Miracle-dz/UniFAR-FTUs huggingface dataset:
Why does frugality influence the recycling intention of waste materials?

Waste recycling significantly impacts the sustainable development of society and the ecological environment, contributing to a vital role within the waste management hierarchy. This paper presents a research model that investigates the influence mechanism of consumers’ frugality on their recycling intentions. This study collected 420 valid samples to test the model with regression analysis. The empirical results show that consumers’ frugality exerts a direct and positive effect on their recycling intention. Except for the positive direct effect, perceived value mediates the relationship between frugality and recycling intention. Besides, environmental concern strengthens the positive relationship between frugality and recycling intention. The findings of this study can better explain the recycling intention, thereby providing a basis for the government and enterprises to formulate policies and measures to promote recycling behavior.
Single-cell analysis reveals the COL11A1+ fibroblasts are cancer-specific fibroblasts that promote tumor progression

Background: Cancer-associated fibroblasts (CAFs) promote tumor progression through extracellular matrix (ECM) remodeling and extensive communication with other cells in tumor microenvironment. However, most CAF-targeting strategies failed in clinical trials due to the heterogeneity of CAFs. Hence, we aimed to identify the cluster of tumor-promoting CAFs, elucidate their function and determine their specific membrane markers to ensure precise targeting. Methods: We integrated multiple single-cell RNA sequencing (scRNA-seq) datasets across different tumors and adjacent normal tissues to identify the tumor-promoting CAF cluster. We analyzed the origin of these CAFs by pseudotime analysis, and tried to elucidate the function of these CAFs by gene regulatory network analysis and cell-cell communication analysis. We also performed cell-type deconvolution analysis to examine the association between the proportion of these CAFs and patients’ prognosis in TCGA cancer cohorts, and validated that through IHC staining in clinical tumor tissues. In addition, we analyzed the membrane molecules in different fibroblast clusters, trying to identify the membrane molecules that were specifically expressed on these CAFs. Results: We found that COL11A1+ fibroblasts specifically exist in tumor tissues but not in normal tissues and named them cancer-specific fibroblasts (CSFs). We revealed that these CSFs were transformed from normal fibroblasts. CSFs represented a more activated CAF cluster and may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. High CSF proportion was associated with poor prognosis in bladder cancer (BCa) and lung adenocarcinoma (LUAD), and IHC staining of COL11A1 confirmed their specific expression in tumor stroma in clinical BCa samples. We also identified that CSFs specifically express the membrane molecules LRRC15, ITGA11, SPHK1 and FAP, which could distinguish CSFs from other fibroblasts. Conclusion: We identified that CSFs is a tumor specific cluster of fibroblasts, which are in active state, may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. Membrane molecules LRRC15, ITGA11, SPHK1 and FAP could be used as therapeutic targets for CSF-targeting cancer treatment.
Human Activity Recognition using Channel State Information

Human Activity Recognition (HAR) is a key enabler of various applications, including smart homes, health care, Internet of Things (IoT), and virtual reality games. A large number of HAR systems are based on wearable sensors and computer vision. However, a challenge that has emerged in the last few years entails recognizing human activities using WiFi Channel State Information (CSI). Exiting state-of-the-art solutions have considered only amplitudes of the CSI to recognize human activities, we explore both amplitudes and phase differences to recognize activities. We utilize Continuous Wavelet Transform (CWT) to generate scalogram images from the CSI measurements. Then, we use these images as input to the pertained Convolution Neural Network (CNN), namely AlexNet to extract features that are resilient to environment changes and classify the activities. The experimental results show that the proposed method achieves an accuracy of 98.18% +/- 1.26% using amplitude and phase difference. We also studied the impact of different environments and people, and the results show its robustness.
Pricing Climate Risk

