bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated analysis of transcriptome and small RNAome reveals regulatory network of rapid and long-term response to heat stress in Rhododendron moulmainense
Authors: Liu Si-Jia , Cai Chang , Cai Hong-Yue , Bai Yu-Qing , Wang Ding-Yue , Zhang Hua , Peng Jin-Gen , Xie Li-Juan
Published: March 2024

Main conclusion

The post-transcriptional gene regulatory pathway and small RNA pathway play important roles in regulating the rapid and long-term response of Rhododendron moulmainense to high-temperature stress.

The Rhododendron plays an important role in maintaining ecological balance. However, it is difficult to domesticate for use in urban ecosystems due to their strict optimum growth temperature condition, and its evolution and adaptation are little known. Here, we combined transcriptome and small RNAome to reveal the rapid response and long-term adaptability regulation strategies in Rhododendron moulmainense under high-temperature stress. The post-transcriptional gene regulatory pathway plays important roles in stress response, in which the protein folding pathway is rapidly induced at 4 h after heat stress, and alternative splicing plays an important role in regulating gene expression at 7 days after heat stress. The chloroplasts oxidative damage is the main factor inhibiting photosynthesis efficiency. Through WGCNA analysis, we identified gene association patterns and potential key regulatory genes responsible for maintaining the ROS steady-state under heat stress. Finally, we found that the sRNA synthesis pathway is induced under heat stress. Combined with small RNAome, we found that more miRNAs are significantly changed under long-term heat stress. Furthermore, MYBs might play a central role in target gene interaction network of differentially expressed miRNAs in R. moulmainense under heat stress. MYBs are closely related to ABA, consistently, ABA synthesis and signaling pathways are significantly inhibited, and the change in stomatal aperture is not obvious under heat stress. Taken together, we gained valuable insights into the transplantation and long-term conservation domestication of Rhododendron, and provide genetic resources for genetic modification and molecular breeding to improve heat resistance in Rhododendron.
Could different structural features affect flammability traits in Mediterranean forest ecosystems?
Authors: Cappelluti Onofrio , Elia Mario , Sanesi Giovanni
Published: March 2024

Key message

Mediterranean forest stands manifest diverse flammability traits according to their potential ecological successional stage and promoting a gradient from flammable to less flammable ecosystem.

From a general consideration of vegetation as ‘fuel’, it has been well proven that plant traits have the potential to promote the forest stand gradient from flammable to less flammable. While the ever-growing literature helps to assess the relationship between plants and their flammability at species level, at the landscape scale this relationship should be evaluated along with a variety of forest features such as structural and stand parameters and from the perspective of successional forest stages. To this end, we clustered several forest stands in Southern Europe (Apulia region, Italy), characterized by oaks, conifers, and arboreal shrub species, according to their flammability traits. We hypothesized that flammability traits change along different horizontal and vertical structural features of forest stands, shifting from high to low-flammability propensity. The results confirmed that forest stands with greater height and diameter classes are associated with traits with a low-flammability propensity. It is worth highlighting the importance of shrub coverage in differentiating the clusters denoting their strong influence in increasing fuel load (litter and fuel bed traits). Finally, our findings lead us to assume that high-flammability propensity traits are associated with typical pioneer successional stages, supporting the notion that later successional forest stands are less flammable and, therefore, that flammability decreases along with succession.
Natural resource development, economic policy uncertainty and urban residents’ consumption in China: a nonlinear ARDL and time-varying parameter vector autoregressive with stochastic volatility approach
Authors: Long Tianxiang , Cui Xiangying , Yan Jiale , Işık Cem , Pinzon Stefania , Irfan Muhammad
Published: March 2024

Increased risks of economic policy uncertainty and overexploitation of natural resources exist in China. At the same time, the growth rate of urban residents’ consumption has generally declined. The paper analyses the role of economic policy uncertainty (EPU) and natural resource exploitation on the urban residents’ consumption in China. Based on the data from the first quarter of 2002 to the third quarter of 2021, the paper uses a nonlinear autoregressive distributed lag model to verify the asymmetric effects. Then the paper constructs a time-varying parameter vector autoregressive model with stochastic volatility term to analyze the nonlinear responses. Impulse response analysis was used to further explain the relationship between the three. The negative impact of rising EPU on urban residents’ consumption is larger than its reduction. Negative shocks to natural resource development increase the urban residents’ consumption. Positive shocks reduce the urban residents’ consumption. There is a time-varying non-linear effect of EPU and natural resource development on urban residents’ consumption in China. The negative impact of EPU on urban consumption has been further exacerbated by major crises such as the financial crisis, COVID-19 and the post-crisis period. The negative impact of natural resource development diminished after the government introduced industrial upgrading policies and environmental regulations. This study provides constructive suggestions for the optimization of economic policies and the improvement of urban consumption. This study also enriches consumer theory and provides new evidence for the resource curse hypothesis.
Diagnostic conversion to bipolar disorder among adolescents and young adults with major depressive disorder: a nationwide longitudinal study
Authors: Kung Fan-Hsuan , Tsai Chia-Kuang , Cheng Chih-Ming , Tsai Shih-Jen , Su Tung-Ping , Chen Tzeng-Ji , Bai Ya-Mei , Liang Chih-Sung , Chen Mu-Hong
Published: March 2024

