bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the subjective and objective efficacy of a cognitive behavioural therapy for insomnia (CBT‐I)‐based smartphone app on sleep: A randomised controlled trial
Authors: Hinterberger Alexandra , Eigl Esther‐Sevil , Schwemlein Robyn Nina , Topalidis Pavlos , Schabus Manuel
Published: December 2023

Due to insufficient treatment options for insomnia, effective solutions are urgently needed. We evaluated the effects of a CBT‐I‐based app combining sleep training with subjective and objective sleep monitoring on (i) sleep and (ii) subjective‐objective sleep discrepancies (SOSD). Fifty‐seven volunteers (20–76 years; MAge = 45.67 ± 16.38; 39 female) suffering from sleep problems were randomly assigned to an experimental group (EG, n = 28) or a waitlist control group (CG, n = 29). During the 6‐week app phase, the EG used the CBT‐I‐based programme and a heart rate sensor for daily sleep monitoring and ‐feedback, while the CG used sleep monitoring only. Sleep was measured (i) subjectively via questionnaires (Insomnia Severity Index, ISI; Pittsburgh Sleep Quality Index, PSQI), (ii) objectively via ambulatory polysomnography (PSG), and (iii) continuously via heart‐rate sensor and sleep diaries. Data revealed interactions for ISI (p = 0.003, ƞ2part = 0.11) and PSQI (p = 0.050, ƞ2part = 0.05), indicating training‐specific improvements in EG, yet not in CG. While PSG‐derived outcomes appear to be less training‐specific, a tendential reduction in wake after sleep onset (WASO) was found in EG (p = 0.061, d = 0.55). Regarding changes in SOSD, the results indicate improvements during the app phase (EG) for sleep efficiency, sleep onset latency, and WASO (p ≤ 0.022, d ≥ 0.46); for total sleep time both groups showed a SOSD reduction. The findings indicate beneficial effects of a novel smartphone app on sleep and SOSD. More scientific evaluation of such digital programmes is needed to ultimately help in reducing the gap in non‐pharmacological insomnia treatment.
Proton pump inhibitor therapy may alter the sensory motor characteristics of pharyngoesophageal motility in infants with suspected GERD
Authors: Jadcherla Sudarshan R. , Helmick Roseanna , Hasenstab Kathryn A. , Njeh Minna , Yildiz Vedat O. , Wei Lai , Slaughter Jonathan L. , Di Lorenzo Carlo
Published: December 2023

Background

Acid reflux index (ARI) is a biomarker for gastroesophageal reflux disease (GERD). The effects of short‐term proton pump inhibitor (PPI) therapy on pharyngoesophageal motility and clearance mechanisms in infants remain unknown. We hypothesized that pharyngoesophageal reflexes and response to PPI are distinct between infants with 3%–7% and >7% ARI.

Methods

Secondary analysis was performed from a subset of infants who participated in a randomized controlled trial (NCT: 02486263). Infants (N = 36, 29.9 ± 4.3 weeks gestation) underwent 4 weeks of PPI therapy, 1 week of washout, and longitudinal testing to assess: (a) clinical outcomes; (b) pH‐impedance and symptom metrics including ARI, distal baseline impedance, clearance time, refluxate height, symptoms, I‐GERQ‐R scores, symptom association probability; (c) pharyngoesophageal motility reflexes and sensory motor characteristics. Comparisons were performed between infants with 3%–7% versus >7% ARI.

Key Results

From the 36 hospitalized infants treated: Pharyngoesophageal reflex latencies were prolonged (p > 0.05) and duration in ARI 3%–7% group only (p = 0.01); GER frequency, proximal ascent and clearance increased (ARI 3%–7%); weight gain velocity, oral feeding success, and fine motor score decreased while length of hospital stays increased in the ARI >7% group despite the decrease in symptoms and I‐GERQ‐R scores.

Conclusions & Inferences

Distinct changes in pharyngoesophageal sensory motor aspects of motility and reflex mechanisms exist after using PPI therapy in infants. Contributory factors may include the effects of maturation and aerodigestive comorbidities (GERD and BPD). Controlled studies incorporating placebo are needed to delineate the effects of PPI on causal and adaptive GERD mechanisms in infants with aerodigestive and feeding‐related comorbidities.
Mycorrhizal effects on crop yield and soil ecosystem functions in a long‐term tillage and fertilization experiment
Authors: Peng Zhenling , Johnson Nancy Collins , Jansa Jan , Han Jiayao , Fang Zhou , Zhang Yali , Jiang Shengjing , Xi Hao , Mao Lin , Pan Jianbin , Zhang Qi , Feng Huyuan , Fan Tinglu , Zhang Jianjun , Liu Yongjun
Published: December 2023

It is well understood that agricultural management influences arbuscular mycorrhizal (AM) fungi, but there is controversy about whether farmers should manage for AM symbiosis.

We assessed AM fungal communities colonizing wheat roots for three consecutive years in a long‐term (> 14 yr) tillage and fertilization experiment. Relationships among mycorrhizas, crop performance, and soil ecosystem functions were quantified.

Tillage, fertilizers and continuous monoculture all reduced AM fungal richness and shifted community composition toward dominance of a few ruderal taxa. Rhizophagus and Dominikia were depressed by tillage and/or fertilization, and their abundances as well as AM fungal richness correlated positively with soil aggregate stability and nutrient cycling functions across all or no‐tilled samples. In the field, wheat yield was unrelated to AM fungal abundance and correlated negatively with AM fungal richness. In a complementary glasshouse study, wheat biomass was enhanced by soil inoculum from unfertilized, no‐till plots while neutral to depressed growth was observed in wheat inoculated with soils from fertilized and conventionally tilled plots.

