bluuebunny/crossref_metadata_2025 huggingface dataset:
Iron overload accelerated lipid metabolism disorder and liver injury in rats with non-alcoholic fatty liver disease
Authors: Zhang Lijia , Dai Xuezheng , Wang Li , Cai Jingming , Shen Jie , Shen Yang , Li Xianan , Zhao Yan
Published: October 2022

Background/aims

Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide. Iron overload has been implicated in chronic non-communicable liver diseases, but its relationship with NAFLD remains unclear. This study aimed to investigate the underlying roles of iron overload in the development of NAFLD.

Methods

Male Sprague Dawley rats were fed with a high-fat diet (HFD) and/or iron for 8, 12, and 20 weeks. Some rats fed with HFD plus iron also received intraperitoneal injection of deferoxamine (DFO) for 8 weeks. Liver steatosis, lipid metabolism and injury were evaluated.

Results

A NAFLD model, including typical liver steatosis, was established by feeding rats with a HFD, while iron overload alone is not enough to induce severe NAFL. Compared with rats fed a HFD, excess iron further increased lipid accumulation, serum levels of lipids, enzymes of liver function, and expression levels of CD36 and FAS in rat liver. In addition, iron overload decreased the activities of antioxidative enzymes in liver compared with HFD rats. The levels of CPT1 and the ratios of p-ACC/ACC were also decreased by iron overload. DFO effectively reversed the abnormal lipid metabolism and liver damage induced by a high-fat, high-iron diet.

Conclusion

A HFD plus iron overload might synergistically aggravate lipid metabolism disorders, liver injury, and oxidative damage, compared with a HFD alone. DFO might help to alleviate lipid metabolism dysfunction and improve the pathogenesis of NAFLD.
Automated data preparation for in vivo tumor characterization with machine learning
Authors: Krajnc Denis , Spielvogel Clemens P. , Grahovac Marko , Ecsedi Boglarka , Rasul Sazan , Poetsch Nina , Traub-Weidinger Tatjana , Haug Alexander R. , Ritter Zsombor , Alizadeh Hussain , Hacker Marcus , Beyer Thomas , Papp Laszlo
Published: October 2022

Background

This study proposes machine learning-driven data preparation (MLDP) for optimal data preparation (DP) prior to building prediction models for cancer cohorts.

Methods

A collection of well-established DP methods were incorporated for building the DP pipelines for various clinical cohorts prior to machine learning. Evolutionary algorithm principles combined with hyperparameter optimization were employed to iteratively select the best fitting subset of data preparation algorithms for the given dataset. The proposed method was validated for glioma and prostate single center cohorts by 100-fold Monte Carlo (MC) cross-validation scheme with 80-20% training-validation split ratio. In addition, a dual-center diffuse large B-cell lymphoma (DLBCL) cohort was utilized with Center 1 as training and Center 2 as independent validation datasets to predict cohort-specific clinical endpoints. Five machine learning (ML) classifiers were employed for building prediction models across all analyzed cohorts. Predictive performance was estimated by confusion matrix analytics over the validation sets of each cohort. The performance of each model with and without MLDP, as well as with manually-defined DP were compared in each of the four cohorts.

Results

Sixteen of twenty established predictive models demonstrated area under the receiver operator characteristics curve (AUC) performance increase utilizing the MLDP. The MLDP resulted in the highest performance increase for random forest (RF) (+0.16 AUC) and support vector machine (SVM) (+0.13 AUC) model schemes for predicting 36-months survival in the glioma cohort. Single center cohorts resulted in complex (6-7 DP steps) DP pipelines, with a high occurrence of outlier detection, feature selection and synthetic majority oversampling technique (SMOTE). In contrast, the optimal DP pipeline for the dual-center DLBCL cohort only included outlier detection and SMOTE DP steps.

Conclusions

This study demonstrates that data preparation prior to ML prediction model building in cancer cohorts shall be ML-driven itself, yielding optimal prediction models in both single and multi-centric settings.
Evaluation of the differentiation of benign and malignant breast lesions using synthetic relaxometry and the Kaiser score
Authors: Meng Lingsong , Zhao Xin , Guo Jinxia , Lu Lin , Cheng Meiying , Xing Qingna , Shang Honglei , Wang Kaiyu , Zhang Bohao , Lei Dongmei , Zhang Xiaoan
Published: October 2022

Objective

To investigate whether there is added value of quantitative parameters from synthetic magnetic resonance imaging (SyMRI) as a complement to the Kaiser score (KS) to differentiate benign and malignant breast lesions.

Materials and methods

In this single-institution study, 122 patients who underwent breast MRI from March 2020 to May 2021 were retrospectively analyzed. SyMRI and dynamic contrast-enhanced MRI were performed using a 3.0-T system. Two experienced radiologists independently assigned the KS and measured the quantitative values of T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) from SyMRI. Pathology was regarded as the gold standard. The diagnostic values were compared using the appropriate statistical tests.

