Miracle-dz/UniFAR-FTUs huggingface dataset:
AUTOMATIC BANDWIDTH CHOICE IN A SEMIPARAMETRIC REGRESSION MODEL

Speckman (1988) proposed a kernel smoothing method to estimate the parametric component β in the semiparametric regression model y = x τ β +g(t)+e, and showed that this kernel smoothing estimator is √ n-consistent for a certain deterministic bandwidth choice. However, the important issue of automatic band- width choice in this semiparametric setting has not been examined. This paper studies the asymptotic behavior of the bandwidth choice based on a general band- width selector which covers such well known data-driven methods as GCV and CV. This automatic bandwidth choice is proved to be asymptotically optimal and its asymptotic normality is established. The resulting data-driven kernel smoothing estimator of β is then showed to be still √ n-consistent. A simulation study is per- formed to compare small sample behaviors of various commonly used bandwidth selectors in this semiparametric setting, and a real data example is given.
Circulating microRNAs for Early Diagnosis of Ovarian Cancer: A Systematic Review and Meta-Analysis

In this study, we conducted a systematic review and meta-analysis to summarize and evaluate the global research potential of different circulating miRNAs as an early diagnostic biomarker for OC. A systematic literature search for relevant studies was conducted in June 2020 and followed up in November 2021. The search was conducted in English databases (PubMed, ScienceDirect). The primary search resulted in a total of 1887 articles, which were screened according to the prior established inclusion and exclusion criteria. We identified 44 relevant studies, of which 22 were eligible for the quantitative meta-analysis. Statistical analysis was performed using the Meta-package in Rstudio. Standardized mean differences (SMD) of relative levels between control subjects and OC patients were used to evaluate the differential expression. All studies were quality evaluated using a Newcastle–Ottawa Scale. Based on the meta-analysis, nine miRNAs were identified as dysregulated in OC patients compared to controls. Nine were upregulated in OC patients compared to controls (miR-21, -125, -141, -145, -205, -328, -200a, -200b, -200c). Furthermore, miR-26, -93, -106 and -200a were analyzed, but did not present an overall significant difference between OC patients and controls. These observations should be considered when performing future studies of circulating miRNAs in relation to OC: sufficient size of clinical cohorts, development of consensus guidelines for circulating miRNA measurements, and coverage of previously reported miRNAs.
Leptin and the rs2167270 Polymorphism Are Associated with Glycemic Control in Type Two Diabetes Mellitus Patients on Metformin Therapy

Background and Objectives: Type two diabetes mellitus (T2DM) is a chronic disease with debilitating complications and high mortality. Evidence indicates that good glycemic control delays disease progression and is hence a target of disease management protocols. Nonetheless, some patients cannot maintain glycemic control. This study aimed to investigate the association between serum leptin levels and several SNPs of the LEP gene with the lack of glycemic control in T2DM patients on metformin therapy. Materials and Methods: In a hospital-based case-control study, 170 patients with poor glycemic control and 170 patients with good glycemic control were recruited. Serum leptin was measured. Patients were genotyped for three SNPs in the LEP gene (rs7799039, rs2167270, and rs791620). Results: Serum leptin was significantly lower in T2DM patients with poor glycemic control (p < 0.05). In multivariate analysis, serum leptin levels significantly lowered the risk of having poor glycemic control (OR = 0.985; CI: 0.976–0.994; p = 0.002); moreover, the GA genotype of rs2167270 was protective against poor glycemic control compared to the GG genotype (OR = 0.417; CI: 0.245–0.712; p = 0.001). Conclusions: Higher serum leptin and the GA genotype of the rs2167270 SNP of the LEP gene were associated with good glycemic control in T2DM patients on metformin therapy. Further studies with a larger sample size from multiple institutions are required to validate the findings.
Assessing preferences for mountain wine and viticulture by using a best-worst scaling approach: do mountains really matter for Italians?

