bluuebunny/crossref_metadata_2025_split huggingface dataset:
The value of using heterogeneous detector groups for the development of time-of-flight (TOF) positron emission tomography (PET) systems
Authors: Xin Zhiqiang , Kao Chien-Min , Liu Yuqing , Chen Xun , Zhang Labao , Wu Peiheng , Xie Qingguo 
Published: August 2023

Abstract

Objective. Much recent attention on positron emission tomography (PET) is the development of time-of-flight (TOF) systems with ever-improving coincidence time resolution (CTR). This is because, when all other factors remain the same, a better CTR leads to images of better statistics and effectively increases the sensitivity of the system. However, detector designs that aggressively improve the CTR often compromise the detection efficiency (DE) and offset the benefit gained. Under this circumstance, in developing a TOF PET system it may be beneficial to employ heterogeneous detector groups to balance the overall CTR and DE of the system. In this study, we examine the potential value of this system design strategy by considering two-dimensional systems that assume several representative ways of mixing two detector groups. Approach. The study is based on computer simulation and specifically considers medium time-resolution (MTR) detectors that have a 528 ps CTR and high time-resolution (HTR) detectors that have a 100 ps CTR and a DE that is 0.7 times that of the MTR detector. We examine contrast recovery, noise, and subjective quality of the resulting images under various ways of mixing the MTR and HTR detectors. Main results. With respect to the traditional configuration that adopts only the HTR detectors, symmetric heterogeneous configurations may offer comparable or better images while using considerably fewer HTRs. On the other hand, asymmetric heterogeneous configurations may allow the use of only a few HTRs for improving image quality locally. Significance. This study demonstrates the value of the proposed system-level design strategy of using heterogeneous detector groups for achieving high effective system sensitivity by factoring into the tradeoff between the CTR and DE of the detector.
Characterisation of the UK high energy proton research beamline for high and ultra-high dose rate (FLASH) irradiation
Authors: Aylward J D , Henthorn N , Manger S , Warmenhoven J W , Merchant M J , Taylor M J , Mackay R I , Kirkby K J 
Published: August 2023

Abstract

Objective. This work sets out the capabilities of the high energy proton research beamline developed in the Christie proton therapy centre for Ultra-High Dose Rate (UHDR) irradiation and FLASH experiments. It also characterises the lower limits of UHDR operation for this Pencil Beam Scanning (PBS) proton hardware. Approach. Energy dependent nozzle transmission was measured using a Faraday Cup beam collector. Spot size was measured at the reference plane using a 2D scintillation detector. Integrated depth doses (IDDs) were measured. EBT3 Gafchromic film was used to compare UHDR and conventional dose rate spots. Our beam monitor calibration methodolgy for UHDR is described. A microDiamond detector was used to determine dose rates at zref. Instantaneous depth dose rates were calculated for 70–245 MeV. PBS dose rate distributions were calculated using Folkerts and Van der Water definitions. Main results. Transmission of 7.05 ± 0.1% is achieveable corresponding to a peak instantaneous dose rate of 112.7 Gy s−1. Beam parameters are comparable in conventional and UHDR mode with a spot size of σ
x = 4.6 mm, σ
y = 6.6 mm. Dead time in the beam monitoring electonics warrants a beam current dependent MU correction in the present configuration. Fast beam scanning of 26.4 m s−1 (X) and 12.1 m s−1 (Y) allows PBS dose rates of the order tens of Grays per second. Significance. UHDR delivery is possible for small field sizes and high energies enabling research into the FLASH effect with PBS protons at our facility. To our knowledge this is also the first thorough characterisation of UHDR irradiation using the hardware of this clinical accelerator at energies less than 250 MeV. The data set out in this publication can be used for designing experiments at this UK research facility and inform the possible future clinical translation of UHDR PBS proton therapy.
Toward automated screening of band gap sensitivity in 2D materials
Authors: Fanta Roman , Dubecký Matúš 
Published: August 2023