This study demonstrates contrasting impacts of low‐input and conventional agricultural practices on AM symbiosis and highlights the importance of considering both crop yield and soil ecosystem functions when managing mycorrhizas for more sustainable agroecosystems.
Diversified molecular adaptations of inorganic nitrogen assimilation and signaling machineries in plants
Authors: Zhang Zhenhua , Diao Runjie , Sun Jingyan , Liu Yannan , Zhao Mengru , Wang Qiuping , Xu Zilong , Zhong Bojian
Published: December 2023

Plants evolved sophisticated machineries to monitor levels of external nitrogen supply, respond to nitrogen demand from different tissues and integrate this information for coordinating its assimilation. Although roles of inorganic nitrogen in orchestrating developments have been studied in model plants and crops, systematic understanding of the origin and evolution of its assimilation and signaling machineries remains largely unknown.

We expanded taxon samplings of algae and early‐diverging land plants, covering all main lineages of Archaeplastida, and reconstructed the evolutionary history of core components involved in inorganic nitrogen assimilation and signaling.

Most components associated with inorganic nitrogen assimilation were derived from the ancestral Archaeplastida. Improvements of assimilation machineries by gene duplications and horizontal gene transfers were evident during plant terrestrialization. Clusterization of genes encoding nitrate assimilation proteins might be an adaptive strategy for algae to cope with changeable nitrate availability in different habitats. Green plants evolved complex nitrate signaling machinery that was stepwise improved by domains shuffling and regulation co‐option.

Our study highlights innovations in inorganic nitrogen assimilation and signaling machineries, ranging from molecular modifications of proteins to genomic rearrangements, which shaped developmental and metabolic adaptations of plants to changeable nutrient availability in environments.
Interpretable Machine Learning Using Partial Linear Models*
Authors: Flachaire Emmanuel , Hué Sullivan , Laurent Sébastien , Hacheme Gilles
Published: December 2023

Despite their high predictive performance, random forest and gradient boosting are often considered as black boxes which has raised concerns from practitioners and regulators. As an alternative, we suggest using partial linear models that are inherently interpretable. Specifically, we propose to combine parametric and non‐parametric functions to accurately capture linearities and non‐linearities prevailing between dependent and explanatory variables, and a variable selection procedure to control for overfitting issues. Estimation relies on a two‐step procedure building upon the double residual method. We illustrate the predictive performance and interpretability of our approach on a regression problem.
Wheat stripe mosaic virus from Brazil and South Africa evolved as distinct subpopulations with low genetic variability
Authors: Stempkowski Lucas Antonio , Pereira Fernando Sartori , Lau Douglas , Kuhnem Paulo , Casa Ricardo Trezzi , Fajardo Thor Vinícius Martins , Junior Antônio Nhani , da Silva Fábio Nascimento , Orílio Anelise Franco , Zerbini Francisco Murilo
Published: December 2023

Wheat stripe mosaic virus (WhSMV) is the causal agent of soilborne wheat mosaic disease (SBWMD) in Brazil, which is a serious threat to wheat production in the southern part of the country. WhSMV also occurs in Paraguay and South Africa. The virus is soilborne, transmitted by Polymyxa graminis, and management strategies are mainly based on genetic resistance. Variation in the reaction (type and severity of symptoms) of cultivars has been reported depending on the region and/or year of cultivation, leading wheat breeding programmes to test their materials in several locations, which increases costs and is time‐consuming. One hypothesis is that this variation in symptoms is a result of the genetic variability of WhSMV. We assessed the genetic variability and population structure of WhSMV infecting wheat in Brazil and South Africa. In field experiments conducted in different locations in southern Brazil, a consistent reproducibility of symptoms was observed in a set of cultivars, and molecular analysis showed a low degree of genetic variability of the Brazilian viral population. The hypothesis that the variation in SBWMD symptoms in Brazil is due to genetic variability of the virus was thus rejected. Comparison of the Brazilian and South African WhSMV isolates indicated that they comprise distinct subpopulations and that the Brazilian subpopulation is more variable than the South African subpopulation. The lower genetic variability of the South African subpopulation suggests genetic stability or a recent emergence of WhSMV in that region.
Parental perspectives on oral health‐related quality of life in children and adolescents with autism spectrum disorder: A systematic review
Authors: Goswami Mousumi , Bhatara Supriya , Bhatara Mohit , Singh Shrey Raj
Published: December 2023

Background

Children with autism spectrum disorder (ASD) face unique challenges related to oral health, which can negatively impact their day‐to‐day lives, significantly compromising their overall quality of life. Primary caregivers of children with ASD have a critical role in delivering and seeking oral health care. Hence, it is vital to study their perspective towards their children's oral health and its impact on their quality of life.

Aim

To explore the parental perception of oral health‐related quality of life in children with autism.

Methods

A systematic electronic and manual search was conducted in Medline (via PubMed), Embase, Google Scholar, Scopus, and LILACS of articles published from January 2003 to May 2023 using appropriate MeSH terms, keywords, and other terms. A four‐phase study selection process was followed according to PRISMA guidelines, and data extraction and synthesis were performed using an extraction form. The selected studies were critically appraised using the QATSDD and Crombie's assessment tool. The inter‐reviewer agreement was assessed using the kappa with a linear weighting coefficient.

