bluuebunny/crossref_metadata_2025 huggingface dataset:
Captodative Effect Facilitates the Excitation in Diboron Molecule (CAAC)2B2(SH)2
Authors: Zhang Huaiyu , Wang Yating , Lu Qingrui , Song Jinshuai , Duan Yandong , Zeng Yanli , Mo Yirong
Published: January 2023

Given the extraordinary versatility in chemical reactions and applications, boron compounds have gained increasing attentions in the past two decades. One of the remarkable advances is the unprecedented preparation of unsaturated boron species. Notably, Braunschweig et al. found that the cyclic (alkyl)(amino) carbenes (CAACs) stabilized diboron molecules (CAAC)2B2(SR)2 host unpaired electrons and exist in the 90°‐twisted diradical form, while other analogues, such as N‐heterocyclic carbenes (NHCs), stabilized diboron molecules prefer a conventional B=B double bond. Since previous studies recognized the differences in the steric effect between CAAC and NHC carbenes, here we focused on the role of thiol substituents in (CAAC)2B2(SR)2 by gradually localizing involved electrons. The co‐planarity of the thiol groups and the consequent captodative effect were found to be the culprit for the 90°‐twisted diradical form of (CAAC)2B2(SR)2. Computational analyses identified two forces contributing to the π electron movements. One is the “push” effect of lone pairs on the sulfur atoms which boosts the π electron delocalization between the BB center and CAACs. The other is the π electron delocalization within each (CAAC)B(SR) fragment where the pull effect originates from the π electron withdrawal by CAACs. There are two such independent and orthogonal push‐pull channels which function mainly in individual (CAAC)B(SR) fragments. This enhanced π push‐pull effect in the triplet state facilitates the electronic excitation in (CAAC)2B2(SR)2 by reducing the singlet‐triplet gap.
Volatility analysis for the GARCH‐Itô model with option data
Authors: Yuan Huiling , Zhou Yong , Zhang Zhiyuan , Cui Xiangyu
Published: January 2023

Low‐frequency historical data, high‐frequency historical data, and option data are three primary sources that can be used to forecast an underlying security's volatility. In this article, we propose an explicit model integrating the three information sources. Instead of directly using option price data, we extract option‐implied volatility from option data and estimate its dynamics. We provide joint quasimaximum likelihood estimators for the parameters and establish their asymptotic properties. Real data examples demonstrate that the proposed model has better out‐of‐sample volatility forecasting performance than other popular volatility models.
Inducement of population sparsity
Authors: Battey Heather S.
Published: January 2023

The pioneering work on parameter orthogonalization by Cox and Reid is presented as an inducement of abstract population‐level sparsity. This is taken as a unifying theme for this article, in which sparsity‐inducing parameterizations or data transformations are sought. Three recent examples are framed in this light: sparse parameterizations of covariance models, the construction of factorizable transformations for the elimination of nuisance parameters, and inference in high‐dimensional regression. Strategies for the problem of exact or approximate sparsity inducement appear to be context‐specific and may entail, for instance, solving one or more partial differential equations or specifying a parameterized path through transformation or parameterization space. Open problems are emphasized.
PROTOCOL: A mixed methods systematic review on the effects of arts interventions for at‐risk and offending children and young people on behavioural, psychosocial, cognitive and offending outcomes
Authors: Mansfield Louise , Daykin Norma , O'Connell Neil E. , Bailey Daniel , Forde Louise , Smith Robyn , Gifford Jake
Published: January 2023

This is the protocol for a Campbell systematic review. The proposed systematic review question is: What is the effectiveness of arts interventions for at‐risk and offending children and young people (8‐25 years)? There are three objectives: (1) To evaluate evidence on the effectiveness and impact of arts interventions on keeping children safe from involvement in violence and crime; (2) To synthesise evidence on factors impacting the implementation of arts interventions, and barriers and facilitators to participation and achievement of intended outcomes; (3) To develop a theory‐of‐change approach to ensure the development of an evidence‐led framework of the processes by which arts interventions might work in preventing offending behaviours.
Assessment of the Present State and Future Fate of River Saraswati, India: Water Quality Indices and Forecast Models as Diagnostic and Management Tools
Authors: Pramanik Sasanka , Biswas Jayanta Kumar , Kaviraj Anilava , Saha Subrata
Published: January 2023

Water quality assessment is key to the conservation and management of rivers. River Saraswati, a distributary of the river Ganga, serves as a lifeline to many villages in the district Hooghly in West Bengal, India. As the river is gradually dying due to diverse man‐made pollution, ten water quality parameters in two sampling spots (PR‐1 and PR‐2) in the river are monitored month‐wise from March 2017 to February 2020,  and these are compared with those from a reference pond. The water quality index (WQI) is determined for the two riverine spots and the reference pond based on the Canadian Council of Ministers of Environment WQI (CCMEWQI) and weighted arithmetic WQI, respectively. In addition to actual observations, three different forecasting methods, exponential smoothing, autoregressive integrated moving average, and artificial neural network, are used to predict WQI for the next two years. This study indicates that free CO2, dissolved oxygen, and turbidity are the key parameters to evaluate this river's anthropogenic stress and health. The actual and forecasted results reflect the precipitous degradation of CCMEWQI in PR‐2. Therefore, the immediate intervention of all stakeholders is required to adopt an integrated and comprehensive river management plan to save the river from utter obliteration.
An unusual carbon cycle budget of a small stream in a mountain silicate terrain: The case of the Gravona river (Corsica)
Authors: Schubert Christina M. , Juhlke Tobias R. , Huneau Frederic , Garel Emilie , Santoni Sebastien , Barth Johannes A. C. , van Geldern Robert
Published: January 2023

