bluuebunny/crossref_metadata_2025 huggingface dataset:
Unraveling the complexities of a highly heterogeneous aquifer under convergent radial flow conditions
Authors: Brunetti Guglielmo Federico Antonio , Maiolo Mario , Fallico Carmine , Severino Gerardo
Published: April 2024

Untangling flow and mass transport in aquifers is essential for effective water management and protection. However, understanding the mechanisms underlying such phenomena is challenging, particularly in highly heterogeneous natural aquifers. Past research has been limited by the lack of dense data series and experimental models that provide precise knowledge of such aquifer characteristics. To bridge this gap and advance our current understanding, we present the findings of a pioneering experimental investigation that characterizes a unique, strongly heterogeneous, laboratory-constructed phreatic aquifer at an intermediate scale under radial flow conditions. This strong heterogeneity was achieved by randomly distributing 2527 cells across 7 layers, each filled with one of 12 different soil mixtures, with their textural characteristics, porosity, and saturated hydraulic conductivity measured in the laboratory. We placed 37 fully penetrating piezometers radially at varying distances from the central pumping well, allowing for an extensive pumping test campaign to obtain saturated hydraulic conductivity values for each piezometer location and scaling laws along eight directions. Results reveal that the aquifer’s strong heterogeneity led to significant vertical and directional anisotropy in saturated hydraulic conductivity. Furthermore, we experimentally demonstrated for the first time that the porous medium tends toward homogeneity when transitioning from the scale of heterogeneity to the scale of investigation. These novel findings, obtained on a uniquely highly heterogeneous aquifer, contribute to the field and provide valuable insights for researchers studying flow and mass transport phenomena. The comprehensive dataset obtained will serve as a foundation for future research and as a tool to validate findings from previous studies on strongly heterogeneous aquifers.
Aktuelle Zahlen zur rheumatologischen Versorgung – Jahresbericht aus der Kerndokumentation der regionalen kooperativen Rheumazentren
Authors: Albrecht Katinka , Thiele Katja , Alexander Tobias , Aringer Martin , Eidner Thorsten , Henes Jörg , Hoese Guido , Karberg Kirsten , Kiltz Uta , Krause Andreas , Ochs Wolfgang , Richter Jutta G , Späthling-Mestekemper Susanna , Steinmüller Mirko , Wassenberg Siegfried , Strangfeld Anja , Callhoff Johanna
Published: April 2024

Die Kerndokumentation der regionalen kooperativen Rheumazentren erfasst seit 1993 jährlich Daten zur rheumatologischen Versorgung von Patient:innen mit entzündlich-rheumatischen Erkrankungen. In diesem erstmals erscheinenden Jahresbericht werden aktuelle Querschnittsdaten zur Medikation und zu patientenberichteten Outcomes vorgestellt, die im Jahr 2022 erhoben wurden.
ChatGPT vs. neurologists: a cross-sectional study investigating preference, satisfaction ratings and perceived empathy in responses among people living with multiple sclerosis
Authors: Maida Elisabetta , Moccia Marcello , Palladino Raffaele , Borriello Giovanna , Affinito Giuseppina , Clerico Marinella , Repice Anna Maria , Di Sapio Alessia , Iodice Rosa , Spiezia Antonio Luca , Sparaco Maddalena , Miele Giuseppina , Bile Floriana , Scandurra Cristiano , Ferraro Diana , Stromillo Maria Laura , Docimo Renato , De Martino Antonio , Mancinelli Luca , Abbadessa Gianmarco , Smolik Krzysztof , Lorusso Lorenzo , Leone Maurizio , Leveraro Elisa , Lauro Francesca , Trojsi Francesca , Streito Lidia Mislin , Gabriele Francesca , Marinelli Fabiana , Ianniello Antonio , De Santis Federica , Foschi Matteo , De Stefano Nicola , Morra Vincenzo Brescia , Bisecco Alvino , Coghe Giancarlo , Cocco Eleonora , Romoli Michele , Corea Francesco , Leocani Letizia , Frau Jessica , Sacco Simona , Inglese Matilde , Carotenuto Antonio , Lanzillo Roberta , Padovani Alessandro , Triassi Maria , Bonavita Simona , Lavorgna Luigi ,   Digital Technologies, Web, Social Media Study Group of the Italian Society of Neurology (SIN)
Published: April 2024

Background

ChatGPT is an open-source natural language processing software that replies to users’ queries. We conducted a cross-sectional study to assess people living with Multiple Sclerosis’ (PwMS) preferences, satisfaction, and empathy toward two alternate responses to four frequently-asked questions, one authored by a group of neurologists, the other by ChatGPT.

Methods

An online form was sent through digital communication platforms. PwMS were blind to the author of each response and were asked to express their preference for each alternate response to the four questions. The overall satisfaction was assessed using a Likert scale (1–5); the Consultation and Relational Empathy scale was employed to assess perceived empathy.

Results

We included 1133 PwMS (age, 45.26 ± 11.50 years; females, 68.49%). ChatGPT’s responses showed significantly higher empathy scores (Coeff = 1.38; 95% CI = 0.65, 2.11; p > z < 0.01), when compared with neurologists’ responses. No association was found between ChatGPT’ responses and mean satisfaction (Coeff = 0.03; 95% CI = − 0.01, 0.07; p = 0.157). College graduate, when compared with high school education responder, had significantly lower likelihood to prefer ChatGPT response (IRR = 0.87; 95% CI = 0.79, 0.95; p < 0.01).

