bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accelerating metabolic models evaluation with statistical metamodels: application to Salmonella infection models
Authors: Frioux Clémence , Huet Sylvie , Labarthe Simon , Martinelli Julien , Malou Thibault , Sherman David , Taupin Marie-Luce , Ugalde-Salas Pablo 
Published: August 2023

Mathematical and numerical models are increasingly used in microbial ecology to model the fate of microbial communities in their ecosystem. These models allow to connect in a mechanistic framework species-level informations, such as the microbial genomes, with macro-scale features, such as species spatial distributions or metabolite gradients. Numerous models are built upon species-level metabolic models that predict the metabolic behaviour of a microbe by solving an optimization problem knowing its genome and its nutritional environment. However, screening the community dynamics with these metabolic models implies to solve such an optimization problem by species at each time step, leading to a significant computational load further increased by several orders of magnitude when spatial dimensions are added.
In this paper, we propose a statistical framework based on Reproducing Kernel Hilbert Space (RKHS) metamodels that are used to provide fast approximations of the original metabolic model. The metamodel can replace the optimization step in the system dynamics, providing comparable outputs at a much lower computational cost. We will first build a system dynamics model of a simplified gut microbiota composed of a unique commensal bacterial strain in interaction with the host and challenged by a Salmonella infection. Then, the machine learning method will be introduced, and particularly the ANOVA-RKHS that will be exploited to achieve variable selection and model parsimony. A training dataset will be constructed with the original system dynamics model and hyper-parameters will be carefully chosen to provide fast and accurate approximations of the original model. Finally, the accuracy of the trained metamodels will be assessed, in particular by comparing the system dynamics outputs when the original model is replaced by its metamodel. The metamodel allows an overall relative error of 4.71% but reducing the computational load by a speed-up factor higher than 45, while correctly reproducing the complex behaviour occurring during Salmonella infection. These results provide a proof-of-concept of the potentiality of machine learning methods to give fast approximations of metabolic model outputs and pave the way towards PDE-based spatio-temporal models of microbial communities including microbial metabolism and host-microbiota-pathogen interactions.
Instabilitäten und Arthrose des Sternoklavikulargelenks
Authors: Plath Johannes E. , Martetschläger Frank , Moroder Philipp , Sandmann Gunther 
Published: August 2023

ZusammenfassungDie Verletzung des Sternoklavikulargelenks (SCG) ist mit 3% der Schulterverletzungen und < 1% der Instabilitäten eine sehr seltene Verletzung. Folglich wird sowohl die Versorgung akuter Instabilitäten wie auch ihrer Folgezustände (chronische Instabilitäten/SCG-Arthrose) kontrovers diskutiert. Erfolgte bisher die Behandlung zumeist konservativ, so ist in den letzten Jahren eine Tendenz zur operativen Therapie zu erkennen. Durch erhebliche Gewalteinwirkung, wie sie bei Verkehrsunfällen oder Kontaktsportarten zu finden ist, kann es zur Zerreißung des an sich äußerst stabilen Bandapparates zwischen medialer Klavikula und Sternum kommen. Während die anteriore Luxation in den meisten Fällen leichter zu reponieren ist, verbleibt in bis zu 50% der Fälle eine Instabilität. Die posteriore Instabilität bedarf in den meisten Fällen – insbesondere auch aufgrund der anatomischen Nähe zu wichtigen kardiopulmonalen Strukturen – einer raschen Reposition. Sofern dies gelingt, ist die
Rate persistierender Instabilitäten gering. Für die chronischen Instabilitäten hat sich in den letzten Jahren die Rekonstruktion/Augmentation des Bandapparates mit Sehnengrafts in der „Figure-of-8-Konfiguration“ als Standardtechnik erwiesen. Für die Arthrose des SCG kommen OP-Techniken wie die Resektion des medialen Klavikulaendes dann in Betracht, wenn die konservative Therapie als gescheitert anzusehen ist.
Orthopädie und Unfallchirurgie 2023 – haben wir genug Nachwuchs?
Authors: Ruchholtz Steffen , Blätzinger Markus , Schädel-Höpfner Michael , Böcker Wolfgang , Kladny Bernd , Pennig Dietmar , Rudert Maximilian 
Published: August 2023

