bluuebunny/crossref_metadata_2025_split huggingface dataset:
Water exchange in the Dardanelles: variations on synoptic to interannual time scales
Authors: Saçu Şehriban , Şen Olgay , Erdik Tarkan , Öztürk İzzet , Stanev Emil V. 
Published: February 2024

AbstractThe bidirectional mass exchange between the Marmara Sea and the Aegean Sea provides one part of the critical hydrodynamic links between the Black Sea and the Mediterranean Sea. In this study, we examined exchange in the Dardanelles based on a 3-D numerical model simulation covering an 11-year period under realistic atmospheric forcing. The model includes the Black Sea, the Marmara Sea, and a part of the Aegean Sea to include the remote effects of basin dynamics. The main features as one-, two-, and three-layered flow structures are successfully reproduced by the model in comparison to earlier observations. It is found that the strait is subject to submaximal exchange by only one control near the Nara Pass. According to long-term modeling results, most variability occurs on synoptic time scales, and wind stress has a dominant role in those variations. The seasonal and interannual variability of exchange flow is relatively low and displays a close relationship with freshwater input to the Black Sea.
On the links between sea level and temperature variations in the Chesapeake Bay and the Atlantic Meridional Overturning Circulation (AMOC)
Authors: Ezer Tal , Updyke Teresa 
Published: February 2024

AbstractRecent studies found that on long time scales there are often unexplained opposite trends in sea level variability between the upper and lower Chesapeake Bay (CB). Therefore, daily sea level and temperature records were analyzed in two locations, Norfolk in the southern CB and Baltimore in the northern CB; surface currents from Coastal Ocean Dynamics Application Radar (CODAR) near the mouth of CB were also analyzed to examine connections between the CB and the Atlantic Ocean. The observations in the bay were compared with daily Atlantic Meridional Overturning Circulation (AMOC) observations during 2005–2021. Empirical Mode Decomposition (EMD) analysis was used to show that variations of sea level and temperature in the upper and lower CB are positively correlated with each other for short time scales of months to few years, but anticorrelated on low frequency modes representing decadal variability and long-term nonlinear trends. The long-term CB modes seem to be linked with AMOC variability through variations in the Gulf Stream and the wind-driven Ekman transports over the North Atlantic Ocean. AMOC variability correlates more strongly with variability in the southern CB near the mouth of the bay, where surface currents indicate potential links with AMOC variability. For example, when AMOC and the Gulf Stream were especially weak during 2009–2010, sea level in the southern bay was abnormally high, temperatures were colder than normal and outflow through the mouth of CB was especially high. Sea level in the upper bay responded to this change only 1–2 years later, which partly explains phase differences within the bay. A persistent trend of 0.22 cm/s per year of increased outflow from the CB, may be a sign of a climate-related trend associated with combination of weakening AMOC and increased precipitation and river discharge into the CB.
Causality between COVID-19 and multiple myeloma: a two-sample Mendelian randomization study and Bayesian co-localization
Authors: Wang Shuaiyuan , Zhao Na , Luo Ting , Kou Songzi , Sun Miaomiao , Chen Kuisheng 
Published: February 2024

AbstractInfection is the leading cause of morbidity and mortality in patients with multiple myeloma (MM). Studying the relationship between different traits of Coronavirus 2019 (COVID-19) and MM is critical for the management and treatment of MM patients with COVID-19. But all the studies on the relationship so far were observational and the results were also contradictory. Using the latest publicly available COVID-19 genome-wide association studies (GWAS) data, we performed a bidirectional Mendelian randomization (MR) analysis of the causality between MM and different traits of COVID-19 (SARS-CoV-2 infection, COVID-19 hospitalization, and severe COVID-19) and use multi-trait analysis of GWAS(MTAG) to identify new associated SNPs in MM. We performed co-localization analysis to reveal potential causal pathways between diseases and over-representation enrichment analysis to find involved biological pathways. IVW results showed SARS-CoV-2 infection and COVID-19 hospitalization increased risk of MM. In the reverse analysis, the causal relationship was not found between MM for each of the different symptoms of COVID-19. Co-localization analysis identified LZTFL1, MUC4, OAS1, HLA-C, SLC22A31, FDX2, and MAPT as genes involved in COVID-19-mediated causation of MM. These genes were mainly related to immune function, glycosylation modifications and virus defense. Three novel MM-related SNPs were found through MTAG, which may regulate the expression of B3GNT6. This is the first study to use MR to explore the causality between different traits of COVID-19 and MM. The results of our two-way MR analysis found that SARS-CoV-2 infection and COVID-19 hospitalization increased the susceptibility of MM.
An 80–84.8 GHz PLL with auto-tracking Miller divider for FMCW applications
Authors: Effendrik Popong , Chen Wei-Zen 
Published: February 2024