Conclusions

ChatGPT-authored responses provided higher empathy than neurologists. Although AI holds potential, physicians should prepare to interact with increasingly digitized patients and guide them on responsible AI use. Future development should consider tailoring AIs’ responses to individual characteristics. Within the progressive digitalization of the population, ChatGPT could emerge as a helpful support in healthcare management rather than an alternative.
An algorithm-based technique for counting mitochondria in cells using immunohistochemical staining of formalin-fixed and paraffin-embedded sections
Authors: Sakashita Mai , Motoi Noriko , Yamamoto Gaku , Gambe Emi , Suzuki Masanori , Yoshida Yukihiro , Watanabe Shun-ichi , Takazawa Yutaka , Aoki Kazunori , Ochiai Atsushi , Sakashita Shingo
Published: April 2024

Purpose

Visualizing mitochondria in cancer cells from human pathological specimens may improve our understanding of cancer biology. However, using immunohistochemistry to evaluate mitochondria remains difficult because almost all cells contain mitochondria and the number of mitochondria per cell may have important effects on mitochondrial function. Herein, we established an objective system (Mito-score) for evaluating mitochondria using machine-based processing of hue, saturation, and value color spaces.

Methods

The Mito-score was defined as the number of COX4 (mitochondrial inner membrane) immunohistochemistry-positive pixels divided by the number of nuclei per cell. The system was validated using four lung cancer cell lines, normal tissues, and lung cancer tissues (199 cases).

Results

The Mito-score correlated with MitoTracker, a fluorescent dye used to selectively label and visualize mitochondria within cells under a microscope (R2 = 0.68) and with the number of mitochondria counted using electron microscopy (R2 = 0.79). Histologically, the Mito-score of small cell carcinoma (57.25) was significantly lower than that of adenocarcinoma (147.5, p < 0.0001), squamous cell carcinoma (120.6, p = 0.0004), and large cell neuroendocrine carcinoma (111.8, p = 0.002).

Conclusion

The Mito-score method enables the analysis of the mitochondrial status of human formalin-fixed paraffin-embedded specimens and may provide insights into the metabolic status of cancer.
Prognostic impact of metabolic syndrome in patients with primary endometrial cancer: a retrospective bicentric study
Authors: Shehaj Ina , Krajnak Slavomir , Rad Morva Tahmasbi , Gasimli Bahar , Hasenburg Annette , Karn Thomas , Schmidt Marcus , Müller Volker , Becker Sven , Gasimli Khayal
Published: April 2024

Purpose

Endometrial cancer (EC) is the most common gynaecological cancer. Its incidence has been rising over the years with ageing and increased obesity of the high-income countries’ populations. Metabolic syndrome (MetS) has been suggested to be associated with EC. The aim of this study was to assess whether MetS has a significant impact on oncological outcome in patients with EC.

Methods

This retrospective study included patients treated for EC between January 2010 and December 2020 in two referral oncological centers. Obesity, arterial hypertension (AH) and diabetes mellitus (DM) were criteria for the definition of MetS. The impact of MetS on progression free survival (PFS) and overall survival (OS) was assessed with log-rank test and Cox regression analyses.

Results

Among the 415 patients with a median age of 64, 38 (9.2%) fulfilled the criteria for MetS. The median follow-up time was 43 months.

Patients suffering from MetS did not show any significant differences regarding PFS (36.0 vs. 40.0 months, HR: 1.49, 95% CI 0.79–2.80 P = 0.210) and OS (38.0 vs. 43.0 months, HR: 1.66, 95% CI 0.97–2.87, P = 0.063) compared to patients without MetS. Patients with obesity alone had a significantly shorter median PFS compared to patients without obesity (34.5 vs. 44.0 months, P = 0.029). AH and DM separately had no significant impact on PFS or OS (p > 0.05).

Conclusion

In our analysis, MetS in patients with EC was not associated with impaired oncological outcome. However, our findings show that obesity itself is an important comorbidity associated with significantly reduced PFS.
Niche partitioning and individual specialisation in resources and space use of sympatric fur seals at their range margin
Authors: Salton Marcus , Raoult Vincent , Jonsen Ian , Harcourt Robert
Published: April 2024

Ecological theory predicts niche partitioning between high-level predators living in sympatry as a mechanism to minimise the selective pressure of competition. Accordingly, male Australian fur seals Arctocephalus pusillus doriferus and New Zealand fur seals A. forsteri that live in sympatry should exhibit partitioning in their broad niches (in habitat and trophic dimensions) in order to coexist. However, at the northern end of their distributions in Australia, both are recolonising their historic range after a long absence due to over-exploitation, and their small population sizes suggest competition should be weak and may allow overlap in niche space. We found some niche overlap, yet clear partitioning in diet trophic level (δ15N values from vibrissae), spatial niche space (horizontal and vertical telemetry data) and circadian activity patterns (timing of dives) between males of each species, suggesting competition may remain an active driver of niche partitioning amongst individuals even in small, peripheral populations. Consistent with individual specialisation theory, broad niches of populations were associated with high levels of individual specialisation for both species, despite putative low competition. Specialists in isotopic space were not necessarily specialists in spatial niche space, further emphasising their diverse individual strategies for niche partitioning. Males of each species displayed distinct foraging modes, with Australian fur seals primarily benthic and New Zealand fur seals primarily epipelagic, though unexpectedly high individual specialisation for New Zealand fur seals might suggest marginal populations provide exceptions to the pattern generally observed amongst other fur seals.
The Impacts of Dimensionality, Diffusion, and Directedness on Intrinsic Cross-Model Simulation in Tile-Based Self-Assembly
Authors: Hader Daniel , Patitz Matthew J.
Published: April 2024