Results

Out of the 885 results, 15 studies were included in the review after the two selection phases, and the study characteristics were summarized in tabular form. Study quality varied considerably, and out of a total possible QATSDD score of 42, scores for the individual studies ranged from 14 to 40. The risk of bias for the seven criteria was found to be low.

Conclusion

The parental perception of the OHRQoL in children with ASD is poor, and the most significant perceived impact is on the child's functional and social well‐being aspects. Parental‐Caregiver Perception Questionnaire was the most commonly used. The most frequent symptoms include bad breath, food lodgment, mouth breathing and night grinding. The familial impact and influence on the OHRQoL of siblings were also studied.
Tracking depressive and anxious symptoms during the first year of COVID‐19: The search for moderators
Authors: Haeffel Gerald J.
Published: December 2023

A growing body of research suggests that the COVID‐19 pandemic did not cause the severe and extensive mental health crisis predicted by some experts. However, this does not mean that everyone was resilient. The purpose of this study was to try to identify subgroups of people that may have experienced more severe and negative trajectories of symptoms during this time. To this end, we examined a host of individual difference factors (e.g., age, gender, race, country, parental status, medical conditions, lost wages, perceived support, initial symptom levels, and cognitive vulnerability) using a 1‐year longitudinal design with 8 time points and participants (n = 233) from over 20 countries. We were unable to identify a single moderator associated with a robust and increasingly negative trajectory of depressive and anxious symptoms throughout the COVID interval. These results underscore the need for better theories of mental illness, stronger research designs that do not rely on simple cross‐sectional between‐group comparisons, and more caution when predicting mental health crises.
Buildings, valuated matroids, and tropical linear spaces
Authors: Battistella Luca , Kühn Kevin , Kuhrs Arne , Ulirsch Martin , Vargas Alejandro
Published: December 2023

Affine Bruhat–Tits buildings are geometric spaces extracting the combinatorics of algebraic groups. The building of parameterizes flags of subspaces/lattices in or, equivalently, norms on a fixed finite‐dimensional vector space, up to homothety. It has first been studied by Goldman and Iwahori as a piecewise‐linear analogue of symmetric spaces. The space of seminorms compactifies the space of norms and admits a natural surjective restriction map from the Berkovich analytification of projective space that factors the natural tropicalization map. Inspired by Payne's result that the analytification is the limit of all tropicalizations, we show that the space of seminorms is the limit of all tropicalized linear embeddings and prove a faithful tropicalization result for compactified linear spaces. The space of seminorms is in fact the tropical linear space associated to the universal realizable valuated matroid.
Gait Sensing and Haptic Feedback Using an Inflatable Soft Haptic Sensor
Authors: Quinones Yumbla Emiliano , Rokalaboina Jahnav , Kanechika Amber , Poddar Souvik , Nibi Tolemy M. , Zhang Wenlong
Published: December 2023

Collecting gait data and providing haptic feedback are essential for the safety and efficiency of robot-based rehabilitation. However, readily available devices that can perform both are scarce. This work presents a novel method for mutual sensing and haptic feedback, through the development of an inflatable soft haptic sensor (ISHASE). The design, modeling, and characterization of ISHASE are discussed. Four ISHASEs are embedded in the insole of a shoe to measure ground reaction forces and provide haptic feedback. Four participants were recruited to evaluate the performance of ISHASE as a sensor and haptic device. Experimental results indicate that ISHASE can accurately estimate user’s ground reaction forces while walking, with a maximum and a minimum accuracy of 91% and 85%, respectively. Haptic feedback was delivered to four different locations under the foot, and users could identify the location with an average 92% accuracy. A case study that exemplifies a rehabilitation scenario is presented to demonstrate ISHASE’s usefulness for mutual sensing and haptic feedback.
Modeling Interfacial Oxidation of Cylindrically Curved Silicon Surfaces Including Dependencies on Stress From Coupled Elastic Analysis
Authors: Delaney Brian C. , Blanchet Thierry A.
Published: December 2023

Our model, treating oxide as solid annulus freely expanded from the silicon (Si) consumed due to increased molecular volume whose geometry enables closed-form expression of time as a function of thickness in constant-parameters case, was revised in non-dimensional form maintaining the appearance of the original Si radius. While this constant-parameters case describes oxide thickness decreasing with decreasing Si radius in concave cases as reported from the experiment, in convex cases thickness is instead described to increase with decreasing Si radius, contradicting published experimental observations. Performing stress analysis displacing surfaces of expanded oxide and remaining Si back to their shared interface, stress-dependent solubility, diffusivity, and reaction rate were investigated toward resolving this discrepancy between the model and reported experiments. With stress-dependent parameters, closed-form expression of time as a function of oxide thickness is no longer achieved, with numerical integration instead required to compute oxidation times. If considering solubility or diffusivity to increase with hydrostatic stress or reaction rate to decrease with increasing interface pressure radially, as hypothesized, increasing oxide thickness with decreasing original Si radius in convex cases remains predicted, in conflict with experimental reports in the literature. It is shown that the experimental observation of an oxide thickness decreasing with decreasing Si radius in convex cases is possible if considering reaction rate to instead increase with increasing interfacial pressure. The same may be possible if considering solubility or diffusivity to instead decrease with increasing hydrostatic stress, tuning activation energies describing the strength of such dependence.
The Effects of Rotation and Solidity on the Aerodynamic Behavior of Low-Pressure Axial Flow Fans
Authors: Venter Adam J. , Owen Michael T. F. , Muiyser Jacques
Published: December 2023