Abstract
Computational materials science relies on simple, yet efficient, measures and indicators of the modeled materials’ properties. Ideally, the desired properties should be linked to such scalar quantities that can be obtained in polynomial time and efficiently integrated within automated high-throughput screening loops for screening and sorting out the evaluated materials to the desired categories. Here, we focus on the freestanding gapped 2D materials and scalar indicator of their band gap sensitivity to the presence of additional stacked 2D layer/s. The proposed measure uses only a freestanding model of a given material, and it is based on an automated integration of the electron density of frontier orbitals extending into the vacuum within the model unit cell. The usefulness and limitations of such an approach for materials pre-screening are demonstrated on a handful of 2D materials, like, e.g. MXenes, graphane, fluorographene, or, allotropes of phosphorus.
A review on modelling methods, tools and service of integrated energy systems in China
Authors: Wu Nianyuan , Zhang Fuzheng , Wang Jiangjiang , Wang Xiaonan , Wu Jianzhong , Huang Jingzhi , Tan Jiawei , Jing Rui , Lin Jian , Xie Shan , Zhao Yingru 
Published: August 2023

Abstract
An integrated energy system (IES) is responsible for aggregating various energy carriers, such as electricity, gas, heating, and cooling, with a focus on integrating these components to provide an efficient, low-carbon, and reliable energy supply. This paper aims to review the modeling methods, tools, and service modes of IES in China to evaluate opportunities for improving current practices. The models reviewed in this paper are classified as demand forecasting or energy system optimization models based on their modeling progress. Additionally, the main components involved in the IES modeling process are presented, and typical domestic tools utilized in the modeling processes are discussed. Finally, based on a review of several demonstration projects of IES, future development directions of IES are summarized as the integration of data-driven and engineering models, improvements in policies and mechanisms, the establishment of regional energy management centers, and the promotion of new energy equipment.
Design of highly stable, high speed and low power 10T SRAM cell in 18-nm FinFET technology
Authors: Kumar Appikatla Phani , Lorenzo Rohit 
Published: August 2023

Abstract
Many scientists are working to develop a static random-access memory (SRAM) cell that used little power and has good stability and speed. This work introduces a fin field effect transistor developed SRAM cell with 10 transistors (10T FinFET SRAM). A cross connected standard inverter and schmitt-trigger inverter is used in the proposed 10T FinFET SRAM cell. We introduce the schmitt trigger based SRAM cell with single-ended read decoupled and feedback-cutting approaches to enhance the static noise margin (SNM) and access time of the SRAM cell. The proposed cell’s power utilization is decreased with the help of stacked N-FinFETs. For determining the relative performance of the proposed 10T FinFET SRAM cell design in terms of fundamental design metrics, it has also been compared with some of the current SRAM cells, including 6T, SBL9T SRAM, 10T SRAM, and DS10T SRAM. The simulation results at 0.6V demonstrate that the suggested design achieves low power utilization when Reading, writing and hold modes of operation in comparison to the aforementioned bit cells. It maintains a high SNM during all operations. The suggested cell is the one with fastest read access. The simulation is carried out with cadence tool using FinFET 18 nm technology.
Improving resilience of sensors in planetary exploration using data-driven models
Authors: Kumar Dileep , Dominguez-Pumar Manuel , Sayrol-Clols Elisa , Torres Josefina , Marín Mercedes , Gómez-Elvira Javier , Mora Luis , Navarro Sara , Rodríguez-Manfredi Jose 
Published: August 2023

