Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation between pulse wave velocity and other measures of arterial stiffness in chronic kidney disease.

AIM Pulse wave velocity (PWV), augmentation index (AIx) and time to first wave reflection (Tr) are all measures of arterial stiffness, but whether these parameters behave similarly in different populations is not well-understood. Given the large burden of cardiovascular disease in individuals with chronic kidney disease (CKD), assessing the relationship between vascular stiffness parameters in this population is important. METHOD A subset of 152 participants enrolled in the Chronic Renal Insufficiency Cohort Study had vascular stiffness parameters (aortic PWV, central AIx, and Tr) measured using the SphygmoCor system. Linear association between these parameters was assessed using Pearson correlation coefficients. Reproducibility across operators of the device was also tested within individuals. RESULTS Association was largest between PWV and heart rate-adjusted AIx (AIx-75). The correlation coefficient was 0.371 (p = 0.0003) for ideal studies and 0.305 (p = 0.0001) for all technically acceptable studies. The association between ideal PWV and AIx-75 measurements was 0.361 (p = 0.005) for men and 0.423 (p = 0.01) for women. Bland-Altman plots comparing the mean value of PWV (n = 31) or AIx-75 (n = 21) when measured by 2 different individuals against the difference in their respective values demonstrate that both measures of arterial stiffness are reproducible across multiple technicians. CONCLUSIONS Thus, we conclude that PWV and AIx-75, despite measuring different quantities in different units, are related measures of arterial stiffness and are reproducible across multiple operators in the population with CKD.
EFFECT OF PROCESSING METHODS ON THE CHEMICAL COMPOSITION AND STORAGE STABILITY OF MAIZE-MILLET-SOYBEAN COMPLEMENTARY FOOD

There is paucity of information concerning the use of multiple processing methods in the production of food products especially complementary foods. Multiple processing methods could provide alternative for improving the nutritional quality of food products. This study was carried out to investigate the effect of combining two or more processing methods on the proximate composition, chemical, and storage stability of maize-millet-soybean complementary foods. Maize, millet, and soybean grains were processed using submerged fermentation, germination and roasting methods (120 ± 10 o C) singly and combined. The fermented, germinated, roasted, and untreated (control) grains were dried in an air oven at 55 °C for 48 h to 10% moisture content and milled separately into fine flours (450 μm). Four complementary food samples (including the control) were formulated and mixed in ratio 50:30:20 maize, millet, and soybean respectively, and analyzed for proximate composition, chemical, and storage stability. The complementary food samples were stored for 13 weeks at ambient temperature (30 ± 2 o C) to determine its storage stability and shelflife. Data were analyzed using computer software for analysis of variance, while Duncan multiple range test (DMRT) was used to separate means where there is a significant difference. Results showed that combining fermentation or germination with roasting method significantly (p<0.05) increased the crude fat, fiber, and free sugar, while starch content of the complementary food samples compare to SC (control) as a result of combined processing methods. The results shows that there were significant difference (p<0.05) in the shelf life of the complementary foods with SFR sample having the best storage stability and shelf life. The study showed that combination of fermentation and roasting methods enhanced proximate composition, chemical, and shelf stability complementary food produced from maizemillet-soybean for infants and young children.
MENTAL TOUGHNESS AND PRE-GAME MENTAL STATES IN ADOLESCENT FOOTBALL PLAYERS: THE MEDIATING ROLE OF ACHIEVEMENT GOALS

