bluuebunny/crossref_metadata_2025_split huggingface dataset:
A review on innovative optical devices for the diagnosis of human soil-transmitted helminthiasis and schistosomiasis: from research and development to commercialization
Authors: Meulah Brice , Bengtson Michel , Lieshout Lisette Van , Hokke Cornelis Hendrik , Kreidenweiss Andrea , Diehl Jan-Carel , Adegnika Ayola Akim , Agbana Temitope Ebenezer 
Published: December 2022

AbstractDiagnosis of soil-transmitted helminth (STH) and schistosome infections relies largely on conventional microscopy which has limited sensitivity, requires highly trained personnel and is error-prone. Rapid advances in miniaturization of optical systems, sensors and processors have enhanced research and development of digital and automated microscopes suitable for the detection of these diseases in resource-limited settings. While some studies have reported proof-of-principle results, others have evaluated the performance of working prototypes in field settings. The extensive commercialization of these innovative devices has, however, not yet been achieved. This review provides an overview of recent publications (2010–2022) on innovative field applicable optical devices which can be used for the diagnosis of STH and schistosome infections. Using an adapted technology readiness level (TRL) scale taking into account the WHO target product profile (TPP) for these diseases, the developmental stages of the devices were ranked to determine the readiness for practical applications in field settings. From the reviewed 18 articles, 19 innovative optical devices were identified and ranked. Almost all of the devices (85%) were ranked with a TRL score below 8 indicating that, most of the devices are not ready for commercialization and field use. The potential limitations of these innovative devices were discussed. We believe that the outcome of this review can guide the end-to-end development of automated digital microscopes aligned with the WHO TPP for the diagnosis of STH and schistosome infections in resource-limited settings.
Turnover in fish species composition is related to water colour of Amazonian rivers
Authors: Borges Sérgio Henrique , D’Aquino Deyse Darse , Victória da Cruz Marcela , Felipe de Souza Ramison 
Published: December 2022

Abstract
Variation in water colour is a remarkable characteristic of Amazonian rivers and reflects their limnological properties and the geomorphology of sub-basins. We present here a literature-based study to examine the relationships between fish species turnover and abiotic properties of Amazonian rivers with contrasting water colours. We analysed fish records and water physicochemical properties (pH, colour, turbidity, dissolved oxygen, ammonia and suspended solids) of eight Amazonian rivers with white-, black- and clearwaters. Rivers with similar water colour shared more fish species than those that contrasted in colour. Increased differences in abiotic parameters imply an increased dissimilarity in fish species composition. Species composition is also related to distance among rivers with high dissimilarity observed in rivers distant to each other. The fish species turnover could be ultimately driven by the geological history of rivers which provides different opportunities to speciation and biotic interchange. Water types likely influence species turnover by selecting fishes with different limits of physiological tolerance and specialized use of different habitat types. Our findings suggest that river water colours are reliable proxies for historical and ecological mechanisms affected fish species distribution. Antropic disturbances of Amazonian rivers with distinct water colours could threaten unique fish assemblages.
Cross-sectional associations between adaptive functioning and social cognitive and neurocognitive functions in adolescents with first-episode, early-onset schizophrenia spectrum disorders
Authors: Jepsen J.R.M. , Rydkjaer J. , Fagerlund B. , Lemvigh Cecilie K. , Pagsberg A.K. , Glenthøj B.Y. , Oranje B. 
Published: December 2022

AbstractBackground:Few studies have explored associations between adaptive functioning and cognition in adolescents with early-onset schizophrenia spectrum disorders (EOS).Methods:Adaptive functioning, cognition, positive, negative, and general symptoms were characterized in adolescents with EOS and healthy controls. A modified scale of negative, respectively, general symptoms was used. Bivariate analyses identified correlates of adaptive functioning to be included in multivariate analysis.Results:Adolescents with EOS showed significant impairments of social- and neurocognitive functions (−0.86 < Cohen´s ds < −0.58) and adaptive functioning (Cohen´s d = −2.23). Visual memory, verbal working memory, processing speed, reaction time, social cognition, and modified negative and general symptoms correlated significantly with adaptive functioning. The multiple regression analysis revealed only verbal working memory as uniquely associated with adaptive functioning (explaining 22.7 % of its variance). Verbal working memory also associated significantly with adaptive functioning in the context of the nonsignificant modified negative and the significant modified general symptoms dimension.Conclusions:Adolescents with first-episode EOS had large impairments in adaptive functioning and moderate to large cognitive deficits. Verbal working memory was an important associate to concurrent adaptive functioning and may be a treatment target for trials to improve cognitive and adaptive functioning in adolescents with EOS.
Herbicide options for sterile oats (Avena ludoviciana) control in winter-planted sorghum
Authors: Mahajan Gulshan , Chauhan Bhagirath Singh 
Published: December 2022