Abstract
Improving the resilience of sensor systems in space exploration is a key objective since the environmental conditions to which they are exposed are very harsh. For example, it is known that the presence of flying debris and Dust Devils on the Martian surface can partially damage sensors present in rovers/landers. The objective of this work is to show how data-driven methods can improve sensor resilience, particularly in the case of complex sensors, with multiple intermediate variables, feeding an inverse algorithm (IA) based on calibration data. The method considers three phases: an initial phase in which the sensor is calibrated in the laboratory and an IA is designed; a second phase, in which the sensor is placed at its intended location and sensor data is used to train data-driven model; and a third phase, once the model has been trained and partial damage is detected, in which the data-driven algorithm is reducing errors. The proposed method is tested with the intermediate data of the wind sensor of the TWINS instrument (NASA InSight mission), consisting of two booms placed on the deck of the lander, and three boards per boom. Wind speed and angle are recovered from the intermediate variables provided by the sensor and predicted by the proposed method. A comparative analysis of various data-driven methods including machine learning and deep learning (DL) methods is carried out for the proposed research. It is shown that even a simple method such as k-nearest neighbor is capable of successfully recovering missing data of a board compared to complex DL models. Depending on the selected missing board, errors are reduced by a factor between 2.43 and 4.78, for horizontal velocity; and by a factor between 1.74 and 4.71, for angle, compared with the situation of using only the two remaining boards.
Improving materials property predictions for graph neural networks with minimal feature engineering
*
Authors: Cong Guojing , Fung Victor 
Published: August 2023

Abstract
Graph neural networks (GNNs) have been employed in materials research to predict physical and functional properties, and have achieved superior performance in several application domains over prior machine learning approaches. Recent studies incorporate features of increasing complexity such as Gaussian radial functions, plane wave functions, and angular terms to augment the neural network models, with the expectation that these features are critical for achieving a high performance. Here, we propose a GNN that adopts edge convolution where hidden edge features evolve during training and extensive attention mechanisms, and operates on simple graphs with atoms as nodes and distances between them as edges. As a result, the same model can be used for very different tasks as no other domain-specific features are used. With a model that uses no feature engineering, we achieve performance comparable with state-of-the-art models with elaborate features for formation energy and band gap prediction with standard benchmarks; we achieve even better performance when the dataset size increases. Although some domain-specific datasets still require hand-crafted features to achieve state-of-the-art results, our selected architecture choices greatly reduce the need for elaborate feature engineering and still maintain predictive power in comparison.
SERS-based detection of efficient removal of organic dyes using molybdenum dichalcogenide nanostructures
Authors: Thayil Ruchika , Cherukulappurath Sudhir 
Published: August 2023

Abstract
Two-dimensional materials have been popular in recent times owing to their special properties that can lead to several applications. In particular, transition metal dichalcogenides have been reported to be potential candidates for photocatalytic degradation and adsorptive removal of organic pollutants. Molybdenum-based chalcogenides have shown to be very efficient in removing pollutant dyes from aqueous solutions. Here, we report a facile method for the removal of organic dyes from aqueous solution using molybdenum dichalcogenide (MoX2; X = S, Se, Te) based nanostructures. The molybdenum dichalcogenide nanostructures were synthesized chemically using the simple hydrothermal method. The samples were characterized by X-ray diffraction, Raman Spectroscopy, UV–visible spectroscopy, and scanning electron microscopy. The as-prepared samples have been utilized as an adsorbent for the removal of common organic dyes such as methylene blue (MB), methyl orange (MO), malachite green (MG), rhodamine B (RhB), rhodamine 6 G (R6G) and mixtures of these organic dyes from aqueous solution. It was observed that among the synthesized samples, molybdenum disulfide (MoS2) presented excellent adsorption affinity towards these dyes. In addition, selective adsorption of MB in the presence of MO and RhB was demonstrated. Furthermore, the application of surface-enhanced Raman scattering (SERS) to monitor the degradation of the dyes in the experiments was also investigated.
Citizen and machine learning-aided high-resolution mapping of urban heat exposure and stress
Authors: Wang Xuewei , Hsu Angel , Chakraborty TC 
Published: August 2023

