bluuebunny/crossref_metadata_2025_split huggingface dataset:
Das modulare Stadion 974: Planung für Rückbau und Wiederverwendung
Authors: Stockhusen Knut , Paech Christoph 
Published: November 2022

AbstractDas Stadion 974 in Doha ist ein modulares Bauwerk, das vollständig rückgebaut und wiederverwendet werden kann. Wie die Waren eines Lagers sind 974 reguläre Schiffscontainer in eine Stahlkonstruktion eingeschoben, die einem großen Hochregallager gleicht. Die Container beinhalten alle Funktionen einer modernen Arena – von Haustechnikzentrale über Sanitäreinrichtungen bis hin zu Aufenthaltsräumen, Logen und Kiosken. Auch die Stahlkonstruktion ist mit reversiblen Verbindungen, standardisierten Elementen und transportfähigen Bauteilen vollständig modular und wiederverwendbar konzipiert. Als mögliche Optionen zur Wiederverwendung wurden in der Planung neben der Nutzung des ganzen Stadions auch weitere Konfigurationen berücksichtigt. So können einzelne Teile der Konstruktion als freistehende Tribünen oder runde Arenen wiederverwendet werden. Ermöglicht wird dies durch die standardisierten Elemente und Verbindungen sowie die globale modulare Geometrie, bei der verschiedene Anordnungen bereits berücksichtigt wurden. Mit dem Stadion 974 im Bezirk Ras Abu Aboud der katarischen Hauptstadt Doha wird das Konzept eines vollständig demontierbaren, transportierfähigen und wiederverwendbaren Stadions nun erstmals realisiert.
DigEST: Digital plug‐n‐probe disease Endotyping Sensor Technology
Authors: Ganguly Antra , Ebrahimzadeh Tahmineh , Komarovsky Jessica , Zimmern Philippe E. , De Nisco Nicole J. , Prasad Shalini 
Published: November 2022

AbstractIn this work, we propose a novel diagnostic workflow—DigEST—that will enable stratification of disease states based on severity using multiplexed point of care (POC) biosensors. This work can boost the performance of current POC tests by enabling clear, digestible, and actionable diagnoses to the end user. The scheme can be applied to any disease model, which requires time‐critical disease stratification for personalized treatment. Here, urinary tract infection is explored as the proof‐of‐concept disease model and a four‐class classification of disease severity is discussed. Our method is superior to traditional enzyme‐linked immunosorbent assay (ELISA) as it is faster and can work with multiple disease biomarkers and categorize diseases by endotypes (or disease subtype) and severity. To map the nonlinear nature of biochemical pathways of complex diseases, the method utilizes an established supervised machine learning model for digital classification. This scheme can potentially boost the diagnostic power of current electrochemical biosensors for better precision therapy and improved patient outcomes.
A recurrent neural networks based framework for at‐risk learners' early prediction and MOOC tutor's decision support
Authors: Mourdi Youssef , Sadgal Mohammed , Elalaoui Elabdallaoui Hasna , El Kabtane Hamada , Allioui Hanane 
Published: November 2022

AbstractSince their beginning, Massive Open Online Courses (MOOC) have known great success and have managed to establish themselves with significant enrollment rates. However, this success was quickly disrupted by the drop‐out phenomenon observed in the majority of MOOCs, which reaches 90% in some courses. Studying and understanding this phenomenon, and consequently determining the relevance of the efforts made to develop MOOCs, has led several researchers to propose predictive models of learners at risk of dropping out. On one hand, these models have been made relying on machine learning and the massive data generated by learners' navigation. On the other hand, these models only provide weekly predictions and do not give clear visibility about the overall course progress. We present in this paper a framework based on the recurrent neural networks' strengths which uses generator and predictor modules. Our framework allows not only the prediction of dropouts but also the generation of each learners' behaviors during the whole course since its first week. Besides, an OLAP analytical module proved great support for MOOC moderators to report on the learners' behavior at‐risk to target their interventions and guide their support.
Self‐Assembling Peptide‐Based Functional Biomaterials
Authors: Huo Yehong , Hu Jian , Yin Yuanyuan , Liu Peng , Cai Kaiyong , Ji Wei 
Published: November 2022

