bluuebunny/crossref_metadata_2025_split huggingface dataset:
Demonstrating Large Low Noise Transition Edge Sensor Arrays for Future FIR Space Missions
Authors: Staguhn Johannes , Sharp Elmer , Brown Ari , Devasia Archana , Doriese William , Durkin Malcolm , Fixsen Dale , Staggs Suzanne , Petit Felipe Colazo , Denis Kevin , DiPirro Mike , Duff Shannon , Glenn Jason , Harrop Bert , Maher Stephen , Mikula Vilem Mikula Vilem , Nagler Peter , Wollack Edward 
Published: November 2023

Abstract
The Astrophysics 2020 Decadal Report recommended a line of Probe missions with far-infrared imaging or spectroscopy capabilities. The achievable sensitivity of these FIR missions will be enabled by advanced cryogenic detector technologies, potentially resulting in up to three orders of magnitude improvement in sensitivity and mapping speeds up to more than a million times of those achieved so far with past missions.
We have obtained NASA funding to build and demonstrate Transition Edge Sensor (TES) based kilopixel arrays with the properties that match the requirements for cryogenic far-infrared space missions: the arrays are very closely tileable in one direction and with a moderate gap in the other direction. This array architecture can meet the sampling- and pixel number requirement of a few 104 pixels. Many details of the architecture have already been demonstrated individually, and the detector board will be optimized for the use of the latest cryogenic NIST 2-D time domain SQUID readout multiplexers with a high density fanout scheme. Additionally, we will use flex-lines that are very similar to those developed at Princeton University for the ACT project. This method allows virtually unlimited tileability of the detector arrays and thus a compact detector/readout design for future FIR instrumentation requiring large pixel counts. We already have a pixel design which, if implemented with TES operating at less than 100mK, will meet the continuum sensitivity requirements for a cryogenic space mission. Furthermore, our array design will be compatible with lower noise TES designs for spectroscopy that already have been demonstrated.
An Integrated Federated Learning with CRSO of Attention-based LSTM Framework for Efficient IoT DataStream Prediction
Authors: El-Saied Asma M. 
Published: November 2023

Abstract
Real-time data stream processing presents a significant challenge in the rapidly changing Internet of Things (IoT) environment. Traditional centralized approaches face hurdles in handling the high velocity and volume of IoT data, especially in real-time scenarios. In order to improve IoT DataStream prediction performance, this paper introduces a novel framework that combines federated learning (FL) with a competitive random search optimizer (CRSO) of Long Short-Term Memory (LSTM) models based on attention. The proposed integration leverages distributed intelligence while employing competitive optimization for fine-tuning. The proposed framework not only addresses privacy and scalability concerns but also optimizes the model for precise IoT DataStream predictions. This federated approach empowers the system to derive insights from a spectrum of IoT data sources while adhering to stringent privacy standards. Experimental validation on a range of authentic IoT datasets underscores the framework's exceptional performance, further emphasizing its potential as a transformational asset in the realm of IoT DataStream prediction. Beyond predictive accuracy, the framework serves as a robust solution for privacy-conscious IoT applications, where data security remains paramount. Furthermore, its scalability and adaptability solidify its role as a crucial tool in dynamic IoT environments.
Simultaneous estimation and variable selection for a non-crossing multiple quantile regression using deep neural networks
Authors: Shin Jungmin , Gwak Seunghyun , Shin Seung Jun , Bang Sungwan 
Published: November 2023

Abstract
In this paper, we present the DNN-NMQR estimator, an approach that utilizes a deep neural network structure to solve multiple quantile regression problems. When estimating multiple quantiles, our approach leverages the structural characteristics of DNN to enhance estimation results by encouraging shared learning across different quantiles through DNN-NMQR. Also, this method effectively addresses quantile crossing issues through the penalization method. To refine our methodology, we introduce a convolution-type quadratic smoothing function, ensuring that the objective function remains differentiable throughout. Furthermore , we provide a brief discussion on the convergence analysis of DNN-NMQR, drawing on the concept of the neural tangent kernel. For a high-dimensional case, we propose the (A)GDNN-NMQR estimator, which applies group-wise L1-type regularization methods and enjoys the advantages of quantile estimation and variable selection simultaneously. We extensively validate all of our proposed methods through numerical experiments and real data analysis.
Optimal Tax Administration under Fake Residency and Tax Avoidance
Authors: Esteller-Moré Alejandro , Galmarini Umberto 
Published: November 2023