Although several studies have examined a diagnostic conversion from major depressive disorder (MDD) to bipolar disorder (BD), only a few studies specifically focused on adolescents and young adults who are at the peak ages of BD onset. Data from participants (N = 130,793) aged 10–29 years who were diagnosed with MDD were extracted from the Taiwan National Health Insurance Research Database. We applied demographic analyses, survival analysis, Aalen Johansen curves, and Cox regression, investigating the diagnostic conversion rate and factors that were most or less predictive of conversion. Among the adolescents and young adults with MDD, the number of participant conversion subsample is 14,187 and the conversion rate was 13.80% (95% confidence interval: 13.54–14.06%) during the 11-year follow-up. The conversion rate was highest in the first year (4.50%; 4.39–4.61%) and decreased over time. The significant predictors were younger age of diagnosis with MDD (p < 0.001), moderate and high antidepressant resistance (p < 0.001), obesity (p < 0.001), psychiatric comorbidities (attention-deficit/hyperactivity disorder, substance use disorder, and cluster B and C personality disorder, all p < 0.001), a family history of mental disorders (schizophrenia and mood disorders, all p < 0.05), lower monthly income (p < 0.001), and more mental health visits to the clinic each year (p < 0.001). A composite of demographic characteristics, antidepressant resistance, physical and psychiatric comorbidities, and family history significantly predicted diagnostic conversion from MDD to BD (area under the curve = 0.795, p < 0.001). Compared to adult population, the adolescents and young adults had different factors that were most or less predictive of conversion, which warrants further investigation.
Bridging horizons beyond CIRCULATE-Japan: a new paradigm in molecular residual disease detection via whole genome sequencing-based circulating tumor DNA assay
Authors: Hashimoto Tadayoshi , Nakamura Yoshiaki , Oki Eiji , Kobayashi Shin , Yuda Junichiro , Shibuki Taro , Bando Hideaki , Yoshino Takayuki
Published: March 2024

Circulating tumor DNA (ctDNA) is the fraction of cell-free DNA in patient blood that originates from a tumor. Advances in DNA sequencing technologies and our understanding of the molecular biology of tumors have increased interest in exploiting ctDNA to facilitate detection of molecular residual disease (MRD). Analysis of ctDNA as a promising MRD biomarker of solid malignancies has a central role in precision medicine initiatives exemplified by our CIRCULATE-Japan project involving patients with resectable colorectal cancer. Notably, the project underscores the prognostic significance of the ctDNA status at 4 weeks post-surgery and its correlation to adjuvant therapy efficacy at interim analysis. This substantiates the hypothesis that MRD is a critical prognostic indicator of relapse in patients with colorectal cancer. Despite remarkable advancements, challenges endure, primarily attributable to the exceedingly low ctDNA concentration in peripheral blood, particularly in scenarios involving low tumor shedding and the intrinsic error rates of current sequencing technologies. These complications necessitate more sensitive and sophisticated assays to verify the clinical utility of MRD across all solid tumors. Whole genome sequencing (WGS)-based tumor-informed MRD assays have recently demonstrated the ability to detect ctDNA in the parts-per-million range. This review delineates the current landscape of MRD assays, highlighting WGS-based approaches as the forefront technique in ctDNA analysis. Additionally, it introduces our upcoming endeavor, WGS-based pan-cancer MRD detection via ctDNA, in our forthcoming project, SCRUM-Japan MONSTAR-SCREEN-3.
Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation
Authors: Vassøy Bjørnar , Langseth Helge
Published: March 2024

In the current landscape of ever-increasing levels of digitalization, we are facing major challenges pertaining to data volume. Recommender systems have become irreplaceable both for helping users navigate the increasing amounts of data and, conversely, aiding providers in marketing products to interested users. Data-driven models are susceptible to data bias, materializing in the bias influencing the models’ decision-making. For recommender systems, such issues are well exemplified by occupation recommendation, where biases in historical data may lead to recommender systems relating one gender to lower wages or to the propagation of stereotypes. In particular, consumer-side fairness, which focuses on mitigating discrimination experienced by users of recommender systems, has seen a vast number of diverse approaches. The approaches are further diversified through differing ideas on what constitutes fair and, conversely, discriminatory recommendations. This survey serves as a systematic overview and discussion of the current research on consumer-side fairness in recommender systems. To that end, a novel taxonomy based on high-level fairness definitions is proposed and used to categorize the research and the proposed fairness evaluation metrics. Finally, we highlight some suggestions for the future direction of the field.
Measuring Alliance and Symptom Severity in Psychotherapy Transcripts Using Bert Topic Modeling
Authors: Lalk Christopher , Steinbrenner Tobias , Kania Weronika , Popko Alexander , Wester Robin , Schaffrath Jana , Eberhardt Steffen , Schwartz Brian , Lutz Wolfgang , Rubel Julian
Published: March 2024

