bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comprehensive review of arsenic contamination in India with an emphasis on its detection through biosensors and bioremediation from the aqueous system
Authors: Maity Sourav , Bose Samprit , Dokania Puja , Lohar Sadhana , Sarkar Angana 
Published: September 2023

AbstractIn India, where millions of people use groundwater for drinking, arsenic pollution in groundwater is a major environmental and public health issue. The review begins by analyzing the sources and causes of groundwater arsenic pollution, including natural geological processes and anthropogenic activities like mining and industrial discharge. It emphasizes India's most arsenic‐contaminated regions and the health risks of long‐term exposure. The review's second section focuses on the use of biosensors to find arsenic in groundwater. A potential method is provided by biosensors because of their great sensitivity, selectivity, and quick response. The benefits and drawbacks of several types of biosensors, including optical, electrochemical, and microbiological biosensors, are discussed. The utilization of nanomaterials, biomolecular recognition components, and miniature devices are only a few of the most recent developments in biosensor technology for arsenic detection that are studied. The review's last section discusses methods for bio‐remediating aqueous systems that have been contaminated with arsenic. Various bioremediation techniques are covered in detail, including microbial degradation, phytoremediation, and biosorption. The promise for removing arsenic using native microbes and plant species is highlighted, along with the difficulties of widespread application and long‐term sustainability. Overall, focusing on the detection of arsenic using biosensors and investigating bioremediation techniques, this review offers a thorough grasp of the arsenic poisoning in groundwater in India. In order to combat arsenic contamination and protect the health and wellbeing of the impacted populations in India, it emphasizes the need for interdisciplinary research and collaboration among scientists, engineers, policymakers, and local communities.
Impact of turbulence and blade surface degradation on the annual energy production of small‐scale wind turbines
Authors: Zarketa‐Astigarraga Ander , Penalba Markel , Martin‐Mayor Alain , Martinez‐Agirre Manex 
Published: September 2023

AbstractSmall‐scale horizontal axis wind‐turbines (SHAWTs) are acquiring relevance within the regulatory policies of the wind sector aiming at net‐zero emissions, while reducing visual and environmental impact by means of distributed grids. SHAWTs operate transitionally, at Reynolds numbers that fall between
. Furthermore, environmental turbulence and roughness affect the energetic outcome of the turbines. In this study, the combined effect of turbulence and roughness is analysed via wind tunnel experiments upon a transitionally operating NACA0021 airfoil. The combined effects cause a negative synergy, inducing higher drops in lift and efficiency values than when considering the perturbing agents individually. Besides, such losses are Reynolds‐dependent, with higher numbers increasing the difference between clean and real configurations, reaching efficiency decrements above 60% in the worst‐case scenario.Thus, these experimental measurements are employed for obtaining the power curves and estimating the annual energy production (AEP) of a 7.8‐kW‐rated SHAWT design by means of a BEM code. The simulations show a worst‐case scenario in which the AEP reduces above 70% when compared to the baseline configuration, with such a loss getting attenuated when a pitch‐regulated control is assumed. These results highlight the relevance of performing tests that consider the joint effect of turbulence and roughness.
Constructing Sentiment Signal-Based Asset Allocation Method with Causality Information
Authors: Taguchi Rei , Sakaji Hiroki , Izumi Kiyoshi , Murayama Yuri 
Published: September 2023

AbstractThis study demonstrates whether financial text is useful for the tactical asset allocation method using stocks. This can be achieved using natural language processing to create polarity indexes in financial news. We perform clustering of the created polarity indexes using the change point detection algorithm. In addition, we construct a stock portfolio and rebalanced it at each change point using an optimization algorithm. Consequently, the proposed asset allocation method outperforms the comparative approach. This result suggests that the polarity index is useful for constructing the equity asset allocation method.
Temporal trends of case-fatality in patients undergoing dual-injection coronary chronic total occlusion recanalization
Authors: Blessing Recha , Keller Karsten , Dimitriadis Zisis , Münzel Thomas , Gori Tommaso , Hobohm Lukas 
Published: September 2023

Abstract
Aims
Recently, interventional techniques and material to treat chronic total occlusion (CTO) with percutaneous coronary intervention (PCI) have evolved significantly. Nevertheless, it is still unknown whether this progress improved treatment success and patients’ outcome. In a nationwide sample, we sought to analyze trends of patients’ characteristics, complications and in-hospital case-fatality of patients undergoing CTO revascularization in Germany.

