bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the role of transcription in evidential consistency of police interview records in England and Wales
Authors: Richardson Emma , Hamann Magnus , Tompkinson James , Haworth Kate , Deamer Felicity 
Published: August 2023

Abstract
Evidential records of investigative interviews serve an important institutional purpose within the legal system in England and Wales. Academic scholars have long recognized that little institutional attention is paid to the transformation process that occurs when written records of the spoken are produced, nor to the potential impact this has on later interpretation by users of the records during the investigation of crimes and later in court. We analyse twenty-nine digitally recorded investigative interviews and their corresponding official written ‘Record of Taped/Videoed Interview’ (ROTI/ROVI) transcripts, taking an ethnomethodological, conversation analytic (CA) approach to examine the social actions that are transformed in this activity by comparing the audio record of police interview evidence to the written transcripts. The intended outcome of this work, within the wider project of which this forms a part, is to better understand this process within the legal system, and to incite improvements. (Investigative interview, transcription, entextualisation, conversation analysis)
Acceptability of a Personal Contact Intervention among People Living with Dementia: Might Baseline Contact Matter?
Authors: Thibault Danielle , Whynot Tynisha D. , Swindle Jennifer , Lee Heunjung , O’Rourke Hannah M. 
Published: August 2023

AbstractOur study aimed to explore how perceived baseline contact may influence acceptability of Connecting Today, a personal contact intervention, among people living with dementia. We aimed to generate hypotheses for testing in future studies. This was a sub-group analysis of pilot study data. Fifteen people living with mild to moderate dementia participated in Connecting Today. We explored how perceptions of intervention acceptability may differ in groups reporting weekly contact (n = 8) compared with groups reporting monthly/unknown (n = 7) contact at baseline. Measures of acceptability included a treatment perceptions and preferences questionnaire, and the number of and reasons for non-consent, missing data, and study withdrawal. We used descriptive statistics and content analysis. In visits one and two, a larger proportion (85.7–100%) of low baseline contact participants reported feeling better, and indicated that the visits helped them and were easy “mostly” or “a lot”, compared with the high baseline contact group (37.5–62.5%). Most missing data (71%) and all study withdrawals occurred in the high baseline contact group. Scheduled in-person visits with family, friends, or a volunteer may appeal to residents in care homes who have few existing opportunities for routine, one-on-one visits with others. Hypotheses generated should be tested in future studies.
Cross-linguistic influence in the simultaneous bilingual child's lexicon: An eye-tracking and primed picture selection study
Authors: Koutamanis Elly , Kootstra Gerrit Jan , Dijkstra Ton , Unsworth Sharon 
Published: August 2023

AbstractIn a between-language lexical priming study, we examined to what extent the two languages in a simultaneous bilingual child's lexicon interact, while taking individual differences in language exposure into account. Primary-school-aged Dutch–Greek bilinguals performed a primed picture selection task combined with eye-tracking. They matched pictures to auditorily presented Dutch target words preceded by Greek prime words. Their reaction times and eye movements were recorded. We tested for effects of between-language phonological priming, translation priming, and phonological priming through translation. Priming effects emerged in reaction times and eye movements in all three conditions, at different stages of processing, and unaffected by language exposure. These results extend previous findings for bilingual toddlers and bilingual adults. Processing similarities between these populations indicate that, across different stages of development, bilinguals have an integrated lexicon that is accessed in a language-nonselective way and is susceptible to interactions within and between different types of lexical representation.
Fatal Years: Background and Aftermath
Authors: Preston Samuel H. , Haines Michael R. 
Published: August 2023

AbstractThis is a history of the creation of the book Fatal Years: Child Mortality in late-Nineteenth-Century America (1991) by the authors. The data were a sample of households from the 1900 United States Census manuscripts. The primary method used was indirect estimation of child mortality (approximately ages 0–4) using information on the age and marriage duration of women. Among the findings were overall lower overall mortality than in the 1900/1902 Glover life tables for the Death Registration Area, and very large variations in mortality by race and size of place of residence.
Modeling the Evolution of Lunar Regolith: 1. Formation Mechanism Through Individual Simple Impact Craters
Authors: Zhang Mingwei , Fa Wenzhe , Eke Vincent R. 
Published: August 2023

