bluuebunny/crossref_metadata_2025_split huggingface dataset:
Digital technology and healthcare delivery in insulin-treated adults with diabetes: a proposal for analysis of self-monitoring blood glucose patterns using a dedicated platform
Authors: Irace Concetta , Acmet Elena , Cutruzzolà Antonio , Parise Martina , Ponzani Paola , Scarpitta Antonietta Maria , Candido Riccardo 
Published: November 2023

Abstract
Purpose
A remote platform for diabetes care (Roche Diabetes® Care Platform, RDCP) has been developed that allows combined face-to-face consultations and remote patient monitoring (RPM).

Methods
A dedicated flowchart is proposed as a clinical approach to help healthcare professionals in the appropriate interpretation of structured self-monitoring blood glucose data, as visualized on the RDCP during the visits, and in the optimal management of patients using the integrated RDCP-RPM tools.

Results
The platform organizes patterns in different blocks: (i) hypoglycemia; (ii) hyperglycemia; (iii) blood glucose variability; (iv) treatment adherence, which identifies a possible individual pattern according to glycemic control challenges, potential causal factors, and behavioral type patterns. The flowchart proposed for use of the RDCP-RPM is self-explanatory and entails 3 steps: (1) evaluation of quality and quantity of self-monitoring blood glucose data; (2) pattern analysis; (3) personalized suggestions and therapy changes.

Conclusion
The main aim of the remote treatment flowchart proposed is to support healthcare professionals in the identification of hypoglycemic and hyperglycemic patterns using the RDCP regardless of the HbA1c value and ongoing treatment, which however, become crucial in combination with pattern analysis in the therapeutical choice.
Gradient-Based Competitive Learning: Theory
Authors: Cirrincione Giansalvo , Randazzo Vincenzo , Barbiero Pietro , Ciravegna Gabriele , Pasero Eros 
Published: November 2023

AbstractDeep learning has been recently used to extract the relevant features for representing input data also in the unsupervised setting. However, state-of-the-art techniques focus mostly on algorithmic efficiency and accuracy rather than mimicking the input manifold. On the contrary, competitive learning is a powerful tool for replicating the input distribution topology. It is cognitive/biologically inspired as it is founded on Hebbian learning, a neuropsychological theory claiming that neurons can increase their specialization by competing for the right to respond to/represent a subset of the input data. This paper introduces a novel perspective by combining these two techniques: unsupervised gradient-based and competitive learning. The theory is based on the intuition that neural networks can learn topological structures by working directly on the transpose of the input matrix. At this purpose, the vanilla competitive layer and its dual are presented. The former is representative of a standard competitive layer for deep clustering, while the latter is trained on the transposed matrix. The equivalence of the layers is extensively proven both theoretically and experimentally. The dual competitive layer has better properties. Unlike the vanilla layer, it directly outputs the prototypes of the data inputs, while still allowing learning by backpropagation. More importantly, this paper proves theoretically that the dual layer is better suited for handling high-dimensional data (e.g., for biological applications), because the estimation of the weights is driven by a constraining subspace which does not depend on the input dimensionality, but only on the dataset cardinality. This paper has introduced a novel approach for unsupervised gradient-based competitive learning. This approach is very promising both in the case of small datasets of high-dimensional data and for better exploiting the advantages of a deep architecture: the dual layer perfectly integrates with the deep layers. A theoretical justification is also given by using the analysis of the gradient flow for both vanilla and dual layers.
Detecting Shape-Based Interactions Among Environmental Chemicals Using an Ensemble of Exposure-Mixture Regression and Interpretable Machine Learning Tools
Authors: Midya Vishal , Gennings Chris 
Published: November 2023

