bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gastrointestinal stromal tumors: a comprehensive radiological review
Authors: Inoue Akitoshi , Ota Shinichi , Yamasaki Michio , Batsaikhan Bolorkhand , Furukawa Akira , Watanabe Yoshiyuki 
Published: July 2022

AbstractGastrointestinal stromal tumors (GISTs) originating from the interstitial cells of Cajal in the muscularis propria are the most common mesenchymal tumor of the gastrointestinal tract. Multiple modalities, including computed tomography (CT), magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography, ultrasonography, digital subtraction angiography, and endoscopy, have been performed to evaluate GISTs. CT is most frequently used for diagnosis, staging, surveillance, and response monitoring during molecularly targeted therapy in clinical practice. The diagnosis of GISTs is sometimes challenging because of the diverse imaging findings, such as anatomical location (esophagus, stomach, duodenum, small bowel, colorectum, appendix, and peritoneum), growth pattern, and enhancement pattern as well as the presence of necrosis, calcification, ulceration, early venous return, and metastasis. Imaging findings of GISTs treated with antineoplastic agents are quite different from those of other neoplasms (e.g. adenocarcinomas) because only subtle changes in size are seen even in responsive lesions. Furthermore, the recurrence pattern of GISTs is different from that of other neoplasms. This review discusses the advantages and disadvantages of each imaging modality, describes imaging findings obtained before and after treatment, presents a few cases of complicated GISTs, and discusses recent investigations performed using CT and MRI to predict histological risk grade, gene mutations, and patient outcomes.
Taxonomic and community composition of epigeal arthropods in monoculture and mixed tree species plantations in a deciduous forest of Ghana
Authors: Damptey Frederick Gyasi , Opuni-Frimpong Emmanuel , Nsor Collins Ayine , Addai James , Debrah Daniel Kwame , Schnerch Benjamin , Bentsi-Enchill Felicity , Korjus Henn 
Published: July 2022

AbstractTropical forests provide several ecosystem services and functions and support approximately two-thirds of the world’s biodiversity but are seriously threatened by deforestation. Approaches to counteract this menace have revolved around afforestation with several or a single tree species. We thus investigated how plantation forests with either a single or several tree species influenced arthropod taxonomic and community composition using pitfall traps to sample selected groups of epigeal arthropods (Araneae, Coleoptera, Orthoptera and Hymenoptera) and with environmental variables assessed simultaneously. Our results revealed 54 taxonomic groups with significantly higher taxonomic richness, activity density, and diversity in the mixed stands than in the monoculture stands. The significant differences in community composition were mainly driven by families including Lycosidae, Formicidae, Staphylinidae, Scotylidae, Hydrophilidae, Gryllidae and Scarabaeidae and were explained by distinct habitat characteristics (canopy openness, litter depth, deadwood volume, and tree height). While the diverse tree communities and heterogeneous vegetation structure offered food and habitat resources for diverse arthropod groups, the allelopathic nature coupled with homogenous stand characteristics of the Tectona grandis stands in the monoculture suppressed the growth of understorey vegetation that could otherwise serve as food and habitat resources for arthropods, which might have led to limited activities and diversity of arthropods in the monoculture plantation stands. The findings thus highlight the need to promote mixed tree plantations in degraded tropical areas, especially when restoring biodiversity is the prime management focus.
Prophylactic Cefazolin Dosing in Obesity—a Systematic Review
Authors: Coates Matthew , Shield Alison , Peterson Gregory M. , Hussain Zahid 
Published: July 2022

Abstract
Currently, there is no consensus on whether a standard 2-g prophylactic cefazolin dose provides sufficient antimicrobial coverage in obese surgical patients. This systematic review analysed both outcome and pharmacokinetic studies, aiming to determine the appropriate cefazolin dose. A systematic search was conducted using 4 databases. In total, 3 outcome and 15 pharmacokinetic studies met the inclusion criteria. All 3 outcome studies concluded that there is no need for increased dose. Also, 9 pharmacokinetic studies reached this conclusion; however, 6 pharmacokinetic studies recommended that 2-g dose is insufficient to achieve adequate plasma or tissue concentrations. The stronger body of evidence supports that 2-g dose of cefazolin is sufficient for surgery lasting up to 4 h; however, large-scale outcome studies are needed to confirm this evidence.
Thermal dissociation kinetics of solid ammonium carbonate for use in NH3-SCR systems
Authors: Mohan Sooraj , Dinesha P. 
Published: July 2022