Implicit axial flow fan models are commonly used for the numerical analysis of industrial heat exchanger systems. However, these fan models perform poorly within the often complex off-design flow environments characteristic of these systems, as their low-order formulations lose applicability under highly 3D flow conditions. At off-design flow conditions, rotation and blade solidity effects cause physical fan blade behavior to deviate from the anticipated 2D behavior characterized by the implicit models. Physical fan blade behavior at off-design flow conditions, however, remains uncertain and the specific effects of rotation and solidity are not yet widely understood. This study investigates off-design fan blade behavior by presenting explicit 3D computations of two low-pressure axial flow fans. The effects of rotation and blade solidity are then identified through a side-by-side comparison of the computed 3D fan blade data against isolated 2D airfoil data. The rotating fan blade lift characteristics are shown to be distinct from the comparative 2D airfoil trends. At low-flow (off-design) operating conditions, rotation establishes large radial flow movements, and the high blade solidities cause standing vortices to develop within the rotating blade passages. The radial outflow energizes the blades' boundary layers, and the vortices inhibit the flow from separating from the blades' surfaces. Consequently, blade stall is avoided and high lift coefficient values are realized. The presented fan blade lift characteristics are unique relative to literature on other turbomachines of lower blade solidity, highlighting the importance of considering solidity effects in implicit rotor model developments.
Evaluation of Thermoacoustic Instability for Chemically Reacting Flows Using Large-Eddy Simulations
Authors: Lim Wei Xian , Chan Wai Lee , Elhadidi Basman
Published: December 2023

Thermoacoustic instability for chemically reacting flows was investigated using large eddy simulations coupled with a lookup table for turbulence-chemistry closure. The onset of instability was evaluated from pressure fluctuations, as well as standard and extended Rayleigh criterion, as suggested in literature. Two configurations were considered, namely, a canonical Rijke tube and a simplified can combustor with a swirling flow injector representing a complex generalized geometry. For the Rijke tube, premixed and nonpremixed combustion models were applied for identical fuel flowrate, resulting in different thermoacoustic outcomes due to differences in reaction rates of the two flame regimes. Results from the Rijke tube case agree with analytic thermoacoustic theory. For the can combustor, only premixed chemistry was considered as it better represents the experimental conditions, and the first resonant pressure mode aligns reasonably with published experimental data. Findings suggest that, if thermoacoustic instability is detected, the resonant frequency can be deduced from the fluctuations of the pressure, heat release, or acoustic source term. However, even though the resonant frequency is correctly identified, fluctuation data alone is insufficient to identify the onset of thermoacoustic instability, requiring the additional application of Rayleigh criterion. Finally, this study concludes that, for the range of configurations evaluated here, the standard Rayleigh criterion is sufficient to determine the onset of thermoacoustic instability, so the extended Rayleigh criterion is not always necessary, in contrast to suggestions from previous work. This conclusion is significant because the standard Rayleigh criterion is the only practical evaluation for physical experiments.
Energy Performance Prediction Model for Mixed-Flow Pumps by Considering the Effect of Incoming Prerotation
Authors: Yang Yang , Chen Xionghuan , Bai Ling , Wang Hui , Ji Leilei , Zhou Ling
Published: December 2023

Mixed-flow pump is one of the most broadly applied sorts of power equipment in the field of petrochemical and water conservancy. The effect of inlet prerotation on the energy characteristics and operational stability of a pump is a significant consideration. The aim of this study is to analyze the relationship between inlet prerotation and the total energy consumption of a mixed flow pump by developing a predictive model. The impact of prerotation on the pumping performance and energy conversion for a typical mixed-flow pump has been investigated by a combined approach of theoretical derivation, numerical simulation, and experimental verification. Validation of the numerical methods was achieved by comparing the results to the experimentally obtained data. A prediction model was developed for head and power, which incorporated inlet prerotation. The study utilized a mathematical model and numerical simulation to compute the head and power output of a mixed-flow pump for a wide range of inlet prerotation angles. The results of the two methods were highly consistent. Moreover, the effects of prerotation on the flow structure of the mixed-flow pump were analyzed. It was found that prerotation led to an increase in the incoming flow angle, resulting in unstable flow patterns causing secondary flows and low-pressure vortex in the impeller flow path. This induced a rise in energy consumption of the impeller. The prediction model and analysis of the internal flow structure provide a theoretical foundation for predicting the hydraulic performances of mixed-flow pumps under prerotation conditions and improving their stability of operation.
Does the COVID-19 outbreak affect dynamic co-movement among the stock markets of China, Japan, and the USA?
Authors: Li Haoyu
Published: December 2023

The research examines the effect of the COVID-19 outbreak on the dynamic co-movement of the stock markets of China, Japan, and the USA using a VAR model and a DCC-GJR-GARCH model. Especially, this study focuses on during and preceding the COVID period. This study data period extends from 1 January 2016 to 31 April 2022. The results demonstrate that COVID-19’s effect increases stock market volatility. Meanwhile, the VAR model revealed that the USA’s exogeneity was greater during COVID-19. In addition, the pre-crisis Granger Causality between China–USA and Japan–China is substantially higher than during the crisis. The findings of DCC-GJR-GARCH indicate the presence of volatility clustering in each of the stock markets. Moreover, the results suggest that the time-varying correlations between China and the USA during the pre-COVID period are greater than during the COVID period. The study’s findings highlight that investors attempting to increase investment diversification opportunities worldwide should always consider dynamic co-movement in different periods to maximize returns and minimize risk.
DSISA: A New Neural Machine Translation Combining Dependency Weight and Neighbors
Authors: Li Lingfang , Zhang Aijun , Luo Ming-Xing
Published: December 2023

