bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of deep convolutional neural network models for species identification of forensically-important fly maggots based on images of posterior spiracles
Authors: Apasrawirote Darlin , Boonchai Pharinya , Muneesawang Paisarn , Nakhonkam Wannacha , Bunchu Nophawan 
Published: March 2022

AbstractForensic entomology is the branch of forensic science that is related to using arthropod specimens found in legal issues. Fly maggots are one of crucial pieces of evidence that can be used for estimating post-mortem intervals worldwide. However, the species-level identification of fly maggots is difficult, time consuming, and requires specialized taxonomic training. In this work, a novel method for the identification of different forensically-important fly species is proposed using convolutional neural networks (CNNs). The data used for the experiment were obtained from a digital camera connected to a compound microscope. We compared the performance of four widely used models that vary in complexity of architecture to evaluate tradeoffs in accuracy and speed for species classification including ResNet-101, Densenet161, Vgg19_bn, and AlexNet. In the validation step, all of the studied models provided 100% accuracy for identifying maggots of 4 species including Chrysomya megacephala (Diptera: Calliphoridae), Chrysomya (Achoetandrus) rufifacies (Diptera: Calliphoridae), Lucilia cuprina (Diptera: Calliphoridae), and Musca domestica (Diptera: Muscidae) based on images of posterior spiracles. However, AlexNet showed the fastest speed to process the identification model and presented a good balance between performance and speed. Therefore, the AlexNet model was selected for the testing step. The results of the confusion matrix of AlexNet showed that misclassification was found between C. megacephala and C. (Achoetandrus) rufifacies as well as between C. megacephala and L. cuprina. No misclassification was found for M. domestica. In addition, we created a web-application platform called thefly.ai to help users identify species of fly maggots in their own images using our classification model. The results from this study can be applied to identify further species by using other types of images. This model can also be used in the development of identification features in mobile applications. This study is a crucial step for integrating information from biology and AI-technology to develop a novel platform for use in forensic investigation.
A numerical algorithm for modeling cellular rearrangements in tissue morphogenesis
Authors: Mohammad Rhudaina Z. , Murakawa Hideki , Svadlenka Karel , Togashi Hideru 
Published: March 2022

AbstractAmong morphological phenomena, cellular patterns in developing sensory epithelia have gained attention in recent years. Although physical models for cellular rearrangements are well-established thanks to a large bulk of experimental work, their computational implementation lacks solid mathematical background and involves experimentally unreachable parameters. Here we introduce a level set-based computational framework as a tool to rigorously investigate evolving cellular patterns, and study its mathematical and computational properties. We illustrate that a compelling feature of the method is its ability to correctly handle complex topology changes, including frequent cell intercalations. Combining this accurate numerical scheme with an established mathematical model, we show that the proposed framework features minimum possible number of parameters and is capable of reproducing a wide range of tissue morphological phenomena, such as cell sorting, engulfment or internalization. In particular, thanks to precise mathematical treatment of cellular intercalations, this method succeeds in simulating experimentally observed development of cellular mosaic patterns in sensory epithelia.
Integration of experimental data and use of automated fitting methods in developing protein force fields
Authors: Polêto Marcelo D. , Lemkul Justin A. 
Published: March 2022

AbstractThe development of accurate protein force fields has been the cornerstone of molecular simulations for the past 50 years. During this period, many lessons have been learned regarding the use of experimental target data and parameter fitting procedures. Here, we review recent advances in protein force field development. We discuss the recent emergence of polarizable force fields and the role of electronic polarization and areas in which additive force fields fall short. The use of automated fitting methods and the inclusion of additional experimental solution data during parametrization is discussed as a means to highlight possible routes to improve the accuracy of force fields even further.
A topological kagome magnet in high entropy form
Authors: Min Lujin , Sretenovic Milos , Heitmann Thomas W. , Valentine Tyler W. , Zu Rui , Gopalan Venkatraman , Rost Christina M. , Ke Xianglin , Mao Zhiqiang 
Published: March 2022

