bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determining the factors impacting the quality of life among the general population in coastal communities in central Vietnam
Authors: Nguyen Gia Thanh , Tran Thang Binh , Le Duong Dinh , Nguyen Tu Minh , Van Nguyen Hiep , Ho Phuong Uyen , Van Tran Son , Thuy Linh Nguyen Hoang , Tran Trung Dinh , Phan Long Thanh , Anh Thu Dang Thi , Watanabe Toru 
Published: March 2024

AbstractPeople living in coastal areas are frequently affected by natural disasters, such as floods and storms. This study aimed to assess the quality of life (QoL) of people living in disadvantaged coastal communes (subdivision of Vietnam) and identify their associated factors by using the World Health Organization’s quality of life instrument (WHOQOL-BREF). To achieve this, a cross-sectional descriptive study was conducted on 595 individuals aged 18 years and above living in the coastal communes in Thua Thien Hue province, Vietnam, from October 2022 to February 2023. The results showed that the mean overall QoL (mean ± SD) was 61.1 ± 10.8. Among the four domains of QoL, the physical health (57.2 ± 12.3) domain had a lower score than the psychological health (61.9 ± 13.0), social relations (63.4 ± 13.4), and environment (61.9 ± 13.3) domains. The QoL score of the domains for participants affected by flooding was significantly lower than that of those not affected, except for social relations. Multivariable logistic regression showed that subjects with not good QoL had the educational background with no formal education (Odds ratio (OR) = 2.63, 95% CI 1.19–5.83), fairly poor/poor households (OR = 2.75, 95% CI 1.48–5.12), suffered Musculoskeletal diseases (OR = 1.61, 95% CI 1.02–2.56), unsatisfaction with health status (OR = 5.27, 95% CI 2.44–11.37), family conflicts (OR = 4.51, 95%CI 2.10–9.69), and low levels of social support (OR = 2.62; 95% CI 1.14–6.02). The analysis also revealed that workers (OR = 0.17, 95% CI 0.04–0.66) had a better QoL than farmer-fisherman. QoL in disadvantaged coastal communes was low, with the lowest scores in the physical health domain. Based on the socioeconomic factors associated with not good QoL identified here, it is recommended that local authorities take more appropriate and practical measures to increase support, including measures for all aspects of physical health, psychological health, social relations, and the living environment, especially for people affected by floods.
How suitable are equity release mortgages as investments for pension funds?
Authors: Buckner Dean , Dowd Kevin , Hulley Hardy 
Published: March 2024

AbstractThis article examines the claim that equity release mortgages, the U.K. equivalent of reverse mortgages in the U.S., are suitable investments for pension funds. We present valuation, stress test and scenario analysis results that suggest that equity release mortgages are unsuitable for pension funds because: (i) they bear returns that are typically below the risk-free rate; (ii) they are not hedges for annuity books, let alone good hedges; and (iii) they are heavily exposed to house price risk, which annuity books are not. Our results suggest that equity release mortgages meet none of these criteria to be suitable for pension funds and are almost entirely dominated by risk-free government bonds. We offer an explanation for why investors appear to be unaware of the low returns on equity release mortgages.
Grating-assisted hot-electron photodetectors for S- and C-band telecommunication
Authors: Shao Weijia , Cui Weihao , Xin Yixiao , Hu Junhui , Li Xiaofeng 
Published: March 2024

Abstract
Although outstanding detectivities, InGaAs photodetectors for optic fiber communication are often costly due to the need for cooling. Therefore, cryogen-free and cost-effective alternatives working in telecommunication bands are highly desired. Here, we present a design of hot-electron photodetectors (HE PDs) with attributes of room-temperature operation and strong optical absorption over S and C bands (from 1460 to 1565 nm). The designed HE PD consists of a metal–semiconductor–metal hot-electron stack integrated with a front grating. Optical simulations reveal that mode hybridizations between Fabry–Pérot resonance and grating-induced surface plasmon excitation lead to high absorption efficiencies (≥0.9) covering S and C bands. Probability-based electrical calculations clarify that device responsivity is mainly determined by working wavelength on the premise of broadband strong absorption. Moreover, through comparison studies between the grating-assisted HE PD and purely planar microcavity system that serves as a reference, we highlight the design superiorities in average absorption and average responsivity with optimized values of 0.97 and 0.73 mA W−1, respectively. The upgraded peformances of the designed device are promising for efficient photoelectric conversion in optic fiber communication systems.
Synthesis of silicon carbide in a matrix of graphite-like carbon prepared via carbonization of rigid-rod polyimide Langmuir–Blodgett films on silicon substrate
Authors: Goloudina Svetlana , Pasyuta Vyacheslav , Kirilenko Demid , Smirnov Aleksandr , Kasatkin Igor , Zhizhin Evgeny , Koroleva Aleksandra , Sevostiyanov Evgeny , Panov Mikhail , Trushlyakova Valentina , Gofman Iosif , Svetlichnyi Valentin , Luchinin Viktor 
Published: March 2024

