bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychosocial Determinants of Premarital Sexual Practices among University Students in Sudan
Authors: Elshiekh Husameddin Farouk , Hoving Ciska , de Vries Hein
Published: August 2022

Sudan is one of the Islamic countries where extramarital sex is religiously forbidden and socially unacceptable. However, increasing numbers of university students become engaged in premarital sex practices, which increases their risk of contracting STIs, including HIV, and puts them into conflicts with their religious beliefs. As little is known about the motivations for abstinence from premarital sex, this study aimed to identify these psychosocial determinants. Using a cross-sectional design, a sample of 257 students between18 and 27 years old was recruited from randomly selected public and private universities in Khartoum. The participants filled out an online questionnaire based on the Integrated Change Model (ICM) to assess their beliefs and practices about abstinence from premarital sex. The analysis of variances (MANOVA) showed that the students who reported being sexually active differed significantly from abstainers in having more knowledge about HIV/AIDS, higher perception of susceptibility to HIV, more exposure to cues that made them think about sex and a more positive attitude towards premarital sex. The abstainers had a significantly more negative attitude towards premarital sex, higher self-efficacy to abstain from sex until marriage and perceived more peer support and norms favouring abstinence from sex until marriage. These findings suggest that promoting abstinence from sex until marriage among university students in Sudan, which aligns with the Sudanese religious values and social norms, requires health communication messages addressing these potential determinants. However, given that sexual encounters still may occur, health communication messages may profit from a more comprehensive approach by also addressing the need for condom use for those unwilling to refrain from sex.
Coping styles mediating the relationship between perceived chronic stress and conspiracy beliefs about COVID-19
Authors: Pfeffer Bettina , Goreis Andreas , Reichmann Adelais , Bauda Ines , Klinger Diana , Bock Mercedes M. , Plener Paul L. , Kothgassner Oswald D.
Published: August 2022

As a global health crisis, COVID-19 has led to a rise in overall stress levels. Concurrently, conspiracy beliefs regarding the origin and spread of the disease have become widespread. Engaging in such beliefs can be explained as a form of coping in order to deal with elevated levels of stress. The present study investigated the indirect effects of coping strategies in the association between perceived chronic stress and COVID-related conspiracy beliefs. We report data from an online survey (N = 1,354 individuals: 807 female; 508 male; 8 diverse; 6 not specified; mean age 39.14 years) in German-speaking countries collected between January and March 2021. Our results indicate that people who felt more stressed were more prone to conspiracy beliefs. Coping via acceptance and self-blame was associated with decreased tendencies towards COVID-related conspiracy beliefs, while people who used denial as a strategy were more prone to these beliefs. These findings emphasize the need for stress management interventions and effective coping strategies during times of crisis in order to reduce chronic perceived stress, promote adaptive coping, and ultimately reduce conspiracy beliefs.
Historic subsurface dimension stone quarry and the stability of its galleries as a function of pillar width and thickness of cover bed
Authors: Zenah Jalal , Görög Péter , Török Ákos
Published: August 2022

There are historic subsurface dimension stones in the capital of Hungary (Budapest) that were excavated in porous limestone. The stability of these subsurface openings is important, since most of them are located in urban areas, where existing buildings or new structures are planned to be built. The paper presents a detailed study considering the geometry of the system and the mechanical parameters of the limestone. The geometry of the cellar system was obtained using terrestrial laser scanning (TLS). The cover beds are few meters in thickness, and the width of the pillar is between 2.50 and 3.98 m, according to the measurements. The rock mass parameters which were used in the calculations were obtained from laboratory tests. A finite element (FEM) software Rocscience (RS2) were applied to model the stability of the galleries. Calculations were made for various geometries taking into account the thickness of cover beds and the width of pillars. Altogether 70 models were made. A surface load of 150 kN/m2 was also applied to model the buildings. New relationships between cover bed thickness, pillar width and displacements are outlined to compare these results to previous works. The strength reduction factor was also calculated for all geometries, indicating the changes in the stability of these underground quarries and pointing out the importance of cellar geometries.
Prediction of impact performance of fiber reinforced polymer composites using finite element analysis and artificial neural network
Authors: Stephen Clifton , Thekkuden Dinu Thomas , Mourad Abdel-Hamid I. , Shivamurthy B. , Selvam Rajiv , Behara Sai Rohit
Published: August 2022

