bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative gastrointestinal organ lengths among Amazonian primates (Primates: Platyrrhini)
Authors: Jesus Anamélia de Souza , El Bizri Hani R. , Fa Julia E. , Valsecchi João , Rabelo Rafael Magalhães , Mayor Pedro 
Published: April 2023

AbstractObjectivesThe morphological features of the gastrointestinal tract (GIT) in mammals reflect a species' food niche breadth and dietary adaptations. For many wild mammals, the relationship between the structure of the GIT and diet is still poorly understood, for example, the GIT for frugivorous primates is usually classified as unspecialized and homogeneous. Here, we compare the GIT structure of 13 primate species from the three families of extant platyrrhines (Atelidae, Pitheciidae, and Cebidae) in Amazonia, and discuss possible evolutionary adaptations to different diets and trophic niches.MethodsWe measured the length of the esophagus, stomach, small intestine, large intestine, cecum, colon, and rectum of the digestive tracts of 289 primate specimens. We determined the allometric relationships of the different tubular organs with the total length of the GIT as a proxy of specimen body size. Allometric parameters were used to establish the quotients of differentiation of every organ for each primate specimen.ResultsThere was a high differentiation in structure of the digestive organs among genera. Alouatta specimens clearly separated from the other genera based on dissimilarities in gastric, colonic, and rectal quotients, likely linked to the fermentation of plant contents. In contrast, all cebines (Sapajus, Cebus, and Saimiri) and Cacajao species had similar small intestine quotients, which is expected due to their high rates of animal matter consumed.ConclusionsWe show that diverse adaptations in digestive structure exist among frugivorous primates, which in turn reflect different dietary patterns within this group that may enable the geographic coexistence of different primate species.
Characteristic Features of Gravitational Wave Lensing as Probe of Lens Mass Model
Authors: Cremonese Paolo , Mota David Fonseca , Salzano Vincenzo 
Published: April 2023

AbstractTo recognize gravitational wave lensing events and being able to differentiate between similar lens models will be of crucial importance once one will be observing several lensing events of gravitational waves per year. In this work, the lensing of gravitational waves is studied in the context of LISA sources and wave‐optics regime. While different papers before the studied microlensing effects enhanced by simultaneous strong lensing, the focus is on frequency (time) dependent phase effects produced by one lens that will be visible with only one lensed signal. It is shows how, in the interference regime (i.e., when interference patterns are present in the lensed image), one is able to i) distinguish a lensed waveform from an unlensed one, and ii) differentiate between different lens models. In pure wave‐optics, on the other hand, the feasibility of the study depends on the signal‐to‐noise ratio of the signal and/or the amplitude of the lensing effect. To achieve these goals, the phase of the amplification factor of the different lens models and its effect on the unlensed waveform is studied, and the signal‐to‐noise calculation to provide some quantitative examples is exploited.
Decentralized linear–quadratic–Gaussian control of networked control systems with asymmetric information
Authors: Wang Na , Liang Xiao , Wang Haixia , Zhang Qiyan , Lu Xiao 
Published: April 2023

AbstractThe decentralized linear–quadratic–Gaussian (LQG) control problem for networked control systems (NCSs) with asymmetric information is investigated, where controller 1 shares its historical information with controller 2, and not vice versa. The asymmetry of the information structure leads to the coupling between controller 2 and estimator 1, and hence the classical separation principle fails. Through the assumption of linear control strategy, the coupling between controller 2 and estimator 1 (CCE) is decoupled, but the estimation gain is still coupled with the control gain. It is noted that the control gain conforms to the backward Riccati equation while estimation gain abides by the forward equation, which is computationally challenging. Applying the stochastic maximum principle, the solvability of the decentralized LQG control problem is reduced to that of corresponding forward and backward stochastic difference equations (FBSDEs). Further, necessary and sufficient conditions for the solvability of optimal control problem are presented by two Riccati equations, one of which is nonsymmetric. Moreover, a novel iterative forward method is proposed to calculate the coupled backward control gain and forward estimation gain.
Synthesis and structure activity relationship studies of 2‐amino‐4‐arylsulfonyl‐5,6,7,8‐tetrahydroquinazolines as 5‐HT6 receptor antagonists
Authors: Shim Young Sun , Lee Yeyong , Wang Hyun Jung , Tae Jinsung , Park Jonghyun , Choo Hyunah , Rhim Hyewhon , Nam Ghilsoo 
Published: April 2023