Abstract
Silicon carbide (SiC) is a wide-band gap semiconductor that exceeds other semiconducting materials (except diamond) in electrical, mechanical, chemical, and radiation stability. In this paper, we report a novel approach to fabrication of SiC nano films on a Si substrate, which is based on the endotaxial growth of a SiC crystalline phase in a graphite-like carbon (GLC) matrix. GLC films were formed by carbonization of rigid rod polyimide (PI) Langmuir–Blodgett (LB) films on a Si substrate at 1000 °C in vacuum. After rapid thermal annealing of GLC films at 1100 °C and 1200 °C, new types of heterostructures SiC(10 nm)/GLC(20 nm)/Si(111) and SiC(20 nm)/GLC(15 nm)/SiC(10 nm)/Si(111) were obtained. The SiC top layer was formed due to the Si-containing gas phase present above the surface of GLC film. An advantage of the proposed method of endotaxy is that the SiC crystalline phase is formed within the volume of the GLC film of a thickness predetermined by using PI LB films with different numbers of monolayers for carbonization. This approach allows growing SiC layers close to the 2D state, which is promising for optoelectronics, photovoltaics, spintronics.
Plasma enhanced atomic layer deposition of silicon nitride using magnetized very high frequency plasma
Authors: Ji You Jin , Kim Hae In , Kang Ji Eun , Choi Seung Yup , Kim Ki Hyun , Kim Doo San , Ellingboe A R , Kim Hye Min , Yeom Geun Young , Kim Dong Woo 
Published: March 2024

Abstract
To obtain high-quality SiN
x
films applicable to an extensive range of processes, such as gate spacers in fin field-effect transistors (FinFETs), the self-aligned quadruple patterning process, etc, a study of plasma with higher plasma density and lower plasma damage is crucial in addition to study on novel precursors for SiN
x
plasma-enhanced atomic layer deposition (PEALD) processes. In this study, a novel magnetized PEALD process was developed for depositing high-quality SiN
x
films using di(isopropylamino)silane (DIPAS) and magnetized N2 plasma at a low substrate temperature of 200 °C. The properties of the deposited SiN
x
films were analyzed and compared with those obtained by the PEALD process using a non-magnetized N2 plasma source under the same conditions. The PEALD SiN
x
film, produced using an external magnetic field (ranging from 0 to 100 G) during the plasma exposure step, exhibited a higher growth rate (∼1 Å/cycle) due to the increased plasma density. Additionally, it showed lower surface roughness, higher film density, and enhanced wet etch resistance compared to films deposited using the PEALD process with non-magnetized plasmas. This improvement can be attributed to the higher ion flux and lower ion energy of the magnetized plasma. The electrical characteristics, such as interface trap density and breakdown voltage, were also enhanced when the magnetized plasma was used for the PEALD process. Furthermore, when SiN
x
films were deposited on high-aspect-ratio (30:1) trench patterns using the magnetized PEALD process, an improved step coverage of over 98% was achieved, in contrast to the conformality of SiN
x
deposited using non-magnetized plasma. This enhancement is possibly a result of deeper radical penetration enabled by the magnetized plasma.
Probe chip nanofabrication enabled reverse tip sample scanning probe microscopy concept and measurements
Authors: Kim Hyeon-Su , Peric Nemanja , Minj Albert , Wouters Lennaert , Serron Jill , Mancini Chiara , Koylan Serkan , Sergeant Stefanie , Hantschel Thomas 
Published: March 2024

Abstract
We introduce a new scanning probe microscopy (SPM) concept called reverse tip sample scanning probe microscopy (RTS SPM), where the tip and sample positions are reversed as compared to traditional SPM. The main benefit of RTS SPM over the standard SPM configuration is that it allows for simple and fast tip changes. This overcomes two major limitations of SPM which are slow data acquisition and a strong dependency of the data on the tip condition. A probe chip with thousands of sharp integrated tips is the basis of our concept. We have developed a nanofabrication protocol for Si based probe chips and their functionalization with metal and diamond coatings, evaluated our probe chips for various RTS SPM applications (multi-tip imaging, SPM tomography, and correlative SPM), and showed the high potential of the RTS SPM concept.
CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues
Authors: Vathrakokoili Pournara Anna , Miao Zhichao , Beker Ozgur Yilimaz , Nolte Nadja , Brazma Alvis , Papatheodorou Irene 
Published: March 2024

Abstract

Motivation
Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods.