In this study, a methodology combining finite element analysis (FEA) and artificial neural network (ANN) through multilayer perceptron architecture was utilized to predict the impact resistance behavior of hybrid and non-hybrid fabric reinforced polymer (FRP) composites. A projectile at 250 m s−1 impact velocity was considered for the high velocity impact simulations. The Kevlar, carbon and glass fabric-based epoxy composites were modelled and the impact tests were performed through finite element simulations. The residual velocity results from FEA were used as training data for the ANN prediction. The ANN predicted results were in good agreement with FEA results with a maximum variation of about 6.6%. In terms of impact resistance, composite laminates with more Kevlar layers exhibited enhanced performance compared to other samples. Neat Kevlar/epoxy (K/K/K) exhibited the best impact resistance performance in terms of lowest residual velocity and highest energy absorption of 101.84 m s−1 and 222.86 J, respectively. Whereas, neat glass/epoxy (G/G/G) specimens registered the highest projectile residual velocity (165.13 m s−1) and lowest energy absorption (158.99 J) compared to all other specimens. 2-fabric sandwich composite K/G/K exhibited a low residual velocity of 115.27 m s−1 and high energy absorption of 218.53 J, which is the second best among all specimens. Comparatively, the 3-fabric hybrid composites registered intermediate impact resistance results lower than that of Kevlar rich specimens, but significantly higher than neat G/G/G composite, thus, proving the effectiveness of hybridization in enhancement of impact performance compared to neat glass composite. Overall, the chosen methodology yielded significantly accurate results for the prediction of impact behavior of FRP composites.
Booking in the Rain. Testing the Impact of Public Information on Prices
Authors: Figini Paolo , Cicognani Simona , Zirulia Lorenzo
Published: August 2022

Weather forecasts are a rare example of public information which is, at the same time, relevant for agents' decisions and entirely exogenous for both sides of the (tourism) market. We develop a model where signals of good weather have a positive impact on accommodation prices, the effect being stronger the higher the accuracy of the forecast and the ex-ante uncertainty in weather conditions. Using data from a sea and sun destination, we estimate an augmented hedonic price model and find that results robustly support the theory. We also find that the response of prices to weather forecasts is larger for upper-scale hotels than for low- and mid-scale hotels, a result we link to the superior pricing capability of the former.
Proclus Timaeus
Authors: Proclus
Published: August 2022

Proclus' Commentary on Plato's dialogue Timaeus is arguably the most important commentary on a text of Plato, offering unparalleled insights into eight centuries of Platonic interpretation. This edition offered the first new English translation of the work for nearly two centuries, building on significant advances in scholarship on Neoplatonic commentators. It provides an invaluable record of early interpretations of Plato's dialogue, while also presenting Proclus' own views on the meaning and significance of Platonic philosophy. The present volume, the third in the edition, offers a substantial introduction and notes designed to help readers unfamiliar with this author. It presents Proclus' version of Plato's account of the elements and the mathematical proportions which bind together the body of the world.
Keeping tabs through collaboration? Sharing ministerial responsibility in coalition governments
Authors: Klüser K. Jonathan
Published: August 2022

Moving past the conventional focus on ministerial portfolios, this paper investigates how coalition governments allocate and share ministerial responsibility for individual policy issues. Sharing responsibility induces coalescing parties to collaborate on policy issues, which addresses the problem of ministerial autonomy. Consequently, I argue that incumbent parties in coalition governments share ministerial responsibility for contentious and salient policy issues. This claim is corroborated based on a newly elicited dataset of over 30,000 ministerial policy responsibilities from Denmark, Germany, and the Netherlands. The findings have important implications for scholarship on coalition governments, as they demonstrate that incumbent parties can use the design of ministerial portfolios itself to insulate a coalition compromise from partisan deviations.
From Spirit Possession to Ritual Theatre—A Potential Scenario for the Development of Japanese Kagura
Authors: Lancashire Terence
Published: August 2022

The Japanese goddess Arne no Uzume no Mikoto bound up her sleeves with a chord of heavenly pi-kage vine, tied around her head a head-band of the heavenly masaki vine, bound together bundles of sasa leaves to hold in her hands, and overturning a bucket before the heavenly rock-cave door, stamped resoundingly upon it. Then she became divinely possessed, exposed her breasts, and pushed her skirt-band down to her genitals. (Philippi 1968:84)

This description of the possession dance of the goddess Ame no Uzume no Mikoto in the eighth century Kojiki (Record of Ancient Matters) A.D. 712, to entice the sun goddess from her place of hiding, is held as the origins of kagura—a ritual dance performed by miko—female shrine attendants. The connection between myth and ritual is made early in Japanese history with the early ninth century Kogo shûi—a record of court rites stating that the successors of Ame no Uzume no Mikoto were an already extinct female priestly group, Sarume Kimi no Uji, and they in turn passed their skill on to the miko.
Is the environment a victim of the economic downturn? Evidence from China's manufacturing firms
Authors: Zhang Xuemei , Yin Haitao , Yang Huimin
Published: August 2022

This paper investigates whether pollution-intensive industries develop faster in a time of economic downturn. Using firm-level panel data from 2005 to 2013, we find supporting empirical results in an analysis of China's manufacturing industries in the 2008 economic crisis. We find that pollution-intensive firms tended to produce more compared with non-pollution-intensive firms in the 2008 economic crisis, with the pre-crisis period as a baseline. We further find that this effect is more pronounced in areas with higher export dependence and a smaller proportion of production from pollution-intensive industries. The relatively faster production expansion in pollution-intensive industries is more evident for state-owned enterprises.
Observation of Topographic Rossby Waves Triggered by Kuroshio Path Meander in the East China Sea
Authors: Chen Juntian , Zhu Xiao‐Hua , Zheng Hua , Nakamura Hirohiko , Zhao Ruixiang , Wang Min , Park Jae‐Hun , Nishina Ayako
Published: August 2022