AbstractA novel series of 4‐arylthio‐ or 4‐arylsulfonyl‐substituted 2‐amino‐5,6,7,8‐tetrahydroquiazolines was synthesized and evaluated for serotonin receptor subtype 6 (5‐HT6R) antagonistic effects in vitro. The structure activity relationships (SAR) of this series were discussed on the basis of in vitro activity. Among the derivatives synthesized in the present study, the lead compound, 7a, having sulfonyl functionality at the 4‐position and N‐methylpiperazine at the 2‐position of the core structure showed the most potent 5‐HT6 receptor inhibitory activity in vitro and good metabolic stability without CYP liability.
Green resource orchestration: A critical appraisal of the use of resource orchestration in environmental management research, and a research agenda for future study
Authors: Andersén Jim 
Published: April 2023

AbstractResource orchestration (RO) is a strategic management framework that details various processes by which how firms structure, bundle, and leverage resources. This study reviews how RO has been considered in environmental management research. The review highlights some limitations on how RO has been used in studies on environmental management, and it also illustrates a lack of knowledge accumulation in the field. To realize the full potential of RO, the concept of green RO is developed. Green RO (GRO) is defined as a firm's capability to coordinate and manage the structuring of resources and the bundling and leveraging of capabilities to create economic value for the company while simultaneously creating environmental benefits. Three main research areas for GRO are described: GRO as an organizational or managerial meta‐capability, management of specific GRO processes, and the synchronization of several GRO processes.
Risk factors for mortality in fulminant acute necrotizing encephalopathy following influenza A in an adolescent boy
Authors: Khosroshahi Nahideh , Rezaei Darya , Emami Farnoosh , Eftekhari Kambiz 
Published: April 2023

Key clinical MessageAcknowledging the risk factors of mortality and morbidity of each disease is effective for its final outcome. Recognizing these cases can have the value of preventing the occurrence of unfortunate events, such as not recommending the use diclofenac in an influenza epidemic.
Fetal hypertrophic cardiomyopathy with elevated middle cerebral artery peak systolic velocity (MCA PSV): A potentially grim association
Authors: Keller Nathan A. , Bracero Luis A. , Kouba Insaf , Talwar Rohit , Blitz Matthew J. 
Published: April 2023

Key Clinical MessageAn elevated middle cerebral artery peak systolic velocity (MCA PSV) in the setting of nondiabetic hypertrophic cardiomyopathy may portend an especially poor prognosis.
Identification of immune‐related genes contributing to head and neck squamous cell carcinoma development using weighted gene co‐expression network analysis
Authors: Guo Qiaojuan , Lu Tianzhu , Xu Hanchuan , Luo Qingfeng , Liu Zhiliang , Jiang Sicong , Pan Jianji , Lin Shaojun , Lin Mengyao , Guo Fang 
Published: April 2023

AbstractBackgroundThis study aimed to identify genes related to the degree of immune cell infiltration in head and neck squamous cell carcinoma (HNSCC), explore their new biological functions, and evaluate their diagnostic and prognostic value in HNSCC.MethodsTranscriptomic data from The Cancer Genome Atlas (TCGA) HNSCC dataset was used to screen differentially expressed genes between tumors and normal tissues, followed by weighted correlation network analysis (WGCNA) to identify immune‐related modules. Differential gene expression, immune cell infiltration, and survival analyses were performed to screen key genes. The expression of these key genes was validated in Oncomine and gene expression omnibus (GEO) datasets and by immunohistochemistry (IHC).Results1869 and 1578 genes were significantly upregulated and downregulated in HNSCC. WGCNA showed that the brown module was associated with the most significant number of immune‐related genes. PPI network analysis demonstrated that PPL, SCEL, KRT4, KRT24, KRT78, KRT13, SPRR3, TGM3, CRCT1, and CRNN were key components in the brown module. Furthermore, the expression levels of KRT4, KRT78, KRT13, and SPRR3 in HNSCC correlated with infiltration levels of CD8+ T cells and macrophages. Survival analyses revealed that the expression of KRT78, KRT13, and SPRR3 in HNSCC correlated with overall survival (OS). The IHC assay indicated that KRT13 (p = .042), KRT78 (p < .001), and SPRR3 (p = .022) protein expression levels in HNSCC were significantly lower than in normal tissues. Analysis of GSE65858 and GSE41613 datasets showed that a worse OS was associated with low expression of KRT78 (p = .0086, and p = .005) and SPRR3 (p = .017, and p = .02).ConclusionsOur findings suggest that KRT4, KRT78, KRT13, and SPRR3 are related to the occurrence and development of HNSCC. Importantly, KRT78 and SPRR3 might serve as diagnostic and prognostic biomarkers of HNSCC.
A novel blockchain tumbling scalability framework in a bitcoin network
Authors: Pathan Summiya A. , Shariff Noorullah 
Published: April 2023