AbstractThe production, distribution, and evolution of lunar regolith are critical in deciphering the lunar bombardment history and comprehending the transport of materials across the lunar surface, which are still not well understood. In this study, we conducted a comprehensive investigation of factors influencing the production and distribution of lunar regolith by individual simple craters. Combining our results for the impact‐generated regolith volume with a lunar production function, we developed an analytical model to describe the regolith growth process. We found that the strength of bedrock significantly affects the crater size and hence the volume of regolith produced especially for subdecameter impactors. The regolith volume produced by an individual impact crater is quantitatively characterized as a function of crater diameter and preimpact regolith thickness. This regolith production is primarily determined by how much bedrock is shattered, followed by the impact‐induced volume change of target material and lastly by the regolith volume created by secondary cratering processes. When a single crater forms, preimpact regolith thickness greatly affects the regolith distribution pattern; a larger fraction of the regolith will be distributed outside the crater rim for a deeper preimpact regolith layer. Our regolith evolution model can serve as a good first‐order estimation of the regolith growth process that provides better constraints on the regolith buffering trend than previous studies. This model also suggests that, when ignoring the contribution from large, distant impacts, the regolith growth process is dominated by impact craters at scales from a meter to a few hectometers.
Toward Improved Regional Hydrological Model Performance Using State‐Of‐The‐Science Data‐Informed Soil Parameters
Authors: Li Chuxuan , Yu Guo , Wang Jiali , Horton Daniel E. 
Published: August 2023

AbstractAccurate soil moisture and streamflow data are an aspirational need of many hydrologically relevant fields. Model simulated soil moisture and streamflow hold promise but models require validation prior to application. Calibration methods are commonly used to improve model fidelity but misrepresentation of the true dynamics remains a challenge. In this study, we leverage soil parameter estimates from the Soil Survey Geographic (SSURGO) database and the probability mapping of SSURGO (POLARIS) to improve the representation of hydrologic processes in the Weather Research and Forecasting Hydrological modeling system (WRF‐Hydro) over a central California domain. Our results show WRF‐Hydro soil moisture exhibits increased correlation coefficients (r), reduced biases, and increased Kling‐Gupta Efficiencies (KGEs) across seven in situ soil moisture observing stations after updating the model's soil parameters according to POLARIS. Compared to four well‐established soil moisture data sets including Soil Moisture Active Passive data and three Phase 2 North American Land Data Assimilation System land surface models, our POLARIS‐adjusted WRF‐Hydro simulations produce the highest mean KGE (0.69) across the seven stations. More importantly, WRF‐Hydro streamflow fidelity also increases, especially in the case where the model domain is set up with SSURGO‐informed total soil thickness. The magnitude and timing of peak flow events are better captured, r increases across nine United States Geological Survey stream gages, and the mean KGE across seven of the nine gages increases from 0.12 to 0.66. Our pre‐calibration parameter estimate approach, which is transferable to other spatially distributed hydrological models, can substantially improve a model's performance, helping reduce calibration efforts and computational costs.
Universal linear intensity transformations using spatially incoherent diffractive processors
Authors: Rahman Md Sadman Sakib , Yang Xilin , Li Jingxi , Bai Bijie , Ozcan Aydogan 
Published: August 2023

AbstractUnder spatially coherent light, a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view (FOVs) if the total number (N) of optimizable phase-only diffractive features is ≥~2NiNo, where Ni and No refer to the number of useful pixels at the input and the output FOVs, respectively. Here we report the design of a spatially incoherent diffractive optical processor that can approximate any arbitrary linear transformation in time-averaged intensity between its input and output FOVs. Under spatially incoherent monochromatic light, the spatially varying intensity point spread function (H) of a diffractive network, corresponding to a given, arbitrarily-selected linear intensity transformation, can be written as H(m, n; m′, n′) = |h(m, n; m′, n′)|2, where h is the spatially coherent point spread function of the same diffractive network, and (m, n) and (m′, n′) define the coordinates of the output and input FOVs, respectively. Using numerical simulations and deep learning, supervised through examples of input-output profiles, we demonstrate that a spatially incoherent diffractive network can be trained to all-optically perform any arbitrary linear intensity transformation between its input and output if N ≥ ~2NiNo. We also report the design of spatially incoherent diffractive networks for linear processing of intensity information at multiple illumination wavelengths, operating simultaneously. Finally, we numerically demonstrate a diffractive network design that performs all-optical classification of handwritten digits under spatially incoherent illumination, achieving a test accuracy of >95%. Spatially incoherent diffractive networks will be broadly useful for designing all-optical visual processors that can work under natural light.
Digital light processing 3D printing for microfluidic chips with enhanced resolution via dosing- and zoning-controlled vat photopolymerization
Authors: Luo Zhiming , Zhang Haoyue , Chen Runze , Li Hanting , Cheng Fang , Zhang Lijun , Liu Jia , Kong Tiantian , Zhang Yang , Wang Huanan 
Published: August 2023