Results

There were 122 lesions (86 malignant and 36 benign) in 122 women. The T1 value was identified as the only independent factor for the differentiation of malignant and benign lesions. The diagnostic accuracy of incorporating the T1 into the KS protocol (T1+KS) was 95.1% and 92.1% for all lesions (ALL) and The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions, respectively, which was significantly higher than that of either T1 (ALL: 82.8%, P = 0.0001; BI-RADS 4: 78.9%, P = 0.002) or KS (ALL: 90.2%, P = 0.031; BI-RADS 4: 84.2%, P = 0.031) alone. The sensitivity and specificity of T1+KS were also higher than those of the T1 or KS alone. The combined diagnosis could have avoided another 15.6% biopsies compared with using KS alone.

Conclusions

Incorporating T1 into the KS protocol improved both the sensitivity and specificity to differentiate benign and malignant breast lesions, thus avoiding unnecessary invasive procedures.
Risk of major adverse events associated with gabapentinoid and opioid combination therapy: A systematic review and meta-analysis
Authors: Hahn Jongsung , Jo Youngkwon , Yoo So Hee , Shin Jaekyu , Yu Yun Mi , Ah Young-Mi
Published: October 2022

Background: The use of opioid–gabapentinoid combinations has increased, raising several safety concerns. However, meta-analysis studies focusing on this issue are limited.

Objective: To evaluate the risk of central nervous system (CNS) depression, gastrointestinal (GI) adverse events, and mortality of combination therapy compared with those of opioid therapy and to explore the differences in the results according to study design and indications.

Methods: Relevant studies were selected (published before 30 January 2022) by searching the MEDLINE, Embase, and CENTRAL databases. The pooled odds ratios (OR) with 95% confidence intervals (CI) of the outcomes were estimated using the Mantel–Haenszel method. Subgroup and meta-regression analyses were performed according to study characteristics. Quality assessment was conducted using the Risk of Bias 2 tool for randomized controlled trials (RCTs) and Cochrane Collaboration’s Risk of Bias in non-RCTs tool for non-randomized trials.

Results: Adverse events were reported in 26 RCTs and 7 non-RCTs, and mortality was reported in 10 non-RCTs. Compared to opioid therapy, dizziness, cognitive dysfunction, and respiratory depression in combination therapy significantly increased in non-RCTs (OR 3.26, 95% CI 1.82–5.85; OR 3.13, 95% CI 1.51–6.50; OR 1.71, 95% CI 1.31–2.24, respectively), and a similar trend for dizziness and cognitive dysfunction was also identified in the RCT analysis, although the difference was not significant. Combination therapy for cancer pain was associated with the highest risk of sedation in subgroup analysis. Combination therapy significantly decreased the risk of GI adverse events, including nausea, vomiting, and constipation. The mortality risk associated with combination therapy was higher than that associated with opioid therapy (OR 2.76, 95% CI 1.26–6.05).

Conclusion: Opioid-gabapentinoid combination therapy could be associated with an increased risk of CNS depression and mortality, despite tolerable GI adverse events. These data suggest that combination therapy requires close monitoring of CNS depression, especially in cancer patients. Caution is needed in interpreting the clinical meanings owing to the lack of risk difference in respiratory depression in the RCT-only analysis and the absence of RCT or prospective studies investigating mortality.
Systematic transcriptome analysis reveals molecular mechanisms and indications of bupleuri radix
Authors: Park Sang-Min , Kim Aeyung , Lee Haeseung , Baek Su-Jin , Kim No Soo , Park Musun , Yi Jin-Mu , Cha Seongwon
Published: October 2022

Pharmacogenomic analysis based on drug transcriptomic signatures is widely used to identify mechanisms of action and pharmacological indications. Despite accumulating reports on the efficacy of medicinal herbs, related transcriptome-level analyses are lacking. The aim of the present study was to elucidate the underlying molecular mechanisms of action of Bupleuri Radix (BR), a widely used herbal medicine, through a systematic transcriptomic analysis. We analyzed the drug-responsive transcriptome profiling of A549 lung cancer cell line after treating them with multiple doses of BR water (W-BR) and ethanol (E-BR) extracts and their phytochemicals. In vitro validation experiments were performed using both A549 and the immortalized human keratinocyte line HaCaT. Pathway enrichment analysis revealed the anti-cancer effects of BR treatment via inhibition of cell proliferation and induction of apoptosis. Enhanced cell adhesion and migration were observed with the W-BR but not with the E-BR. Comparison with a disease signature database validated an indication of the W-BR for skin disorders. Moreover, W-BR treatment showed the wound-healing effect in skin and lung cells. The main active ingredients of BR showed only the anti-cancer effect of the E-BR and not the wound healing effect of the W-BR, suggesting the need for research on minor ingredients of BR.
Baiying qingmai formulation ameliorates thromboangiitis obliterans by inhibiting HMGB1/RAGE/NF-κB signaling pathways
Authors: Zou Chongchong , Liu Li , Huang Chuanqi , Hu Song
Published: October 2022

