bluuebunny/crossref_metadata_2025 huggingface dataset:
Study and comparison of different Machine Learning-based approaches to solve the inverse problem in Electrical Impedance Tomographies
Authors: Aller Martín , Mera David , Cotos José Manuel. , Villaroya Sebastián
Published: November 2022

Electrical Impedance Tomography (EIT) is a non-invasive technique used to obtain the electrical internal conductivity distribution from the interior of bodies. This is a promising method from the manufacturing viewpoint, since it could be used to estimate different physical inner body properties during the production of goods. Nevertheless, this technique requires dealing with an inverse problem that makes its usage in real-time processes challenging. Recently, Machine Learning techniques have been proposed to solve the inverse problem accurately. However, the majority of prior research is focused on qualitative results, and they typically lack a systematic methodology to determine the optimal hyperparameters appropriately. This work presents a systematic comparison of six popular Machine Learning algorithms: Artificial Neural Network, Random Forest, K-Nearest Neighbors, Elastic Net, Ada Boost, and Gradient Boosting. Particularly, the last two algorithms were based on decision tree learners. Furthermore, we studied the relationship between model performance and different EIT configurations. Specifically, we analyzed whether the measurement pattern and the number of used electrodes could increase the model performance. Experiments revealed that tree-based models present high performance, even better than Neural Networks, the most widely-used Machine Learning model to deal with EIT. Experiments also showed a model performance improvement when the EIT configuration was optimized. Most favorable metrics were attained using the tree-based Gradient Boosting model with a combination of both adjacent and mono measurement patterns as well as with 32 electrodes deployed during the tomographic process. With this particular setting, we achieved an accuracy of 99.14% detecting internal artifacts and a Root Mean Square Error of 4.75 predicting internal conductivity distributions.
Analysis of non-Markovian repairable fault trees through rare event simulation
Authors: Budde Carlos E. , D’Argenio Pedro R. , Monti Raúl E. , Stoelinga Mariëlle
Published: November 2022

Dynamic fault trees (DFTs) are widely adopted in industry to assess the dependability of safety-critical equipment. Since many systems are too large to be studied numerically, DFTs dependability is often analysed using Monte Carlo simulation. A bottleneck here is that many simulation samples are required in the case of rare events, e.g. in highly reliable systems where components seldom fail. Rare event simulation (RES) provides techniques to reduce the number of samples in the case of rare events. In this article, we present a RES technique based on importance splitting to study failures in highly reliable DFTs, more precisely, on a variant of repairable fault trees (RFT). Whereas RES usually requires meta-information from an expert, our method is fully automatic. For this, we propose two different methods to derive the so-called importance function. On the one hand, we propose to cleverly exploit the RFT structure to compositionally construct such function. On the other hand, we explore different importance functions derived in different ways from the minimal cut sets of the tree, i.e., the minimal units that determine its failure. We handle RFTs with Markovian and non-Markovian failure and repair distributions—for which no numerical methods exist—and implement the techniques on a toolchain that includes the RES engine FIG, for which we also present improvements. We finally show the efficiency of our approach in several case studies.
The Sumo coach problem
Authors: Rehsmann Daniel
Published: November 2022

We address the optimal allocation of stochastically dependent resource bundles to a set of simultaneous contests. For this purpose, we study a modification of the Colonel Blotto Game called the Tennis Coach Problem. We devise a thoroughly probabilistic method of payoff representation and fully characterize equilibria in this class of games. We further formalize the idea of strategic team training in a comparative static setting. The problem applies to several distinct economic interactions but seems most prevalent in team sports with individual matches, for instance, in Tennis and Sumo.
Values of blockchain for risk-averse high-tech manufacturers under government’s carbon target environmental taxation policies
Authors: Choi Tsan-Ming
Published: November 2022

Today, high-tech industries such as consumer electronics commonly face government rules on carbon emissions. Among the rules, carbon emission tax as well as extended producer responsibility (EPR) tax are two important measures. Using blockchain, the policy makers can better determine the carbon target environmental taxation (CTET) policy with accurate information. In this paper, based on the mean-variance framework, we study the values of blockchain for risk-averse high-tech manufacturers who are under the government’s CTET policy. To be specific, the government first determines the optimal CTET policy. The high-tech manufacturer then reacts and determines its optimal production quantity. We analytically prove that the CTET policy simply relies on the setting of the optimal EPR tax. Then, in the absence of blockchain, we consider the case in which the government does not know the manufacturer’s degree of risk aversion for sure and then derive the expected value of using blockchain for the high-tech manufacturers. We study when it is wise for the high-tech manufacturer and the government to implement blockchain. To check for robustness, we consider in two extended models respectively the situations in which blockchain incurs non-trivial costs as well as having an alternative risk measure. We analytically show that most of the qualitative findings remain valid.
A novel design scheme for acoustic cloaking of complex shape based on region partitioning and multi-origin coordinate transformation
Authors: Li Pengfei , Yang Fan , Wang Peng , Zhao Jinfeng , Zhong Zheng
Published: November 2022