Topographic Rossby waves (TRWs) are motions triggered by potential vorticity adjustments, which strongly contribute to deep ocean variabilities. This study discerned near‐36‐day significant along‐slope fluctuations, speculated to be TRWs, using deep current observations over the continental slope in the East China Sea (ECS). The TRWs propagated southwestward along the continental slope with wavelengths of ∼95 km in the northern stations and ∼36 km in the southern stations where the slope is steeper. The group velocity was estimated to be ∼15.5 km/day, and the maximum current speed was ∼10 cm/s. It was assumed that the energy source originates from the Kuroshio path meander, which has a similar typical period to the TRWs and can induce surface eddy kinetic energy, along with depth variations of water column in west of the Tokara Strait. Analyses involving ray tracing model of TRWs showed consistency with the observations in wave characteristics, thereby confirming our postulation regarding the TRWs and their origin. Moreover, the energy rays, emanated from the origin, intensively propagated along the slope; and after climbing over the successive slope, eventually stopped when reaching the flat areas. Additionally, the TRWs' hyperbolic intensification and vertical coherent phase features were revealed in model results. The seasonality of the Kuroshio path meander induced depth variation of water column was estimated to be prevalent in February and August. Overall, this study revealed the propagation features and generation mechanism of TRWs over the continental slope in the ECS for the first time.
Obstructive sleep apnea is position dependent in young infants
Authors: Kukkola Hanna-Leena , Kirjavainen Turkka
Published: August 2022

Background

Obstructive sleep apnea in infants with Pierre Robin sequence is sleep-position dependent. The influence of sleep position on obstructive events is not established in other infants.

Methods

We re-evaluated ten-year pediatric sleep center data in infants aged less than six months, with polysomnography performed in different sleep positions. We excluded infants with syndromes, genetic defects, or structural anomalies.

Results

Comparison of breathing between supine and side sleeping positions was performed for 72 infants at the median corrected age of 4 weeks (interquartile range (IQR) 2-8 weeks). Of the infants, 74% were male, 35% were born prematurely, and 35% underwent study because of a life-threatening event or for being a SIDS sibling. Upper airway obstruction was more frequent (obstructive apnea-hypopnea index (OAHI), p < 0.001), 95th-percentile end-tidal carbon dioxide levels were higher (p = 0.004), and the work of breathing was heavier (p = 0.002) in the supine than in the side position. Median OAHI in the supine position was 8 h−1 (IQR 4–20 h−1), and in the side position was 4 h−1 (IQR 0-10 h−1).

Conclusions

Obstructive upper airway events in young infants are more frequent when supine than when sleeping on the side.

Impact

The effect of sleep position on obstructive sleep apnea is not well established in infants other than in those with Pierre Robin sequence.

A tendency for upper airway obstruction is position dependent in most infants aged less than 6 months. Upper airway obstruction is more common, end-tidal carbon dioxide 95th-percentile values higher, and breathing more laborious in the supine than in the side-sleeping position.

Upper airway obstruction and obstructive events have high REM sleep predominance.

As part of obstructive sleep apnea treatment in young infants, side-sleeping positioning may prove useful.
ABCA1 is an extracellular phospholipid translocase
Authors: Segrest Jere P. , Tang Chongren , Song Hyun D. , Jones Martin K. , Davidson W. Sean , Aller Stephen G. , Heinecke Jay W.
Published: August 2022

Production of high density lipoprotein (HDL) requires ATP-binding cassette transporter A1 (ABCA1) to drive phospholipid (PL) from the plasma membrane into extracellular apolipoprotein A-I. Here, we use simulations to show that domains of ABCA1 within the plasma membrane remove PL from the membrane’s outer leaflet. In our simulations, after the lipid diffuses into the interior of ABCA1’s outward-open cavity, PL extracted by the gateway passes through a ring-shaped domain, the annulus orifice, which forms the base of an elongated hydrophobic tunnel in the transporter’s extracellular domain. Engineered mutations in the gateway and annulus strongly inhibit lipid export by ABCA1 without affecting cell-surface expression levels. Our finding that ABCA1 extracts lipid from the outer face of the plasma membrane and forces it through its gateway and annulus into an elongated hydrophobic tunnel contrasts with the alternating access model, which proposes that ABCA1 flops PL substrate from the inner leaflet to the outer leaflet of the membrane. Consistent with our model, ABCA1 lacks the charged amino acid residues in the transmembrane domain found in the floppase members of the ABC transporter family.
Tuning moiré excitons and correlated electronic states through layer degree of freedom
Authors: Chen Dongxue , Lian Zhen , Huang Xiong , Su Ying , Rashetnia Mina , Yan Li , Blei Mark , Taniguchi Takashi , Watanabe Kenji , Tongay Sefaattin , Wang Zenghui , Zhang Chuanwei , Cui Yong-Tao , Shi Su-Fei
Published: August 2022