The current research of carbon cycling in inland waters lacks a sound knowledge of carbon outgassing from small streams. As a consequence, these compartments of the terrestrial water cycle might still be seriously underrepresented in estimates of global carbon transfer budgets from land surfaces. This study investigated carbon sources and sinks of a mountain river in a silicate catchment. For this purpose, the high‐relief Gravona river, in the western part of the island of Corsica (France) in the Western Mediterranean, was investigated for field parameters, dissolved inorganic carbon (DIC) and its stable carbon isotopes (δ13CDIC). The source region was characterized by low DIC contents and high δ13CDIC values that decreased further downstream due to increasing soil respiration. Associated increasing DIC concentrations and elevated seasonality in the lower river section also indicated more respiration and subsequent DIC‐input by weathering. The aqueous partial pressure (pCO2(aq)) was lowest at the source of the Gravona river and samples from the cold season even showed undersaturation that led to uptake of atmospheric CO2. Further downstream, the seasonality of pCO2(aq) increased and was particularly pronounced near the river mouth where CO2 degassing took place. Average DIC flux along the river was 0.129 Gg C year−1 and was almost equal to CO2 degassing from the river surface with 0.128 Gg C year−1. Our study showed that on an annual basis the river is an overall weak to medium source of CO2 to the atmosphere even though headwater parts of the river seasonally act as CO2 sinks.
Simplification of earthquake induced vehicle bridge interaction contact simulation for urban viaducts
Authors: Shi Wen , Xu Yan , Lin Guocai
Published: January 2023

The possibility of motor vehicles parking on or slowly driving on the urban viaducts during earthquakes has been largely increased to a non‐negligible level due to the traffic jams in most of modern cities. As a fact of the earthquake disaster investigation, detachment and collision between motor vehicles and the bridge deck endangered the safety of both drivers and the bridge structure itself. In recent studies, Hertz model was therefore proposed to simulate this nonlinear contact and collision behavior with the complexity and inefficient in solving the kinetic equilibrium equations of earthquake induced vehicle bridge interaction (VBI) system, and hence hindered the comprehensive numerical analysis. In this paper, two linearized contact models, that is, a piecewise linear tangent model derived by Taylor series expansion of the Hertz model and a piecewise secant model derived by least square method of error minimization of the Hertz model, are both proposed to simplify the simulation of the vehicle bridge contact behavior for earthquake induced VBI system. A total of 3*2041VBI parametric systems considering different vehicle masses, frequencies and ground motions, are calculated and statistically analyzed to compare the accuracy of each model with nonlinear Hertz model. Statistical analysis result shows that the vertical contact force calculated by two simplified models are acceptable in earthquake induced VBI analysis with less than 10% error in more than 99% analysis cases. However, the piecewise tangent model is more accurate than the piecewise secant model when the vehicle and bridge stay attached. If detachment occurs, the secant model would have higher accuracy in predicting the initial peak ground acceleration (PGA) of vehicle detachment from the bridge. Based on this result, a formula using the piecewise secant model for predicting the initial detachment PGA of vehicles from the bridge deck is proposed to simplify the increment dynamic analysis (IDA) method in further earthquake induced VBI analysis.
Quantifying and analysing rock trait distributions of rocky fault scarps using deep learning
Authors: Chen Zhiang , Scott Chelsea , Keating Devin , Clarke Amanda , Das Jnaneshwar , Arrowsmith Ramon
Published: January 2023

We apply a deep learning model to segment and identify rock characteristics based on a Structure‐from‐Motion orthomap and digital elevation model of a rocky fault scarp in the Volcanic Tablelands, Eastern California, USA. By post‐processing the deep learning results, we build a semantic rock map and analyse the rock trait distributions. The resulting semantic map contains nearly 230 000 rocks with effective diameters ranging from 2 to 250 cm. Rock trait distributions provide a new perspective on rocky fault scarp development and extend past research on scarp geometry including slope, height and length. Heatmaps indicate rock size spatial distributions on the fault scarp and surrounding topographic flats. Median grain size changes perpendicular to the fault scarp trace, with the largest rocks on the downslope proximal to the scarp footwall. Correlation analyses illustrate the relationship between rock trait statistics and fault scarp geomorphology. Local fault scarp height correlates with median grain size (
 = 0.6), the mean grain size of the largest rocks (
 = 0.8) and the ratio of the number of small to large rocks (
 = 0.4). The positive correlation (
 = 0.8) between local fault scarp height and standard deviation of grain size suggests that rocks on a higher fault scarp are less well sorted. The correlation analysis between fault scarp height and rock orientation statistics supports a particle transportation model in which locally higher fault scarps have relatively more rocks with long axes parallel to fault scarp trace because rocks have a larger distance to roll and orient the long axes. Our work demonstrates a data‐driven approach to geomorphology based on rock trait distributions, promising a greater understanding of fault scarp formation and tectonic activity, as well as many other applications for which granulometry is an indicator of process.
Mechanism of palmitoleic acid oxidation into volatile compounds during heating
Authors: Gao Pengxun , Bao Yuxiang , Wang Shuo , Lei Liming , Wang Binchen , Xiao Lin , Cheng Kunya , Wang Yian , Zhang Sufang , Dong Liang
Published: January 2023

