Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing Citizens’ and Health Care Professionals’ Searches for Smell/Taste Disorders and Coronavirus in Finland During the COVID-19 Pandemic: Infodemiological Approach Using Database Logs

Background The COVID-19 pandemic has prevailed over a year, and log and register data on coronavirus have been utilized to establish models for detecting the pandemic. However, many sources contain unreliable health information on COVID-19 and its symptoms, and platforms cannot characterize the users performing searches. Prior studies have assessed symptom searches from general search engines (Google/Google Trends). Little is known about how modeling log data on smell/taste disorders and coronavirus from the dedicated internet databases used by citizens and health care professionals (HCPs) could enhance disease surveillance. Our material and method provide a novel approach to analyze web-based information seeking to detect infectious disease outbreaks. Objective The aim of this study was (1) to assess whether citizens’ and professionals’ searches for smell/taste disorders and coronavirus relate to epidemiological data on COVID-19 cases, and (2) to test our negative binomial regression modeling (ie, whether the inclusion of the case count could improve the model). Methods We collected weekly log data on searches related to COVID-19 (smell/taste disorders, coronavirus) between December 30, 2019, and November 30, 2020 (49 weeks). Two major medical internet databases in Finland were used: Health Library (HL), a free portal aimed at citizens, and Physician’s Database (PD), a database widely used among HCPs. Log data from databases were combined with register data on the numbers of COVID-19 cases reported in the Finnish National Infectious Diseases Register. We used negative binomial regression modeling to assess whether the case numbers could explain some of the dynamics of searches when plotting database logs. Results We found that coronavirus searches drastically increased in HL (0 to 744,113) and PD (4 to 5375) prior to the first wave of COVID-19 cases between December 2019 and March 2020. Searches for smell disorders in HL doubled from the end of December 2019 to the end of March 2020 (2148 to 4195), and searches for taste disorders in HL increased from mid-May to the end of November (0 to 1980). Case numbers were significantly associated with smell disorders (P<.001) and taste disorders (P<.001) in HL, and with coronavirus searches (P<.001) in PD. We could not identify any other associations between case numbers and searches in either database. Conclusions Novel infodemiological approaches could be used in analyzing database logs. Modeling log data from web-based sources was seen to improve the model only occasionally. However, search behaviors among citizens and professionals could be used as a supplementary source of information for infectious disease surveillance. Further research is needed to apply statistical models to log data of the dedicated medical databases.
Environmental influence on Triatoma vitticeps occurrence and Trypanosoma cruzi infection in the Atlantic Forest of south-eastern Brazil.

Trypanosoma cruzi requires a triatomine insect vector for its life cycle, which can be complex in different enzootic scenarios, one of which is the unique transmission network in the Atlantic Forest of south-eastern Brazil. In Espírito Santo (ES) State, highly infected Triatoma vitticeps are frequently reported invading domiciles. However, triatomines were not found colonizing residences and mammals in the surrounding areas did not present T. cruzi infection. To date, the biotic and abiotic variables that modulate T. vitticeps occurrence and T. cruzi infection in ES State are still unknown. The aim of this study was to identify the environmental variables that modulate their occurrence. Local thematic maps were generated for two response variables: T. vitticeps occurrence and T. cruzi infection. The following explanatory variables were tested: climate (temperature, relative air humidity and rainfall), altitude elevation, mammalian species richness as well as soil and vegetation types. Spatiotemporal distribution patterns and correlation levels between response and explanatory variables were assessed through spatial statistics and map algebra modelling. The central and southern mesoregions presented higher T. vitticeps and T. cruzi distributions and can be considered transmission hotspots. The explanatory variables that can explain these phenomena were relative air humidity, average temperature, soil type, altitude elevation and mammalian species richness. Algebra map modelling demonstrated that central and southern mesoregions presented the environmental conditions needed for T. vitticeps occurrence and T. cruzi infection. The consideration of environmental variables is essential for understanding the T. cruzi transmission cycle. Cartographic and statistical methodologies used in parasitology have been demonstrated to be reliable and enlightening tools that should be incorporated routinely to expand the understanding of vector-borne parasite transmission.
Mudharabah Financing Determination on Sharia Banking of Indonesia

The purpose of this study was to examine the determination of mudharabah financing in Islamic banking of Indonesia. The data used in this study were sourced from 11 Islamic Commercial Banks with a period of 2012-2016. Methods of data analysis using panel data regression and was simulated using eviews 10. After conducting the Chow test and Hausman test reveal that the random effect model was the appropriate model choose, due to partially the capital has no effect on mudharabah financing, while mudharabah savings and mudharabah deposits have a significant effect and positive for mudharabah financing. On the other hand mutually, the capital, mudharabah savings and mudharabah deposits have a significant and positive effect on mudharabah financing.
The Oxford Handbook of Planning for Climate Change Hazards