Moiré coupling in transition metal dichalcogenides (TMDCs) superlattices introduces flat minibands that enable strong electronic correlation and fascinating correlated states, and it also modifies the strong Coulomb-interaction-driven excitons and gives rise to moiré excitons. Here, we introduce the layer degree of freedom to the WSe2/WS2 moiré superlattice by changing WSe2 from monolayer to bilayer and trilayer. We observe systematic changes of optical spectra of the moiré excitons, which directly confirm the highly interfacial nature of moiré coupling at the WSe2/WS2 interface. In addition, the energy resonances of moiré excitons are strongly modified, with their separation significantly increased in multilayer WSe2/monolayer WS2 moiré superlattice. The additional WSe2 layers also modulate the strong electronic correlation strength, evidenced by the reduced Mott transition temperature with added WSe2 layer(s). The layer dependence of both moiré excitons and correlated electronic states can be well described by our theoretical model. Our study presents a new method to tune the strong electronic correlation and moiré exciton bands in the TMDCs moiré superlattices, ushering in an exciting platform to engineer quantum phenomena stemming from strong correlation and Coulomb interaction.
Skyrmions in synthetic antiferromagnets and their nucleation via electrical current and ultra-fast laser illumination
Authors: Juge Roméo , Sisodia Naveen , Larrañaga Joseba Urrestarazu , Zhang Qiang , Pham Van Tuong , Rana Kumari Gaurav , Sarpi Brice , Mille Nicolas , Stanescu Stefan , Belkhou Rachid , Mawass Mohamad-Assaad , Novakovic-Marinkovic Nina , Kronast Florian , Weigand Markus , Gräfe Joachim , Wintz Sebastian , Finizio Simone , Raabe Jörg , Aballe Lucia , Foerster Michael , Belmeguenai Mohamed , Buda-Prejbeanu Liliana D. , Pelloux-Prayer Johan , Shaw Justin M. , Nembach Hans T. , Ranno Laurent , Gaudin Gilles , Boulle Olivier
Published: August 2022

Magnetic skyrmions are topological spin textures that hold great promise as nanoscale information carriers in non-volatile memory and logic devices. While room-temperature magnetic skyrmions and their current-induced motion were recently demonstrated, the stray field resulting from their finite magnetisation and their topological charge limit their minimum size and reliable motion. Antiferromagnetic skyrmions allow to lift these limitations owing to their vanishing magnetisation and net zero topological charge, promising ultra-small and ultra-fast skyrmions. Here, we report on the observation of isolated skyrmions in compensated synthetic antiferromagnets at zero field and room temperature using X-ray magnetic microscopy. Micromagnetic simulations and an analytical model confirm the chiral antiferromagnetic nature of these skyrmions and allow the identification of the physical mechanisms controlling their size and stability. Finally, we demonstrate the nucleation of synthetic antiferromagnetic skyrmions via local current injection and ultra-fast laser excitation.
A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues
Authors: Saul Dominik , Kosinsky Robyn Laura , Atkinson Elizabeth J. , Doolittle Madison L. , Zhang Xu , LeBrasseur Nathan K. , Pignolo Robert J. , Robbins Paul D. , Niedernhofer Laura J. , Ikeno Yuji , Jurk Diana , Passos João F. , Hickson LaTonya J. , Xue Ailing , Monroe David G. , Tchkonia Tamara , Kirkland James L. , Farr Joshua N. , Khosla Sundeep
Published: August 2022

Although cellular senescence drives multiple age-related co-morbidities through the senescence-associated secretory phenotype, in vivo senescent cell identification remains challenging. Here, we generate a gene set (SenMayo) and validate its enrichment in bone biopsies from two aged human cohorts. We further demonstrate reductions in SenMayo in bone following genetic clearance of senescent cells in mice and in adipose tissue from humans following pharmacological senescent cell clearance. We next use SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from human and murine bone marrow/bone scRNA-seq data. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Using this senescence panel, we are able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways. SenMayo also represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.
An Artificial Intelligence Dataset for Solar Energy Locations in India
Authors: Ortiz Anthony , Negandhi Dhaval , Mysorekar Sagar R. , Nagaraju Shivaprakash K. , Kiesecker Joseph , Robinson Caleb , Bhatia Priyal , Khurana Aditi , Wang Jane , Oviedo Felipe , Ferres Juan Lavista
Published: August 2022

Rapid development of renewable energy sources, particularly solar photovoltaics (PV), is critical to mitigate climate change. As a result, India has set ambitious goals to install 500 gigawatts of solar energy capacity by 2030. Given the large footprint projected to meet renewables energy targets, the potential for land use conflicts over environmental values is high. To expedite development of solar energy, land use planners will need access to up-to-date and accurate geo-spatial information of PV infrastructure. In this work, we developed a spatially explicit machine learning model to map utility-scale solar projects across India using freely available satellite imagery with a mean accuracy of 92%. Our model predictions were validated by human experts to obtain a dataset of 1363 solar PV farms. Using this dataset, we measure the solar footprint across India and quantified the degree of landcover modification associated with the development of PV infrastructure. Our analysis indicates that over 74% of solar development In India was built on landcover types that have natural ecosystem preservation, or agricultural value.
Risk factors and prediction model for nonalcoholic fatty liver disease in northwest China
Authors: Li Danting , Zhang Meiyu , Wu Shengli , Tan Huiwen , Li Nong
Published: August 2022