AbstractTopological kagome magnets RMn6Sn6 (R = rare earth element) attract numerous interests due to their non-trivial band topology and room-temperature magnetism. Here, we report a high entropy version of kagome magnet, (Gd0.38Tb0.27Dy0.20Ho0.15)Mn6Sn6. Such a high entropy material exhibits multiple spin reorientation transitions, which is not seen in all the related parent compounds and can be understood in terms of competing magnetic interactions enabled by high entropy. Furthermore, we also observed an intrinsic anomalous Hall effect, indicating that the high entropy phase preserves the non-trivial band topology. These results suggest that high entropy may provide a route to engineer the magnetic structure and expand the horizon of topological materials.
Geothermal energy as a means to decarbonize the energy mix of megacities
Authors: Vargas Carlos A. , Caracciolo Luca , Ball Philip J. 
Published: March 2022

AbstractThe global number of megacities is projected to increase from 33 to 43 by 2030. Megacities are critical for the world’s economy; however, their resource management is particularly challenging. The increase of energy demand, in parallel to population growth and climate change, requires urgent investment in sustainable energies. We examine the megacities of Bogotá, Los Angeles, and Jakarta and reveal that the potential geothermal resource base is enough to cover the residential electricity demand by 1.14, 4.25, 1.84 times, respectively. Geothermal energy, a clean baseload resource independent from weather conditions, could significantly contribute to energy needs, improved air quality, and the decarbonization of the world’s megacities. We conclude that it is critical that governments and public are educated about the benefits of geothermal. Moreover, those energy policies coupled with investment in research and development are needed to ensure geothermal is successfully integrated into the future energy mix.
Online Training Modules for Teaching Assessment Skills to Graduate Student Clinicians
Authors: Radville Katharine M. , Larrivee Emilie C. , Baron Lauren S. , Kelley-Nazzaro Patricia , Christodoulou Joanna A. 
Published: March 2022

Purpose:
Assessment is a crucial skill for speech-language pathologists, who rely on standardized tests to identify characteristics of speech, language, hearing, literacy, and related skill sets. Training in assessment administration is an integral part of graduate education that lays the foundation for appropriate use of these tools. Teaching students to administer standardized assessments is time intensive, can vary depending on student learning pace, and involves both general and test-specific knowledge. The current pilot study investigated the effectiveness of researcher-developed and scalable online training modules for beginning and advanced graduate students for knowledge and self-efficacy outcomes.

Method:

Graduate students (
n
= 61) across four cohorts (two beginning and two advanced) were trained using online, asynchronous assessment training modules. The modules addressed the administration of standardized assessments using written tutorials, video demonstrations, and quizzes. Students completed pre- and posttests on knowledge and self-efficacy for administering and scoring the trained assessments before and after the online training modules.

Results:
We found significant pretest to posttest gains in specific assessment-related knowledge for beginning and advanced groups. Following completion of the training modules, beginning graduate students demonstrated increased self-efficacy for general assessment principles, whereas advanced graduate students started and remained high in self-efficacy at posttest.

Conclusions:
Using researcher-developed online training modules, both beginning and advanced graduate students improved knowledge for assessment skills. These training modules can be used as a model for developing teaching materials across a range of assessments and related topics that are scalable in the context of remote teaching and learning.
Synthesis of P- and S-Stereogenic Compounds via Enantioselective C–H Functionalization
Authors: Qian Pu-Fan , Li Jun-Yi , Zhou Tao , Shi Bing-Feng 
Published: March 2022