Acoustic cloaking is an important application of acoustic metamaterials. This article proposes a novel design scheme for acoustic cloaking based on the region partitioning and multi-origin coordinate transformation. The cloaked region is partitioned into multiple narrow strips. For each strip, a local coordinate system is established with the local origin located at the strip center, and a coordinate transformation in the local coordinate system is conducted to squeeze the material along the strip length direction to form the cloaked region. To facilitate the implementation of the acoustic cloak, the multilayer effective medium is used to approximate the non-uniform anisotropic material parameters. The effectiveness of the proposed coordinate transformation method is verified by comparing the results from our method with those in the literature. Firstly, the results of a circular acoustic cloak in the literature are reproduced by using our finite element (FE) simulations for validation. Then, a comparison is made between the traditional coordinate transformation scheme and our new scheme for simulating an elliptical acoustic cloak. The results indicate that the proposed multi-origin coordinate transformation method has a better cloaking effect on the incident wave along the ellipse minor axis direction than the traditional method. This means that for the same object, an appropriate transformation scheme can be selected for different incident wave directions to achieve the optimal control effect. The validated scheme is further used to design an arch-shaped cloak composed of an upper semicircular area and a lower rectangular area, by combining the traditional single-centered coordinate transformation method for the semicircular area and the proposed multi-origin method for the rectangular area. The results show that the designed cloak can effectively control the wave propagation with significantly reduced acoustic pressure level. This work provides a flexible acoustic cloak design method applicable for arbitrary shapes and different wave incident directions, enriching the theory of acoustic cloaking based on coordinate transformation.
How to help digital-native students to successfully take control of their learning: A return of 8 years of experience on a computer science e-learning platform in higher education
Authors: Beaudoin Laurent , Avanthey Loïca
Published: November 2022

In this article, we present an educational reform we implemented a few years ago to respond to a marked drop in the success of students entering higher education in computer science. The main objective of our reform is to adapt the teaching methods of Generation X-Y to Generation Y-Z or more. To do this, we propose two approaches. First, to make learning more active, stimulating and empowering. Second, to make learning more individualized in a context of a large group of students with an optimization of the teacher’s time. We first present an analysis of the probable reasons for the lower level of students and the specific issues encountered by both students and teachers. Then, we detail how we implemented these solutions in the form of an original e-learning platform based on two back-end tools able to manage large number of students: an efficient real-time auto-corrector of source codes and a very robust anti-plagiarism software based on computer distance information theory. Finally, we present the results obtained after an experimentation of 8 years. These results are put into perspective by an analysis of 15 years of qualitative and quantitative indicators carried out on hundreds of students each year. The analysis shows that the technical skills and the involvement of students are improved even in groups of several hundreds of students. Computer science teachers wishing to quickly and concretely develop the involvement of their students can rely on these tried and tested key levers and solutions presented.
Exploring the Role of Organizational Mindfulness on Cloud Computing and Firm Performance: The Case of Kenyan Organizations
Authors: Oredo John , Dennehy Denis
Published: November 2022

The popularity and use of cloud computing has largely been driven by the reported benefits on firm performance. Despite this technology providing a paradigm shift in information technology (IT) services, the process through which the adoption of cloud computing effects organizational performance in the context of developing countries is still unclear. The aim of this study is to provide a theoretical discussion that advances our understanding about the mediating and moderating roles of organizational mindfulness in the context of cloud computing adoption and organizational performance. A research model is developed and tested using structural equation modelling. A firm level cross sectional survey was conducted on a sample of 180 organizations in the financial, manufacturing and IT sectors in Kenya. The findings reveal that organizations need to systematically develop mindfulness capabilities to benefit from the adoption of cloud, and IT innovations in general. The study has implications for research and practice.
Networks of Adversity in Childhood and Adolescence and Their Relationship to Adult Mental Health
Authors: Pollmann Ayla , Fritz Jessica , Barker Edward , Fuhrmann Delia
Published: November 2022

Adverse experiences before the age of eighteen are common and include diverse events ranging from sexual abuse to parental divorce. These stressful experiences have been linked to physical and mental health issues. Previous research has focused mainly on childhood adversity, such as experiences in the family environment. Little consideration has been given to adversities that may be particularly harmful in adolescence. To understand adolescents’ adverse experiences, this project used data from the Avon Longitudinal Study of Parents and Children (ALSPAC, total N = 14,901, N ≈ 1,200 − 10,000 per measure). We modelled interrelations of adversities in childhood (1–11 years) and adolescence (11–23 years) and examined adversity clusters using network analysis. We found two similar clusters in the childhood and adolescence networks: (1) direct abuse and (2) adverse family factors. We identified a third cluster of (3) educational and social adversities for adolescence. For both age groups, emotional abuse in the family environment was closely linked to mental health in early adulthood and most adversities were linked with depression in early adulthood. In adolescence, housing and academic issues and abuse by a romantic partner were particularly central to the network of adversities. Thus, we found commonalities and differences in the relevance of adverse experiences at different developmental stages. These findings highlight the need to develop age-dependent frameworks for adversity research and policymaking.
Cesàro means with varying parameters of Walsh–Fourier series
Authors: Gát György , Goginava Ushangi
Published: November 2022

