bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nitrogen and sulfur-doped biochar supported magnetic CuZnFe2O4 as a sustainable adsorbent for efficient reactive black dye 5 removal from industrial wastewater
Authors: Abdelfatah Ahmed M. , Fawzy Manal , El-Khouly Mohamed E. , Eltaweil Abdelazeem S. 
Published: February 2024

AbstractThe shortage of clean and safe water resources, due to the growing pollution and the high cost of water treatment techniques, has become a real threat. Herein, CuZnFe2O4@N,S-doped biochar (CZF@N,S-BC), a novel magnetic, cleaner, and completely green-based composite, was fabricated using the aqueous extract of Beta vulgaris (sugar beet) leaves for the efficient removal of reactive black dye 5 (RB5) from industrial wastewater discharge. With the aid of numerous techniques, including Fourier-Transform Infrared Spectroscopy (FTIR), X-ray Photoelectron Spectroscopy (XPS), Scanning Electron Spectroscopy (SEM), Vibrating Sample Magnetometer (VSM), and zeta potential analyses, CZF@N,S-BC was well-characterized. The results revealed the successful fabrication of CZF@N,S-BC with good magnetic saturation of 12 emu/g and a highly positively charged surface of 32 mV at pH 2. The removal efficiency of RB5 was reached 96.5% at equilibrium time 60 min, and adsorbent dose of 80 mg. The equilibrium data fitted well with the Freundlich isotherm model, while the adsorption kinetics followed a pseudo-second-order model (PSO), with a maximum adsorption capacity of 276.57 mg/g. The thermodynamics results confirmed the physical interaction between the composite and RB5. Additionally, the composite also demonstrated exceptional reusability, maintaining a removal efficiency of 57.27% even after six consecutive cycles. To evaluate the performance of CZF@N,S-BC composite in a real water matrix, the composite was subjected to remove RB5 from a real wastewater sample obtained from an industrial discharge of a textile dyeing industry. Also, a plausible mechanism of RB5 removal by the composite was intensively discussed using XPS before and after adsorption.
Portable smartphone-based molecular test for rapid detection of Leishmania spp.
Authors: Kobialka Rea Maja , Ceruti Arianna , Roy Madhurima , Roy Sutopa , Chowdhury Rajashree , Ghosh Prakash , Hossain Faria , Weidmann Manfred , Graf Elena , Bueno Alvarez Jesus , Moreno Javier , Truyen Uwe , Mondal Dinesh , Chatterjee Mitali , Abd El Wahed Ahmed 
Published: February 2024

Abstract
Purpose
Leishmaniasis, caused by the parasite of the genus Leishmania, is a neglected tropical disease which is endemic in more than 60 countries. In South-East Asia, Brazil, and East Africa, it mainly occurs as kala-azar (visceral leishmaniasis, VL), and subsequently as post kala-azar dermal leishmaniasis (PKDL) in a smaller portion of cases. As stated per WHO roadmap, accessibility to accurate diagnostic methods is an essential step to achieve elimination. This study aimed to test the accuracy of a portable minoo device, a small battery-driven, multi-use fluorimeter operating with isothermal technology for molecular diagnosis of VL and PKDL.

Methods
Fluorescence data measured by the device within 20 min are reported back to the mobile application (or app) via Bluetooth and onward via the internet to a backend. This allows anonymous analysis and storage of the test data. The test result is immediately returned to the app displaying it to the user.

Results
The limit of detection was 11.2 genome copies (95% CI) as determined by screening a tenfold dilution range of whole Leishmania donovani genomes using isothermal recombinase polymerase amplification (RPA). Pathogens considered for differential diagnosis were tested and no cross-reactivity was observed. For its diagnostic performance, DNA extracted from 170 VL and PKDL cases, comprising peripheral blood samples (VL, n = 96) and skin biopsies (PKDL, n = 74) from India (n = 108) and Bangladesh (n = 62), was screened. Clinical sensitivity and specificity were 88% and 91%, respectively.