Abstract
In a two-country model, the citizens of a ‘big home country’ can either fictitiously
move residence to a ‘small foreign country’ where residence-based taxes are lower
(external avoidance), or under-report the tax base at home (internal avoidance).
The home and the foreign government compete on tax rates, with the former
also setting two types of administration policies, each one targeting one type of
tax avoidance. Although tax revenue is maximized by employing both types of
administration policies, the optimal policy faces a tradeoff in terms of fiscal outcomes:
in fiscal environments with large intrinsic opportunities of tax avoidance,
internal avoidance increases and external avoidance decreases, while the reverse
occurs in environments with small opportunities.
Light channel signal analysis with the lithium molybdate crystal R\&amp;D detectors for AMoRE-II experiments
Authors: Sharma B. , Kim S.C. , Kim W.T. , Bhandari B. , Mailyan B. , Kim M.B. , Kim Y.D. , Kim Y.H. , Lee H.J. , Lee M.H. 
Published: November 2023

Abstract

This paper presents a comparative study of various light detectors (LDs) developed for different phases of the AMoRE neutrinoless double beta decay experiment. We analyze the performance of these detectors in terms of characteristics such as time response, light collection, and energy resolution. Our primary focus is on evaluating the performance of the AMoRE-II light detector (LD), which is integral to the forthcoming AMoRE-II experiment. It is found that AMoRE-II type LDs outperform other previous light detector types. The best-performing LD exhibits FWHM energy resolution of 99 eV, 185 eV, 182 eV, and 493 eV for baseline and 55Fe X-ray energies of 5.9 keV, 6.5 keV, and 17.5 keV molybdenum X-ray, respectively. We adopted a convolution method to estimate the energy of the scintillation signals from 2.615 MeV gamma rays fully absorbed in a lithium molybdate crystal. The measured energy of scintillation light with AMoRE-II type LDs falls in the range of 2.1--2.5 keV, which corresponds to 0.80--0.96 keV/MeV. This measured energy is approximately 14–39% higher than that measured with previous LD types for the experiments.
The impact of restrictive blood transfusion on the safety of patients with esophageal varices after endoscopic variceal ligation
Authors: Chen Yufeng , Ming Wen , Chen Jingjing , Wang Xi , He Guobin 
Published: November 2023

Abstract

Background:To study the effect of restrictive blood transfusion on the safety of early rebleeding after endoscopic variceal ligation(EVL) in patients with liver cirrhosis.Methods:The patients with cirrhosis and esophageal varices who underwent endoscopic variceal ligation at the Affiliated Hospital of North Sichuan Medical College from September 2021 to March 2023 were collected. The clinical data such as serum albumin level, hemoglobin level, liver function classification and the incidence of early rebleeding were recorded. The patients were divided into restrictive red blood cell transfusion group and non transfusion group according to whether there was red blood cell transfusion during hospitalization. The influence of restrictive transfusion and non transfusion group on the postoperative safety of endoscopic variceal ligation was observed.Results:A total of 246 cirrhotic patients were included in the analysis. There were significant differences in hemoglobin level, liver function classification, early rebleeding rate, hospitalization days, and hospitalization expenses between the restrictive transfusion and the non transfusion groups. The early rebleeding rate was significantly different between the groups with different hemoglobin levels after operation. Multivariate logistic analysis showed that postoperative hemoglobin level(OR=0.964, 95%CI: 0.956–0.971;P<0.001) and preoperative albumin level(OR=0.910, 95%CI: 0.892–0.929;P<0.001) were independent influencing factors of early rebleeding.Conclusions:The higher the hemoglobin level of cirrhotic patients with esophageal varices after endoscopic variceal ligation, the lower the incidence of early rebleeding, and restrictive blood transfusion appeared to increase the risk of early rebleeding, which needs be further confirmed in future research.
Multibody Models Generated from Natural Language
Authors: Gerstmayr Johannes , Manzl Peter , Pieber Michael 
Published: November 2023

