bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surgical site infections by atypical mycobacteria: prevalence and species characterization using MALDI-TOF and molecular LCD chip array
Authors: Gad Maha A. , Khairat Sahar M. , Salama Amira M. A. , Abd Elmoez Omnia A. , Soliman Noha S. 
Published: June 2022

Abstract
Background
Surgical site infection (SSI) is a post-operative complication of high concern with adverse impact on patient prognosis and public health systems. Recently, SSI pathogens have experienced a change in microbial profile with increasing reports of non-tuberculous mycobacteria (NTM) as important pathogens.

Aim
of the study
The study aimed to detect the prevalence of NTM among cases with SSIs and describe their species using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) and PCR-based microarray.

Methods
The study was conducted with 192 pus samples collected from patients with SSI. Mycobacterial investigations were done in the form of Ziehl–Neelsen (ZN) smears for acid-fast bacilli, automated mycobacterial culture to isolate mycobacteria, followed by immunochromatography test to predict NTM. NTM-positive cultures were tested by MALDI -TOF MS and PCR-based microarray to reach species-level identification.

Results
Mycobacterial growth was found in 11/192 samples (5.7%) and identified as 4 NTM and 7 M. tuberculosis isolates with prevalence of 2.1% and 3.64%, respectively. The NTM species were described by MALDI-TOF as M. abscessus, M. porcinum, M. bacteremicum, and M. gordonae. Microarray agreed with MALDI-TOF in identifying one isolate (M. abscessus), while two isolates were classified as belonging to broad groups and one isolate failed to be identified.

Conclusions
The prevalence of NTM among SSI was found to be low, yet have to be considered in the diagnosis of mycobacteria. Employing advanced technologies in diagnosis is recommended to guide for appropriate treatment.
RST-Net: a spatio-temporal residual network based on Region-reConStruction algorithm for shared bike prediction
Authors: Tan Yanyan , Wang Bin , Yan Zeyuan , Liu Haoran , Zhang Huaxiang 
Published: June 2022

AbstractAs a new form of public transportation, shared bikes have greatly facilitated people’s travel in recent years. However, in the actual operation process, the uneven distribution of bicycles at each shared bicycle station has limited the travel experience. In this paper, we propose a deep spatio-temporal residual network model based on Region-reConStruction algorithm to predict the usage of shared bikes in the bike-sharing system. We first propose an Region-reConStruction algorithm (RCS) to partition the shared bicycle sites within a city into separate areas based on their geographic location information as well as bikes’ migration trends between stations. We then combine the RCS algorithm with a deep spatio-temporal residual network to model the key factors affecting the usage of shared bicycles. RCS makes good use of the migration trend of shared bikes during user usage, thus greatly improving the accuracy of prediction. Experiments performed on New York’s bike-sharing system show that our model’s prediction accuracy is significantly better than that of previous models.
Judicial authority through the experiences of crisis
Authors: Janusiene Aiste 
Published: June 2022

AbstractThis article is concerned with law’s experiences and making sense of crisis. When we talk about law’s response to crisis, we refer to law not as an abstract set of rules but as an embodied and animated assemblage of relations and practices. This way, law needs to make sense of any crisis to respond to it. The article draws on cultural legal studies to explore the constitution of judicial authority in the context of a democracy in flux. The article relies on fieldwork data collected in the interviews conducted by the author with Lithuanian judges in 2019. Highest in more than two decades, public trust in the judiciary in 2018 indicated a remarkable achievement for Lithuania, a country whose judicial system had been in a state of flux since the end of the Soviet era. However, after an unprecedented and highly mediated judicial corruption scandal in 2019, the rates of public trust plummeted, uncovering complex dynamics between the image of courts, mass media, and the public. Against this backdrop, the article explores how judges make sense of crisis that develops on the intersections of provocative reality judging and formal judicial institutions. It shows how judicial authority is constituted in the conditions of crisis on the tension between law and culture. Emerging from a crisis of authority is the changing face of judging. A post-colonial vantage point and theatrical jurisprudence are used to respond to a development of a desire of power under a mask of rationality, objectivity, and universality. The article concludes by contemplating how this authority shapes our lifeworlds.
Resurgence from Crisis Through Awareness of Natural Inclusion
Authors: Vass Eva , Rayner Alan 
Published: June 2022

