Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Parental Influences in the Theory of Normative Social Behavior

The theory of normative social behavior (TNSB) suggests that injunctive norms, group identity, outcome expectations, and peer communication moderate this relation between descriptive norms and behavioral intentions. This article extends the TNSB by conceptualizing parental influences (parental monitoring and disapproval) as important moderators in the relationship between descriptive norms and Korean mid-adolescents’ prior drinking behaviors as well as their drinking intentions. A study was conducted among Korean high school students (N = 538) to assess their normative perceptions, parental monitoring, parental disapproval of drinking, drinking intentions, and past alcohol use. The current study found a significant association between parental monitoring and disapproval, on the one hand, and drinking and intentions, on the other, after controlling for descriptive norms. The results revealed that the harmful effects of adolescents’ perceptions about the prevalence of alcohol consumption among their peers may be mitigated through active parental involvement. When adolescents believed that their parents closely monitored and expressed disapproval of their drinking, they were less likely to be influenced by the high-risk behaviors practiced by their peers.
Molecular docking interaction of Mycobacterium tuberculosis LipB enzyme with Isoniazid, Pyrazinamide and a structurally altered drug 2, 6 Dimethoxyisonicotinohydrazide

Tuberculosis is an infectious airborne disease caused by a bacterial infection that affects the lungs and other parts of the body. Vaccination against tuberculosis is available but proved to be unsuccessful against emerging multi drug and extensive drug resistant bacterial strains. This in turn raises the pressure to speed up the research on developing new and more efficient anti-tuberculosis drugs. Lipoate biosynthesis protein B (LipB) is found to play vital role in the lipoylation process in Mycobacterium tuberculosis and thus making it a very promising drug target. The existing first line drugs such as Isoniazid, Pyrazinamide and Rifampicin etc shows only profound binding affinity with this target protein. Therefore, new or modified drugs with better docking approach that exhibit a closer and stronger binding affinity is essential. This current study opens up a novel approach towards anti-tuberculosis agents by determining drugs that share similar structures with some of the best available first line drug and also happen to possess better binding affinity. In this article, a computational method by which, pristine as well certain first line and structurally modified drugs were docked with the LipB protein target; where, structurally modified 2, 6 Dimethoxyisonicotinohydrazide show superior target docking.
Information fusion and decision-making using belief functions : application to therapeutic monitoring of cancer. (Fusion de l'information et prise de décisions à l'aide des fonctions de croyance : application au suivi thérapeutique du cancer)

Radiation therapy is one of the most principal options used in the treatment of malignant tumors. To enhance its effectiveness, two critical issues should be carefully dealt with, i.e., reliably predicting therapy outcomes to adapt undergoing treatment planning for individual patients, and accurately segmenting tumor volumes to maximize radiation delivery in tumor tissues while minimize side effects in adjacent organs at risk. Positron emission tomography with radioactive tracer fluorine-18 fluorodeoxyglucose (FDG-PET) can noninvasively provide significant information of the functional activities of tumor cells. In this thesis, the goal of our study consists of two parts: 1) to propose reliable therapy outcome prediction system using primarily features extracted from FDG-PET images; 2) to propose automatic and accurate algorithms for tumor segmentation in PET and PET-CT images. The theory of belief functions is adopted in our study to model and reason with uncertain and imprecise knowledge quantified from noisy and blurring PET images. In the framework of belief functions, a sparse feature selection method and a low-rank metric learning method are proposed to improve the classification accuracy of the evidential K-nearest neighbor classifier learnt by high-dimensional data that contain unreliable features. Based on the above two theoretical studies, a robust prediction system is then proposed, in which the small-sized and imbalanced nature of clinical data is effectively tackled. To automatically delineate tumors in PET images, an unsupervised 3-D segmentation based on evidential clustering using the theory of belief functions and spatial information is proposed. This mono-modality segmentation method is then extended to co-segment tumor in PET-CT images, considering that these two distinct modalities contain complementary information to further improve the accuracy. All proposed methods have been performed on clinical data, giving better results comparing to the state of the art ones.
Hyperhomocysteinemia, Pregnancy Complications, and the Timing of Investigation