ZusammenfassungAllgemein zeichnet sich für Deutschland ein zunehmender Ärztemangel ab. Im Rahmen der
vorliegenden Umfrage soll die aktuelle Situation für orthopädische und/oder
unfallchirurgische Kliniken (O und U) dargestellt werden.Die Umfrage wurde vom 22.11. bis 5.12.2022 rein webbasiert über die Akademie für
Unfallchirurgie (AUC) und über den Verband der Leitenden Orthopäden und Unfallchirurgen
(VLOU) durchgeführt.185 Kliniken haben den Onlinefragebogen beantwortet. Unter den Antwortenden befanden
sich ca. 20% Universitätskliniken und Maximalversorger sowie ein Drittel
Schwerpunktversorger bzw. Grund- und Regelversorger. Mehr als die Hälfte (55%) der
Abteilungen gibt im Median 2,7 unbesetzte Stellen an. Freie Oberarztstellen gibt es in 47%
der Abteilungen mit offenen Stellen, freie Facharztstellen in 33% und freie
Assistenzarztstellen in 89%. In den Universitätskliniken bzw. Maximalversorgern wurden im
Vergleich zu den anderen O- und U-Kliniken am wenigsten offene Stellen (31–41%) angegeben.
Bezüglich der Einschätzung der Chefärzte zur Bewerbersituation allgemein wurden durchweg
negative Angaben gemacht.Mehr als die Hälfte der antwortenden Kliniken hatten unbesetzte Arztstellen. Um der
Entwicklung des zunehmenden Ärztemangels in O und U entgegenzuwirken, muss die generelle
Situation im Sinne einer Steigerung der klinisch tätigen Studienabgänger*innen und einer
Verbesserung der Arbeitsbedingungen für Ärztinnen und Ärzte optimiert werden. Gleichzeitig
sollten Abteilungen mit Studierendenausbildung ihre Aktivität mit Blick auf eine Steigerung
der Attraktivität des Faches O und U erhöhen.
Industry Payments and Academic Influence in Reconstructive Microsurgery
Authors: Sethi Ila , Mellia Joseph A. , Murphy Alexander I. , Diatta Fortunay , Asadourian Paul , Fischer John P. , Azoury Saïd C. , Bui Duc T. 
Published: August 2023

Abstract
Background Financial relationships between industry and microsurgeons help facilitate innovation but have the potential to bias a surgeon's academic work. To better understand industry–academic relationships, this study investigated the association between industry payments made to microsurgeons and their academic influence.
Methods A cross-sectional analysis of microsurgeons at Accreditation Council for Graduate Medical Education–accredited plastic surgery residency programs during the 2020–2021 academic year was performed. The Center for Medicare and Medicaid Services' Open Payments Database was used to collect industry payments (research and nonresearch related) to each surgeon. Academic influence was measured by Hirsch index (h-index) and number of publications. Mann–Whitney's U and Kruskal–Wallis' tests were used for statistical analysis.
Results Of the 199 microsurgeons identified, 156 (78.39%) received an industry nonresearch payment, but 0 (0.0%) received an industry research payment. Surgeons who received any amount of industry payments did not have a higher mean h-index or higher mean number of publications than surgeons with no industry payments. However, surgeons with total industry payments more than $10,000 (n = 15) had a higher number of publications than surgeons with no industry payments (135.47 vs. 36.02, p = 0.0074), $1 to $1,000 in payments (135.47 vs. 34.37, p = 0.0006), and $1,000 to $10,000 in payments (135.47 vs. 45.43, p = 0.0268). Surgeons with total industry payments more than $10,000 also had higher h-indices than surgeons with $1 to $1,000 in payments (24.4 vs. 10.34, p = 0.0039) and $1,000 to $10,000 in payments (24.4 vs. 11.34, p = 0.0413).
Conclusion Industry funding is associated with higher h-index and higher number of publications for high earners (> $10,000). Private companies may favor these surgeons for their academic expertise.
Definitions, phenomenology, diagnosis, and management of the disorders of laughter and crying in amyotrophic lateral sclerosis (ALS): Consensus from ALS and Motor Neuron Disease Scientific Department of the Brazilian Academy of Neurology
Authors: Gondim Francisco de Assis Aquino , Pinto Wladimir Bocca Vieira de Rezende , Chieia Marco Antônio Troccoli , Correia Carolina da Cunha , Cunha Francisco Marcos Bezerra , Dourado Jr Mário Emílio Teixeira , França Júnior Marcondes Cavalcante , Marques Júnior Wilson , Oliveira Acary Souza Bulle , Rodrigues Cleonisio Leite , Silva Delson José da , Dias-Tosta Elza 
Published: August 2023