To better understand the mechanism of palmitoleic acid oxidation into volatile compounds during heating, volatile profiling was investigated by combining thermal‐desorption cryo‐trapping with gas chromatography–mass spectrometry. A total of 49 volatile compounds were detected and identified during this process, including aldehydes (18), ketones (14), alcohols (9), furans (3) and acids and ester (5). The forming temperature of each volatile was determined. Most of the volatiles with short carbon chains were generated at low temperatures, while those with long carbon chains were generated at high temperatures. Results of principal component analysis show that nearly all of the identified volatiles were considered as the characteristic ones of the high temperature points. Meanwhile, the oxidative products of the C7–C11 saturated and unsaturated aldehydes were also detected and identified during heating to intensively investigate the oxidative mechanism of palmitoleic acid during heating. Results demonstrated that only the C10 saturated and unsaturated aldehydes could continue to be oxidized during heating. Therefore, the oxidation reactions above the secondary level of lipids mainly occurred in the C10 saturated and unsaturated aldehydes.
Dawn into Mid‐Afternoon: New Era in Energy Services
Authors: DeCotis Paul A.
Published: January 2023

The task of transforming world economies to clean energy and decarbonizing energy infrastructure is monumental. It is difficult to even envision given the state of the world's reliance on fossil fuels and the work needed to meet clean energy and environmental goals. Public and private sector funding in the United States—available through the Infrastructure and Investment Jobs Act of 2021 (IIJA), the Inflation Reduction Act of 2022 (IRA), and the CHIPS and Science Act of 2022 (CHIPS)—provides opportunities for individuals, developers, energy service providers (including utilities), and manufacturers to partner with government to transform the energy economy in the United States. Partnerships are vital if there is to be any chance of decarbonizing the world's economies and the United States can lead by example. In this vein, funding for basic and applied research and development is crucial for bringing new technologies and practices to market in support of ambitious clean energy and climate goals.
Stimulation‐induced entrainment of hippocampal network activity: Identifying optimal input frequencies
Authors: Johnson Teryn D. , Keefe Katherine R. , Rangel Lara M.
Published: January 2023

The hippocampus contains rich oscillatory activity, with continuous ebbs and flows of rhythmic currents that constrain its ability to integrate inputs. During associative learning, the hippocampus must integrate inputs from a range of sources carrying information about events and the contexts in which they occur. Under these circumstances, temporal coordination of activity between sender and receiver is likely essential for successful communication. Previously, it has been shown that the coordination of rhythmic activity between the lateral entorhinal cortex (LEC) and the CA1 region of the hippocampus is tightly correlated with the onset of learning in an associative learning task. We aimed to examine whether rhythmic inputs from the LEC in specific frequency ranges were sufficient to enhance the temporal coordination of activity in downstream CA1. In urethane‐anesthetized rats, we applied extracellular low‐intensity alternating current stimulation across the length of the LEC. Using this method, we aimed to phase‐bias ongoing neuronal activity in LEC at a range of different frequencies (from 1.25 to 55 Hz). Rhythmic stimulation of LEC at both 35 and 50 Hz increased the proportion of CA1 neurons significantly entrained to the phase of the applied stimulation current. A subset of stimulation frequencies modified CA1 spiking relationships to the phase of local ongoing CA1 oscillations, with each stimulation frequency exerting a unique influence upon downstream CA1, often in frequency ranges outside the target stimulation frequency. These results suggest there are optimal frequencies for LEC–CA1 communication, and that different profiles of LEC rhythms likely have distinct outcomes upon CA1 processing.
Fulfilling the promise of applied developmental science: Is it time to reconsider our approach?
Authors: Holochwost Steven J. , Mills‐Koonce W. Roger , Brown Eleanor D.
Published: January 2023

The promise of applied developmental science is that we can use scientific methods to promote positive human development and improve the lives of children and families. However, the present political environment in the United States makes the creation of research‐informed federal policy difficult, even when the evidence supporting a given policy is unequivocal. In this essay, we hope to begin a conversation about how we, as applied developmental scientists, may modify our approach in order to best fulfill the promise of applied developmental science. To begin this conversation, we discuss the potential for establishing long‐term partnerships with smaller entities, including state and municipal governments and non‐governmental organizations to narrow the gap between what we know about children and families and the policies and programs that impact them. This ‘bottom‐up’ approach has a long lineage in applied developmental science, and is currently enjoying a renaissance through the burgeoning interest in researcher‐practitioner partnerships. Whether implicitly or explicitly, these partnerships often incorporate a systems perspective on children's development; here, we review why embracing a systems perspective may increase the likelihood of crafting policies and programs that can improve the lives of children and families.
Biodegradable and antithrombogenic chitosan/elastin blended polyurethane electrospun membrane for vascular tissue integration
Authors: Selvaras Thiviya , Alshamrani Somyah Ali , Gopal Rathosivan , Jaganathan Saravana Kumar , Sivalingam Sivakumar , Kadiman Suhaini , Saidin Syafiqah
Published: January 2023