Baiying Qingmai Formulation (BF) is a classical clinical prescription used for decades to treat thromboangiitis obliterans (TAO). Although it effectively relieves pain and ischemic ulcers in patients with TAO, its anti-TAO mechanisms remain unclear. The chemical components of BF were analyzed using high-performance liquid chromatography and the potential targets of the compounds identified in BF were analyzed using molecular docking. Further, the signaling pathways and molecular mechanism of BF in treating TAO were studied using a rat model of TAO. Seven compounds (gallic acid, catechin, chlorogenic acid, caffeic acid, paeoniflorin, quercetin, and paeonol) were identified in BF, and molecular docking predicted their high affinities with HMGB1/RAGE/NF-κB proteins. In in vivo studies, BF not only inhibited the protein expression of HMGB1, RAGE, ICAM-1, and VCAM-1; mRNA levels of HMGB1 and RAGE; and the phosphorylation of NF-κB, ERK, Janus kinase (JNK) and p38 MAPK in the femoral artery, but also reduced the levels of inflammatory cytokines (IL-6, TNF-α, IL-1β, HMGB1) and stable metabolite (TXB2) of cytokine promoting thrombosis (TXA2) in the plasma. Moreover, BF stimulated the secretion of stable metabolite (6-keto-PGF1α) of cytokine inhibiting thrombosis (PGI2) in the plasma. BF inhibited the inflammatory response and thrombosis in the femoral artery, thus reducing the degree of vascular occlusion, which alleviated the symptoms in rats with TAO. Our findings suggest that BF ameliorates TAO by inhibiting the activation of the ERK, JNK, p38 MAPK and HMGB1/RAGE/NF-κB signaling pathways, thereby providing novel ideas for the treatment of TAO and essential information for the further development and utilization of BF as a promising drug to treat TAO.
A multi-task FP-GNN framework enables accurate prediction of selective PARP inhibitors
Authors: Ai Daiqiao , Wu Jingxing , Cai Hanxuan , Zhao Duancheng , Chen Yihao , Wei Jiajia , Xu Jianrong , Zhang Jiquan , Wang Ling
Published: October 2022

PARP (poly ADP-ribose polymerase) family is a crucial DNA repair enzyme that responds to DNA damage, regulates apoptosis, and maintains genome stability; therefore, PARP inhibitors represent a promising therapeutic strategy for the treatment of various human diseases including COVID-19. In this study, a multi-task FP-GNN (Fingerprint and Graph Neural Networks) deep learning framework was proposed to predict the inhibitory activity of molecules against four PARP isoforms (PARP-1, PARP-2, PARP-5A, and PARP-5B). Compared with baseline predictive models based on four conventional machine learning methods such as RF, SVM, XGBoost, and LR as well as six deep learning algorithms such as DNN, Attentive FP, MPNN, GAT, GCN, and D-MPNN, the evaluation results indicate that the multi-task FP-GNN method achieves the best performance with the highest average BA, F1, and AUC values of 0.753 ± 0.033, 0.910 ± 0.045, and 0.888 ± 0.016 for the test set. In addition, Y-scrambling testing successfully verified that the model was not results of chance correlation. More importantly, the interpretability of the multi-task FP-GNN model enabled the identification of key structural fragments associated with the inhibition of each PARP isoform. To facilitate the use of the multi-task FP-GNN model in the field, an online webserver called PARPi-Predict and its local version software were created to predict whether compounds bear potential inhibitory activity against PARPs, thereby contributing to design and discover better selective PARP inhibitors.
Filling model of oil and polar liquid for electrowetting displays based on phase change
Authors: Jiang Hongwei , Qian Rongzhen , Chen Wenwen , Zhou Rui , Zhou Guofu
Published: October 2022

Reflective displays have recently attracted more and more attention because of the advantages of low power consumption and eye protection. Among them, electrowetting display (EWD) is the most potential reflective display technology due to its full color and video speed advantages. However, filling models of oil and polar liquids in EWD fabrication were rarely reported. In this paper, a phase change filling model was proposed, and its related equipment was designed and manufactured. The efficiency of phase change filling model has a significant advantage compared to conventional filling models, which can finish the whole process of filling and coupling for 400*500 mm panel within 270 s while the efficiency of other filling models is over 10 min. Since the process of oil filled into the pixels was released into the air environment, the dosing method was significantly enriched, and dosing accuracy was more controllable. The experimental results showed that, a good response time and a high pixel aperture ratio of 31.78 ms and 68.2% can be obtained, respectively.
Game theory approaches for autonomy
Authors: Dennis Steven , Petry Fred , Sofge Donald
Published: October 2022

Game theory offers techniques for applying autonomy in the field. In this mini-review, we define autonomy, and briefly overview game theory with a focus on Nash and Stackleberg equilibria and Social dilemma. We provide a discussion of successful projects using game theory approaches applied to several autonomous systems.
Virtual Reality “exergames”: A promising countermeasure to improve motivation and restorative effects during long duration spaceflight missions
Authors: Keller Nathan , Whittle Richard S. , McHenry Neil , Johnston Adam , Duncan Colton , Ploutz-Snyder Lori , Torre Gabriel G. De La , Sheffield-Moore Melinda , Chamitoff Gregory , Diaz-Artiles Ana
Published: October 2022