This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online. For more information, please read the site FAQs.
Personal Care Robot Navigation System Based on Multi-sensor Fusion

In recent years, intelligent elderly care equipment represented by personal care robots has gradually become a focus of academic research in various countries. A reliable navigation system is a foundation for personal care robots to perform complex tasks. Traditional nursing robots are difficult to apply to the real home living environment due to the simple operating environment of the navigation system. This paper proposes a personal care robot navigation system employed in a home environment, which uses a multi-sensor data fusion method to sense the surrounding environment information of the robot accurately. Thus, the robot able to perform complex navigation tasks in the home environment, reliably and stably. The navigation system is based on the seed robot hardware platform and ROS (Robot Operating System) operating system. Experimental results show that the navigation system can achieve reliable operation of personal care robots in complex home environments.
A comparative study of design-based and analysis-based approaches to causal inference with observational data

Causal inference with observational data is a central goal in many fields. Propensity score methods are design-based approaches that try to ensure covariate balance without using information from the outcome variables. Analysis-based approaches, such as the Bayesian Additive Regression Tree and the Causal Forest, bypass the issue of covariate balance, and directly model the outcomes. We use a Monte Carlo simulation to study the performance of these two types of approaches. Some of the simulation scenarios involve large number of covariates relative to the number of observations. We find that the analysis-based approaches can yield very poor performance, without any warning about not enough overlap between the covariate distributions for the treated and control groups. In contrast, the propensity score methods provide warning about not enough overlap, but such warning could be overly-cautious when there is enough overlap.
Characterization of Substitution Mutations of eIF4G Gene Generated through Adenine Base Editors in Rice

Adenine base editor (ABE) creates A to G transitions within its editing window. In the present study, an ABE was used to target a stretch of six amino acid residues, VLFPNL in translation initiation factor four gamma (eIF4G) gene of rice. Agrobacterium-mediated transformation of rice cultivar ASD16 resulted in T0 events with high mutation efficiency of 89.29 %. Substitution mutations of A > G occurred within the editing window of four to eight bases at A7 > G7 (74.67 %) and A4 > G4 (2.46 %). Non-canonical substitutions of G > C/A was also observed at G15 > C15 (9.29 %) and G8 > A8 (1.15 %). A total of 15 missense base substitution events affecting the target residue was identified. Taken together, the present study showed that ABEs create unexpected base substitutions besides efficient canonical editing of A > G in the rice genome
Long memory linkages amongst Latin American stock markets. A fractional cointegration approach

ABSTRACT This paper examines long-run relationships amongst six Latin American stock markets as possible evidence for their economic development, by using fractional cointegration which is applied to monthly observations for the period September 2002 to November 2019. Additionally, a novel summary table is proposed in an exhaustive way, which attempts to help to understand the puzzle of market integration around the different economic regions of the world. Hereby, the analysis suggests that there are four cointegrating vectors among the six equity markets, suggesting that Latin American stock markets are not fully nor perfectly integrated.
Brain Image Segmentation to Diagnose Tumor by Applying Wiener Filter and Intelligent Water Drop Algorithm

—Segmentation of image has wide application in the field of medical, military, surveillance, etc. This work segments medical resonance image for detection of tumor in brain where work identify three parts in the image. First is skull, second is brain and third is tumor. Presented paper includes description of image segmentation in unsupervised manner where proposed model identify all segments of image without any training. Here, wiener filter preprocessed the input images by removing unwanted information from the image matrix. Filtered image then passed in Intelligent Water Drop (IWD) genetic algorithm for finding representative pixel value sets of image segments. Graphical water drop movement in the IWD algorithm has representative pixels value set selection accuracy. Experiment is performed in real dataset of brain tumor and detection is done by taking reference of ground truth images. Proposed model evaluated average precision value 0.98 and average accuracy 96%. Hence, when results is compared with existing methods then it is obtained that proposed segmentation work increased the segmentation evaluation parameter values.
The Impact of Emerging Technologies in the Aviation Manufacturing Industry: A Case Study of the Gradual-Change Factors in Shaanxi, PR China