AbstractAustralian grain growers are showing interest in winter-planted sorghum to avoid heat and water stress during the grain-filling stage. Winter-planted sorghum may face competition from winter weeds, including sterile oats, and no herbicides are registered for controlling winter weeds in winter-planted sorghum. The objectives of this study were to (1) identify alternate herbicide options for sterile oats control in winter-sown imidazolinone (IMI)-resistant sorghum and (2) assess the crop injury levels due to herbicides. Sterile oats control with pendimethalin at 0.59 kg ai ha−1, trifluralin at 0.38 kg ai ha−1, and prosulfocarb + S-metolachlor at 2.3 kg ai ha−1 was poor (<30%). Atrazine at 2.7 kg ai ha−1, imazamox + imazapyr at 0.048 kg ai ha−1, and atrazine at 2.7 kg ai ha−1 followed by imazamox + imazapyr at 0.048 kg ai ha−1 reduced the sterile oats biomass by 93%, 96%, and 100% and increased yields by 116%, 136%, and 140%, respectively, compared with nontreated control. Pendimethalin at 0.59 kg ai ha−1 and trifluralin at 0.38 kg ai ha−1 caused phytotoxicity to the crop and gave similar yields to nontreated control. Triallate at 0.8 kg ai ha−1, pyroxasulfone at 0.1 kg ai ha−1, and terbuthylazine at 1.0 kg ai ha−1 provided moderate weed control (44% to 65%) and increased yields by 68%, 108%, and 80%, respectively, compared with nontreated control. This research identified herbicide treatments for the effective control of sterile oats in winter-sown IMI-resistant sorghum that could be used in rotations to reduce the reliance on single herbicide treatments.
Using a Simple Representation of Non‐Structural Carbohydrates Allocation to Predict Wood Growth in Temperate Forests
Authors: Fang Jing , Liu Feng , Shugart Herman H. , Yan Xiaodong 
Published: December 2022

AbstractWood growth is an important process of carbon sequestration and plant physiology in forest ecosystems. Hence, understanding and predicting wood growth is central to quantifying forest carbon cycling. Current dynamic global vegetation models (DGVMs) are mainly driven by carbon inputs (e.g., Gross Primary Production, GPP). However, observations indicate that wood growth is often independent of carbon flux at the annual scale. Here, we revised a DGVM, FORCCHN2 model, to use the active non‐structural carbohydrates (NSC) pool and slow NSC pool (i.e., represented temporary and long‐term NSC storage, respectively), and to integrate the stored NSC with annual wood growth. For the diameter increments (ΔDBH) and aboveground wood growth of 506 trees in 32 plots of Harvard Forest, we tested the NSC allocation coefficients from 5% to 95%. The predictions reproduced 31.2%–55.1% of individual‐tree ΔDBH and 36.8%–43.0% of the aboveground wood increment. Trees of shade‐intolerant species invested more of their available carbon resources (i.e., NSC storage) into wood growth than shade‐tolerant species. Specifically, the shade‐tolerant trees consumed approximately 32% NSC storage by wood growth at the annual scale, while the shade‐intolerant trees consumed about 90%. Our study provides a simple framework that constructs a direct link between annual wood growth and NSC dynamics. The findings highlight the need for research into NSC storage and allocation in trees, particularly in considering NSC allocation strategies of different tree species.
Designing an Optimal GNSS Receiver Network for Space Weather Studies Using Unsupervised Machine Learning Algorithm
Authors: Dashora N. , Harsha P. Babu Sree 
Published: December 2022