Methods and Results
We analyzed data on characteristics, treatments, and in-hospital outcomes for all coronary artery disease (CAD) patients (ICD-code I25) undergoing dual-injection CTO recanalization (OPS procedural code: 8–839.9) in Germany from 2009 to 2020. Overall, 4,998,457 inpatients aged ≥ 18 years with diagnosis of CAD were treated in German hospitals in this period. Among these, 52,879 patients (1.1%) underwent CTO recanalization. Annual number of CTO PCIs increased from 1263 in 2009 to 6435 in 2020 (β 3.48 [95% CI 3.44–3.52]; p < 0.001) in parallel with a significant decrease of case-fatality (2.2% in 2009 to 1.4% in 2020; β  – 0.60 [95% CI  – 0.82 to  – 0.39]; p < 0.001). Overall, 754 (1.4%) patients with CTO recanalization died during the in-hospital stay and in-hospital case-fatality grew exponentially with age (β 0.82 [95% CI 0.73–0.90]; p < 0.001). Significant predictors of in-hospital case fatality with an OR > 3 were cancer, stroke, hemopericardium, acute renal failure, pulmonary embolism and shock.

Conclusion
Annual number of CTO procedures performed in Germany increased from 2009 to 2020 with a concomitant anti-proportional decrease in the case-fatality. Our findings may help to draw more attention to predictors of in-hospital case fatality in patients hospitalized for CTO recanalization.

Graphical abstract
The disappearance of gastric metastasis and liver metastasis in non-small cell lung adenocarcinoma is due to osimertinib
Authors: Wang Yun , Yan Chao , Zhang Chuantao , Yu Enhao , Wang Kai , Liu Xiangyong , Yu Jie , Zhou Chunyang , Yang Aijie 
Published: September 2023

Abstract
Purpose
Gastric metastasis of lung cancer is rare, and the cases of disappearance of gastric metastasis and liver metastasis caused by oxitinib treatment have not been reported.

Methods
A 47-year-old male patient with no history of diabetes, hypertension or smoking presented with chest discomfort after eating. At the time of consultation, the diagnosis of adenocarcinoma of the right lower lobe of the lung with liver and gastric metastasis was considered by pathological examination of biopsy of the fundus of the stomach near the cardia, pathological examination of CT-guided lung aspiration and pathological examination of liver occupancy aspiration, combined with immunohistochemical results. He was found to have exon 19 deletion in next generation sequencing. We performed osimertinib on him (EGFR–TKI) systemic therapy, followed by local radiation therapy to the right lower lung primary lesion.

Results
After systemic treatment with osimertinib and local radiotherapy of the primary site, the metastases disappeared and the primary site showed post-radiotherapy changes, and the evaluated efficacy was complete remission.

Conclusions
This is the first report to our knowledge of a patient who presented with gastric and hepatic metastases from lung cancer and achieved complete remission with osimertinib and local radiotherapy, with good quality of life, which also provides a basis for future clinical work and is of great significance.
Types of mathematical tasks in lower secondary classrooms in Germany
Authors: Adleff Ann-Kristin , Ross Natalie , König Johannes , Kaiser Gabriele 
Published: September 2023