Current commercialized vascular membranes to treat coronary heart disease (CHD) such as Dacron and expanded polytetrafluoroethylene (ePTFE) have been associated with biodegradable and thrombogenic issues that limit tissue integration. In this study, biodegradable vascular membranes were fabricated in a structure of electrospun nanofibers composed of polyurethane (PU), chitosan (CS) and elastin (0.5%, 1.0%, and 1.5%). The physicochemical properties of the membranes were analyzed, followed by the conduction of several test analyses. The blending of CS and elastin has increased the fiber diameter, pore size and porosity percentage with the appearance of identical chemical groups. The wettability of PU membranes was enhanced up to 39.6%, demonstrating higher degradation following the incorporation of both natural polymers. The PU/CS/elastin electrospun membranes exhibited a controlled release of CS (Higuchi and first‐order mechanisms) and elastin (Higuchi and Korsmeyer‐Peppas mechanisms). Delayed blood clotting time was observed through both activated partial thromboplastin time (APTT) and partial thromboplastin time (PT) analyses where significantly delay of 26.8% APTT was recorded on the PU membranes blended with CS and elastin, in comparison with the PU membranes, supporting the membrane's antithrombogenic properties. Besides, these membranes produced a minimum of 2.6 ± 0.1 low hemolytic percentage, projecting its hemocompatibility to be used as vascular membrane.
Bmi‐1 Overexpression Improves Sarcopenia Induced by 1,25(OH)2D3 Deficiency and Downregulates GATA4‐Dependent Rela Transcription
Authors: Wang Qiuyi , Zhao Jingyu , Chen Haiyun , Zhou Jiawen , Chen Ao , Zhang Jin'ge , Wang Yue , Mao Zhiyuan , Wang Jiachen , Qiu Xuehan , Chen Yutong , Wang Rong , Zhang Yongjie , Miao Dengshun , Jin Jianliang
Published: January 2023

Sarcopenia increases with age, and an underlying mechanism needs to be determined to help with designing more effective treatments. This study aimed to determine whether 1,25(OH)2D3 deficiency could cause cellular senescence and a senescence‐associated secretory phenotype (SASP) in skeletal muscle cells to induce sarcopenia, whether GATA4 could be upregulated by 1,25(OH)2D3 deficiency to promote SASP, and whether Bmi‐1 reduces the expression of GATA4 and GATA4‐dependent SASP induced by 1,25(OH)2D3 deficiency in skeletal muscle cells. Bioinformatics analyses with RNA sequencing data in skeletal muscle from physiologically aged and young mice were conducted. Skeletal muscles from 2‐month‐old young and 2‐year‐old physiologically aged wild‐type (WT) mice and 8‐week‐old WT, Bmi‐1 mesenchymal transgene (Bmi‐1Tg), Cyp27b1 homozygous (Cyp27b1−/−), and Bmi‐1TgCyp27b1−/− mice were observed for grip strength, cell senescence, DNA damage, and NF‐κB‐mediated SASP signaling of skeletal muscle. We found that muscle‐derived Bmi‐1 and vitamin D receptor (VDR) decreased with physiological aging, and DNA damage and GATA4‐dependent SASP activation led to sarcopenia. Furthermore, 1,25(OH)2D3 deficiency promoted DNA damage‐induced GATA4 accumulation in muscles. GATA4 upregulated Rela at the region from −1448 to −1412 bp at the transcriptional level to cause NF‐κB‐dependent SASP for aggravating cell senescence and muscular dysfunction and sarcopenia. Bmi‐1 overexpression promoted the ubiquitination and degradation of GATA4 by binding RING1B, which prevented cell senescence, SASP, and dysfunctional muscle, and improved sarcopenia induced by 1,25(OH)2D3 deficiency. Thus, Bmi‐1 overexpression improves sarcopenia induced by 1,25(OH)2D3 deficiency, downregulates GATA4‐dependent Rela transcription, and sequentially inhibits GATA4‐dependent SASP in muscle cells. Therefore, Bmi‐1 overexpression could be used for translational gene therapy for the ubiquitination of GATA4 and prevention of sarcopenia. © 2023 American Society for Bone and Mineral Research (ASBMR).
Brand extension failure and parent brand penalty: The role of implicit theories
Authors: Jain Shailendra Pratap , Mathur Pragya , Isaac Mathew S. , Mao Huifang , Maheswaran Durairaj
Published: January 2023

Given that the vast majority of brand extensions fail, it is important to understand how extension failure influences consumer judgments of the parent brand that launched the extension. In the brand extension literature, there is a paucity of research on the role of consumer characteristics in influencing response to such failures. To fill this gap, the present research examines the impact of consumers' implicit theory orientation—their perspective on whether personality traits are malleable versus fixed—on the severity of negative feedback effects following extension failure. Seven studies show that entity theorists, who believe in the fixedness of personality traits, penalize parent brands more than incremental theorists, who endorse trait malleability. This brand penalty effect arises because as compared to incremental theorists, entity theorists are motivated to view brands as a cohesive group and therefore equate extension failure with the diminishment of the overarching parent brand. This effect is more likely when brand cohesiveness is low or ambiguous, but it is less likely when brand cohesiveness is high. Furthermore, while entity theorists are more likely to reduce brand evaluations after extension failure, the two groups do not differ in parent brand evaluations after extension success.
Machine learning‐driven blood transcriptome‐based discovery of SARS‐CoV‐2 specific severity biomarkers
Authors: Krishnamoorthy Pandikannan , Raj Athira S , Kumar Himanshu
Published: January 2023