Conclusion
Minoo devices can offer a convenient, cheaper alternative to other molecular diagnostics. Its easy handling makes it ideal for use in low-resource settings to identify parasite burden.
Janus Quasi-Solid Electrolyte Membranes with Asymmetric Porous Structure for High-Performance Lithium-Metal Batteries
Authors: Chen Zerui , Zhao Wei , Liu Qian , Xu Yifei , Wang Qinghe , Lin Jinmin , Wu Hao Bin 
Published: February 2024

AbstractQuasi-solid electrolytes (QSEs) based on nanoporous materials are promising candidates to construct high-performance Li-metal batteries (LMBs). However, simultaneously boosting the ionic conductivity (σ) and lithium-ion transference number (t+) of liquid electrolyte confined in porous matrix remains challenging. Herein, we report a novel Janus MOFLi/MSLi QSEs with asymmetric porous structure to inherit the benefits of both mesoporous and microporous hosts. This Janus QSE composed of mesoporous silica and microporous MOF exhibits a neat Li+ conductivity of 1.5 × 10–4 S cm−1 with t+ of 0.71. A partially de-solvated structure and preference distribution of Li+ near the Lewis base O atoms were depicted by MD simulations. Meanwhile, the nanoporous structure enabled efficient ion flux regulation, promoting the homogenous deposition of Li+. When incorporated in Li||Cu cells, the MOFLi/MSLi QSEs demonstrated a high Coulombic efficiency of 98.1%, surpassing that of liquid electrolytes (96.3%). Additionally, NCM 622||Li batteries equipped with MOFLi/MSLi QSEs exhibited promising rate performance and could operate stably for over 200 cycles at 1 C. These results highlight the potential of Janus MOFLi/MSLi QSEs as promising candidates for next-generation LMBs.
Advances in cofactor immobilization for enhanced continuous-flow biocatalysis
Authors: Reus Bente , Damian Matteo , Mutti Francesco G. 
Published: February 2024

AbstractThe merging of biocatalysis with continuous-flow chemistry opens up new opportunities for sustainable and efficient chemical synthesis. Cofactor-dependent enzymes are essential for various industrially attractive biocatalytic reactions. However, implementing these enzymes and biocatalytic reactions in industry remains challenging due to the inherent cost of cofactors and the requirement for their external supply in significant quantities. The development of efficient, low cost, simple and versatile methods for cofactor immobilization can address this important obstacle for biocatalysis in flow. This review explores recent progress in cofactor immobilization for biocatalysis by analyzing advantages and current limitations of the available methods that comprise covalent tethering, ionic adsorption, physical entrapment, and hybrid variations thereof. Moreover, this review analyzes all these immobilization techniques specifically for their utilization in continuous-flow chemistry and provides a perspective for future work in this area. This review will serve as a guide for steering the field towards more sustainable and economically viable continuous-flow biocatalysis.
Graphical Abstract
Medical student health care: a single center pilot study of utilization and barriers
Authors: Pazzi Carlotta , Farrehi Clara , Capron Maclain , Stillman Michael 
Published: February 2024

AbstractAccessing routine healthcare is known to be challenging for medical students and previous studies have explored the utilization of mental health and primary medical care services in this population. This single-institution study investigated not only usage of primary medical and mental health care among medical students, but also of vision and dental care services. Additionally, the study examined perceived barriers to healthcare access. Analysis of our 38-item questionnaire revealed that fewer participants sought vision and dental care after starting medical school than before enrolling and that lack of time was the predominant barrier to accessing health care services. Many respondents reported that their mental health condition had worsened during medical school, and among respondents with mental health conditions, 39.1% had faced financial barriers to receiving appropriate care. Protecting time for primary care appointments, subsidizing medical insurance, and creating student-specific clinics were frequently suggested by survey participants to improve access to care for this population. These responses suggest the need for further investigation into financial barriers to care experienced by medical students.
Hommes de lettres et révolution scientifique
Authors: Rabinovitch Oded 
Published: February 2024

