bluuebunny/crossref_metadata_2025 huggingface dataset:
Tax Collection and Management Digitalization and Enterprises’ Social Security Compliance
Authors: Yu Changlin , Li Yanming
Published: April 2024

Using the enforcement of the “Golden Tax Project Phase III” (Hereinafter referred to as “GTPIII”) as a quasi-natural experiment, this paper employs the Time-varying difference-in-difference (DID) method to comprehensively assess the impact of tax collection and management digitalization on enterprises’ social security compliance, based on National Tax Survey Data from 2007 to 2016 in China. This study found that the “GTPIII” significantly improved enterprises’ actual contribution rate of social security by 6.28 % and their likelihood of participating in social security by 17.62 % on average. Similar positive effects were obtained when various kinds of social security compliance behavior were considered. The “GTPIII” achieved such facilitating effects by promoting the interconnection of tax-related information between departments, discouraging enterprises from concealing contribution bases, and discouraging local governments’ flexible collection behavior. Heterogeneity research reveals that the “GTPIII” has a greater impact on social security compliance in SMEs, non-state-owned enterprises, low average salary and low profitability enterprises. Further analysis reveals that the “GTPIII”, while significantly increasing revenue for the regional social security fund, has caused enterprises to shift the tax burden by reducing jobs and lowering employee wages, forcing them to take the initiative to increase R&D expenditures.
Prevalence of Anxiety and Depressive Symptoms Among Clinical Physiotherapy Students Following Prolonged Lecturers Strike in a Sub-Saharan University.
Authors: Okonkwo Uchenna Prosper , Udechukwu Ray-Thelma Chisonyerem , Chukwuemeka Uchechukwu Martha , Amaechi Ifeoma Adaigwe , Akobundu Uzoamaka Nwakego
Published: April 2024

Objectives
To determine the prevalence of anxiety, and depressive symptoms among clinical physiotherapy students of Nnamdi Azikiwe University, Nnewi Campus, following prolonged lecturers (teachers) strike. a
Methods
This cross-sectional survey consecutively recruited 131 physiotherapy undergraduates of Nnamdi Azikiwe University, Nnewi Campus, in clinical classes. The researchinstruments were a socio-demographic questionnaire and the Hospital Anxiety and Depression Scale (HADS). Data was analyzed using descriptive statistics and a Chi-square inferential statistical test at an alpha level of 0.05.
Results: The majority of the participants were between 18-23 years of age, 75 (57.25%) of the participants were in their fourth year of study (400 level), while 56 (42.75%) of the participants were in their fifth year of study (500 level). The prevalence of anxiety and depression within the population of the study were 20.6% and 4.6% respectively. There was a significant association between the pairs of anxiety symptoms and gender (p=0.017); depressive symptoms and gender (p=0.008), with members of the male gender presenting more significant cases of anxiety and depressive symptoms.
Conclusion
The prevalence of depression and anxiety within the population of study were relatively high, and actively associated with gender.
What are community perspectives regarding brain- computer interfaces? A cross-sectional study of community-dwelling adults in the UK
Authors: El-Osta Austen , Ammouri Mahmoud Al , Khan Shujhat , Altalib Sami , Karki Manisha , Riboli-Sasco Eva , Majeed Azeem Majee
Published: April 2024

Background
Brain-computer interfaces (BCIs) have emerged as ground-breaking tools in neuroscience, enabling direct communication between the brain and external devices. This technology holds promise for enhancing the lives of individuals with neurological disorders offering new avenues for rehabilitation, communication and personal autonomy. Despite rapid technological advancements, public perceptions and ethical considerations surrounding BCI technology remain largely unexplored especially within the community setting in the UK.
Aims
The primary aim was to investigate the knowledge, attitudes and perceptions of community-dwelling adults in the UK regarding BCIs. We also sought to uncover ethical considerations and gauge public interest in potential medical and non-medical applications.
Methods
This cross-sectional study collected data from 846 respondents using a structured 29-item online questionnaire disseminated through various platforms. Data were collected on demographics, awareness of BCI technology, its applications and participants' willingness to use BCIs under different circumstances.
Results
Most respondents had never heard of or used BCIs, showing a significant awareness gap. Despite this, there was a strong interest in the medical applications of BCIs particularly for rehabilitation and aiding individuals with disabilities reflecting a cautious optimism towards their development. Conversely, non-medical uses elicited concerns about privacy, data security and long-term societal impacts highlighting ethical and regulatory challenges.
Conclusion
We recorded broad support for the development of BCI technology especially for applications that improve the quality of life for individuals with disabilities. This support was tempered by a pressing need for public education, engagement and the development of robust ethical guidelines and regulatory frameworks to navigate the future integration of BCIs into society. Addressing these challenges is crucial for realizing the full potential of BCIs in a manner that aligns with societal values and expectations.
Evaluation of the relationship between drugs’ safety competence and Medication Administration Error Perceptions in Clinical nurses of Northwest Iran
Authors: Zadeh Mehdi Mahmoud , Zia Sana Khalilzadeh , Dadkhah Behrouz , Mohamadi Mohammad Ail
Published: April 2024