AbstractPeptides can self‐assemble into various hierarchical nanostructures through noncovalent interactions and form functional materials exhibiting excellent chemical and physical properties, which have broad applications in bio‐/nanotechnology. The self‐assembly mechanism, self‐assembly morphology of peptide supramolecular architecture and their various applications, have been widely explored which have the merit of biocompatibility, easy preparation, and controllable functionality. Herein, we introduce the latest research progress of self‐assembling peptide‐based nanomaterials and review their applications in biomedicine and optoelectronics, including tissue engineering, anticancer therapy, biomimetic catalysis, energy harvesting. We believe that this review will inspire the rational design and development of novel peptide‐based functional bio‐inspired materials in the future.
The unheard victims: Challenges of identifying experiences of trauma among children with ASD
Authors: Bernadoni Amy 
Published: November 2022

Trigger warning: Sexual assault. Several years ago, I was providing individual psychotherapy to a kind, intelligent woman in her 40's who was in the process of obtaining an advanced scientific degree in a very competitive university program. She received a diagnosis of autism spectrum disorder (ASD) as an adult and was seeking psychotherapy to improve her social skills in hopes of better maintaining personal relationships in both her personal and professional life. Approximately 3 months into therapy, we were exploring common challenges she faces in maintaining positive relationships with fellow graduate students and work colleagues. She casually described an event from a few years ago, during which she was forced to engage in non‐consensual sex with a male colleague in her workplace bathroom. While she seemed distressed in telling her story, she did not appear to understand the gravity of what she was describing. “I didn't like it,” she stated. “That was a bad day at work.” When asked why she didn't mention this in therapy before (she denied any “traumatic or stressful life experiences” during her intake appointment), she stated, “I've never told anyone. Was I supposed to? I don't really know what's ‘normal’, especially with the opposite sex. It made me uncomfortable, but lots of things make me uncomfortable that everyone just tells me to get over. Did I do something wrong?”
Glucose/Furfural Substrate Mixtures in Non‐Engineered Yeast: Potential for Massive Rerouting of Fermentation to C−C Bond Formation on Furfural
Authors: Sannelli Francesca , Gao Sanni , Jensen Pernille Rose , Meier Sebastian 
Published: November 2022

AbstractSuitable mixtures of glucose and furfural may provide novel strategies for C−C bond formation on furfural due to the versatility of low‐cost biological catalysts. We use in‐cell NMR with non‐engineered commercial yeast as the catalyst to determine the interplay between furfural and glucose metabolism in non‐engineered yeast. The presence of furfural is shown to modulate kinetic barriers in glucose conversion and to favor the accumulation of acetaldehyde in situ. As a result, glucose carbons are remarkably strongly redirected towards C−C bond formation between furfural and a glucose‐derived C2 unit. In the presence of suitable glucose/furfural substrate mixtures in non‐engineered yeasts, glucose carbons can achieve relative influxes of at least 80 % into the C−C bond formation on furfural, compared to only 20 % into ethanol. Chain‐elongation of furfural by yeast thus seems a viable strategy for the upgrading of lignocellulosic biomass through concurrent conversion of furfural and glucose. The product is related to chemicals that already have found value in the fine chemical and pharmaceutical industries.
Efficient Aerobic Oxidative Coupling of Methyl Heteroarenes with Indoles
Authors: Zhang Lei‐Yang , Wang Nai‐Xing , Yan Zhan , Wu Yue‐Hua , Gao Xue‐Wang , Feng Ke , Lucan Dumitra , Xing Yalan 
Published: November 2022

AbstractDirect oxidative coupling of inert C(sp3)−H bond has been a great challenge. Herein, an environmentally friendly aerobic oxidative coupling of α‐methyl substituted N‐heteroarenes with indoles is reported. A variety of diheteroaryl ketones were prepared in good yields (up to 72 %). This protocol features simple operation and broad substrates scope (26 examples). Significantly, a plausible mechanism about catalytic cycle was proposed, and two key intermediates were confirmed by high resolution mass spectrometry.
Theoretical Exploration on the Role of Magnetic States to the N2 Fixation behaviors of 2D Transition Metal Tri‐borides (TMB3s)
Authors: Lin Yuxing , Shi Li , Chen Yu , Yao Xiaojing , Meng Lijuan , Han Ying , Zhao Xinli , He Maoshuai , Liu Yongjun , Zhang Xiuyun 
Published: November 2022