AbstractIonospheric maps from an optimal GNSS (global navigation satellite system) receiver network may lead to better understanding and prediction of the equatorial ionospheric gradients. An unsupervised machine learning framework is proposed using the ‐means clustering approach to optimize the available number of GNSS receivers. Beginning with = 15 receivers, the simulations are performed to obtain distribution of the ionospheric pierce points (IPPs) in different grid resolutions up to = 1,000. The algorithm uses a reference grid and subsequently optimizes the locations according to the available IPPs in a cluster. The IPP cluster centers are iteratively optimized based on minimizing the “within cluster sum of squares” error. The IPPs from the optimal receiver locations are used to generate a 2‐D vertical total electron content (VTEC) map using NeQuick‐G model. A one‐sigma confidence limit derived from hourly histogram of the IPPs from the locations is used as decisive criteria for useable grid cells. The number of empty bins thus obtained in a given scenarios provides a percentage normalized empty grid ratio (). A below 10% is used as a threshold to make a decision over eligibility of a scenario to produce a desired VTEC map. Several scenarios are thus tested for varying temporal and spatial grid resolutions, geographical boundaries, GNSS and NavIC satellite configurations, considering the diurnal and annual variation in year 2019. The framework is found to be successful in designing a GNSS network for any geographical region to obtain high resolution 2‐D VTEC maps for space weather applications.
Towards an Optimal Representation of Sub‐Grid Heterogeneity in Land Surface Models
Authors: Torres‐Rojas L. , Vergopolan N. , Herman J. D. , Chaney N. W. 
Published: December 2022

AbstractOne of the persistent challenges of Land Surface Models (LSMs) is to determine a realistic yet efficient sub‐grid representation of heterogeneous landscapes. This is particularly important in emulating the fine‐scale and nonlinear interactions between water, energy, and biogeochemical fluxes at the land surface. In LSMs, landscape heterogeneity can be represented using sub‐grid tiling techniques, which partition macroscale grid cells (e.g., 1°) into smaller units or “tiles.” However, there is currently no formal procedure to define the number of tiles required to adequately represent the heterogeneity of hydrologic processes within a macroscale grid cell, and across spatial scales. To address these challenges, a new approach is presented to diagnose sub‐grid process heterogeneity formally and to infer an optimal number of tiles per macroscale grid cell. The approach is demonstrated using the HydroBlocks modeling framework coupled to Noah‐MP LSM implemented over a 1.0‐degree domain in Western Colorado in the United States. Our results show that (a) a surrogate model can accurately infer the spatial structure of the LSM's time‐averaged hydrological fields, with over 95% overall R2 performance in the validation stage; (b) the optimal configurations for a target level of complexity can be determined using a multi‐objective Pareto efficiency analysis, which includes the simultaneous representation of the multi‐scale heterogeneity of several processes; (c) the use of ∼100 tiles effectively reproduces a quasi‐fully distributed LSM setup (i.e., 83,000 tiles) with approximately 1% of the computational expense. This method provides a path forward to efficiently determine the optimal tile configurations for LSMs while simultaneously considering the spatial heterogeneity and spatial accuracy of hydrologic processes.
A bispecific nanobody dimer broadly neutralizes SARS-CoV-1 & 2 variants of concern and offers substantial protection against Omicron via low-dose intranasal administration
Authors: Ma Huan , Zhang Xinghai , Zeng Weihong , Zhou Junhui , Chi Xiangyang , Chen Shaohong , Zheng Peiyi , Wang Meihua , Wu Yan , Zhao Dan , Gong Fanwu , Lin Haofeng , Sun Hancong , Yu Changming , Shi Zhengli , Hu Xiaowen , Zhang Huajun , Jin Tengchuan , Chiu Sandra 
Published: December 2022