AbstractThe spectrum of neuropsychiatric phenomena observed in amyotrophic lateral sclerosis (ALS) is wide and not fully understood. Disorders of laughter and crying stand among the most common manifestations. The aim of this study is to report the results of an educational consensus organized by the Brazilian Academy of Neurology to evaluate the definitions, phenomenology, diagnosis, and management of the disorders of laughter and crying in ALS patients. Twelve members of the Brazilian Academy of Neurology - considered to be experts in the field - were recruited to answer 12 questions about the subject. After exchanging revisions, a first draft was prepared. A face-to-face meeting was held in Fortaleza, Brazil on 9.23.22 to discuss it. The revised version was subsequently emailed to all members of the ALS Scientific Department from the Brazilian Academy of Neurology and the final revised version submitted for publication. The prevalence of pseudobulbar affect/pathological laughter and crying (PBA/PLC) in ALS patients from 15 combined studies and 3906 patients was 27.4% (N = 1070), ranging from 11.4% to 71%. Bulbar onset is a risk factor but there are limited studies evaluating the differences in prevalence among the different motor neuron diseases subtypes, including patients with and without frontotemporal dementia. Antidepressants and a combination of dextromethorphan and quinidine (not available in Brazil) are possible therapeutic options. This group of panelists acknowledge the multiple gaps in the current literature and reinforces the need for further studies.
Use of a Medication Safety Audit and Feedback Tool in the Emergency Department Is Affected by Prescribing Characteristics
Authors: Burningham Zach , Jackson George L. , Kelleher Jessica L. , Morris Isis , Stevens Melissa B. , Cohen Joy , Maloney Gerald , Sauer Brian C. , Halwani Ahmad S. , Chen Wei , Vaughan Camille P. 
Published: August 2023

Abstract
Background The Enhancing Quality of Prescribing Practices for Older Veterans Discharged from the Emergency Department (EQUIPPED) program developed an audit and feedback health information technology (IT) solution with the intent to replace the in-person academic detailing service provided by the program. The EQUIPPED dashboard provides emergency department (ED) providers with a personalized view of their prescribing performance.
Objectives Here, we analyze the association between ED provider characteristics and viewership of the EQUIPPED dashboard, adding insight into strategies for addressing barriers to initial use.
Methods We performed a retrospective analysis of EQUIPPED dashboard viewership among four Veterans Affairs (VA) EDs. We extracted quantitative data from user interaction logs to determine evidence of dashboard use. Provider characteristics and baseline potentially inappropriate medication (PIM) prescribing rate were extracted from the VA's Corporate Data Warehouse. Logistic regression was used to examine the association between dashboard use and provider characteristics.
Results A total of 82 providers were invited to receive audit and feedback via the EQUIPPED dashboard. Among invited providers, 40 (48.7%) had evidence of at least 1 dashboard view during the 1-year feedback period. Adjusted analyses suggest that providers with a higher baseline PIM prescribing rate were more likely to use the dashboard (odds ratio [OR]: 1.22; 95% confidence interval [CI]: 1.01–1.47). Furthermore, providers at ED site D were more likely to use the dashboard in comparison to the other sites (OR: 9.99; 95% CI: 1.72–58.04) and reportedly had the highest site-level baseline PIM rate.
Conclusion Providers with lower PIM prescribing rates (i.e., <5%) receive communication from an integrated dashboard reminder system that they are “optimal prescribers” which may have discouraged initial attempts to view the dashboard. Site D had the highest baseline PIM rate, but further qualitative investigation is warranted to better understand why site D had the greatest users of the dashboard.
Development and Validation of SafeHIT: An Instrument to Assess the Self-Reported Safe Use of Health Information Technology
Authors: Salahuddin Lizawati , Ismail Zuraini , Abdul Rahim Fiza , Anawar Syarulnaziah , Hashim Ummi Rabaah 
Published: August 2023