AbstractThere is growing interest in discovering interactions between multiple environmental chemicals associated with increased adverse health effects. However, most existing approaches (1) either use a projection or product of multiple chemical exposures, which are difficult to interpret and (2) cannot simultaneously handle multi-ordered interactions. Therefore, we develop and validate a method to discover shape-based interactions that mimic usual toxicological interactions. We developed the Multi-ordered explanatory interaction (Moxie) algorithm by merging the efficacy of Extreme Gradient Boosting with the inferential power of Weighted Quantile Sum regression to extract synergistic interactions associated with the outcome/odds of disease in an adverse direction. We evaluated the algorithm’s performance through simulations and compared it with the currently available gold standard, the signed-iterative random forest algorithm. We used the 2017–18 US-NHANES dataset (n = 447 adults) to evaluate interactions among nine per- and poly-fluoroalkyl substances and five metals measured in whole blood in association with serum low-density lipoprotein cholesterol. In simulations, the Moxie algorithm was highly specific and sensitive and had very low false discovery rates in detecting true synergistic interactions of 2nd, 3rd, and 4th order through moderate (n = 250) to large (n = 1000) sample sizes. In NHANES data, we found a two-order synergistic interaction between cadmium and lead detected in people with whole-blood cadmium concentrations and lead above 0.605 ug/dL and 1.485 ug/dL, respectively. Our findings demonstrate a novel validated approach in environmental epidemiology for detecting shape-based toxicologically mimicking interactions by integrating exposure-mixture regression and machine learning methods.
Interpretation of empirical results in intervention studies: a commentary and kick-off for discussion
Authors: Büsch Dirk , Loffing Florian 
Published: November 2023

AbstractSports science as an empirical science produces study results that are to be interpreted hypothesis-oriented. The validity of the interpretation of statistically and practically significant results depends on the one hand on the theoretical foundation of the research question and on the other hand on the concrete methodological procedure in intervention studies. Considering hypotheses at the empirical-content and statistical level, recurring interpretation difficulties arise when numbers are translated into words or recommendations for action. On the basis of two examples, a discussion in the scientific community is to be initiated, which could be continued in this journal in case of corresponding interest in methodological issues.
Seasonal temperature and precipitation record breakings in Hungary in a warming world
Authors: Szabó Péter , Bartholy Judit , Pongrácz Rita 
Published: November 2023

AbstractClimate change is leading to new daily record-breaking values globally. Since there is a clear shift towards the higher temperature values, the ratio of the numbers of new record high temperatures to record lows indicates the acceleration of global warming differently at regional levels—but is there an amplification for precipitation records as well? The main purpose of this regional analysis is to determine how many record highs/lows are broken on a seasonal level, and how large the area affected is, which enables us to assess the potentially large impacts at a local scale. The analysis is based on the statistical characteristics that the number of record breakings decreases exponentially with time for a stationary climate (when natural variability prevails). The assessment focuses on Hungary and considers the past from 1971 and the future from 2021. Results suggest that (1) currently the ratio of the numbers of new record high to record low temperatures is higher in Hungary than globally, particularly for summer and autumn (around 3.5); (2) substantially more new warm records and almost no cold records are expected by the late century (with a ratio of 140–160) following a high emission scenario, particularly in summer, when the impacts of these record breakings are the largest; (3) new precipitation records in the region are much less affected by the anthropogenic activity.
Lean Ergonomics—an empirical combination of Management Science and Ergonomics
Authors: Brunner Stefan , Kühnel Klaus , Bengler Klaus 
Published: November 2023

AbstractThis paper presents Lean Ergonomics (LE) as an employee- and process-related method in a practice-oriented way. Stagnations in economic improvements of the processes, combined with known, high stresses of the basic workers on the shopfloor with ambiguous starting points of ergonomic measures hold broad analysis and optimization potential. This can be shown exploratively based on LE. 12 representative work processes at large reactors in the chemical industry form the study area. Each individual work process receives a Lean Ergonomics data set consisting of time data [standard deviation in min & %], objective ergonomics [EAWS] and subjective ergonomics [Borg, NASA-TLX; both pseudonymized]. Two process-identical production halls are provided, which is why KFzA (short questionnaire for work analysis) is also collected anonymously for additional general analysis of work system design. Consequently resulting in a diverse data structure of quantifiable person-related methods, objective, process-related loads and economically relevant, likewise process-related KPIs.
Level and Program Analytics of MUM-T System
Authors: Kim Byung Woon , Choi Ga Eun 
Published: November 2023