AbstractCurrent SARS-CoV-2 Omicron subvariants impose a heavy burden on global health systems by evading immunity from most developed neutralizing antibodies and vaccines. Here, we identified a nanobody (aSA3) that strongly cross-reacts with the receptor binding domain (RBD) of both SARS-CoV-1 and wild-type (WT) SARS-CoV-2. The dimeric construct of aSA3 (aSA3-Fc) tightly binds and potently neutralizes both SARS-CoV-1 and WT SARS-CoV-2. Based on X-ray crystallography, we engineered a bispecific nanobody dimer (2-3-Fc) by fusing aSA3-Fc to aRBD-2, a previously identified broad-spectrum nanobody targeting an RBD epitope distinct from aSA3. 2-3-Fc exhibits single-digit ng/mL neutralizing potency against all major variants of concerns including BA.5. In hamsters, a single systemic dose of 2-3-Fc at 10 mg/kg conferred substantial efficacy against Omicron infection. More importantly, even at three low doses of 0.5 mg/kg, 2-3-Fc prophylactically administered through the intranasal route drastically reduced viral RNA loads and completely eliminated infectious Omicron particles in the trachea and lungs. Finally, we discovered that 2(Y29G)-3-Fc containing a Y29G substitution in aRBD-2 showed better activity than 2-3-Fc in neutralizing BA.2.75, a recent Omicron subvariant that emerged in India. This study expands the arsenal against SARS-CoV-1, provides potential therapeutic and prophylactic candidates that fully cover major SARS-CoV-2 variants, and may offer a simple preventive approach against Omicron and its subvariants.
Rapid evolution of hybrid breakdown following recent divergence with gene flow in Senecio species on Mount Etna, Sicily
Authors: Wong Edgar L. Y. , Nevado Bruno , Hiscock Simon J. , Filatov Dmitry A. 
Published: December 2022

AbstractHow do nascent species evolve reproductive isolation during speciation with on-going gene flow? How do hybrid lineages become stabilised hybrid species? While commonly used genomic approaches provide an indirect way to identify species incompatibility factors, synthetic hybrids generated from interspecific crosses allow direct pinpointing of phenotypic traits involved in incompatibilities and the traits that are potentially adaptive in hybrid species. Here we report the analysis of phenotypic variation and hybrid breakdown in crosses between closely-relatedSenecio aethnensisandS. chrysanthemifolius, and their homoploid hybrid species, S. squalidus. The two former species represent a likely case of recent (<200 ky) speciation with gene flow driven by adaptation to contrasting conditions of high- and low-elevations on Mount Etna, Sicily. As these species form viable and fertile hybrids, it remains unclear whether they have started to evolve reproductive incompatibility. Our analysis represents the first study of phenotypic variation and hybrid breakdown involving multipleSeneciohybrid families. It revealed wide range of variation in multiple traits, including the traits previously unrecorded in synthetic hybrids. Leaf shape, highly distinct betweenS. aethnensisandS. chrysanthemifolius, was extremely variable in F2hybrids, but more consistent inS. squalidus. Our study demonstrates that interspecific incompatibilities can evolve rapidly despite on-going gene flow between the species. Further work is necessary to understand the genetic bases of these incompatibilities and their role in speciation with gene flow.
Urgency and necessity of Epstein-Barr virus prophylactic vaccines
Authors: Zhong Ling , Krummenacher Claude , Zhang Wanlin , Hong Junping , Feng Qisheng , Chen Yixin , Zhao Qinjian , Zeng Mu-Sheng , Zeng Yi-Xin , Xu Miao , Zhang Xiao 
Published: December 2022

AbstractEpstein-Barr virus (EBV), a γ-herpesvirus, is the first identified oncogenic virus, which establishes permanent infection in humans. EBV causes infectious mononucleosis and is also tightly linked to many malignant diseases. Various vaccine formulations underwent testing in different animals or in humans. However, none of them was able to prevent EBV infection and no vaccine has been approved to date. Current efforts focus on antigen selection, combination, and design to improve the efficacy of vaccines. EBV glycoproteins such as gH/gL, gp42, and gB show excellent immunogenicity in preclinical studies compared to the previously favored gp350 antigen. Combinations of multiple EBV proteins in various vaccine designs become more attractive approaches considering the complex life cycle and complicated infection mechanisms of EBV. Besides, rationally designed vaccines such as virus-like particles (VLPs) and protein scaffold-based vaccines elicited more potent immune responses than soluble antigens. In addition, humanized mice, rabbits, as well as nonhuman primates that can be infected by EBV significantly aid vaccine development. Innovative vaccine design approaches, including polymer-based nanoparticles, the development of effective adjuvants, and antibody-guided vaccine design, will further enhance the immunogenicity of vaccine candidates. In this review, we will summarize (i) the disease burden caused by EBV and the necessity of developing an EBV vaccine; (ii) previous EBV vaccine studies and available animal models; (iii) future trends of EBV vaccines, including activation of cellular immune responses, novel immunogen design, heterologous prime-boost approach, induction of mucosal immunity, application of nanoparticle delivery system, and modern adjuvant development.
Autonomous driving using imitation learning with look ahead point for semi structured environments
Authors: Ahn Joonwoo , Kim Minsoo , Park Jaeheung 
Published: December 2022