In recent years, nonalcoholic fatty liver disease (NAFLD) has become the most important chronic liver disease worldwide. The prevalence of NAFLD in China has also increased year by year. This study aimed to detect NAFLD early by developing a nomogram model in Chinese individuals. A total of 8861 subjects who underwent physical examination in Karamay and were 18 to 62 years old were enrolled. Clinical information, laboratory results and ultrasound findings were retrieved. The participants were randomly assigned to the development set (n = 6203) and the validation set (n = 2658). Significant variables independently associated with NAFLD were identified by least absolute shrinkage and selection operator (LASSO) regression and the multiple logistic regression model. Six variables were selected to construct the nomogram: age, sex, waist circumference (WC), body mass index (BMI), alanine aminotransferase (ALT), triglycerides and glucose index (TyG). The area under the receiver operating characteristic curve (AUROC) of the development set and validation set was 0.886 and 0.894, respectively. The calibration curves showed excellent accuracy of the nomogram model. This physical examination and laboratory test-based nomogram can predict the risk of NAFLD intuitively and individually.
Decontamination of actual radioactive wastewater containing 137Cs using bentonite as a natural adsorbent: equilibrium, kinetics, and thermodynamic studies
Authors: Muslim Wasan A. , Albayati Talib M. , Al-Nasri Salam K.
Published: August 2022

Batch adsorption treatment using Iraqi bentonite as a natural adsorbent was adopted in this study to decontaminate actual 137Cs radioactive wastewater from the Al-Tuwaitha Nuclear Research Center, located south of Baghdad. The bentonite characterization was applied before and after treatment, using chemical compositions analyses, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Brunauer–Emmett–Teller (BET) surface area analysis and Fourier-transform infrared spectroscopy (FT-IR). The batch adsorption mode was applied with the initial radioactivity concentration (1440.5 Bq/L), solid/liquid ratio (1 g/L), pH (6–8), contact time (1.5 h), and temperature (298°K). The adsorption experiments showed a decontamination removal efficiency of about 95.66% of 137Cs. A Freundlich adsorption isotherm model was approved for the adsorption of 137Cs, with a coefficient of determination R2 = 0.998. A pseudo-second-order model fitted well with the adsorption of 137Cs, with R2 = 0.983. The positive value of ΔH° in the thermodynamic results indicated that the adsorption process was endothermic physisorption (ΔH° = 15.01 kJ mol−1), spontaneous and favorable (ΔG° = −7.66 kJ mol−1 K−1), with a very low degree of disorder (ΔS° = 0.076 kJ mol−1 K−1).
Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging
Authors: Glaser Yannik , Shepherd John , Leong Lambert , Wolfgruber Thomas , Lui Li-Yung , Sadowski Peter , Cummings Steven R.
Published: August 2022

Background

Mortality research has identified biomarkers predictive of all-cause mortality risk. Most of these markers, such as body mass index, are predictive cross-sectionally, while for others the longitudinal change has been shown to be predictive, for instance greater-than-average muscle and weight loss in older adults. And while sometimes markers are derived from imaging modalities such as DXA, full scans are rarely used. This study builds on that knowledge and tests two hypotheses to improve all-cause mortality prediction. The first hypothesis is that features derived from raw total-body DXA imaging using deep learning are predictive of all-cause mortality with and without clinical risk factors, meanwhile, the second hypothesis states that sequential total-body DXA scans and recurrent neural network models outperform comparable models using only one observation with and without clinical risk factors.

Methods

Multiple deep neural network architectures were designed to test theses hypotheses. The models were trained and evaluated on data from the 16-year-long Health, Aging, and Body Composition Study including over 15,000 scans from over 3000 older, multi-race male and female adults. This study further used explainable AI techniques to interpret the predictions and evaluate the contribution of different inputs.

Results

The results demonstrate that longitudinal total-body DXA scans are predictive of all-cause mortality and improve performance of traditional mortality prediction models. On a held-out test set, the strongest model achieves an area under the receiver operator characteristic curve of 0.79.

Conclusion

This study demonstrates the efficacy of deep learning for the analysis of DXA medical imaging in a cross-sectional and longitudinal setting. By analyzing the trained deep learning models, this work also sheds light on what constitutes healthy aging in a diverse cohort.
Medicine–food herb:Angelica sinensis, a potential therapeutic hope for Alzheimer's disease and related complications
Authors: Long Yu , Li Dan , Yu Shuang , Shi Ai , Deng Jie , Wen Jing , Li Xiao-qiu , Ma Yin , Zhang Yu-lu , Liu Song-yu , Wan Jin-yan , Li Nan , Yang Ming , Han Li
Published: August 2022

As a typical medicine–food herb,Angelica sinensiscan alleviate AD and AD complications based on pharmaceutical material and dietary supply.
Research output software for energetic materials based on observational modelling 2.1 (RoseBoom2.1©)
Authors: Wahler Sabrina , Klapötke Thomas M.
Published: August 2022

With the development of the program RoseBoom©, the development of new modern energetic materials will be advanced, since it aims to provide access to quick and easy prediction of performance parameters before they have been synthesized.
Spontaneous formation and growth kinetics of lipid nanotubules induced by passive nanoparticles
Authors: Chelladurai Roobala , Debnath Koushik , Jana Nikhil R. , Basu Jaydeep K.
Published: August 2022