We aim to use topic modeling, an approach for discovering clusters of related words (“topics”), to predict symptom severity and therapeutic alliance in psychotherapy transcripts, while also identifying the most important topics and overarching themes for prediction. We analyzed 552 psychotherapy transcripts from 124 patients. Using BERTopic (Grootendorst, 2022), we extracted 250 topics each for patient and therapist speech. These topics were used to predict symptom severity and alliance with various competing machine-learning methods. Sensitivity analyses were calculated for a model based on 50 topics, LDA-based topic modeling, and a bigram model. Additionally, we grouped topics into themes using qualitative analysis and identified key topics and themes with eXplainable Artificial Intelligence (XAI). Symptom severity could be predicted with highest accuracy by patient topics ($$r$$
r
=0.45, 95%-CI 0.40, 0.51), whereas alliance was better predicted by therapist topics ($$r$$
r
=0.20, 95%-CI 0.16, 0.24). Drivers for symptom severity were themes related to health and negative experiences. Lower alliance was correlated with various themes, especially psychotherapy framework, income, and everyday life. This analysis shows the potential of using topic modeling in psychotherapy research allowing to predict several treatment-relevant metrics with reasonable accuracy. Further, the use of XAI allows for an analysis of the individual predictive value of topics and themes. Limitations entail heterogeneity across different topic modeling hyperparameters and a relatively small sample size.
The Impact of Sibling Relationships on Behavioral and Sexual Health among Latino Sexual Minority Men
Authors: Zapata Juan Pablo , Rojas Edwin , Durán Petra , Martínez Angel J. , del Pino Homero E.
Published: March 2024

Pre-exposure prophylaxis (PrEP) is a highly effective method for preventing HIV acquisition and plays a crucial role in the Ending the HIV Epidemic in the US initiative. However, there are various barriers that hinder the access and uptake of PrEP among Latino sexual minority men (SMM) at individual, interpersonal, and cultural levels. While the significance of cultural factors in designing and implementing HIV prevention programs for Latino populations has been consistently emphasized in the literature and prioritized by the Centers for Disease Control and Prevention, few studies have directly integrated these cultural factors into their programs. Our study aimed to investigate the potential influence of siblings in promoting the utilization of PrEP for HIV prevention, an area that has received limited attention. We conducted interviews with 31 pairs of siblings between December 2020 and January 2021, which were held in either English or Spanish and lasted approximately 45–60 min. The data were analyzed using a deductive thematic content analysis approach. The interviews revealed several key themes and categories, including: (1) Sibling support for coming out; (2) Types of support that siblings provide to each other for behavior change; (3) Sibling support for PrEP; and (4) The impact of the study interview on the quality of the sibling relationships. Our findings indicated that siblings were willing to provide support for PrEP in various ways, ranging from emotional support for brothers who may be concerned about potential rejection to practical support such as transportation or financial assistance. These results have significant implications for the design of HIV prevention interventions for Latinos. Incorporating siblings or other extended family members into these interventions can facilitate communication between siblings and their brothers, ultimately encouraging the use of PrEP or similar prevention methods. By considering the unique dynamics and support systems within Latino communities, researchers can develop more effective strategies to promote HIV prevention and support the well-being of Latino SMM.
6G secure quantum communication: a success probability prediction model
Authors: Akbar Muhammad Azeem , Khan Arif Ali , Hyrynsalmi Sami , Khan Javed Ali
Published: March 2024

The emergence of 6G networks initiates significant transformations in the communication technology landscape. Yet, the melding of quantum computing (QC) with 6G networks although promising an array of benefits, particularly in secure communication. Adapting QC into 6G requires a rigorous focus on numerous critical variables. This study aims to identify key variables in secure quantum communication (SQC) in 6G and develop a model for predicting the success probability of 6G-SQC projects. We identified key 6G-SQC variables from existing literature to achieve these objectives and collected training data by conducting a questionnaire survey. We then analyzed these variables using an optimization model, i.e., Genetic Algorithm (GA), with two different prediction methods the Naïve Bayes Classifier (NBC) and Logistic Regression (LR). The results of success probability prediction models indicate that as the 6G-SQC matures, project success probability significantly increases, and costs are notably reduced. Furthermore, the best fitness rankings for each 6G-SQC project variable determined using NBC and LR indicated a strong positive correlation (rs = 0.895). The t-test results (t = 0.752, p = 0.502 > 0.05) show no significant differences between the rankings calculated using both prediction models (NBC and LR). The results reveal that the developed success probability prediction model, based on 15 identified 6G-SQC project variables, highlights the areas where practitioners need to focus more to facilitate the cost-effective and successful implementation of 6G-SQC projects.
Multimodal seismic assessment of infrastructures retrofitted with exoskeletons: insights from the Foggia Airport case study
Authors: Cucuzza Raffaele , Aloisio Angelo , Domaneschi Marco , Nascimbene Roberto
Published: March 2024