AbstractTo generate high frequency signals for frequency modulated continuous wave (FMCW) application, components such as doubler, tripler or multiplier are usually utilized to process further signals from the low frequency voltage controlled oscillator (VCO). In this paper, a phase-locked loop (PLL) is intended to be the primary part used to generate frequency modulated continuous wave (FMCW) signals from 80 to 84.8 GHz by utilizing a fundamental frequency VCO. To divide those high frequency output signal and large output bandwidth, the auto-tracking Miller divider topology is proposed. This new topology can achieve 9 GHz locking range. In order to generate FMCW signals with a straight-line triangular chirp, the cascaded PLL is used. The integrated jitter from 1 kHz to 1 GHz is 887 fs for the cascaded PLL, while the single stage PLL used 1.264 ps. Moreover, when architecture with doubler or multiplier is used, the fundamental tone has an effect towards the next systems, while the cascaded PLL does not. It can be highlighted that this work achieves the best RMS-FMerror/BWchirp and RMS-FMerror/(BWchirp × fc × Tc) with value of 0.013% and 0.77e−12, respectively. The designed PLL for FMCW signal generator is implemented in 28 nm CMOS technology. By using a supply voltage of 1.2 V, the chip consumes power of 102 mW. Including all the chip pads, the implemented circuit occupies a silicon area of 1440 µm × 820 µm.
Prioritizing water availability study settings to address geogenic contaminants and related societal factors
Authors: Erickson Melinda L. , Brown Craig J. , Tomaszewski Elizabeth J. , Ayotte Joseph D. , Böhlke John K. , Kent Douglas B. , Qi Sharon 
Published: February 2024

AbstractWater availability for human and ecological uses depends on both water quantity and water quality. The U.S. Geological Survey (USGS) is developing strategies for prioritizing regional-scale and watershed basin-scale studies of water availability across the nation. Previous USGS ranking processes for basin-scale studies incorporated primarily water quantity factors but are now considering additional water quality factors. This study presents a ranking based on the potential impacts of geogenic constituents on water quality and consideration of societal factors related to water quality. High-concentration geogenic constituents, including trace elements and radionuclides, are among the most prevalent contaminants limiting water availability in the USA and globally. Geogenic constituents commonly occur in groundwater because of subsurface water–rock interactions, and their distributions are controlled by complex geochemical processes. Geogenic constituent mobility can also be affected by human activities (e.g., mining, energy production, irrigation, and pumping). Societal factors and relations to drinking water sources and water quality information are often overlooked when evaluating research priorities. Sociodemographic characteristics, data gaps resulting from historical data-collection disparities, and infrastructure condition/age are examples of factors to consider regarding environmental justice. This paper presents approaches for ranking and prioritizing potential basin-scale study areas across the contiguous USA by considering a suite of conventional physical and geochemical variables related to geogenic constituents, with and without considering variables related to societal factors. Simultaneous consideration of societal and conventional factors could provide decision makers with more diverse, interdisciplinary tools to increase equity and reduce bias in prioritizing focused research areas and future water availability studies.
Revolutionizing crop disease detection with computational deep learning: a comprehensive review
Authors: Ngugi Habiba N. , Ezugwu Absalom E. , Akinyelu Andronicus A. , Abualigah Laith 
Published: February 2024