Different stages of evolution of lipid nanotubules generated on supported lipid membranes upon binding of charged CdSe–ZnS quantum dots.
Local binary pattern‐based reversible data hiding
Authors: Sahu Monalisa , Padhy Neelamadhab , Gantayat Sasanko Sekhar , Sahu Aditya Kumar
Published: August 2022

A novel local binary pattern‐based reversible data hiding (LBP‐RDH) technique has been suggested to maintain a fair symmetry between the perceptual transparency and hiding capacity. During embedding, the image is divided into various 3×3 blocks. Then, using the LBP‐based image descriptor, the LBP codes for each block are computed. Next, the obtained LBP codes are XORed with the embedding bits and are concealed in the respective blocks using the proposed pixel readjustment process. Further, each cover image (CI) pixel produces two different stego‐image pixels. Likewise, during extraction, the CI pixels are restored without the loss of a single bit of information. The outcome of the proposed technique with respect to perceptual transparency measures, such as peak signal‐to‐noise ratio and structural similarity index, is found to be superior to that of some of the recent and state‐of‐the‐art techniques. In addition, the proposed technique has shown excellent resilience to various stego‐attacks, such as pixel difference histogram as well as regular and singular analysis. Besides, the out‐off boundary pixel problem, which endures in most of the contemporary data hiding techniques, has been successfully addressed.
Real‐time out‐of‐distribution detection in cyber‐physical systems with learning‐enabled components
Authors: Cai Feiyang , Koutsoukos Xenofon
Published: August 2022

Learning‐enabled components (LECs) such as deep neural networks are used increasingly in cyber‐physical systems (CPS) since they can handle the uncertainty and variability of the environment and increase the level of autonomy. LECs, however, may compromise system safety since their predictions may have large errors, for example, when the data available at runtime are different than the data used for training. This study considers the problem of efficient and robust out‐of‐distribution detection for learning‐enabled CPS. Out‐of‐distribution detection using a single input example is typically not robust and may result in a large number of false alarms. The proposed approach utilises neural network architectures that are used to compute efficiently the nonconformity of new inputs relative to the training data. Specifically, variational autoencoder and deep support vector data description networks are used to learn models for the real‐time detection of out‐of‐distribution high‐dimensional inputs. Robustness can be improved by incorporating saliency maps that identify parts of the input contributing most to the LEC predictions. We demonstrate the approach using simulation case studies of an advanced emergency braking system and a self‐driving end‐to‐end controller, as well as a real‐world data set for autonomous driving. The experimental results show a small detection delay with a very small number of false alarms while the execution time is comparable to the execution time of the original LECs.
Distributed output agreement of PWM‐controlled double‐integrator multi‐agent systems with switching topologies
Authors: Xu Jingwei , Bao Adiya , Jin Zhenghong , Liu Tengfei
Published: August 2022

This paper studies the distributed pulse‐width‐modulation (PWM) control problem for double‐integrator multi‐agent systems with switching topologies. Usually, a PWM control signal updates only on discrete‐time sample instants and only takes three constant values. This means that the methods based on linear and continuous designs are not directly applicable. The major contribution of this paper is that a new class of distributed PWM controllers, which feature nested saturated loops, is proposed. With the new design, the outputs of the controlled agents asymptotically converge to each other, as long as a mild connectivity condition is satisfied. The validity of the proposed PWM controller is proved based on a new invariant‐set‐like method. This work first shows that the state of each PWM‐controlled agent stays within an appropriately chosen closed set if the interactions are bounded. Then, under a mild connectivity condition, the state boundedness and convergence of the closed‐loop multi‐agent system by analyzing the boundedness of the interactions are proved. A numerical example is employed to verify the effectiveness of the proposed design.
Short‐term load forecasting in smart grids using artificial intelligence methods: A survey
Authors: Salehimehr Sirus , Taheri Behrooz , Sedighizadeh Mostafa
Published: August 2022

Electrical load forecasting is crucial to achieving better efficiency, reliability, and power quality in modern power systems. Applying short‐term load forecasting, a balance can be preserved between supply and demand; the cost of electricity production will also be decreased. Several methods are proposed for short‐term load forecasting in smart grids in recent years and each of them has its own advantages and weaknesses. Among these methods, popularity is increasing in machine learning techniques. This study is to review three common artificial intelligence load forecasting methods, including long short‐term memory, group method of data handling, and adaptive neuro‐fuzzy inference system that have been used to forecast load in a smart grid consisting of a photovoltaic, wind turbine, battery energy storage system, and electric vehicle charging stations. The performance of these methods is evaluated given accuracy and the system's hardware requirements. The noisy condition of the system is also investigated when these methods are used for load forecasting. The results show that the long short‐term memory model is more accurate than the group method of data handling and adaptive neuro‐fuzzy inference system models. However, this method requires much better hardware requirements.
Mode-selective ballistic pathway to a metastable electronic phase
Authors: Böckmann Hannes , Horstmann Jan Gerrit , Razzaq Abdus Samad , Wippermann Stefan , Ropers Claus
Published: August 2022