I exploit a new dataset from Four Twenty Seven and identify physical climate risk factors that can explain the variation in global individual stock returns. North American stocks are currently exposed to an extreme rainfall factor and an overall climate risk factor. European and Japanese stocks are currently exposed to an extreme rainfall factor, a heat stress factor, and an overall climate risk factor. I assess the pricing of policy related to these risks by drawing on new data from the Transition Pathway Initiative that summarises publicly-available information on a firm's emissions and targets. Physical climate risk and transition risk factors cannot explain the returns of portfolios sorted on standard accounting variables (such as investment, momentum and profitability), and vice-versa. However, a quality factor can explain both climate-related and non-climate-related portfolios. Climate risks may be mispriced and quality captures a confounding association between the environment and the zoo of factors used to explain asset returns.
Cutaneous Melanoma: Etiology and Therapy

The book provides an up-to-date, concise, multidisciplinary overview of the epidemiology, pathology, and current evidence-based treatment options for patients with all stages of melanoma. These aspects are presented in two sections: epidemiology and pathophysiology, and therapy and management. In section 1, five chapters provide a comprehensive overview of the epidemiology, heterogeneity, and biology of melanoma. In section 2, six chapters discuss the various treatment options and surveillance recommendations for afflicted patients. Electronic version is freely available. Hardcover copies are available at books@codonpublications.com
The formal side of informality: non-state trading practices and local Uyghur ethnography

ABSTRACT This article approaches ‘informal’ modes of organization among Uyghur bazaar traders in Xinjiang and Kyrgyzstan in a complex context of increasing state regulatory measures and strong social networks. It captures this organization as a ‘formal side of informality’. The practices comprising it are deemed ‘informal’ from a state-centred perspective, as they are not regulated by the state law or bureaucracy, but they still display a non-state formalization in the sense of being codified, regular and predictable to the traders. The article explores areas and examples of such ‘informal’ formality in the bazaar trade that are built around notions of morality, piousness, pride and shame. It pays special attention to oral contracts, purchase on credit, go-betweens and the status of profit. The article draws on participant observation and interviews in Xinjiang and Kyrgyzstan as well as on descriptions of trade morals and trade customs in ethnographic and folkloristic publications by local Uyghur scholars in Xinjiang.
A multi-agent model of changes in urban safety livability

Urban livability is an important factor in decisions regarding modern urban construction. Based on multi-agent modeling theory, a model of the changes in urban safety livability is proposed to analyze the present situation and the trends in urban safety livability in complex urban systems. Considering safety as an example, five environmental indicators, namely public security, fire protection, traffic, emergency response, and residence, are selected. The interactive dynamic feedback mechanisms among resident decision-making behaviors and urban safety livability in the context of these five indicators and relevant policies are provided. A simulation of the changes in urban safety livability is implemented based on resident behaviors. The results show that the multi-agent modeling method is effective for analyzing urban safety livability and can provide decision support for urban development planning.
Association of BDNF gene missense polymorphism rs6265 (Val66Met) with three quantitative traits, namely, intelligence quotient, body mass index, and blood pressure: A genetic association analysis from North India