Аннотация Психологическая устойчивость высоко ценится в соревновательных видах спорта, так же как и компетенция предсоревновательного восприятия и позитивный психологический настрой. Механизмы, через которые психологическая устойчивость приводит к улучшению предигрового психологического настроя, однако, по-прежнему мало изучены. Таким образом, целью данного исследования было изучение процесса достижения целей, опосредованного связью между психологической устойчивостью и эффективностью ключевых психических состояний, а именно, уверенностью в себе и внимательностью. В исследовании приняли участие 112 подростков, участвующих в соревнованиях по американскому футболу. Участники прошли процедуру измерения психологической устойчивости за неделю до начала соревнований и момента достижения поставленных целей и ответили на вопросы анкет о психологическом состоянии, две из которых заполнялись в течение 30 минутного периода соревнований. Результаты показали, что эго-ориентация значительно опосредует связь между психической устойчивостью и уверенностью в себе, эффект общей модели R2=33.16%, и между психической устойчивостью и внимательностью, эффект общей модели R2=32.32%. Таким образом, более высокий эго-фокус (желание выиграть) может оказаться полезным в предсоревновательный период и на нем должно акцентироваться внимание спортсменов, тренеров и спортивных психологов. Ключевые слова: психическая устойчивость, подростки, достижения целей, соревновательные состояния.
Informedia digital video library

Vastdigital libraries of information will soon be available on the nation’s Information Superhighway as a result of emerging technologies for multimedia computing. These libraries wiU profoundly impact the conduct of business, professional, andpersonal activity. However, it is not enough to simply store and play back video (ss in currently envisioned commercial video-on-demand services); to be most effective, new technology is needed for searching through these vast data collections and retrieving the most relevant selections.
The Antikythera Mechanism: From the bottom of the sea to the scrutiny of modern technology

The Antikythera Mechanism is an ancient greek analogue astronomical computer. Using a handle, probably similar to a doorknob, the user could insert an input date on a dial in its front side. The calculations were made using a set of gears (at least 30), and the results were displayed on several scientific scales. It was used to calculate the diurnal and annual motion of the Sun, the Moon and (most probably) the planets among the stars. It put into practice the astronomical knowledge of ancient Greeks about the motion of these objects with astonishing accuracy, including eccentric gearing for the anomalous orbit of the Moon (first lunar anomaly). It could also predict eclipses of the Sun and the Moon from the Saros period, which has been found in one of its back scales. It calculated the dates of the Olympic Games (and the other major crown games that took place in ancient Greece). Finally it was equipped with extended Dorian inscriptions, often quoted as User’s Manual. Its complexity and multiple functions indicate that it was not used for a single purpose. I strongly believe that its main use was for educational purposes. The Antikythera Mechanism was as important for the development of Technology, as the Parthenon for the development of Architecture. Taking into account the theoretical and technological knowledge required for the construction of the Mechanism, it can easily be ranked among the Wonders of the Ancient World.
From Mordell to Zilber-Pink The Mordell conjecture

This lecture is concerned with some recent applications of mathematical logic to Diophantine geometry. More precisely it concerns applications of o-minimality, a branch of model theory which treats tame structures in real geometry, to certain finiteness problems descending from the classical conjecture of Mordell. Mathematics Subject Classification (2010). Primary 03C64, 11G18.
University of Groningen First-year university students ’ academic success

Considering the pivotal role of academic adjustment for student success, it is important to gain insight into how several motivational and behavioural factors affect academic adjustment and the extent to which academic adjustment influences student success. This empirical study investigated how intrinsic motivation, academic self-efficacy, selfregulated study behaviour and satisfaction with the chosen degree programme influenced academic adjustment in university and how these variables and adjustment affected three important indicators of student success: grade point average (GPA), attained number of credits (ECTS) and intention to persist. The sample consisted of 243 first-year university students in the Netherlands. Structural equation modelling showed that academic adjustment was influenced by intrinsic motivation, self-regulated study behaviour and degree programme satisfaction, which together explained 72% of the variance in adjustment. Motivational and behavioural variables did not influence GPA and credits directly but through academic adjustment. Furthermore, only satisfaction with the degree programme predicted intention to persist. These results point to the importance of academic adjustment in predicting university GPA and credits and the pivotal role of satisfaction with the degree programme in predicting intention to persist. Universities could integrate the development of self-regulated study skills—the biggest contributor to academic adjustment—in the first-year programme. Moreover, looking at the importance of students’ satisfaction with the programme, communication and collaboration between secondary schools and universities should be enhanced in order to Eur J Psychol Educ (2018) 33:749–767 DOI 10.1007/s10212-017-0347-8 * Els C. M. van Rooij e.c.m.van. rooij@rug.nl Ellen P. W. A. Jansen e.p.w.a. jansen@rug.nl Wim J. C. M. van de Grift w.j.c.m.van.de. grift@rug.nl 1 Department of Teacher Education, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, The Netherlands First-year university students’ academic success: the importance of academic adjustment help students to choose a university degree programme that matches their abilities, interests and values.
Chapter 11 . Towards OpenTagging Platform using Semantic Web Technologies