RésuméAu contraire d’autres mouvements équivalents, lemouvement scientifique né dans l’Europe du xviie siècle s’inscrivit dans la durée au lieu de s'essouffler au bout de quelques générations. Afin de comprendre cette persistance, cet article s’appuie sur le cas de la France au temps de Louis XIV (r. 1643-1715). Il soutient que les hommes de lettres ont joué un rôle crucial dans la légitimation du mouvement scientifique naissant. Ces hommes de lettres, qui jouissaient d’une affinité sociale, intellectuelle et esthétique avec la « nouvelle science », tissèrent le récit du progrès scientifique en mettant en avant l’idée d’une rupture radicale avec le passé. Défenseurs des idées modernes ou des modèles classiques, ils diffusèrent ce récit au sein de l'élite culturelle, mobilisant penseurs, découvertes et instruments scientifiques de leur époque à travers des débats variés. Ce faisant, ils forgèrent le récit d'une « révolution scientifique », qui exerça une profonde influence sur l’histoire sociale et culturelle de la science moderne.
Telematics combined actuarial neural networks for cross-sectional and longitudinal claim count data
Authors: Duval Francis , Boucher Jean-Philippe , Pigeon Mathieu 
Published: February 2024

AbstractWe present novel cross-sectional and longitudinal claim count models for vehicle insurance built upon the combinedd actuarial neural network (CANN) framework proposed by Wüthrich and Merz. The CANN approach combines a classical actuarial model, such as a generalized linear model, with a neural network. This blending of models results in a two-component model comprising a classical regression model and a neural network part. The CANN model leverages the strengths of both components, providing a solid foundation and interpretability from the classical model while harnessing the flexibility and capacity to capture intricate relationships and interactions offered by the neural network. In our proposed models, we use well-known log-linear claim count regression models for the classical regression part and a multilayer perceptron (MLP) for the neural network part. The MLP part is used to process telematics car driving data given as a vector characterizing the driving behavior of each insured driver. In addition to the Poisson and negative binomial distributions for cross-sectional data, we propose a procedure for training our CANN model with a multivariate negative binomial specification. By doing so, we introduce a longitudinal model that accounts for the dependence between contracts from the same insured. Our results reveal that the CANN models exhibit superior performance compared to log-linear models that rely on manually engineered telematics features.
Evaluation of intravenous amoxicillin-clavulanate use in two Canadian hospitals
Authors: Wong Maggie , Malhotra Sangita , Afra Kevin 
Published: February 2024

Abstract
We describe our experience with intravenous amoxicillin-clavulanate, which is new to the Canadian market. The majority of patients were successfully de-escalated from piperacillin-tazobactam or a carbapenem for respiratory infections or skin and soft tissue infections. Intravenous amoxicillin-clavulanate provides a good alternative in an era of rising Pseudomonas aeruginosa resistance.
A systematic approach to defining and verifying descriptors used in the Qualitative Behavioural Assessment of sows
Authors: Ibach Sarah , Chou Jen-Yun , Battini Monica , Parsons Thomas D 
Published: February 2024

Abstract
Qualitative Behaviour Assessment (QBA) is a welfare evaluation tool that uses a holistic approach to capturing an animal’s emotional state. Lists of QBA descriptors validated to assess pig welfare exist, but their definitions are often not described in peer-reviewed literature and the processes used to develop definitions are lacking. The objective of this study is to detail a systematic approach to creating clear definitions for a pre-existing fixed list of QBA descriptors and test their application. A fixed list of 20 descriptors from the EU Welfare Quality® assessment protocol for pigs was modified, and ten pig experts were recruited to assist with defining these descriptors in a focus group-style discussion. Half of the experts involved in creating descriptor definitions partook in a subsequent step, where the newly developed definitions were tested by implementing QBA on a video library of post-weaned sows selected to capture the breadth of sow behaviour. Experts displayed excellent agreement in identifying a PCA dimension interpreted as the valence of descriptors and good agreement for another reflecting arousal. Inter-observer reliability was also measured for each descriptor. Only two descriptors exhibited less than moderate agreement between experts whereas half of the descriptors evoked substantial agreement or better. These findings support our process to delineate clear definitions for a fixed list of QBA descriptors in pigs. This study is the first of its kind detailing the in-depth process of creating and verifying descriptor definitions for future use in sow welfare assessment.
Antidumping Protectionism and Globalized Economies
Authors: Coleman Tyler 
Published: February 2024