The Coronavirus disease 2019 (COVID‐19) pandemic, caused by rapidly evolving variants of severe acute respiratory syndrome coronavirus (SARS‐CoV‐2), continues to be a global health threat. SARS‐CoV‐2 infection symptoms often intersect with other nonsevere respiratory infections, making early diagnosis challenging. There is an urgent need for early diagnostic and prognostic biomarkers to predict severity and reduce mortality when a sudden outbreak occurs. This study implemented a novel approach of integrating bioinformatics and machine learning algorithms over publicly available clinical COVID‐19 transcriptome data sets. The robust 7‐gene biomarker identified through this analysis can not only discriminate SARS‐CoV‐2 associated acute respiratory illness (ARI) from other types of ARIs but also can discriminate severe COVID‐19 patients from nonsevere COVID‐19 patients. Validation of the 7‐gene biomarker in an independent blood transcriptome data set of longitudinal analysis of COVID‐19 patients across various stages of the disease showed that the dysregulation of the identified biomarkers during severe disease is restored during recovery, showing their prognostic potential. The blood biomarkers identified in this study can serve as potential diagnostic candidates and help reduce COVID‐19‐associated mortality.
Persistent hypersomnia following repetitive mild experimental traumatic brain injury: Roles of chronic stress and sex differences
Authors: Portillo Edwin , Zi Xiaomei , Kim Yeonho , Tucker Laura B. , Fu Amanda , Miller Lauren A. , Valenzuela Krystal S. , Sullivan Genevieve M. , Gauff Amina K. , Yu Fengshan , Radomski Kryslaine L. , McCabe Joseph T. , Armstrong Regina C.
Published: January 2023

Traumatic brain injury (TBI) is often more complicated than a single head injury. An extreme example of this point may be military service members who experience a spectrum of exposures over a prolonged period under stressful conditions. Understanding the effects of complex exposures can inform evaluation and care to prevent persistent symptoms. We designed a longitudinal series of non‐invasive procedures in adult mice to evaluate the effects of prolonged mild stress and head injury exposures. We assessed anxiety, depression, and sleep–wake dysfunction as symptoms that impact long‐term outcomes after mild TBI. Unpredictable chronic mild stress (UCMS) was generated from a varied sequence of environmental stressors distributed within each of 21 days. Subsequently, mice received a mild blast combined with closed‐head mild TBI on 5 days at 24‐h intervals. In males and females, UCMS induced anxiety without depressive behavior. A major finding was reproducible sleep–wake dysfunction through 6‐ to 12‐month time points in male mice that received UCMS with repetitive blast plus TBI events, or surprisingly after just UCMS alone. Specifically, male mice exhibited hypersomnia with increased sleep during the active/dark phase and fragmentation of longer wake bouts. Sleep–wake dysfunction was not found with TBI events alone, and hypersomnia was not found in females under any conditions. These results identify prolonged stress and sex differences as important considerations for sleep–wake dysfunction. Furthermore, this reproducible hypersomnia with impaired wakefulness is similar to the excessive daytime sleepiness reported in patients, including patients with TBI, which warrants further clinical screening, care, and treatment development.
Synthesizing cross‐design evidence and cross‐format data using network meta‐regression
Authors: Hamza Tasnim , Chalkou Konstantina , Pellegrini Fabio , Kuhle Jens , Benkert Pascal , Lorscheider Johannes , Zecca Chiara , Iglesias‐Urrutia Cynthia P. , Manca Andrea , Furukawa Toshi A. , Cipriani Andrea , Salanti Georgia
Published: January 2023

In network meta‐analysis (NMA), we synthesize all relevant evidence about health outcomes with competing treatments. The evidence may come from randomized clinical trials (RCT) or non‐randomized studies (NRS) as individual participant data (IPD) or as aggregate data (AD). We present a suite of Bayesian NMA and network meta‐regression (NMR) models allowing for cross‐design and cross‐format synthesis. The models integrate a three‐level hierarchical model for synthesizing IPD and AD into four approaches. The four approaches account for differences in the design and risk of bias (RoB) in the RCT and NRS evidence. These four approaches variously ignoring differences in RoB, using NRS to construct penalized treatment effect priors and bias‐adjustment models that control the contribution of information from high RoB studies in two different ways. We illustrate the methods in a network of three pharmacological interventions and placebo for patients with relapsing–remitting multiple sclerosis. The estimated relative treatment effects do not change much when we accounted for differences in design and RoB. Conducting network meta‐regression showed that intervention efficacy decreases with increasing participant age. We also re‐analysed a network of 431 RCT comparing 21 antidepressants, and we did not observe material changes in intervention efficacy when adjusting for studies' high RoB. We re‐analysed both case studies accounting for different study RoB. In summary, the described suite of NMA/NMR models enables the inclusion of all relevant evidence while incorporating information on the within‐study bias in both observational and experimental data and enabling estimation of individualized treatment effects through the inclusion of participant characteristics.
Frightened or familiarised? Permanent residents' and second‐home owners' risk perceptions of extreme weather events
Authors: Czarnecki Adam , Dacko Aneta , Dacko Mariusz , Skowera Barbara
Published: January 2023