AbstractFixing nitrogen (N2) by electrosynthesis method has become a promising way to ammonia (NH3) production, nevertheless, developing electrocatalysts combining long‐term stable and low‐cost feathers are still a great challenge to date. Using comprehensive first‐principles calculations, we herein investigate the potential of a new class of two‐dimensional (2D) transition metal tri‐borides (TMB3s) as nitrogen reduction reaction (NRR) electrocatalysts, and explore the effect of magnetic orders on the NRR. Our results show that the TMB3s can sufficiently activate N2 and convert it to NH3. Particularly, TiB3 is identified as a high‐efficiency catalyst for NRR because of its low limiting potential (−0.24 V) and good suppression of the competitive hydrogen evolution reaction (HER). For the first time, we present that these TMB3s with various magnetic states exhibit different performances in the adsorption of N2 and NRR intermediates, and minor effect on activation of N2. Besides, VB3, CrB3, MnB3, and FeB3 monolayers possess the superior capacity to suppress surface oxidation via the self‐activating process, which reduces *O/*OH into *H2O under NRR electrochemical conditions, thus favoring the N2 electroreduction. This work paves the way for finding high‐performance NRR catalysts for transition metal borides and pioneering the research of magnetic states effects in NRR.
Fast and Cost‐Efficient 17O‐Isotopic Labeling of Carboxylic Groups in Biomolecules: From Free Amino Acids to Peptide Chains
Authors: Špačková Jessica , Goldberga Ieva , Yadav Rishit , Cazals Guillaume , Lebrun Aurélien , Verdié Pascal , Métro Thomas‐Xavier , Laurencin Danielle 
Published: November 2022

Abstract17O NMR spectroscopy is a powerful technique, which can provide unique information regarding the structure and reactivity of biomolecules. However, the low natural abundance of 17O (0.04 %) generally requires working with enriched samples, which are not easily accessible. Here, we present simple, fast and cost‐efficient 17O‐enrichment strategies for amino acids and peptides by using mechanochemistry. First, five unprotected amino acids were enriched under ambient conditions, consuming only microliter amounts of costly labeled water, and producing pure molecules with enrichment levels up to ∼40 %, yields ∼60‐85 %, and no loss of optical purity. Subsequently, 17O‐enriched Fmoc/tBu‐protected amino acids were produced on a 1 g/day scale with high enrichment levels. Lastly, a site‐selective 17O‐labeling of carboxylic functions in peptide side‐chains was achieved for RGD and GRGDS peptides, with ∼28 % enrichment level. For all molecules, 17O ssNMR spectra were recorded at 14.1 T in reasonable times, making this an important step forward for future NMR studies of biomolecules.
Dual‐Functional Hosts for Polysulfides Conversion and Lithium Plating/Stripping towards Lithium‐Sulfur Full Cells
Authors: Shen Nan , Sun Hongxu , Li Boya , Xi Baojuan , An Xuguang , Li Jingfa , Xiong Shenglin 
Published: November 2022

AbstractThe practical application of lithium‐sulfur (Li−S) batteries is greatly hindered by the shuttle effect of dissolved polysulfides in the sulfur cathode and the severe dendritic growth in the lithium anode. Adopting one type of effective host with dual‐functions including both inhibiting polysulfide dissolution and regulating Li plating/stripping, is recently an emerging research highlight in Li−S battery. This review focuses on such dual‐functional hosts and systematically summarizes the recent research progress and application scenarios. Firstly, this review briefly describes the stubborn issues in Li−S battery operations and the sophisticated counter measurements over the challenges by dual‐functional behaviors. Then, the latest advances on dual‐functional hosts for both cathode and anode in Li−S full cells are catalogued as species, including metal chalcogenides, metal carbides, metal nitrides, heterostuctures, and the possible mechanisms during the process. Besides, we also outlined the theoretical calculation tools for the dual‐functional host based on the first principles. Finally, several sound perspectives are also rationally proposed for fundamental research and practical development as guidelines.
Palladium(0)‐CatalyzedAnti‐Selective Addition‐Cyclizations of Alkynyl Electrophiles
Authors: Tsukamoto Hirokazu , Ito Kazuya , Ueno Tatsuhiko , Shiraishi Mitsugu , Kondo Yoshinori , Doi Takayuki 
Published: November 2022