Background Brain-derived neurotrophic factor (BDNF), a neurotransmitter modulator, plays a significant role in neuronal survival and growth and participates in neuronal plasticity, thus being essential for learning, memory, and the development of cognition. Additionally, it is crucial for appetite, weight, and metabolic control and plays a pivotal role in the cardiovascular system. The Val66Met polymorphism (rs6265) of the BDNF gene causes a decrease in BDNF secretion and plays a role in impairments in cognition, energy homeostasis, and cardiovascular events. The present study aimed to evaluate the association of polymorphism (rs6265) of the BDNF gene with three quantitative traits simultaneously, namely, intelligence quotient (IQ), body mass index (BMI), and blood pressure (BP). Methods Psychometric, morphometric, and physiometric data of the total participants (N = 246) were collected. WASI-IIINDIA was used to measure cognitive ability. Genotyping was carried out using allele-specific PCR for the rs6265 polymorphism (C196T), and genotypes were determined. Statistical analyses were performed at p < 0.05 significance level using MS-Excel and SigmaPlot. The odds ratio models with a 95% confidence interval were used to test the associations. The used models are co-dominant, recessive, dominant, over–dominant, and additive. Results The allelic frequencies of alleles C and T were 72 and 28%, respectively. Under the dominant genetic model, a significant susceptible association of minor allele T was observed with a lower average verbal comprehensive index (OR = 2.216, p = 0.003, CI (95%) =1.33–3.69), a lower average performance reasoning index (OR = 2.634, p < 0.001, CI (95%) = 1.573–4.41), and a lower average full-scale IQ-4 (OR = 3.159, p < 0.001, CI (95%) = 1.873–5.328). Carriers of Met-alleles were found to have an increased body mass index (OR = 2.538, p < 0.001, CI (95%) = 1.507–4.275), decreased systolic blood pressure (OR = 2.051, p = 0.012, CI (95%) = 1.202–3.502), and decreased diastolic blood pressure (OR = 2.162, p = 0.006, CI (95%) = 1.278–3.657). Under the recessive genetic model, several folds decrease in IQ and BP and an increase in BMI with the presence of the T allele was also detected. Conclusion This novel study may improve our understanding of genetic alterations to the traits and hence be helpful for clinicians and researchers to investigate the diagnostic and prognostic value of this neurotrophic factor.
Unsupervised Anomaly Detection via DBSCAN for KPIs Jitters in Network Managements

: For many Internet companies, a huge amount of KPIs (e.g., server CPU usage, network usage, business monitoring data) will be generated every day. How to closely monitor various KPIs, and then quickly and accurately detect anomalies in such huge data for troubleshooting and recovering business is a great challenge, especially for unlabeled data. The generated KPIs can be detected by supervised learning with labeled data, but the current problem is that most KPIs are unlabeled. That is a time-consuming and laborious work to label anomaly for company engineers. Build an unsupervised model to detect unlabeled data is an urgent need at present. In this paper, unsupervised learning DBSCAN combined with feature extraction of data has been used, and for some KPIs, its best F-Score can reach about 0.9, which is quite good for solving the current problem.
Potential mechanisms and modulators of food intake during pregnancy

Dietary choice during pregnancy is crucial not only for fetal development, but also for long-term health outcomes of both mother and child. During pregnancy, dramatic changes in endocrine, cognitive, and reward systems have been shown to take place. Interestingly, in different contexts, many of these mechanisms play a key role in guiding food intake. Here, we review how food intake may be impacted as a function of pregnancy-induced changes across species. We first summarize changes in endocrine and metabolic signaling in the course of pregnancy. Then, we show how these may be related to cognitive function and reward processing in humans. Finally, we link these to potential drivers of change in eating behavior throughout the course of pregnancy.
CD5L-induced activation of autophagy is associated with hepatoprotection in ischemic reperfusion injury via the CD36/ATG7 axis

Hepatic ischemia/reperfusion (I/R) injury is a side effect of major liver surgery that is difficult to prevent. I/R injury induces metabolic strain on hepatocytes and limits the tolerable ischemia during liver resection, as well as preservation times during transplantation. Additionally, I/R injury induces apoptosis in hepatocytes. CD5-like (CD5L), an inducer of autophagy, is a soluble scavenger cysteine-rich protein that modulates hepatocyte apoptosis. The aim of the present study was to determine if pharmacologic CD5L was protective against hepatic ischemia-reperfusion injury. Hepatocytes were subjected to I/R culture conditions, and apoptosis and caspase family activity were measured after I/R to model hepatic injury. Treatment with recombinant CD5L significantly suppressed apoptosis and caspase activity through modulating cellular autophagy to maintain activation of the cluster of differentiation 36 (CD36)-dependent autophagy-related 7 (ATG7) signaling pathway. The regulation loop between CD5L and the autophagy signaling pathway was identified to be associated with the inhibition of oxidative stress. Treatment with CD5L significantly inhibited cellular oxidative stress, which was confirmed by silencing the CD36 receptor or the autophagy related protein ATG7 using small interfering RNA, which reversed the antiapoptotic and antioxidative effects of CD5L on hepatocytes under I/R conditions. The results of the present study suggested that CD5L-mediated attenuation of hepatic I/R injury occurs through the CD36-dependent ATG7 pathway, accompanied by the inhibition of oxidative stress, which is associated with enhanced autophagy. In conclusion, the present study identifies CD5L as a novel therapeutic agent for hepatic I/R injury.
Improving radiotherapy using image analysis and machine learning