Exploiting vibrational excitation for the dynamic control of material properties is an attractive goal with wide-ranging technological potential. Most metal-to-insulator transitions are mediated by few structural modes and are, thus, ideal candidates for selective driving toward a desired electronic phase. Such targeted navigation within a generally multi-dimensional potential energy landscape requires microscopic insight into the non-equilibrium pathway. However, the exact role of coherent inertial motion across the transition state has remained elusive. Here, we demonstrate mode-selective control over the metal-to-insulator phase transition of atomic indium wires on the Si(111) surface, monitored by ultrafast low-energy electron diffraction. We use tailored pulse sequences to individually enhance or suppress key phonon modes and thereby steer the collective atomic motion within the potential energy surface underlying the structural transformation. Ab initio molecular dynamics simulations demonstrate the ballistic character of the structural transition along the deformation vectors of the Peierls amplitude modes. Our work illustrates that coherent excitation of collective modes via exciton-phonon interactions evades entropic barriers and enables the dynamic control of materials functionality.
Thermally induced failure mechanisms in double and triple cations perovskite solar cells
Authors: Olanrewaju Yusuf A. , Koech Richard K. , Oyelade Omolara V. , Ahmed Ridwan A. , Ichwani Reisya , Ebunu Abraham I. , Cromwell Jaya , Bello Abdulhakeem , Anye Vitalis C. , Oyewole Oluwaseun K. , Soboyejo Winston O.
Published: August 2022

The control of the cation composition of formamidinium (FA), methylammonium (MA), and cesium (Cs) has been used to engineer significant improvements in organic–inorganic perovskite solar cells. However, the thermal stability of mixed-cation perovskite solar cells is not fully understood. In this work, we present the results of an experimental study of the stability of double-cation perovskites [(FAPbI3)0.97(MAPbBr3)0.03] [(FAMA)-perovskite solar cells (PSCs)] and triple-cation based-perovskites [Cs0.05(FA0.95MA0.05)0.95Pb(I0.95Br0.05)3] [(CsFAMA)-PSCs] operated between 40 and 60°C. The thermally induced changes in the film microstructure are elucidated via scanning electron microscopy and x-ray diffraction analyses, and these are related to changes in optoelectronic properties, charge transport, and current–voltage characteristics of (FAMA)-PSCs and (CsFAMA)-PSCs. The implications of the observed degradation mechanisms are also discussed for the future development of efficient and stable PSCs.
Nanoparticle hybrids as efficient theranostic nanoagents with enhanced near-infrared optical absorption and scattering
Authors: Chen Qin , Ren Yatao , Qi Hong , Yan Yuying
Published: August 2022

The design of high-efficiency theranostic nanoagents that can be utilized in tumor diagnosis and treatment has been investigated extensively in recent years. However, most of the existing nanoagents consist of uncommon materials and complex shell structures. Despite the efforts that have been made, the development of a simple and easily synthesized theranostic nanoplatform that can be applied in optical-based imaging-guided photothermal therapy still remains a challenge. In this paper, we investigated the optical characteristics of nanoparticle aggregates as potential theranostic nanoplatforms. The mechanism of spectrum shifting and the optical properties of contacting and non-contacting short nanochains were investigated. It was found that the near-field interaction of the gold nanosphere will not shift the localized surface plasmon resonance peak to the near-infrared region. However, when the nanospheres are connected to each other, a low energy resonance peak will be excited. On this basis, a simple hybrid theranostic nanoagent consisting of different nanosphere clusters was proposed. The nanohybrid exhibits high absorption and low scattering in the first near-infrared window (NIR-I) and high scattering and near-zero absorption in the second NIR (NIR-II). This characteristic can be beneficial to tumor diagnosis and treatment, i.e., NIR-I for photothermal therapy and NIR-II for optical imaging. Numerical results show that the performance of the proposed hybrid theranostic nanoagent remains excellent even with the existence of potential impurities.
Online engagement with 2020 election misinformation and turnout in the 2021 Georgia runoff election
Authors: Green Jon , Hobbs William , McCabe Stefan , Lazer David
Published: August 2022

Following the 2020 general election, Republican elected officials, including then-President Donald Trump, promoted conspiracy theories claiming that Joe Biden’s close victory in Georgia was fraudulent. Such conspiratorial claims could implicate participation in the Georgia Senate runoff election in different ways—signaling that voting doesn’t matter, distracting from ongoing campaigns, stoking political anger at out-partisans, or providing rationalizations for (lack of) enthusiasm for voting during a transfer of power. Here, we evaluate the possibility of any on-average relationship with turnout by combining behavioral measures of engagement with election conspiracies online and administrative data on voter turnout for 40,000 Twitter users registered to vote in Georgia. We find small, limited associations. Liking or sharing messages opposed to conspiracy theories was associated with higher turnout than expected in the runoff election, and those who liked or shared tweets promoting fraud-related conspiracy theories were slightly less likely to vote.
The historical dialectology of stative morphology in Zapotecan
Authors: Beam de Azcona Rosemary G.
Published: August 2022