AbstractPalladium(0)/monophosphine complexes catalyzeanti‐selective alkylative, arylative, and alkynylative cyclizations of alkynyl electrophiles with organometallic reagents. The remarkableanti‐selectivity results from novel oxidative addition, that is, the nucleophilic attack of electron‐rich palladium(0) on the electrophile across the alkyne followed by transmetalation and reductive elimination (“anti‐Wacker”‐type cyclization). With regard to 5‐alkynals, triphenylphosphine (PPh3)‐ligated palladium(0) catalyzes the cyclization of terminal alkynes and conjugated alkenyl‐ or alkynyl‐substituted ones to afford 2‐cyclohexen‐1‐ol and 2‐alkylidene‐cyclopentanol derivatives, respectively. For 6‐alkyl‐ or 6‐aryl‐5‐alkynals, the cyclization does not proceed with the palladium/PPh3catalyst; however, it does proceed with palladium/tricyclohexylphosphine (PCy3), to yield the former products predominantly. Remarkably, the latter catalyst completely switches the regioselectivity in the cyclization of the conjugated diyne‐aldehydes. Notably, palladium/PPh3‐catalyzed cyclizations also proceed with other organometallics or even without them.
Molecular Twisting Affects the Solid‐State Photochemical Reactions of Unsaturated Ketones and the Photomechanical Effects of Molecular Crystals
Authors: Yue Yuan , Shu Yuanhong , Ye Kaiqi , Sun Jingbo , Liu Cheng , Dai Shuting , Jin Liuyang , Ding Chengde , Lu Ran 
Published: November 2022

AbstractThree groups of chalcone derivatives and their analogues involving halogen atoms (X=F, Cl, Br) have been synthesized. Firstly, the nearly planar acyclic chalcone derivatives were inclined to undergo photo‐induced stereospecific [2+2] cycloaddition, which triggered the crystals to exhibit macroscopic motions of bending or cracking. In particular, the single‐crystal‐to‐single‐crystal transformation happened upon UV irradiation of the crystals, which was helpful for the understanding photomechanical effects. Cyclic 3,4‐dihydronaphthalene‐based chalcone analogues possess a more twisted conformation, and they tend to undergo trans‐cis isomerization. No photomechanical effect was observed for the crystals of the cyclic chalcone analogues due to the lower isomerization rate. The twist degree of chroman‐based molecules was in between of the first two, [2+2] cycloaddition and trans‐cis isomerization simultaneously took place in crystals. Photo‐induced bending and twisting were observed for the crystals of chroman‐based chalcone analogues. Therefore, the differences in molecular dihedral angles in α,β‐unsaturated ketones were responsible for their photochemical characters and in turn to tune the photomechanical effects. In this work, a bridge between the molecular structures and solid‐state photochemical reactions triggered photomechanical crystals is built.
The Potential Application of Single‐Use Bioreactors in Cultured Meat Production
Authors: Kurt Tutku , Höing Tobias , Oosterhuis Nico 
Published: November 2022

AbstractProduction of cultured meat by proliferation of stem cells is a fast‐growing field drawing significant attention and big investments. Replacement of traditional meat by cell‐based meat can have a huge positive impact on the environmental burden of human meat consumption. Large‐scale production to make cell‐based meat economically feasible and comparable to the cost of conventional meat requires further bioprocess optimization and large investments. Application of single‐use bioreactors at a restricted scale of operation reduces the overall capital expenditures for cultured meat production. The advantages of single‐use bioreactors as experienced in biopharmaceutical applications are applicable to cultured meat production. Here, it is shown that the transfer from traditional cultivation systems to single‐use systems is easily possible. Single‐use bioreactors can contribute to the realization of cultured meat production at “farm level”, thus limiting the investment and technical risks of very large‐scale productions.
An improved dynamic latent variable regression model for fault diagnosis and causal analysis
Authors: Zhang Haitian , Zhu Qinqin 
Published: November 2022

AbstractThe advancement of industrial techniques has imposed a high demand for powerful machine learning algorithms to model the increasingly complicated relations in the data. Among them, dynamic models are widely studied to capture the inevitable temporal relations. However, most existing methods only focus on the dynamics between input and output data, failing to exploit other valuable information in the output. In this article, an improved dynamic latent variable regression (LVR) method is proposed to capture both auto‐correlations and cross‐correlations between input and output with an auto‐regressive exogenous model, which is referred to as dynamic regularized LVR with auto‐regressive exogenous input (DrLVR‐ARX). Further, a DrLVR‐ARX‐based fault detection and diagnosis framework is designed to identify the root causes of a detected fault. The framework systematically integrates reconstruction‐based contribution, time‐domain Granger causality, and conditional spectral Granger causality to determine and locate the assignable causes. The effectiveness of the proposed algorithms is demonstrated with two industrial processes.
Experimental performance analysis of cloud resource allocation framework using spider monkey optimization algorithm
Authors: Kumar Mohit , Dubey Kalka , Singh Samayveer , Kumar Samriya Jitendra , Gill Sukhpal Singh 
Published: November 2022