AbstractConventional manufacturing techniques to fabricate microfluidic chips, such as soft lithography and hot embossing process, have limitations that include difficulty in preparing multiple-layered structures, cost- and labor-consuming fabrication process, and low productivity. Digital light processing (DLP) technology has recently emerged as a cost-efficient microfabrication approach for the 3D printing of microfluidic chips; however, the fabrication resolution for microchannels is still limited to sub-100 microns at best. Here, we developed an innovative DLP printing strategy for high resolution and scalable microchannel fabrication by dosing- and zoning-controlled vat photopolymerization (DZC-VPP). Specifically, we proposed a modified mathematical model to precisely predict the accumulated UV irradiance for resin photopolymerization, thereby providing guidance for the fabrication of microchannels with enhanced resolution. By fine-tuning the printing parameters, including optical irradiance, exposure time, projection region, and step distance, we can precisely tailor the penetration irradiance stemming from the photopolymerization of the neighboring resin layers, thereby preventing channel blockage due to UV overexposure or compromised bonding stability owing to insufficient resin curing. Remarkably, this strategy can allow the preparation of microchannels with cross-sectional dimensions of 20 μm × 20 μm using a commercial printer with a pixel size of 10 μm × 10 μm; this is significantly higher resolution than previous reports. In addition, this method can enable the scalable and biocompatible fabrication of microfluidic drop-maker units that can be used for cell encapsulation. In general, the current DZC-VPP method can enable major advances in precise and scalable microchannel fabrication and represents a significant step forward for widespread applications of microfluidics-based techniques in biomedical fields.
Subtle adversarial image manipulations influence both human and machine perception
Authors: Veerabadran Vijay , Goldman Josh , Shankar Shreya , Cheung Brian , Papernot Nicolas , Kurakin Alexey , Goodfellow Ian , Shlens Jonathon , Sohl-Dickstein Jascha , Mozer Michael C. , Elsayed Gamaleldin F. 
Published: August 2023

AbstractAlthough artificial neural networks (ANNs) were inspired by the brain, ANNs exhibit a brittleness not generally observed in human perception. One shortcoming of ANNs is their susceptibility to adversarial perturbations—subtle modulations of natural images that result in changes to classification decisions, such as confidently mislabelling an image of an elephant, initially classified correctly, as a clock. In contrast, a human observer might well dismiss the perturbations as an innocuous imaging artifact. This phenomenon may point to a fundamental difference between human and machine perception, but it drives one to ask whether human sensitivity to adversarial perturbations might be revealed with appropriate behavioral measures. Here, we find that adversarial perturbations that fool ANNs similarly bias human choice. We further show that the effect is more likely driven by higher-order statistics of natural images to which both humans and ANNs are sensitive, rather than by the detailed architecture of the ANN.
Learning more from the inter-rater reliability of interstitial fibrosis assessment beyond just a statistic
Authors: Liang Peir-In , Lin Wei-Chou , Wen Mei-Chin , Huang Shun-Chen , Fang Pei-Wei , Chuang Hao-Wen , Lin Yi-Jia , Chien Hui-Ping , Chen Huan-Da , Chen Tai-Di 
Published: August 2023

AbstractInterstitial fibrosis assessment by renal pathologists lacks good agreement, and we aimed to investigate its hidden properties and infer possible clinical impact. Fifty kidney biopsies were assessed by 9 renal pathologists and evaluated by intraclass correlation coefficients (ICCs) and kappa statistics. Probabilities of pathologists’ assessments that would deviate far from true values were derived from quadratic regression and multilayer perceptron nonlinear regression. Likely causes of variation in interstitial fibrosis assessment were investigated. Possible misclassification rates were inferred on reported large cohorts. We found inter-rater reliabilities ranged from poor to good (ICCs 0.48 to 0.90), and pathologists’ assessments had the worst agreements when the extent of interstitial fibrosis was moderate. 33.5% of pathologists’ assessments were expected to deviate far from the true values. Variation in interstitial fibrosis assessment was found to be correlated with variation in interstitial inflammation assessment (r2 = 32.1%). Taking IgA nephropathy as an example, the Oxford T scores for interstitial fibrosis were expected to be misclassified in 21.9% of patients. This study demonstrated the complexity of the inter-rater reliability of interstitial fibrosis assessment, and our proposed approaches discovered previously unknown properties in pathologists’ practice and inferred a possible clinical impact on patients.
Study on the spatial decomposition of the infection probability of COVID-19
Authors: Liu Lu 
Published: August 2023