European Commission has recently published the rules on the use of the quality term "mountain product". The new regulation aims to promote the sustainable development of mountain areas and to facilitate the identification of mountain products by consumers. Despite the importance of viticulture for several European mountain communities and the growing interest of European consumers in quality certified foods, the regulation did not encompass wines. The literature addresses many issues regarding wines and consumer preferences, but so far mountain wines are not specifically researched. With this study, we seek to fill this gap by analysing Italian consumers’ preferences for mountain wines as well as their opinion on the inclusion of this product in the mountain labelling scheme. To do so, this study applies a best-worst scaling model and subsequent latent class analysis. Data was collected through an online questionnaire applied to a consumer panel. The results indicate that most of respondents are in favour of applying the mountain label to wines. The three most preferred attributes are related to human health, ecological sustainability and product typicity. Most of the participants gave less importance to the attributes that characterize mountain agriculture. Only one consumer segment valued some of these. The findings suggest that the inclusion of mountain wines in the labelling scheme may increase the interest of Italian wine consumers, especially if health, sustainability and typicity are ensured by producers.
Test Consistency with Varying Sampling Frequency

This paper considers the consistency property of some test statistics based on a time series of data. While the usual consistency criterion is based on keeping the sampling interval fixed, we let the sampling interval take any equispaced path as the sample size increases to infinity. We consider tests of the null hypotheses of the random walk and randomness against positive autocorrelation (stationary or explosive). We show that tests of the unit root hypothesis based on the first-order correlation coefficient of the original data are consistent as long as the span of the data is increasing. Tests of the same hypothesis based on the first-order correlation coefficient of the first-differenced data are consistent against stationary alternatives only if the span is increasing at a rate greater than T½, where T is the sample size. On the other hand, tests of the randomness hypothesis based on the first-order correlation coefficient applied to the original data are consistent as long as the span is not increasing too fast. We provide Monte Carlo evidence on the power, in finite samples, of the tests Studied allowing various combinations of span and sampling frequencies. It is found that the consistency properties summarize well the behavior of the power in finite samples. The power of tests for a unit root is more influenced by the span than the number of observations while tests of randomness are more powerful when a small sampling frequency is available.
Optimal Strategies of Customization and Information Sharing in the Presence of Feature Creep

Feature creep captures the phenomenon that additional features result in product complexity and even decrease the usability of products. According to consumers’ heterogeneous tastes for products’ sophisticated features, we divide them into the low-end segment and the high-end segment. The proportions of the two segments are uninformed as to the manufacturer, but known to the platform. We take into account feature creep, and consider a supply chain consisting of a manufacturer and a platform. The manufacturer decides whether to adopt customization strategy, and the platform decides whether to share its private information. By formulating several sequential game models, we explore both firms’ optimal strategies and then examine the impacts of customization production and information sharing on environmental performance. Our findings reveal that adopting customization strategy can drive the manufacturer to improve its innovation efforts and raise the wholesale price. Additionally, if the low-end consumers’ proportion exceeds the manufacturer’s expectations, this improvement can be enhanced when the platform shares its private information, and vice versa. Furthermore, if the cost that the manufacturer takes to embed various functions in the product is quite small, it is environmentally friendly for the manufacturer to adopt customization strategy. While, if the cost is relatively large, taking customization strategy causes even greater negative effects on the environment. In addition to generating higher profits for both parties, the platform sharing its private information also contributes to lowering the environmental performance in certain conditions.
Design and Development of a Wearable Wristband for Measuring Pulse Transit Time (PTT) using Pressure Sensors

