Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on the Impact of Housing Price Volatility on Foreign Capital Entry from the Perspective of Spatial Spillover

Foreign direct investment in the local market is an indispensable driving force for China to accelerate the new development pattern of Chinese and international dual circulation. The continuous increase in the sale price of commercial housing in China will inevitably have an impact on the daily operations of foreign-funded enterprises. A more comprehensive understanding of the impact of housing price volatility on the entry of foreign capital from the perspective of spatial spillover will help the government to formulate more targeted regulatory policies. According to research results, it is found that the direct impact of volatility in local housing price on the entry of local foreign investment is not significant, but the indirect spillover effect on the entry of foreign capital in neighboring regions is significantly positive. In addition, measures such as expanding the capacity of the local market and increasing the total supply of local labor are all conducive to increasing the attractiveness of foreign investment.
Comment on “Biostatistical Considerations When Using RWD and RWE in Clinical Studies for Regulatory Purposes: A Landscape Assessment”

aDepartment of Data Science, Center for Clinical Research, National Center for Global Health and Medicine, Tokyo, Japan; bDepartment of Information and Computer Technology, Tokyo University of Science, Tokyo, Japan; cDepartment of Biostatistics and Bioinformatics, The University of Tokyo, Tokyo, Japan; dCenter for Research Administration and Support, Biostatistics Division, National Cancer Center, Tokyo, Japan
Pilot Study of Eco-Physiological Pepper Responses to Starfish-Based Organic Soil Amendments in Open-Field and Greenhouse Cultivations

This pilot study was conducted to compare eco-physiological responses to starfish (SF)-treated red peppers (Capsicum annuum L.) in organic open-field (OF) and greenhouse (GH) cultivations in commercial farmhouses, South Korea in 2019. Treatments included starfish-liquid fertilizer (LF) applied in OF (SF-OF) and GH (SF-GH) plots, and SF + seaweed in OF (SFS-OF) and GH (SFS-GH). Weekly pH levels in SFS-LF were fluctuated for a 16-week storage period at room temperature due to having higher soluble salt levels than those of SF-LF. All experimental plots were ranged on soil pH between 7.1 and 7.4. SF- and SFS-GH plots resulted in increased soil electrical conductivity, organic matter, and increased concentrations of total nitrogen, phosphorous pentoxide, potassium oxide, and magnesium oxide, as well as exhibiting a richer and more diverse bacterial community. Leaf width and length and plant height increased in plants cultivated in GH, with low canopy width and stem diameter also observed to have increased. Total fruit yields were approximately two times higher for peppers cultivated in GH compared to OF cultivated peppers.
Tourist Expectations of Malaysian Shopping Mall Experiences

This paper reports on a qualitative research which was undertaken to explore tourists’ expectations of shopping experiences in Malaysia. Knowledge regarding the elements of tourists’ expectations about their shopping activity experiences in Malaysia is deficient amid the fact that shopping holds the second biggest share of tourist expenditure for Malaysia. Seven international tourists were intercepted in different shopping malls in Kuala Lumpur and responded to the questions, “what specific mall attributes do you desire when shopping? ” and “what were your shopping expectations for the shopping experience that day? ” Results from the research will be used to form items suggested for a quantitative survey which will be undertaken in a bigger study.
Integrating Big Data Into Evaluation: R Code for Topic Identification and Modeling

Despite the rising popularity of big data, there is speculation that evaluators have been slow adopters of these new statistical approaches. Several possible reasons have been offered for why this is the case: ethical concerns, institutional capacity, and evaluator capacity and values. In this method note, we address one of these barriers and aim to build evaluator capacity to integrate big data analytics into their studies. We focus our efforts on a specific topic modeling technique referred to as latent Dirichlet allocation (LDA) because of the ubiquitousness of qualitative textual data in evaluation. Given current equity debates, both within evaluation and the communities in which we practice, we analyze 1,796 tweets that use the hashtag #equity with the R packages topicmodels and ldatuning to illustrate the use of LDA. Furthermore, a freely available workbook for implementing LDA topic modeling is provided as Supplemental Material Online.
Hybrid SiC-Si DC–AC Topology: SHEPWM Si-IGBT Master Unit Handling High Power Integrated With Partial-Power SiC-MOSFET Slave Unit Improving Performance