AbstractDigital image processing has witnessed a significant transformation, owing to the adoption of deep learning (DL) algorithms, which have proven to be vastly superior to conventional methods for crop detection. These DL algorithms have recently found successful applications across various domains, translating input data, such as images of afflicted plants, into valuable insights, like the identification of specific crop diseases. This innovation has spurred the development of cutting-edge techniques for early detection and diagnosis of crop diseases, leveraging tools such as convolutional neural networks (CNN), K-nearest neighbour (KNN), support vector machines (SVM), and artificial neural networks (ANN). This paper offers an all-encompassing exploration of the contemporary literature on methods for diagnosing, categorizing, and gauging the severity of crop diseases. The review examines the performance analysis of the latest machine learning (ML) and DL techniques outlined in these studies. It also scrutinizes the methodologies and datasets and outlines the prevalent recommendations and identified gaps within different research investigations. As a conclusion, the review offers insights into potential solutions and outlines the direction for future research in this field. The review underscores that while most studies have concentrated on traditional ML algorithms and CNN, there has been a noticeable dearth of focus on emerging DL algorithms like capsule neural networks and vision transformers. Furthermore, it sheds light on the fact that several datasets employed for training and evaluating DL models have been tailored to suit specific crop types, emphasizing the pressing need for a comprehensive and expansive image dataset encompassing a wider array of crop varieties. Moreover, the survey draws attention to the prevailing trend where the majority of research endeavours have concentrated on individual plant diseases, ML, or DL algorithms. In light of this, it advocates for the development of a unified framework that harnesses an ensemble of ML and DL algorithms to address the complexities of multiple plant diseases effectively.
Traceability and reuse mechanisms, the most important properties of model transformation languages
Authors: Höppner Stefan , Tichy Matthias 
Published: February 2024

Abstract

Context

Dedicated model transformation languages are claimed to provide many benefits over the use of general purpose languages for developing model transformations. However, the actual advantages and disadvantages associated with the use of model transformation languages are poorly understood empirically. There is little knowledge and even less empirical assessment about what advantages and disadvantages hold in which cases and where they originate from. In a prior interview study, we elicited expert opinions on what advantages result from what factors surrounding model transformation languages as well as a number of moderating factors that moderate the influence.

Objective

We aim to quantitatively asses the interview results to confirm or reject the influences and moderation effects posed by different factors. We further intend to gain insights into how valuable different factors are to the discussion so that future studies can draw on these data for designing targeted and relevant studies.

Method

We gather data on the factors and quality attributes using an online survey. To analyse the data and examine the hypothesised influences and moderations, we use universal structure modelling based on a structural equation model. Universal structure modelling produces significance values and path coefficients for each hypothesised and modelled interdependence between factors and quality attributes that can be used to confirm or reject correlation and to weigh the strength of influence present.

Results

We analyzed 113 responses. The results show that the MTL capabilities Tracing and Reuse Mechanisms are most important overall. Though the observed effects were generally 10 times lower than anticipated. Furthermore, we found that moderation effects need to be individually assessed for each influence on a quality attribute. The moderation effects of a single moderating variable vary significantly for each influence, with the strongest effects being 1000 times higher than the weakest.

Conclusion

The empirical assessment of MTLs is a complex topic that cannot be solved by looking at a single stand-alone factor. Our results provide clear indication that evaluation should consider transformations of different sizes and use-cases that go beyond mapping one elements attributes to another. Language development on the other hand should focus on providing practical, transformation specific reuse mechanisms that allow MTLs to excel in areas such as maintainability and productivity compared to GPLs.
Measurement of Diffusion Coefficients in Binary Mixtures and Solutions by the Taylor Dispersion Method
Authors: Martin Trusler J. P. 
Published: February 2024