Pulse diagnosis using noninvasive methods is a valuable technique in clinical applications. Wearable wristbands that measure pulse transit time (PTT) are becoming increasingly essential devices for diagnosing cardiac activities. While attempts have been made to predict blood pressure using PTT with various algorithms, it has been observed that PTT and its inverse parameter, pulse wave velocity (PWV), can vary over time. PTT can be measured between any two points in the body. An experiment is performed to fix the positioning of the sensors at the radial artery wrist with minimum standard deviation. Pressure sensors are used to capture the wrist pulse signals at the radial artery of the wrist with two different distances. Two pressures are initially tested to capture the PTT with 2.5 cms gap and later PTT is recorded with 4.5 cms gap. 11 participants are used to acquire the wrist pulse data from the designed pressure sensor. The coefficient of variation was computed for the PTT and best possible distance for the sensor is concluded.
Relative Validity and Reproducibility of a Web-Based Semi-Quantitative Food Frequency Questionnaire in the Danish Diet, Cancer, and Health—Next Generations MAX Study

The food frequency questionnaire (FFQ) is designed to capture an individual’s habitual dietary intake and is the most applied method in nutritional epidemiology. Our aim was to assess the relative validity and reproducibility of the FFQ used in the Diet, Cancer, and Health—Next Generations cohort (DCH-NG). We included 415 Danish women and men aged 18–67 years. Spearman’s correlations coefficients, Bland–Altman limits of agreement and cross-classification between dietary intakes estimated from the FFQ administered at baseline (FFQbaseline), and the mean of three 24-h dietary recalls (24-HDRs) and the FFQ administered after 12 months (FFQ12 months) were determined. Nutrient intakes were energy-adjusted by Nutrient Density and Residual methods. Correlation coefficients ranged from 0.18–0.58 for energy and energy-adjusted nutrient intakes, and the percentage of participants classified into the same quartile ranged from 28–47% between the FFQbaseline and the 24-HDRs. For the FFQ12 months compared with FFQbaseline, correlation coefficients ranged from 0.52–0.88 for intakes of energy, energy-adjusted nutrients, and food groups, and the proportion of participants classified into the same quartiles ranged from 43–69%. Overall, the FFQ provided a satisfactory ranking of individuals according to energy, nutrient, and food group intakes, making the FFQ suitable for use in epidemiological studies investigating diet in relation to disease outcomes.
Comparison between the performance of artificial neural network and adaptive neuro-fuzzy inference system in modelling crop evapotranspiration of a maize crop in soil amended with biochar and inorganic fertilizer

The success of irrigation management is highly dependent on the accurate estimation of crop evapotranspiration (ETc), necessitating the need to accurately and precisely determine the performance of artificial intelligence (AI) in predicting maize crop under different soil conditions. The crop evapotranspiration is affected by the soil conditions and the meteorological parameters. Therefore, the amount of soil conditioners (biochar and inorganic fertilizer) in the field study under different water application levels were used as model input. In addition, the meteorological data were included as part of the model input. AI models (ANN and ANFIS) were used for the prediction. The crop evapotranspiration were determined in the field using water balance method. Also, the performance evaluation of the considered models were carried out by using metrics like Root Mean Square Error (RMSE), Normalized Root Mean Square Error (NRMSE), Mean Absolute Error (MAE) and the coefficient of determination $(\mathbf{r}^{2})$. Result of the analysis showed that during training, the coefficient of determination $(\mathbf{r}^{2})$ was 0.998, 0.95, and 0.96 for ANFIS, ANN-LOGSIG and ANN-TANSIG, respectively. Similarly, the testing result showed a very high accuracy and precision in terms of the $\mathbf{r}^{2}$, RMSE and the MAE values. During validation, $\mathbf{r}^{2}$ values were 1, 0.996 and 0.999 for ANFIS, ANN-LOGSIG and ANN-TANSIG, respectively. The prediction of all data showed that $\mathbf{r}^{2}$ were 0.988, 0.984, and 0.997 for the ANN-LOGSIG, ANN-TANSIG and ANFIS models. Therefore, the incorporation of AI model into the estimation of crop water use may be important for proper and adequate water budgeting in Agriculture
Modelling of transmission lines using idempotent decomposition