Abstract
Computational models are conventionally created with input data, script files, programming interfaces, or graphical user interfaces. This paper explores the potential of expanding model generation, with a focus on multibody system dynamics. In particular, we investigate the ability of Large Language Models (LLMs), to generate models from natural language. Our experimental findings indicate that LLMs, some of them having been trained on our multibody code Exudyn, surpass the mere replication of existing code examples. The results demonstrate that LLMs have a basic understanding of kinematics and dynamics, and that they can transfer this knowledge into a programming interface. Although our tests reveal that complex cases regularly result in programming or modeling errors, we found that LLMs can successfully generate correct multibody simulation models from natural language descriptions for simpler cases, often on the first attempt (zero-shot). Next to a basic introduction into the functionality of LLMs, our Python code, and the test setups, we provide a summarized evaluation for a series of examples with increasing complexity. We start with a single mass oscillator, both in SciPy as well as in Exudyn, and include varied inputs and statistical analysis to highlight the robustness of our approach. Hereafter, systems with mass points, constraints, and rigid bodies are evaluated. In particular, we show that in-context learning can levitate basic knowledge of a multibody code into a zero-shot correct output.
Blooming and Pruning: Learning from Mistakes with Memristive Synapses
Authors: Nikiruy Kristina , Perez Eduardo , Baroni Andrea , Reddy Keerthi Dorai Swamy , Pechmann Stefan , Wenger Christian , Ziegler Martin 
Published: November 2023

Abstract
Blooming and pruning is one of the most important developmental mechanisms of the biological brain in the first years of life, enabling it to adapt its network structure to the demands of the environment. The mechanism is thought to be fundamental for the development of cognitive skills. Inspired by this, Chialvo and Bak proposed in 1999 a learning scheme that learns from mistakes by eliminating from the initial surplus of synaptic connections those that lead to an undesirable outcome. Here, this idea is implemented in a neuromorphic circuit scheme using CMOS integrated HfO2-based memristive devices. The implemented two-layer neural network learns in a self-organized manner without positive reinforcement and exploits the inherent variability of the memristive devices. A combined experimental and simulation-based parameter study is presented to find the relevant system and device parameters leading to a compact and robust memristive neuromorphic circuit that can handle association tasks.
Spatiotemporal projections of extreme Temperatures over Algeria using CMIP6-MME global climate models outputs
Authors: ABED Salah SAHABI , Selmane Ahmed Nour-EL-Islam 
Published: November 2023

Abstract
Algeria is vulnerable to climate extremes due to its large surface, growing population, and diverse valuable and fragile ecosystems. We assess in this paper the spatiotemporal projections of extreme temperatures over Algeria derived from the adjusted multi-model ensemble mean (MME) data derived from eleven daily historical simulations of CMIP6-GCMs models that participated in IPCC Sixth Assessment Report (AR6), considered the most authoritative source on climate change. We assess the projected spatial patterns of twelve extreme temperature indices defined by the Expert Team on Climate Change Detection and Indices. The evolution of the projected changes is examined for two future time periods: the mid-future 2041–2070 and the far future 2071–2100, relative to the baseline period 1985–2014, under three Shared Socio-economic Pathways (SSP) scenarios: low emission SSP1-2.6; medium emission SSP2-4.5 and high emission scenario (SSP5-8.5). The selected climate indices reflect the intensity (TXx, TNx, TXn, TNn and DTR), frequency (TX90p and TN10p) and duration (WSDI, SU, CSDI, TR, and FD) of the extreme thermal events. The MME Projections show a heightened warming. Future Climate features depict a continuous increase in the occurrence of hot days and nights and an amplification of the intensity of the extreme temperature and an extension of the heat wave duration period. These positive changes are likely to be more important by the end of the 21st century in the southern region than in the northern one and under SSP5-8.5 than in the remaining scenarios, with the exception of the occurrence of summer days (SU), where the northern region is projected to experience relatively more summer days as compared to the southern region. A stabilization of the upsurge trend is remarkably observed for most indices under SSP1-2.6 starting from the 2050s. In the last decades, Algeria has been experiencing recurrently the impacts of extreme weather leading to irreversible impacts. The projected extreme climate events in Algeria underscore the urgency of climate change mitigation and adaptation measures. The future changes depicted in this study should help to assess the distribution of the impacts across different regions of Algeria in order to enhance resilience, establish the appropriate adaptation responses and improve disaster preparedness.
Reassessment of casual association between body mass index and site-specific solid cancers: A comprehensive Mendelian randomization study
Authors: Lai Jianxiong , Xu Yuanhui , Li Jian 
Published: November 2023