AbstractSelective catalytic reduction (SCR) systems using solid ammonia carriers like carbamates, carbonates, etc., have gained interest in the recent past for NOx abatement from compression ignition engines. Solid ammonia carriers have successfully demonstrated their use in SCR systems. In this experimental study, the thermal dissociation study of ammonium carbonate is made using nonisothermal thermogravimetric analysis. Ammonium carbonate is subjected to three heating rates, $$\emptyset$$
∅
of 2, 4, and 8 K/min. The corresponding highest rates of reaction are obtained at temperatures ($$T_{p}$$

T
p

) of 96, 118, and 128 °C, respectively. At these points, the mass of the samples has been reduced to 1/3rd of the initial mass. From the Arrhenius plots, the average activation energy obtained is 77.39 kJ/mol which is 15% higher than that of ammonium carbamate. An expression for $$T_{p}$$

T
p

as a function of activation energy, $$\emptyset$$
∅
, and order of the reaction is developed using kinetic model. The model can predict the temperatures at which the reaction rates are maximum for a given heating rate.
A data analytics approach for university competitiveness: the QS world university rankings
Authors: Estrada-Real Ana Carmen , Cantu-Ortiz Francisco J. 
Published: July 2022

AbstractIn recent years, higher education has felt pressured to prepare its graduates for the highly competitive international market due to globalization. Thus, many institutions have turned to position themselves well in university rankings as a way to attract the best academic and student talent from all over the world. Our work presents a predictive model for measuring university performance in the QS world university rankings (QS-WUR). We used a ten-year dataset to build models with statistical and machine learning algorithms contained in the library Caret of the RStudio software tool, to forecast global university position in QS-WUR. With these tools, we designed a methodology to predict the university partners' Final Scores based on their historical performance, achieving errors in the range of one or two points out of 100. The modelling may be a useful aid for university officers to develop strategies for improving institutional processes to attract the best students, faculty, and funding, enhance international collaboration and outlook, and foster international university prestige.
Urbanization and population contraction
Authors: Muroishi Madoka , Yakita Akira 
Published: July 2022

AbstractUrbanization is treated in the literature as a process that occurs along with economic development. We consider an overlapping generations model with two regions, designated as ‘urban’ and ‘rural’. Concentration of population to urban areas involves population inflows from rural areas, thereby exacerbating urban congestion. Inverse agglomeration economies in rural areas exert negative effects on rural income, consequently increasing the attractiveness of urban areas. Because of lower urban fertility rates, urbanization involves population decreases. Therefore, population dynamics might be explained as simultaneous urbanization and population contraction. However, depopulation mitigates congestion, which increases the fertility rate and the worker’s lifetime utility level. Eventually, it can lead to a stationary population size.
Combining N-mixture models with ecological niche modeling supplies a low-cost and fast procedure for estimating population size in remote areas
Authors: Sacchi Roberto , Coladonato Alan Jioele , Scali Stefano , Mangiacotti Marco , Zuffi Marco Alberto Luca 
Published: July 2022