SummaryThe cloud services demand has increased exponentially in the last decade due to its plethora of services. It becomes a significant platform to compute large and diverse applications over the internet. On the contrary, on‐demand resource allocation to a variety of applications becomes a serious issue due to dynamic workload conditions and uncertainty in the cloud environment. Several existing state of art techniques often fails to allocate the optimal resources to forthcoming demands, leading to an imbalance workload over cloud platform, degrading the performance. This article introduces a secure and self‐adaptive resource allocation framework that addressed the mentioned issues and allocates the most suitable resources to users' applications while ensuring the deadline constraints. Further, the proposed framework is integrated with a metaheuristic algorithm named enhanced spider monkey optimization algorithm that is based on the intelligent foraging behavior of spider monkeys. The proposed algorithm finds an optimal resource for the user's application using the fission‐fusion approach and improves multiple influential parameters like time, cost, degree of load balancing, energy consumption, task rejection ratio and so on. The experimental CloudSim based results verified that the proposed framework performs superior to state of art approaches like PSO, GSA, ABC, and IMMLB.
Towards the significance of taxi recommender systems in smart cities
Authors: Katarya Rahul 
Published: November 2022

SummarySince their launch in the early 1990's, recommender systems (RSs) have played an essential role in information filtering and providing personalized information to users by utilizing the web, mobile, context, personalized, and practical applications. Many research articles have been published in various application domains such as movies, books, documents, news, images, music, shopping, TV programs, tourism, group, social, taxi, and others. However, from these domains, taxi recommendation is a new and thrust area of research, as publications in this domain are few and recently published. Taxi recommendations are associated with drivers‐passengers with their: behavior, hotspots, trajectory, point of interest, route planning or prediction, taxi finding, anomaly or fraud detection, urban computing, mobility patterns and so forth. Due to this diversity and various agendas in taxi recommendations, more exploration is required, as it is a less mature and growing field than other domains. So we have done a literature review in the taxi domain by classification, incorporating reputed articles published from 2001 to August 2022. We include the reputed papers which highlight, analyze and perform studies only on the taxi domain. This article categorizes and discusses the research and development in taxi recommendations as nature, approaches, algorithms, methods, datasets, models, devices, information, and evaluation techniques. This survey article will actively help the researchers and professionals understand the current situations in taxi RS and resolve future trends, opportunities, and research.
Elevational changes in insect herbivory on woody plants in six mountain ranges of temperate Eurasia: Sources of variation
Authors: Kozlov Mikhail V. , Zverev Vitali , Zvereva Elena L. 
Published: November 2022

AbstractCurrent theory predicts that the intensity of biotic interactions, particularly herbivory, decreases with increasing latitude and elevation. However, recent studies have revealed substantial variation in both the latitudinal and elevational patterns of herbivory. This variation is often attributed to differences in study design and the type of data collected by different researchers. Here, we used a similar sampling protocol along elevational gradients in six mountain ranges, located at different latitudes within temperate Eurasia, to uncover the sources of variation in elevational patterns in insect herbivory on woody plant leaves. We discovered a considerable variation in elevational patterns among different mountain ranges; nevertheless, herbivory generally decreased with increasing elevation at both the community‐wide and individual plant species levels. This decrease was mostly due to openly living defoliators, whereas no significant association was detected between herbivory and elevation among insects living within plant tissues (i.e., miners and gallers). The elevational decrease in herbivory was significant for deciduous plants but not for evergreen plants, and for tall plants but not for low‐stature plants. The community‐wide herbivory increased with increases in both specific leaf area and leaf size. The strength of the negative correlation between herbivory and elevation increased from lower to higher latitudes. We conclude that despite the predicted overall decrease with elevation, elevational gradients in herbivory demonstrate considerable variation, and this variation is mostly associated with herbivore feeding habits, some plant traits, and latitude of the mountain range.