Most of the previous neural machine translations (NMT) rely on parallel corpus. Integrating explicitly prior syntactic structure information can improve the neural machine translation. In this article, we propose a Syntax Induced Self-Attention (SISA) which explores the influence of dependence relation between words through the attention mechanism and fine-tunes the attention allocation of the sentence through the obtained dependency weight. We present a new model, Double Syntax Induced Self-Attention (DSISA), which fuses the features extracted by SISA and a compact convolution neural network (CNN). SISA can alleviate long dependency in sentence, while CNN captures the limited context based on neighbors. DSISA utilizes two different neural networks to extract different features for richer semantic representation and replaces the first layer of Transformer encoder. DSISA not only makes use of the global feature of tokens in sentences but also the local feature formed with adjacent tokens. Finally, we perform simulation experiments that verify the performance of the new model on standard corpora.
CSAIL2019 Crypto-Puzzle Solver Architecture
Authors: Gribok Sergey , Pasca Bogdan , Langhammer Martin
Published: December 2023

tThe CSAIL2019 time-lock puzzle is an unsolved cryptographic challenge introduced by Ron Rivest in 2019, replacing the solved LCS35 puzzle. Solving these types of puzzles requires large amounts of intrinsically sequential computations, with each iteration performing a very large (3,072-bit for CSAIL2019) modular multiplication operation. The complexity of each iteration is several times greater than known field-programmable gate array (FPGA) implementations, and the number of iterations has been increased by about 1,000x compared with LCS35. Because of the high complexity of this new puzzle, a number of intermediate, or milestone, versions of the puzzle have been specified. In this article, we present several FPGA architectures for the CSAIL2019 solver, which we implement on a medium-sized Intel Agilex device. We develop a new multi-cycle modular multiplication method, which is flexible and can fit on a wide variety of sizes of current FPGAs. We introduce a class of multi-cycle squarer-based architectures that allow for better resource and area trade-offs. We also demonstrate a new approach for improving the fitting and timing closure of large, chip-filling arithmetic designs. We used the solver to compute the first 23 out of 28 milestone solutions of the puzzle, which are the first reported results for this problem.
Analysis of the Severity of Accidents on Rural Roads Using Statistical and Artificial Neural Network Methods
Authors: Habibzadeh Mohammad , Ayar Pooyan , Mirabimoghaddam Mohammad Hassan , Ameri Mahmoud , Sadat Haghighi Seyede Mojde
Published: December 2023

This study assesses the relationship that existed between various variables and their subvariables on rural roads in Qom, Iran, using statistical analysis and calculates the relationship between the considered factors and accident severity. A logit model was applied to determine the factors affecting the severity of accidents. In addition, two artificial neural network (ANN) models were developed using two kinds of learning methods to train neurons to select the best result. The results of modeling and analysis of accidents using various techniques revealed that each technique, depending on its purpose, examined the severity of accidents from a different point of view and represented various outcomes. Finally, the performance of the proposed models was validated utilizing other mathematical models. As a result, putting the output results together, the best measures can be suggested to increase the safety of people on rural roads. The outcomes of this study may aid these service providers in strategic planning and policy framework.
A Model-Based Bayesian Inference Approach for On-Board Monitoring of Rail Roughness Profiles: Application on Field Measurement Data of the Swiss Federal Railways Network
Authors: Stoura Charikleia D. , Dertimanis Vasilis K. , Hoelzl Cyprien , Kossmann Claudia , Cigada Alfredo , Chatzi Eleni N.
Published: December 2023

According to the International Union of Railways, railway networks count more than one million kilometers of tracks worldwide, a number that is to rise further as the goal is to promote rail transportation as a sustainable means to face the challenge of increased mobility. However, such a vast expansion further necessitates efficient and reliable infrastructure monitoring schemes able to guarantee the quality and safety of rail transportation. Traditional monitoring approaches, relying on visual inspection and portable measuring devices, cannot rise to the task as they do not allow for continuous inspection of extended portions of rail infrastructure. Therefore, mobile monitoring methodologies based on dedicated diagnostic vehicles have emerged as an alternative. Despite revolutionizing traditional monitoring methods, such vehicles are usually expensive and can only operate under the suspension of regular rail service. In this work, we propose an alternative approach for mobile sensing of railway infrastructure based on on-board monitoring data collected from low-cost vibration sensors, e.g., accelerometers, which can be mounted on in-service trains. Specifically, we focus on identifying the roughness profile of the tracks and propose a fusion of reduced-order vehicle models with a Bayesian inference approach for joint input-state estimation. To enhance the inference, we opt for a prior updating of the vehicle model parameters on the basis of an unscented Kalman filter and available measurements from a diagnostic vehicle. The key contributions of this work are (i) the consideration of the dynamic interaction between trains and tracks, which is usually ignored in rail roughness estimation, (ii) the adoption of reduced train vehicle models that decrease the computational effort of the identification task, (iii) the updating of the vehicle parameters to account for inconsistencies in the model used, and (iv) the application of the proposed methodology to actual acceleration measurements collected from a diagnostic vehicle of the Swiss Federal Railways network.
An Efficient Algorithm for Resource Allocation in Mobile Edge Computing Based on Convex Optimization and Karush–Kuhn–Tucker Method
Authors: Wang Kaijing , Akhtar Shelily F. , Al-Zahrani Fahad Ahmed
Published: December 2023