Long duration spaceflight missions will require novel exercise systems to protect astronaut crew from the detrimental effects of microgravity exposure. The SPRINT protocol is a novel and promising exercise prescription that combines aerobic and resistive training using a flywheel device, and it was successfully employed in a 70-day bed-rest study as well as onboard the International Space Station. Our team created a VR simulation to further augment the SPRINT protocol when using a flywheel ergometer training device (the Multi-Mode Exercise Device or M-MED). The simulation aspired to maximal realism in a virtual river setting while providing real-time biometric feedback on heart rate performance to subjects. In this pilot study, five healthy, male, physically-active subjects aged 35 ± 9.0 years old underwent 2 weeks of SPRINT protocol, either with or without the VR simulation. After a 1-month washout period, subjects returned for a subsequent 2 weeks in the opposite VR condition. We measured physiological and cognitive variables of stress, performance, and well-being. While physiological effects did not suggest much difference with the VR condition over 2 weeks, metrics of motivation, affect, and mood restoration showed detectable differences, or trended toward more positive outcomes than exercise without VR. These results provide evidence that a well-designed VR “exergaming” simulation with biometric feedback could be a beneficial addition to exercise prescriptions, especially if users are exposed to isolation and confinement.
Radar-based remote physiological sensing: Progress, challenges, and opportunities
Authors: Islam Shekh Md Mahmudul
Published: October 2022

Modern microwave Doppler radar-based physiological sensing is playing an important role in healthcare applications and during the last decade, there has been a significant advancement in this non-contact respiration sensing technology. The advantages of contactless, unobtrusive respiration monitoring have drawn interest in various medical applications such as sleep apnea, sudden infant death syndromes (SIDS), remote respiratory monitoring of burn victims, and COVID patients. This paper provides a perspective on recent advances in biomedical and healthcare applications of Doppler radar that can detect the tiny movement of the chest surfaces to extract heartbeat and respiration and its associated different vital signs parameters (tidal volume, heart rate variability (HRV), and so on) of the human subject. Additionally, it also highlights the challenges, and opportunities of this remote physiological sensing technology and several future research directions will be laid out to deploy this sensor technology in our day-to-day life.
Rice Chalky Grain 5 regulates natural variation for grain quality under heat stress
Authors: Chandran Anil Kumar Nalini , Sandhu Jaspreet , Irvin Larissa , Paul Puneet , Dhatt Balpreet K. , Hussain Waseem , Gao Tian , Staswick Paul , Yu Hongfeng , Morota Gota , Walia Harkamal
Published: October 2022

Heat stress occurring during rice (Oryza sativa) grain development reduces grain quality, which often manifests as increased grain chalkiness. Although the impact of heat stress on grain yield is well-studied, the genetic basis of rice grain quality under heat stress is less explored as quantifying grain quality is less tractable than grain yield. To address this, we used an image-based colorimetric assay (Red, R; and Green, G) for genome-wide association analysis to identify genetic loci underlying the phenotypic variation in rice grains exposed to heat stress. We found the R to G pixel ratio (RG) derived from mature grain images to be effective in distinguishing chalky grains from translucent grains derived from control (28/24°C) and heat stressed (36/32°C) plants. Our analysis yielded a novel gene, rice Chalky Grain 5 (OsCG5) that regulates natural variation for grain chalkiness under heat stress. OsCG5 encodes a grain-specific, expressed protein of unknown function. Accessions with lower transcript abundance of OsCG5 exhibit higher chalkiness, which correlates with higher RG values under stress. These findings are supported by increased chalkiness of OsCG5 knock-out (KO) mutants relative to wildtype (WT) under heat stress. Grains from plants overexpressing OsCG5 are less chalky than KOs but comparable to WT under heat stress. Compared to WT and OE, KO mutants exhibit greater heat sensitivity for grain size and weight relative to controls. Collectively, these results show that the natural variation at OsCG5 may contribute towards rice grain quality under heat stress.
Effect of diffuse fraction on gross primary productivity and light use efficiency in a warm-temperate mixed plantation
Authors: Liu Peirong , Tong Xiaojuan , Zhang Jinsong , Meng Ping , Li Jun , Zhang Jingru , Zhou Yu
Published: October 2022

Diffuse radiation (If) is one of important variables determining photosynthetic rate and carbon uptake of forest ecosystems. However, the responses of gross primary productivity (GPP) and light use efficiency (LUE) to diffuse fraction (DF) are still poorly understood. We used a 6-year dataset of carbon flux at a warm-temperate mixed plantation site in North China to explore the impacts of DF on GPP and LUE. During 2011-2017, ecosystem apparent quantum yield (α) and photosynthesis at photosynthetically active radiation (PAR) of 1800 µmol m-2 s-1 (P1800) on cloudy days were 63% and 17% higher than on clear days, respectively. Under lower vapor pressure deficit (VPD) and air temperature (Ta) conditions, canopy photosynthesis was significantly higher on cloudy skies than on clear skies. On half-hourly scale, increased DF enhanced α and P1800. Daily GPP peaked at a median DF (=0.5), while daily LUE significantly increased with DF (p<0.01). Both GPP and LUE were mainly controlled directly by DF and PAR. DF had an indirect effect on LUE and GPP mainly through PAR. At high DF levels (>0.5), the increase in LUE did not make GPP enhancement. The direct effect of DF on GPP and LUE under lower Ta and VPD was more sensitive than under higher Ta and VPD. When DF was incorporated into the Michaelis-Menten model, it performed well in the GPP estimation, and the determination coefficient increased by 32.61% and the root mean square error decreased by 25.74%. These findings highlight the importance of incorporating DF into carbon sequestration estimation in North China.
Pavlovian threat learning shapes the kinematics of action
Authors: Starita Francesca , Garofalo Sara , Dalbagno Daniela , Degni Luigi A. E. , di Pellegrino Giuseppe
Published: October 2022

