Miracle-dz/UniFAR-FTUs huggingface dataset:
Factor Influencing Intention Repeat Tourism to Visit Singapore in New Normal based on Indonesia Traveler’s

The Covid-19 pandemic which has spread in various countries has a severe impact on all sectors in every country, especially the economic and tourism sectors. One of which is Singapore, which has closed access to foreign tourism with a lockdown policy and has progressively implemented a series of steps to reduce the risk of a wider spread of the COVID-19 pandemic in the community. Singapore has managed to maintain sustainable tourism over the years. Several tourist attractions in Singapore have resumed operations after being closed for several months. Indonesia was the market for the first largest source of income from tourism for Singapore for five consecutive years in 2016. This study aims to determine the perception of Indonesian travelers to return to tourism after the Singapore government reopened tourism to foreign countries. The research method used is quantitative, the sampling technique uses non-probability sampling and a sample of 285 respondents is obtained. The analytical tool used Path analysis and the hypothesis uses a significance test using the Partial Least Square Structural Equation Model (PLS SEM). The results of this study indicate that destination attractiveness, tourist motivation, accessibility, and risk perception can directly revisit the intention of Indonesian tourists to travel in Singapore. Then, destination attractiveness and tourist motivation can affect the revisit intention of Indonesian tourists to travel back to Singapore after the Covid-19 outbreak.
The Design of Wireless Smart Home System based on ZigBee

A functional and flexible wireless Smart Home system that based on GSM short message is presented. The design can control and monitor household equipments and environmental conditions. It uses the TMS320VC5402, CC2430 as the core hardware devices. Through ZigBee and the GSM integration, Smart Home remote monitoring and control are implemented. It has reflected the characteristic of low cost, low power dissipation, great practical and good scalability. All this work is significant for enhancing the actual application level and research level of Smart home control system further more.
Estimating the received solar irradiances by traditional vaulted roofs using optimized neural networks and transfer learning

Traditional vaulted roof-forms have long been utilized in hot-desert climate for better indoor environmental quality. Unprecedently, this research investigates the possible contribution of machine learning to estimate the received solar irradiances by those roofs, based on simulation-derived training and testing datasets, where two algorithms were used to reduce their higher-dimensionality. Then, four models of ordinary least-squares and artificial neural networks were developed. Their ability to accurately estimate solar irradiances was confirmed, with R2 of 95.599–98.794% and RMSE of 12.437–23.909 Wh/m2. Transfer Learning was also applied to pass the stored knowledge of the best-performing model into another one for estimating the performance of new roof-forms. The results demonstrated that transferred models could provide better estimations with R2 of 87.416–97.889% and RMSE of 79.300–13.971 Wh/m2, compared to un-transferred models. Machine learning shall redefine the practice of building performance, providing architects with flexibility to rapidly make informed decisions during the early design stages.
Ficus dubia Latex Extract Induces Cell Cycle Arrest and Apoptosis by Regulating the NF-κB Pathway in Inflammatory Human Colorectal Cancer Cell Lines

Simple Summary In this study, the anti-tumor activity of Ficus dubia latex extract (FDLE) against HCT-116 and HT-29 human colorectal cancer cell lines in normal and inflammatory conditions was investigated. The results indicated that an inflammation-activated NF-κB increased proliferation-related proteins and decreased apoptosis-related proteins, leading to hyperproliferation of colorectal cancer cell lines. FDLE exhibited remarkable antiproliferative activity in both conditions, however, more effective anti-proliferation was observed due to its more effective regulation of NF-κB inactivation and some proteins related to cell cycle progression and apoptosis induction in inflammatory condition. Our finding may promote the antiproliferative study of FDLE in inflammation-induced colorectal cancer progression. Abstract Colorectal cancer is one of the most diagnosed cancers that is associated with inflammation. Ficus dubia latex is recognized as a remedy with various therapeutic effects in traditional medicine, including anti-inflammatory and antioxidant activity. The present study aims to compare the anti-tumor activity of Ficus dubia latex extract (FDLE) against HCT-116 and HT-29 human colorectal cancer cell lines in normal and inflammatory condition and explore its mechanism of action. FDLE exhibited remarkable antiproliferative activity against HCT-116 and HT-29 colorectal cancer cell lines in both conditions using MTT and colony formation assays and more effective anti-proliferation was observed in inflammatory condition. Mechanistically, FDLE induced cell cycle arrest at G0/G1 phase by down-regulating NF-κB, cyclin D1, CDK4 and up-regulatingp21 in both cell in normal condition. In inflammatory condition, FDLE not only exhibited stronger induction of cell cycle arrest in both cells by down-regulating NF-κB, cyclin D1, CDK4 and down-regulating p21, but also selectively induced apoptosis in HCT-116 cells by down-regulating NF-κB and Bcl-xl and up-regulating Bid, Bak, cleaved caspase-7 and caspase-3 through stronger ability to regulate these proteins. Our results demonstrated that the phytochemical agent in the latex of Ficus dubia could potential be used for treatment and prevention of human colorectal cancer, especially in inflammation-induced hyperproliferation progression.
Pandemic-Era Uncertainty