SummaryBitcoin is a decentralized digital currency system that uses a distributed data structure called blockchain, a log that lists all transaction details accomplished with the currency. The bitcoin network delivers a promising infrastructure for one who makes use of e‐currency in e‐commerce. However, the transaction of bitcoin is highly suffered with some scalability issues that could not be overwhelmed with the prior methodologies. Hence, a novel scalability blockchain tumbling framework is proposed to tackle the scalability issues in which a rake interior blockchain etiquette is designed to increase the number of bitcoin transactions in which peer faction algorithm groups blocks that reduces propagation delay and ravenous algorithm ensure higher credibility of transaction with tamper resistant. However, transaction size of the record is high hence, to manage transaction record a novel batch payment into one transaction approach is utilized to limit the size of the transaction records by initiating a precise block using block summing‐up and chagrin algorithms that collects all trust information about blocks. Thus the proposed framework attains 550 bitcoin transaction within 2 min and latency of proposed model is reduced below 60 s.
A novel hybrid meta‐heuristic‐oriented latency sensitive cloud object storage system
Authors: Nataraj N. , Nataraj R. V. 
Published: April 2023

SummaryCloud providers must find out how to properly arrange data in a limited count of servers while ensuring latency assurances to reduce total storage expenses. Timeout is also important to consider because it has a substantial impact on response latency. The core aim of this task is to implement a new cloud object storage system strategy that handles challenges like “latency‐sensitive data allocation, latency‐sensitive data re‐allocation, and latency‐sensitive workload consolidation.” The main contribution here is that distributing the latency of the cloud object storage system allows for better data allocation, data reallocation, and workload consolidation. The primary aim is to use the fewest number of servers feasible to fulfill all requests while maintaining their latency requirements, lowering the overall data transmission cost. As a consequence, Whale Butterfly Optimization Method (WBOA) is a novel hybrid meta‐heuristic algorithm that solves NP‐hard problems by combining baseline advanced algorithms. The simulation outcomes reveal that the offered paradigm consistently provides the greatest outcomes regarding throughput utilization, lower latency, higher storage, and number of used nodes when compared to competing techniques.
Uncertainty‐aware structural damage warning system using deep variational composite neural networks
Authors: Eltouny Kareem A. , Liang Xiao 
Published: April 2023

AbstractStructural health monitoring (SHM) is, without a doubt, one of the most important assets for building resilient communities. The vast and rapidly advancing research in data science and machine learning has provided researchers in the civil engineering community with various tools that can facilitate the processing of significant amounts of gathered data. However, deep learning models are prone to mistakes, and with the catastrophic consequences that can happen due to damage misidentification, damage diagnosis models’ predictions should not be taken for granted. In this study, we present an uncertainty‐aware early‐warning system that can provide near real‐time SHM. The system utilizes a deep composite encoder‐decoder network that combines elements from convolutional neural networks, recurrent neural networks, and variational inference (VI) to provide damage index distributions. The framework can detect anomalies in the structural system during seismic events and provide a measure of uncertainty that can be used to question the model's predictions. To assess the system's validity and practicality, we apply our proposal to three real structures, two of which suffered damage during the 1994 Northridge earthquake. We found that the early warning system delivers an accurate, yet cautious, continuous monitoring that is capable of sending warning signals when damage occurs in the course of seismic events. Source code is available at: https://github.com/keltouny/VSCAN.
Effect of combined application of carbonate salts and hot water treatment for the management of postharvest anthracnose (Colletotrichum gloeosporioides) of papaya
Authors: Getnet Muluken , Alemu Kumlachew , Tsedaley Binyam 
Published: April 2023