OBJECTIVE: To assess associations between vitamin-dependent homocysteine metabolism and vascular-related pregnancy complications by considering interval between delivery and postpartum investigation and maternal age. METHODS: Case-control study performed at the University Medical Center Nijmegen in the Netherlands. Patients had experienced pregnancy-induced hypertension (n = 37), preeclampsia (n = 144), hemolysis, elevated liver enzymes, low platelets (HELLP) syndrome (n = 104), recurrent early pregnancy loss (n = 544), abruptio placentae (n = 135), intrauterine growth restriction (n = 144), or intrauterine fetal death (n = 104). Controls comprised 176 women with uncomplicated obstetric histories. Oral methionine loading tests and fasting vitamin profiles were performed more than 6 weeks after delivery. Odds ratios and 95% confidence intervals were calculated after logistic regression analysis. RESULTS: Hyperhomocysteinemia was associated with an approximately 2-fold to 3-fold increased risk for pregnancy-induced hypertension, abruptio placentae, and intrauterine growth restriction. Cobalamin deficiency was associated with HELLP syndrome, abruptio placentae, intrauterine growth restriction, and intrauterine fetal death. Pyridoxal 5-phosphate deficiency increased the risk for pregnancy-induced hypertension 4-fold. These associations lost their significance after adjustment for time interval and maternal age. High red cell folate was associated with a decreased risk for abruptio placentae and intrauterine growth restriction. An increased creatinine concentration was associated with pregnancy-induced hypertension, preeclampsia, HELLP syndrome, and abruptio placentae. CONCLUSION: Hyperhomocysteinemia and vitamin deficiencies are largely determined by the interval between delivery and postpartum investigation and by maternal age. Time interval and maternal age should be considered in the risk estimation for vascular-related pregnancy complications. LEVEL OF EVIDENCE: II-2
Lim Domain Binding 2: A Key Driver of Transendothelial Migration of Leukocytes and Atherosclerosis

Objective— Using a multi-tissue, genome-wide gene expression approach, we recently identified a gene module linked to the extent of human atherosclerosis. This atherosclerosis module was enriched with inherited risk for coronary and carotid artery disease (CAD) and overlapped with genes in the transendothelial migration of leukocyte (TEML) pathway. Among the atherosclerosis module genes, the transcription cofactor Lim domain binding 2 (LDB2) was the most connected in a CAD vascular wall regulatory gene network. Here, we used human genomics and atherosclerosis-prone mice to evaluate the possible role of LDB2 in TEML and atherosclerosis. Approach and Results— mRNA profiles generated from blood macrophages in patients with CAD were used to infer transcription factor regulatory gene networks; Ldlr –/– Apob 100/100 mice were used to study the effects of Ldb2 deficiency on TEML activity and atherogenesis. LDB2 was the most connected gene in a transcription factor regulatory network inferred from TEML and atherosclerosis module genes in CAD macrophages. In Ldlr –/– Apob 100/100 mice, loss of Ldb2 increased atherosclerotic lesion size ≈2-fold and decreased plaque stability. The exacerbated atherosclerosis was caused by increased TEML activity, as demonstrated in air-pouch and retinal vasculature models in vivo, by ex vivo perfusion of primary leukocytes, and by leukocyte migration in vitro. In THP1 cells, migration was increased by overexpression and decreased by small interfering RNA inhibition of LDB2. A functional LDB2 variant (rs10939673) was associated with the risk and extent of CAD across several cohorts. Conclusions— As a key driver of the TEML pathway in CAD macrophages, LDB2 is a novel candidate to target CAD by inhibiting the overall activity of TEML.
Axiomatic Analysis of Language Modelling of Recommender Systems