Results
In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods.

Availability and implementation
https://github.com/Papatheodorou-Group/CATD_snakemake.
Functional traits of non-vascular epiphytes influence fine scale thermal heterogeneity under contrasting microclimates: insights from sub-Mediterranean forests
Authors: Canali Giulia , Di Nuzzo Luca , Benesperi Renato , Nascimbene Juri , Giordani Paolo 
Published: March 2024

Abstract
Lichens and bryophytes contribute to regulating the forest microclimate and support ecosystem functions. Exploring the thermal heterogeneity at a trunk-level may help elucidate the effect of thermoregulation of epiphytes. We hypothesized that (i) the thermal patterns of epiphytic communities depend on the microclimatic conditions of the surrounding atmosphere and (ii) the thermal heterogeneity at a trunk-level may in turn depend on functional traits of epiphytic communities, such as thallus colour and growth form. We carried out two measurement sessions under contrasting microclimatic conditions (wet vs. dry). Using a thermal camera, we acquired infra-red (IR) images of 50 trees during the same time period under the contrasting wet and dry conditions. Results showed significant differences in thermal characteristics of the trees when contrasting wet with dry conditions and that colour and growth form were significantly associated with changes in thermal patterns at the trunk-level. The study highlights the importance of understanding the thermoregulatory processes of epiphytic communities.
Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer’s disease
Authors: Wang Yaxuan , Li Qian , Yao Li , He Ning , Tang Yingying , Chen Lizhou , Long Fenghua , Chen Yufei , Kemp Graham J , Lui Su , Li Fei 
Published: March 2024

Abstract
Alzheimer’s disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.
Fragile X cortex is characterized by decreased parvalbumin-expressing interneurons
Authors: Juarez Pablo , Salcedo-Arellano Maria Jimena , Dufour Brett , Martinez-Cerdeño Veronica 
Published: March 2024

Abstract
Fragile X syndrome is a genetic neurodevelopmental disorder caused by a mutation of the fragile X messenger ribonucleoprotein 1 (FMR1) gene in the X chromosome. Many fragile X syndrome cases present with autism spectrum disorder and fragile X syndrome cases account for up to 5% of all autism spectrum disorder cases. The cellular composition of the fragile X syndrome cortex is not well known. We evaluated alterations in the number of Calbindin, Calretinin, and Parvalbumin expressing interneurons across 5 different cortical areas, medial prefrontal cortex (BA46), primary somatosensory cortex (BA3), primary motor cortex (BA4), superior temporal cortex (BA22), and anterior cingulate cortex (BA24) of fragile X syndrome and neurotypical brains. Compared with neurotypical cases, fragile X syndrome brains displayed a significant reduction in the number of PV+ interneurons in all areas and of CR+ interneurons in BA22 and BA3. The number of CB+ interneurons did not differ. These findings are the first to demonstrate that fragile X syndrome brains are characterized by cortical wide PV+ interneuron deficits across multiple cortical areas. These add to the idea that deficits in PV+ interneurons could disrupt the cortical balance and promote clinical deficits in fragile X syndrome patients and help to develop novel therapies for neurodevelopmental disorders like fragile X syndrome and autism spectrum disorder.
ELSM: Evidence-Based Line Segment Merging
Authors: Hamid Naila , Khan Nazar , Akram Arbish 
Published: March 2024

Abstract
Existing line segment detectors break perceptually contiguous linear structures into multiple line segments. This can be offset by re-merging the segments, but existing merging algorithms over-merge and produce globally incorrect segments. Geometric cues are necessary but not sufficient for deciding whether to merge two segments or not. By restricting the result of any merging decision to have underlying image support, we reduce over-merging and globally incorrect segments. We propose a novel measure for evaluating merged segments based on line segment Hausdorff distance. On images from YorkUrbanDB, we show that our algorithm improves both qualitative and quantitative results obtained from four existing line segment detection methods and is better than two existing line segment merging methods. Our method does not suffer from inconsistent results produced by four recent deep learning-based models. The method is easily customisable to work for line drawings such as hand-drawn maps to obtain vectorized representations.
Software Failure Prediction Based On Program State and First-Error Characteristics
Authors: Zhu Lina , Zhang Zuochang 
Published: March 2024