We examine several measures of uncertainty to make five points. First, equity market traders and executives at nonfinancial firms have shared similar assessments about one-year-ahead uncertainty since the pandemic struck. Both the one-year VIX and our survey-based measure of firm-level uncertainty at a one-year forecast horizon doubled at the onset of the pandemic and then fell about half-way back to pre-pandemic levels by mid-2021. Second, and in contrast, the 1-month VIX, a Twitter-based Economic Uncertainty Index, and macro forecaster disagreement all rose sharply in reaction to the pandemic but retrenched almost completely by mid-2021. Third, Categorical Policy Uncertainty Indexes highlight the changing sources of uncertainty—from healthcare and fiscal policy uncertainty in spring 2020 to elevated uncertainty around monetary policy and national security as of May 2022. Fourth, firm-level risk perceptions skewed heavily to the downside in spring 2020 but shifted rapidly to the upside from fall 2020 onwards. Perceived upside uncertainty remains highly elevated as of early 2022. Fifth, our survey evidence suggests that elevated uncertainty is exerting only mild restraint on capital investment plans for 2022 and 2023, perhaps because perceived risks are so skewed to the upside.
The Effect of Individualised Haptic Guidance Paths for Free-Air Teleoperation Tasks

Haptic Shared Control (HSC) can improve human-in-the-loop teleoperation task execution by providing forces to guide the operator along a path. The current guidance path designs do not take individual movement preferences into account, leading to disagreement between the operator and the HSC controller. This study investigates if a Machine Learning technique, the taskparametrised Gaussian Mixture Model (GMM), can provide guidance paths learned from individual demonstrations. Subjects (n=12) performed a human factors bolt-and-spanner teleoperation experiment with two different types of haptic guidance paths: individually learned paths calculated by the GMM, and paths calculated by the Minimum Jerk (MJ) model. It was found that HSC improved task execution over manual control, and that using GMM paths in learned situations reduced the disagreement. This effect disappeared with situations outside of the learned range: depending on the path, MJ guidance resulted in better or similar operator workload and disagreement compared to the GMM guidance.
Autonomous UAV controlled collision landing via eye-in-hand visual servoing

Catastrophic damage to fixed-wing unmanned aerial vehicles (UAV) is most likely to occur during the landing stage. Vision-based autonomous landing methods for small UAV have been proposed in literature to address the issue. This paper improves on previous work on vision-based landing via a controlled collision with a large inflatable airbag. In the proposed method the UAV steers towards a large, multi-coloured, dome-shaped airbag using visual feedback obtained from a UAV-mounted camera. A multi-colour airbag is proposed to facilitate a robust and efficient colour-based detection method for real-time detection of the dome in images. A proposed visual servoing controller translates the dome location into desired pitch and yaw rate commands to achieve an exponential decay of the image error. A model predictive UAV controller that achieves desired roll and yaw rates is designed and tested in simulations. The lateral and longitudinal UAV dynamics were decoupled and a linear discrete state space model of the dy.
Harnessing Unconventional T Cells and Innate Lymphoid Cells to Prevent and Treat Hematological Malignancies: Prospects for New Immunotherapy

Unconventional T cells and innate lymphoid cells (ILCs) make up a heterogeneous set of cells that characteristically show prompt responses toward specific antigens. Unconventional T cells recognize non-peptide antigens, which are bound and presented by diverse non-polymorphic antigen-presenting molecules and comprise γδ T cells, MR1-restricted mucosal-associated invariant T cells (MAITs), and natural killer T cells (NKTs). On the other hand, ILCs lack antigen-specific receptors and act as the innate counterpart to the T lymphocytes found in the adaptive immune response. The alteration of unconventional T cells and ILCs in frequency and functionality is correlated with the onset of several autoimmune diseases, allergy, inflammation, and tumor. However, depending on the physio-pathological framework, unconventional T cells may exhibit either protective or pathogenic activity in a range of neoplastic diseases. Nonetheless, experimental models and clinical studies have displayed that some unconventional T cells are potential therapeutic targets, as well as prognostic and diagnostic markers. In fact, cell-mediated immune response in tumors has become the focus in immunotherapy against neoplastic disease. This review concentrates on the present knowledge concerning the function of unconventional T cell sets in the antitumor immune response in hematological malignancies, such as acute and chronic leukemia, multiple myeloma, and lymphoproliferative disorders. Moreover, we discuss the possibility that modulating the activity of unconventional T cells could be useful in the treatment of hematological neoplasms, in the prevention of specific conditions (such as graft versus host disease), and in the formulation of an effective anticancer vaccine therapy. The exact knowledge of the role of these cells could represent the prerequisite for the creation of a new form of immunotherapy for hematological neoplasms.
Using Malaise Traps and Metabarcoding for Biodiversity Assessment in Vineyards: Effects of Weather and Trapping Effort