Aims: The present study aimed to Evaluate of relationship between drugs’ safety competence and Medication Administration Error Perceptions in clinical nurses who are working in clinical nurses of northwest Iran
Background: The first and most important aim of a medical facility, as in the Nightingale pledge, is to not harm patients and protect their safety in the first place. One of the major threats to patient safety is drug-related errors.
Methods: This correlational study was conducted in Ardabil, northwest of Iran, in 2023. In these 300 nurses have been categorized by a proportional stratified sampling method. For data collection, we used the Bijani et al(2023) Persian version of the medication safety competence Questionnaire and the Wakefield et all (2005) Medication Administration Error Perceptions Questionnaire”.The collected data were analyzed in SPSS software (26) using descriptive statistics, independent t-test, analysis of variance, Pearson correlation coefficients, and linear regression model.
Results: The results revealed that the drug safety competencies in Nurses (77%) and Medication Administration Error Perceptions in nurses (96%) were at a moderate level. The mean nurses’ drug safety competence and Medication Administration Error Perceptions were reported (294.22 ± 26.61) and (135.48 ± 15.14) and this difference was statistically significant (P<0.001). There was a positive and significant correlation between drug safety competencies and Medication Administration Error Perceptions (P=0.007, r=0.15). A simple linear regression model showed that The field of "patient-centered medication management" of medication safety competency was a stronger predictor than other variables in medication error perception.
Conclusion: In the present study, nurses reported medication safety competence and perception of medication error at an average level. It is suggested that health policymakers and decision-makers take the necessary measures by holding consensus meetings and effective workshops to reduce medication errors and improve nurses' medication perception.
Development of machine learning-based prediction models of inadequate postoperative analgesia after noncardiac surgery: a retrospective cohort study
Authors: Zhan Gaofeng , Yan Xu , Sun Rao , Hu Liu , Xu Qiaoqiao , Yan Jing , Li Shiyong , Luo Ailin , Zhou Zhiqiang
Published: April 2024

Background
Early identification of high-risk patients with inadequate postoperative analgesia is crucial in noncardiac surgery. This study aimed to develop prediction models for inadequate postoperative analgesia in noncardiac surgery using machine learning algorithms.
Methods
This article reports on a study that enrolled 199,517 adult patients who underwent noncardiac surgery. The discovery cohort included patients who had surgical procedures performed between June 2018 and April 2022, while the validation cohort included those who had surgeries between May 2022 and October 2022. Machine learning algorithms such as logistic regression (LR), random forest (RF), eXtreme gradient boosting tree (XGBoost), artificial neural network (ANN), and gradient boosting machine (GBM) were used to develop predictive models of inadequate postoperative analgesia based on perioperative variables.
Results
The overall prevalence of inadequate postoperative analgesia was 18.1%. Among the five machine learning algorithms we considered, GBM performed the best performance, with an AUROC value of 0.831 [95% CI, 0.827–0.834]. The SHAP analysis showed that surgery duration, type of surgery, anesthesia method, intraoperative fluid management, and use of hormones were the strongest five predictors. In addition, we observed that as the number of predicted features gradually decreased from all to 20, the performance of the prediction model exhibited only a marginal decline from 0.83 to 0.81.
Conclusions
This study demonstrates that the GBM algorithm demonstrated superior predictive performance in comparison to all other algorithms utilized. Screening for inadequate postoperative analgesia based on the prediction model could improve postoperative pain management.
Chakravyuha: A Scheme to Resist Fast Correlation Attack for Word Oriented LFSR based Stream Cipher
Authors: Nandi Subrata , Krishnaswamy Srinivasan , GS Nitesh Narayana , Mitra Pianki
Published: April 2024

In LFSR-based stream ciphers, the knowledge of the feedback equation of the LFSR plays a critical role in most attacks. In word-based stream ciphers such as those in the SNOW series, even if the feedback configuration is hidden, knowing the characteristic polynomial of the state transition matrix of the LFSR enables the attacker to create a feedback equation over GF(2).This, in turn, can be used to launch Fast Correlation Attacks. In this work, we propose a method for hiding both the feedback equation of a word-based LFSR and the characteristic polynomial of the state transition matrix. Here, we employ az-primitive σ-LFSR whose characteristic polynomial is randomly sampled from the distribution of primitive polynomials over GF(2) of the appropriate degree. We propose an algorithm for locating z-primitive σ-LFSR configurations of a given degree. Further, an invertible matrix is generated from the key. This is then employed to generate a public parameter to retrieve the feedback configuration using the key. If the key size is $n$- bits, the process of retrieving the feedback equation from the public parameter has an average time complexity O(2n−1). The proposed method has been tested on SNOW 3G for resistance to Fast Correlation Attacks. In addition to that, the scheme withstands other attacks like Algebraic Attacks, Distinguishing Attacks, Guess and Determine Attacks. We have demonstrated that the security of SNOW 2.0 and SNOW 3G increases from 128 bits to 256 bits
Deciphering the Genetic and Environmental Nexus of Air Pollution, Personality Traits, and Psychiatric Disorders: A Multi-Faceted Genomic Analysis
Authors: Feng Yu , Jia Ningning , Xiao Chenxu , Shen Jing
Published: April 2024