Abstract
Monitoring population changes and trends is a central task in conservation. However, obtaining detailed information for wide and low accessible areas, such as remote islands, is challenging, and cannot be achieved with conventional approaches, such as capture–mark–recapture protocols (CMR). In this paper, we show that combining N-mixture models with ecological niche modeling allows assessing reliable estimates of population size over large target areas on short time intervals. We used it to estimate the population size of a subspecies of the Italian wall lizards (Podarcis siculus calabresiae) endemic to the Island of Montecristo (10.39 km2 in surface). During a single week, we first generated a niche model of the species based on satellite images sampled few days before sampling. Then, we estimated lizard abundance through Bayesian N-mixture models on repeated counts (n = 3) along transects (n = 6), settled in different areas of habitat suitability defined on the basis of the niche model. Finally, we estimated in approximately 20.000 the total number of lizards living in the Island by extrapolating the values computed on transects to the areas of the islands with the same suitability estimated by the niche model. The procedure can be easily repeated allowing monitoring the status of conservation of the species in the island of Montecristo. More in general, this procedure has the potential to be applied to monitor any other species of conservation interest in remote areas whenever detailed satellite images are available.

Graphical Abstract
Invite everyone to the table, but not to every course
Authors: Oschinsky Frederike Marie , Klein Hans Christian , Niehaves Bjoern 
Published: July 2022

AbstractInnovative collaboration strategies are a promising tool for fostering the governance of smart cities while acknowledging citizen centricity. During implementation, however, determining the number and background of the involved actors is challenging. The Design-Thinking (DT) approach appears suitable for addressing this issue as it offers a concrete and adaptable course of action. The present contribution involves a study on implementing DT principles in a German health resort and identifies three critical components: (1) team, (2) process, and (3) workspace. Our use case is an adaptable project- and workshop plan that encourages the implementation of DT collaboration in smart cities when designing digital services. Our results provide initial guidelines on how to involve diverse actors, when to integrate trained DT coaches, and how to design collaborative innovation in a digital way. The practice-oriented insights gained in the study can be applied, adapted, and discussed in other smart cities and citizen-centered projects.
Visual analysis of blow molding machine multivariate time series data
Authors: Musleh Maath , Chatzimparmpas Angelos , Jusufi Ilir 
Published: July 2022

Abstract
The recent development in the data analytics field provides a boost in production for modern industries. Small-sized factories intend to take full advantage of the data collected by sensors used in their machinery. The ultimate goal is to minimize cost and maximize quality, resulting in an increase in profit. In collaboration with domain experts, we implemented a data visualization tool to enable decision-makers in a plastic factory to improve their production process. The tool is an interactive dashboard with multiple coordinated views supporting the exploration from both local and global perspectives. In summary, we investigate three different aspects: methods for preprocessing multivariate time series data, clustering approaches for the already refined data, and visualization techniques that aid domain experts in gaining insights into the different stages of the production process. Here we present our ongoing results grounded in a human-centered development process. We adopt a formative evaluation approach to continuously upgrade our dashboard design that eventually meets partners’ requirements and follows the best practices within the field. We also conducted a case study with a domain expert to validate the potential application of the tool in the real-life context. Finally, we assessed the usability and usefulness of the tool with a two-layer summative evaluation that showed encouraging results.

Graphical Abstract
Onsite/offsite social commerce adoption for SMEs using fuzzy linguistic decision making in complex framework
Authors: Hussain Walayat , Merigo Jose M. 
Published: July 2022

AbstractThere has been a growing social commerce adoption trend among SMEs for few years. However, it is often a challenging strategic task for SMEs to choose the right type of social commerce. SMEs usually have a limited budget, technical skills and resources and want to maximise productivity with those limited resources. There is much literature that discusses the social commerce adoption strategy for SMEs. However, there is no work to enable SMEs to choose social commerce—onsite/offsite or hybrid strategy. Moreover, very few studies allow the decision-makers to handle uncertain, complex nonlinear relationships of social commerce adoption factors. The paper proposes a fuzzy linguistic multi-criteria group decision-making in a complex framework for onsite, offsite social commerce adoption to address the problem. The proposed approach uses a novel hybrid approach by combining FAHP, FOWA and selection criteria of the technological–organisation–environment (TOE) framework. Unlike previous methods, the proposed approach uses the decision maker's attitudinal characteristics and recommends intelligently using the OWA operator. The approach further demonstrates the decision behaviour of the decision-makers with Fuzzy Minimum (FMin), Fuzzy Maximum (FMax), Laplace criteria, Hurwicz criteria, FWA, FOWA and FPOWA. The framework enables the SMEs to choose the right type of social commerce considering TOE factors that help them build a stronger relationship with current and potential customers. The approach's applicability is demonstrated using a case study of three SMEs seeking to adopt a social commerce type. The analysis results indicate the proposed approach's effectiveness in handling uncertain, complex nonlinear decisions in social commerce adoption.
Clozapine-Induced Chemogenetic Neuromodulation Rescues Post-Stroke Deficits After Chronic Capsular Infarct
Authors: Cho Jongwook , Ryu Seungjun , Lee Sunwoo , Kim Junsoo , Park Ji-Young , Kwon Hyuk-Sang , Kim Hyoung-Ihl 
Published: July 2022