AbstractThis study establishes the concept and classification system of MUM-T for the operation and development of AI-based complex combat systems. We analyze the core aspects of this system: autonomy, interoperability, and program level. AI MUM-T can improve the survivability of manned systems, expand their operational range, and increase combat effectiveness. We analyze technical challenges and program levels using data from the USA and UK, which are building the AI MUM-T integrated combat system. Currently, MUM-T is at the level of complex operation of a manned platform and an unmanned aerial vehicle platform. In the mid to long term, interoperable communication between heterogeneous platforms such as unmanned ground vehicles, unmanned surface vehicles, and unmanned underwater vehicles is possible. Depending on the level of development of the common architecture and standard protocols for interoperability between AI MUM-T systems, MUM-T can evolve from the “1 to N” concept to various combinations of operating concepts from “N to N.” The difference of this study from existing studies is that the core technologies of the fourth industrial revolution, such as AI, autonomy, and data interoperability, are reflected in the MUM-T system. In addition, an AI-enabled autonomous MUM-T operation and facility classification system was established by reflecting AI and autonomy in the existing unmanned system taxonomy, and the level and program were analyzed taking this into consideration.
Literature review on the application of 5 mm endostaplers in pediatric endoscopic surgery
Authors: Rafe Tanvir , Ross Andrew 
Published: November 2023

AbstractThis non-systematic Pubmed review was performed to evaluate the use of 5 mm endostaplers in pediatric endoscopic surgery with results available in children aged between 1 day and 17 years. Three reports identified the use of the endostapler in bowel anastomosis, two in laparoscopic anorectoplasty and one in thoracoscopic resections of congenital lung malformations. Although the actual surgical application may be in larger number of patients, the number of published reports with regards to the application of the 5 mm endostapler in pediatric endoscopic procedures are limited and further reporting will provide better insights into further possible applications and outcomes.
A comparative analysis of design and analysis methods for steel connections: contrasting American and European perspectives
Authors: Naqash Muhammad Tayyab , Alluqmani Ayed Eid , Farooq Qazi Umar 
Published: November 2023

AbstractLoad transmission from one element to another is achieved using steel connections, making them an integral part of any structural design. This article examines the differences between the American Codes (AISC) and Eurocode 3 for the design and analysis of steel connections. Moment connections' stiffness, strength, and ductility as expressed in both codes are the core focus of this research. Each tactic's advantages and disadvantages have been detailed, and the effect of seismic load on steel connection design has been investigated. The feasibility of using techniques like haunches and stiffeners to enhance connection design is also explored. The study focuses on moment connections and how they fare under different loads and conditions like stiffness, strength, and ductility. Additionally, the effect of seismic loading on the development of steel connections is analyzed. Finally, the significance of testing and documentation to guarantee the safety and dependability of steel connections has been evaluated. This research can help engineers select a suitable code and connection typology for their projects for improved performance of the overall structural behaviour.
Drag on a plate perpendicular to the flow of an elasto-viscoplastic fluid
Authors: Jossic Laurent , Ouattara Zemihori , Gueye Moctar , Dufour Frédéric , Magnin Albert 
Published: November 2023

AbstractThe flow with no inertia of an elasto-viscoplastic fluid around a plate perpendicular to the flow direction was considered. Firstly, experiments were performed with a model yield stress fluid, an aqueous Carbopol gel. The viscoelastic behavior of the fluid is identified by steady and transient rheological measurements. The drag force on the plate has been measured as a function of the plate velocity in steady state and in relaxation after stopping the movement. The role of the initial stress state in the fluid was highlighted. Secondly, numerical simulations were carried out using the finite element method with Lagrangian integration points. As a first approach, the elasto-viscoplastic behaviour of the gel has been simplified by a constitutive equation based on the Maxwell and Herschel-Bulkley models. The solid–liquid transition is defined by the von Mises criterion. The comparison between experimental and numerical data are quite satisfactory.
Meta-Analysis on the Health Effects Resulting from Evacuation or Relocation
Authors: Adams Grace G. , MacMillan Laurel , Smith Todd , Sharp Amy , Casagrande Rocco 
Published: November 2023