The intricate relationship between air pollution and psychiatric disorders is a subject of increasing concern, given the profound impact these elements have on individuals and society. Recent studies have implicated air pollution, a significant environmental issue, in affecting mental health both directly and indirectly. Through a comprehensive analysis involving genome-wide association studies (GWAS) that examine data on common air pollutants (PM2.5, PM10, NOx, NO2) and various psychiatric disorders along with personality traits, researchers have delved deep into the genetic interplay underlying these connections. Utilizing advanced statistical tools like linkage disequilibrium score regression, GenomicSEM, and Mendelian randomization, among others, this study has revealed a complex genetic correlation between air pollution levels and mental health disorders. Key findings include the identification of genetic factors through GenomicSEM that link air pollution with psychiatric disorders, and the discovery of 142 loci using a multi-trait analysis approach that connects air pollution directly to psychiatric conditions. The study also highlighted significant genetic loci, such as those in the 5q21.2 region, which show a strong correlation with both air pollution and psychiatric disorders, suggesting that certain areas of the genome may be particularly susceptible to environmental influences on mental health. Moreover, the research suggests that air pollution may affect mental health indirectly by influencing personality traits like mood swings, loneliness, and a general sense of dissatisfaction. This underlines the complex ways in which environmental factors can intertwine with genetic predispositions to impact mental well-being. The insights gained from this study are crucial for understanding the multifaceted interactions between environmental pollution and psychiatric health, pointing towards the urgent need to address air quality as part of broader mental health strategies.
MC simulation in shor algorithm
Authors: Ho Nam-Chol , Yun Nam-Jin , Ri Su-Bok , Jang Gyong-Song , Kim Won Gwan
Published: April 2024

We suggest a new algorithm for large number’s factorization to simulate Shor algorithm on a classical computer by using QFT. On the basis of this algorithm, we establish a way of MC simulation to resolve large number into factors.
A causal relationship between sleep behaviour and osteoporosis: a two-sample reverse-mediated Mendelian randomisation study
Authors: Wang Yunqing , Li Gang , Liu Jiang
Published: April 2024

Background
In recent years, there have been more and more clinical observational studies on sleep behaviour and osteoporosis, but the causal relationship between sleep behaviour and osteoporosis at the genetic level, and whether there are mediating factors between the two is still unclear.
Methods
From the published GWAS data, seven sleep behaviours were selected as exposure factors: insomnia, sleep time, getting up in the morning, napping during the day, sleep type (early/late rise), narcolepsy and snoring. Bone mineral density of heel (H-BMD), forearm (FA-BMD), lumbar vertebra (LS-BMD) and femoral neck (FN-BMD) were the outcome factors. The causal relationship between low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) was analyzed through Mendelian randomization.
Results
The results of a two-sample Mendelian randomization study showed that snoring was positively correlated with lumbar bone density (OR = 1.555, 95%CI: 1.189–2.032, P = 0.001). The results of reverse Mendelian randomization showed that lumbar bone density was not the cause of snoring (P = 0.466). Mediating Mendelian randomization studies showed that both LDL cholesterol and triglycerides had mediating effects on sleep behaviour and bone density (OR = 0.92, 95%CI: 0.87–0.98, P = 5.56e-3) (OR = 1.17, 95%CI: 1.09–01.26, P = 3.72e-5).
Conclusions
Our study shows that snoring is a factor affecting lumbar bone density, and low-density lipoprotein cholesterol and triglyceride play an intermediary role in it. Therefore, correcting snoring and controlling low-density lipoprotein cholesterol and triglyceride index should be included in the clinical regimen for preventing and treating bone mineral density decline.
Effect of traditional Chinese Yijinjing exercise on hand dysfunction in rheumatoid arthritis patients: a randomized controlled trial
Authors: Chang Tian , Ma Xieli , Gong Xun , Jiang Quan , Zhang Rouman
Published: April 2024

Background:
Rheumatoid arthritis (RA) patients suffer from hand dysfunction. Exercise has been shown to affect pain, function and quality of life, as recommended by guidelines. Yijinjing is a traditional Chinese exercise that is beneficial to mind-body health. This study aimed to evaluate the efficacy and safety of Yijinjing for preventing hand dysfunction in RA patients.
Methods: This was a single-center, randomized controlled trial (RCT) in which the outcome assessors were blinded. RA participants who met the eligibility criteria (n = 66) were randomly assigned to the exercise (n = 33) or control (n = 33) group. The former underwent professional Yijinjing exercise three times a week for 12 weeks. The latter maintained ordinary activities without intervention. All outcomes, including the Michigan Hand Function Scale (MHQ), handgrip strength, active range of motion (AROM), RA disease activity (DAS28-ESR), Health Assessment Questionnaire Disability Index (HAQ), anxiety and depression mental status, and wrist ultrasound, were obtained at baseline and after 12 weeks.
Results: The MHQs of the exercise group significantly improved
compared with those in the control group at 12 weeks (p<0.05), with improvements in handgrip strength and active joint range of motion (wrist extension, radial deviation, and metacarpophalangeal flexion) (p<0.05). Although the difference was not statistically significant, the ultrasound score of the exercise group did not increase (p>0.05). The morning stiffness duration, DAS28-ESR, ESR, and CRP level were significantly greater in the exercise group than in the control group (p<0.05). For the quality of life, anxiety, and depression scores, both groups presented improvements compared with the baseline group (p<0.05), while the exercise group was clearly better than the control group (p<0.05). Following the 12-week intervention, neither group experienced any adverse events or substantial abnormalities in their vital signs according to ECG.
Conclusion: Yijinjing exercise can improve hand function and enhance handgrip strength and flexibility in RA patients with low disease activity while ameliorating quality of life and alleviating anxiety and depression while safe and not aggravating joint inflammation.
Clinical trial registration: [https://clinicaltrials.gov/study/NCT05527158], Identifier [NCT05527158].
Usefulness of interim contrast-enhanced breast MRI for predicting response of breast cancer to neoadjuvant chemotherapy
Authors: Kato Eri , Sasada Shinsuke , Masumoto Norio , Emi Akiko , Shigematsu Hideo , Okada Morihito , Kadoya Takayuki
Published: April 2024