AbstractLong-term disabilities induced by stroke impose a heavy burden on patients, families, caregivers, and public health systems. Extensive studies have demonstrated the therapeutic value of neuromodulation in enhancing post-stroke recovery. Among them, chemogenetic neuromodulation activated by clozapine-N-oxide (CNO) has been proposed as the potential tool of neuromodulation. However, recent evidence showed that CNO does not cross the blood − brain barrier and may in fact have low binding affinity for chemogenetic tool. Thus, clozapine (CLZ) has been suggested for use in chemogenetic neuromodulation, in place of CNO, because it readily crosses the blood–brain barrier. Previously we reported that low doses of CLZ (0.1 mg/kg) successfully induced neural responses without off-target effects. Here, we show that low-dose clozapine (0.1 mg/kg) can induce prolonged chemogenetic activation while avoiding permeability issues and minimizing off-target effects. In addition, clozapine-induced excitatory chemogenetic neuromodulation (CLZ-ChemoNM) of sensory-parietal cortex with hsyn-hM3Dq-YFP-enhanced motor recovery in a chronic capsular infarct model of stroke in rats, improving post-stroke behavioral scores to 56% of pre-infarct levels. Longitudinal 2-deoxy-2-[18F]-fluoro-D-glucose microPET (FDG-microPET) scans showed that a reduction in diaschisis volume and activation of corticostriatal circuits were both correlated with post-stroke recovery. We also found c-Fos increases in bilateral cortices and BDNF increases in the cortices and striatum after CLZ-ChemoNM, indicating an increase in neural plasticity. These findings suggest the translational feasibility of CLZ-ChemoNM for augmenting recovery in chronic stroke.
A Neural-Symbolic Approach for Explanation Generation Based on Sub-concept Detection: An Application of Metric Learning for Low-Time-Budget Labeling
Authors: Rabold Johannes 
Published: July 2022

AbstractDeep learning methods, although effective in their assigned tasks, are mostly black-boxes with respect to their inner workings. For image classification with CNNs, there exists a variety of visual explanation methods that highlight parts of input images that were relevant for the classification result. But in many domains visual highlighting may not be expressive enough when the classification relies on complex relations within visual concepts. This paper presents an approach to enrich visual explanations with verbal local explanations, emphasizing important relational information. The proposed SymMetric algorithm combines metric learning and inductive logic programming (ILP). Labels given by a human for a small subset of important image parts are first generalized to a neighborhood of similar images using a learned distance metric. The information about labels and their spatial relations is then used to build background knowledge for ILP and ultimately to learn a first-order theory that locally explains the black-box with respect to the given image. The approach is evaluated with the Dogs vs. Cats data set demonstrating the generalization ability of metric learning and with Picasso Faces to illustrate recognition of spatial meaningful constellations of sub-concepts and creation of an expressive explanation.
The Ergogenic Effects of Acute Carbohydrate Feeding on Resistance Exercise Performance: A Systematic Review and Meta-analysis
Authors: King Andrew , Helms Eric , Zinn Caryn , Jukic Ivan 
Published: July 2022

Abstract
Background
Carbohydrate (CHO) ingestion has an ergogenic effect on endurance training performance. Less is known about the effect of acute CHO ingestion on resistance training (RT) performance and equivocal results are reported in the literature.