Abstract
Through conversion of land cover to more built-up, impervious surfaces, cities create hotter environments than their surroundings for urban residents, with large differences expected between different parts of the city. Existing measurements of ambient air temperature and heat stress, however, are often insufficient to capture the intra-urban variability in heat exposure. This study provides a replicable method for modeling air temperature, humidity, and moist heat stress over the urban area of Chapel Hill while engaging citizens to collect high-temporal and spatially-resolved air temperature and humidity measurements. We use low-cost, consumer-grade sensors combined with satellite remote sensing data and machine learning to map urban air temperature and relative humidity over various land-cover classes to understand intra-urban spatial variability of ambient heat exposure at a relatively high resolution (10 m). Our findings show that individuals may be exposed to higher levels of air temperature and moist heat stress than weather station data suggest, and that the ambient heat exposure varies according to land cover type, with tree-covered land the coolest and built-up areas the warmest, and time of day, with higher air temperatures observed during the early afternoon. Combining our resulting dataset with sociodemographic data, policymakers and urban planners in Chapel Hill can use data output from this method to identify areas exposed to high temperature and moist heat stress as a first step to design effective mitigation measures.
TRPS1 immunohistochemical expression in salivary gland tumors: A pilot study
Authors: Tjendra Youley , Kerr Darcy A , Gomez-Fernandez Carmen , Velez Torres Jaylou M 
Published: August 2023

Abstract

Objectives
TRPS1 is a new, sensitive marker for breast carcinoma (BC). Salivary glands and breasts are both exocrine glands; thus, their tumors may share similar morphology and immunophenotype. Among salivary gland–type BC, TRPS1 is reported to be positive in secretory carcinomas (SCs) but negative in acinic cell carcinomas (AciCCs) and most adenoid cystic carcinomas (AdCCs). A subset of salivary duct carcinomas (SDCs) is positive for TRPS1. Herein, we investigate TRPS1 immunohistochemical expression in salivary gland tumors (SGTs).

Methods
A retrospective search yielded 110 SGTs (97 primary and 13 metastatic). TRPS1 immunohistochemistry was scored as negative, low positive, intermediate positive, or strongly positive.

Results
TRPS1 was expressed in 78% (14/18) of pleomorphic adenoma (PA) cases but negative/low positive in all Warthin tumors (6/6 [100%]). In basal cell adenoma (BCA), TRPS1 expression was intermediate to strong (13/14 [92%]) in the stromal cells, whereas ductal or basal cells showed low expression. TRPS1 expression varied in malignant SGTs, with intermediate to strong staining in 100% (15/15) of AdCCs, 100% (5/5) of basal cell adenocarcinoma, 100% (3/3) of intraductal carcinoma, 89% (8/9) of polymorphous adenocarcinoma, and 89% (7/8) of SDCs; negative/low positive expression was observed in 100% (3/3) of SCs, 89% (8/9) of AciCCs, and 50% (3/3) of mucoepidermoid carcinomas. In addition, strong and intermediate TRPS1 expression was observed in metastatic SGT to the lungs, lymph nodes, and soft tissue.

Conclusions
Overall, TRPS1 is strongly expressed in PA as well as malignant and metastatic SGT. In addition, TRPS1 is positive in stromal cells of BCA but negative or low positive in ductal and basal cells.
Clinical pharmacist practitioners on primary care teams play an important role in caring for complex patients with diabetes
Authors: Miller Donald R , Reisman Joel I , McDannold Sarah E , Kleinberg Felicia , Gillespie Chris , Zogas Anna , Ndiwane Ndindam , Ourth Heather L , Morreale Anthony P , Tran Michael , McCullough Megan B 
Published: August 2023

Abstract

Purpose
To evaluate whether clinical pharmacist practitioners (CPPs) are being utilized to care for patients with complex medication regimens and multiple chronic illnesses, we compared the clinical complexity of diabetes patients referred to CPPs in team primary care and those in care by other team providers (OTPs).

Methods
In this cross-sectional comparison of patients with diabetes in the US Department of Veterans Affairs (VA) healthcare system in the 2017-2019 period, patient complexity was based on clinical factors likely to indicate need for more time and resources in medication and disease state management. These factors include insulin prescriptions; use of 3 or more other diabetes medication classes; use of 6 or more other medication classes; 5 or more vascular complications; metabolic complications; 8 or more other complex chronic conditions; chronic kidney disease stage 3b or higher; glycated hemoglobin level of ≥10%; and medication regime nonadherence.