Addressing the seismic vulnerability of infrastructures is critical, especially for those built before the introduction of the current seismic regulations. One of the primary challenges lies in retrofitting these buildings without interrupting their functionality. In this context, the use of exoskeletons for seismic retrofitting represents an effective solution. This approach increases the seismic resistance and ensures the continuous operation of the building during retrofitting. This advantage is especially crucial for critical infrastructures, such as airports. Nevertheless, traditional seismic assessment methods based on pushover analyses might not accurately predict the seismic capacity of complex infrastructures dominated by local vibration modes. To bridge this gap, the study proposes refining the multimodal pushover analysis tailored for seismic vulnerability assessments of large infrastructures with exoskeletons characterized by low modal participation ratios. The Foggia Airport case study exemplifies these points and highlights the practical applications of the discussed advancements. The authors compared two force distributions for push-over analysis, addressing the fine-tuning of exoskeletons to maximize their seismic resistance.
Genetic connectivity in the Arizona toad (Anaxyrus microscaphus): implications for conservation of a stream dwelling amphibian in the arid Southwestern United States
Authors: Oyler-McCance Sara J. , Ryan Mason J. , Sullivan Brian K. , Fike Jennifer A. , Cornman Robert S. , Giermakowski J. Tomasz , Zimmerman Shawna J. , Harrow Rachel L. , Hedwall Shaula J. , Hossack Blake R. , Latella Ian M. , Lovich Robert E. , Siefken Sarah , Sigafus Brent H. , Muths Erin
Published: March 2024

The Arizona Toad (Anaxyrus microscaphus) is restricted to riverine corridors and adjacent uplands in the arid southwestern United States. As with numerous amphibians worldwide, populations are declining and face various known or suspected threats, from disease to habitat modification resulting from climate change. The Arizona Toad has been petitioned to be listed under the U.S. Endangered Species Act and was considered “warranted but precluded” citing the need for additional information – particularly regarding natural history (e.g., connectivity and dispersal ability). The objectives of this study were to characterize population structure and genetic diversity across the species’ range. We used reduced-representation genomic sequencing to genotype 3,601 single nucleotide polymorphisms in 99 Arizona Toads from ten drainages across its range. Multiple analytical methods revealed two distinct genetic groups bisected by the Colorado River; one in the northwestern portion of the range in southwestern Utah and eastern Nevada and the other in the southeastern portion of the range in central and eastern Arizona and New Mexico. We also found subtle substructure within both groups, particularly in central Arizona where toads at lower elevations were less connected than those at higher elevations. The northern and southern parts of the Arizona Toad range are not well connected genetically and could be managed as separate units. Further, these data could be used to identify source populations for assisted migration or translocations to support small or potentially declining populations.
External Governance Oversight and the IPO Process: Empirical Evidence from China
Authors: Liu Lewis
Published: March 2024

This study examines the effects of political affiliations as an external governance element on various aspects of the IPO procedure in China. Within China, the significance of political connections is widely recognized as a notable external governance factor capable of exerting influence over both the IPO process. Utilizing a distinctive dataset comprising IPO information from 1856 firms in China spanning the period between 2014 and 2021, the primary objective of this research is to demonstrate that companies with political affiliations have a higher probability of experiencing underpricing, coupled with an increased likelihood of attracting investments from retail investors. Furthermore, these firms tend to attract prestigious underwriters and more underwriter subscriptions, despite having to pay higher floating costs and underwriting fees. Lastly, the study demonstrates that political connections are especially beneficial for firms during market uncertainty, such as the recent pandemic. Political connections act as monitors, reducing information asymmetry and signaling positive aspects of the firms to investors. To strengthen the main conclusions, the study conducts various robustness tests, including PSM and subsample analysis. Overall, the research adds to the existing literature on the crucial role of political connections in promoting IPO practices and reducing information asymmetry through monitoring and support.
On the Radial Growth of Ballistic Aggregation and Other Aggregation Models
Authors: Bosch Tillmann , Winter Steffen
Published: March 2024

For a class of aggregation models on the integer lattice $${{\mathbb {Z}}}^d$$

Z

d

, $$d\ge 2$$

d
≥
2

, in which clusters are formed by particles arriving one after the other and sticking irreversibly where they first hit the cluster, including the classical model of diffusion-limited aggregation (DLA), we study the growth of the clusters. We observe that a method of Kesten used to obtain an almost sure upper bound on the radial growth in the DLA model generalizes to a large class of such models. We use it in particular to prove such a bound for the so-called ballistic model, in which the arriving particles travel along straight lines. Our bound implies that the fractal dimension of ballistic aggregation clusters in $${{\mathbb {Z}}}^2$$