Motivated by applications in DNA-nanotechnology, theoretical investigations in algorithmic tile-assembly have blossomed into a mature theory. In addition to computational universality, the abstract Tile Assembly Model (aTAM) was shown to be intrinsically universal (FOCS 2012), a strong notion of completeness where a single tile set is capable of simulating the full dynamics of all systems within the model; however, this construction fundamentally required non-deterministic tile attachments. This was confirmed necessary when it was shown that the class of directed aTAM systems, those where all possible sequences of tile attachments result in the same terminal assembly, is not intrinsically universal (FOCS 2016). Furthermore, it was shown that the non-cooperative aTAM, where tiles only need to match on 1 side to bind rather than 2 or more, is not intrinsically universal (SODA 2014) nor computationally universal (STOC 2017). Building on these results to further investigate the other dynamics, Hader et al. examined several tile-assembly models which varied across (1) the numbers of dimensions used, (2) how tiles diffused through space, and (3) whether each system is directed, and determined which models exhibited intrinsic universality (SODA 2020). In this paper we extend those results to provide direct comparisons of the various models against each other by considering intrinsic simulations between models. Our results show that in some cases, one model is strictly more powerful than another, and in others, pairs of models have mutually exclusive capabilities. This paper is a greatly expanded version of that which appeared in ICALP 2023.
Venous thromboembolism chemical prophylaxis after skull base surgery
Authors: Waqar Mueez , Yaseen Omar , Chadwick Annabel , Lee Jing Xian , Khan Ghazn , Evans D. Gareth , Horner Daniel , Jaiswal Archana , Freeman Simon , Bhalla Rajiv , Lloyd Simon , Hammerbeck-Ward Charlotte , Rutherford Scott A. , King Andrew T. , Pathmanaban Omar N.
Published: April 2024

Purpose

There is no guidance surrounding postoperative venous thromboembolism (VTE) prophylaxis using pharmacological agents (chemoprophylaxis) in patients undergoing skull base surgery. The aim of this study was to compare VTE and intracranial haematoma rates after skull base surgery in patients treated with/without chemoprophylaxis.

Methods

Review of prospective quaternary centre database including adults undergoing first-time skull base surgery (2009–2020). VTE was defined as deep vein thrombosis (DVT) and pulmonary embolism (PE) within 6 months of surgery. Multivariate logistic regression was used to determine factors predictive of postoperative intracranial haematoma/VTE. Propensity score matching (PSM) was used in group comparisons.

Results

One thousand five hundred fifty-one patients were included with a median age of 52 years (range 16–89 years) and female predominance (62%). Postoperative chemoprophylaxis was used in 81% of patients at a median of 1 day postoperatively. There were 12 VTE events (1.2%), and the use of chemoprophylaxis did not negate the risk of VTE entirely (p > 0.99) and was highest on/after postoperative day 6 (9/12 VTE events). There were 18 intracranial haematomas (0.8%), and after PSM, chemoprophylaxis did not significantly increase the risk of an intracranial haematoma (p > 0.99). Patients administered chemoprophylaxis from postoperative days 1 and 2 had similar rates of intracranial haematomas (p = 0.60) and VTE (p = 0.60), affirmed in PSM.

Conclusion

Postoperative chemoprophylaxis represents a relatively safe strategy in patients undergoing skull base surgery. We advocate a personalised approach to chemoprophylaxis and recommend it on postoperative days 1 or 2 when indicated.
Development of a workflow to build optimal machine learning models for stress concentration factor regression
Authors: Tunsch Paul , Becker Nils , Schlecht Berthold
Published: April 2024

In the design of shafts for drivetrains, it is important to have precise knowledge of the effective stress in critical notches. In nominal stress approaches, stress concentration factors are used to estimate the stress in the notch based on geometric properties of the shaft. They can be calculated using numerical methods like finite element method, which can be time consuming. Analytical equations have been developed for simple geometries, like shaft shoulders and round grooves, they are less accurate but much faster than numerical solutions. In this paper, machine learning is used to combine the advantages of both solutions. A process chain to develop models for the calculation of stress concentration factors is presented. It consists of methods to process data, creation and training of regression models and evaluation of the results. This toolbox allows different regression models to be used for different tasks without the need for major changes to the source code. The process is illustrated for shaft shoulders under tension and compression, bending and torsion. The resulting model is capable of calculating stress concentration factors with better accuracy than common analytical approaches while having comparable computation time.
Global burden of young-onset gastric cancer: a systematic trend analysis of the global burden of disease study 2019
Authors: Li Yunhao , Hahn Anne I. , Laszkowska Monika , Jiang Fang , Zauber Ann G. , Leung Wai K.
Published: April 2024

Background

While gastric cancer is generally declining globally, the temporal trend of young-onset (< 40 years) gastric cancer remains uncertain. We performed this analysis to determine the temporal trends of young-onset gastric cancer compared to late-onset cancer (≥ 40 years).