AbstractFor millennia, the Western mindset has been predisposed to the inherited custom to split mind and matter, emotion and cognition, art and science, the spiritual and the intellectual, the inner and outer, contemplation and objective inquiry. Our contemporary sense of dislocation from nature has arisen from this objectivistic perception. The current societal, economic and environmental crises urge us to break down the pervasive conceptual boundaries and binary distinctions and rethink what science is or what it can become. Covid 19 has exposed the iniquities and deep fault lines in the political and economic structure of globalized modern society founded on false division or unification of individual from or with group. We see Natural Inclusionality as the path to begin to resurrect and cultivate a new normal of co-creative community from the wreckage of the old normal of cultural tyranny (Rayner, 2020). The most ground-breaking dimension of the NI perception lies in its rejection of both extremes of dualism: the narrow objectivistic view of the world as dividable into discrete entities and the equally limiting monistic view of the world as some sort of uniform oneness. We propose to unpack these insights through dialogue: an ongoing professional dialogue between two authors, between two philosophical orientations, between natural and social sciences and between science and art. Our intentions are to show Natural Inclusional awareness as humanity’s ultimate resource for a resurgence from crisis—breaching the Great Lie that isolates individual from common good. In particular, we discuss the significance of these considerations in the context of educational science and practice.
A Sociomaterial Lens on Crowdsourcing for Learning
Authors: Tyrrell Jessica , Shalavin Courtney 
Published: June 2022

AbstractCrowdsourcing is increasingly being applied in educational contexts to explore the ideation and problem-solving capacity of large, networked groups. Research is emerging on the use of crowdsourcing in education, yet little is known about how the particular affordances of crowdsourcing platforms facilitate student learning. This paper applies sociomaterial theory to analysing a case study of a crowdsourcing experiment undertaken at the University of Sydney. It reflects on the crowdsourcing experiment as an assemblage of different relations, dynamics and materials, building on a recent typology for analysing social learning software through a sociomaterial lens. We contribute to the growing discourse around sociomaterial approaches by exploring how the material affordances of a unique online learning environment participate to produce certain kinds of learning experiences. This supports future research into the potentialities of crowdsourcing pedagogies at a time when increased online and blended learning brought about by the Covid-19 pandemic has galvanised educators’ interest in exploring different online environments and approaches.
Interface dynamics and flow fields’ structure under thermal heat flux, thermal conductivity, destabilizing acceleration and inertial stabilization
Authors: Ilyin Dan V. , Abarzhi Snezhana I. 
Published: June 2022

Abstract
Interfaces and interfacial mixing are omnipresent in fluids, plasmas, materials in vastly different environments. A thorough understanding of their fundamentals is essential in many areas of science, mathematics, and technology. This work focuses on the classical problem of stability of a phase boundary that is a subject to fluxes of heat and mass across it for non-ideal thermally conducting fluids. We develop a rigorous theory resolving challenges not addressed before, including boundary conditions for thermal heat flux, structure of perturbation waves, and dependence of waves coupling on system parameters in a broad range of conditions. We discover the novel class of fluid instabilities in the three regimes—advection, diffusion, and low Mach—with properties that were never earlier discussed and that are defined by the interplay of the thermal heat flux, thermal conductivity and destabilizing acceleration with the inertial stabilization. We reveal the parameter controlling transitions between the regimes through varying the initial conditions. We find that the interface stability is set primarily by the macroscopic inertial mechanism balancing the destabilizing acceleration. The thermal heat flux and the microscopic thermodynamics create vortical fields in the bulk. By linking micro to macro scales, the interface is the place where balances are achieved.

Article highlights

This work yields the general theory of interface dynamics in a broad range of conditions.

The interplay is explored of inertial stabilization, destabilizing acceleration, thermal conductivity and heat flux.

We discover that interface is the place where balances are achieved through linking micro to macro scales.
Measuring When a Music Generation Algorithm Copies Too Much: The Originality Report, Cardinality Score, and Symbolic Fingerprinting by Geometric Hashing
Authors: Yin Zongyu , Reuben Federico , Stepney Susan , Collins Tom 
Published: June 2022

AbstractResearch on automatic music generation lacks consideration of the originality of musical outputs, creating risks of plagiarism and/or copyright infringement. We present the originality report—a set of analyses that is parameterised by a “similarity score”—for measuring the extent to which an algorithm copies from the input music. First, we construct a baseline, to determine the extent to which human composers borrow from themselves and each other in some existing music corpus. Second, we apply a similar analysis to musical outputs of runs of MAIA Markov and Music Transformer generation algorithms, and compare the results to the baseline. Third, we investigate how originality varies as a function of Transformer’s training epoch. Fourth, we demonstrate the originality report with a different “similarity score” based on symbolic fingerprinting, encompassing music with more complex, expressive timing information. Results indicate that the originality of Transfomer’s output is below the 95% confidence interval of the baseline. Musicological interpretation of the analyses shows that the Transformer model obtained via the conventional stopping criteria produces single-note repetition patterns, resulting in outputs of low quality and originality, while in later training epochs, the model tends to overfit, producing copies of excerpts of input pieces. Even with a larger data set, the same copying issues still exist. Thus, we recommend the originality report as a new means of evaluating algorithm training processes and outputs in future, and question the reported success of language-based deep learning models for music generation. Supporting materials (data sets and code) are available via https://osf.io/96emr/.
A Fully Automated Methodology for the Selection and Extraction of Energy-Relevant Features for the Energy Consumption of Battery Electric Vehicles
Authors: Petersen Patrick , Sax Eric 
Published: June 2022