Based on partial power conversion concept, this article proposes a hybrid silicon carbide (SiC)-silicon (Si) dc–ac topology to improve performance in high power application. First, master unit (MU) uses Si-IGBT working in low frequency to handle main high power because of its high rated current capacity and high switching loss, whereas the low power quality of MU is induced by the low switching frequency. And SiC-MOSFET suffers from high cost and high conduction loss at high power level. To solve these problems, the partial-power slave unit (SU) based on SiC-MOSFET is connected with MU in series through line-frequency transformer, whereas SU works in high frequency to compensate the harmonic of MU and adjusts the total output voltage. In this new topology, the corresponding hybrid modulation strategy and multiple quasi-proportional-resonance control for single-phase system are introduced in detail to ensure the reliable operation. In the end, a 4.5-kW converter prototype was implemented and tested. Simulation and experiment results are given to verify the performance of the proposed hybrid dc–ac topology.
Building Trauma Informed Teachers: A Constructivist Grounded Theory Study of Remote Primary School Teachers’ Experiences With Children Living With the Effects of Complex Childhood Trauma

The experiences of remote teachers who work with children living with the effects of complex childhood trauma is under explored. Children from remote areas of Australia are vulnerable to complex childhood trauma as their communities can face the effects of colonization, higher rates of disadvantage and exposure to potentially traumatic circumstances, such as natural disasters and family and community violence. This is compounded by the tyranny of distance in accessing effective supports. In such contexts, the roles of schools and teachers in addressing the debilitating impacts of trauma are both vital and amplified. This article summarizes a qualitative study, incorporating constructivist grounded theory, that generated a new theory to explain social processes that teachers in remote schools undergo when working with the effects of complex childhood trauma. Data were collected from teachers in individual interviews (n = 23) and a focus group. Data were analyzed using constant comparative method, emergent themes were categorized, leading to the development of the grounded theory, Building Trauma Informed Teachers. This overarching theory consists of seven categories. This study contributes insights into the scope and nature of the work of teachers in remote schools and recommends ways in which cognate systems can prepare and support teachers for their professional work supporting and educating trauma-impacted children.
The status quo of Facebook usage among young generations in civil engineering education

Abstract The Architecture, Engineering and Construction (AEC) industry is known to be slow in technology adoption. Higher education is an industry that well-placed to assist the AEC industry to move towards digital transformation. Given the popularity of Facebook among generations Y (ages 28–42 years old) and Z (ages 13–27 years old), Facebook could be an innovative learning and teaching platform in higher education. Although research on Facebook usage has been studied extensively in the past, users’ behaviour tends to evolve with the emergence of new social media and new features. Hence, this study aims to explore the current state of Facebook usage among civil engineering undergraduate students. Data was collected through a questionnaire survey. Results of questionnaire discovered that Facebook usage among civil engineering students could be categorized into four groups, namely: ‘Fulfill basic needs of psychological health’, ‘Personal enhancement/life long learning’, ‘Maintaining social connectivity’ and ‘Engaging for academic achievement’. In conclusion, Facebook is a viable and preferable choice of a learning and teaching platform among younger generations. Educators can consider exploring further the benefits and limitations of using Facebook in improving students’ learning experience and collaborative skills in civil engineering programme in the digitalization era.
Deep Learning Based Thermal Image Processing Approach for Detection of Buried Objects and Mines

Thermal imaging based mine detection technique is widely adopted due it suitability of detecting buried metallic and also non-metallic land mines in battle fields. Accurate mine detection using thermal images depends on thermal contrast between the soil and mine and it is affected by various factors such as the depth of burial; soil properties and attributes, water content in the soil, mine properties; as well as the time of day of image acquisition. With temporal temperature variations of the soil, it is difficult to distinguish and discriminate between the buried object and the background in the thermal image using the conventionally followed binary thresholding approach in gray scale. This paper presents deep learning region convolution based neural network approach to identify the buried objects in thermal images. A region interest selection using a bound box is followed for identifying the buried object in the thermal image. From the experimental results, it is found that there is temperature variation in the thermal images of the buried objects due to the change in heat carrying capacity of the surround soil. Proposed neural network method showed 90% accuracy in predicting the target locations of buried objects in the thermal images and it can be extended for land mine detection using thermal image processing approach.
Study of Co-Relation between Hepatitis C Viral Load with Clinical Presentations, Laboratory Investigations and Sofosbuvir Combination Therapy

Hepatitis C virus is a causative agent of both acute and chronic liver disease and is associated with varied clinical presentations. Aims & Objectives: The study was undertaken co-relate the various clinical manifestations and derangement of liver and endocrine function with HCV viral replication and to find out the impact of Sofosbuvir combination therapy. Result: Derangement of liver function as indicated by Bilirubin, AST and ALT has significant corelation with active viral replication as indicated by viral load assay. Derangement of Thyroid function is also found in a third of HCV infected patients. The study also found Sofosbuvir combination therapy induces an early virologic response in both Genotype 1 and Genotype 3 infection.
Expression of Cytokine-Coding Genes BMP8B, LEFTY1 and INSL5 Could Distinguish between Ulcerative Colitis and Crohn’s Disease