AbstractTasks play an important role in mathematics education, as they provide opportunities for students to develop their competencies and to cognitively engage with the mathematical content. The potential for cognitive activation as a central feature of a mathematical task has been considered in numerous studies, mostly as a didactical analysis by means of existing classification systems. In this study, which has been carried out in the frame of the TEDS research program, a different approach is taken by which we aim to identify the cognitive demand level of tasks used in ordinary mathematics lessons. Thus, the correlation between general mathematical competencies and the cognitive mathematical activities required to solve the task was analyzed and common properties of groupings of tasks were empirically extracted. In detail, 2490 tasks from mathematics lessons in Germany were analyzed by means of a rational task analysis with regard to their potential for fostering general mathematical competencies, namely modelling, problem solving, reasoning and argumentation, use of representations, use of symbols and operations, and communication. Latent class analysis revealed six classes of mathematical tasks with varying potential for the different competencies. In accordance with previous studies on mathematical tasks in Germany, the biggest class focused solely on the use of symbols and operations, while other classes showed different foci. Post hoc analyses revealed that the classes of tasks differ with regard to the level of cognitive activity they require. The results of the study highlight that the potential for cognitive activation of the tasks used in the classrooms of this more recent study has not improved in the last decades, despite many reform activities in German mathematics education, and that many mathematical tasks used are still more or less calculation oriented.
Reactivity in chemistry: the propensity view
Authors: Suárez Mauricio , Sánchez Gómez Pedro J. 
Published: September 2023

AbstractWe argue for an account of chemical reactivities as chancy propensities, in accordance with the ‘complex nexus of chance’ defended by one of us in the past. Reactivities are typically quantified as proportions, and an expression such as “A + B → C” does not entail that under the right conditions some given amounts of A and B react to give the mass of C that theoretically corresponds to the stoichiometry of the reaction. Instead, what is produced is a fraction α < 1 of this theoretical amount, and the corresponding percentage is usually known as the yield, which expresses the relative preponderance of its reaction. This is then routinely tested in a laboratory against the observed actual yields for the different reactions. Thus, on our account, reactivities ambiguously refer to three quantities at once. They first refer to the underlying propensities effectively acting in the reaction mechanisms, which in ‘chemical chemistry’ (Schummer in Hyle 4:129–162, 1998) are commonly represented by means of Lewis structures. Besides, reactivities represent the probabilities that these propensities give rise to, for any amount of the reactants to combine as prescribed. This last notion is hence best understood as a single case chance and corresponds to a theoretical stoichiometric yield. Finally, reactivities represent the actual yields observed in experimental runs, which account for and provide the requisite evidence for/against both the mechanisms and single case chances ascribed.
Wideband ultrathin and polarization insensitive metamaterial absorber for Ku-band applications
Authors: Saadeldin A. Samy , Sayed Amr M. , Amr Adnan M. , Sayed Menna O. , Hameed Mohamed Farhat O. , Obayya S. S. A. 
Published: September 2023

AbstractIn this paper, wideband, and ultrathin metamaterial absorber is proposed, analyzed and fabricated for Ku-band applications. The reported absorber has a nearly perfect absorptivity above 90% covering the entire Ku band (12–20 GHz) at normal incidence for both transverse electric and transverse magnetic polarization. This is due to the supported electric and magnetic resonances simultaneously. Consequently, the effective permittivity and permeability can be designed to obtain impedance matching with free space. This leads to the absorption of the entire incident energy in the metamaterial absorber. The suggested structure also shows a good absorption response (above 80%) under oblique incidence (from 0 to 50°). Therefore, the proposed absorber represents a good potential for Ku-band applications.
Improving case duration accuracy of orthopedic surgery using bidirectional encoder representations from Transformers (BERT) on Radiology Reports
Authors: Zhong William , Yao Phil Y. , Boppana Sri Harsha , Pacheco Fernanda V. , Alexander Brenton S. , Simpson Sierra , Gabriel Rodney A. 
Published: September 2023

Abstract
Purpose
A major source of inefficiency in the operating room is the mismatch between scheduled versus actual surgical time. The purpose of this study was to demonstrate a proof-of-concept study for predicting case duration by applying natural language processing (NLP) and machine learning that interpret radiology reports for patients undergoing radius fracture repair.