Mobile edge computing (MEC) is receiving more attention than centralized cloud computing due to the massive increase in transmission and compute requirements in 5G vehicle networks. It offers a significant amount of processing and storage resources to the edge of networks, offloading applications from vehicle terminals that are computation-intensive and delay-sensitive. For devices with limited resources, it uses edge resources to provide computationally heavy operations while conserving energy. This paper proposes a novel approach for computing offloading in MEC. To effectively optimize the MEC resources, this paper proposes a novel algorithm. First, the joint optimization and service cache decision subproblems were determined from continuous and discrete variables. Then, the near-optimal solution is determined from the subproblems through convex optimization and Karush–Kuhn–Tucker method. Simulation results show that the proposed algorithm has better computational offloading and resource allocation performance as compared to existing algorithms.
Supplementary Table 1 from Pilot Phase II Trial of Neoadjuvant Immunotherapy in Locoregionally Advanced, Resectable Cutaneous Squamous Cell Carcinoma of the Head and Neck
Authors: Ferrarotto Renata , Amit Moran , Nagarajan Priyadharsini , Rubin M. Laura , Yuan Ying , Bell Diana , El-Naggar Adel K. , Johnson Jason M. , Morrison William H. , Rosenthal David I. , Glisson Bonnie S. , Johnson Faye M. , Lu Charles , Mott Frank E. , Esmaeli Bita , Diaz Eduardo M. , Gidley Paul W. , Goepfert Ryan P. , Lewis Carol M. , Weber Randal S. , Wargo Jennifer A. , Basu Sreyashi , Duan Fei , Yadav Shalini S. , Sharma Padmanee , Allison James P. , Myers Jeffrey N. , Gross Neil D.
Published: December 2023

This table lists the antibodies used for CyTOF analyses.
Pattern of Expression of MicroRNA in Patients with Radiation-Induced Bladder Injury
Authors: Nakamura Ko , Ohno Takaya , Inamoto Teruo , Takai Tomoaki , Uchimoto Taizo , Fukushima Tatsuo , Nishimura Kazuki , Yano Yusuke , Nishio Kyosuke , Kinoshita Shoko , Matsunaga Tomohisa , Nakamori Keita , Tsutsumi Takeshi , Tsujino Takuya , Uehara Hirofumi , Komura Kazumasa , Takahara Kiyoshi , Azuma Haruhito
Published: December 2023

Introduction: Bladder cancer (BC) is sensitive to radiation treatment and a subset of patients experience radiation-induced injuries including shrinkage of bladder due to bladder fibrosis. Methods: This study is a retrospective cohort study. Three Japanese BC patients were randomly selected. Using a microRNA (miRNA) array, comparing their samples with or without radiation-induced injuries, we have checked the clustering of miRNA expression. Results: Hsa-miR-130a, hsa-miR-200c, hsa-miR-141, and hsa-miR-96 were found to be highly expressed (>50 times) in patients with fibrotic bladder shrinkage (FBS) compared to those with intact bladder (IB) function. In patients with FBS, hsa-miR-6835, hsa-miR-4675, hsa-miR-371a, and hsa-miR-6885 were detected to have lesser than half expression to IB patients. We have analyzed the significance of these genes in relation to overall survival of 409 BC patients retrieved from the Cancer Genome Atlas data set. All available cutoff values between the lower and upper quartiles of expression are used for the selected genes, and false discovery rate using the Benjamini-Hochberg method is computed to correct for multiple hypothesis testing. We have run combined survival analysis of the mean expression of these four miRNAs highly expressed in FBS patients. 175 patients with high expression had a longer median survival of 98.47 months than 23.73 months in 233 patients with low expression (hazard ratio [HR]: 0.53; 0.39–0.72, log-rank p value: 7.3e−0.5). Combination analysis of all 8 genes including hsa-miR-6835, hsa-miR-4675, hsa-miR-371a, and hsa-miR-6885 showed the same HR for OS. Target scanning for these miRNAs matched specific cytokines known as an early biomarker to develop radiation-induced fibrosis. Conclusions: BC patients with fibrotic radiation injury have specific miRNA expression profile targeting profibrotic cytokines and these miRNAs possibly render to favorable survival.
Clinical Outcomes of Diffuse Angiogram‐Negative Subarachnoid Hemorrhage Versus Aneurysmal Subarachnoid Hemorrhage: A Propensity Score‐Matched Analysis
Authors: Lu Guang‐Dong , Wang Cheng , Zhao Lin‐Bo , Shi Hai‐Bin , Liu Sheng
Published: December 2023

Background

The outcome of diffuse angiogram‐negative subarachnoid hemorrhage (dan‐SAH) compared with aneurysmal SAH (aSAH) remains unclear. This study aimed to compare outcomes using propensity score matching.