AbstractTransition metal-catalyzed enantioselective C–H functionalization has emerged as an efficient and powerful strategy to access various chiral molecules. Recently, this strategy has also provided a complementary pathway to the construction of P- and S-stereogenic compounds. In this short review, we summarize the development and applications of various catalytic systems: Pd(II)/mono-N-protected amino acids (MPAA), Pd(0)/trivalent phosphorus chiral ligands, chiral cyclopentadienyl-ligated metal catalysts [CpxM(III)] (M = Rh, Ir), half-sandwich d6 Ir(III) and Ru(II) with a chiral carboxylic acid (CCA) ligand, Ir(I)/chiral bidentate boryl ligand, and Ir(I)/chiral cation, for accessing these chiral compounds via enantioselective C–H functionalization. 1	Introduction2	Pd(II)/Mono-N-protected Amino Acids3	Pd(0)/Trivalent Phosphorus Chiral Ligands4	Chiral Cyclopentadienyl-Ligated Metal Catalysts [CpxM(III)] (M = Rh, Ir)5	Half-sandwich d6 Ir(III) and Ru(II) with a Chiral Carboxylic Acid (CCA) Ligand6	Ir(I)/Chiral Bidentate Boryl Ligand7	Ir(I)/Chiral Cation8	Conclusion and Outlook
Assessment of Laparoscopic Posterior Mesh Rectopexy for Complete Rectal Prolapse: A Case Series with Review of Literature
Authors: Chawda Vishal , Joshi Abhijit 
Published: March 2022

Abstract
Background Trans-abdominal rectopexy for complete rectal prolapse (CRP) reportedly yields more definitive results as compared with trans-perineal surgery. In the era of minimal access surgery, minimally invasive laparoscopic rectopexy has become a popular treatment option for patients with rectal prolapse (RP). Herein, we describe our preferred surgical procedure for the correction of RP and evaluate its results. We further aim to perform a comparative assessment between perioperative outcomes achieved with open and laparoscopic applications of this technique.
Materials and methods This was a retrospective cross-sectional observational study conducted at a tertiary health care center in Maharashtra, India. We studied cases of RP who underwent laparoscopic posterior mesh rectopexy during the past 15 years (2005–2021), in our institution, operated upon by a single surgeon.
Results Of the total 14 patients, 12 were managed with laparoscopic posterior mesh rectopexy. The remaining two underwent laparoscopic suture rectopexy. The mean operative time was 120 minutes. Constipation improved among 28.57%, remained the same among 21.42%, and worsened among 35.71% patients. No intra-operative blood transfusion was required. Mean length of hospital stay was 4 days. There were no recurrences over a mean follow-up period of 94 months, i.e., 7.83 years (range 7–197 months).
Conclusions Laparoscopic posterior rectopexy can be safely performed in older patients to achieve early postoperative ambulation and significantly shorten the hospital stay. It may, therefore, be considered an effective treatment for CRP and urinary dysfunction. However, the incidence of de-novo constipation and worsening of pre-existing constipation is significantly high.
Yield and zinc accumulation response of basmati rice to incremental zinc fertilisation of a zinc-deficient soil
Authors: Verma Gayatri , Dhaliwal S. S. , Sharma Vivek 
Published: March 2022

Zinc (Zn) deficiency in basmati rice grown under submerged conditions leads to decrease in yield and nutritional quality. Fertilisation with Zn is a cost-effective and rapid way to increase crop productivity with Zn-enriched grain. A field experiment was conducted with five Zn levels (0, 5, 10, 20 and 40 kg ha−1) for two consecutive years to assess the effects of Zn fertilisation on yield, Zn content and accumulation in basmati rice grown in a Zn-deficient soil. Maximum grain and straw yields were measured with Zn application of 40 kg ha−1, although statistically similar to yields with applications of 10 and 20 kg Zn ha−1. Increases in average yield compared with the control varied from 14.8% to 27.7% for grain and from 20% to 33.5% for straw with Zn application treatments. Accumulation of Zn in basmati rice grains was highest with Zn application of 40 kg ha−1, although not significantly different from accumulation with 10 and 20 kg Zn ha−1. Indexes of Zn use efficiency were as follows: agronomic efficiency 21–88 kg kg−1, physiological efficiency 6.93–7.39 t kg−1, grain physiological efficiency 14.95–15.21 t kg−1, apparent recovery efficiency 0.97–4.19%, and utilisation efficiency 6.7–31.0 t kg−1. All of these were higher at lower Zn levels and decreased at increasing levels of Zn. The highest benefit–cost ratio occurred with Zn application of 10 kg ha−1. Therefore, we conclude that Zn application of 10 kg ha−1 was the best treatment in terms of high grain yield, maximum benefit–cost ratio, and Zn accumulation in a Zn-deficient soil.
Is it you you’re looking for?
Authors: Westbury Chris , Wurm Lee H. 
Published: March 2022