Many social media sites such as Del.icio. us, Flickr, or weblogs have recently become popular. This has led to adoption of tagging functions on traditional web sites at a steady pace. However, producing tagging data from these sites without supporting the social exchange involved can be regarded as an incomplete set of metadata. Although tagging captures our individual conceptual associations, the tagging system itself does not promote a social transmission that units both creators and consumers. To achieve social transmission environments for tagging, we need a formal conceptual model to represent the tagging activity and a service platform to encourage its exchange and interoperation.
Phytochemical analysis , antifungal bioassay and folklore uses of selected medicinal plants of family Rosaceae

Keeping in view the traditional uses of medicinal plants, this study was conducted to evaluate the antifungal activity of selected members of family Rosaceae for the first time. Activity of Rosa indica L. Prunus amygdalus L. and Prunus armeniaca L was evaluated against the Penicillium digitatum L. Antifungal activity of the aforementioned plant extracts were indicated by the measuring zone of inhibition on agar plate. Highest activity against the test strain of fungus was recorded in ethanol extracts of the selected plants. Antifungal activity of extracts from the selected plants was dependent on the concentration of the extracts with highest activity being recorded when its strength was 15%. Maximum zone of inhibition (19.6 mm) was formed against the test fungus exposed to 15% root extract of R. indica L. taken in ethanol. However, aqueous root extract of the same plant was less effective indicating that the bioactive compound(s) in the root were of relatively low polarity. Bioactive compounds of the other two plants were also of low polarity as their activity was relatively greater when extracted in ethanol than that in aqueous extract. Contrary to R. indica, Leave of P. armeniaca were seat of high amount of bioactive compounds. While flavonoids and tannin were recorded in all samples, alkaloids and carbohydrates were found only in R. indica L. Similarly, fixed oil and fats were present in P. amygdalus L. and P. armeniaca L only. According to antifungal activity the aforementioned plants can be arranged as R. indica L. >P. armeniaca L. >P. amygdalus L. It may be concluded that these plants may be of great medicinal value and may provide a source of valuable novel compounds.
Prediction of energy load of buildings using machine learning methods

The climatic conditions within the residential buildings in warm climates can be modified with the use of air conditioners equipments. However, constant use of these equipments may result in high energy consumption. To reduce the use of such equipments and maintain the desired internal temperature is possible to design energy-efficient buildings. To measure the energy efficiency of a building is necessary to estimate its heating and cooling loads, considering some of its physical characteristics defined in the design. Machine Learning Methods can be applied to this problem estimating an answer from a set of inputs. These methods require a training phase, called supervised training, which considers a database drawn from selected variables in the problem domain. This work evaluates the performance of four Machine Learning Methods in the prediction of cooling and heating loads of residential buildings. The training database consists of eight input variables and two output variables, derived from building designs. Methods were selected according to an exhaustive search and adjusted by a strategy with cross-validation. To the evaluate were used four performance metrics. This strategy resulted in algorithms with optimized parameters and allowed to obtain competitive results with the literature.
A conceptual model of m-commerce customers' continuance intention based on the customers' perceived value

In the research field of mobile commerce (m-commerce), attention is focused on customers' adoption of m-commerce. However, the success of enterprises depends on customers' long-term use. In this paper, through contrasting the dimensions of customers' perceived value and factors that affect the m-commerce customer's behaviour, we propose the dimensions of m-commerce customer's perceived value and the conceptions of these dimensions. Based on the key conception of m-commerce customers' perceived value, we extend the expectation-confirmation model for information technology and build a conceptual model of m-commerce customers' continuance intention.
Infrared Stripe Correction Algorithm Based on Wavelet Analysis and Gradient Equalization