Methods

We extracted cross-sectional data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. The burden of gastric cancer from 1990 to 2019 was assessed through indicators including incidence and mortality rates, which were classified at global, national, and regional levels, and according to socio-demographic indexes (SDI) and age or sex groups. Joinpoint regression analysis was used to identify specific years with significant changes. The correlation between AAPC with countries' average SDI was tested by Pearson’s Test.

Results

The global incidence rate of young-onset gastric cancer decreased from 2.20 (per 100,000) in 1990 to 1.65 in 2019 (AAPC: − 0.95; 95% confidence interval [CI] − 1.25 to − 0.65; P < 0.001). Late-onset cancer incidence also decreased from 59.53 (per 100,000) in 1990 to 41.26 in 2019 (AAPC: − 1.23; 95% CI − 1.39 to − 1.06, P < 0.001). Despite an overall decreasing trend, the incidence rate of young-onset cancer demonstrated a significant increase from 2015 to 2019 (annual percentage change [APC]: 1.39; 95% CI 0.06 to 2.74; P = 0.041), whereas no upward trend was observed in late-onset cancer. Mortality rates of young- and late-onset cancer both exhibited a significant decline during this period (AAPC: − 1.82; 95% CI − 2.15 to − 1.56; P < 0.001 and AAPC: − 1.69, 95% CI − 1.79 to − 1.59; P < 0.001). The male-to-female rate ratio for incidence and mortality in both age groups have been increasing since 1990. While countries with high SDI have had a greater decline in the incidence of late-onset gastric cancer (slope of AAPC change: − 0.20, P = 0.004), it was not observed in young-onset cancer (slope of AAPC change: − 0.11, P = 0.13).

Conclusions

The global incidence and mortality rates of both young- and late-onset gastric cancer have decreased since 1990. However, the incidence rate of young-onset cancer has demonstrated a small but significant upward trend since 2015. There was disparity in the decline in young-onset gastric cancer among male and high SDI countries. These findings could help to inform future strategies in preventing gastric cancer in younger individuals.
Japanese Classification of Esophageal Cancer, 12th Edition: Part I
Authors: Mine Shinji , Tanaka Koji , Kawachi Hiroshi , Shirakawa Yasuhiro , Kitagawa Yuko , Toh Yasushi , Yasuda Takushi , Watanabe Masayuki , Kamei Takashi , Oyama Tsuneo , Seto Yasuyuki , Murakami Kentaro , Arai Tomio , Muto Manabu , Doki Yuichiro
Published: April 2024

This is the first half of English edition of Japanese Classification of Esophageal Cancer, 12th Edition that was published by the Japan Esophageal Society in 2022.
Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective
Authors: Mehdiyev Nijat , Majlatow Maxim , Fettke Peter
Published: April 2024

In the rapidly evolving landscape of manufacturing, the ability to make accurate predictions is crucial for optimizing processes. This study introduces a novel framework that combines predictive uncertainty with explanatory mechanisms to enhance decision-making in complex systems. The approach leverages Quantile Regression Forests for reliable predictive process monitoring and incorporates Shapley Additive Explanations (SHAP) to identify the drivers of predictive uncertainty. This dual-faceted strategy serves as a valuable tool for domain experts engaged in process planning activities. Supported by a real-world case study involving a medium-sized German manufacturing firm, the article validates the model’s effectiveness through rigorous evaluations, including sensitivity analyses and tests for statistical significance. By seamlessly integrating uncertainty quantification with explainable artificial intelligence, this research makes a novel contribution to the evolving discourse on intelligent decision-making in complex systems.
BRCA1/2 mutation carriers vs the general breast cancer population (N = 799,986): 21-gene assay-based molecular characterization
Authors: Yerushalmi Rinat , Pomerantz Adi , Lewin Ron , Paluch-Shimon Shani , Soussan-Gutman Lior , Baehner Frederick L. , Voet Hillary , Bareket-Samish Avital , Kedar Inbal , Goldberg Yael , Peretz-Yablonski Tamar , Kadouri Luna
Published: April 2024

Purpose

We compared 21-gene recurrence score (RS) distribution and expression of the single-gene/gene groups within this assay between BC patients with pathogenic variants (PV) in BRCA1/2 vs the general 21-gene-tested BC population.

Methods

This retrospective study included consecutive 21-gene-tested female ER + HER2-negative BC patients with germline PVs in BRCA1/2. RS/gene expression data were compared to a previously described commercial use database (CDB, N = 799,986). Chi-square and 1-sample t test were used to compare RS distribution and single-gene/gene group scores between the study group and the CDB.

Results

Study group patients (N = 81) were younger and their RS results were higher compared to the CDB (age: median [IQR], 56 [47–61.5] vs 60 [51–67] years; p < 0.001; proportion of patients with RS ≥ 26: 49.4% vs 16.4%, p < 0.001). Expression of 12/16 cancer genes in the assay and the ER, proliferation, and invasion gene group scores differed significantly between the study group and the CDB, all in a direction contributing to higher RS. The differences between the study group and the CDB were mostly retained, upon stratifying the patients by menopausal status.