Abstract
Purpose
Previous Mendelian randomization (MR) studies on association between body mass index (BMI) and cancer only focused on several common cancers, and the genetic instruments varied, making the effect of BMI on other cancers unclear and direct comparison across all cancer types difficult. Our comprehensive MR aims to reinforce the established evidence of the association.
Methods
We conducted a unified MR analysis to reassess the association between BMI and 19 site-specific solid cancers. Genetic instruments for BMI were extracted from genome-wide association studies (GWAS) of 806,834 European individuals and 86,757 East Asian individuals, respectively. The associations of genetic instruments with 19 site-specific solid cancer (sub)types extracted from the FinnGen study, the Biobank Japan (BBJ) project, and international consortia were examined by using various MR methods.
Results
For lung, endometrial and breast cancers in the FinnGen study, estimation of the MR analysis aids the triangulation of the positive or inverse association between genetically predicted BMI and these (sub)types. In several large consortia in the European population, our results strengthen confidence in previously established positive findings for lung, ovarian, endometrial and breast cancer and null findings for prostate cancer. In the BBJ project, no causal association was found between BMI and cancers, although a possible increased risk for endometrial cancer may exist.
Conclusion
Our comprehensive MR estimates reinforce the causal role of BMI in some solid cancers in the European population but cannot rule out a possible causal role in some other cancer (sub)types and in other populations.
A piezoelectric sensor with high accuracy and reduced measurement error
Authors: Ghemari Zine , Belkhiri Salah , Saad Salah 
Published: November 2023

Abstract
In this work, the main focus is on studying the effects of piezoelectric materials and exploring the functionality of piezoelectric sensors. The physical behavior of the sensor is thoroughly examined and a mathematical formula relating the accuracy of the sensor to relative movement or vibratory displacement is derived. The developed model is verified through simulations and experimental tests. By carefully selecting the appropriate damping rate, it is possible to enhance the parameters of the piezoelectric sensor and advance the technique of vibratory analysis. Overall, this research aims to enhance our understanding of piezoelectric materials and sensors, and how they can be effectively utilized in various applications involving vibratory analysis. The findings from this study can contribute to better design and implementation of piezoelectric sensors, improving their accuracy and effectiveness in capturing and analysing vibratory movements.
End-to-End Modeling of the TDM Readout System for CMB-S4
Authors: Goldfinger David C. , Ahmed Zeeshan , Barron Darcy R. , Doriese W. Bertrand , Durkin Malcolm , Filippini Jeffery P. , Haller Gunther , Henderson Shawn W. , Herbst Ryan , Hubmayr Johannes , Irwin Kent , Reese Benjamin , Sapozhnikov Leonid , Thompson Keith L. , Ullom Joel , Vissers Michael R. 
Published: November 2023

Abstract

The CMB-S4 experiment is developing next-generation ground-based microwave telescopes to observe the Cosmic Microwave Background with unprecedented sensitivity. This will require an order of magnitude increase in the 100 mK detector count, which in turn increases the demands on the readout system. The CMB-S4 readout will use time division multiplexing (TDM), taking advantage of faster switches and amplifiers in order to achieve an increased multiplexing factor. To facilitate the design of the new readout system, we have developed a model that predicts the bandwidth and noise performance of this circuity and its interconnections. This is then used to set requirements on individual components in order to meet the performance necessary for the full system. We present an overview of this model and compare the model results to the performance of both legacy and prototype readout hardware.
The effect of psychoactive substances used on clinical outcomes in injured drivers referred to emergency medicine; case-control study
Authors: Tavakoli Nader , Mousavi Zahra , Amanollahi Alireza , Babeveynezhad Tannaz 
Published: November 2023