Abstract
Background Implementing health information technology (HIT) may cause unintended consequences and safety risks when incorrectly designed and used. Yet, the tools to assess self-reported safe use of HIT are not well established.
Objective This study aims to develop and validate SafeHIT, an instrument to assess self-reported safe use of HIT among health care practitioners.
Methods Systematic literature review and a semistructured interview with 31 experts were adopted to generate SafeHIT instrument items. In total, 450 physicians from various departments at three Malaysian public hospitals participated in the questionnaire survey to validate SafeHIT. Exploratory factor analysis and confirmatory factor analysis (CFA) were undertaken to explore the items that best represent a specific construct and to confirm the reliability and validity of the SafeHIT, respectively.
Results The final SafeHIT consisted of 14 constructs and 58 items in total. The result of the CFA confirmed that all constructs demonstrated adequate convergent and discriminant validity.
Conclusion A reliable and valid theoretically underpinned measure of determinants of safe HIT use behavior has been developed. Understanding external factors that influence safe HIT use is useful for developing targeted interventions that favor the quality and safety of health care.
Different estimation methods for the generalized unit half-logistic geometric distribution: Using ranked set sampling
Authors: Alsadat Najwan , Hassan Amal S. , Gemeay Ahmed M. , Chesneau Christophe , Elgarhy Mohammed 
Published: August 2023

The generalized unit half-logistic geometric distribution (GUHLGD) is a modern two-parameter unit distribution with attractive shape flexibility for the corresponding probability density and hazard rate functions. Due to its versatility, it may be used to model a variety of current bounded real-world datasets. On the other hand, an effective sampling strategy for both parametric and non-parametric inferences is the ranked set sampling (RSS) method. This article focuses on estimating the parameters of the GUHLGD based on the RSS method as well as the simple random sampling (SRS) method. Eleven traditional estimation methods are taken into consideration, including the percentile, Cramér–von Mises, maximum likelihood, Anderson–Darling, right-tailed Anderson–Darling, left-tailed Anderson–Darling, least squares, weighted least squares, minimum spacing absolute-log distance, maximum product of spacing, and minimum spacing absolute distance methods. A Monte Carlo simulation is employed to compare the performance of the resultant estimates based on some accuracy measures. We draw the conclusion that, for both sampling procedures, the maximum likelihood estimation methodology is the best option among the rest based on the partial and total ranking measures. The estimates based on the RSS method are more efficient than the others based on the SRS method. Results from actual data further support the advantage of the RSS design over the SRS design.
Quasi-equilibrium state based quantification of biological macromolecules in single-molecule localization microscopy
Authors: Chen Xuecheng , Li Yaqian , Li Xiaowei , Sun Jielin , Czajkowsky Daniel M , Shao Zhifeng 
Published: August 2023

Abstract
The stoichiometry of molecular components within supramolecular biological complexes is often an important property to understand their biological functioning, particularly within their native environment. While there are well established methods to determine stoichiometry in vitro, it is presently challenging to precisely quantify this property in vivo, especially with single molecule resolution that is needed for the characterization stoichiometry heterogeneity. Previous work has shown that optical microscopy can provide some information to this end, but it can be challenging to obtain highly precise measurements at higher densities of fluorophores. Here we provide a simple approach using already established procedures in single-molecule localization microscopy (SMLM) to enable precise quantification of stoichiometry within individual complexes regardless of the density of fluorophores. We show that by focusing on the number of fluorophore detections accumulated during the quasi equilibrium-state of this process, this method yields a 50-fold improvement in precision over values obtained from images with higher densities of active fluorophores. Further, we show that our method yields more correct estimates of stoichiometry with nuclear pore complexes and is easily adaptable to quantify the DNA content with nanodomains of chromatin within individual chromosomes inside cells. Thus, we envision that this straightforward method may become a common approach by which SMLM can be routinely employed for the accurate quantification of subunit stoichiometry within individual complexes within cells.
Carbon dots derived from citric acid and urea as fluorometric probe for determining melamine contamination in infant formula sample
Authors: Phimmasone Souliyanh , Boonsri Pornthip , Siangproh Weena , Ratanawimarnwong Nuanlaor , Jittangprasert Piyada , Mantim Thitirat , Limchoowong Nunticha , Songsrirote Kriangsak 
Published: August 2023