Purpose
In breast cancer patients, contrast-enhanced breast magnetic resonance imaging (MRI) is usually performed after completing neoadjuvant chemotherapy (NAC) to determine treatment efficacy. We compared the ability of MRI conducted during the interim phase (interim MRI) with that of MRI conducted after NAC (post-NAC MRI) to predict treatment response.
Methods
In this retrospective study, 260 patients with invasive breast cancer who underwent NAC between April 2010 and December 2020 and who had undergone MRI before, during, and after NAC were included. Most patients received taxane and anthracycline sequentially, while human epidermal growth factor receptor 2 (HER2)-positive cases also received anti-HER2 agents.
Results
Sixty-five patients (25%) demonstrated a pathological complete response (pCR). The sensitivity and specificity of interim MRI for predicting pCR in all patients were 84% and 83%, respectively, which were comparable with those of post-NAC MRI (88% and 64%, respectively). Its sensitivity and specificity in luminal-type breast cancer were 95% and 50%, respectively, and those in HER2-positive breast cancer were 77% and 73%, respectively, while those in triple-negative breast cancer (TNBC) cases were 94% and 89%, respectively. Twenty-nine (83%) of 35 cases diagnosed with clinical complete response (cCR) by interim MRI achieved pCR, whereas 25 (93%) of the 27 HER2-positive type or TNBC cases achieved pCR. Similarly, 189 (84%) of 225 cases indicated as non-cCR by interim MRI were non-pCR, whereas 94 (95%) of 99 non-cCR luminal-type cases were non-pCR.
Conclusion
Interim MRI could predict treatment response at an early stage in breast cancer patients receiving NAC.
Demographic and biographical data from cancer patients of a national online self-help forum
Authors: Hentze Antonia , Keinki Christian , Walter Stefanie , Hübner Jutta
Published: April 2024

Purpose: Our study aimed to identify the members of Germany’s largest self-help forum, understanding their characteristics, and addressing their needs effectively.
Methods: The sociodemographic and cancer-specific data of 7,171 members were extracted from the forum, categorised, and analysed in January 2023.
Results: The members had an average age of 51.5 years, with 84% women and 1.8% men. In terms of occupation, 18.7% worked in administration and office work, 17.7% in healthcare and 11.7% in education and research. Regarding leisure activities, 49.9% were involved in sports and 41.3% in knowledge building. The most common cancers were breast cancer (71.9%), adnexal tumours (6.3%), and gastrointestinal tumours (4.1%). Common metastases included bone (31.3%), liver (22.1%), and lung (11.6%). Most cases had low T-stages, intermediate grading, and low lymph node involvement. The hormone receptor status showed 38.8% were oestrogen receptor positive, 50.6% triple-negative, and 22.9% HER2/neu receptor positive. Cancer treatment compromised surgery (87.2%), cancer drugs (45.7%), endocrine therapy (27.8%), and radiotherapy (34.7%).
Conclusion: The FSH online forum supports a diverse group of cancer patients, especially those with breast cancer. Moderation ensures a secure environment for sharing and finding like-minded individuals. As barriers to digital information use may decrease over time, healthcare professionals should recommend online forums for cancer support. Physicians, nurses, and cancer centres can help by including these forums in their recommended resources for patients.
Implications for Cancer Survivors: Online cancer self-help forums offer valuable information for cancer survivors and enable mutual exchange, using well-moderated, high-quality platforms.
Role of Wind and Waves in Shaping the Coastal Environment in Central Kerala, India: A Pre-monsoon Study
Authors: Shankar Vasudevan , R Sajeev
Published: April 2024

This study analyzes wind and wave data from the coastal region of central Kerala during the years 2015 and 2016 to investigate the impact of wind patterns and wave characteristics on the coastal environment before the onset of the monsoon season. It is essential to comprehend these factors when evaluating coastal conditions, sea state, and regional wind scale. In particular, the study focuses on Shamal events, which are characterized by northwesterly winds and lead to significant changes in wave height and period. In addition, the daily cycle of the sea breeze, which plays a key role in the change of wind speed and wave height at the coast, is investigated. While local wind patterns such as the sea breeze influence wave development, the land breeze from the northeast has minimal impact due to limited fetch. The study emphasizes the importance of the Shamal waves and the intensity and duration of the sea breeze for sediment transport along the coast. Overall, this study emphasizes the significance of meteorological conditions, especially wind patterns and their impact on waves, for coastal processes during the pre-monsoon season.
Prevalence and predictors of Eating Disorders’ risk in medical students at Damascus University: a cross-sectional study
Authors: Nahas Lujain , Mohamad Lama , Soqia Jameel , Agha Laila Yakoub , Nahas Mehdy , Alsaid Bayan
Published: April 2024