In this paper we discuss some convergence and divergence properties of subsequences of Cesàro means with varying parameters of Walsh–Fourier series. We give necessary and sufficient conditions for the convergence regarding the weighted variation of numbers.
Multitemporal landslide exposure and vulnerability assessment in Medellín, Colombia
Authors: Kühnl Marlene , Sapena Marta , Wurm Michael , Geiß Christian , Taubenböck Hannes
Published: November 2022

Landslides are often deadly natural events. Steep slopes and certain loose soil types are predestined areas for them. Moreover, in the context of climate change, extreme weather events such as heavy rainfall, which often trigger landslides, are becoming even more likely. While all this is well known, it, therefore, stands to reason that this knowledge will lead to the avoidance of these risks. On the other hand, however, there are highly dynamic urbanization processes that often overtake formal urban planning processes by rising population figures and areal expansion. In the course of these processes, economically deprived population groups often have no other option than to informally build on high-risk areas. Against these backgrounds, we systematically examine in this study how these risks develop over a 24-year period from 1994 to 2018 taking into account three time steps, with respect to the citywide exposure and in particular with respect to different social groups. For this purpose, we use heterogeneous input data from remote sensing, landslide hazard maps, and census data. Our case study is the city of Medellín in Colombia. We develop and apply a set of methods integrating the heterogenous data sets to map, quantify and monitor exposure and social vulnerability at a fine spatial granularity. Our results document first of all the highly dynamic growth in total population and urban areas. However, our results reveal that the city's expansion is socially unevenly distributed. People of higher vulnerability proxied by informal settlements are found to settle in considerably higher shares of areas exposed to landslides. This study proposes a methodological setup that allows for monitoring exposure and social vulnerability over long time spans at a fine spatial resolution, allows to bring inequality into the spotlight, and provides decision-makers with better information to develop socially responsible policies.
Gender Stereotypes and Peer Selection in STEM Domains Among Children and Adolescents
Authors: McGuire Luke , Hoffman Adam J. , Mulvey Kelly Lynn , Hartstone-Rose Adam , Winterbottom Mark , Joy Angelina , Law Fidelia , Balkwill Frances , Burns Karen P. , Butler Laurence , Drews Marc , Fields Grace , Smith Hannah , Rutland Adam
Published: November 2022

Gender stereotypes are harmful for girls’ enrollment and performance in science and mathematics. So far, less is known about children’s and adolescents’ stereotypes regarding technology and engineering. In the current study, participants’ (N = 1,206, girls n = 623; 5–17-years-old, M = 8.63, SD = 2.81) gender stereotypes for each of the STEM (science, technology, engineering, and mathematics) domains were assessed along with the relation between these stereotypes and a peer selection task in a STEM context. Participants reported beliefs that boys are usually more skilled than are girls in the domains of engineering and technology; however, participants did not report gender differences in ability/performance in science and mathematics. Responses to the stereotype measures in favor of one’s in-group were greater for younger participants than older participants for both boys and girls. Perceptions that boys are usually better than girls at science were related to a greater likelihood of selecting a boy for help with a science question. These findings document the importance of domain specificity, even within STEM, in attempts to measure and challenge gender stereotypes in childhood and adolescence.
Effect of total parathyroidectomy in patients with secondary hyperparathyroidism: a retrospective study
Authors: Gong Xixiang , Wang Yi An , Li Chunqi , Liao Xue , Li Shihua , Yang Liping , Jiang Xuelian , Sun Yang , Xu Jianqing , Tong Zongwu , Lu Yongxin
Published: November 2022

Purpose

To investigate the therapeutic efficacy, feasibility, and safety of total parathyroidectomy (tPTX) in the treatment of secondary hyperparathyroidism (SHPT).

Methods

The clinical data of 34 SHPT patients admitted to the Department of Nephrology, Yuxi People’s Hospital, from January 2018 to January 2021 who had received tPTX, were retrospectively analyzed. The indications for tPTX were severe SHPT that did not respond to medical treatment and was ineligible for kidney transplantation. tPTX without autotransplantation was adopted to compare the level of symptom relief and changes in serum intact parathyroid hormone (iPTH), blood calcium, and blood phosphorus pre- and postoperatively.

Results

In 34 patients, 142 parathyroid glands were removed, including 21 ectopic parathyroid glands (14.78%). Six patients (17.64%, 6/34) had supernumerary parathyroid glands. At 6 h postoperatively, arthralgia and bone pain were significantly reduced to almost zero in 94.12% (32/34) of patients. At 24 h postoperatively, relief of bone pain and improvement of limb movement were observed in 100% (34/34) of patients, and pruritus almost disappeared in 86.36% (19/22) of patients. There were significant differences in iPTH (χ2 = 134.93, P < 0.05), calcium (χ2 = 23.02, P < 0.05), and phosphorus (χ2 = 102.11, P < 0.05) levels preoperatively and 40 min, 24 h, 1 week, half a year, and last available (> 1 year) postoperatively.