Ulcerative colitis (UC) and Crohn’s disease (CD) are characterized by an imbalance between pro-inflammatory and anti-inflammatory cytokines, interfering with the resolution of inflammation. Due to the crucial role of cytokines, new insights into their profiles in UC and CD would help to improve our understanding of pathogenesis and enable the development of new treatment modalities. We provide an expression profile of cytokines in UC and CD, using bioinformatics approach, and experimental validation of expression of the selected genes. We retrieved data and analyzed the cytokine gene expression profiles of UC and CD. From ten genes with inverse expression, common to CD and UC, BMP8B, LEFTY1 and INSL5 were selected for gene expression experimental validation. Experimentally, BMP8B and INSL5 were down-regulated in both CD and UC but followed the bioinformatics trend. The expression of genes LEFTY1 and BMP8B was statistically significant when comparing UC and CD in colon and the expression of gene LEFTY1 showed statistical significance when CD in ileum and colon were compared. Using the bioinformatics approach and experimental validation, we found differences in expression profiles between UC and CD for INSL5, LEFTY1 and BMP8B. These three promising candidate genes need to be further explored at different levels, such as DNA methylation and protein expression, to provide more evidence on their potential diagnostic role in CD and UC.
Evidence of the largest Late Holocene mountain glacier extent in southern and southeastern Greenland during the middle Neoglacial from 10Be moraine dating

The timing of mountain glacier fluctuations is poorly constrained in some parts of Greenland during the Late Holocene. We present 31 10Be cosmic‐ray exposure ages (CRE) of boulders collected from three mountain glacier moraines located in the Tasilap valley, in southeastern Greenland, and 10 10Be CRE ages from one mountain glacier in the Isortup valley, in southern Greenland. For the first time in these areas, mountain glacier fluctuations are documented from moraine CRE for the Late Holocene period. Several glacier advances during the Late Holocene are revealed with exposure ages ranging from 3.90±0.26 to 0.4±0.04 ka. Moraines of three of the four glaciers investigated, dated to 3.75±0.13 ka (n = 3), 3.3±0.19 ka (n = 2) and 2.87±0.13 ka (n = 3), show a common timing of the largest glacier expansion during the Late Holocene. Evidence of at least one individual moraine deposited at ~1.2 ka was found on all glaciers. Finally, the most recent period of glacial advance during the Late Holocene is documented by one glacier in each valley at ~0.66–0.70 ka. The maximum glacier extent at ~3 ka differs from the Late Holocene glacier maximum extent usually reported during the Little Ice Age in east Greenland based on moraine dating and lake sediments. We suggest that the combination of a stronger East Greenland Current and a weaker Irminger Current, potentially associated with increased sea‐ice concentration, superimposed on the long‐term decrease in summer insolation during the Late Holocene could be responsible for this large glacial advance at ~3 ka in southern and southeastern Greenland.
Health professionals’ attitudes toward religiosity and spirituality: a NERSH Data Pool based on 23 surveys from six continents

Background In order to facilitate better international and cross-cultural comparisons of health professionals (HPs) attitudes towards Religiosity and/or Spirituality (R/S) using individual participant data meta-analysis we updated the NERSH Data Pool. Methods We performed both a network search, a citation search and systematic literature searches to find new surveys. Results We found six new surveys (N=1,068), and the complete data pool ended up comprising 7,323 observations, including 4,070 females and 3,253 males. Most physicians (83%, N=3,700) believed that R/S had “some” influence on their patients’ health (CI95%) (81.8%–84.2%). Similarly, nurses (94%, N=1,020) shared such a belief (92.5%–95.5%). Across all samples 649 (16%; 14.9%–17.1%) physicians reported to have undergone formal R/S-training, compared with nurses where this was 264 (23%; 20.6%–25.4%). Conclusions Preliminary analysis indicates that HPs believe R/S to be important for patient health but lack formal R/S-training. Findings are discussed. We find the data pool suitable as a base for future cross-cultural comparisons using individual participant data meta-analysis.
Living arrangements, intergenerational support, and married women’s subjective well-being

ABSTRACT Theory suggests that relationships between intergenerational coresidence and married women’s subjective well-being may be either positive or negative. We extend previous research on this question in two ways: by focusing also on geographical proximity to parents(-in-law) and by examining differences in married women’s well-being both between and within different types of living arrangements. Using data from a nationally representative survey of adults in Japan, we found no differences in married women's subjective well-being between living arrangements, but observed significant differences within living arrangements depending on married women’s position in the household and the direction of intergenerational support transfers. Our results suggest that comparisons across living arrangements may be complicated by within-group associations with well-being and that attention to married women’s position in the household and the direction of intergenerational transfers is essential for understanding how married women in Japan experience different living arrangements.
Prophet