Simple Summary A strong decline in insect biomass and biodiversity has been observed in the past decades. Long-term monitoring programs are important to understand the reasons for changes in species occurrence, which are mostly attributed to habitat destruction, intensified agriculture, invasive organisms, and climate change. Metabarcoding, a procedure for identifying insect species in bulk samples based on their DNA sequences, provides a method to replace otherwise time-consuming species identification in a time- and cost-efficient way. In this study, we examined how weather and trapping effort affect biomass and biodiversity of Malaise trap catches in vineyards using metabarcoding. Most insects were caught during warm and hot weather. We observed that, as the number of trapping days and sites increased, there was a very high accumulation of taxa due to species with low abundance. The results can help in developing monitoring programs. Common species can be extensively surveyed with less effort, whereas rare taxa require excessive effort to be completely surveyed due to a lack of saturation. Thus, metabarcoding can play an important role in conducting monitoring by offsetting the additional effort required to detect rare species by making identification less time consuming and costly Abstract Metabarcoding is a powerful tool for ecological studies and monitoring that might provide a solution to the time-consuming taxonomic identification of the vast diversity of insects. Here, we assess how ambient weather conditions during Malaise trap exposure and the effort of trapping affect biomass and taxa richness in vineyards. Biomass varied by more than twofold with weather conditions. It increased with warmer and drier weather but was not significantly related with wind or precipitation. Taxa richness showed a saturating relationship with increasing trapping duration and was influenced by environmental and seasonal effects. Taxa accumulation was high, increasing fourfold from three days of monthly trap exposure compared to continuous trapping and nearly sixfold from sampling at a single site compared to 32 sites. The limited saturation was mainly due to a large number of singletons, such as rare species, in the metabarcoding dataset. Metabarcoding can be key for long-term insect monitoring. We conclude that single traps operated for up to ten days per month are suitable to monitor the presence of common species. However, more intensive trapping is necessary for a good representation of rare species in biodiversity monitoring. The data collected here can potentially guide the design of monitoring studies.
Natural and anthropogenic controls on lake water‐level decline and evaporation‐to‐inflow ratio in the conterminous United States

Lake water levels are integral to lake function, but hydrologic changes from land and water management may alter lake fluctuations beyond natural ranges. We constructed a conceptual model of multifaceted drivers of lake water levels and evaporation‐to‐inflow ratio (Evap : Inflow). Using a structural equation modeling framework, we tested our model on (1) a national subset of lakes in the conterminous United States with minimal water management to describe natural drivers of lake hydrology and (2) five ecoregional subsets of lakes to explore regional variation in water management effects. Our model fits the national and ecoregional datasets and explained up to 47% of variation in Evap : Inflow, 38% of vertical water level decline, and 79% of horizontal water level decline (littoral exposure). For lakes with minimal water management, Evap : Inflow was related to lake depth (β = −0.31) and surface inflow (β = −0.44); vertical decline was related to annual climate (e.g., precipitation β = −0.18) and water management (β = −0.21); and horizontal decline was largely related to vertical decline (β = 0.73) and lake morphometry (e.g., depth β = −0.18). Anthropogenic effects varied by ecoregion and likely reflect differences in regional water management and climate. In the West, water management indicators were related to greater vertical decline (β = 0.38), whereas in the Midwest, these indicators were related to more stable and full lake levels (β = −0.22) even during drought conditions. National analyses show how human water use interacts with regional climate resulting in contrasting impacts to lake hydrologic variation in the United States.
Information System Quality and Web Compatibility of Korea Tourism Organization's Foreign Language Homepage