As China’s economy becomes more robust, the government has emphasized the need to increase the civil aviation industry’s rapid development and reduce civil aviation’s technological gap compared to other advanced aircraft manufacturers. The use of the appropriate technologies in the aviation industry can help achieve the government’s plan of creating more jobs and increasing its revenue through the civil aviation industry. However, emerging technologies’ uncertainty and dynamic nature have led to significant challenges when these technologies are applied to the aviation manufacturing industry. This article applies the principles and methods of system dynamics based on the gradual-change factors of emerging technologies as identified through expert interviews to construct conceptual models depicting the gradual-change of emerging technologies in the aviation manufacturing field. Historical data from Shaanxi province were used to simulate and analyze the gradual development of emerging technologies. An analysis of the simulation results revealed that the rapid growth of competitive technologies in the growth process inhibits the gradual-change of emerging technologies. Also, increasing enterprise innovation capabilities, market demand expansion, and technology optimization significantly promote emerging technologies’ development and application. Furthermore, the research result shows that competitive products and technologies influence the gradual development of emerging technologies. Finally, the results indicate that the civil aviation industry should optimize the performance and function of emerging technologies during the early development stage instead of at the market application stage.
Impact of Germination Time on Resveratrol, Phenolic Acids, and Antioxidant Capacities of Different Varieties of Peanut (Arachis hypogaea Linn.) from China

In China, peanut sprouts are popular among consumers as functional vegetables. This study reports the change in total phenolic content (TPC), total flavonoid content (TFC), monomeric anthocyanin content (MAC), vitamin C, trans-resveratrol content, antioxidant capacities, and phenolic profile of three different varieties of peanut during 8 days of germination. The TPC, TFC, and antioxidant capacity of peanut samples were reduced and then increased with an increase in germination time. TFC values were highly correlated with 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) values. MAC values of peanuts were first increased and then decreased during 8 days of germination. The TFC, DPPH, and FRAP values of germinated peanuts were lower compared to the non-germinated peanut. Germination of peanut samples enhanced the total phenolic acids and trans-resveratrol content, but the vitamin C content of peanut sprouts was lower than ungerminated peanuts.
Enhanced Pose Adjustment System for Wing-Box Assembly in Large Aircraft Manufacturing

Strict quality requirements in aircraft manufacturing demand high accuracy concerning pose alignments of aircraft structures. However, even though a pose adjustment system does pass the accuracy verification, the pose of the large complex structure has difficulty in smoothly and efficiently converging on the desired pose in large aircraft assembly. To solve this problem, we developed a pose adjustment system enhanced by integrating physical simulation for the wing-box assembly of a large aircraft. First, the development of the pose adjustment system, which is the base of the digital pose alignment of a large aircraft’s outer wing panel, is demonstrated. Then, the pose alignment principles of duplex and multiple assembly objects based on the best-fit strategy are successively explored. After that, the contributor analysis is conducted for nonideal pose alignment, in which the influences of thermal and gravity deformations on the pose alignment are discussed. Finally, a physical simulation-assisted pose alignment method considering multisource errors, which uses the Finite Element Analysis (FEA) to integrate temperature fluctuation and gravity field effects, is developed. Compared with a conventional digital pose adjustment system driven by the classical best-fit, the deviations of the Key Characteristic Points (KCPs) significantly decreased despite the impacts of thermal and gravity deformations. The developed pose alignment system has been applied to large aircraft wing-box assembly in Aviation Industry Corporation of China, Ltd. It provides an improved understanding of the pose alignment of large-scale complex structures.
Inefficient exploitation of accessory receptors reduces the sensitivity of chimeric antigen receptors

Chimeric antigen receptors (CARs) can re-direct T cells to target abnormal cells but their activity is limited by a profound defect in antigen sensitivity, the source of which remains unclear. Here we show that, while CARs have a >100-fold lower antigen sensitivity compared to the T cell receptor (TCR) when antigen is presented on antigen-presenting-cells (APCs), they have nearly identical sensitivity when antigen is presented as purified protein on artificial surfaces. We next measured the impact of engaging accessory receptors (CD2, LFA-1, CD28, CD27, 4-1BB) on antigen sensitivity by adding their purified ligands. Unexpectedly, we found that engaging CD2 or LFA-1 improved TCR antigen sensitivity by 125 and 22-fold, respectively, but only improved CAR sensitivity by <5-fold. This differential effect of CD2 and LFA-1 engagement on TCR versus CAR sensitivity was confirmed using APCs. We found that sensitivity to antigen can be partially restored by fusing the CAR variable domains to the TCR CD3ε subunit (also known as a TRuC), and fully restored by exchanging the CAR variable domains with the TCRαβ variable domains (also known as STAR or HIT). Importantly, these improvements in TRuC and STAR/HIT sensitivity can be predicted by their enhanced ability to exploit CD2 and LFA-1. These findings demonstrate that the CAR sensitivity defect is a result of their inefficient exploitation of accessory receptors, and suggest approaches to increase sensitivity.
Behavioral Analysis of Sustained Individual Investors