The patients were followed up for 15–47 months (median 33 months). Hypoparathyroidism was observed in three patients, who underwent neck dissection or partial thymotomy concurrently for different reasons. No intractable hypocalcemia or adynamic bone disease occurred during the follow-up period.

Conclusion

In SHPT patients who were ineligible for renal transplantation, tPTX was effective, safe, and reliable, with a low recurrence rate. However, when tPTX was performed alone without autologous transplantation, bilateral neck exploration was sufficient, and central neck dissection and thymic resection were inadvisable.
Causal Reasoning Meets Visual Representation Learning: A Prospective Study
Authors: Liu Yang , Wei Yu-Shen , Yan Hong , Li Guan-Bin , Lin Liang
Published: November 2022

Visual representation learning is ubiquitous in various real-world applications, including visual comprehension, video understanding, multi-modal analysis, human-computer interaction, and urban computing. Due to the emergence of huge amounts of multimodal heterogeneous spatial/temporal/spatial-temporal data in the big data era, the lack of interpretability, robustness, and out-of-distribution generalization are becoming the challenges of the existing visual models. The majority of the existing methods tend to fit the original data/variable distributions and ignore the essential causal relations behind the multi-modal knowledge, which lacks unified guidance and analysis about why modern visual representation learning methods easily collapse into data bias and have limited generalization and cognitive abilities. Inspired by the strong inference ability of human-level agents, recent years have therefore witnessed great effort in developing causal reasoning paradigms to realize robust representation and model learning with good cognitive ability. In this paper, we conduct a comprehensive review of existing causal reasoning methods for visual representation learning, covering fundamental theories, models, and datasets. The limitations of current methods and datasets are also discussed. Moreover, we propose some prospective challenges, opportunities, and future research directions for benchmarking causal reasoning algorithms in visual representation learning. This paper aims to provide a comprehensive overview of this emerging field, attract attention, encourage discussions, bring to the forefront the urgency of developing novel causal reasoning methods, publicly available benchmarks, and consensus-building standards for reliable visual representation learning and related real-world applications more efficiently.
Influence of nutrient supplementation and stress conditions on the biomass and lipid production of Microchloropsis salina for biodiesel production
Authors: El-Sheekh Mostafa M. , Mansour Heba M. , Bedaiwy Mohamed Y. , El-shenody Rania A.
Published: November 2022

This work aimed to introduce a new technique for improving sustainable biodiesel from Microchloropsis salina by examining the impact of various nitrogen sources, salt stress, and carbon enrichment, individually or in combination, to determine the best treatment conditions for biomass and lipid productivity as well as biodiesel quality. M. salina effectively utilizes nitrate (NaNO3 and KNO3) and organic nitrogen (especially yeast extract and glycine) but not ammonium for growth. The highest biomass and lipid productivity were observed on yeast extract (0.11 g L−1 day−1 and 52.11 μgmL−1 day−1, respectively). Lipid production enhanced by 80% under 300 mM of NaCl, while growth increased only by 30%. Acetate could not be used to cultivate the alga mixotrophically; only glucose and glycerol were effective. The ideal organic carbon supply values for glucose and glycerol were 3 g L−1 and 2 g L−1, respectively. Nutrition by 2 g L−1 glycerol promoted biomass and lipid productivities by 62% and 95%, respectively, while biomass productivity was reduced by 16% under combined and lipid productivity increased by 80%. All treatments significantly improved the biomass and biodiesel quality-related fatty acid profile.
New insight for spent hops utilization: simultaneous extraction of protein and xanthohumol using deep eutectic solvents
Authors: Grudniewska Aleksandra , Pastyrczyk Natalia
Published: November 2022

Agro-food by-products are a cheap source of bioactive and functional compounds that should be used via a biorefinery approach to produce a range of bio-based products. Spent hops (SH) are an important by-product of the brewing industry and are rich in valuable ingredients such as proteins and xanthohumol (XN). Considering the increasing demand for plant-based proteins and the broad spectrum of XN bioactivity, it is important to develop eco-friendly and cost-effective techniques to extract these components. In this work, a simple, one-pot, green method for the simultaneous extraction of proteins and XN from SH using deep eutectic solvents (DESs) was developed. Protein and XN-rich precipitates were obtained by adding water (antisolvent) to the DES extracts. To determine the XN content, the precipitates were extracted with methanol and the extracts were analyzed by HPLC. The presence of protein in the methanol-insoluble fractions was confirmed by techniques such NMR, IR, elemental analysis, and SDS-PAGE. The protein content varied between 40 and 64%, which was up to 87% higher than the protein content in the SH. This study demonstrates the potential use of SH and DESs to develop an environmentally friendly method to obtain protein and XN-rich products.