Abstract
Objective
The use of psychoactive substances increases the risk of accidents. This study evaluated the relationship between the type of psychoactive substances among traffic injured admitted to the medical center.
Methods
Injured drivers (100 used drugs), (260 control group), who were transferred to 7-Tir Hospital from April 2021 to March 2022 were studied. The information related to the accident scene, personal characteristics, and the substance used was collected from the police and the medical center documents. We used multiple logistic regression to find the important factor in outcomes.
Results
The mean age of the case group (37.49 ± 13.61) compared to the control group (34.18 ± 14.05) was significant (p = 0.044). The most common substances in the case group were opioids which had the highest mean age (41.90 ± 13.541). Injured who used sedatives had higher signs of head trauma than the others. Also, being guilty had a remarkable difference in the groups (94.6 vs 62.4 p = < 0.001). Motorcyclist drivers were 185(65%) responsible for the accident, in addition, 69(69%) were in the case group. Head trauma, type of accident, and level of triage had a significant effect on the death of the injured.
Conclusion
Using sedatives causes increased head trauma. Driving under the effect of psychoactive drugs is more common among motorcycle drivers, and a large percentage of them are guilty of accidents.
Risk factors of renal survival in patients with microscopic polyangiitis and severe renal injury in 6 months
Authors: Wang Xiaoying , Hao Weiwei , Dong Fang , Liu Rui , Zhang Lie , Li Wei , Liu Shengyun 
Published: November 2023

Abstract
Objective.
Patients with life-threatening microscopic polyangiitis (MPA) with kidney involvement have poor prognosis. This study aimed to identify the risk factors of progressing to end-stage renal disease (ESRD) in 6 months for patients with MPA and kidney involvement.
Methods.
Inpatients with MPA and kidney involvement and at least one follow-up in 6 months after therapy were included and divided to the ESRD or non-ESRD groups according to outcome at 6 months after therapy. Baseline clinical characteristics, immunosuppressive therapies and clinical and biological data prospectively collected during follow-up visits were analysed.
Results.
Patients were divided into the ESRD (N = 73) and non-ESRD groups (N = 89) according to outcomes. More female patients were included in the ESRD group than in the non-ESRD group (64% vs 48%, p = 0.041). Patients in the ESRD group showed decreased cell count in blood routine examination, elevated levels of proteinuria over a 24 h period, lowered C3 levels, decreased lymphocyte counts (especially T and CD4 + lymphocytes), higher rates of cardiovascular and nerve system involvement according to BVAS value criteria and lower frequency of glucocorticoid (GC) or cyclophosphamide (CTX) treatment than those in the non-ESRD group (all p < 0.05). After adjustment for potential confounders, non-ESRD survival was shown to be negatively associated with cardiovascular involvement (HR 0.563, 95% CI 0.323 to 0.981, p = 0.043) and positively associated with GCs (HR 2.041, 95% CI 1.079 to 3.861, p = 0.028) and CTX treatment (HR 1.913, 95% CI 1.027 to 3.565, p = 0.041).
Conclusions
Amongst patients with MPA and active kidney involvement, GCs and CTX therapy were protective factors of progressing to ESRD within 6 months, whereas cardiovascular involvement was an aggravating factor.
Transferability of a European-derived Alzheimer’s Disease Genetic Risk Score across Multi-Ancestry Populations.
Authors: Lambert Jean-Charles 
Published: November 2023

Abstract
We built a genetic risk score (GRS) from the most complete landscape of the Alzheimer disease (AD) genetics. We extended its analysis in 16 European countries and observed a consistent association of this GRS with AD risk, age at onset and cerebrospinal fluid (CSF) AD biomarker levels regardless of the Apolipoprotein E (APOE) genotype. This GRS was also associated with AD risk (independently of APOE) with a decreasing order of magnitude in those with an European-American, North-African, East-Asian, Latin-American, African-American sub-Saharan African and Indian background respectively. No association of the GRS to AD was seen in sub-Saharan African and Indian populations. This GRS captures information specific to AD as its association decreases as the diagnosis broadens. In conclusion, a simple GRS captures shared genetic information specific to AD between multi-ancestry populations. However, more population diversity is needed to better understand the AD genetic complexity across populations.