Methods
Logistic regression, random forest, and feedforward neural networks were tested without NLP and with bag-of-words. Another NLP method tested used feedforward neural networks and Bidirectional Encoder Representations from Transformers specifically pre-trained on clinical notes (ClinicalBERT). A total of 201 cases were included. The data were split into 70% training and 30% test sets. The average root mean squared error (RMSE) were calculated (and 95% confidence interval [CI]) from 10-fold cross-validation on the training set. The models were then tested on the test set to determine proportion of times surgical cases would have scheduled accurately if ClinicalBERT was implemented versus historic averages.

Results
The average RMSE was lowest using feedforward neural networks using outputs from ClinicalBERT (25.6 min, 95% CI: 21.5–29.7), which was significantly (P < 0.001) lower than the baseline model (39.3 min, 95% CI: 30.9–47.7). Using the feedforward neural network and ClinicalBERT on the test set, the percentage of accurately predicted cases, which was defined by the actual surgical duration within 15% of the predicted surgical duration, increased from 26.8 to 58.9% (P < 0.001).

Conclusion
This proof-of-concept study demonstrated the successful application of NLP and machine leaning to extract features from unstructured clinical data resulting in improved prediction accuracy for surgical case duration.
La Voz De La Hechicera: De La Narración Oral Al Registro Judicial
Authors: Gala Pellicer Susana 
Published: September 2023

AbstractHalfway between orality and writing, the statement of the women accused by the Inquisition of practicing sorcery raises interpretive difficulties that are hard to resolve. The analysis of the confession made by Vicenta Graçia Almenar before the Inquisition of Valencia (1623) will allow us to detect some of the factors that mediate between the discourse of the woman and the text produced by the Inquisition: aspects such as the transcription process (for example, the presence of errors and spelling slips introduced by the notary), the context of emission (which determines the use of a characteristic formulaic language) or the discursive typology (the narration of experiences and magical practices), among others, will shed new light on the construction of the defendant’s speech and on its transformation into a judicial text.
Pre-electoral coalitions and the distribution of political power
Authors: Hortala-Vallve Rafael , Meriläinen Jaakko , Tukiainen Janne 
Published: September 2023

AbstractPre-electoral coalitions (PECs) may increase parties’ chances of winning an election, but they may also distort electoral results and policies away from citizens’ preferences. To shed light on how PECs shape post-electoral power distribution, we study the causes and consequences of PECs in Finland where elections use an open-list proportional representation system, and parties may form joint lists. We present descriptive evidence showing that PECs are more common between parties of equal size and similar ideology, and when elections are more disproportional or involve more parties. Using difference-in-differences and density discontinuity designs, we illustrate that voters punish coalescing parties and target personal votes strategically within the coalitions, and that PECs are formed with the particular purpose of influencing the distribution of power. PECs increase small parties’ chances of acquiring leadership positions, lead to more dispersed seat distributions, and sometimes prevent absolute majorities. They can thus enable a broader representation of citizens’ policy preferences.
Patient adherence to patient-reported outcome measure (PROM) completion in clinical care: current understanding and future recommendations
Authors: Unni Elizabeth , Coles Theresa , Lavallee Danielle C. , Freel Jennifer , Roberts Natasha , Absolom Kate 
Published: September 2023

Abstract
Background
Patient-reported outcome measures (PROMs) are increasingly being used as an assessment and monitoring tool in clinical practice. However, patient adherence to PROMs completions are typically not well documented or explained in published studies and reports. Through a collaboration between the International Society for Quality-of-Life Research (ISOQOL) Patient Engagement and QOL in Clinical Practice Special Interest Groups (SIGs) case studies were collated as a platform to explore how adherence can be evaluated and understood. Case studies were drawn from across a range of clinically and methodologically diverse PROMs activities.

Results
The case studies identified that the influences on PROMs adherence vary. Key drivers include PROMs administeration methods within a service and wider system, patient capacity to engage and clinician engagement with PROMs information. It was identified that it is important to evaluate PROMs integration and adherence from multiple perspectives.