Abstract
Previous evidence has implicated personal relevance as a predictive factor in lexical access. Westbury (2014) showed that personally relevant words were rated as having a higher
subjective familiarity than words that were not personally relevant, suggesting that personally relevant words are processed more
fluently than less personally relevant words. Here we extend this work by defining a measure of personal relevance that does not
rely on human judgments but is rather derived from first-order co-occurrence of words with the first-person singular personal
pronoun, I. We show that words estimated as most personally relevant are recognized more quickly, named faster,
judged as more familiar, and used by infants earlier than words that are less personally relevant. Self-relevance is also a strong
predictor of several measures that are usually measured only by human judgments or their computational estimates, such as
subjective familiarity, age of acquisition, imageability, concreteness, and body-object interaction. We have made all
self-relevance estimates (as well as the raw data and code from our experiments) available at https://osf.io/gdb6h/.
Some Translation Studies informed suggestions for further balancing methodologies for machine translation quality evaluation
Authors: Krüger Ralph 
Published: March 2022

Abstract
This article intends to contribute to the current debate on the quality of neural machine translation (NMT) vs. (professional) human translation quality, where recently claims concerning (super)human performance of NMT systems have emerged. The article will critically analyse some current machine translation (MT) quality evaluation methodologies employed in studies claiming such performance of their MT systems. This analysis aims to identify areas where these methodologies are potentially biased in favour of MT and hence may overvalue MT performance while undervaluing human translation performance. Then, the article provides some Translation Studies informed suggestions for improving or debiasing these methodologies in order to arrive at a more balanced picture of MT vs. (professional) human translation quality.
A review on SRAM-based computing in-memory: Circuits, functions, and applications
Authors: Lin Zhiting , Tong Zhongzhen , Zhang Jin , Wang Fangming , Xu Tian , Zhao Yue , Wu Xiulong , Peng Chunyu , Lu Wenjuan , Zhao Qiang , Chen Junning 
Published: March 2022

Abstract
Artificial intelligence (AI) processes data-centric applications with minimal effort. However, it poses new challenges to system design in terms of computational speed and energy efficiency. The traditional von Neumann architecture cannot meet the requirements of heavily data-centric applications due to the separation of computation and storage. The emergence of computing in-memory (CIM) is significant in circumventing the von Neumann bottleneck. A commercialized memory architecture, static random-access memory (SRAM), is fast and robust, consumes less power, and is compatible with state-of-the-art technology. This study investigates the research progress of SRAM-based CIM technology in three levels: circuit, function, and application. It also outlines the problems, challenges, and prospects of SRAM-based CIM macros.
Tunable crystal structure of Cu–Zn–Sn–S nanocrystals for improving photocatalytic hydrogen evolution enabled by copper element regulation
Authors: Yin Zhe , Hu Min , Liu Jun , Fu Hao , Wang Zhijie , Tang Aiwei 
Published: March 2022

Abstract
Hydrogen energy is a powerful and efficient energy resource, which can be produced by photocatalytic water splitting. Among the photocatalysis, multinary copper-based chalcogenide semiconductor nanocrystals exhibit great potential due to their tunable crystal structures, adjustable optical band gap, eco-friendly, and abundant resources. In this paper, Cu–Zn–Sn–S (CZTS) nanocrystals with different Cu content have been synthesized by using the one-pot method. By regulating the surface ligands, the reaction temperature, and the Cu content, kesterite and hexagonal wurtzite CZTS nanocrystals were obtained. The critical factors for the controllable transition between two phases were discussed. Subsequently, a series of quaternary CZTS nanocrystals with different Cu content were used for photocatalytic hydrogen evolution. And their band gap, energy level structure, and charge transfer ability were compared comprehensively. As a result, the pure hexagonal wurtzite CZTS nanocrystals have exhibited an improved photocatalytic hydrogen evolution activity.
Modelling and fabrication of wide temperature range Al0.24Ga0.76As/GaAs Hall magnetic sensors
Authors: Fan Hua , Yue Huichao , Mao Jiangmin , Peng Ting , Zuo Siming , Feng Quanyuan , Wei Qi , Heidari Hadi 
Published: March 2022