Background: Eating disorders are among the most important psychiatric problems, and they are triggered by a complex network of factors. These disorders also seem to affect medical field students far more than others.
Objective: To determine the point prevalence of the risk of disordered eating behaviors in medical students at Damascus University and to study the possible reasons for this risk.
Methods: A cross-sectional study at Damascus University, Faculty of Medicine, was carried out between October and December of 2023. Data were collected from randomly sampled students from the second to sixth years via online surveys using the Eating Attitudes Test-26 (EAT-26) and the Sick, Control, One, Fat, Food (SCOFF) questionnaires as primary screening tools. Binary logistic regression was used to determine possible influencing factors on eating disorders.
Results: Among the 829 participants, 11.3% had a greater risk of disordered eating behavior according to the EAT-26, and 20.3% had a greater risk according to the SCOFF. The average age was 21.29 years (1.76), and 67.6% of the participants’ body mass index (BMI) was within the normal range. Preclinical-aged female students (OR=1.89, p=0.009 for SCOFF and OR=0.66, p=0.017 for SCOFF) were at greater risk. Another important correlation was found between BMI and exposure to recent stressors (p<0.001 in both comparisons). However, age did not demonstrate any traceable importance (p=0.17) in addition to living or marital status (p=0.13 and p=0.18, respectively).
Conclusion: There is a risk of developing eating disorders among medical students, which might go unrecognized due to a lack of awareness of the importance of their detection. This risk also seems to stem from multiple risk factors that still require further research. Improving the relationship with psychological disorders and working on changing their rooted stigmatization will most likely prevent the escalation of these disorders in the future.
Systemic antibiotic treatment of cows with metritis early postpartum does not change the progression of uterine disease or the uterine microbiome at 1 month postpartum
Authors: Moraes Joao Gabriel Nascimento , Gull Tamara B. , Ericsson Aaron C. , Caldeira Monica O. , Evans Tim J. , Poock Scott E. , Lucy Matthew C.
Published: April 2024

Background: Postpartum uterine disease (metritis) is common in dairy cows. The disease develops within 1 week after calving and is associated with microbial dysbiosis, fever, and fetid uterine discharge. Cows with metritis have a greater likelihood of developing endometritis and infertility later postpartum. Antibiotic treatment is used to relieve symptoms of metritis but the capacity of antibiotic treatment to improve fertility later postpartum is inconsistent across published studies. We hypothesized that an antibiotic has only a short-term effect on the uterine microbiome and does not change the progression of disease from metritis to endometritis. To test this hypothesis, we studied the effects of systemic antibiotic given to cows diagnosed with metritis and healthy cows early postpartum on the development of endometritis and the uterine microbiome at 1 month postpartum.
Results: Cows diagnosed with metritis were compared to healthy ones in a 2 x 2 factorial design, where they were either treated with an antibiotic (ceftiofur hydrochloride) at 7 to 10 days postpartum or left untreated. Cows were slaughtered at one month postpartum and the uterus was assessed for endometritis (presence of purulent material in the uterine lumen and inflammation in the endometrium) and uterine samples were collected for bacteriology and metagenomics (16S rRNA gene sequencing). As expected, the uterine microbiome at disease diagnosis had dysbiosis of typical metritis pathogens (e.g., Fusobacterium, Bacteroides, and Porphyromonas) in diseased compared with healthy cows. At one month postpartum, there was a tendency for more endometritis in metritis cows compared with healthy but antibiotic treatment had no effect on endometritis prevalence regardless of the original disease diagnosis. Likewise, when bacteria were cultured or sequenced, there were a greater number of species (culture) or amplicon sequence variants (ASV; sequencing) in the uterine lumen of cows with metritis. However, antibiotic treatment had no effect on the prevalence of cultured species or the composition of the detected ASV. The uterine microbiome at 1 month postpartum was associated with the clinical observation of the uterus (endometritis or healthy).
Conclusions: Early postpartum antibiotic treatment only provides temporary resolution of uterine dysbiosis that is not sustained long-term. Failure to resolve the dysbiosis is associated with a greater prevalence of endometritis in cows with metritis, and the occurrence of endometritis significantly impacts fertility later postpartum.
Zn-Co needle-grass shape nanostructure in-situ grown on porous Nickle foam as an electrocatalyst for efficient HER
Authors: Xiao Linfeng , Han Jing , Liang Boyu , Deng Wenqiang , Hong Yan , Du Jie , Liao Runhua , Fu Lichun , Xie Zhixiang
Published: April 2024

Due to the low cost and abundant reserves of transition metals, there is an urgent need for the design and fabrication of transition metal electrocatalysts for hydrogen evolution reaction (HER) in order to facilitate hydrogen production. In this study, we present a self-supported needle-grass shaped Zn-Co composition on porous Nickel foam (NF) through typical hydrothermal synthesis. The Zn-Co/NF electrodes exhibit highly efficient HER performance in 1.0 M KOH alkaline solution. Specifically, the ZC (1:4)/NF catalyst requires only 98 mV overpotential at a current density of 50 mA cm− 2 due to the synergistic effect between the Zn-Co composition and Ni layers. Furthermore, stability tests reveal that after 1000 continuous cycles with a scan rate of 20 mV s− 1, there is only slight change observed in the LSV curves of ZC (1:4)/NF catalysts. This work provides a novel strategy for designing and fabricating efficient HER electrocatalysts.
Blind Quality Evaluator for Multi-Exposure Fusion Image via Joint Sparse Features and Complex-Wavelet Statistical Characteristics
Authors: Yang Benquan , Cui Yueli , Liu Lihong , Chen Guang , Xu Jiamin , Lin Junhao
Published: April 2024