In the uncooled infrared imaging systems, owing to the non-uniformity of the amplifier in the readout circuit, the infrared image has obvious stripe noise, which greatly affects its quality. In this study, the generation mechanism of stripe noise is analyzed, and a new stripe correction algorithm based on wavelet analysis and gradient equalization is proposed, according to the single-direction distribution of the fixed image noise of infrared focal plane array. The raw infrared image is transformed by a wavelet transform, and the cumulative histogram of the vertical component is convolved by a Gaussian operator with a one-dimensional matrix, in order to achieve gradient equalization in the horizontal direction. In addition, the stripe noise is further separated from the edge texture by a guided filter. The algorithm is verified by simulating noised image and real infrared image, and the comparison experiment and qualitative and quantitative analysis with the current advanced algorithm show that the correction result of the algorithm in this paper is not only mild in visual effect, but also that the structural similarity (SSIM) and peak signal-to-noise ratio (PSNR) indexes can get the best result. It is shown that this algorithm can effectively remove stripe noise without losing details, and the correction performance of this method is better than the most advanced method.
Effect of Erosion on Water Absorption and Morphology for Treated Date Palm Fiber-Reinforced Polyester Composites

In this study, a composite material contains a matrix (Polyester resin) and a natural fiber (Date Palm) was prepared . The volume fraction for date palm fibers was 40% in all prepared composite materials. All samples were prepared by hand layup process, A chemical treatment with at 5% concentration Maleic acid solutions for 20 hours is conducted, and tested under erosion conditions. The results showed a weight with time due to presence of voids on the surface of composite. Also, the increasing of drying time leads to decrease water absorption in case of longitudinal direction and transverse direction for date palm fibers in composite materials. Index Term-Date palm fiber, Erosion, Water absorption, Morphology, Composite Material.
AISB ’ 05 Virtual Social Characters Symposium Can Embodied Conversational Agents Induce Empathy In Users ?

In this paper, we discuss the results of a study which was aimed at investigating which forms of empathy may be induced by ECAs on users, how empathy can be measured and which aspects of the ECA’s behaviour may increase this effect. The study was performed with a Wizard of Oz tool which enabled us to vary easily the agent’s behaviour, and involved subjects with different backgrounds.
Stock Market Prediction Using Machine Learning Methods

Stock price forecasting is a popular and important topic in financial and academic studies. Share market is an volatile place for predicting since there are no significant rules to estimate or predict the price of a share in the share market. Many methods like technical analysis, fundamental analysis, time series analysis and statistical analysis etc. are used to predict the price in tie share market but none of these methods are proved as a consistently acceptable prediction tool. In this paper, we implemented a Random Forest approach to predict stock market prices. Random Forests are very effectively implemented in forecasting stock prices, returns, and stock modeling. We outline the design of the Random Forest with its salient features and customizable parameters. We focus on a certain group of parameters with a relatively significant impact on the share price of a company. With the help of sentiment analysis, we found the polarity score of the new article and that helped in forecasting accurate result. Although share market can never be predicted with hundred per-cent accuracy due to its vague domain, this paper aims at proving the efficiency of Random forest for forecasting the stock prices.
The Use of Exhaled Nitric Oxide in the Management of Asthma

It has recently become clear that airways disease associated with eosinophilic airway inflammation, but not other patterns of inflammation, is closely associated with favourable short-and long-term responses to corticosteroid therapy, irrespective of the clinical context in which it occurs. Moreover, a raised exhaled nitric oxide (FENO) is a reasonable marker of eosinophilic airway inflammation, which has a number of advantages as a diagnostic and monitoring tool. In this review we outline essential background information on the use of FENO in clinical practice and discuss some recent work evaluating the clinical value of this technique.
AUTOMATED ATTENDANCE CAPTURE AND TRACKING SYSTEM EU