AbstractIn the course of our observations of the transmission of COVID-19 around the world, we perceived substantial concern about imported cases versus cases of local transmission. This study, therefore, tries to isolate cases due to local transmission (also called community spread) from those due to externally introduced COVID-19 infection, which can be key to understanding the spread pattern of the pandemic. In particular, we offer a probabilistic perspective to estimate the scale of the outbreak at the epicenter of the COVID-19 epidemic with an environmental focus. First, this study proposes a novel explanation of the probability of COVID-19 cases in the local population of the target city, in which the chain of probability is based on the assumption of independent distribution. Then it conducts a spatial statistical analysis on the spread of COVID-19, using two model specifications to identify the spatial dependence, more commonly known as the spillover effect. The results are found to have strong spatial dependence. Finally, it confirms the significance of residential waste in the transmission of COVID-19, which indicates that the fight against COVID-19 requires us to pay close attention to environmental factors. The method shown in this study is critical and has high practical value, because it can be easily applied elsewhere and to other future pandemics.
Using principles of motor control to analyze performance of human machine interfaces
Authors: Patwardhan Shriniwas , Gladhill Keri Anne , Joiner Wilsaan M. , Schofield Jonathon S. , Lee Ben Seiyon , Sikdar Siddhartha 
Published: August 2023

AbstractThere have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.
Genomic diversity of Yersinia pestis from Yunnan Province, China, implies a potential common ancestor as the source of two plague epidemics
Authors: Qin Jingliang , Wu Yarong , Shi Liyuan , Zuo Xiujuan , Zhang Xianglilan , Qian Xiuwei , Fan Hang , Guo Yan , Cui Mengnan , Zhang Haipeng , Yang Fengyi , Kong Jinjiao , Song Yajun , Yang Ruifu , Wang Peng , Cui Yujun 
Published: August 2023

AbstractPlague, caused by Yersinia pestis, is a zoonotic disease that can reemerge and cause outbreaks following decades of latency in natural plague foci. However, the genetic diversity and spread pattern of Y. pestis during these epidemic-silent cycles remain unclear. In this study, we analyze 356 Y. pestis genomes isolated between 1952 and 2016 in the Yunnan Rattus tanezumi plague focus, China, covering two epidemic-silent cycles. Through high-resolution genomic epidemiological analysis, we find that 96% of Y. pestis genomes belong to phylogroup 1.ORI2 and are subdivided into two sister clades (Sublineage1 and Sublineage2) characterized by different temporal-spatial distributions and genetic diversity. Most of the Sublineage1 strains are isolated from the first epidemic-silent cycle, while Sublineage2 strains are predominantly from the second cycle and revealing a west to east spread. The two sister clades evolved in parallel from a common ancestor and independently lead to two separate epidemics, confirming that the pathogen responsible for the second epidemic following the silent interval is not a descendant of the causative strain of the first epidemic. Our results provide a mechanism for defining epidemic-silent cycles in natural plague foci, which is valuable in the prevention and control of future plague outbreaks.
Extracellular Pgk1 interacts neural membrane protein enolase-2 to improve the neurite outgrowth of motor neurons
Authors: Fu Chuan-Yang , Chen Hong-Yu , Lin Cheng-Yung , Chen Shiang-Jiuun , Sheu Jin-Chuan , Tsai Huai-Jen 
Published: August 2023

AbstractUnderstanding the molecular interaction between ligand and receptor is important for providing the basis for the development of regenerative drugs. Although it has been reported that extracellular phosphoglycerate kinase 1 (Pgk1) can promote the neurite outgrowth of motoneurons, the Pgk1-interacting neural receptor remains unknown. Here we show that neural membranous Enolase-2 exhibits strong affinity with recombinant Pgk1-Flag, which is also evidently demonstrated by immunoelectron microscopy. The 325th-417th domain of Pgk1 interacts with the 405th-431st domain of Enolase-2, but neither Enolase-1 nor Enolase-3, promoting neurite outgrowth. Combining Pgk1 incubation and Enolase-2 overexpression, we demonstrate a highly significant enhancement of neurite outgrowth of motoneurons through a reduced p-P38-T180/p-Limk1-S323/p-Cofilin signaling. Collectively, extracellular Pgk1 interacts neural membrane receptor Enolase-2 to reduce the P38/Limk1/Cofilin signaling which results in promoting neurite outgrowth. The extracellular Pgk1-specific neural receptor found in this study should provide a material for screening potential small molecule drugs that promote motor nerve regeneration.