Graphical abstract
Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction
Authors: Banco Daniel P. , Miller Eric , Beaudoin Armand , Miller Matthew P. , Chatterjee Kamalika
Published: November 2022

Measured intensity in high-energy monochromatic X-ray diffraction (HEXD) experiments provides information regarding the microstructure of the crystalline material under study. The location of intensity on an areal detector is determined by the lattice spacing and orientation of crystals so that changes in the heterogeneity of these quantities are reflected in the spreading of diffraction peaks over time. High temporal resolution of such dynamics can now be experimentally observed using technologies such as the mixed-mode pixel array detector (MM-PAD) which facilitates in situ dynamic HEXD experiments to study plasticity and its underlying mechanisms. In this paper, we define and demonstrate a feature computed directly from such diffraction time series data quantifying signal spread in a manner that is correlated with plastic deformation of the sample. A distinguishing characteristic of the analysis is the capability to describe the evolution from the distinct diffraction peaks of an undeformed alloy sample through to the non-uniform Debye–Scherrer rings developed upon significant plastic deformation. We build on our previous work modeling data using an overcomplete dictionary by treating temporal measurements jointly to improve signal spread recovery. We demonstrate our approach in simulations and on experimental HEXD measurements captured using the MM-PAD. Our method for characterizing the temporal evolution of signal spread is shown to provide an informative means of data analysis that adds to the capabilities of existing methods. Our work draws on ideas from convolutional sparse coding and requires solving a coupled convex optimization problem based on the alternating direction method of multipliers.
Knee osteoarthritis and adverse health outcomes: an umbrella review of meta-analyses of observational studies
Authors: Veronese Nicola , Honvo Germain , Bruyère Olivier , Rizzoli René , Barbagallo Mario , Maggi Stefania , Smith Lee , Sabico Shaun , Al-Daghri Nasser , Cooper Cyrus , Pegreffi Francesco , Reginster Jean-Yves
Published: November 2022

Background

Knee osteoarthritis (OA) is a common condition, associated with a high rate of disability and poor quality of life. Despite the importance of such evidence in public health, no umbrella review (i.e., a review of other systematic reviews and meta-analyses) has systematically assessed evidence on association between knee OA and adverse health outcomes.

Aims

To map and grade all health outcomes associated with knee OA using an umbrella review approach.

Methods

The search was made across several databases up to 22 April 2022. We used an umbrella review of systematic reviews with meta-analyses of observational studies assessing the effect sizes, based on random effect summary, 95% prediction intervals, heterogeneity, small study effects, and excess significance bias. The evidence was then graded from convincing (class I) to weak (class IV).

Results

Among 3,847 studies initially considered, five meta-analyses were included for a total of five different outcomes. Three adverse outcomes were significantly associated with knee OA (i.e., cardiovascular mortality, falls, and subclinical atherosclerosis). The presence of knee OA was associated with a significantly higher risk of cardiovascular mortality (odds ratio, OR = 1.17; 95%CI, confidence intervals: 1.02–1.34), falls (RR = 1.34; 95%CI: 1.10–1.64), and conditions associated with subclinical atherosclerosis (OR = 1.43; 95%CI: 1.003–2.05). The certainty of each of this evidence was weak.

Conclusions

Our umbrella review suggests that knee OA can be considered as putative risk factor for some medical conditions, including cardiovascular diseases and falls, however, it is important to note that the evidence is affected by potential biases.
Size effects in the uniaxial compressive properties of 3D printed models of rocks: an experimental investigation
Authors: Wu Hao , Ju Yang , Han Xin , Ren Zhangyu , Sun Yue , Zhang Yanlong , Han Tianyi
Published: November 2022

Transparent physical models of real rocks fabricated using three-dimensional (3D) printing technology are used in photoelastic experiments to quantify the evolution of the internal stress and deformation fields of rocks. Therefore, they are rendered as an emerging powerful technique to quantitatively reveal the intrinsic mechanisms of rock failure. The mechanical behavior of natural rocks exhibits a significant size effect; however, limited research has been conducted on whether transparent physical models observe similar size effects. In this study, to make the transparent printed models accurately demonstrate the mechanical behavior of natural rocks and reveal the internal mechanism of the size effect in rock mechanical behavior, the size effect in 3D printed models of fractured and porous rocks under uniaxial compressive loading was investigated. Transparent cylindrical models with different sizes that contained different fractured and porous structures were printed using the fracture and porous characteristics extracted from natural coal and sandstone. The variation in uniaxial compressive strength and elastic modulus of fractured and porous models for increasing model sizes were obtained through uniaxial compression experiments. Finally, the influence of internal discontinuous structural features, such as fractures and pores, on the size effect pertaining to the mechanical behavior of the model was analyzed and elaborated by comparing it with the mechanical properties of the continuous homogeneous model without fractures and pores. The findings provided support and reference to analyze the size effect of rock mechanical behavior and the effect of the internal discontinuous structure using 3D printed transparent models.
Can value chain integration explain the diverging economic performance within the EU?
Authors: Kügler Agnes , Reinstaller Andreas , Friesenbichler Klaus S.
Published: November 2022