AbstractThe theory and application of the Taylor Dispersion technique for measuring diffusion coefficients in binary systems is reviewed. The theory discussed in this paper includes both the ideal Taylor–Aris model and the estimation of corrections required to account for small deviations from this ideal associated with a practical apparatus. Based on the theoretical treatment, recommendations are given for the design of practical instruments together with suggestions for calibration, data acquisition and reduction, and the rigorous estimation of uncertainties. The analysis indicates that relative uncertainties on the order of 1% are achievable in practice.
Validating the International Classification of Functioning, Disability and Health Core Sets for Autism in a Sample of Australian School-Aged Children on the Spectrum
Authors: Hayden-Evans Maya , Evans Kiah , Milbourn Benjamin , D’Arcy Emily , Chamberlain Angela , Afsharnejad Bahareh , Whitehouse Andrew , Bölte Sven , Girdler Sonya 
Published: February 2024

AbstractAssessing functioning of children on the autism spectrum is necessary to determine the level of support they require to participate in everyday activities across contexts. The International Classification of Functioning, Disability and Health (ICF) is a comprehensive biopsychosocial framework recommended for classifying health-related functioning in a holistic manner, across the components of body functions, activities and participation, and environmental factors. The ICF Core Sets (ICF-CSs) are sub-sets of relevant codes from the broader framework that provide a basis for developing condition-specific measures. This study combined the ICF-CSs for autism, attention deficit hyperactivity disorder (ADHD) and cerebral palsy (CP) to validate the ICF-CSs for autism in an Australian sample of school-aged children. This cross-sectional study involved caregivers of school-aged children on the spectrum (n = 70) completing an online survey and being visited in their homes by an occupational therapist to complete the proxy-report measure based on the ICF-CSs for autism, ADHD and CP. Absolute and relative frequencies of ratings for each of the codes included in the measure were calculated and reported, along with the number of participants who required clarification to understand the terminology used. Findings indicate that the body functions and activities and participation represented in the ICF-CSs for autism were the most applicable for the sample. However, findings relating to environmental factors were less conclusive. Some codes not currently included in the ICF-CSs for autism may warrant further investigation, and the language used in measures based on the ICF-CSs should be revised to ensure clarity.
Parent and Provider Differences in Ratings of Mental Health and Neurodevelopmental Concerns in Children with Neurologic Disorders
Authors: Schwartzman Jessica M. , Williams Zachary J. , Molnar Andrew E. 
Published: February 2024

AbstractChildren with neurologic disorders face increased risks for mental health and neurodevelopmental conditions, with information often limited to parent report. To better understand mental health and neurodevelopmental needs in this population, a retrospective chart review of a convenience sample of children with neurologic disorders referred for a neuropsychological evaluation was conducted in the present study to explore interrater agreement between care team members (referring providers, parents, pediatric neuropsychologist). Qualitative and quantitative data were collected from the evaluation reports of 129 youth (9:0–17:11 years old; 51.2% of female sex) with neurologic disorders (i.e., 38.0% traumatic brain injury, 27.1% epilepsy, 14.7% premature birth, 7.8% pediatric cancer, 3.9% prenatal substance exposure, and 14.7% other) who completed an evaluation in 2019. Over half the youth were flagged for unmet neurodevelopmental and mental health concerns and analyses revealed low interrater agreement for mental health concerns (κ = .324), better agreement for neurodevelopmental concerns (κ = .511), and low sensitivity of referring providers (Se = .326) and parents (Se = .366). One-way analyses of variance uncovered important factors (e.g., symptom severity, adaptive skills) that may account for missed concerns. Findings guide recommendations to strengthen methods for understanding mental health and/or neurodevelopmental concerns in children with neurologic disorders.
Applying the Somatic Symptom Disorder Diagnosis to Individuals with Fibromyalgia: Strengths and Limitations
Authors: LoBrutto Lara R. , Keeley Jared W. , Dautovich Natalie D. 
Published: February 2024