AbstractPostharvest anthracnose (Colletotrichum gloeosporioides Penz.Sacc) is the most economically important biological constraint to papaya production and consumption, which causes substantial yield loss worldwide. The effect of combined application of carbonate salts and hot water treatments on the development of postharvest anthracnose and maintenances of postharvest quality of papaya fruit was studied in completely randomized design (CRD) under laboratory condition. The results revealed that combined application of hot water treatment and carbonate salts significantly (p < .05) reduced the incidence and severity of postharvest papaya anthracnose disease. The disease incidence reached 100% 21 days after inoculation in the control treatment; this level was significantly reduced to 26.70% by dipping the fruits in NH4CO3 at 50°C and NH4CO3 at 54°C. Similarly, treatments significantly (p < .05) reduced the disease severity in different degrees from the first day of disease appearance to the date of 100% unmarketability of control fruits. Furthermore, the combined application of carbonate salt and hot water treatments significantly improves fruit marketability by 93.33%. Moreover, the treatments showed significant (p < .05) effect on maintaining pH, TSS, TA, and reducing postharvest weight loss of papaya fruit. In conclusion, postharvest treatment of papaya fruit with NH4CO3 at 54°C, NH4CO3 at 52°C, and NaCO3 at 54°C can significantly reduce anthracnose development and improve marketability of the fruits without pronounced effect on their edible qualities.
A delayed intervention start randomized controlled trial of high‐ and low‐tech communication training approaches for school‐age autistic children with co‐occurring intellectual disability
Authors: Gilroy Shawn P. , McCleery Joseph P. , Leader Geraldine 
Published: April 2023

AbstractThe researchers designed a delayed intervention start randomized controlled trial to compare improvements in functional communication following augmentative and alternative communication (AAC) interventions. The study compared outcomes from function‐based applied behavior analytic (ABA) and eclectic non‐ABA forms of classroom‐based communication strategies (waitlist control) as well as from high‐ and low‐tech forms of AAC. High‐tech AAC consisted of tablet‐based communication, and low‐tech AAC used an exchange of picture cards. The community‐based sample consisted of 29 autistic children with a co‐occurring intellectual disability. Participants were randomized to groups (AAC, waitlist control), and each group received approximately 3 months of communication intervention. Multilevel modeling of learner outcomes indicated that the function‐based approach produced greater improvements than the eclectic alternative, but significant differences were not observed between outcomes of high‐ and low‐tech forms of function‐based AAC. These results are consistent with earlier investigations and provide supporting evidence that both high‐ and low‐tech forms of function‐based intervention are effective for use with autistic children with accompanying intellectual disability. Additional discussion is provided regarding further research into how technology is applied and incorporated into behavior analytic programming.
Effect of forest chronosequence on ecological stoichiometry and nitrogen and phosphorus stocks in Alnus nepalensis forest stands, central Himalaya
Authors: Joshi Rajendra Kumar , Garkoti Satish Chandra 
Published: April 2023