Methods and Results

Sixty‐five patients with dan‐SAH and 857 patients with aSAH admitted between January 2018 and December 2022 were retrospectively reviewed. Propensity score matching resulted in matching 65 patients with dan‐SAH to 260 patients with aSAH, and clinical outcomes were compared between the groups. Compared with patients with dan‐SAH, patients with aSAH were more likely to experience rehemorrhage (8.8% versus 0%,
P
=0.027), death (11.2% versus 1.5%; odds ratios [OR] 8.04 [95% CI, 1.07–60.12];
P
=0.042), or delayed cerebral ischemia (12.3% versus 3.1%; OR, 4.42 [95% CI, 1.03–18.95];
P
=0.045). Multivariate analysis revealed that Hunt–Hess grade 4 to 5 (OR, 3.13 [95% CI, 2.11–4.64];
P
<0.001), presence of intraventricular hemorrhage (OR, 3.58 [95% CI, 1.72–7.46];
P
=0.001), and smoking (OR, 2.44 [95% CI, 1.12–5.28];
P
=0.024) were independently associated with the incidence of unfavorable outcomes (modified Rankin scale score >2 at 3 months), whereas dan‐SAH was not (OR, 0.66 [95% CI, 0.25–1.73];
P
=0.40).

Conclusions

Compared with patients with dan‐SAH, patients with aSAH had higher rehemorrhage rates and in‐hospital mortality, as well as a higher incidence of delayed cerebral ischemia. Unfavorable outcomes were associated with admission Hunt–Hess grade, the presence of intravenetricular hemorrhage, and smoking history, but there was no relation with the  pathogenesis of the hemorrhage (dan‐SAH versus aSAH).
Aging‐Associated ALKBH5‐m
6
A Modification Exacerbates Doxorubicin‐Induced Cardiomyocyte Apoptosis Via AT‐Rich Interaction Domain 2
Authors: Chen Runtai , Zhang Guogang , Sun Kun , Chen Alex F.
Published: December 2023

Background

Chemotherapy‐induced cardiovascular disease is a growing concern in the elderly population who have survived cancer, yet the underlying mechanism remains poorly understood. We investigated the role of ALKBH5 (AlkB homolog 5), a primary N
6
‐methyladenosine (m
6
A) demethylase, and its involvement in m
6
A methylation‐mediated regulation of targets in aging‐associated doxorubicin‐induced cardiotoxicity.

Methods and Results

To validate the relationship between doxorubicin‐induced cardiotoxicity and aging, we established young and old male mouse models. ALKBH5 expression was modulated through adeno‐associated virus 9 (in vivo),
Lentivirus
, and siRNAs (in vitro) to examine its impact on cardiomyocyte m
6
A modification, doxorubicin‐induced cardiac dysfunction, and remodeling. We performed mRNA sequencing, methylated RNA immunoprecipitation sequencing, and molecular assays to unravel the mechanism of ALKBH5‐m
6
A modification in doxorubicin‐induced cardiotoxicity. Our data revealed an age‐dependent increase in doxorubicin‐induced cardiac dysfunction, remodeling, and injury. ALKBH5 expression was elevated in aging mouse hearts, leading to reduced global m
6
A modification levels. Through mRNA sequencing and methylated RNA immunoprecipitation sequencing analyses, we identified ARID2 (AT‐rich interaction domain 2) as the downstream effector of ALKBH5‐m
6
A modulation in cardiomyocytes. Further investigations revealed that ARID2 modulates DNA damage response and enhances doxorubicin‐induced cardiomyocyte apoptosis.

Conclusions

Our findings provide insights into the role of ALKBH5‐m
6
A modification in modulating doxorubicin‐induced cardiac dysfunction, remodeling, and cardiomyocyte apoptosis in male mice. These results highlight the potential of ALKBH5‐targeted treatments for elderly patients with cancer in clinical settings.
Quantitative Prediction of Right Ventricular Size and Function From the ECG
Authors: Duong Son Q. , Vaid Akhil , My Vy Thi Ha , Butler Liam R. , Lampert Joshua , Pass Robert H. , Charney Alexander W. , Narula Jagat , Khera Rohan , Sakhuja Ankit , Greenspan Hayit , Gelb Bruce D. , Do Ron , Nadkarni Girish N.
Published: December 2023

Background

Right ventricular ejection fraction (RVEF) and end‐diastolic volume (RVEDV) are not readily assessed through traditional modalities. Deep learning–enabled ECG analysis for estimation of right ventricular (RV) size or function is unexplored.

Methods and Results

We trained a deep learning–ECG model to predict RV dilation (RVEDV >120 mL/m
2
), RV dysfunction (RVEF ≤40%), and numerical RVEDV and RVEF from a 12‐lead ECG paired with reference‐standard cardiac magnetic resonance imaging volumetric measurements in UK Biobank (UKBB; n=42 938). We fine‐tuned in a multicenter health system (MSH
original
[Mount Sinai Hospital]; n=3019) with prospective validation over 4 months (MSH
validation
; n=115). We evaluated performance with area under the receiver operating characteristic curve for categorical and mean absolute error for continuous measures overall and in key subgroups. We assessed the association of RVEF prediction with transplant‐free survival with Cox proportional hazards models. The prevalence of RV dysfunction for UKBB/MSH
original
/MSH
validation
cohorts was 1.0%/18.0%/15.7%, respectively. RV dysfunction model area under the receiver operating characteristic curve for UKBB/MSH
original
/MSH
validation
cohorts was 0.86/0.81/0.77, respectively. The prevalence of RV dilation for UKBB/MSH
original
/MSH
validation
cohorts was 1.6%/10.6%/4.3%. RV dilation model area under the receiver operating characteristic curve for UKBB/MSH
original
/MSH
validation
cohorts was 0.91/0.81/0.92, respectively. MSH
original
mean absolute error was RVEF=7.8% and RVEDV=17.6 mL/m
2
. The performance of the RVEF model was similar in key subgroups including with and without left ventricular dysfunction. Over a median follow‐up of 2.3 years, predicted RVEF was associated with adjusted transplant‐free survival (hazard ratio, 1.40 for each 10% decrease;
P
=0.031).