AbstractAmidst broad changes to the somatic disorder diagnoses, DSM-IV pain disorder was absorbed into DSM-5’s somatic symptom disorder (SSD) as a specifier. However, clinical research testing of its use for the chronic pain population has been limited and its utility remains inconclusive. Using the exemplar of fibromyalgia, this article evaluates the validity, reliability, clinical utility, and acceptability of the SSD pain specifier. The diagnosis appears to have moderate validity but low specificity for the fibromyalgia population. The pain specifier has neither undergone sufficient field testing nor been evaluated for use by medical providers, with available data suggesting low reliability. Further research is needed to establish clinical utility via assessment of differential treatment outcomes. Concerns about social, legal, and economic consequences of classifying pain patients with a mental health diagnosis are outstanding. The current SSD criteria should be used with caution among the fibromyalgia patient population until its application for chronic pain has been further researched.
Optimization Algorithms for Multi-species Spherical Spin Glasses
Authors: Huang Brice , Sellke Mark 
Published: February 2024

AbstractThis paper develops approximate message passing algorithms to optimize multi-species spherical spin glasses. We first show how to efficiently achieve the algorithmic threshold energy identified in our companion work (Huang and Sellke in arXiv preprint, 2023. arXiv:2303.12172), thus confirming that the Lipschitz hardness result proved therein is tight. Next we give two generalized algorithms which produce multiple outputs and show all of them are approximate critical points. Namely, in an r-species model we construct $$2^r$$

2
r

approximate critical points when the external field is stronger than a “topological trivialization" phase boundary, and exponentially many such points in the complementary regime. We also compute the local behavior of the Hamiltonian around each. These extensions are relevant for another companion work (Huang and Sellke in arXiv preprint, 2023. arXiv:2308.09677) on topological trivialization of the landscape.
Integrating Making with Authentic Science Classes: An Approach and Evidence
Authors: Chen Kaiyuan , Chu Sharon Lyn , Quek Francis , Schlegel Rebecca J. 
Published: February 2024

AbstractAlthough research has touted the value of making in educational settings, scant work has been done in formal school contexts utilizing quantitative methods. This could be attributed to the various challenges in integrating making in school settings. To fill in the gap, this study presents an approach to integrate making into science classes at the 3rd to 5th grade levels in a U.S. public school for four consecutive years (2015–2019). We examined the effect of the program on students’ self-beliefs (self-efficacy, motivation, and self-concept) using a longitudinal quasi-experimental design. We also examined the effect of making on students’ knowledge and skills using state testing data. Results suggest that when averaged across post school year surveys, students in maker classes (vs. control) reported higher self-efficacy beliefs in science and making as well as more interests in STEM-related careers. Moreover, over two school years, we observed that students in the control group experienced declines on some of our variables while our maker students did not. Data thereby speaks to the potential value and promise of integrating making into formal school settings. Practical implications are discussed.
Porous polypropylene produced by phase separation for high solar reflectivity and passive cooling
Authors: Vámos Csenge , Bárány Tamás , Marosfői Botond Béla 
Published: February 2024

AbstractPassive cooling techniques have gained widespread use in everyday life and various industries by utilizing sunlight reflection to cool objects without requiring additional energy input. Porous polymer materials possess the unique ability to provide both thermal insulation and solar reflection due to their inherent multiphase structure. In this study, we developed a porous polypropylene (PP) with a hierarchically structured surface layer using a simple and efficient solvent treatment method based on recrystallization. As a result, the porous structure and hierarchically structured surface significantly increase the solar reflectance from 11 to 86%. We found that by manipulating the recrystallization process and using reflective additives, solar reflectivity can be further improved. With the use of TiO2 and BaSO4 additives, a solar reflectance of 90% was achieved, while a solar reflectance of 93% was achieved with nucleating agents. In practical terms, these improvements result in significant temperature reductions in cooling performance tests compared to extruded PP sheets: 17, 19, and 22 °C for porous PP, porous PP/TiO2 or PP/BaSO4, and porous nucleated PP, respectively. The modification method introduced could help PP offer new possibilities for developing low-cost chemically resistant and thermally insulating layers in thermal management applications.