Z

2

is 2, which proves a long standing conjecture in the physics literature.
Improved Lightweight Head Detection Based on GhostNet-SSD
Authors: Hou Hongtao , Guo Mingzhen , Wang Wei , Liu Kuan , Luo Zijiang
Published: March 2024

This abstract proposes an algorithm for human head detection in elevator cabins that addresses the challenges of improving detection accuracy, reducing detection speed, and decreasing the number of parameters. The algorithm is based on GhostNet-SSD and includes several improvements, such as an efficient coordinate attention mechanism to replace the Squeeze-and-Excitation attention mechanism, optimization of auxiliary convolutional layer with large parameter weight, and adjustment of anchor ratio based on the statistical results of human head labeling frame. In addition, data normalization and convolutional fusion methods are used for inference acceleration. The algorithm was tested on JETSON XAVIER NX development board and achieved a new state-of-the-art 97.91% AP at 61FPS, outperforming other detectors with similar inference speed. The effectiveness of each component was validated through careful experimentation.
Multi-dimensional phase portraits of stochastic fractional derivatives for nonlinear dynamical systems with solitary wave formation
Authors: Ansari Ali R. , Jhangeer Adil , Imran Mudassar , Alsubaie A. S. A. , Inc Mustafa
Published: March 2024

This manuscript delves into the examination of the stochastic fractional derivative of Drinfel’d-Sokolov-Wilson equation, a mathematical model applicable in the fields of electromagnetism and fluid mechanics. In our study, the proposed equation is through examined through various viewpoints, encompassing soliton dynamics, bifurcation analysis, chaotic behaviors, and sensitivity analysis. A few dark and bright shaped soliton solutions, including the unperturbed term, are also examined, and the various 2D and 3D solitonic structures are computed using the Tanh-method. It is found that a saddle point bifurcation causes the transition from periodic behavior to quasi-periodic behavior in a sensitive area. Further analysis reveals favorable conditions for the multidimensional bifurcation of dynamic behavioral solutions. Different types of wave solutions are identified in certain solutions by entering numerous values for the parameters, demonstrating the effectiveness and precision of Tanh-methods. A planar dynamical system is then created using the Galilean transformation, with the actual model serving as a starting point. It is observed that a few physical criteria in the discussed equation exhibit more multi-stable properties, as many multi-stability structures are employed by some individuals. Moreover, sensitivity behavior is employed to examine perturbed dynamical systems across diverse initial conditions. The techniques and findings presented in this paper can be extended to investigate a broader spectrum of nonlinear wave phenomena.
Measuring Corruption Risk in Public Procurement over Emergency Periods
Authors: Gnaldi Michela , Del Sarto Simone
Published: March 2024

Times of crisis provide fertile ground for corruption because of looser regulatory frameworks, weaker oversight, and skyrocketing financing levels. Public procurement systems are particularly vulnerable to corruption risks over emergency periods as they are at the frontline of many country responses to crises. In this paper, we propose a curated selection of red flag indicators of corruption risk over crises and discuss a general measurement framework for their computation. The proposed approach exploits the time discontinuity introduced by a crisis and allows us to characterise and differentiate companies and/or contracting authorities with different degree of risk through statistical testing. The suggested framework is intended to accommodate the changing and far-reaching corruption risks induced by crises and mitigate them effectively.
Proxies of Trustworthiness: A Novel Framework to Support the Performance of Trust in Human Health Research
Authors: Harvey Kate , Laurie Graeme
Published: March 2024

Without trust there is no credible human health research (HHR). This article accepts this truism and addresses a crucial question that arises: how can trust continually be promoted in an ever-changing and uncertain HHR environment? The article analyses long-standing mechanisms that are designed to elicit trust—such as consent, anonymization, and transparency—and argues that these are best understood as trust represented by proxies of trustworthiness, i.e., regulatory attempts to convey the trustworthiness of the HHR system and/or its actors. Often, such proxies are assumed to operate as markers that trust exists or, at least, has not been lost. But, since trust can neither be “built” nor “secured,” this is a precarious assumption. Worryingly, there is no existing theoretical account of how to understand and evaluate these proxies of trustworthiness as part of a trusted HHR ecosystem. To remedy this, the paper argues for a radical reimagining of trust and trustworthiness as performative acts that ought to be understood in relation to each other and by reference to the common values at stake. It is shown that proxies of trustworthiness are the operational tools used to perform trustworthiness. It advocates for a values-based approach to understanding the relationship between trust and trustworthiness. This establishes a strong basis for an evaluative framework for proxies of trustworthiness, i.e., to determine how to perform trustworthiness well. Five common proxies in HHR are scrutinized from a values perspective. The contribution is to provide a far-reaching normative and practical framework by which existing and future proxies of trustworthiness can be identified, assessed, maintained, or replaced in rapidly changing HHR regulatory ecosystems where trust itself is crucial to the success of the entire HHR enterprise.
Surrogacy and Adoption: An Empirical Investigation of Public Moral Attitudes
Authors: Baron T. , Svingen E. , Leyva R.
Published: March 2024

