bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractAdverse 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.
Multitemporal landslide exposure and vulnerability assessment in Medellín, Colombia
Authors: Kühnl Marlene , Sapena Marta , Wurm Michael , Geiß Christian , Taubenböck Hannes 
Published: November 2022

AbstractLandslides 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

AbstractGender 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

Abstract
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

AbstractVisual 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

Abstract
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

Abstract 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

AbstractMeasured 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

AbstractBackgroundKnee 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.AimsTo map and grade all health outcomes associated with knee OA using an umbrella review approach.MethodsThe 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).ResultsAmong 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.ConclusionsOur 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

AbstractTransparent 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

AbstractThis 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

ZusammenfassungIn 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

AbstractClimate 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.