AbstractIn the mid and high elevations of the central Himalaya, Nepalese alder (Alnus nepalensis D. Don) occurs in areas affected by landslides/landslips and is a nitrogen‐fixing species; it quickly improves soil physical and chemical properties and facilitates the restoration of degraded forests. In the present study, we evaluated the effect of A. nepalensis forest chronosequence on the carbon (C), nitrogen (N), and phosphorus (P) concentrations, N and P stocks, and stoichiometry in the soil, including microbial biomass C (MBC), microbial biomass N (MBN) and microbial biomass P (MBP), and in the plant components. Six naturally occurring forest stands were identified in a chronosequence of A. nepalensis (age 3–270 years old) forest stands, namely alder‐early regenerating (AER), alder‐late regenerating (ALR), alder young‐mixed (AYM), alder mature‐oak (Quercus leucotrichophora) mixed (AMOM), alder mature‐rhododendron (Rhododendron arboreum) mixed (AMR), and alder old‐oak (Q. leucotrichophora) mixed (AOOM) forests. The biomass of tree components was estimated using species‐specific allometric equations developed by previous workers for the region. Soil total N and total P stocks of each species were determined by the N and P concentrations and bulk density. Structural equation modeling (SEM) was performed to quantify the contribution of N and P pools to ecosystem nitrogen and phosphorus stocks. The results of this study revealed that the stoichiometry (C:N, N:P, and C:P ratios) of tree components (i.e., leaves, leaf litter, twig), soil and microbial biomass varied widely, and the presence of nitrogen‐fixing A. nepalensis in different succession stages significantly improved the soil and microbial biomass stoichiometry. Total vegetation (tree, herbs, shrubs, and litter) biomass N stock ranged from 346.77 to 4662.06 kg N ha−1, and soil N stock varied from 816.48 to 7334.24 kg N ha−1. Total ecosystem N and P stocks ranged from 1163.26 to 11,996.31 kg N ha−1 and 76.10 to 799.28 kg P ha−1, respectively, and positively increased with A. nepalensis total biomass. The soil P stock accounted for 63.49% to 74.80% of the total P stocks of the forest ecosystems. Overall, our findings suggest that A. nepalensis forest chronosequence enhanced the N and P stocks, and introducing this species in degraded forests appears to be an option for enhancing forest conservation and rehabilitation actions in the central Himalaya.
Both biotic and abiotic predictors explain significant variation in cyanobacteria biomass across lakes from temperate to subarctic zones
Authors: MacKeigan Paul W. , Taranu Zofia E. , Pick Frances R. , Beisner Beatrix E. , Gregory‐Eaves Irene 
Published: April 2023

AbstractThe development of cyanobacteria blooms is of increasing concern in many lakes worldwide, and as a result, modeling their predictors is vital for understanding where and why they occur. In this study, we developed and analyzed a 640‐lake data set that spans Canada and 12 ecozones to identify the drivers of cyanobacteria biomass and of several key toxin‐ and bloom‐forming genera (Microcystis, Aphanizomenon, and Dolichospermum). The database consisted of an exhaustive list of potential predictors (n = 55), including water chemistry, land‐use, and zooplankton variables. We applied a series of empirical modeling approaches to identify significant predictors and thresholds (generalized linear and additive models, mixed effect regression trees), all while accounting for ecozone variability. Across all modeling approaches, and ecozones total phosphorus was identified as the most important predictor of total cyanobacterial and focal genera biomass. In addition, cyanobacteria across Canada showed significant associations with increasing dissolved organic and inorganic carbon, and several ions. Despite the widely held notion that cyanobacteria are often toxic and/or a poor food source for zooplankton, we found a positive relationship between cyanobacteria and zooplankton, particularly with daphnid and copepod biomass. Localized top‐down forces and evolutionary adaptations resulting from long‐term exposure in eutrophic lakes are among the possible explanations for this observed positive association. By considering a suite of complementary modeling approaches, we found that nonlinear models provided greater predictive power and the random ecozone effect was minor due to the overarching importance of local abiotic and biotic factors.
Research and Application of Medical Polyetheretherketone as Bone Repair Material
Authors: Pu Feifei , Yu Yihan , Zhang Zhicai , Wu Wei , Shao Zengwu , Li Chao , Feng Jing , Xue Longjian , Chen Fengxia 
Published: April 2023

AbstractPolyetheretherketone (PEEK) can potentially be used for bone repair because its elastic modulus is similar to that of human natural bone and good biocompatibility and chemical stability. However, its hydrophobicity and biological inertness limit its application in the biomedical field. Inspired by the composition, structure, and function of bone tissue, many strategies are proposed to change the structure and functionality of the PEEK surface. In this review, the applications of PEEK in bone repair and the optimization strategy for PEEK's biological activity are reviewed, which provides a direction for the development of multifunctional bone repair materials in the future.