AbstractWhy do firms demand antidumping protectionism? Contemporary literature highlights a plethora of causal mechanisms within the data-generating process, including retaliatory motives, exchange rate appreciations, business cycles, and deindustrialization. I argue that countries that are economically integrated into global markets should be associated with less demand for antidumping trade remedies. In particular, countries with higher levels of trade and financial flows should receive fewer petitions for antidumping trade remedies from firms overall, ceteris paribus. I test this theoretical argument with a series of de facto globalization indicators collected from thirty-three countries between 1978 and 2022, finding support for these arguments.
Philosophical Agreement and Philosophical Progress
Authors: Smith Julia 
Published: February 2024

Abstract
In the literature on philosophical progress it is often assumed that agreement is a necessary condition for progress. This assumption is sensible only if agreement is a reliable sign of the truth, since agreement on false answers to philosophical questions would not constitute progress. This paper asks whether agreement among philosophers is (or would be) likely to be a reliable sign of truth. Insights from social choice theory are used to identify the conditions under which agreement among philosophers would be a reliable indicator of the truth, and it is argued that we lack good reason to think that philosophical inquiry meets these conditions. The upshot is that philosophical agreement is epistemically uninformative: agreement on the answer to a philosophical question does not supply even a prima facie reason to think that the agreed-upon view is true. However, the epistemic uninformativeness of philosophical agreement is not an indictment of philosophy's progress, because philosophy is valuable independent of its ability to generate agreement on the correct answers to philosophical questions.
Length of antibiotic therapy among adults hospitalized with uncomplicated community-acquired pneumonia, 2013–2020
Authors: McCarthy Natalie L. , Baggs James , Wolford Hannah , Kazakova Sophia V. , Kabbani Sarah , Attell Brandon K. , Neuhauser Melinda M. , Walker Lindsey , Yi Sarah H. , Hatfield Kelly M. , Reddy Sujan , Hicks Lauri A. 
Published: February 2024

AbstractObjective:The 2014 US National Strategy for Combating Antibiotic-Resistant Bacteria (CARB) aimed to reduce inappropriate inpatient antibiotic use by 20% for monitored conditions, such as community-acquired pneumonia (CAP), by 2020. We evaluated annual trends in length of therapy (LOT) in adults hospitalized with uncomplicated CAP from 2013 through 2020.Methods:We conducted a retrospective cohort study among adults with a primary diagnosis of bacterial or unspecified pneumonia using International Classification of Diseases Ninth and Tenth Revision codes in MarketScan and the Centers for Medicare & Medicaid Services databases. We included patients with length of stay (LOS) of 2–10 days, discharged home with self-care, and not rehospitalized in the 3 days following discharge. We estimated inpatient LOT based on LOS from the PINC AI Healthcare Database. The total LOT was calculated by summing estimated inpatient LOT and actual postdischarge LOT. We examined trends from 2013 to 2020 in patients with total LOT >7 days, which was considered an indicator of likely excessive LOT.Results:There were 44,976 and 400,928 uncomplicated CAP hospitalizations among patients aged 18–64 years and ≥65 years, respectively. From 2013 to 2020, the proportion of patients with total LOT >7 days decreased by 25% (68% to 51%) among patients aged 18–64 years and by 27% (68%–50%) among patients aged ≥65 years.Conclusions:Although likely excessive LOT for uncomplicated CAP patients decreased since 2013, the proportion of patients treated with LOT >7 days still exceeded 50% in 2020. Antibiotic stewardship programs should continue to pursue interventions to reduce likely excessive LOT for common infections.
Attitudes toward automation and the demand for policies addressing job loss: the effects of information about trade-offs
Authors: Magistro Beatrice , Loewen Peter , Bonikowski Bart , Borwein Sophie , Lee-Whiting Blake 
Published: February 2024