Multi-Exposure Fusion (MEF) technique aims to fuse multiple images taken from the same scene at different exposure levels into an image with more details. Although more and more MEF algorithms have been developed, how to effectively evaluate the quality of MEF images has not been thoroughly investigated. To address this issue, a blind quality evaluator for MEF image via joint sparse features and complex-wavelet statistical characteristics is developed. Specifically, considering that color and structure distortions are inevitably introduced during the MEF operations, we first train a color dictionary in the Lab color space based on the color perception mechanism of human visual system, and extract sparse perceptual features to capture the color and structure distortions. Given an MEF image to be evaluated, its components in both luminance and color channels are derived first. Subsequently, these obtained components are sparsely encoded using the trained color dictionary, and the perceived sparse features are extracted from the produced sparse coefficients. In addition, considering the insensitivity of sparse features towards weak structural information in images, complex steerable pyramid decomposition is further performed over the generated chromaticity map. Consequently, perceptual features of magnitude, phase and cross-scale structural similarity index are extracted from complex wavelet coefficients within the chromaticity map as quality-aware features. Experimental results demonstrate that our proposed metric outperforms the existing classic image quality evaluation metrics while maintaining high accordance with human visual perception.
Day – ahead traffic flow forecast using LSTM and Cuckoo Search Optimization
Authors: V Rajalakshmi , P Sharon Femi , A Kala
Published: April 2024

To monitor and regulate the traffic flow there is always a need to implement a dynamic and proactive traffic control system. Traffic flow forecasting is an essential and critical requirement for developing a traffic control system in intelligent transportation systems (ITS). In this paper, traffic flow forecasting is done on the England highways dataset of MIDAS site. LSTM networks play a critical role in sequence learning. It is used to forecast the patterns of forecast in the near future. Bio-inspired algorithms are commonly employed in numerous research to optimize the model's parameters. In this work, optimizing the performance of LSTM parameters is initiated with the Cuckoo Search Evolutionary Algorithm. Optimizing weights of various layers improves the performance of LSTM model. The cuckoo search optimization is used in finding the optimum weights and bias values for the LSTM network. The prior traffic flow data is imparted with intelligence using the LSTM – Cuckoo Search (CS) to provide adequate decisions to drivers. The results propagate that the Cuckoo Search has improved the performance of LSTM with the R2 of 0.98.
On-chip dual-microcomb based fiber-optic acoustic mapper
Authors: Yao Baicheng , He Xinyue , Tan Teng , Chang Bing , Xiang Jinlong , Yang Ziyi , Wang Shangce , Wang Zeping , Liang Yupei , Zhou Heng , Huang Yongjun , Yan Yingzhan , Su Yikai , Rao Yun-Jiang , Wu Yu , Guo Xuhan
Published: April 2024

Sense of hearing is a fairly basic but extraordinary feature in nature. It involves a complicated interplay of multi-dimensional signal detection, transmission, and analysis to fully accomplish acoustic detection, orientation, localization and recognition. Conventional design of a listening system typically necessitates numerous hardware components and intricate software interactions. Here, by assembling stabilized dual-microcombs, passive optical elements, optoelectronic photodetectors, electronic processors all-on-chip along with a fiber optic microphone array, we present an integrated optic-acoustic sensing and localization system that demonstrates coherent parallelism and compact integration. Our study establishes a paradigm in which an integrated soliton microcomb can simultaneously drive and demodulate networking sensors, thus overcoming the technological gaps between silicon-based photonics and fiber optic sensing technology. Utilizing two microcomb chips as the core, we boast sensitive optical acoustic detection, precise acoustic localization, and swift acoustic tracing capabilities together. Leveraging the unique advantages of soliton microcombs especially low noise and multi-channel outputs, we achieve a minimum detectable acoustic pressure of 0.79 μPa/Hz^(1/2) and a localization error of less than 1 cm. We further demonstrate its efficacy by detecting, tracking and identifying different targets such as a small drone in a field setting. Such a fusion of dual-comb technology and sensor-networking scheme could be a significant step towards the design of future listening systems.
Experimental characterization of wear and failure modes depending on different loading conditions applied on cylindrical polyamide 66 gears
Authors: Hriberšek Matija , Kulovec Simon
Published: April 2024