Prompt response to environmental threats is critical to survival. Previous research has revealed mechanisms underlying threat-conditioned physiological responses, but little is known about how threats shape action. Here we tested if threat learning shapes the kinematics of reaching in human adults. In two different experiments conducted on independent samples of participants, after Pavlovian threat learning, in which a stimulus anticipated the delivery of an aversive shock, whereas another did not, the peak velocity and acceleration of reaching increased for the shocked-paired stimulus, relative to the unpaired one. These kinematic changes appeared as a direct consequence of learning, emerging even in absence of an actual threat to body integrity, as no shock occurred during reaching. Additionally, they correlated with the strength of sympathetic response during threat learning, establishing a direct relationship between previous learning and subsequent changes in action. The increase in velocity and acceleration of action following threat learning may be adaptive to facilitate the implementation of defensive responses. Enhanced action invigoration may be maladaptive, however, when defensive responses are inappropriately enacted in safe contexts, as exemplified in a number of anxiety-related disorders.
Influence of motivation and academic performance in the use of Augmented Reality in education. A systematic review
Authors: Amores-Valencia Antonio , Burgos Daniel , Branch-Bedoya John W.
Published: October 2022

The recent technologies rise today as a tool of significant importance today, especially in the educational context. In this sense, Augmented Reality (AR) is a technology that is achieving a greater presence in educational centers in the last decade. However, Augmented Reality has not been explored in depth at the Secondary Education stage. Due to this, it is essential to analyze and concentrate the scientific research developed around this educational technology at that stage. Therefore, the aim of this research is to describe the influence that Augmented Reality shows on the motivation and academic performance of students in the Secondary Education stage. In relation to the methodology, a systematic review of the literature has been conducted using the Kitchenham protocol, where several factors have been analyzed, such as subjects, activities, and electronic implementation devices, together with the effects on motivation and student's academic performance. The Scopus and Web of Science (WoS) databases have been used to search for scientific papers, with a total of 344 investigations being analyzed between 2012 and 2022. The methodological stages considered were the formulation of research questions, the choice of data sources, search strategies, inclusion and exclusion criteria and quality assessment, and finally, data extraction and synthesis. The results obtained have shown that the use of AR in the classroom provides higher levels of motivation, reflected by factors such as attention, relevance, confidence, and satisfaction, and reflects better results in the tests carried out on the experimental groups compared to the control groups, which means an improvement in the academic performance of students. These results supply a fundamental theoretical basis, where the different teachers should be supported for the incorporation of AR in the classroom, since how this educational technology has been shown offers great opportunities. Likewise, the development of research in areas not so addressed can further clarify the generality of AR based on its influence on learning. In addition, the fields of natural sciences and logical-mathematical have been the most addressed, managing to implement their contents through object modeling. In short, this research highlights the importance of incorporating Augmented Reality into all areas and educational stages, since it is a significant improvement in the teaching and learning process.
Factors influencing consumers’ willingness to accept service robots: Based on online reviews of Chinese hotels
Authors: Chang Cheng , Shao Bingjia , Li Yong , Zhang Yong
Published: October 2022

The application of robots in service industry is increasing. Compared with related studies in other countries, the research on users’ acceptance of mid-range and high-range hotel service robots in China is preliminary. Based on the interaction between Chinese consumers and hotel service robots, this study explored the factors that influence consumers’ willingness to accept robots in human–robot interaction. According to the service robot integration willingness scale (performance efficacy, intrinsic motivation, anthropomorphism, social influence, facilitating conditions, and emotion), this study conducted content analysis and sentiment analysis on 4,107 online reviews from 68 mid-range and high-range hotels in Qunar. The results showed that users’ overall evaluation of robot service in mid-range and high-range hotels is positive. The most frequently mentioned dimension by users is performance efficacy, followed by intrinsic motivation, anthropomorphism, and emotion, finally, the facilitating conditions, the five dimensions have positive impact on users’ evaluation of service robots; the influence of social influence on human–robot interaction evaluation has not been found. This study supplements the research on service robot and provides a reference for hotel managers to make decisions.
The role of work-family conflict and job role identification in moderated mediating the relationship between perceived supervisor support and employee proactive behaviors
Authors: Wang Zhicheng
Published: October 2022