The number and severity of extreme weather events have been increasing globally. Given the vulnerabilities of second homes to natural disasters, it is important to learn how their owners consider the related risks. This paper investigates the extreme weather‐event risk perceptions and their preconditions between second‐home owners and local people in the Little Beskid mountains in Poland. The results show that, despite significant differences in social, demographic and presence–absence terms, the two populations were very similar with respect to risk perception. It then lays the ground for community preparedness and successful recovery from extreme weather hazards.
Evaluation of preservation protocols for oxygen‐sensitive minerals within laminated aquatic sediments
Authors: Ledesma Gabrielle , Islam Raisa , Swanner Elizabeth D.
Published: January 2023

Laminated sediments can record seasonal changes in sedimentation of material from anoxic waters, including minerals of the redox‐sensitive elements Fe, Mn, and S that form under varying oxygen levels, mineral saturation conditions, and from microbial metabolism. However, preserving the oxygen‐sensitive minerals for identification is challenging when preservation of the spatial arrangement of laminae is also required. In this study, we compare methods for embedding sedimentary materials from anoxic waters and sediments from Brownie Lake, Minnesota, USA for analysis of the speciation for Fe, Mn, and S using synchrotron‐based X‐ray absorption near edge spectroscopy (XANES). We found that acetone dehydration and resin replacement in a 100% N2glovebox successfully preserved the speciation of Fe and Mn minerals within laminated sediments. However, acetone removed some sulfur species from sediments, and epoxies contained sulfur species, which challenged identification of native sulfur species. Results from this study will aid researchers who are interested in spatial analysis of oxygen sensitive sediments, soils, or microbial mats in choosing a preservation method.
Rough hypoellipticity for the heat equation in Dirichlet spaces
Authors: Hou Qi , Saloff‐Coste Laurent
Published: January 2023

This paper aims at proving the local boundedness and continuity of solutions of the heat equation in the context of Dirichlet spaces under some rather weak additional assumptions. We consider symmetric local regular Dirichlet forms, which satisfy mild assumptions concerning (1) the existence of cut‐off functions, (2) a local ultracontractivity hypothesis, and (3) a weak off‐diagonal upper bound. In this setting, local weak solutions of the heat equation, and their time derivatives, are shown to be locally bounded; they are further locally continuous, if the semigroup admits a locally continuous density function. Applications of the results are provided including discussions on the existence of locally bounded heat kernel; structure results for ancient (local weak) solutions of the heat equation.
Strata ofp‐origamis
Authors: Flake Johannes , Thevis Andrea
Published: January 2023

Given a two‐generated group of prime‐power order, we investigate the singularities of origamis whose deck group acts transitively and is isomorphic to the given group. Geometric and group‐theoretic ideas are used to classify the possible strata, depending on the prime‐power order. We then show that for many interesting known families of two‐generated groups of prime‐power order, including all regular, or powerful ones, or those of maximal class, each group admits only one possible stratum. However, we also construct examples of two‐generated groups of prime‐power order, which do not determine a unique stratum.
Comprehensive characterization and building of National Registry of von Hippel–Lindau disease in Brazil
Authors: Dallagnol Tabatha Nakakogue , Da Cás Eduardo , Junior Odery Ramos , Casali‐da‐Rocha José Cláudio
Published: January 2023

Background

Von Hippel‐Lindau (VHL) disease is an autosomal dominant disorder caused by pathogenic variants in VHL gene. The common manifestations include hemangioblastomas (HB) of the central nervous system (CNS) and retina (RH); pheochromocytoma (PHEO); clear cell renal cell carcinoma (ccRCC); pancreatic and renal cysts (PRC) and pancreatic neuroendocrine neoplasm (PNEN).

Methods

The first characterization of VHL in Brazil was published in 2003 and included 20 families with a history of VHL. The aim of this study was to expand the previous Brazilian cohort to include more families, as well as to collect prospectively both clinical and molecular characteristics of patients with VHL to build the VHL Brazilian Registry (VHLBR). Patients with VHL were selected through review of data from medical records of experts and from social networks of support for families with VHL in Brazil.

Results

A total of 142 subjects representing 62 unrelated Brazilian families with VHL were registered. The mean age of VHL onset was 28.78 years old and 128 individuals (90.1%) had at least one VHL‐related lesion. CNS HB was the most common manifestation occurring in 91 (71%) patients, followed by multiple PRC (48.4%), RH (39.8%), ccRCC (28.9%), PHEO (12.5%) and PNEN (7.8%). Of the 97 subjects whose presence of VHL variants was confirmed, 51 (52.6%) had missense variants, 22 (22.7%) large deletions, 10 (10.3%) frameshift, 7 (7.2%) splice site, 4 (4.1%) nonsense and 3 (3.1%) in‐frame deletions. Regarding surveillance, 115 (81%) participants had at least one physician responsible for their outpatient follow‐up; however, 69 (60%) of them did not report a regular frequency of tests.