Abstract
Melamine has been intentionally added into food products to increase the protein count at less cost, especially in dairy products for infant resulting in serious adverse effects on health of consumers. Therefore, this study aimed to develop a method to quantify melamine in dairy products based on the change of fluorescent properties of carbon dots (CDs) as sensing probe. CDs with green-fluorescent emission were synthesized from citric acid and urea under microwave irradiation. The synthesized CDs emitted fluorescence at the maximum wavelength of 538 nm with excitation wavelength of 410 nm. Thus, they provided high sensitivity and selectivity on melamine detection by which fluorescent emission of the CDs was increasingly quenched upon increasing melamine concentrations. Optimal conditions for melamine determination using the CDs was under pH 6, volume ratio between CDs and sample of 2:8 and reaction time of 15 min. The developed method provided high precision of melamine determination with less than 5% of %RSD (n = 5), wide detection range from 1.0 to 200.0 ppm, and high sensitivity with limit of detection (LOD) of 0.47 ppm and limit of quantification (LOQ) of 1.56 ppm, which is within the regulated level by the Food and Drug Administration of the United States for melamine in dairy products. Several analytical characterization techniques were conducted to elucidate the reaction mechanism between CDs and melamine, and the hydrogen bonding interaction was proposed.
A systematic framework to improve the digital green innovation performance of photovoltaic materials for building energy system
Authors: Hu Chengli , Sun Tongtong , Yin Shi , Yin Jiayi 
Published: August 2023

Abstract
Under the current ‘double carbon’ policy, the building materials manufacturing industry has seriously restricted the improvement of social and environmental benefits. Digital green innovation (DGI) in photovoltaic building materials enterprises (PBMES) plays a crucial role in solving the problems of high-quality environmental and economic development. In order to make the DGI of PBMES more effective, it is very critical to evaluate the performance of the DGI activities of PBMES. First, the evaluation index system is constructed. Then, it constructs the theoretical framework of the DGI performance evaluation of PBMES. After that, on the basis of combining various evaluation methods, a combination evaluation model based on compatibility and consistency was constructed and the convergence test and consistency test of the combination evaluation results were carried out by means of the variance method and Spearman rank correlation coefficient, which verified the scientificity and validity of the method. Finally, using the evaluation model, 16 PBMES were empirically studied. It reflected that the DGI performance evaluation index system of PBMES is composed of four indexes, namely, technology input, economic output, scientific and technological output, and social effect. The key factors affecting the DGI performance of PBMES are the investment in talent training, the proportion of digital technology in green products, the success rate of digital innovation product development increased by DGI cooperation, and the digital level of adopting environmental management system. This article combines consistency-based evaluation methods to not only obtain reasonable evaluation results, but also fully utilize multi-level methods to better describe the evaluation object. The means provided in this article are a new way to solve the DGI performance evaluation of PBMES.
Numerical and experimental investigation of the droplet size for MQL aerosol under different operating parameters with Flow visualization
Authors: Jadhav Prasad A , Deivanathan R 
Published: August 2023

Abstract
Minimum quantity lubrication (MQL) is a sustainable machining process in which oil and air are mixed to form a spray that can be directed to the cutting zone. MQL spray factors like droplet size and velocity and their effect on machining remain unclear, especially when employing diverse oils and operating settings. Mist formation factors determine how well spray droplets lubricate the targeted area during machining. Numerical and Experimental studies were conducted with different values for MQL parameters like cutting oil type, air pressure and oil flow rate, to establish the best possible combination to give the ideal droplet size and surface roughness. The study utilized three types of oils and varied air pressures to evaluate the cooling effectiveness of MQL spray during end milling operations. Experimental droplet size and velocity measurements were obtained using ‘Phase Doppler Anemometry (PDA)’ and ‘Particle Image Velocimetry (PIV)’ techniques. A numerical model within ANSYS Fluent software, employing computational fluid dynamics (CFD), predicted spray flow properties and was validated using PIV data. Raising the air pressure decreased the droplet size, while increasing velocity to achieve greater overall speed and enhanced lubrication in the cutting region. Changing the coolant flow rate or the compressed air pressure affected the Sauter mean diameter (SMD) of oil particles. The research showed that increasing air pressure from 1 bar to 3 bar reduced surface roughness by 55.40 percent and SMD by 24.58 percent for 120V oil. Among the three cutting oils tested, the 120V oil achieved the lowest surface roughness at 0.227μm under specific conditions: a flow rate of 150 ml hr−1, pressure of 3 bars, and SMD of 35.5 μm. These findings provide valuable insights into improving MQL efficiency for machining operations.