Surrogacy and adoption are both family-making measures subject to extensive domestic and international regulation. In this nationally representative survey study (N = 1552), we explore public attitudes to various forms of surrogacy and adoption in the United Kingdom, in response to an early proposal to allow “double donor” surrogacy as part of the ongoing legal reform project. We sought to both gauge public moral support for adoption and surrogacy generally, the effect that prospective parents’ fertility had on this support, and the extent to which the public would find equivalencies between “double donor” surrogacy (DDS) and planned private adoption (PPA) to be morally significant. Our findings indicate that whilst there is broad baseline support for all forms of adoption and surrogacy, this support increases significantly when one or both prospective parents are infertile. These findings also suggest that the language in which a family-making arrangement is characterized has a greater influence on moral support for the arrangement than practical features such as the biological relationship (or absence thereof) between one/both parents and the child.
Pericarditis recurrence is associated with milder electrocardiographic, echocardiographic, and laboratory findings
Authors: Weiss Tal , Itelman Edward , Lotan Dor , Segev Amitai , Freimark Dov , Arad Michael , Wasserstrum Yishay
Published: March 2024

Recurrent pericarditis (RP) complicates approximately 30% of acute pericarditis (AP) cases. We sought to compare the prevalence and severity of objective findings seen in patients with RP. A retrospective single-center study during 2010–2019, including 765 patients diagnosed with AP. Clinical, electrocardiographic, echocardiographic, and laboratory findings were extracted from the local electronic health records. Recurrence during follow-up was documented in 134 patients (17.5%), with a median time to recurrence of 101 (± 59–251) days. The median age was 60 years (IQR 45–72), 68% were male. Most patients were defined as having idiopathic\viral pericarditis (64%). The clinical manifestation during the recurrent event of pericarditis was less prominent or attenuated when compared to the initial event—ECG signs (ST elevation 12% vs. 26%; p = 0.006, Knuckle sign 13% vs. 33%; p < 0.001, ST larger in lead L2 than L3 4% vs. 19%; p < 0.001), pericardial effusion moderate and above (11% vs. 30%; p = 0.02), and inflammatory markers (mean peak CRP levels 66 mg/l vs. 97 mg/l; p < 0.001). Similar results were seen in the subgroup of patients defined as having idiopathic\viral pericarditis. Up to 20% of patients who did not have ECG signs or a significant pericardial effusion in their 1st event demonstrated these findings during the recurrence, though still to a lesser extent compared with those who had these signs in their 1st event. The objective findings of AP are less pronounced during recurrent events. Future studies should focus on the role of advanced biomarkers and imaging in defining true RP events.
Delineation of groundwater prospective zones using multivariate and spatial analysis techniques in Henan Province North China Plain
Authors: Dars Rabia , Ping Jianhua , Mei Xuemei , Shah Shoukat Ali
Published: March 2024

Groundwater is an essential resource that meets all of humanity’s daily water demands, supports industrial development, influences agricultural output, and maintains ecological equilibrium. The objective behind this research is to find groundwater prospective zones and their sustainable development in Henan Province, located in the North China Plain, with the help of analytical hierarchical process (AHP) and frequency ratio (FR) models. Consequently, a groundwater inventory map was created, utilizing 70% of the data for training and 30% for testing purposes. The resulting maps were overlaid with groundwater levels and the locations of wells within the study area. The performance and validation of the models were assessed using the Area Under Curve (AUC) curve, which indicated an accuracy of 70% for the AHP model and 69% for the FR model. The study indicates that areas with suitable gradients and rainfall patterns generally have high groundwater prospective zonation (GWPZ), i.e., Zhumadian and Nanyang (ZN). However, AHP demonstrated a higher predictive capability in comparison to FR the broader context. Whereas GIS-RS methodology aligns with existing wells and field data that validate it in range of good and excellent. In conclusion, this study provides valuable insights for effective groundwater exploration and sustainable water supply planning in Henan Province.
Experimental investigation to understand the effect of fracturing fluid on the geomechanical behavior of mowry shale
Authors: Dabbaghi Ehsan , Ng Kam , Kou Zuhao , Copeland Grant , Alvarado Vladimir
Published: March 2024