This paper studies the interplay of integration into EU value chains and industrial development measured by labour productivity. We focus on the mediating role of domestic institutions compared to technological determinants for the distribution of the economic value generated along the European and global value chains. Our integration indicator measures value chain trade within the Single Market relative to global value chain networks. Using a simultaneous equation model, we find an overall positive effect of integration on labour productivity, which is driven by upstream integration. While the effect of productivity on integration is positive, it decreases with increasing productivity levels. Highly productive industries rather seek global value chain trade than regional integration. Better domestic institutions facilitate EU integration, although they favour industries with less complex product portfolios and lower levels of knowledge cumulativeness. This creates politically unwanted specialisation effects leading to an unequal distribution of the economic value generated.
Wie theoriebasiert sind Forschungsbeiträge zur Bildungsbeteiligung? Eine Qualitative Inhaltsanalyse ausgewählter Fachzeitschriften der Erwachsenen- und Weiterbildungsforschung
Authors: Troidl Kilian , Schroll-Decker Irmgard
Published: November 2022

In der Vergangenheit wurde beklagt, dass in der empirischen Forschung zur Bildungsbeteiligung Erwachsener selten eine Integration von Theorie und Empirie erfolge und die mangelnde empirische Prüfung eine theoretische Weiterentwicklung des Forschungsfeldes erschwere. Mittels einer Qualitativen Inhaltsanalyse von Beiträgen ausgewählter Fachzeitschriften der Erwachsenen‑/Weiterbildungsforschung wurde versucht, die Aktualität dieser Feststellung empirisch zu überprüfen. Dazu wurden 38 empirische Forschungsbeiträge zur Bildungsbeteiligung der Jahrgänge 2018 bis 2020 von neun Fachzeitschriften mit Peer-Review untersucht. Die Einschätzung der Beiträge erfolgte hinsichtlich des Grades der Theorieeinbindung. Die Ergebnisse der Analyse zeigen ein gemischtes Bild: neun Beiträge (24 %) binden keine Theorie in den Forschungsprozess ein, ein Beitrag (3 %) zitiert Theorie lediglich, ohne sie weiter einzubinden. Am häufigsten ist eine Einbindung zum theoriegeleiteten Vorgehen (16 Beiträge, 42 %). Eine tiefergehende Theorieanwendung findet sich in sechs Beiträgen (16 %). Eine theorieprüfende oder -bildende Einbindung liegt mit je drei Beiträgen (je 8 %) seltener vor. Die rezipierten Theorien sind vielfältig: es werden 20 verschiedene Theorieansätze festgestellt. Den Forderungen nach einer verstärkten Einbindung von Theorie in den Forschungsprozess kann somit weiterhin Gültigkeit attestiert werden: ein substanzieller Teil der Beiträge berichtet keine Theorieeinbindung, eine empirische Prüfung oder Weiterentwicklung findet relativ selten statt.
A modelling study on quantifying the impact of urbanization and regional effects on the wintertime surface temperature over a rapidly-growing tropical city
Authors: Nandini Gopinath , Vinoj V. , Sethi Soumya Satyakanta , Nayak H. P. , Landu Kiranmayi , Swain D. , Mohanty U. C.
Published: November 2022

Climate change and sustainability are among the most widely used terms among policymakers and the scientific community in recent times. However, climate action or steps to sustainable growth in cities in the global south are mostly borrowed from general studies at a few large urban agglomerations in the developed world. There are very few modeling studies over south Asia to understand and quantify the impact of climate change and urbanization on even the most primary meteorological variable, such as temperature. Such quantifications are difficult to estimate due to the non-availability of relevant long-term observational datasets. In this modeling study, an attempt is made to understand the urban heat island (UHI), its transition, and the segregation of regional climate change effects and urbanization over the rapidly growing tier 2 tropical smart city Bhubaneswar in India. The model is able to simulate the UHI for both land surface temperature, called the SUHI, and 2-m air temperature, called UHI, reasonably well. Their magnitudes were ~ 5 and 2.5°C, respectively. It is estimated that nearly 60–70% of the overall air and 70–80% of the land surface temperature increase during nighttime over the city between the period 2004 and 2015 is due to urbanization, with the remaining due to the regional/non-local effects.
Estimating the risk of completion total thyroidectomy using real-world data to guide initial surgical decision-making for patients with clinical low-risk papillary thyroid carcinoma
Authors: Liu Wen , Zhan Xiangxiang , Dong Zhizhong , Su Yanjun , Zhang Jianming , Qian Jun , Ma Yunhai , Diao Chang , Cheng Ruochuan
Published: November 2022

Background

Continuing controversy exists in different guidelines’ recommendations regarding whether total thyroidectomy (TT) or lobectomy is the optimal surgery for patients with low-risk papillary thyroid carcinoma (PTC). Diverse perceptions of the risk of completion TT after lobectomy are the main debate between guidelines and institutions.