The increasing number of students in colleges or universities is becoming a challenge for the lecturers especially when taking their attendance. Besides that, some students might just come to get their attendance marked and then leave the class. As existing systems do not track the students before marking their attendance, students are able to leave the class once their attendances are taken, resulting in the attendance taken by the system to be not accurate. Hence, in this paper, a tracking algorithm which will ensure that the students were actually present for certain duration of time before having their attendance taken by the system is proposed, resulting in a more accurate attendance capturing system. This system employs the Viola-Jones method for the face detection algorithm and Eigenfaces method for the face recognition algorithm. The tracking was done by allocating points to students who were successfully recognized and then dividing the total point for each student with the system’s counter that represents the total time of the lecture. The proposed system was able to achieve a 78% attendance marking accuracy. From the results obtained, it is found that the system is able to verify that the students are present for a set duration of time before marking their attendance which improves the accuracy of the attendance capture system.
The Relationship Between Platelet–Lymphocyte Ratio, Neutrophil–Lymphocyte Ratio, and Survival in Metastatic Gastric Cancer on Firstline Modified Docetaxel and Cisplatinum Plus 5 Fluorourasil Regimen: A Single Institute Experience

Background/Aims: The association between platelet–lymphocyte ratio (PLR), neutrophil–lymphocyte ratio (NLR), and survival with response rates were evaluated in metastatic gastric cancer (MGC). Patients and Methods: MGC patients on firstline modified docetaxel/cisplatinum/5-fluorourasil [mDCF; docetaxel 60 mg/m2 (days 1–5), cisplatin 60 mg/m2 (day 1), 5FU 600 mg/m2 (days 1–5), q3w] were evaluated retrospectively. The cutoff values were 160 for PLR and 2.5 for NLR. Progression-free survival (PFS) and overall survival (OS) were estimated for group I (PLR >160), group II (PLR ≤ 160), group III (NLR ≥ 2.5), group IV (NLR < 2.5), group V (PLR > 160 and NLR ≥ 2.5), group VI (PLR ≤ 160 and NLR <2.5), and group VII [VIIa (PLR > 160 and NLR < 2.5) and VIIb (PLR ≤160 and NLR ≥ 2.5)]. Results: One hundred and nine MGC patients were evaluated for basal hematological parameters and survival analysis, retrospectively. Most of the patients were male in their fifties with grade III adenocarcinoma (62.9%) and liver metastasis (46.7%). Patients with PLR > 160 and/or NLR ≥ 2.5 had significantly shorter PFS and OS (P = 0.04, 0.01, 0.019, and P = 0.003, 0.002, 0.000, respectively). Conclusion: High PLR (> 160) and/or NLR (≥ 2.5) seem to be poor prognostic factors in MGC.
Exploration of coping styles in male patients with head and neck cancer: a prospective cohort study

ABSTRACT Majority of head and neck cancer (HNC) patients are male, and more than 85% of patients with HNC have the habit of smoking and drinking. Due to the specific demographic characteristics, HNC patients are anticipated to have specific coping styles, affecting psychological distress, survival, and quality of life. We explored the subscales of the Mental Adjustment to Cancer (MAC) Scale in male patients with HNC, and then examined the correlation between revised subscales of the MAC scale and anxiety/depression. Participants were 150 male inpatients with HNC, and their demographic and medical data were obtained. Coping style was assessed by MAC scale. Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale. Out of 40 items in the original MAC scale, 19 items were excluded by factor analysis, and the remaining 21 items were divided into three factors: Negative Adjustment, Positive Adjustment, and Abandonment. Negative and Positive Adjustments were similar to the copings of mixed gender patients with heterogeneous cancers, and Abandonment was a new subscale specific to male patients with HNC. This subscale had a weak positive correlation with anxiety and depression. Male HNC patients revealed a specific coping style of Abandonment, related with psychological distress. We believe that an understanding of the Abandonment coping style revealed in our study will improve the psychological support offered to male patients with HNC.