In recent years, the outbreak and persistence of COVID-19 has greatly changed the way people work, and encouraging employees to work online from home has become a new form of work for organizations responding to the epidemic. Based on the W-HR model, this paper explored supervisor support as a situational resource in the context of online office, aiming to verify the changes in work-family status caused by individuals facing the background of supervisor support, and then relate employees’ proactive behavior. Meanwhile, the predicted moderating effect of job role identification on supervisor support and work-family conflict was verified by considering the role identification generated in the positive interaction between employees and supervisors as individual resources. In this study, 555 employees from enterprises in the provinces of Jiangsu and Guangdong were selected as the research participants, and data were recovered at two time nodes. The results show that: (1) Perceived supervisor support significantly relates employee proactive behavior. (2) Work-family conflict mediates the relationship between perceived supervisor support and employee proactive behavior. (3) Job role identification has a significant moderating effect on the relationship between perceived supervisor support and work-family conflict, and high level of job role identification moderated the mediating effect of work-family conflict on perceived supervisor support and employee proactive behavior significantly. This paper expands the research perspective of employee proactive behavior. It can be used as a reference for enterprises to formulate strategies to improve employee proactive behavior in the process of digital reform.
Designing a conversational agent to promote teamwork and collaborative practices using design thinking: An explorative study on user experiences
Authors: Skov Sofie Smedegaard , Andersen Josefine Ranfelt , Lauridsen Sigurd , Bab Mads , Bundsbæk Marianne , Nielsen Maj Britt Dahl
Published: October 2022

Appearance, voice features, and communication style affect users trust in conversational agents (chatbots), but few studies have assessed what features users like and dislike. Using design thinking, we developed Susa, a conversational agent, to help workplaces promote teamwork and collaborative practices. Design thinking prioritizes co-creation and multidisciplinary teamwork to develop innovative solutions to complex problems. The aim of this qualitative study was to explore users’ interactions with and reactions toward Susa and explain how we used user inputs to adapt and refine the first prototype. The employees and managers from four workplaces participated in three workshops to test and refine the agent. We applied an explorative thematic analysis of data collected via video recordings of the workshops. The results of the analyses revealed that visual identity, communication style and personality was important for acceptability. Users favored a more human like agent that primarily communicated with the team via text messages. Users disliked emoticons and humor because these features clashed with the seriousness of the topic. Finally, users highlighted that Susa helped structure organizational change processes, develop concrete action plans, and stay on track. It is a weakness that Susa is a simple robot based on a preprogrammed script that does not allow users to adapt the process.
Artificial Intelligence and Human Psychology in Online Transaction Fraud
Authors: Firdaus Raheela , Xue Yang , Gang Li , Sibt e Ali Muhammad
Published: October 2022

Banking operations have changed due to technological advancement. On one hand, modernization in technology has facilitated the daily operation of banks; on the other hand, this has also resulted in an increase in the number of cyber-attacks. Artificial Intelligence has introduced new models to detect and prevent cybercrimes. Some fraud has also occurred due to the involvement of employees inside particular organizations. So, this study has focused on both sides: the machine as well as the human. Firstly, the research has focused on fraud diamond theory and has analyzed factors such as rationalization, capabilities, perceived pressure, and perceived opportunities to understand the psychology of the fraudster. Secondly, Artificial Intelligence characteristics, threat exposure, big data management, explainability, cost effectiveness, and risk prediction are evaluated to explore their use in fraud reduction in banks. The research data have been collected from 15 Banks in Pakistan with the help of a questionnaire using five-item Likert scales. The data have been analyzed using IBM SPSS Software. The results gained after correlation and regression analysis proved that Fraud diamond theory and AI characteristics have positive and significant effects on cybercrimes. This study is a great contribution to the banking industry of Pakistan as it provides a complete analysis to control fraud inside organizations by understanding the mindset of fraudsters with the help of fraud diamond theory. At the same time, outside fraud will be handled with the help of Artificial Intelligence. This will result in banks growth, which ultimately boosts the economy of a country.
Using English medium instruction to teach a general course in a College of Business and Management
Authors: Oraif Iman , Alrashed Mohammed
Published: October 2022

Even though learning can be complex when using a language other than one’s mother tongue, the English-medium communicative approach has been widely adopted in Saudi universities over recent years. Many universities in Saudi Arabia are teaching their courses through the medium of English rather than Arabic, as was previously the case. This also applies to the social and natural sciences. Moreover, instructors are trying to avoid using any Arabic in class, given that English has become the lingua franca in many domains. Thus, the current study seeks to understand how students in the College of Business and Management at Al-Imam University, Riyadh, Saudi Arabia feel about English being used as the medium of instruction (EMI) as they study general course. Also examined is the relationship between their previous language test scores and current reflections. Twenty-four female students participated in a survey adapted from generating results to reveal a positive attitude to using EMI on their course. However, no relationship was found between the participants’ language assessment test scores and current feelings.
Behavioral pathway to a broken heart: The link between adverse childhood experiences, depression, physical exercise and cardiovascular health
Authors: Bertele Sebastian , Heitland Ivo , Fraccarollo Daniela , Stapel Britta , Bauersachs Johann , Westhoff-Bleck Mechthild , Kahl Kai G.
Published: October 2022

Background and aim

Adverse childhood experiences (ACEs) are a major risk factor for unfavorable behavioral, mental and health outcomes later in life. However, the precise pathwayviawhich ACEs convey these risks, in particular regarding health outcomes such as cardiovascular disease, remains unknown. Here, we combined psychiatric and cardiac methods to investigate the pathwayviawhich childhood adversities may lead to adult adverse cardiovascular health, with a focus on epicardial adipose tissue (EAT) as a risk marker.