With ever increasing advancements in imaging, there is an increasing abundance of images being acquired in the clinical environment. However, this increase in information can be a burden as well as a blessing as it may require significant amounts of time to interpret the information contained in these images. Computer assisted evaluation is one way in which better use could be made of these images. This thesis presents the combination of texture analysis of images acquired during the treatment of cancer with machine learning in order to improve radiotherapy. The first application is to the prediction of radiation induced pneumonitis. In 1337% of cases, lung cancer patients treated with radiotherapy develop radiation induced lung disease, such as radiation induced pneumonitis. Three dimensional texture analysis, combined with patient-specific clinical parameters, were used to compute unique features. On radiotherapy planning CT data of 57 patients, (14 symptomatic, 43 asymptomatic), a Support Vector Machine (SVM) obtained an area under the receiver operator curve (AUROC) of 0.873 with sensitivity, specificity and accuracy of 92%, 72% and 87% respectively. Furthermore, it was demonstrated that a Decision Tree classifier was capable of a similar level of performance using sub-regions of the lung volume. The second application is related to prostate cancer identification. T2 MRI scans are used in the diagnosis of prostate cancer and in the identification of the primary cancer within the prostate gland. The manual identification of the cancer relies on the assessment of multiple scans and the integration of clinical information by a clinician. This requires considerable experience and time. As MRI becomes more integrated within the radiotherapy work flow and as adaptive radiotherapy (where the treatment plan is modified based on multi-modality image information acquired during or between RT fractions) develops it is timely to develop automatic segmentation techniques for reliably identifying cancerous regions. In this work a number of texture features were coupled with a supervised learning model for the automatic segmentation of the main cancerous focus in the prostate the focal lesion. A mean AUROC of 0.713 was demonstrated with 10-fold stratified cross validation strategy on an aggregate data set. On a leave one case out basis a mean AUROC of 0.60 was achieved which resulted in a mean DICE coefficient of 0.710. These results showed that is was possible to delineate the focal lesion in the majority (11) of the 14 cases used in the study.
An investigation on body composition, dietary intakes and physical activity in girls aged 8-11 years in Saudi Arabia