AbstractCompared to traditional vehicles, battery electric vehicles (BEVs) have a limited driving range. Therefore, accurately estimating the range of BEVs is an important requirement to eliminate range anxiety, which describes the driver’s fear of getting stranded. However, range estimators used in currently available BEVs are not accurate enough. To overcome this problem, more precise energy estimation techniques have been investigated. Modeling the energy consumption of BEVs is essential to obtaining an accurate estimation. For accurately estimating the energy consumption, many non-deterministic influencing factors such as weather and traffic conditions, driving style, and the travel route need to be considered. Thus, reducing the possible feature space to improve estimation is necessary. In consequence, we propose a fully automatic methodology to select and extract a subset of energy-relevant features. Utilizing existing real-world data to investigate all types of influencing factors. Taking into account different segmentation methods, data scalers, feature selection, and extraction techniques, our methodology uses the full range of combinations to identify the combination that yields the best subset of features.
Improving the local climate zone classification with building height, imperviousness, and machine learning for urban models
Authors: Fung Kwun Yip , Yang Zong-Liang , Niyogi Dev 
Published: June 2022

AbstractThe Local Climate Zone (LCZ) classification is already widely used in urban heat island and other climate studies. The current classification method does not incorporate crucial urban auxiliary GIS data on building height and imperviousness that could significantly improve urban-type LCZ classification utility as well as accuracy. This study utilized a hybrid GIS- and remote sensing imagery-based framework to systematically compare and evaluate different machine and deep learning methods. The Convolution Neural Network (CNN) classifier outperforms in terms of accuracy, but it requires multi-pixel input, which reduces the output’s spatial resolution and creates a tradeoff between accuracy and spatial resolution. The Random Forest (RF) classifier performs best among the single-pixel classifiers. This study also shows that incorporating building height dataset improves the accuracy of the high- and mid-rise classes in the RF classifiers, whereas an imperviousness dataset improves the low-rise classes. The single-pass forward permutation test reveals that both auxiliary datasets dominate the classification accuracy in the RF classifier, while near-infrared and thermal infrared are the dominating features in the CNN classifier. These findings show that the conventional LCZ classification framework used in the World Urban Database and Access Portal Tools (WUDAPT) can be improved by adopting building height and imperviousness information. This framework can be easily applied to different cities to generate LCZ maps for urban models.
Deciphering dissolved organic matter by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS): from bulk to fractions and individuals
Authors: Qi Yulin , Xie Qiaorong , Wang Jun-Jian , He Ding , Bao Hongyan , Fu Qing-Long , Su Sihui , Sheng Ming , Li Si-Liang , Volmer Dietrich A. , Wu Fengchang , Jiang Guibin , Liu Cong-Qiang , Fu Pingqing 
Published: June 2022

AbstractExploring the source, transformation pathways, and the fate of natural organic matter (NOM) is critical to understanding the regional/global carbon cycle and carbon budget. The dissolved fraction of NOM, i.e., dissolved organic matter (DOM), is a complex mixture resulting from the transformation of plant, animal and microbial matter and plays a crucial role in many biogeochemical processes at the land-ocean-atmosphere interfaces. The advance of Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS) makes the detailed characterization of DOM at the molecular level possible. On the other hand, elucidation of complex DOM sample also presents significant analytical challenges, and these challenges also act as a driving force for the instrumentation and methodology development on FT-ICR MS. This review article has been written to aid those working in biogeochemistry, environmental and atmospheric chemistry, and related areas which investigate elemental cycles and DOM transformations. First, the fundamental theory, historical perspective, and recent advances in the field have been introduced. The detailed molecular characterization of environmental and geological samples continues to present significant analytical challenges, and it also has become a driving force for the development of the instrumentation and experimental methods. These achievements in DOM analysis have had an impact upon the fields of environmental science, geochemistry, and analytical chemistry. Next, varieties of applications of FT-ICR MS have also been described, followed by our view of the future of this technique in earth science research. We believe that this review covers the essential pairing of FT-ICR MS and collectively offers environmental and geochemical scientists a substantial resource for their research.
Graphical abstract
Biochar mitigates allelopathy through regulating allelochemical generation from plants and accumulation in soil
Authors: Chen Quan , Lan Pinyao , Wu Min , Lu Meng , Pan Bo , Xing Baoshan 
Published: June 2022