Conclusion

We built the largest prospective VHLBR with organized collections of clinical and genetic data from families with VHL, which will be helpful to guide policies for VHL care and oncogenetics in Brazil. Although there have been improvements in diagnosis and clinical screening methods, VHL care in Brazil is still deficient, especially regarding surveillance and regular medical appointments with experts.
Lp error estimate of nonlinear Schrödinger equation using a two‐grid finite element method
Authors: Hu Hanzhang
Published: January 2023

A two‐grid finite element scheme is presented for nonlinear Schrödinger equation. superconvergence error estimates of finite element solutions based on bound of finite element solutions is proved. The optimal order error estimations of the two‐grid solution in the and norm are given without any time‐step size conditions. It is shown, both theoretically and numerically, that the coarse space can be extremely coarse, with no loss in the order of accuracy.
A novel local Hermite radial basis function‐based differential quadrature method for solving two‐dimensional variable‐order time fractional advection–diffusion equation with Neumann boundary conditions
Authors: Liu Jianming , Li Xin Kai , Hu Xiuling
Published: January 2023

A novel Hermite radial basis function‐based differential quadrature (H‐RBF‐DQ) method is presented in this paper based on 2D variable order time fractional advection–diffusion equations with Neumann boundary conditions. The proposed method is designed to treat accurately for derivative boundary conditions, which considerably improve the approximation results and extend the range of applicability for the method of RBF‐DQ. The advantage of the present method is that the Hermite interpolation coefficients are only dependent of the point distribution yielding a substantially better imposition of boundary conditions, even for time evolution. The proposed algorithm is thoroughly validated and is demonstrated to handle the fractional calculus problems with both Dirichlet and Neumann boundaries very well.
Tumor region associated with specific processing speed outcomes
Authors: Peterson Rachel K. , Ng Rowena , Ludwig Natasha N. , Jacobson Lisa A.
Published: January 2023

Objective

Processing speed (PS) is a vulnerable cognitive skill in pediatric cancer survivors as a consequence of treatments and, less consistently, tumor region. Studies conventionally examine graphomotor PS; emerging research suggests other aspects of PS may be impacted. This study examined types of PS in pediatric brain tumor survivors to determine which aspects are impaired. Given discordance across studies, we additionally investigated the relationship between brain region and PS.

Methods

The sample consisted of 167 pediatric brain tumor patients (100 supratentorial). PS (oral naming, semantic fluency, phonemic fluency, motor speed, graphomotor speed, visual scanning) was gathered via clinical neuropsychological assessment. To examine PS by region, infratentorial and supratentorial groups were matched on age at diagnosis and neuropsychological assessment, and time since diagnosis.

Results

The whole sample performed below normative means on measures of oral naming (p < .001), phonemic fluency (p < .001), motor speed (p = .03), visual scanning (p < .001), and graphomotor speed (p < .001). Only oral naming differed by region (p = .03), with infratentorial tumors associated with slower performance. After controlling for known medical and demographic risk factors, brain region remained a significant predictor of performance (p = .04). Among the whole sample, greater than expected proportions of patients with impairment (i.e., >1 standard deviation below the normative mean) were seen across all PS measures. Infratentorial tumors had higher rates of impairments across all PS measures except phonemic fluency.

Conclusions

Results indicate pediatric brain tumor survivors demonstrate weaknesses in multiple aspects of PS, suggesting impairments are not secondary to peripheral motor slowing alone. Additionally, tumor region may predict some but not all neuropsychological outcomes in this population.
Design and characterization of multijunction photovoltaic laser power converters for nonuniform irradiance light profiles
Authors: Delgado Marina , García Iván , Hinojosa Manuel , Algora Carlos
Published: January 2023

Nonuniform irradiance profiles of lasers used in power‐by‐light systems deteriorate the efficiency of photovoltaic laser power converters. We analyze three approaches to deal with this efficiency loss: (1) to design the power converter front grid for the nonuniform light received from the power‐by‐light system; (2) to strengthen the peak current and decrease the series resistance of tunnel junctions; and (3) to homogenize the light spot impinging the power converter by simply distancing it from the laser fiber. In the context of these approaches, this paper tackles the optimization of multijunction photovoltaic laser power converters to achieve their maximum efficiency under nonuniform irradiance profiles, without using any optical element to homogenize them and, this way, reproducing realistic operating conditions. As a direct application of the design shown in this paper, we have increased the experimental efficiency of our GaAs devices by up to 3% absolute for a nominal laser wavelength of 857 nm.
Identification of salivary autoantibodies as biomarkers of oral cancer with immunoglobulin A enrichment combined with affinity mass spectrometry
Authors: Chu Hao‐Wei , Chang Kai‐Ping , Yen Wei‐Chen , Liu Hao‐Ping , Chan Xiu‐Ya , Liu Chiao‐Rou , Hung Chu‐Mi , Wu Chih‐Ching
Published: January 2023