Conclusion

BC patients with PVs in BRCA1/2 have higher RS results that stem from distinct gene expression profiles in the majority of genes in the 21-gene assay.
Preparing Colombian coffee production for climate change: Integrated spatial modelling to identify potential robusta coffee (Coffea canephora P.) growing areas
Authors: González-Orozco Carlos E. , Porcel Mario , Byrareddy Vivekananda Mittahalli , Rahn Eric , Cardona William A. , Velandia Diego A. Salinas , Araujo-Carrillo Gustavo A. , Kath Jarrod
Published: April 2024

Meeting future demand for coffee under climate change is a challenge. Approaches that can inform where coffee may grow best under current and future climate scenarios are needed. Robusta coffee (Coffea canephora P.) is planted in many tropical areas and makes up around 40% of the world’s coffee supply. However, as the climate shifts, current robusta areas may become less productive, while in other areas new growing regions for robusta may emerge. Colombia is one of the world’s most important Arabica coffee producer, famous for its high-quality coffee. Although robusta coffee is not yet a commercial crop in Colombia, it could be one of the future bastions for robusta coffee in South America contributing to meeting the increasing demand, but this remains unexplored. We aimed to identify areas with highest biophysical and socio-economic potential to grow robusta coffee in Colombia. An integrated modelling approach was used, combining climate suitability and crop-yield modelling for current and future climate scenarios, soil constraints, pest risk assessment and socio-economic constraints to identify the regions with the highest potential productivity and the lowest pest and climate change risks with good market access and low security risks which don’t further expand the agricultural frontier. Our results showed that parts of the foothills along the eastern Andean Mountain ranges, the high plains of the Orinoquía region and the wet parts of the Caribbean region are the best candidates for the potential development of robusta coffee plantations in Colombia. The crop-yield model indicated highest yields of green coffee on the foothills of the eastern Andean Mountain range with an estimated average yield of 2.6 t ha−1 (under rain-fed conditions) which is projected to occur at elevations below 600 m avoiding interference with the traditional and established Arabica coffee regions in Colombia. Under a 2 °C global warming scenario climate change is projected to have the largest impacts on the Caribbean region. Therefore, larger scale irrigated production system could be an appropriate option in the Caribbean region, while diversified smallholder robusta coffee agroforestry systems are considered more favourable in the Orinoquía region.
Underestimations of the income-based ecological footprint inequality
Authors: Andretti Bernardo , Vieites Yan , Ramos Guilherme A. , Elmor Larissa , Andrade Eduardo B.
Published: April 2024

Previous research has demonstrated that the wealthy harm the environment to a much greater extent than those with lesser means. According to recent estimates, the wealthiest 1% of the world’s population emit 50% more CO2 than the bottom half of the income distribution. The reason for this inequality is clear: affluence boosts consumption, which in turn increases the ecological footprint. Although the phenomenon seems intuitive, little is known as to whether the layperson notices it. The current study assesses the extent to which individuals recognize or fail to notice such massive ecological footprint inequality and why misperceptions may arise. Across four preregistered studies (N = 1,188) conducted in a highly unequal socio-economic environment (Brazil), we show that people often fail to accurately perceive the meaningful ecological footprint inequality that surrounds them. These misperceptions are explained by people’s (a) failure to properly incorporate the impact of income-based differences in consumption in their ecological footprint assessments and (b) tendency to associate wealth with superior environmental education, greater resources to act sustainably, and better local infrastructure (e.g., cleaner paved streets and proper waste collection). Emphasizing the lack of infrastructure in deprived neighborhoods further exacerbates the misperceptions, whereas highlighting key differences in consumption habits across the socio-economic spectrum increases accuracy. This research, thus, identifies the factors that magnify existing misperceptions in ecological footprint inequality and provides avenues for policymakers to reduce such mistakes.
Classification-driven intelligent system for automated evaluation of higher education exam paper quality
Authors: Ahmed Hosnia M. M. , Sorour Shaymaa E.
Published: April 2024

Evaluating the quality of university exam papers is crucial for universities seeking institutional and program accreditation. Currently, exam papers are assessed manually, a process that can be tedious, lengthy, and in some cases, inconsistent. This is often due to the focus on assessing only the formal specifications of exam papers. This study develops an intelligent system for the automatic evaluation of university exam papers in terms of form and content, ensuring adherence to quality standards. The system is composed of two subsystems: the first evaluates compliance with formal specifications, and the second analyzes the content. The content analysis involves automatically categorizing exam questions based on Bloom's cognitive levels (BCLs) and determining the representation ratio of these levels in the exam paper. This subsystem comprises four main modules: 1) question collection, 2) text pre-processing using natural language processing (NLP) methods, 3) feature engineering using the CountVectorizer method to convert questions into feature vectors, and 4) a classification module based on the Logistic Regression (LR) algorithm to categorize exam questions into categories like knowledge, comprehension, application, analysis, synthesis, and evaluation. Experimental results indicate that the system achieves an average accuracy of 98.5%.
Inner and Outer Versions of Hyper-Elasticity
Authors: Pedregal Pablo
Published: April 2024