AbstractSoil health is a key factor for the global food security. One of the main bottlenecks for the efficient utilization of farmland soil is the accumulation of allelochemicals excreted by plant roots, leached and volatilized from plants, and released during the decomposition of plant residues. The negative impacts derived from allelochemicals include: decreasing soil fertility, breaking the balance of soil microbial community, reducing seed germination rate and crop yield, and interfering with the growth of neighboring or successive plants. Recently, biochar, a soil amendment with low cost and high performance, is extensively studied on its functions and effects on farmland systems. In this review, we focused on the potential role of biochar in controlling the environmental fate and risk of allelochemicals in soils. The source and potential toxicity of allelochemicals in farmland and the deficiencies in current methods for alleviating the allelopathy were summarized first, followed by the discussion on their sorption and degradation by biochar as well as the impact of biochar properties on the performance and mechanism. At the same time, the generation of allelochemicals regulated by biochar through improving plant growth conditions was analyzed. The modification of biochar for alleviating the allelopathy and then overcoming the obstacles of agricultural production was also addressed. Future research directions, such as targeted biochar production, the interactions between different allelochemicals and biochar investigated by simulations and modeling, negative effects and stability of biochar or modified biochar, were then proposed. This review will provide useful theoretical and technical supports for targeted biochar applications in soils with allelopathy.
Graphical abstract
Engineered biochar for environmental decontamination in aquatic and soil systems: a review
Authors: Chen Hanbo , Gao Yurong , Li Jianhong , Fang Zheng , Bolan Nanthi , Bhatnagar Amit , Gao Bin , Hou Deyi , Wang Shengsen , Song Hocheol , Yang Xing , Shaheen Sabry M. , Meng Jun , Chen Wenfu , Rinklebe Jörg , Wang Hailong 
Published: June 2022

AbstractContamination of aquatic and soil systems by organic and inorganic pollutants has become a serious issue of concern worldwide. Viable and cost-effective solutions are urgently needed to mitigate the negative impacts of diverse pollutants on the environment and human health. Biochar has emerged as an effective and green material for the remediation of a wide spectrum of (in)organic pollutants. However, applications of pristine biochar in decontamination have encountered bottlenecks due to its limited properties which cannot meet the desired remediation requirements. Therefore, multiple modification methods have been developed for tailoring the physicochemical properties of biochar to enhance its effectiveness in environmental decontamination. This work provides a holistic review on the recent advances on the synthesis of engineered biochar using physical, chemical, and biological methods. Further applications and related mechanisms of engineered biochar in the field of environmental decontamination in aquatic and soil systems have also been summarized and discussed. In addition, existing challenges and research gaps are outlined, and future research needs are proposed. This review summarizes the scientific opportunities for a comprehensive understanding of using engineered biochars as effective materials for the remediation of contaminated water and soil.
Graphical abstract
Thermal stabilization effect and oxygen replacement reaction together regulate N/S co-doped microporous carbon synthesis
Authors: Shi Shanshan , Jia Chao , Huo Xiaoyu , Zhang Shicheng , Xu Qunjie , Zhu Xiangdong 
Published: June 2022

AbstractPotassium thiocyanate (KSCN) activation showed great potential to prepare N/S co-doped microporous carbon for environmental remediation, however, predictable preparation for targeted application was a challenge. This study suggested that thermal stabilization effect and oxygen replacement reaction during KSCN activation could together regulate pore formation and N/S co-doping. Results showed that carbonaceous precursor with high thermal stability (expressed by high R50 index) could support stable carbon matrix for KSCN pore-forming. Meanwhile, carbonaceous precursor with high polarity (expressed by high O/C) was more prone to occur oxygen replacement reaction, promoting N/S co-doping. N/S co-doped microporous carbon with high micropore surface area can promote BPA adsorption via the pore-filling mechanism. However, reaction induced by S contained groups can enhance heavy metal (Pb2+) adsorption while prepared material with S doping. In summary, a carbonaceous precursor with high R50 index was conducive to preparing carbon material for organic pollutant adsorption, while the carbonaceous precursor with high O/C was suit to fabricate carbon material with high adsorption capacity for Pb2+ immobilization. This study provided important insights into the directional synthesis of optimized N/S doped microporous carbon.
Graphical Abstract