Engineering plastics are increasingly used for engineering applications, such as the automotive sector, e-mobility sector, and household appliances. The use of engineering plastics is conditioned by the lack of knowledge of their material properties, especially for gears. A selection of the materials for a given gear pair has a significant impact on the mechanical and thermal response of the whole system. In this paper, steel-Polyamide 66 gear pairs were tested under various torques to define failure life and associated failure modes of the polymer gears. Additionally, to discover new knowledge on the field of tribological contact between observed gear pairs, meshing temperatures were monitored and correlated with calculated wear coefficients of Polyamide 66 material according to technical guideline VDI2736-2. The results show that gear flank wear of PA66 HT is directly proportional to the meshing temperature and torque. Thermal melting is a characteristic failure mode of the polymer gears which are exposed to higher load levels. In the middle torques, the dominant failure mode is flank fracture known as pitch point fracture. The greater impact of the gear wear mechanism occurs at lower torques where initial crack propagation starts at the pitch point and ends in the tooth root area.
Characterizations and dielectric properties of Ag2O/Chitosan nanocomposites a combined impedimetric and computational study
Authors: Bashal Ali , Abdel-Basset T.A. , Alkayal Nazeeha S. , Habeeb Talaat , Khalil Khaled
Published: April 2024

We have synthesized nanocomposite films of silver oxide nanoparticles loaded on chitosan (Ag2O/CS) with different nanoparticle weight percentages. The Ag2O/CS nanocomposites were analysed using several techniques, including FTIR, SEM, EDX, TGA, and complete density functional theory analysis. The measured dielectric properties (via impedance spectroscopy) of the nanocomposite films are featured by an increase in the permittivity with the increase of the Ag2O content, suggesting that the underlying polarization mechanism is of the Maxwell-Wagner-Sillars type at the Ag2O/CS interfaces. Moreover, the film conductivities are governed by the correlated barrier hopping conduction between the nanoparticle sites. Semiempirical quantum calculations of the frontier orbitals show that the Ag2O/CS structure is stable and reactive. These electrochemical properties of our Ag2O/CS combined with the well-known antibacterial activities of Ag nanoparticles render the Ag2O/CS as a nanocomposite with a wide range of catalytic, biochemical and electrical applications.
Depleted housing elicits cardiopulmonary dysfunction after a single flaming eucalyptus wildfire smoke exposure in a sex-specific manner in ApoE knockout mice
Authors: Fiamingo Michelle , Toler Sydnie , Lee Kaleb , Oshiro Wendy , Krantz Todd , Evansky Paul , Davies David , Gilmour M. Ian , Farraj Aimen , Hazari Mehdi S.
Published: April 2024

Although it is well established that wildfire smoke exposure can increase cardiovascular morbidity and mortality, the combined effects of non-chemical stressors and wildfire smoke remains understudied. Housing is a non-chemical stressor that is a major determinant of cardiovascular health, however, disparities in neighborhood and social status have exacerbated the cardiovascular health gaps within the United States. Further, pre-existing cardiovascular morbidities, such as atherosclerosis, can worsen the response to wildfire smoke exposures. This represents a potentially hazardous interaction between inadequate housing and stress, cardiovascular morbidities, and worsened responses to wildfire smoke exposures. The purpose of this study was to examine the effects of enriched (EH) versus depleted (DH) housing on pulmonary and cardiovascular responses to a single flaming eucalyptus wildfire smoke (WS) exposure in male and female apolipoprotein E (ApoE) knockout mice, which develop an atherosclerosis-like phenotype. The results of this study show that cardiopulmonary responses to WS exposure occur in a sex-specific manner. EH blunts adverse WS-induced ventilatory responses, specifically an increase in tidal volume (TV), expiratory time (Te), and relaxation time (RT) after a WS exposure, but only in females. EH also blunted a WS-induced increase in isovolumic relaxation time (IVRT) and the myocardial performance index (MPI) 1-wk after exposures, also only in females. Our results suggest that housing alters the cardiovascular response to a single WS exposure, and that DH might cause increased susceptibility to environmental exposures that manifest in altered ventilation patterns and diastolic dysfunction in a sex-specific manner.
Ecological Inference for Relative Risks, with Application to Infrequent Mental Health Events
Authors: Congdon Peter
Published: April 2024

Mental health outcomes may show wide contrasts in incidence or prevalence between ethnic groups, often for relatively infrequent events (e.g. suicide). To gauge such relativities, one ideally seeks age standardised comparisons, given that ethnic groups may differ in age structure, and that the events themselves often show wide disparities in risk between ages. It is also advantageous to provide a geographically disaggregated (e.g. neighbourhood) perspective on relative risk differences, with sampling densities (e.g. Poisson) appropriate to possibly infrequent events. Often only total disease counts (with no socio-demographic disaggregation) are available for neighbourhoods, though data on ethnic mix (e.g. Census data) are available. We consider in this paper an ecological inference method, applicable to infrequent events, which can use such information, and which furthermore takes account of the impacts of neighbourhood age structure on the health outcome. We consider two case studies to estimate age standardised relative risks by neighbourhood and ethnicity, one involving suicide, the other concerning psychosis. The analyses are for 6856 neighbourhoods in England.
Stability Investigations and Insights on the Pseudodepth Domain- Based (1 st -order Riemannian Solver) Seismic Wavefield Modeling
Authors: MUHAMMED HUSSEIN , Li Zhenchun , Gadelmula Abdelhafiz
Published: April 2024