Through suitable changes of variables for a typical problem in hyper-elasticity, either in the reference or deformed configurations, one can setup and analyze versions of the same problem in terms of inner or outer maps or variations. Though such kind of transformations are part of the classical background in the Calculus of Variations, we explore under what sets of hypotheses such versions can be shown to have minimizers and be equivalent to the standard form of the problem. Such sets of hypotheses lead naturally to some distinct poly-convex energy densities for hyper-elasticity. Likewise we explore optimality in either of the two forms through a special way to generate one-parameter families of feasible deformations, feasibility including injectivity and non-interpenetration of matter.
Mid-Surface Scaling Invariance of Some Bending Strain Measures
Authors: Acharya Amit
Published: April 2024

The mid-surface scaling invariance of bending strain measures proposed in (Int. J. Solids Struct. 37(39):5517–5528, 2000) is discussed in light of the work of (J. Elast. 146(1):83–141, 2021).
Selective unidirectional median crack propagation in glass achieved by mechanical scribing
Authors: Itoh Sho , Matsusaka Souta , Hidai Hirofumi , Murakami Kumiko , Kitaichi Mitsuru
Published: April 2024

This work reports a selective median crack propagation phenomenon in glass, leading to a novel glass cutting process. We found that by scribing a glass sample to the extent of plastic deformation with a deformation depth of 100–400 nm, followed by inducing an initial crack, a subsurface crack with a depth of ~ 10 μm was propagated backward along the centerline of the scribed region with a speed of 1 μm/s order. The crack depth and propagation speed were increased by increasing the scribing load. We conclude that the propagation direction was determined by the effect of the shear stress caused by a scribing tip sliding motion.
Mast Cells are Dependent on Glucose Transporter 1 (GLUT1) and GLUT3 for IgE-mediated Activation
Authors: Grujic Mirjana , Alim Md Abdul , Hellman Lars , Peterson Magnus , Pejler Gunnar
Published: April 2024

Mast cells (MCs) are known to have a pathological impact in a variety of settings, in particular in allergic conditions. There is also limited evidence implicating MCs in diabetes, raising the possibility that MC function may be influenced by alterations in glucose levels. However, it is not known whether MCs are directly affected by elevated glucose concentrations. Moreover, it is not known which glucose transporters that are expressed by MCs, and whether MCs are dependent on glucose transporters for activation. Here we addressed these issues. We show that MCs express high levels of both glucose transporter 1 (GLUT1/Slc2A1) and GLUT3 (Slc2A3). Further, we show that the inhibition of either GLUT1 or GLUT3 dampens both MC degranulation and cytokine induction in response to IgE receptor crosslinking, and that combined GLUT1 and GLUT3 inhibition causes an even more pronounced inhibition of these parameters. In contrast, the inhibition of GLUT1 or GLUT3, or combined GLUT1 and GLUT3 inhibition, had less impact on the ability of the MCs to respond to activation via compound 48/80. Elevated glucose concentrations did not affect MC viability, and had no stimulatory effect on MC responses to either IgE receptor crosslinking or compound 48/80. Altogether, these findings reveal that MCs are strongly dependent on glucose transport via GLUT1 and/or GLUT3 for optimal responses towards IgE-mediated activation, whereas MC functionality is minimally affected by elevated glucose levels. Based on these findings, antagonists of GLUT1 and GLUT3 may be considered for therapeutic intervention in allergic conditions.
Phase transformations in yttria-partly stabilized zirconia induced by dental polishing regimes
Authors: Wertz Markus , Berthold Christoph , Flicker Annette , Sander Stephan A. H. , Brinkmann Lisa , Fuchs Florian , Koenig Andreas
Published: April 2024

The study examined how three polishing methods, using equipment from NTI CeraGlaze (NTI), Komet Dental (Komet), and EVE Diacera (EVE) and employing either wet or dry grinding, affect the texture (roughness) and phase composition of Y-PSZ dental crowns. Dental crowns made from VITA’s 3Y-/4Y-/5Y-partly stabilized zirconia (Y-PSZ; YZ-HT/ST/XT), utilizing a standard CAD/CAM process, underwent both wet or dry grinding and polishing. The effects of distinct polishing treatments on Y-PSZ surface phase content were investigated using X-ray diffraction (XRD) and Rietveld refinement, the grain size was measured by field emission scanning electron microscopy (FE-SEM), and confocal scanning laser microscopy (CLSM) was used to determine the surface roughness as the arithmetical mean height (Sa). To analyse the different mode of action, the components of the polishers were analysed using XRD, along with micro X-ray computer tomography (µXCT), FE-SEM, and CLSM for microstructural examination. The Komet and NTI polishing regimes reduced roughness significantly better than the EVE regime for the 3Y and all wet specimens, but caused a rhombohedral phase fraction. A possible explanation for this result is the overall finer structure of the EVE coarse polisher (abrasive particle size and content, texture density), which probably results in a lower force on the Y-PSZ surface. Therefore, the rhombohedral phase boundary would not be reached. Due to rhombohedral phase having larger volume expansion and shear than the monoclinic phase, it may result in enhanced transformation toughening or detrimental low-temperature degradation effects.