Abstract

Objective:
Evacuation and relocation are key actions used to protect the public in response to natural or technological disasters, but there are inherent risks to both. Unfortunately, these risks have not been fully quantified, which limits the ability of emergency managers and the public to effectively balance the risks and benefits of evacuation or relocation. This work provides quantitative data on the risks of health effects from displacement following evacuation or relocation.

Methods:
Researchers performed a literature review and meta-analysis of published studies and quantified risks of 14 different health effects, including both physical and socio-behavioral outcomes, from studies of 9 different disaster types.

Results:
The findings show statistically significant increases in 9 of the 14 health effects in displaced populations, indicating an increased likelihood of experiencing detrimental health effects compared with nondisplaced populations. A pooled analysis of all negative health effects found an odds ratio of 1.49 (95% confidence interval: 1.24-1.79), which shows a significant relationship between displacement and negative health outcomes.

Conclusions:
These findings demonstrate that evacuated or relocated populations have an increased risk of experiencing negative health effects associated with displacement. The broad number of disaster types included mean that findings are applicable to any emergency evacuation or relocation.
Alcohol-based decontamination of gloved hands: A randomized controlled trial
Authors: Thom Kerri A. , Rock Clare , Robinson Gwen L. , Reisinger Heather R.S. , Baloh Jure , Chasco Emily , Liang Yuanyuan , Li Shanshan , Diekema Daniel J. , Herwaldt Loreen A. , Johnson J. Kristie , Harris Anthony D. , Perencevich Eli N. 
Published: November 2023

AbstractObjective:The gold standard for hand hygiene (HH) while wearing gloves requires removing gloves, performing HH, and donning new gloves between WHO moments. The novel strategy of applying alcohol-based hand rub (ABHR) directly to gloved hands might be effective and efficient.Design:A mixed-method, multicenter, 3-arm, randomized trial.Setting:Adult and pediatric medical-surgical, intermediate, and intensive care units at 4 hospitals.Participants:Healthcare personnel (HCP).Interventions:HCP were randomized to 3 groups: ABHR applied directly to gloved hands, the current standard, or usual care.Methods:Gloved hands were sampled via direct imprint. Gold-standard and usual-care arms were compared with the ABHR intervention.Results:Bacteria were identified on gloved hands after 432 (67.4%) of 641 observations in the gold-standard arm versus 548 (82.8%) of 662 observations in the intervention arm (P < .01). HH required a mean of 14 seconds in the intervention and a mean of 28.7 seconds in the gold-standard arm (P < .01). Bacteria were identified on gloved hands after 133 (98.5%) of 135 observations in the usual-care arm versus 173 (76.6%) of 226 observations in the intervention arm (P < .01). Of 331 gloves tested 6 (1.8%) were found to have microperforations; all were identified in the intervention arm [6 (2.9%) of 205].Conclusions:Compared with usual care, contamination of gloved hands was significantly reduced by applying ABHR directly to gloved hands but statistically higher than the gold standard. Given time savings and microbiological benefit over usual care and lack of feasibility of adhering to the gold standard, the Centers for Disease Control and Prevention and the World Health Organization should consider advising HCP to decontaminate gloved hands with ABHR when HH moments arise during single-patient encounters.Trial Registration: NCT03445676.
Executive compensation: investor preferences during say-on-pay votes and the role of proxy voting advisers
Authors: Gomtsian Suren 
Published: November 2023