The modelling of wave propagation in multiconductor transmission line involves full matrices for the wave propagation and characteristic impedances functions. Modal decomposition, as in the fdLine model in the EMTP, leads to an elegant and numerically efficient solution, even in the presence of frequency dependent parameters. The advantages of modal decomposition are lost, however, when the transformation matrix relating modal and phase quantities cannot be assumed constant and real but is complex and changes with frequency. This is the case, for instance, when there is strong conductor asymmetry in multicircuit transmission lines and cable systems. A number of alternatives have been proposed to solve the problem of frequency dependent transformation matrices: from frequency synthesis of the transformation matrices to working directly in the phase domain. Both of these approaches, however, have drawbacks. Direct synthesis of the transformation matrices with stable rational functions is difficult because the eigenvectors that make up the columns of these matrices are not uniquely defined at each frequency point. Direct phase-domain modelling is also difficult because an Af-phase transmission line has TV propagation modes and N time delays and the N elements of [Ap h a s e] are a combinations of these basic travelling times and modes. The idempotent Line Model (idLine) expresses the line propagation function as a matrix directly in phase coordinates [Ap h a s e] (thus avoiding modal transformation matrices), but the expression is in terms of the N natural propagation modes (thus avoiding mixed-up travelling times). With idempotent decomposition, the line
Co-creation of food tourism experiences: Tourists’ perspectives of a Lisbon food tour

Gastronomy has become a distinctive tourism product with the potential of contributing to visitors’ engaged immersion in destinations. Few studies have reflected on visitors’ perceptions of participation in food tour experiences, and research on co-creation in food tours is even more scarce. This study analyses co-creative tourism experience dimensions, previously identified in the literature, through a passive netnography, involving 658 online tourist reviews on TripAdvisor of a food tour experience in Lisbon, to understand how value was co-created by comparing the perceptions of visitors and the service provider. Interview-based data were subject to content analysis. Results showed that “aesthetics/sense,” “feel,” “thinking/education,” “relate,” and “personalization” were the most reported dimensions in tourists’ discourse, which was confirmed by the service provider. The present study provides insights to destination management organizations, marketers and entrepreneurs in creating opportunities for and designing appealing co-creative food experiences.
Classifying European Court of Human Rights Cases Using Transformer-Based Techniques

In the field of text classification, researchers have repeatedly shown the value of transformer-based models such as Bidirectional Encoder Representation from Transformers (BERT) and its variants. Nonetheless, these models are expensive in terms of memory and computational power but have not been utilized to classify long documents of several domains. In addition, transformer models are also often pre-trained on generalized languages, making them less effective in language-specific domains, such as legal documents. In the natural language processing (NLP) domain, there is a growing interest in creating newer models that can handle more complex input sequences and domain-specific languages. Keeping the power of NLP in mind, this study proposes a legal documentation classifier that classifies the legal document by using the sliding window approach to increase the maximum sequence length of the model. We used the ECHR (European Court of Human Rights) publicly available dataset which to a large extent is imbalanced. Therefore, to balance the dataset we have scrapped the case articles from the web and extracted the data. Then, we employed conventional machine learning techniques such as SVM, DT, NB, AdaBoost, and transformer-based neural networks models including BERT, Legal-BERT, RoBERTa, BigBird, ELECTRA, and XLNet for the classification task. The experimental findings show that RoBERTa outperformed all the mentioned BERT versions by obtaining precision, recall, and F1-score of 89.1%, 86.2%, and 86.7%, respectively. While from conventional machine learning techniques, AdaBoost outclasses SVM, DT, and NB by achieving scores of 81.9%, 81.5%, and 81.7% for precision, recall, and F1-score, respectively.
Comparison Conditions in Research on Persuasive Message Effects: Aligning Evidence and Claims About Persuasiveness

ABSTRACT In persuasion message effects research, two kinds of research design are common. One compares the persuasiveness of two different advocacy messages on the same topic. The other compares the persuasiveness of an advocacy message against a no-advocacy-message control condition. Because these two designs contain different comparisons they underwrite different claims, but the designs – and their corresponding claims – are prone to misunderstanding and confusion. And when a study combines the two designs, especially complex issues can arise. This article aims to sort out the relevant issues in the service of better alignment between evidence and claims in persuasive message effects research.
On Some Generalization of Smoothing Problems