Results
Patients with diabetes referred to one of 110 CPPs for care (n = 12,728) scored substantially higher (P &lt; 0.001) than patients with diabetes in care with one of 544 OTPs (n = 81,183) on every complexity measure, even after adjustment for age, sex, race, and marital status. Based on composite summary scores, the likelihood of complexity was 3.42 (interquartile range, 3.25-3.60) times higher for those in ongoing CPP care (ie, those with 2 or more visits) versus OTP care. Patients in CPP care also were, on average, younger, more obese, and had more prior outpatient visits and hospital stays.

Conclusion
The greater complexity of patients with diabetes seen by CPPs in primary care suggests that CPPs are providing valuable services in comprehensive medication and disease management of complex patients.
Dispositionalism’s (grand)daddy issues: time travelling and perfect masks
Authors: Giannini Giacomo , Donati Donatella 
Published: August 2023

AbstractThere is a tension between Dispositionalism––the view that all metaphysical modality is grounded in actual irreducible dispositional properties––and the possibility of time travel. This is due to the fact that Dispositionalism makes it much harder to solve a potentiality-based version of the grandfather paradox. We first present a potentiality-based version of the grandfather paradox, stating that the following theses are inconsistent: 1) time travel is possible, 2) powers fully ground modality, 3) self-defeating actions are impossible, 4) time-travellers retain their intrinsic powers upon time-travelling, and 5) time-travellers are ordinary agents with basic intrinsic potentialities. We then consider a number of potential solutions, and find them wanting. We argue that the metaphysical impossibility of performing a self-defeating action acts as a necessary perfect mask––while time-travel lets us “slip” the potentiality under the mask, thus generating the contradiction. We conclude considering what are the options for the dispositionalist.
Trends in the Expression of Epistemic Stance in NIH Research Funding Applications: 1985–2020
Authors: Millar Neil , Mathis Bryan , Batalo Bojan , Budgell Brian 
Published: August 2023

Abstract
We report on changes in the expression of epistemic stance in competitive funding applications—that is, applicants’ confidence and certainty towards knowledge and beliefs. We analysed abstracts describing all projects funded by the US National Institutes of Health during the period 1985–2020 for 140 stance features. Trends that we identify indicate that applicants adopt a stance less cautious and less tentative, and increasingly confident, optimistic, and promissory. This is evidenced, for example, by a consistent decline in weak possibility/probability, as expressed by modal verbs (e.g. may, might, should), by epistemic status verbs (indicate, seem) and adverbs (e.g. possible, probable, perhaps); and an increase among features that convey certainty, importance, and empiricism—for example, status verbs (e.g. demonstrate, establish, reveal), and adverbs that emphasize frequency/degree (usually, widely, almost). We argue that (i) these shifts are best understood in relation to increasing salesmanship and structural and cultural shifts within the research ecosystem, and (ii) trends in this dataset are better analysed at the level of individual features, rather than at the level of metadiscoursal categories.
Clock Drawing Test Performance of Young Adults Based on a One-Shot Case Study
Authors: McDaniel Samantha L , Shuster Linda I , Kennedy Mary R T 
Published: August 2023

Abstract

Objective
The clock drawing test (CDT) is being used regularly by medical professionals in a variety of settings to aid in assessing cognitive functioning in adults of all ages. As our technological environment has changed significantly, because of the inception of this measure, the use of and exposure to the analog clock have diminished. We investigated whether young adults, who have grown up in a mainly digital world, can draw and tell time on an analog clock.

Method
Participants aged 18–30 years (N = 80, Mage = 24.2, SD = 3.93), who self-identified as having normal cognition, completed the CDT, as well as setting hands on a pre-drawn clock and identifying analog clock times.

Results
About 25% of participants received a CDT score below the expected range. There was a moderate, positive correlation between analog clock hand setting and time identification in the group who scored below the expected range on the CDT only (rs(16) = 0.472, p = .048). Most participants reported not wearing an analog watch.

Conclusions
Based on these findings, the CDT should be used with caution to screen cognitive functioning in young adults (i.e., aged 18–30 years). Consideration of an alternative approach to screening cognition and modifying cognitive assessments in which the CDT is embedded is recommended for this population. These findings warrant further investigation into CDT performance in the young adult population.