AbstractDoes providing information about the costs and benefits of automation affect the perceived fairness of a firm's decision to automate or support for government policies addressing automation's labor market consequences? To answer these questions, we use data from vignette and conjoint experiments across four advanced economies (Australia, Canada, the UK, and the US). Our results show that despite people's relatively fixed policy preferences, their evaluation of the fairness of automation—and therefore potentially the issue's political salience—is sensitive to information about its trade-offs, especially information about price changes attributable to automated labor. This suggests that the political impact of automation may depend on how it is framed by the media and political actors.
Trainee-perceived benefits of a virtual temporal bone competition
Authors: Yao Alexander , Richards Emma , Dalton C. Lucy 
Published: February 2024

AbstractObjectiveTo assess the perceived benefits of a novel educational approach for otolaryngology trainees: a virtual reality temporal bone simulator drilling competition.MethodsRegional otolaryngology trainees participated in the competition. Drilling activities using the Voxel-Man TempoSurg simulator were scored by experts. Questionnaires that contained questions covering motivators for attending, perceived learning and enjoyment were sent to participants. Agreement with statements was measured on a 10-point Likert scale (1 = strongly disagree, 10 = strongly agree).ResultsEighteen trainees participated. The most cited reason for attending was for learning and/or education (61 per cent), with most attendees (72 per cent) believing that competition encourages more reading and/or practice. Seventeen attendees (94 per cent) believed Voxel-Man TempoSurg-based simulation would help to improve intra-operative performance in mastoidectomy (mean 7.83 ± 1.47, p < 0.001) and understanding of anatomy (mean 8.72 ± 1.13, p < 0.001). All participants rated the competition as ‘fun’ and 83 per cent believed the competitive element added to this.ConclusionThe virtual reality temporal bone competition is a novel educational approach within otolaryngology that was positively received by otolaryngology trainees.
Learning in European Administrative Networks: a process to all or only to a few?
Authors: Soares Ana Carolina 
Published: February 2024

AbstractThrough the pooling and exchange of resources such as expertise and knowledge between network participants, European Administrative Networks (EANs) are expected to play a significant role in enhancing policy learning. Yet, scarce empirical evidence has been presented concerning the learning process taking place within EANs. This paper addresses this gap through the analysis of the Network of the Heads of European Environmental Protection Agencies (EPA Network). Based on a unique survey dataset, social network analysis and exponential random graph models are used to trace the interaction patterns within the network and test which factors shape them. The analysis highlights the relevance of national political factors – i.e. the preferences of national governments and ministries – in shaping the learning processes taking place in the EPA Network. While the network is an important venue for disseminating knowledge between directly and indirectly connected actors, learning processes are mainly limited to like-minded peers.
Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding
Authors: Fang Xinyuan , Hu Xiaonan , Li Baoli , Su Hang , Cheng Ke , Luan Haitao , Gu Min 
Published: February 2024

AbstractMachine learning with optical neural networks has featured unique advantages of the information processing including high speed, ultrawide bandwidths and low energy consumption because the optical dimensions (time, space, wavelength, and polarization) could be utilized to increase the degree of freedom. However, due to the lack of the capability to extract the information features in the orbital angular momentum (OAM) domain, the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network model. Here, we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network (CNN) based on Laguerre-Gaussian (LG) beam modes with diverse diffraction losses. The proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction, and deep-learning diffractive layers as a classifier. The resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding, leading to an accuracy as high as 97.2% for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes, as well as a resistance to eavesdropping in point-to-point free-space transmission. Moreover, through extending the target encoded modes into multiplexed OAM states, we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%. Our work provides a deep insight to the mechanism of machine learning with spatial modes basis, which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.