Abstract
Evaluating program reliability against software faults involves the work of analyzing program failure against software faults as behavior on failures is fundamental for assessing reliability. Similar failure behavior reflects similar reliability assessment against software faults of same time–space distribution. Since program failure is determined by fault manifestations, working on similarities on fault manifestations helps figuring out failures in similarity as well. In this paper, we propose a novel method to characterize program behavior by defining fine-grained runtime states at assembly-level of code, aiming to capture the very first abnormal manifestation—first-error—after software fault being activated during program run. Failure prediction model and measurement is presented based on similarities reflected by the runtime behaviors obtained. Fault injection experiments are conducted to verify the prediction measurement by utilizing software faults of Orthogonal Defect Classification to inject and MiBench programs to perform. Over 15 000+ times of fault injection by considering type and location of fault were conducted into each program in order to quantify and analyze the sensitivity on first-error and similarity on failure accordingly. The results show that programs having particular structural features (e.g. massive operations with regards to calculations, nested function-calls, case structures and loop structures, etc.) are well characterized toward first-error behaviors by extracting fine-grained states. Similarities on first-error sensitivity can be represented better for these programs as well. Same trend is seen on failure behavior and its prediction measurement.
SDTA: Secure Decentralized Trading Alliance for Electronic Medical Data
Authors: Zhang Xi , Su Ye , Qin Jing , Sun Jiameng 
Published: March 2024

Abstract
Massive medical data are indispensable for training diagnostic models to provide high-quality health monitoring services. The methods for sharing data in existing works involve securely and essentially copying data but often overlook the integration and efficiency of data storage, exchange and application. In this paper, we propose a Secure Decentralized Trading Alliance (SDTA) to encompass the entire process holistically. With monetary incentives, we formulate a chain-net structure for recording data digests and authentic transactions, thereby transforming data sharing into data trading without duplicating data storage. Data privacy is promised by encryption. To manage and employ encrypted medical data, users can update and search their encrypted data using an index and keywords, subsequently retrieving data within the SDTA framework. It is realized by a novel dynamic searchable symmetric encryption (SSE) with an $l$-level access strategy, which confines users to data pertinent solely to them, thus circumventing unnecessary data leakage. We scrutinize the storage efficiency and prove the fairness and security of SDTA. Finally, we generate datasets of varying sizes, where the time required to search for a single keyword is approximately 0.04 s with 1 000 000 (keyword, identifier) pairs, showing it quite acceptable.
Human Activity Recognition Based On Video Summarization And Deep Convolutional Neural Network
Authors: Kushwaha Arati , Khare Manish , Bommisetty Reddy Mounika , Khare Ashish 
Published: March 2024

Abstract
In this technological era, human activity recognition (HAR) plays a significant role in several applications like surveillance, health services, Internet of Things, etc. Recent advancements in deep learning and video summarization have motivated us to integrate these techniques for HAR. This paper introduces a computationally efficient HAR technique based on a deep learning framework, which works well in realistic and multi-view environments. Deep convolutional neural networks (DCNNs) normally suffer from different constraints, including data size dependencies, computational complexity, overfitting, training challenges and vanishing gradients. Additionally, with the use of advanced mobile vision devices, the demand for computationally efficient HAR algorithms with the requirement of limited computational resources is high. To address these issues, we used integration of DCNN with video summarization using keyframes. The proposed technique offers a solution that enhances performance with efficient resource utilization. For this, first, we designed a lightweight and computationally efficient deep learning architecture based on the concept of identity skip connections (features reusability), which preserves the gradient loss attenuation and can handle the enormous complexity of activity classes. Subsequently, we employed an efficient keyframe extraction technique to minimize redundancy and succinctly encapsulate the entire video content in a lesser number of frames. To evaluate the efficacy of the proposed method, we performed the experimentation on several publicly available datasets. The performance of the proposed method is measured in terms of evaluation parameters Precision, Recall, F-Measure and Classification Accuracy. The experimental results demonstrated the superiority of the presented algorithm over other existing state-of-the-art methods.
Identity Driven Information Ecosystems
Authors: Hiaeshutter-Rice Dan , Madrigal Guadalupe , Ploger Gavin , Carr Sydney , Carbone Mia , Battocchio Ava Francesca , Soroka Stuart 
Published: March 2024

Abstract
This article proposes a theoretical approach that highlights the role of identity in information exposure and processing. This Identity Driven Information Ecosystem (IDIE) approach is premised on the idea that everyone’s information ecosystem varies, shaped by who they are, where they live, and who they interact with. Identities play a crucial role in determining the sites of communication that individuals use and engage with, and as a result, there are systematic differences in where people get information, what information they see, and how they react to it. This article lays out an argument for how identity is associated with the information we are exposed to, select, believe, and share; and it argues that identity, technology, affordances, and structures interact to shape our information ecosystems. The article concludes with a case study of the COVID-19 pandemic as an illustration of applying the IDIE approach to understand individual-level variation in information ecosystems.