This chapter highlights how Erich Ludendorff turned to works of commentary and prophecy. The failure of the Kapp and Beer Hall putsches and his inability to seize control of the splintering völkisch movement in the mid-1920s began the process of slowly dissolving most of the connections Ludendorff had forged to various political movements. As those bonds dissolved, the chapter unveils a new ideological movement that would attract tens of thousands to Ludendorff’s ideals. This chapter then takes a look at the marriage of Ludendorff and Mathilde von Kemnitz, and focuses on the two projects, the cultivation of Ludendorff’s legend in the Tannenberg League and evangelizing for Mathilde’s neopagan philosophy, “Deutsche Gotterkenntnis” (Germanic understanding of God). Ultimately, it illustrates Ludendorff’s 1922 work Kriegsführung und Politik and discusses his evolution from the “stab in the back” of 1918–19 toward the full-blown belief in the pernicious influence of the “supranational powers” that fills the pages of his works by the late 1920s.
The Relationship Between Weight Self-Stigma and Quality of Life Among Youth in the Jazan Region, Saudi Arabia

Background: Studies on the role of weight self-stigma on the quality of life of young adults are limited. Therefore, the present study aimed to examine the relationship between different forms of weight self-stigma (self-devaluation and fear of enacted stigma) and the quality of life among Saudi youth in the Jazan region. Methods: A cross-sectional study was performed using a sample of 399 participants who were invited through social media platforms. We used Arabic, validated versions of the weight self-stigma questionnaire (WSSQ) and the World Health Organization quality of life questionnaire. Data analysis was performed by independent samples t-test and analysis of variance with Tukey's post hoc test. Results: The study sample consisted of 399 participants aged 21.12 years ± 2.91 years. A total of 264 (66.2%) were female. The overall weight self-stigma score of the study population was 34.81 ± 10.73 on the WSSQ. The analysis showed a significant association between weight self-stigma and quality of life and body mass index (BMI; p < 0.01). In addition, participants who were overweight and obese had more self-devaluation and fear of enacted stigma than did participants with normal weight. Participants with high weight self-stigma had lower quality of life than did those with less weight self-stigma. Conclusions: The results of this study show that weight self-stigma is negatively correlated with the individual's quality of life. Weight self-stigma was positively associated with BMI.
Remote Sensing Image Vehicle Detection Based on Pre-Training and Random-Initialized Fusion Network

Vehicle detection based on remote sensing images is of great significance to intelligent traffic management and smart city planning. The performances of the mainstream vehicle detection methods such as Fast-RCNN, SSD, FCRN, etc. are mainly affected by their extracted features, whose richness and robustness can be enhanced by introducing pre-training models from other datasets. However, the weights of the pre-training models used in traditional methods like FCRN, only shallow-tuned from the weights of another database training, without deep optimization from random initialization. This letter proposes a new pre-training and random-initialized fusion network (PRFN): the random initialization model and the pre-training model are connected in parallel, and an encoder is used to fuse their features, thereby improving the richness of features and the robustness of the model. We evaluate four different combination patterns of the pre-training and random initialized models, and the effect of the fusion feature encoder. Experiments show the parallel concatenating pattern with the fusion feature encoder achieves the best performance than other patterns. We test on three datasets, our PRFN exceeds the traditional methods, and, respectively, 1.23%, 1.04%, 0.94% higher than the baseline. All codes are available from https://github.com/LHKRobert/PRFN.
IVQFIoT: An intelligent vulnerability quantification framework for scoring internet of things vulnerabilities

With time smart services have become more domineering than ever before however, the pertinent security considerations fade to correspond with growing heterogeneity in the internet of things (IoT) devices and new technologies coupled with resource constraints, crafting IoT‐based systems more susceptible to cyber‐attacks. To ensure a secure IoT environment, pro‐active security mechanisms, like scanning vulnerabilities and prioritizing to remediate them timely, should be embedded in the system. Motivated by the facts, we in this paper, highlight the state of the art of several works trading with a common vulnerability scoring system (CVSS), its limitations, and the emendations recommended to conclude its maturity. CVSS is an industry standard that has been adopted worldwide to quantify the vulnerabilities in organizations for IT and IoT‐based systems. The vulnerabilities mathematical score coalesces with environmental knowledge for finding attack paths and apt score for prioritization. The specific functionality and exclusive dynamics of IoT and cyber‐physical systems in comparison to traditional computer networks, make the legacy cyber‐security exemplars unfit for these advanced networks. This paper studies the relevance of CVSS for smart systems and present an intelligent vulnerability quantification framework for IoT systems grounded on the CVSS v3.1 framework with threat intelligence and machine learning models. Further by applying blockchain technology in the proposed framework, the issues concerning security, lack of trust, and privacy possibly will resolve by hiring a smart contract.