Globally, oral cavity squamous cell carcinoma (OSCC) is one of the most common fatal illnesses. Its high mortality is ascribed to the fact that the disease is often diagnosed at a late stage, which indicates an urgent need for approaches for the early detection of OSCC. The use of salivary autoantibodies (autoAbs) as OSCC biomarkers has numerous advantages such as easy access to saliva samples and efficient detection of autoAbs using well‐established secondary reagents. To improve OSCC screening, we identified OSCC‐associated autoAbs with the enrichment of salivary autoAbs combined with affinity mass spectrometry (MS). The salivary IgA of healthy individuals and OSCC patients was purified with peptide M‐conjugated beads and then applied to immunoprecipitated antigens (Ags) in OSCC cells. Using tandem MS analysis and spectral counting‐based quantitation, the level of 10 Ags increased in the OSCC group compared with the control group. Moreover, salivary levels of autoAbs to the 10 Ags were determined by a multiplexed bead‐based immunoassay. Among them, seven were significantly higher in early‐stage OSCC patients than in healthy individuals. A marker panel consisting of autoAbs to LMAN2, PTGR1, RAB13, and UQCRC2 was further developed to improve the early diagnosis of OSCC.
Transfer learning based deep learning model and control chart for bearing useful life prediction
Authors: Wang Fu‐Kwun , Gomez William , Amogne Zemenu Endalamaw , Rahardjo Benedictus
Published: January 2023

The remaining useful life (RUL) of the machine is one of the key information for predictive maintenance. If there is a lack of predictive maintenance strategy, it will increase the maintenance and breakdown costs of the machine. We apply transfer learning techniques to develop a new method that predicts the RUL of target data using degradation trends learned from complete bearing test data called source data. The training length of the model plays a crucial role in RUL prediction. First, the exponentially weighted moving average (EWMA) chart is used to identify the abnormal points of the bearing to determine the starting point of the model's training. Secondly, we propose transfer learning based on a bidirectional long and short‐term memory with attention mechanism (BiLSTMAM) model to estimate the RUL of the ball bearing. At the same time, the public data set is used to compare the estimation effect of the BiLSTMAM model with some published models. The BiLSTMAM model with the EWMA chart can achieve a score of 0.6702 for 11 target bearings. The accuracy of the RUL estimation ensures a reliable maintenance strategy to reduce unpredictable failures.
Distributed estimation for multi‐agent systems with relative measurements and quantized communication: A feedback quadratic framework
Authors: Liu Qinyuan , Zheng Shaoyu , Wang Zidong , Alotaibi Naif D. , Alsaadi Fawaz E.
Published: January 2023

In this paper, the feedback quadratic distributed state estimation problem is investigated for a class of linear discrete time‐varying multi‐agent systems subject to non‐Gaussian noises. For the multi‐agent systems, each agent has access to not only the local measurements but the relative states to its adjacent agents as well. Due to the bandwidth constraints of the digital communication networks, the signals are quantized and then exchanged between two adjacent agents, where the probabilistic uniform quantizations are taken into account. The purpose of the addressed problem is to design a novel quadratic distributed estimator for each agent based on the local information and the predictions received from the neighbors. In particular, an output injection term is introduced to handle the unstable systems. By means of the state/measurement augmentation approach, the underlying system is transformed into an augmented one, which aggregates the original vector and its second‐order Kronecker power. Accordingly, a distributed estimator is constructed such that an upper bound is ensured for the estimation error covariance and the suboptimal estimator parameters, which minimize such an upper bound, are subsequently calculated in terms of the solutions to certain matrix difference equations. Finally, an illustrative example is provided to verify the effectiveness and superiority of the proposed quadratic estimation scheme.
Regression analysis of logistic model with latent variables
Authors: Ye Yuan , Liu Zhongchun , Pan Deng , Wu Yuanshan
Published: January 2023

We propose a joint modeling approach to investigating the effects of social‐psychological factors on the onset of depression. The proposed model comprises two components. The first one is a confirmatory factor analysis model that summarizes latent factors through multiple correlated observed variables. The second one is a logistic regression model that investigates the effects of observed and latent influence factors on the occurrence of depression. We develop a hybrid procedure based on the borrow‐strength estimation procedure and the weighted score function to estimate the model parameters. The asymptotic properties of the proposed estimators are established. Simulation studies demonstrate that the method we proposed performs well. An application to a study concerning the social‐psychological factors of depression is provided.
Extraordinary Acceleration of an Electrophilic Reaction Driven by the Polar Surface of 2D Aluminosilicate Nanosheets
Authors: L. Torad Nagy , Tsuji Yuta , Alowasheeir Azhar , Momotake Masako , Okazawa Kazuki , Yoshizawa Kazunari , Matsumoto Michio , Yamato Masafumi , Yamauchi Yusuke , Eguchi Miharu
Published: January 2023

To increase chemical reaction rates, general solutions include increasing the concentration/temperature and introducing catalysts. In this study, the rate constant of an electrophilic metal coordination reaction is accelerated 23‐fold on the surface of layered aluminosilicate (LAS), where the reaction substrate (ligand molecule) induces dielectric polarization owing to the polar and anionic surface. According to the Arrhenius plot, the frequency factor (A) is increased by almost three orders of magnitude on the surface. This leads to the conclusion that the collision efficiency between the ligands and metal ions is enhanced on the surface due to the dielectric polarization. This is surprising because one side of the ligand is obscured by the surface, so the collision efficiency is expected to be decreased. This unique method to accelerate the chemical reaction is expected to expand the range of utilization of LASs, which are chemically inert, abundant, and environmentally friendly. The concept is also applicable to other metal oxides which have polar surfaces, which will be useful for various chemical reactions in the future.