, and mast cell mediators, chymase and tryptase, have not been measured longitudinally across the dengue phases. The utility of these proteins as prognostic biomarkers for severe dengue has also not been assessed in an older adult population.

Methods
We prospectively enrolled 99 adults with dengue—40 dengue fever, 46 dengue with warning signs and 13 severe dengue, along with 30 controls. Plasma levels of suPAR, olfactomedin 4, chymase and tryptase were measured at the febrile, critical and recovery phases in dengue patients.

Results
The suPAR levels were significantly elevated in severe dengue compared to the other dengue severities and controls in the febrile (P &lt; .001), critical (P &lt; .001), and recovery (P = .005) phases. In the febrile phase, suPAR was a prognostic biomarker of severe dengue, with an AUROC of 0.82. Using a cutoff derived from Youden's index (5.4 ng/mL) and an estimated prevalence of severe dengue (16.5%) in our healthcare institution, the sensitivity was 71.4% with a specificity of 87.9% in the febrile phase, and the positive and negative predictive values were 54.7% and 95.8%, respectively. Olfactomedin 4 was elevated in dengue patients but not in proportion to disease severity in the febrile phase (P = .04) There were no significant differences in chymase and tryptase levels between dengue patients and controls.

Conclusions
In adult dengue, suPAR may be a reliable prognostic biomarker for severe dengue in the febrile phase.
Forest canopy mortality during the 2018-2020 summer drought years in Central Europe: The application of a deep learning approach on aerial images across Luxembourg
Authors: Schwarz Selina , Werner Christian , Fassnacht Fabian Ewald , Ruehr Nadine K 
Published: October 2023

Abstract
Efficient monitoring of tree canopy mortality requires data that cover large areas and capture changes over time while being precise enough to detect changes at the canopy level. In the development of automated approaches, aerial images represent an under-exploited scale between high-resolution drone images and satellite data. Our aim herein was to use a deep learning model to automatically detect canopy mortality from high-resolution aerial images after severe drought events in the summers 2018–2020 in Luxembourg. We analysed canopy mortality for the years 2017–2020 using the EfficientUNet++, a state-of-the-art convolutional neural network. Training data were acquired for the years 2017 and 2019 only, in order to test the robustness of the model for years with no reference data. We found a severe increase in canopy mortality from 0.64 km2 in 2017 to 7.49 km2 in 2020, with conifers being affected at a much higher rate than broadleaf trees. The model was able to classify canopy mortality with an F1-score of 66%–71% and we found that for years without training data, we were able to transfer the model trained on other years to predict canopy mortality, if illumination conditions did not deviate severely. We conclude that aerial images hold much potential for automated regular monitoring of canopy mortality over large areas at canopy level when analysed with deep learning approaches. We consider the suggested approach a cost-efficient and -effective alternative to drone and field-based sampling.