Abstract
Silicon Hall-effect sensors have been widely used in industry and research fields due to their straightforward fabrication process and CMOS compatibility. However, as their material property limitations, technicians usually implement complex CMOS circuits to improve the sensors’ performance including temperature drift and offset compensation for fitting tough situation, but it is no doubt that it increases the design complexity and the sensor area. Gallium arsenide (GaAs) is a superior material of Hall-effect device because of its large mobility and stable temperature characteristics. Concerning there is no specified modelling of GaAs Hall-effect device, this paper investigated its modelling by using finite element method (FEM) software Silvaco TCAD® to help and guide GaAs Hall-effect device fabrication. The modeled sensor has been fabricated and its experimental results are in agreement with the simulation results. Comparing to our previous silicon Hall-effect sensor, the GaAs Hall-effect sensor demonstrates potential and reliable benchmark for the future Hall magnetic sensor developments.
A GPU-based general numerical framework for plasma simulations in terms of microscopic kinetic equations with full collision terms
Authors: ZHANG Junjie , ZHANG Xin , PENG Guoliang , REN Zeping 
Published: March 2022

Abstract
We have proposed a general numerical framework for plasma simulations on graphics processing unit clusters based on microscopic kinetic equations with full collision terms. Our numerical algorithm consistently deals with both long-range (classical forces in the Vlasov term) and short-range (quantum processes in the collision term) interactions. Providing the relevant particle masses, charges and types (classical, fermionic or bosonic), as well as the external forces and the matrix elements (in the collisional integral), the algorithm consistently solves the coupled multi-particle kinetic equations. Currently, the framework is being tested and applied in the field of relativistic heavy-ion collisions; extensions to other plasma systems are straightforward. Our framework is a potential and competitive numerical platform for consistent plasma simulations.
Effectiveness of acute geriatric unit care on functional decline, clinical and process outcomes among hospitalised older adults with acute medical complaints: a systematic review and meta-analysis
Authors: O’Shaughnessy Íde , Robinson Katie , O’Connor Margaret , Conneely Mairéad , Ryan Damien , Steed Fiona , Carey Leonora , Leahy Aoife , Shanahan Elaine , Quinn Colin , Galvin Rose 
Published: March 2022

Abstract

Background
the aim of this systematic review and meta-analysis was to update and synthesise the totality of research evidence on the effectiveness of acute geriatric unit (AGU) care for older adults admitted to hospital with acute medical complaints.

Methods
MEDLINE, CINAHL, CENTRAL and Embase databases were systematically searched from 2008 to February 2022. Screening, data extraction and quality grading were undertaken by two reviewers. Only trials with a randomised design comparing AGU care and conventional care units were included. Meta-analyses were performed in Review Manager 5.4 and the Grading of Recommendations, Assessment, Development and Evaluations framework was used to assess the certainty of evidence. The primary outcome was incidence of functional decline between baseline 2-week prehospital admission status and discharge and at follow-up.

Results
11 trials recruiting 7,496 participants across three countries were included. AGU care resulted in a reduction in functional decline at 6-month follow-up (risk ratio (RR) 0.79, 95% confidence interval (CI) 0.66–0.93; moderate certainty evidence) and an increased probability of living at home at 3-month follow-up (RR 1.06, 95% CI 0.99–1.13; high certainty evidence). AGU care resulted in little or no difference in functional decline at hospital discharge or at 3-month follow-up, length of hospital stay, costs, the probability of living at home at discharge, mortality, hospital readmission, cognitive function or patient satisfaction.

Conclusions
AGU care improves clinical and process outcomes for hospitalised older adults with acute medical complaints. Future research should focus on greater inclusion of clinical and patient reported outcome measures.