Methods

210 adult congenital heart disease outpatients (mean age 35.5 y, 43% female) completed a thorough cardiac and psychiatric evaluation. Psychiatric measurements included an expert interview, the childhood trauma questionnaire (CTQ), Beck's depression inventory II (BDI-II), quality of life and the global scale of functioning, amongst others. All patients completed a full cardiac workup including EAT assessment using echocardiography. We then computed bootstrapping mediation models using ACEs as a predictor, depression and physical activity as mediators and EAT as dependent variable in PROCESS.

Results

CTQ scores had a significant indirect effect on EATviaa serial mediation of BDI and physical activity [a*b2*d = 0.0260, 95% BCa CI [0.0047, 0.0619]].

Conclusion

Using mediation analyses, we show that adverse childhood events are linked to increased depressive symptoms, which are linked to decreased physical activity, which in turn are linked to a higher amount of epicardial adipose tissue. While other pathways most certainly exist and replication is needed, this suggests a meaningful pathwayviawhich ACEs lead to adverse cardiovascular health, with several potential targets for health interventions across time.
Potential productivity loss from uncorrected and under-corrected presbyopia in low- and middle-income countries: A life table modeling study
Authors: Ma Qian , Chen Min , Li Dehua , Zhou Ruiqing , Du Yali , Yin Shengjie , Chen Binyao , Wang Hongxi , Jiang Jiao , Guan Zhiqiang , Qiu Kunliang
Published: October 2022

Objective

To estimate the burden of potential productivity losses due to uncorrected and under-corrected presbyopia in LMICs among the working-age population in both the cross-sectional and longitudinal manner.

Methods

We extracted data for the prevalence of presbyopia from the Global Burden of Diseases (GBD), Injuries, and Risk Factors Study 2019. Data for the gross domestic product (GDP) per capita were extracted from the World Bank database and Central Intelligence Agency's World Factbook. We introduced life table models to construct age cohorts (in 5-year age groups) of the working-age population (aged from 40 to 64 years old) in LMICs, with simulated follow-up until 65 years old in people with and without uncorrected presbyopia. The differences in productivity-adjusted life years (PALYs) lived and productivity between these two cohorts were calculated. The potential productivity loss was estimated based on GDP per capita. The WHO standard 3% annual discount rate was applied to all years of life and PALYs lived.

Results

In 2019, there were 238.40 million (95% confidence interval [CI]: 150.92–346.78 million) uncorrected and under-corrected presbyopia cases in LMICs, resulting in 54.13 billion (current US dollars) (95% confidence interval [CI]: 34.34–79.02 billion) potential productivity losses. With simulated follow-up until retirement, those with uncorrected and under-corrected presbyopia were predicted to experience an additional loss of 155 million PALYs (an average loss of 0.7 PALYs per case), which was equivalent to a total loss of US$ 315 billion (an average loss of US$ 1453.72 per person).

Conclusions

Our findings highlight the considerable productivity losses due to uncorrected and under-corrected presbyopia in LMICs, especially in a longitudinal manner. There is a great need for the development of enabling eye care policies and programs to create access to eye care services, and more healthcare investment in the correction of presbyopia in the working-age population in LMICs. This study could provide evidences for some potential health-related strategies for socio-economic development.
Exploring gender biases in ML and AI academic research through systematic literature review
Authors: Shrestha Sunny , Das Sanchari
Published: October 2022

Automated systems that implement Machine learning (ML) and Artificial Intelligence (AI) algorithms present promising solutions to a variety of technological and non-technological issues. Although, industry leaders are rapidly adopting these systems for anything from marketing to national defense operations, these systems are not without flaws. Recently, many of these systems are found to inherit and propagate gender and racial biases that disadvantages the minority population. In this paper, we analyze academic publications in the area of gender biases in ML and AI algorithms thus outlining different themes, mitigation and detection methods explored through research in this topic. Through a detailed analysis of N = 120 papers, we map the current research landscape on gender specific biases present in ML and AI assisted automated systems. We further point out the aspects of ML/AI gender biases research that are less explored and require more attention. Mainly we focus on the lack of user studies and inclusivity in this field of study. We also shed some light into the gender bias issue as experienced by the algorithm designers. In conclusion, in this paper we provide a holistic view of the breadth of studies conducted in the field of exploring, detecting and mitigating gender biases in ML and AI systems and, a future direction for the studies to take in order to provide a fair and accessible ML and AI systems to all users.
Liquid crystal-polymer composites switchable windows for radiant energy flow and privacy control
Authors: Halder Suman , Shin Yunho , Zhou Ziyuan , Zhang Xinfang , Hu Lang , Yang Deng-Ke
Published: October 2022