The enlightenment of Earth's nether regions presents itself as a matter of profound intrigue. A novel and avant-garde method, known as the Least-squares reverse-time migration is considered as the cutting-edge seismic imaging technique due to its outstanding structural irradiating. Its procedure consumes a lot of time and occupies huge memory amounts thus wavefield extrapolation has been juxtaposed in a Riemannian coordinate system to transform the vertical axis to overcome the above-mentioned issues and oversampling/aliasing for modelling deeper parts of the seismic section. The problem of stabilizing this Riemannian wavefield arises from the introduction of the mapping velocity and the vertical axis operator that converts the finite difference solution partially from time into frequency domains. For every point in the Cartesian space, there is a corresponding vertical-time point with the coordinates hence we can interpolate the reconstructed source wavefield by drawing a Cartesian-to-Riemannian mapping function. Our stability and convergence analysis suggests that the spatial derivatives of 1st order Riemannian axis can be approximated by a Fourier pseudo-spectral methods as well as fast-Fourier transform using a special Gaussian-like impulse function to generate the vector-matrix of the source term within the finite-difference operator, in addition to the mapping velocity, which is a differential form of the initial input velocity model, manifestly controls the CFL conditions of the associated Riemannian-finite difference operator. Numerical and synthetic examples indicate that this approach is more stable and efficient in extrapolating a smooth Riemannian wavefield while maintaining Claerbout’s principle for locating subsurface reflectors also choosing an appropriate sampling rate for the new vertical axis is related inversely by the maximum frequency of the impulse wavelet and directly with minimum velocity value in the given model.
Synthesis and characterization of copper bismuth oxide/rGO nanocomposite by sonochemical method and investigation of its photocatalytic performance in dibenzothiophene desulfurization
Authors: Tahmasbi Mohammad Reza , Mousavi-Kamazani Mehdi , Keramati Narjes
Published: April 2024

In order to improve the efficiency of desulfurization of petroleum derivatives, copper bismuth oxide/reduced graphene oxide (Bi7.38Cu0.62O11.69/rGO) nanocomposite was synthesized by sonochemical method. The synthesized nanocomposite was identified by FESEM, FT-IR, XRD, DRS, and EDS analyses. Based on XRD analysis, pure copper bismuth oxide is formed using hydrazine, while using sodium hydroxide does not lead to the desired product. FESEM images showed that the size of Bi7.38Cu0.62O11.69 particles decreases in the presence of rGO. The desulfurization results showed that the presence of rGO causes a significant increase in efficiency due to increased light absorption and reduced recombination rate, so that Bi7.38Cu0.62O11.69/rGOnanocomposite has an efficiency of 87%, while pure Bi7.38Cu0.62O11.69 has an efficiency of 68%. Also, it was found that the purity of the copper bismuth oxide has a great effect on the photocatalytic efficiency, so that by calcining the product and removing the impurities, the efficiency increases from 55% to 68%.
Quality Evaluation of Urban Low-carbon Development based on Fermatean Fuzzy Regret Theory Model
Authors: Pan Yan
Published: April 2024

In response to the complexity and fuzziness of the evaluation environment for urban low-carbon development quality, and by integrating the regret avoidance psychology of experts in the evaluation process, this paper proposes a Fermatean fuzzy regret-theory multi-index decision-making model incorporating bidirectional projection. Firstly, considering the defects of misjudgment of similarity and unlimited range of projection values in the projection, a novel Fermatean fuzzy bidirectional projection method is proposed. Secondly, since the conflictiveness of indexes should only be related to the degree of association of the indexes, independent of the positive and negative signs, a CRITIC (CRiteria Importance Through Intercriteria Correlation) weight assignment method harmonizing with Fermatean fuzzy bidirectional projection is proposed to eliminate the influence of the positive and negative signs of similarity on the weighting results. Finally, the viability of the presented model is verified by urban low-carbon development quality cases, and a comparison analysis is also conducted to show the superiority of the presented method.
AstroPlant Sentinel: Next-Gen Space AgricultureMonitoring and ADS
Authors: Das Rajdeep , Sharma Vaishnavi , Kumari Priyanka
Published: April 2024

With the expanding role of humanity in outer space, sustainable food production becomes crucial. The success of space farming is determined as much by thecultivation of crops as by the rigorous monitoring and control of environmentalfactors. In this undertaking, we are pleased to offer you AstroPlant Sentinel, acombination of IoT technology with ADS custom-made for space farming. Ourresearch stresses the need for real-time environmental monitoring within spaceshuttles, where any deviations from environmental conditions may lead to plantillness and drop in crop yield. To address this challenge, we designed a miniature IoT environment equipped with three key sensors: Soil Moisture Sensor,Sensor for Temperature and Humidity, and Air Quality Sensor. Through intensive experiments and sensitivity analysis, we discover what are the thresholdsof these factors that are suitable for plant growth in space. However, recognizing the inherent variability and occasional aberrations in environmental data,we delve into the development and evaluation of three distinct machine learningmodels for anomaly detection: One-Class Support Vector Machines (OCSVM),Isolation Forest, and Density-Based Spatial Clustering of Applications with Noise(DBSCAN). Essentially, our results prove that DBSCAN outperforms other techniques in finding out the anomalies in fluctuating data. Lastly, our methodologyfor data visualization using a Software as a Service (SaaS) cloud platform isthoroughly detailed, which improves interpretability and enables informed decision making. This paper identifies the synergy between IoT-based monitoring and advanced anomaly detection, which is instrumental in enhancing both therobustness and efficacy of space agriculture attempts.