AbstractThe paper deals with the generalized smoothing problem in abstract Hilbert spaces. This generalized problem involves particular cases such as the interpolating problem, the smoothing problem with weights, the smoothing problem with obstacles, the problem on splines in convex sets and others. The theorem on the existence and characterization of a solution of the generalized problem is proved. It is shown how the theorem gives already known theorems in special cases as well as some new results.
Categorization and Evaluation Methods for Control Strategies of Bilateral Tasks in Arm Prosthetics

Controlling multi-joint prostheses intuitively and effortlessly has been a research topic since the appearance of the first electric elbow prostheses. Researchers mainly focused on single handed tasks, however in daily life these are mostly executed with the healthy hand and the prosthetic arms only become relevant for two-handed manipulations. Thus, a new approach is presented in this paper addressing bilateral tasks. A taxonomy for bilateral tasks is elaborated in order to categorize and prioritize bilateral manipulations involving a prosthetic arm. Five different key figures for rating bilateral movements are introduced and used to form two quality criteria, which allow evaluation and comparison of different control strategies. Based on the proposed taxonomy and quality criteria, a generalized benchmark test environment is developed with five different evaluation scenarios and realized in virtual reality in an exemplary manner. Furthermore, a new controller-agent strategy, greatly facilitating the usage of prosthetic arms, is presented. The effectiveness of the criteria for evaluation of different control strategies is demonstrated with healthy subjects. With this evaluation concept, we provide the community a means to explore and compare controlling methods and inputs, facilitating the progress and development of new strategies.
Condition “Vasa Vasorum” in Patients with Thoracic Aortic Aneurysm

It is known that vasa vasorum contributes substantially to the blood supply and nutrition of one-third of the wall of the ascending thoracic aorta. Therefore, we focused on studying the relationship between inflammatory cells and vasa vasorum vessels in patients with aortic aneurysm. The material for the study was biopsies of thoracic aortic aneurysms taken from patients during an aneurysmectomy (34 men, 14 women, aged 33 to 79 years). The biopsies belonged to patients with non-hereditary thoracic aortic aneurysm. An immunohistochemical study was carried out using antibodies to antigens of T cells (CD3, CD4, CD8); macrophages (CD68); B cells (CD20); endothelium (CD31, CD34, von Willebrand factor (vWF)); and smooth muscle cells (alpha actin). Samples without inflammatory infiltrates contained less vasa vasorum in the tunica adventitia than samples with inflammatory infiltrates, and this difference was statistically significant p < 0.05. T cell infiltrates in the adventitia of aortic aneurysms were found in 28 of 48 patients. In the vessels of the vasa vasorum, surrounded by inflammatory infiltrates, T cells that adhered to the endothelium were found. The same cells were also localized in the subendothelial area. The number of adherent T cells in patients with inflammatory infiltrates in the aortic wall dominated the number of these cells in patients without inflammation of the aortic wall. This difference was statistically significant, p < 0.0006. Hypertrophy and sclerosis of the arteries of the vasa vasorum system, the narrowing of their lumen, and, as a result, impaired blood supply to the aortic wall, were found in 34 patients with hypertension. In 18 patients (both in patients with hypertension and in patients without hypertension), T cells that adhered to the vasa vasorum endothelium were found. In nine cases, massive infiltrates of T cells and macrophages were found, which surrounded and squeezed the vasa vasorum, preventing blood circulation. In six patients, parietal and obturating blood clots were found in the vasa vasorum vessels, which disrupted the normal blood supply to the aortic wall. We believe that this indicates the importance of the state of the vessels of the vasa vasorum in the development of an aortic aneurysm. In addition, pathological changes in these vessels may not always play a primary role, but always a very important role, in the pathogenesis of this disease.