Global warming is becoming a more and more severe crisis for humans. One way to resolve the concern is to reduce energy consumption. Smart switchable windows for office and residential buildings and vehicles can help reduce energy consumption. An ideal smart window should be able to control radiant energy flow and privacy. We investigated the capability of switchable windows based on liquid crystal/polymer composites, such as polymer dispersed liquid crystal (PDLC), polymer stabilized liquid crystal (PSLC), and polymer stabilized cholesteric texture (PSCT), to control the privacy and radiant energy flow. Through a systematic study, we identified methods to improve their capabilities. We demonstrated that PDLC and PSCT windows of sufficient thick film thickness can control both privacy and energy flow.
Anisotropic cloud string cosmological model with five-dimensional kaluza-klein space-time
Authors: Ray Pranjal Kumar , Roy Baruah Rajshekhar
Published: October 2022

Anisotropic cloud string cosmological models has been investigated in the context of five dimensional Kaluza- Klein space time. In this paper the energy momentum tensor is generated by rest energy density and tension density of the string with particle density attached to them. To obtained the exact solutions of the Einstein field equations we assumed a scale factor a(t)=e1β2βt+c where β and c are positive constant, which yields a variable deceleration parameter (DP) q=−aäȧ2=βH+α. The physical and geometrical behavior of the models is also discussed in detail.
The quiet sun at mm wavelengths as seen by ALMA
Authors: Alissandrakis Costas E. , Bastian T. S. , Brajša Roman
Published: October 2022

Solar observations at sub-mm, mm and cm wavelengths offer a straightforward diagnostic of physical conditions in the solar atmosphere because they yield measurement of brightness temperature which, for optically thick features, equals intrinsic temperature - much unlike solar diagnostics in other spectral ranges. The Atacama Large Millimeter and sub-millimeter Array (ALMA) has therefore opened a new, hitherto underexplored, spectral window for studying the enigmatic solar chromosphere. In this review we discuss initial ALMA studies of the quiet chromosphere that used both single-dish and compact-array interferometric observing modes. We present results on the temperature structure of the chromosphere, comparison with classic empirical models of the chromosphere, and observations of the chromospheric network and spicules. Furthermore, we discuss what may be expected in the future, since the ALMA capabilities continuously expand and improve towards higher angular resolution, wavelength coverage, and polarization measurement for magnetometry.
Effect of guanidine acetic acid on meat quality, muscle amino acids, and fatty acids in Tibetan pigs
Authors: Cui Yiyan , Tian Zhimei , Yu Miao , Liu Zhichang , Rong Ting , Ma Xianyong
Published: October 2022

This study investigated the effects of guanidine acetic acid (GAA) supplementation on growth performance, carcass traits, and meat quality in Tibetan pigs. A total of 18 male Tibetan pigs (21.35 ± 0.99 kg) were randomly assigned to the control (basal diet) and GAA (basal diet + 800 mg/kg GAA) groups for 125 days. Growth performance, carcass traits, and meat quality in pigs, and the chemical composition of Longissimus thoracis (LT) were not altered by GAA. In LT, compared to the control group, dietary GAA increased the superoxide dismutase activity, transcripts of stearoyl CoA desaturase (SCD) and fatty acid synthase (FAS), and contents of glutamate, glutamine, C24:0, C20:3n-6, C20:4n-6, and polyunsaturated fatty acids (P < 0.05), but it decreased the malondialdehyde content (P < 0.001). In back fat, dietary GAA reduced the transcript of peroxisome proliferator-activated receptor γ (PPARγ) and the contents of C10:0, C12:0, C14:0, and C16:0 (P < 0.05), whereas it increased the contents of C22:0, C20:1, C22:1, C24:1, C20:2, C20:3n-3, and C22:2 (P < 0.05). These findings will provide a basis for high-quality Tibetan pork production.
Climate-Smart Tillage Practices with Straw Return to Sustain Crop Productivity
Authors: Liu Zhen , Wang Ning , Lü Jinling , Wang Lan , Li Geng , Ning Tangyuan
Published: October 2022

Climate change seriously threatens global crop production. However, there are few reports on field crop yield and yield components based on long-term different climate conditions. The objectives of this study were to identify and compare the differences in crop yield and yield components in long-term tillage and straw returning under different climate regions. Conventional tillage (CT) and rotary tillage (RT) in combination with no straw return and whole straw return (S) were conducted under a wheat (Triticum aestivum L.)–maize (Zea mays L.) cropping system in cool-wet and warm-dry regions from 2010 to 2019. We hypothesized that long-term suitable tillage under warm-dry or cool-wet regions can increase the yield and components of wheat and maize, and temperature and precipitation had significant effects on crop yield and yield components. Conventional tillage with straw return (CTS) in the warm-dry region and rotary tillage with straw return (RTS) in the cool-wet region can increase the yield and yield components of wheat and maize, respectively, compared with CT. The yield stability of wheat was higher than that of maize under the two climate conditions. Compared with tillage practices, the effects of experimental sites and straw return on crop yield and yield components were more remarkable. The combination of mean temperature, annual precipitation, and yield components explained 75% and 100% of the variance in the wheat yield and maize yield, respectively. The thousand-kernel weight was the key factor in regulating wheat yield, and kernel number was the key factor in regulating maize yield. In conclusion, the combination of rotary tillage in cool-wet regions or conventional tillage in warm-dry regions with straw return is a good technique for increasing crop security.