With a direct access to 32 self-directed investors from two European countries and the USA, we found that with experience, investors learn to mitigate well-studied behavioral biases while new biases and convictions emerge. The explorative interview method revealed reasons for seemingly irrational behavior not discovered by existing empirical studies using aggregated quantitative data. Thematic analyses were done using open coding and predefined concepts of mainstream and behavioral finance. The findings were contrasted with empirical literature and validated with expert interviews. Learning from mistakes, investors in our sample acknowledged the presence of emotions and built ways to mitigate behavioral issues. We found that overconfidence referenced in numerous studies diminishes after initial enthusiasm; underconfidence may emerge after painful losses. Illusion of control could not be identified. Instead, investors reported feeling of insufficient control on their investments. An important new bias candidate, tangibility bias was discovered which makes investors accept lower financial utility if they feel being in control of their investments. Tangibility bias contributes to less efficient portfolios due to the priority for small number of well-known investments instead of well-diversified but not transparent funds. Beyond decision-making biases, investors had developed experience-based convictions which may be rational or unfounded. Taking into account non-financial motivations, we argue that seemingly irrational actions have a purpose and efficacy.
Prejudice in Turkey and Belgium: The cross‐cultural comparison of correlations of right‐wing authoritarianism and social dominance orientation with sexism, homophobia, and racism

Using data from Turkey and Belgium, this study investigated the relationships of right-wing authoritarianism and social dominance orientation with ambivalent sexism, homophobia, and subtle racism. First, we predicted that men are more prejudiced than women. This hypothesis was confirmed in the Turkish but not in the Belgian sample. Second, Muslims were higher in authoritarianism and homophobia than people belonging to other (or no) religious groups. Third, Muslims also showed more hostile sex-ism toward both men and women. Fourth, negative associations of education with authoritarianism, sexism, and homophobia were expected and found. Fifth, in both countries, authoritarianism was positively related to homopho-bia and sexism, and social dominance orientation was positively associated with racism. Finally, groups comparing both samples, we found that Turks’ authoritarianism and prejudice was higher than Belgians’. Implications for theory and practice are discussed.
Prediction of Investor-Specific Trading Trends in South Korean Stock Markets Using a BiLSTM Prediction Model Based on Sentiment Analysis of Financial News Articles

Abstract Stock market performance is determined by supply and demand of individual, institutional, and foreign investors, who increasingly use media such as news articles for decision-making. We present a bidirectional long short term memory model to forecast trading trends based on statistically significant investor-specific topics from financial news datasets. The application of this study shows three valuable results: (i) topics significantly meaningful to each investor type differ, (ii) investors show different decision-making trends for the same news topics and different sensitivity levels, and (iii) news topics significantly associated with investors’ responses differ according to the stock market and sensitivity.
Attitudes towards the ‘Shisha No Thanks’ campaign video: Content analysis of Facebook comments

INTRODUCTION While social media are commonly used in public health campaigns, there is a gap in our understanding of what happens after the campaign is seen by the target audience. This study aims to understand how the Shisha No Thanks campaign video was received by the Facebook audience by analyzing Facebook comments posted to it. Specifically, this study aims to determine whether the Facebook audience accepted or rejected the campaign’s message. METHODS A sample of the Facebook comments was extracted, and the study team, which included cultural support workers, developed content categories consistent with the research question. Each comment was then coded by three team members, and only assigned a category if there was agreement by at least two members. RESULTS Of the 4990 comments that were sampled, 9.1% (456) accepted the campaign message, 22.9% (1144) rejected the message, 21.8% (1089) were unclear, and 46.1% (2301) contained only tagged names. Of the sample, 2.8% (138) indicated the commenter took on board the campaign message by expressing an intention to stop smoking shisha, or asking a friend to stop smoking shisha. Of the comments that showed rejection of the campaign, the majority were people dismissing the campaign by laughing at it or expressing pro-shisha sentiments. CONCLUSIONS This study demonstrates that conducting content analyses of social media comments can provide important insight into how a campaign message is received by a social media audience.
Protective Factors for Loneliness among Adolescents during COVID-19: Role of the Interpersonal Relationships and Sibling Status

This study examined the moderating effects of parent-child, same-sex, opposite-sex and teacher-student relationships between sibling status and loneliness during COVID-19. A total of 1,591 adolescents in China completed the study questionnaires which assessed the aforementioned variables. The results showed that same-sex and teacher-student relationships moderated the association between sibling status and loneliness. The results indicated that among participants with good same-sex relationships during COVID-19, compared to non-only-children participants, the only-children participants were more likely to experience a lower level of loneliness. However, participants with poor same-sex relationships experienced similar level of loneliness regardless of whether they had siblings. These findings would be helpful for parents, teachers, and other stakeholders to take effective measures to reduce loneliness feelings among Chinese adolescents.