Hydraulic fracturing of shale reservoirs is one of the important technologies in the oil and gas industry. To ensure the safe operation of oil and gas recovery, it is important to study the shale-fluid interactions on the geomechanical behavior of shale. This study investigated the effect of fracturing fluid treatment on the mechanical and elastic properties of the Mowry Shale formation, Wyoming, USA. Cylindrical Mowry Shale specimens with a diameter of 12.5 mm collected from the United States Geological Survey (USGS) and School of Energy Resources (SER) of the University of Wyoming were treated with brine and brine + stimulation fluid for one month each at pressures of 9 and 11.7 MPa and temperatures of 96 and 66 °C, respectively. Triaxial compression experiments were conducted on the specimens. Results showed that all Mowry Shale specimens experienced an increase in maximum volumetric strain with the increase in effective confining pressure (Pd). Regardless of aging fluids, the maximum deviatoric stress (Δσd) of most Mowry Shale specimens increases with the increase in Pd. At a lower Pd, the USGS specimen aged with brine and stimulation fluid exhibits higher maximum Δσd than those aged with brine only. However, at a higher Pd, the USGS specimen aged with brine exhibits a higher maximum Δσd. SER specimens aged with brine and stimulation fluid exhibit higher maximum Δσd values than those aged with brine for all three Pd values. Regardless of the aging fluids, most USGS specimens experience a brittle failure mode, while SER specimens aged with brine and stimulation fluid experienced a more ductile behavior.
Covid-19 pandemic lockdowns and distance education in Australia: Positive experiences of migrant/refugee parents and future directions
Authors: Zaini Amin , Molla Tebeje , Shokouhi Hossein , Arber Ruth
Published: March 2024

This paper presents findings from a study investigating the engagement of migrant and refugee parents in supporting the distance education of their children amidst the Covid-19 lockdowns in Australia. While existing research has extensively addressed challenges within online education during the Covid-19 pandemic, there is a dearth of research examining the opportunities afforded to migrant and refugee parents. In pursuit of this, 20 migrant and refugee parents participated in individual interviews as part of the data collection process. The transcribed data underwent thematic analysis, drawing on the frameworks proposed by, to scrutinise how the imposed structure of lockdowns has informed parents’ educational and social opportunities. The findings suggest that parents’ opportunities encompass improving their English language skills, helping their children to develop their mother tongue skills, familiarising themselves with school subjects, understanding how the education system works in Australia and strengthening their knowledge about improving their relationships with their children. The paper also discusses how the education system can prepare parents to educate their children more effectively in the future, while their education can promise a more inclusive education system.
A new commutativity property of exceptional orthogonal polynomials
Authors: Castro M. M. , Grünbaum F. A.
Published: March 2024

We exhibit three examples showing that the “time-and-band limiting” commutative property found and exploited by D. Slepian, H. Landau and H. Pollak at Bell Labs in the 1960s, and independently by M. Mehta and later by C. Tracy and H. Widom in Random matrix theory, holds for exceptional orthogonal polynomials. The property in question is the existence of local operators with simple spectrum that commute with naturally appearing global ones. We illustrate numerically the advantage of having such a local operator.
PD-L1 expression in keratinocyte and infiltration of CD4 + T lymphocyte can predict a severe type of erythema multiforme major induced by the anti-PD-1 antibody, pembrolizumab
Authors: Kadoi Ryohei , Yoshida Taichi , Noto Mai , Toyoshima Aya , Fujii Sino , Fukuda Koji , Shimazu Kazuhiro , Taguchi Daiki , Shinozaki Hanae , Kodama Naoki , Kono Michihiro , Nanjyo Hiroshi , Shibata Hiroyuki
Published: March 2024

Skin toxicity is the most common adverse event of treatment with immune check point inhibitors. Among them, erythema multiforme is a rare occurrence with a frequency of 4%, with most of the cases developing grade 1/2 disease. We experienced high grade erythema multiforme major developing with pembrolizumab treatment for anal canal cancer with extensive skin metastases. Steroid ointment was ineffective, and the skin lesions with blisters expanded to > 45% of the body surface area. The patient was at risk for symptom aggravation, and a pulse therapy with methylprednisolone and increasing the dose of oral prednisolone (1 mg/kg) were started. The skin lesions improved in 1.8 months. Unless urgent and appropriate treatments such as high dose steroid administration were conducted, the skin toxicities could not be controlled. The presence of CD4+ T cells and PD-L1+ keratinocytes in the skin biopsy might be a predictive marker of erythema multiforme major resistant to standard steroid treatment.
A wind semi-sub platform with hinged floats for omnidirectional swell wave energy conversion
Authors: Stansby Peter , Li Gangqiang
Published: March 2024

The capacity of wind turbines on offshore wind platforms is presently much greater than that for wave energy conversion. However, wind availability with speed greater than 5 m/s, just above cut in, is typically 30–40% requiring storage to provide uniformity of supply, but this may be improved by adding swell wave energy conversion with typical availability of 90%. A hybrid platform is considered with three effectively rigid cylindrical floats connected by beams at right angles to support a wind turbine with its base on the central float, and two wave energy floats, opposite the wind floats, with beams at 90° and hinges with dampers for mechanical energy absorption on the central float. With swell periods over 10 s, pitch resonance may be achieved with the fore and aft floats about half a wavelength apart with anti-phase forcing causing a moment on hinges above water level. The NREL 5 MW wind turbine is incorporated and average swell wave power absorption in a typical significant wave height of 2 m is over 200 kW. The analysis is by time domain linear diffraction–radiation modelling validated for other multi-float configurations. Significant wave energy conversion is omnidirectional over a wide range of heading angles. An added benefit is that in larger waves associated with strong winds, when the wave energy conversion would be disengaged, the wave float rotation on free hinges reduces the hub accelerations below that for rigid floats, enabling a longer time for wind power generation.
Process engineering of demineralisation of moderate to high ash Indian coals through NaOH-HCl leaching and HF leaching
Authors: Dhawan Heena , Sharma D. K.
Published: March 2024