AbstractShareholder say-on-pay voting allows institutional investors to influence the incentives of managers and, consequently, corporate behaviour. Surprisingly, the preferences of investors on executive compensation have been largely overlooked in the ongoing debates on the role of say-on-pay in corporate governance and the impact of shareholder stewardship on sustainable corporate behaviour. The analysis of investor disclosed explanations of say-on-pay votes in the FTSE 100 companies during 2013–2021 shows that institutional investors rely repeatedly on several dominant themes aimed at improving the incentives of corporate managers and controlling managerial rent extraction. But shareholder interests remain the core focus of say-on-pay votes, with only few investors demanding that companies reward executive directors for protecting the interests of a broader range of affected stakeholders. Additionally, most investors can be grouped into several clusters formed around the voting recommendations of proxy advisers. A group of UK-based institutional investors stands out by taking a more individualistic and diverse approach to the stewardship of executive compensation. These findings highlight the role of local investors in the oversight of executive pay, the growing influence of proxy advisers along with the increasing share of foreign institutional investors, and the influence of best practice governance codes in driving investor stewardship preferences.
Circum‐Cratonic Triassic Syenite Province of North China Craton Reveals Heterogeneous Lithospheric Mantle Related to Dual Subduction
Authors: Liu Xu , Peng Peng , Mitchell Ross N. , Wang Chong , Kang Jianli 
Published: November 2023

AbstractSubduction‐induced metasomatism may increase heterogeneity in the subcontinental lithospheric mantle (SCLM) over time. Syenite and its relevant varieties are typically derived from the most metasomatized portions of the SCLM and thus provide a key to decipher its heterogeneity. The only circum‐cratonic syenite province in the world, the Late Triassic belt around North China craton, is unique and offers an opportunity to investigate heterogeneity of the SCLM right before its destruction in the Mesozoic. New and previous data of whole‐rock Sr‐Nd and zircon in situ Hf‐O isotopes of syenite intrusions encircling the craton indicate two distinct types of metasomatism characterized by an alteration of juvenile or ancient materials. The spatiotemporally distinct sources can be discriminated by melts from oceanic slabs subducting beneath much of North China followed by deep subduction of South China craton only in the south. This unique setting of a circum‐cratonic syenite belt proves in a single case study that subduction‐induced metasomatism may cause craton‐scale SCLM heterogeneity.
Network-level mechanisms underlying effects of transcranial direct current stimulation (tDCS) on visuomotor learning in schizophrenia
Authors: Sehatpour Pejman , Kreither Johanna , Lopez-Calderon Javier , Shastry Adithya M. , De Baun Heloise M. , Martinez Antigona , Javitt Daniel C. 
Published: November 2023

AbstractMotor learning is a fundamental skill to our daily lives. Dysfunction in motor performance in schizophrenia (Sz) has been associated with poor social and functional outcomes. Transcranial direct current stimulation (tDCS), a non-invasive electrical brain stimulation approach, can influence underlying brain function with potential for improving motor learning in Sz. We used a well-established Serial Reaction Time Task (SRTT) to study motor learning, in combination with simultaneous tDCS and EEG recording, to investigate mechanisms of motor and procedural learning deficits in Sz, and to develop refined non-invasive brain stimulation approaches to improve neurocognitive dysfunction. We recruited 27 individuals with Sz and 21 healthy controls (HC). Individuals performed the SRTT task as they received sham and active tDCS with simultaneous EEG recording. Reaction time (RT), neuropsychological, and measures of global functioning were assessed. SRTT performance was significantly impaired in Sz and showed significant correlations with motor-related and working memory measures as well as global function. Source-space time-frequency decomposition of EEG showed beta-band coherence across supplementary-motor, primary-motor and visual cortex forming a network involved in SRTT performance. Motor-cathodal and visual-cathodal stimulations resulted in significant modulation in coherence particularly across the motor-visual nodes of the network accompanied by significant improvement in motor learning in both controls and patients. Here, we confirm earlier reports of SRTT impairment in Sz and demonstrate significant reversal of the deficits with tDCS. The findings support continued development of tDCS for enhancement of plasticity-based interventions in Sz, as well as source-space EEG analytic approaches for evaluating underlying neural mechanisms.