Objective
The current systematic review and meta-analysis sought to determine if and to what degree CHO ingestion influences RT performance.

Methods
PubMed, MEDLINE, SportDiscus, Scopus, and CINAHL databases were searched for peer-reviewed articles written in English that used a cross-over design to assess the acute effect of CHO ingestion on RT performance outcomes (e.g., muscle strength, power, and endurance) in healthy human participants compared to a placebo or water-only conditions. The Cochrane Collaboration’s risk of bias tool and GRADE approaches were used to assess risk of bias and certainty of evidence, respectively. Random effects meta-analyses were performed for total training session volume and post-exercise blood lactate and glucose. Sub-group meta-analysis and meta-regression were performed for categorical (session and fast durations) and continuous (total number of maximal effort sets, load used, and CHO dose) covariates, respectively.

Results
Twenty-one studies met the inclusion criteria (n = 226 participants). Pooled results revealed a significant benefit of CHO ingestion in comparison to a placebo or control for total session training volume (standardised mean difference [SMD] = 0.61). Sub-group analysis revealed a significant benefit of CHO ingestion during sessions longer than 45 min (SMD = 1.02) and after a fast duration of 8 h or longer (SMD = 0.39). Pooled results revealed elevated post-exercise blood lactate (SMD = 0.58) and blood glucose (SMD = 2.36) with CHO ingestion. Meta-regression indicated that the number of maximal effort sets, but not CHO dose or load used, moderates the effect of CHO ingestion on RT performance (beta co-efficient [b] = 0.11). Carbohydrate dose does not moderate post-exercise lactate accumulation nor do maximal effort sets completed, load used, and CHO dose moderate the effect of CHO ingestion on post-exercise blood glucose.

Conclusions
Carbohydrate ingestion has an ergogenic effect on RT performance by enhancing volume performance, which is more likely to occur when sessions exceed 45 min and where the fast duration is ≥ 8 h. Further, the effect is moderated by the number of maximal effort sets completed, but not the load used or CHO dose. Post-exercise blood lactate is elevated following CHO ingestion but may come at the expense of an extended time-course of recovery due to the additional training volume performed. Post-exercise blood glucose is elevated when CHO is ingested during RT, but it is presently unclear if it has an impact on RT performance.

Protocol Registration
The original protocol was prospectively registered on the Open Science Framework (Project identifier: https://doi.org/10.17605/OSF.IO/HJFBW).
Electron transfer dominated triboelectrification at the hydrophobic/slippery substrate—water interfaces
Authors: Chen Yi , Li Xiaojuan , Xu Chenggong , Wang Daoai , Huang Jinxia , Guo Zhiguang , Liu Weimin 
Published: July 2022

AbstractTriboelectric nanogenerator (TENG) based on triboelectrification has attracted wide attention due to its effective utilization of green energy sources such as marine energy. However, researches about liquid-liquid triboelectrification are still scanty as solid—liquid triboelectrification has been widely studied. Herein, this work focuses on the hydrophobic/slippery substrate—water interfacial triboelectrification based on the solid friction materials of polytetrafluoroethylene (PTFE) nanoparticles. The hydrophobic/slippery substrate—water interfacial triboelectrification are studied by assembling PTFE coated Al sheets and perfluoropolyether (PFPE) infused PTFE coated Al sheets (formed the slippery lubricant-infused surfaces (SLIPSs)) as the friction electrode, and water as liquid friction materials, respectively. The results show that the hydrophobic TENG output performances improved as the PTFE nanoparticles cumulating, and the SLIPSs TENG output performances increased with the thinner PFPE thickness. Both the triboelectrification behavior of hydrophobic/SLIPSs TENG assembled in this work are dominated by the electron transfer. Thanks to the introduction of SLIPSs, the SLIPSs TENG exhibits superior stability and durability than the hydrophobic TENG. The investigation of hydrophobic/slippery substrate—water interfacial triboelectrification contributes to optimize the TENG performances, and expands the application in harsh environments including low temperature and high humidity on the ocean.