Conclusion
PROM completion rates are an important indicator of patient adherence. Future research prioritizing an understanding of PROMs completion rates by patients is needed.
Eliciting a value set for the Swedish Capability-Adjusted Life Years instrument (CALY-SWE)
Authors: Meili Kaspar Walter , Mulhern Brendan , Ssegonja Richard , Norström Fredrik , Feldman Inna , Månsdotter Anna , Hjelte Jan , Lindholm Lars 
Published: September 2023

AbstractPurposeOur aim was to elicit a value set for Capability-Adjusted Life Years Sweden (CALY-SWE); a capability-grounded quality of life instrument intended for use in economic evaluations of social interventions with broad consequences beyond health.MethodsBuilding on methods commonly used in the quality-adjusted life years EQ-5D context, we collected time-trade off (TTO) and discrete choice experiment (DCE) data through an online survey from a general population sample of 1697 Swedish participants. We assessed data quality using a score based on the severity of inconsistencies. For generating the value set, we compared different model features, including hybrid modeling of DCE and TTO versus TTO data only, censoring of TTO answers, varying intercept, and accommodating for heteroskedasticity. We also assessed the models’ DCE logit fidelity to measure agreement with potentially less-biased DCE data. To anchor the best capability state to 1 on the 0 to 1 scale, we included a multiplicative scaling factor.ResultsWe excluded 20% of the TTO answers of participants with the largest inconsistencies to improve data quality. A hybrid model with an anchor scale and censoring was chosen to generate the value set; models with heteroskedasticity considerations or individually varying intercepts did not offer substantial improvement. The lowest capability weight was 0.114. Health, social relations, and finance and housing attributes contributed the largest capability gains, followed by occupation, security, and political and civil rights.ConclusionWe elicited a value set for CALY-SWE for use in economic evaluations of interventions with broad social consequences.
Analyst ability and research effort: non-EPS forecast provision as a research quality signal
Authors: Pope Peter F. , Wang Tong 
Published: September 2023

AbstractThe range of non-EPS forecast types provided by individual analysts to I/B/E/S has increased dramatically over time but varies considerably across firms. We propose that in providing a broader range of forecast types, analysts can signal superior research ability and research effort. Consistent with this hypothesis, we document positive associations between the number of forecast types (NFT) an analyst provides and common proxies for research quality, including earnings forecast accuracy, price target accuracy, stock recommendation profitability, market reactions to stock recommendation revisions, and analyst career outcomes. The effects of NFT are incremental to other quality proxies used in the literature and are distinct from the issuance of specific non-EPS forecast types studied previously (e.g., cash flow forecasts). We demonstrate the information value of NFT to investors by examining the out-of-sample performance of portfolios formed conditional on NFT and exploiting revisions in consensus earnings forecasts and individual analysts’ stock recommendations. We conclude that the number of forecast types an analyst provides for a firm is a readily available proxy for the quality of her research.
Parsimonious mixtures for the analysis of tensor-variate data
Authors: Tomarchio Salvatore D. , Punzo Antonio , Bagnato Luca 
Published: September 2023

AbstractReal data is taking on more and more complex structures, raising the necessity for more flexible and parsimonious statistical methodologies. Tensor-variate (or multi-way) structures are a typical example of such kind of data. Unfortunately, real data often present atypical observations that make the traditional normality assumption inadequate. Thus, in this paper, we first introduce two new tensor-variate distributions, both heavy-tailed generalizations of the tensor-variate normal distribution. Then, we use these distributions for model-based clustering via finite mixture models. To introduce parsimony in the models, we use the eigen-decomposition of the components’ scale matrices, obtaining two families of parsimonious tensor-variate mixture models. As a by-product, we also introduce the parsimonious version of tensor-variate normal mixtures. As for parameter estimation, we illustrate variants of the well-known EM algorithm. Since the number of parsimonious models depends on the order of the tensors, we implement strategies intending to shorten the initialization and fitting processes. These procedures are investigated via simulated analyses. Finally, we fitted our parsimonious models to two real datasets having a 4-way and a 5-way structure, respectively.