The purpose of this research is to analyze the information system quality of Korea Tourism Organization (KTO)’s website in foreign language versions that target foreigners and to evaluate the web compatibility of the KTO website with various web browsers. To examine the differences in the information system quality of the KTO website for specific countries, data were collected by distributing 89 copies of a questionnaire in English, 93 in Chinese, and 91 in Japanese. Multivariate analysis of variance (MANOVA) was conducted with SPSS 23.0. Results of the analysis show that the three groups significantly differed on all information system quality components except “usage convenience. ” As for the information system quality, the Japanese website group ranked it as first, followed by the Chinese website group and the English website group. To look into the compatibility of the KTO website in foreign language versions, a website analyzing tool called Sort Site was used. The result shows that the English website and the Japanese website of KTO have 3 types of minor issues on page 8 and there were one major issue and 3 minor issues on page 10 in the Chinese website. The result of this research can strengthen the competitiveness of Korean tourism.
Time Series Analysis Using Different Forecast Methods and Case Fatality Rate for Covid‐19 Pandemic

Abstract This study presents forecasting methods using time series analysis for confirmed cases, the number of deaths and recovery cases, and individual vaccination status in different states of India. It aims to forecast the confirmed cases and mortality rate and develop an artificial intelligence method and different statistical methodologies that can help predict the future of Covid‐19 cases. Various forecasting methods in time series analysis such as ARIMA, Holt's trend, naive, simple exponential smoothing, TBATS, and MAPE are extended for the study. It also involved the case fatality rate for the number of deaths and confirmed cases for respective states in India. This study includes the forecast values for the number of positive cases, cured patients, mortality rate, and case fatality rate for Covid‐19 cases. Among all forecast methods involved in this study, the naive and simple exponential smoothing method shows an increased number of positive instances and cured patients.
Connecting Curriculum to Industry: a Comparative Study on British and Korean Cases of Design Collaboration

This paper is based on two design collaboration cases between university and industry. The design projects were carried out in two very different cultural environments and circumstances: Great Britain and South Korea. The intention was not simply to compare and contrast the two cases, but rather to extract various issues to be generally considered for more effective collaboration. The lessons learned reflected the differences and contributed toward the major benefits of such collaboration for British and Korean education, viz. enhancing the employability and professionalization of students from the educational point of view. Naturally, there were many benefits for industry, too. A cultural connection was made by the lessons commonly found, while the contrasting nature of the settings within which the projects were initiated and carried out supported the credibility of such lessons and benefits. The research aims to establish:  what may trigger a design collaboration between university and industry;  how cultural and circumstantial differences may influence the pedagogy and collaboration process;  the beneficial focus for British and Korean design education, as well as the beneficial convergence from both;  various issues and a possible framework for a strategic curriculum development for preparing students for real-world practice that could be applied in different cultures and circumstances.
Digital fabrication and local participation: A community maker space dissolving boundaries

This paper reports on our experience of setting up, operating, and evaluating the Mixhaus – a mobile community maker space inside a disused shipping container in Townsville, North Queensland, Australia. The project, which emerged from a pitch at the local StartUp Weekend in 2015, has seen community members coalesce around a shared interest in learning about and practising digital fabrication skills and techniques. We present and discuss the data we gathered from interviews, participant observations, and community workshops. Our thematic analysis was guided by the conceptual framework of boundary objects. We found that the Mixhaus maker space presents itself as an object crossing and dissolving boundaries along four different dimensions: an organisational mix, a social mix, a disciplinary mix, and a spatial mix. Our insights inform local community engagement initiatives and policies as well as design implications.
The RED report: recognition, enhancement, development: the contribution of sessional teachers in higher education

This large-scale study into the recognition, enhancement and development of sessional teaching in higher education builds on the Australian Universities Teaching Committee Report (2003a) Training, Support and Management of Sessional Teaching Staff. The aim of the current Project was to identify and analyse current national practice and refocus attention on the issues surrounding sessional teachers in the university sector. The Project had three objectives: to establish the extent of the contribution that sessional teachers make to higher education; to identify and analyse good practice examples for dissemination; and to consider the possible developments for institutional and sector-wide improvements to the quality enhancement of sessional teaching. Sixteen Australian universities were involved in the Project, representing the ‘Group of 8’ (Go8), regional, Australian Technology Network (ATN), transnational and multi-campus institutions in all states and territories. At each of the participating universities, the number and typology of sessional teachers was audited across the institution and sixty interviews were conducted with the full range of participants, from sessional teachers to university executive staff. The Project had three objectives: to establish the extent of the contribution that sessional teachers make to higher education; to identify and analyse good practice examples for dissemination; and to consider the possible developments for institutional and sector-wide improvements to the quality enhancement of sessional teaching.