Chemical leaching of coals would be required to produce cleaner coals for some special applications where physical beneficiation may not be effective enough. This would also help in recovering Li and rare earth metals besides in the sequestration of CO2. About 20 Indian coals having complexly distributed moderate to high ash contents were sequentially treated with various alkali–acid such as NaOH-HCl, HF, HCl, HCl-HF, and NaOH-HCl-HF leaching. This aimed to establish and design the best stepwise sequential process for the highest degree of demineralisation through a chemical leaching process. Kinetics and process intensification studies were carried out. More than 80% demineralisation of Madhaipur and Neemcha coals was observed using the best sequential treatment designed presently. The repeated stepwise treatment of the alkali and the acid was also studied, which was found to significantly enhance the degree of demineralisation of coals. The integrated process of alkali–acid leaching followed by solvent extraction (Organo-refining) and vice versa of the treated coal was also studied for producing cleaner coals.
Dynamic Neural Assimilation: a deep learning and data assimilation model for air quality predictions
Authors: Tučkus Nikodemas , D’Elia Ilaria , Chinnici Marta , Arcucci Rossella
Published: March 2024

Ambient air pollution is known to be a serious issue that has an impact on human health and the environment. Assessing air quality is of the utmost importance to protect human health and the environment. Different tools are available, from monitoring stations to complex models. These systems are capable of accurately predicting air quality levels, but they are often computationally very expensive which makes them poorly efficient. In this paper, we developed a novel model called Dynamic Neural Assimilation (DyNA) integrating Recurrent Neural Networks and Data Assimilation methods to derive a physics-informed system capable of accurately forecasting air pollution tendencies and investigating the relationship with industrial statistics. DyNA is trained in historical data and is fine-tuned as soon as new data comes available. We trained and tested the system on real data provided by the air quality monitoring stations located in Italy from the European Environment Agency and simulated results derived from the air quality modelling system Atmospheric Modelling System-Model to support the International Negotiation on atmospheric pollution on a National Italian level. We analysed air pollution data in Italy from the years 2003–2010 and studied its correlation with nearby industries in some regions where monitoring sensors were available.
Digital transformation of education, the limitations and prospects of introducing the fourth industrial revolution asynchronous online learning in emerging markets
Authors: Mhlanga David
Published: March 2024

This study aims to evaluate the opportunities and limitations of switching from conventional, face-to-face education to online, asynchronous education made possible by the Fourth Industrial Revolution’s technology. This transition has been considerably expedited in several nations by the COVID-19 epidemic. Desktop analysis was used to conduct the research, along with non-intrusive approaches, including documentary analysis and conceptual analysis, and reliable sources were consulted. The research findings identified several barriers to the broad implementation of the Fourth Industrial Revolution asynchronous online education in emerging nations to address COVID-19’s effects and keep the needs of the revolution. Among these challenges are poverty and inequality, power shortages, a lack of knowledge, restricted access to technology and the internet in rural areas, and a clear national policy. Despite these difficulties, institutions can increase access to top-notch education by establishing themselves as centres of excellence and innovation through online learning. Therefore, for the infrastructure required to enable the widespread use of asynchronous education, the education sector in emerging nations requires additional resources. Therefore, the study recommends that educational institutions in emerging markets prioritize investments in digital infrastructure and training. This will enable a smoother transition to asynchronous online education. Additionally, policymakers should develop comprehensive strategies that address the digital divide, ensuring equitable access to technology and the Internet, especially in rural and underserved areas. Collaboration between governments, educational institutions, and private sectors is essential for the effective implementation of 4IR technologies in education.
Universal approximation property of stochastic configuration networks for time series
Authors: Zhang Jin-Xi , Zhao Hangyi , Zhang Xuefeng
Published: March 2024

For the purpose of processing sequential data, such as time series, and addressing the challenge of manually tuning the architecture of traditional recurrent neural networks (RNNs), this paper introduces a novel approach-the Recurrent Stochastic Configuration Network (RSCN). This network is constructed based on the random incremental algorithm of stochastic configuration networks. Leveraging the foundational structure of recurrent neural networks, our learning model commences with a modest-scale recurrent neural network featuring a single hidden layer and a solitary hidden node. Subsequently, the node parameters of the hidden layer undergo incremental augmentation through a random configuration process, with corresponding weights assigned structurally. This iterative expansion continues until the network satisfies predefined termination criteria. Noteworthy is the adaptability of this algorithm to handle time series data, exhibiting superior performance compared to traditional recurrent neural networks with similar architectures. The experimental results presented in this paper underscore the efficacy of the proposed RSCN for sequence data processing, showcasing its advantages over conventional recurrent neural networks in the context of the performed experiments.