Background: Obesity rates in Saudi Arabia are amongst the highest in the world. It is known that teenage girls are less active than teenage boys, but less is known about the diet and activity patterns in younger girls. Therefore this study sought to investigate dietary intake and daily physical activity in girls aged 8-11 years old in Saudi Arabia. Methods: This was a crosssectional observational study conducted in seven schools across the city of Makkah. A total of 266 girls had anthropometric measurements taken including height, weight, waist circumference and body fat estimations. Dietary assessment using a 4 day unweighed diet diary was undertaken in 136 of these participants, and 134 agreed to monitor their physical activity for the 4 days using an accelerometer. After exclusion for underreporting, 109 remained in the dietary analysis and 78 in the physical activity analyses. Differences in means between BMI groups were determined using one-way ANOVA with post hoc Tukey test. Multivariable linear regression analysis was performed to look at the effect of multiple variables on body weight. Results: A total of 30% of participants were classified obese or overweight. There was a significant difference in the mean daily energy intake between the BMI groups with the obese group having the highest energy, fat, carbohydrate and protein intake (obese group: 2677 ± 804 kcal/d; healthy weight group: 1806 ± 403 kcal/d, p < 0.001), but the percentage contribution of the macronutrients to energy intake remained the same across the BMI groups. There were no differences in number of steps taken per day or time spent in moderate to vigorous intensity exercise according to BMI category. Most of the girls did not meet daily physical activity guidelines (5969 to 6773 steps per day and 18.5 22. 5 mins per day of moderate to vigorous activity). Multiple linear regression showed that energy intake positively predicted body weight (Beta = 0.279, p =0 .001), whereas, total energy expenditure per kg of body weight and family income had a significant negative influence on body weight (Beta = −0.661, p < 0.001; −0.131, p = 0.028 respectively). Conclusions: The results of this cross sectional analysis suggest that obesity in girls aged 8-11 years is linked to excessive energy intake from all macronutrients and the majority of girls in all weight categories are inactive. Research should be conducted to further investigate causal relationships in longitudinal studies and develop interventions to promote dietary change and activity that is culturally acceptable for girls in Saudi Arabia.
Synchronous random switching frequency modulation technique based on the carrier phase shift to reduce the PWM noise

Pulse width modulation (PWM) technique brings harsh acoustic noise in motor drive system. Thus, synchronous random switching frequency modulation (SRSFM) technique based on carrier phase shift for paralleled three-phase voltage source inverters is proposed in this study to eliminate the PWM noise. The proposed SRSFM technique is able to remove the high-frequency PWM noise more effectively than the conventional random switching frequency PWM; it not only completely eliminates the PWM noise nearby odd-order carrier frequency but also reduces PWM vibration noise around even-order carrier frequency depending on the switching frequency variation range. Furthermore, the SRSFM technique is simple to implement and requires no additional hardware. Finally, the effectiveness of the proposed method is verified by detailed experimental results.
Child-Robot Interaction Studies: From Lessons Learned to Guidelines

This project is about the creation of a set of guidelines for ChildRobot Interaction (CRI) studies in cognitive therapeutic settings. We collected past experiences and lessons learned from previous relevant studies - relating to Traumatic Brain Injury (TBI) and Autism Spectrum Disorder (ASD) – and transformed them into general guidelines. The main idea is to 1) motivate the scientific community to collect empirical quantitative data to further develop guidelines for child-robot interaction studies; 2) to give support and facilitate the adoption process to those practitioners implementing similar robot rehabilitation programs; 3) to ultimately help build safer and more effective personalized and engaging educational settings for children in their neurodevelopmental process.
Transcriptome analysis and identification of genes associated with leaf crude protein content in foxtail millet [Setaria italica (L.) P. Beauv.]

Introduction: Spruce spider mite is a primary insect pest of Chinese chestnut in China and seriously influences its yield and quality. However, the current management against this mite is costly and poorly effective. In previous research, we bred several foxtail millet materials for interplanting with chestnut tree, and found that they had high levels of crude protein (CP) in leaves and attracted spruce spider mite to feed on the leaves, thereby reducing chestnut damage. Methods: In this study, four foxtail millet varieties with significant differences in leaf crude protein content were used for high-throughput sequencing and identification of genes associated with leaf crude protein content. Gene enrichment analyses were carried out to comprehend the functions of these genes and the biological processes in which they are involved. In addition, transcription factors (TFs) were evaluated. Results: 435 differentially expressed genes (DEGs) were identified, suggesting their potential role in crude protein accumulation. Some differentially expressed genes were found to be associated with nitrogen metabolism and ubiquitin-mediated proteolysis pathways. Moreover, we identified 40 TF genes categorized into 11 transcription factor families. Discussion: Our findings represent an important resource that clarifies the mechanisms of accumulation and control of leaf crude protein in foxtail millet, and provide an opportunity for suppression of spruce spider mite attack on Chinese chestnut by interplanting with foxtail millet varieties with high concentrations of leaf crude protein.