Graphical abstract
Continuity with caveats in anesthesia: state and response entropy of the EEG
Authors: Ebensperger Max , Kreuzer Matthias , Kratzer Stephan , Schneider Gerhard , Schwerin Stefan
Published: April 2024

The growing use of neuromonitoring in general anesthesia provides detailed insights into the effects of anesthetics on the brain. Our study focuses on the processed EEG indices State Entropy (SE), Response Entropy (RE), and Burst Suppression Ratio (BSR) of the GE EntropyTM Module, which serve as surrogate measures for estimating the level of anesthesia. While retrospectively analyzing SE and RE index values from patient records, we encountered a technical anomaly with a conspicuous distribution of index values. In this single-center, retrospective study, we analyzed processed intraoperative electroencephalographic (EEG) data from 15,608 patients who underwent general anesthesia. We employed various data visualization techniques, including histograms and heat maps, and fitted custom non-Gaussian curves. Individual patients’ anesthetic periods were evaluated in detail. To compare distributions, we utilized the Kolmogorov–Smirnov test and Kullback–Leibler divergence. The analysis also included the influence of the BSR on the distribution of SE and RE values. We identified distinct pillar indices for both SE and RE, i.e., index values with a higher probability of occurrence than others. These pillar index values were not age-dependent and followed a non-equidistant distribution pattern. This phenomenon occurs independently of the BSR distribution. SE and RE index values do not adhere to a continuous distribution, instead displaying prominent pillar indices with a consistent pattern of occurrence across all age groups. The specific features of the underlying algorithm responsible for this pattern remain elusive.
Causality Detection and Quantification by Ensembles of Time Delay Neural Networks for Application to Nuclear Fusion Reactors
Authors: Gelfusa Michela , Rossi Riccardo , Murari Andrea
Published: April 2024

The understanding and control of complex systems in general, and thermonuclear plasmas in particular, require analysis tools, which can detect not the simple correlations but can also provide information about the actual mutual influence between quantities. Indeed, time series, the typical signals collected in many systems, carry more information than can be extracted with simple correlation analysis. The objective of the present work consists of showing how the technology of Time Delay Neural Networks (TDNNs) can extract robust indications about the actual mutual influence between time indexed signals. A series of numerical tests with synthetic data prove the potential of TDNN ensembles to analyse complex nonlinear interactions, including feedback loops. The developed techniques can not only determine the direction of causality between time series but can also quantify the strength of their mutual influences. An important application to thermonuclear fusion, the determination of the additional heating deposition profile, illustrates the capability of the approach to address also spatially distributed problems.
Unmasking Risky Habits: Identifying and Predicting Problem Gamblers Through Machine Learning Techniques
Authors: Sándor Máté Cs. , Bakó Barna
Published: April 2024

The use of machine learning techniques to identify problem gamblers has been widely established. However, existing methods often rely on self-reported labeling, such as temporary self-exclusion or account closure. In this study, we propose a novel approach that combines two documented methods. First we create labels for problem gamblers in an unsupervised manner. Subsequently, we develop prediction models to identify these users in real-time. The methods presented in this study offer useful insights that can be leveraged to implement interventions aimed at guiding or discouraging players from engaging in disordered gambling behaviors. This has potential implications for promoting responsible gambling and fostering healthier player habits.
Image segmentation and classification for fission track analysis for nuclear forensics using U-net model
Authors: Elgad Noam , Babayew Rami , Last Mark , Weiss Aryeh , Gilad Erez , Levy Galit Katarivas , Halevy Itzhak
Published: April 2024

This study introduces a novel methodology for the detection and classification of fission track (FT) clusters in microscope images, employing state-of-the-art deep learning techniques for segmentation and classification (Elgad in nuclear forensics—fission track analysis—star segmentation and classification using deep learning, Ben-Gurion University, 2022). The U-Net model, a fully convolutional network, was used to carry out the segmentation of various star-like patterns in both single-class and multi-class scenarios.
Financing Climate-Smart Agriculture: a case study from the Indo-Gangetic Plains
Authors: Villalba Roberto , Joshi Garima , Daum Thomas , Venus Terese E.
Published: April 2024

The Indo-Gangetic Plains represents one of South Asia’s most productive agricultural regions, yet it is highly vulnerable to climate change and requires the widespread adoption of Climate-Smart Agriculture. Although farmers understand the benefits of such technologies, financial constraints often undermine adoption. Using a case study from Haryana, we assess the opportunities and challenges aligned with the different pathways available for farmers to adopt and finance two capital-intensive technologies: laser land levelers and happy seeders. Our analysis uses unique data from Karnal, where stakeholders have partnered in Climate-Smart-Villages, and combines a household survey from 120 farmers, interviews, and focus group discussions with banks and cooperatives. Our results indicate adoption rates of 77% for laser land levelers and 52% for happy seeders, with only 7% and 21% of farmers owning the technologies, respectively. Hiring is highly preferred over purchase, mainly due to the flourishing of Custom-Hiring Centers, which are vital in driving large-scale implementation. We find that farmers prefer funding from family, savings, and moneylenders (indirect pathways) rather than from commercial banks (direct pathways) to get immediate access to credit and avoid bureaucratic procedures. Our study offers broader insights into the state of agricultural finance in India and adaptation to climate change and reveals that institutional innovations can enhance the financing of CSA technologies for smallholder farmers. Our findings have important implications for decision-makers seeking to streamline credit access for CSA machinery rental. Future research should focus on the efficacy of different finance channels and their causal impact on pathways for technology adoption.
Cumulative histogram as a feature selection technique for anomaly detection
Authors: Nassar Mostafa , Salama Rania A. , Saleeb Adel A. , El-bahnasawy Nirmeen A. , Ahmed Hossam Eldin H. , Abd El-Samie Fathi E.
Published: April 2024