This paper updates the reconstruction of the stative aspect prefix in Proto-Zapotecan as *n- and tracks
innovations in stative marking. An early change is proposed to have deleted preconsonantal nasals, rendering segmentally unmarked
stative forms of consonant-initial verbs in varieties of Zapotec then spoken in and around the city of Monte Albán. Contact with
Chatino may be a factor in the retention of preconsonantal *n in Zapotec varieties spoken to the south. A fuller stative prefix,
usually *na-, arose later from a grammaticalized form of the stative-marked copula (Munro
2007; Uchihara 2021). *na- is more productive than *n- and
provides the basis for a new proposed “Eastern Zapotec” genetic grouping. However, the isogloss for *na- crosscuts the earlier
isogloss for preconsonantal nasal deletion, showing that any model of Zapotecan linguistic history needs to address not only
divergence but also convergence. Ethnohistorical and archaeological evidence provide a social context to the linguistic changes
discussed.
Tailoring the composition of the functional Cu–Cr–Zr–La/Ce alloys for electromechanical applications
Authors: Ibrahim Mervat , Reda Reham
Published: August 2022

Tailoring the compositions of the functional Cu–Cr–Zr–La/Ce alloys involve producing alloys with dilute (0.05%), low (0.16–0.2%), medium (0.41–0.44%), and high (0.66–0.91%) Cr content at dilute (0.06%), medium (0.5%), and high (0.98%) Zr content with (0.23–0.4%) La or (0.03–0.12%) Ce. The effect of these compositional differences on the microstructure, hardness, and electrical properties was studied for different aging times (0, 1, and 1.5 h). The best combination of hardness and electrical properties was achieved after 1.5 h of aging for all studied alloys. The effect of the chemical composition on tensile properties and wear resistance was studied after 1.5 h of aging. Unlike Zr, high Cr content has a negative influence on the tensile strength and wear resistance.
Microinstability simulations for stellarators involving kinetic electrons and realistic profiles
Authors: Riemann J , Kleiber R , Borchardt M , Slaby C
Published: August 2022

In this work, linear simulation results obtained with the global particle-in-cell code EUTERPE are applied to plasmas with both adiabatic and kinetic electrons in a Wendelstein 7-X magnetic configuration. Special attention is paid to challenges arising from the need to design realistic and consistent gradient scans on realistic profiles used in global simulations. Results obtained in a pressure-preserving gradient scan performed with kinetic electrons suggest a strong impact of a finite density gradient on the growth of electron-driven instabilities below the ion-temperature-gradient stability limit. Power transfer diagnostics are used to identify the nature of the coexisting driving mechanisms.
Cosmic birefringence from monodromic axion dark energy
Authors: Gasparotto Silvia , Obata Ippei
Published: August 2022

The recently reported non-zero isotropic birefringence angle in Planck 2018 polarization
data provides a tantalizing hint for new physics of axions. In this paper, we explain this by a
string theory motivated axion with a monodromy potential that plays the role of dark energy. Upon
using the birefringence measurement and the constraint on the equation of state for dark energy in
this scenario, we find an upper bound on the axion decay constant as fa
≲ 1016 
GeV. This naturally gives an energy scale of order GUT and can resolve the theoretical issue of
super-Planckian field range of the conventional axion dark energy model. We further study the
implications of cosmic birefringence for the underlying theory and its consequences for the string
swampland conjectures. We finally discuss oscillatory features in the dark energy sector and the
expected cosmic birefringence tomography.
Construction of multi-walled carbon nanotubes/ZnSnO3 heterostructures for enhanced acetone sensing performance
Authors: Du Liyong , Sun Heming
Published: August 2022

Carbon nanotubes (CNTs) have attracted many researcher’s attention in gas sensing field because of their excellent physical and chemical properties. Herein, multi-walled carbon nanotubes (MWCNTs)/ZnSnO3 heterostructures have been obtained by a simple hydrothermal method without additional annealing process. The structural and composition information are characterized by x-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and x-ray photoelectron spectroscopy (XPS). The acetone sensing properties of pure MWCNTs, ZnSnO3 and MWCNTs/ZnSnO3 heterostructures are systematically investigated, respectively. The results show that MWCNTs/ZnSnO3 heterostructures have better sensing properties compared with pure MWCNTs and ZnSnO3 sample. Specifically, MWCNTs/ZnSnO3 heterostructures exhibit not only high responses of 24.1 and rapid response/recovery speed of 1 s/9 s to 100 ppm acetone, but also relatively good repeatability and long-term stability. The enhanced sensing performance is analyzed in detail. In addition, this work provides the experimental and theory basis for synthesis of high-performance MWCNT-based chemical sensors.
Quantum simulation and quantum computation of noisy-intermediate scale
Authors: Xu Kai , Fan Heng
Published: August 2022

In the past years, great progresses have been made on quantum computation and quantum simulation. Increasing the number of qubits in the quantum processors is expected to be one of the main motivations in the next years, while noises in manipulation of quantum states may still be inevitable even the precision will improve. For research in this direction, it is necessary to review the available results about noisy multiqubit quantum computation and quantum simulation. The review focuses on multiqubit state generations, quantum computational advantage, and simulating physics of quantum many-body systems. Perspectives of near term noisy intermediate-quantum processors will be discussed.