Methods

Patients who underwent thyroidectomy and prophylactic central lymph node dissection for ≤ 4 cm PTC (January 2007 to December 2020) by high-volume surgeons were included. Patients with preoperatively known high-risk characteristics or suspicious bilateral multifocality were excluded. The pathological findings were defined as the risk stratifications of completion TT from low to high to evaluate which initial surgical procedure could allow more patients to meet the criteria of optimal surgical extent.

Results

Of 4965 consecutive patients met lobectomy criteria as the initial operation. Aggressive histological subtypes were found in 2.5% of patients, T3b disease in 1.1%, T4 disease in 3.1%, LNs involved ≤ 5 in 29.5%, LNs involved > 5 in 3.1%, and incidental bilateral multifocality in 7.9%. According to our defined risk stratification system, TT and lobectomy would be considered the optimal initial procedure in 12.0% and 67.2% PTC patients with a tumor ≤ 1 cm and 28.7% and 36.6% in the 1–4 cm groups in our real-world cohort, respectively.

Conclusion

Lobectomy alone, as an initial procedure, could allow more low-risk PTC patients with a tumor either ≤ 1 cm or 1–4 cm to achieve the optimal surgical extent. Moreover, surgeons should balance the high-risk characteristics and complication risks during surgery to re-evaluate surgical decision-making.
Comparison of body mass index, anti-müllerian hormone and insulin resistance parameters among different phenotypes of polycystic ovary syndrome
Authors: Gürsu Türkan , Eraslan Alper , Angun Berk
Published: November 2022

Background

Diagnosis of polycystic ovary syndrome (PCOS) depends on 2003 Rotterdam Criteria. According to these criteria there are four possible combinations resulting in various phenotypes. We aimed (i)to confirm that the levels of body mass index (BMI), anti-müllerian hormone (AMH) levels and insulin resistance (IR) are higher in PCOS patients and higher in phenotype-A among PCOS patients, and (ii)to determine cut-off values for the diagnosis of PCOS and phenotype-A.

Materials and methods

This study was conducted in an IVF Center, between November 2019 and January 2021. Data of infertile women participating in the study was evaluated retrospectively. Parameters such as menstruation pattern, clinical hyperandrogenism, age, BMI, follicle stimulating hormone (FSH), luteinizing hormone (LH), estradiol, thyroid stimulating hormone (TSH), prolactin, AMH, dehydroepiandrosterone sulphate (DHEA-S), fasting blood glucose, fasting insulin levels, antral follicle counts (AFC) and ovarian volumes were recorded for each patient. Women were grouped as PCOS and non-PCOS, and PCOS group was further divided into 4 sub-groups according to their phenotypes. Data of infertile patients with PCOS patients were compared with infertile non-PCOS patients and PCOS phenotypes were compared among each other.

Results

Data of 244 infertile patients was included in the study. BMI, AMH, AFC, and HOMA-IR were statistically higher in PCOS patients, compared to non-PCOS patients. We found the AMH level of >3.105 ​ng/ml to be having 90.8% sensitivity and 90% specificity to diagnose a patient as PCOS. Among different phenotypes, also BMI, AMH, and insulin resistance index (HOMA-IR) levels were significantly higher in infertile PCOS phenotype-A when compared to other three phenotypes (p:0.003, p:0.000, and p:0.000, respectively). The AMH cut-off value to estimate phenotype-A was found as 6.095 ​ng/ml with 69.2% sensitivity and 86.7% specificity. We did not found threshold levels of BMI and HOMA-IR with high sensitivity to identify phenotype-A.

Conclusion

Properly diagnosing PCOS and determining the phenotype are crucial due to the long-term health conditions. Therefore, we suggest that serum AMH level could be included in PCOS diagnosis criteria, and the value of 3.105 ​ng/ml would have a 90.8% sensitivity and 90% specificity. Also, to identify phenotype-A, AMH level could be used. Therefore, we speculate that AMH may serve to identify PCOS and PCOS phenotype-A in places where ultrasound imaging is not straightforward to perform or not easily accessible.
Two times two temperaments of legal scholarship and the question of commodification
Authors: Somek Alexander
Published: November 2022

The article offers a brief account of the continental European (viz., German) and the US American approach to legal education and scholarship. It then explores in which respect legal academics active in these cultures are vulnerable to the lure of commodification, that is, incentives to produce legal expertise for clients. After concluding that these incentives may well be stronger in countries where legal academics consider themselves badly paid and where scholarly traditions are weak, the article explores how commodification can adversely affect the culture of ‘legal science’ as a whole and even work to the detriment of clients.
Defending Ukraine with EU weapons: arms control law in times of crisis
Authors: Hamilton Tomas
Published: November 2022

The wish from 24 February 2022 onwards to help Ukraine defend against Russian aggression has led to the provision of unprecedented lethal European Union (EU) military assistance. As the ‘taboo’ of supplying lethal assistance into non-EU conflicts is swept aside, what is the role of international arms control law? The legal requirements of the EU Common Position on arms exports and the Arms Trade Treaty compel EU Member States to assess various short- and long-term risks associated with arms exports. But it is unclear how arms control norms are being taken into account by the EU Council in its rapidly evolving role as a peacemaker.