The enhancement of Intrusion Detection Systems (IDS) is required to ensure protection of network resources and services. This is a hot research topic, especially in the presence of advanced intrusions and attacks. This paper provides a comparison between Distributed Cumulative Histogram (DCH) as a Feature Selection (FS) technique, Information Gain Ratio (IGR) FS and wrapper-based FS in terms of accuracy and Root Mean Square Error (RMSE). The utilization of DCH of the traffic instances in normal and attack cases allows us to compare the traffic charts. We can observe the difference between effective features and less effective ones. We verify the feasibility of using DCH as an FS technique in the field of anomaly detection with just six selected features giving more accurate results with most classifiers compared to the IGR and wrapper-based FS. We applied our experiments on the modern UNSW dataset with the WEKA simulation platform that contains a group of classification, feature reduction and selection techniques.
Alternate realities in interactive digital narratives – understanding and improving design and prosocial effects through empirical methods
Authors: Koenitz Hartmut , Roth Christian , Mekler Elisa
Published: April 2024

Abstract

Interactive digital narratives (IDNs) create alternate realities using both fictional and non-fiction material. The interactive aspect of IDN turns audiences into participants and enables the exploration of alternative perspectives and actions within a single artifact. Such multifaceted representations make IDN a vehicle for representing complex issues, a crucial capability at a time when the limits of traditional narrative media to adequately represent complex issues such as climate change become apparent. Conversely, properly evaluated, generalized knowledge about how exactly IDNs engage and influence us and what this means for the design of such works is still scant and thus this topic needs scholarly attention. In this overview paper, we discuss the potential of IDN, but also the difficulties of realizing this potential in terms of design and of verifying the effectiveness through empirical research methods. The potential of IDN as dynamic, participatory, and encyclopedic artifacts can be clearly expressed, yet the same cannot be said when it comes to the design and especially the evaluation of intended prosocial effects, the topic this paper is focused on. We start by identifying the problem of IDN design resulting from a combination of the lack of generalized knowledge and formal professional training. Then, we discuss the challenge of measuring the effectiveness of IDN design for prosocial effects and report on several case studies. In this context, we discuss methodological issues and advocate for best practices. Finally, we consider future steps in addressing the continuing challenge of evaluating IDNs.
Intraoperative magnetic resonance imaging in glioma surgery: a single-center experience
Authors: Mirzayeva Leyla , Uçar Murat , Kaymaz Ahmet Memduh , Temel Esra
Published: April 2024

Purpose

To investigate the effect of intraoperative magnetic resonance imaging (Io MRI) on overall and progression-free survival (OS and PFS), on the extent of resection (EOR) in patients with glioma, and impact of the radiological diagnosis on the decision to continue the surgery when a residual mass was detected on Io MRI.

Methods

The study comprised 153 glioma patients who received surgical treatment between 2013 and 2023. One-hundred twenty-five of them had Io MRI guidance during surgery. The remainder 28 patients constituted the control group who did not undergo Io MRI. All patients' age at surgery, gender, initial radiological diagnosis, primary tumor localization, EOR, last histopathological diagnosis, and the follow-up periods were recorded.

Results

The rate of tumor recurrence in Io MRI cases was significantly lower compared to the cases in the control group (p < .0001). It was decided to continue the operation in 45 Io MRI applied cases. This raised the gross total resection (GTR) rate from 33.6% to 49.6% in the Io MRI group. The frequency of GTR was significantly higher in patients with an initial radiological diagnosis of low grade glioma than those with high grade glioma. The shortest OS was seen in occipital gliomas.

Conclusion

In this study, the convenience provided by the high-field MRI device was explored and proven both in reducing the tumor burden, increasing the PFS, and providing the surgeon with a maximal resection in the first operation.
“Wrong” skewness and endogenous regressors in stochastic frontier models: an instrument-free copula approach with an application to estimate firm efficiency in Vietnam
Authors: Haschka Rouven E.
Published: April 2024

Stochastic frontier models commonly assume positively skewed inefficiency. However, if the data speak against this assumption, sample-failure problems are often cited, but less attention is paid to economic reasons. We consider this phenomenon as a signal of distinctive population characteristics stemming from the inefficiency component, emphasizing its potential impact on evaluating market conditions. Specifically, we argue more generally that “wrong” skewness could indicate a lack of competition in the market. Moreover, endogeneity of model regressors presents another challenge, hindering the identification of causal relationships. To tackle these issues, this paper proposes an instrument-free estimation method based on Gaussian copulas to model the dependence between endogenous regressors and composite errors, while accommodating positively or negatively skewed inefficiency through simultaneous identification. Monte Carlo simulation experiments demonstrate the suitability of our estimator, comparing it with alternative methods. The contributions of this study are twofold. On the one hand, we contribute to the literature on stochastic frontier models by providing a comprehensive method for dealing with “wrong” skewness and endogenous regressors simultaneously. On the other hand, our contribution to an economic understanding of “wrong” skewness expands the comprehension of market behaviors and competition levels. Empirical findings on Vietnamese firm efficiency indicate that endogeneity hinders the detection of “wrong” skewness and suggests a lack of competitive market conditions. The latter underscores the importance of policy interventions to incentivize firms in non-competitive markets.