AbstractSemi-structured environments are difficult for autonomous driving because there are numerous unknown obstacles in drivable area without lanes, and its width and curvature considerably change. In such environments, searching for a path on a real-time is difficult, and localization data are inaccurate, reducing path tracking accuracy. Instead, alternative methods that reactively avoid obstacles in real-time using candidate paths or an artificial potential field have been studied. However, these require heuristics to identify specific parameters for handling various environments and are vulnerable to inaccurate input data. To address these limitations, this study proposes a method in which a vehicle drives toward drivable area using vision and deep learning. The proposed imitation learning method learns the look-ahead point where the vehicle should reach on a vision-based occupancy grid map to obtain a safe policy with a clear state action pattern relationship. Furthermore, using this point, the data aggregation (DAgger) algorithm with weighted loss function is proposed, which imitates expert behavior more accurately, especially in unsafe or near-collision situations. Experimental results in actual semi-structured environments demonstrated the limitations of general model-based methods and the effectiveness of the proposed imitation learning method. Moreover, simulation experiments showed that DAgger with the weight obtains a safer policy than existing DAgger algorithms.
Energetic and atomic structural analyses of the screw dislocation absorption at tilt grain boundaries in BCC-Fe
Authors: Kura Chiharu , Wakeda Masato , Hayashi Kazushi , Ohmura Takahito 
Published: December 2022

AbstractThe dislocation–grain boundary (GB) interaction plays an important role in GB-related plasticity. Therefore, an atomistic investigation of the interaction provides a deeper understanding of the strength and fracture of polycrystalline metals. In this study, we investigated the absorption of a screw dislocation with a Burgers vector perpendicular to the GB normal and the corresponding symmetric tilt grain boundaries (STGBs) in BCC-Fe based on molecular static simulations focusing on the STGB-dislocation interaction energy and atomistic structural changes at GB. The STGB-screw dislocation interaction depends on the energetical stability of the STGB against the GB shift along the Burgers vector direction. When the interaction exhibited a large attractive interaction energy, the dislocation dissociation and the GB shift along the Burgers vector direction occurred simultaneously. The interaction energy reveals that the interaction depends on the energetical stability of the STGB in terms of the GB shift in addition to the geometrical descriptor of the GB type, such as the Σ value. The same behavior was also obtained in the reaction when the second dislocation was introduced. We also discuss the screw dislocation absorption and rearrangement of the GB atomistic structure in STGB from an energetic viewpoint.
Effective screening strategies for safe opening of universities under Omicron and Delta variants of COVID-19
Authors: Rabil Marie Jeanne , Tunc Sait , Bish Douglas R. , Bish Ebru K. 
Published: December 2022

AbstractAs new COVID-19 variants emerge, and disease and population characteristics change, screening strategies may also need to change. We develop a decision-making model that can assist a college to determine an optimal screening strategy based on their characteristics and resources, considering COVID-19 infections/hospitalizations/deaths; peak daily hospitalizations; and the tests required. We also use this tool to generate screening guidelines for the safe opening of college campuses. Our compartmental model simulates disease spread on a hypothetical college campus under co-circulating variants with different disease dynamics, considering: (i) the heterogeneity in disease transmission and outcomes for faculty/staff and students based on vaccination status and level of natural immunity; and (ii) variant- and dose-dependent vaccine efficacy. Using the Spring 2022 academic semester as a case study, we study routine screening strategies, and find that screening the faculty/staff less frequently than the students, and/or the boosted and vaccinated less frequently than the unvaccinated, may avert a higher number of infections per test, compared to universal screening of the entire population at a common frequency. We also discuss key policy issues, including the need to revisit the mitigation objective over time, effective strategies that are informed by booster coverage, and if and when screening alone can compensate for low booster coverage.