The standards that are being used to shape EU decision-making on Ukraine matter both for their precedent-setting as reflecting the trajectory of EU normative power, as well as on the long-term blowbacks of proliferation on illicit arms trafficking. While from the EU Council, there has been limited public articulation of these risks, greater consideration thereof would serve as a reminder of the reality of post-conflict arms proliferation, ie. illicit arms trafficking of weapons leached from the conflict, and their subsequent misuse by undesirable actors. Geostrategic precedent is being set, with implications that extend far beyond Ukraine, including to other conflicts where the EU is already intervening. The EU’s delivering of massive lethal military assistance alters also the reflexive perception of its institutions.
The Italian Constitutional Court, the plurality of legal orders and supranational fundamental rights: a discussion in terms of interlegality
Authors: Cozzi Alessia-Ottavia
Published: November 2022

This work aims to investigate the stance of the Italian Constitutional Court (ItCC) on ECHR and CFREU and their respective Courts, ECtHR and CJEU. The aim is to verify if the attitude of the ItCC could be described in terms of openness or closedness, understanding openness as an effort to practise loyal cooperation through procedural means and, substantively, as greater attention for the norms of supranational orders, and closedness as the setting aside of all forms of procedural ties with the supranational Courts and the voluntary dissociation from their outcome, with the purpose of prioritising domestic constitutional provisions. To conduct the analysis, the article refers to the theory of interlegality, questioning whether ItCC, operating ‘on the borders between several normative orders’, has a broader accountability to these different orders. The first part of the paper is devoted to some elements drawn from the case law indicating openness, such as the language use by the ItCC, the procedures, the legal reasoning, and the effects of judgements. Attention is given to the contextual reference to the recognition norms of both the Italian Constitution and European Union (EU) Treaties and to the increasing use of preliminary rulings to the CJEU. The second part of the paper discusses a substantive criterion created by the ItCC, the ‘greatest extension of guarantees’, demonstrating that it does not refer to the level of protection of individual rights, but to the balance of the entire constitutional system. Our conclusion is that the ItCC trends concerning supranational rights express a deferent and operational, but vigilant cooperation, retaining a margin to ensure the vitality of the domestic Constitution.
Elements of prime order in Tate–Shafarevich groups of abelian varieties over
Authors: Shnidman Ari , Weiss Ariel
Published: November 2022

For each prime p, we show that there exist geometrically simple abelian varieties A over

${\mathbb Q}$

with

. Specifically, for any prime

$N\equiv 1 \ \pmod p$

, let

$A_f$

be an optimal quotient of

$J_0(N)$

with a rational point P of order p, and let

$B = A_f/\langle P \rangle $

. Then the number of positive integers

$d \leq X$

with

is

$ \gg X/\log X$

, where

$\widehat B_d$

is the dual of the dth quadratic twist of B. We prove this more generally for abelian varieties of

$\operatorname {\mathrm {GL}}_2$

-type with a p-isogeny satisfying a mild technical condition. In the special case of elliptic curves, we give stronger results, including many examples where

for an explicit positive proportion of integers d.
The effects of cannabidiol on behavioural and oxidative stress parameters induced by prolonged haloperidol administration
Authors: Kajero Jaiyeola Abiola , Seedat Soraya , Ohaeri Jude U. , Akindele Abidemi , Aina Oluwagbemiga
Published: November 2022

Objectives:

We investigated the influence of oral cannabidiol (CBD) on vacuous chewing movements (VCM) and oxidative stress parameters induced by short- and long-term administration of haloperidol in a rat model of tardive dyskinesia (TD).

Methods:

Haloperidol was administered either sub-chronically via the intraperitoneal (IP) route or chronically via the intramuscular (IM) route to six experimental groups only or in combination with CBD. VCM and oxidative stress parameters were assessed at different time points after the last dose of medication.

Results:

Oral CBD (5 mg/kg) attenuated the VCM produced by sub-chronic administration of haloperidol (5 mg/kg) but had minimal effects on the VCM produced by chronic administration of haloperidol (50 mg/kg). In both sub-chronic and chronic haloperidol groups, there were significant changes in brain antioxidant parameters compared with CBD only and the control groups. The sub-chronic haloperidol-only group had lower glutathione activity compared with sub-chronic haloperidol before CBD and the control groups; also, superoxide dismutase, catalase, and 2,2-diphenyl-1-picrylhydrazyl activities were increased in the sub-chronic (IP) haloperidol only group compared with the CBD only and control groups. Nitric oxide activity was increased in sub-chronic haloperidol-only group compared to the other groups; however, the chronic haloperidol group had increased malondialdehyde activity compared to the other groups.

Conclusions:

Our findings indicate that CBD ameliorated VCM in the sub-chronic haloperidol group before CBD, but marginally in the chronic haloperidol group before CBD. There was increased antioxidant activity in the sub-chronic group compared to the chronic group.