Conclusions

Deep learning–ECG analysis can identify significant cardiac magnetic resonance imaging RV dysfunction and dilation with good performance. Predicted RVEF is associated with clinical outcome.
Impact of Obesity on Atrial Fibrillation Pathogenesis and Treatment Options
Authors: Sha Rina , Baines Olivia , Hayes Abbie , Tompkins Katie , Kalla Manish , Holmes Andrew P. , O'Shea Christopher , Pavlovic Davor
Published: December 2023

Atrial fibrillation (AF) is the most common cardiac arrhythmia. AF increases the risk of stroke, heart failure, dementia, and hospitalization. Obesity significantly increases AF risk, both directly and indirectly, through related conditions, like hypertension, diabetes, and heart failure. Obesity‐driven structural and electrical remodeling contribute to AF via several reported mechanisms, including adiposity, inflammation, fibrosis, oxidative stress, ion channel alterations, and autonomic dysfunction. In particular, expanding epicardial adipose tissue during obesity has been suggested as a key driver of AF via paracrine signaling and direct infiltration. Weight loss has been shown to reverse these changes and reduce AF risk and recurrence after ablation. However, studies on how obesity affects pharmacologic or interventional AF treatments are limited. In this review, we discuss mechanisms by which obesity mediates AF and treatment outcomes, aiming to provide insight into obesity‐drug interactions and guide personalized treatment for this patient subgroup.
Beyond Segment Inventories: Phonological Complexity Measures and Suprasegmental Variables in Contact Situations
Authors: Napoleão de Souza Ricardo , Sinnemäki Kaius
Published: December 2023

This article has three goals. First, it provides a broad cross-linguistic survey of phonological change in contact situations focusing on the suprasegmental domain. The term suprasegmental refers here to syllable structure, stress patterns, tonal patterns, and vowel and nasal harmony systems. Secondly, it assesses phonological change to suprasegmental variables whereby external influence causes an increase in complexity in the recipient language’s structure. Thirdly, using insights from the phonological typology literature, it provides a preliminary framework to evaluate suprasegmental phenomena, which can then serve as an additional tool to disentangle inheritance from contact-induced change. Data from 45 languages suggest that the suprasegmental domain provides fertile ground for inspecting contact-influenced increases in linguistic complexity. Overall, we argue that the data reviewed here highlight the relevance of phonological structure as a variable in studies of language contact, which have been mostly preoccupied with morphosyntactic variables.
ASEAN and the Major Powers in the South China Sea: the Role of Law, Diplomacy, and Deterrence in Moderating Sovereignty Claims
Authors: Nathan K.S.
Published: December 2023

This article focuses on the rising strategic significance of the South China Sea for the Association of Southeast Asian Nations (ASEAN) and the major powers. It traces the origins of the South China Sea (SCS) dispute, and the claimants that are directly involved (China, Vietnam, Philippines, Malaysia, and Brunei). It then examines why balance of power considerations have influenced and continue to influence the role of regional states as well as the major external powers (China, United States, India, and Japan, together with other interested middle powers such as Australia and Canada). It argues that the SCS is an international maritime regime (global commons), and therefore subject to the principles and practice of International Law, specifically United Nations Convention on the Law of the Sea (UNCLOS). Any attempt at nationalisation of the SCS will be rejected under international law, as evidenced by the 2016 decision of the Permanent Court of Arbitration (PCA), with respect to the submission in 2013 by the Philippines on its dispute with China, for compulsory arbitration by the The Hague Court. It notes the lack of unity in ASEAN over how to deal with China’s assertive conduct in the SCS. It suggests that only a dynamic balance of power approach, which includes external power engagement with regional interests, will create the necessary space for diplomacy and dialogue by upholding the primacy of the rule of law, freedom of the open seas, and the legitimate rights and interests of all claimant states. It concludes that law, politics, diplomacy, and deterrence are interactive variables requiring strategic management to promote shared interests, stability and security in the South China Sea.
Digital Innovations during the COVID-19 Pandemic: Facebook Use for Local E-Governance in the Province of South Cotabato
Authors: Bajar Jayson Troy Ferro , Porsche-Ludwig Markus
Published: December 2023

The full-scale adoption of digital technologies in Filipino social life became more apparent during the COVID-19 pandemic. The abrupt emergence of this global catastrophe challenged many to shift to digital infrastructures instantaneously, similar to how local government units (LGU s) implemented their e-governance initiatives. Following a case study design, this article sought to find out how local governments carry out digital innovations, specifically the Province of South Cotabato which can be considered exemplary in this area based on awards it received. A total of 524 Facebook posts, gathered from the first quarter of 2021, were examined using quantitative content analysis. Findings of this study revealed that the LGU s (city, municipality and province) demonstrated “prioritization,” “appropriation,” and “amplification” in fulfilling adjunct roles of being public administrators and content creators at the same time. This article strongly recommends the development of a scientifically informed social media policy framework for government entities.