Language Models constitute an effective framework for text retrieval tasks. Recently, it has been extended to various collaborative filtering tasks. In particular, relevance-based language models can be used for generating highly accurate recommendations using a memory-based approach. On the other hand, the query likelihood model has proven to be a successful strategy for neighbourhood computation. Since relevance-based language models rely on user neighbourhoods for producing recommendations, we propose to use the query likelihood model for computing those neighbourhoods instead of cosine similarity. The combination of both techniques results in a formal probabilistic recommender system which has not been used before in collaborative filtering. A thorough evaluation on three datasets shows that the query likelihood model provides better results than cosine similarity. To understand this improvement, we devise two properties that a good neighbourhood algorithm should satisfy. Our axiomatic analysis shows .
Physical performance changes after unsupervised training during the autumn/spring semester break in competitive tennis players

Background: All competitive tennis players take time away from coaches throughout the year; however, little information is available as to the short-term physiological effect of these breaks. Objective: The purpose of this investigation was to evaluate the impact of a 5 week off-campus structured, yet unsupervised, break from regular training in top collegiate tennis players. Methods: A nationally ranked collegiate NCAA Division I male tennis team (n = 8) performed a test battery in December and again in January after a 5 week period of recommended, yet unsupervised, training. The tests performed were 5, 10 and 20 m sprints, spider agility test, medicine ball power throws, standing long jump, Wingate anaerobic power test, VO2max, push-up and sit-up test, grip strength and range of motion (ROM) measures (goniometer) of the shoulder, hip, hamstring and quadriceps. Results: Paired t tests (p<0.05) showed significant decreases in mean (SEM) Wingate power measurements in Watts/kg (pre: 8.35 (0.19) w/kg ; post: 7.80 (0.24) w/kg ), minimum Wingate power (pre: 5.89 (0.27) w/kg; post: 5.10 (0.38) w/kg) and VO2max values (pre: 53.90 (1.11) ml/kg/min; post: 47.86 (1.54) ml/kg/min). A significant increase was seen in the athlete’s fatigue index (pre: 44.26 (2.85)%; post: 51.41 (3.53)%), fastest 5 m (pre: 1.07 (0.03) s; post: 1.12 (0.02) s), 10 m (pre: 1.79 (0.03) s; post: 1.84 (0.04) s) and 20 m (pre: 3.07 (0.05) s; post: 3.13 (0.05) s) sprint times. No significant differences were seen for the other variables tested. Conclusions: These results suggest that a 5 week interruption of normal training can result in significant reductions in speed, power and aerobic capacity in competitive tennis players, likely owing to poor compliance with the prescribed training regimen. Therefore, coaches and trainers might benefit from techniques (eg, pre- and post-testing) requiring athletes’ to have accountability for unsupervised workouts.
Standardised regression coefficient as an effect size index in summarising findings in epidemiological studies

Background: a major problem in evaluating and reviewing the published findings of studies on the association between a quantitative explanatory variable and a quantitative dependent variable is that the results are analysed and reported in many different ways. To achieve an effective review of different studies, a consistent presentation of the results is necessary. This paper aims to exemplify the main topics related to summarising and pooling research findings from multivariable models with a quantitative response variable. Methods: we outline the complexities involved in synthesising associations. We describe a method by which it is possible to transform the findings into a common effect size index which is based on standardised regression coefficients. To describe the approach we searched original research articles published before January 2012 for findings of the relationship between polychlorinated biphenyls (PCBs) and birth weight of new-borns. Studies with maternal PCB measurements and birth weight as a continuous variable were included. Results: the evaluation of 24 included articles reveled that there was variation in variable measurement methods, transformations, descriptive statistics and inference methods. Research syntheses were performed summarizing regression coefficients to estimate the effect of PCBs on birth weight. A birth weight decline related to increase in PCB level was found. Conclusions: the proposed method can be useful in quantitatively reviewing published studies when different exposure measurement methods are used or differential control of potential confounding factors is not an issue.
Subunit-selective proteasome activity profiling uncovers uncoupled 1 proteasome subunit activities during bacterial infections

The proteasome is a nuclear - cytoplasmic proteolytic complex involved in nearly all regulatory 37 pathways in plant cells. The three different catalytic activities of the proteasome can have 38 different functions but tools to monitor and control these subunits selectively are not yet 39 available in plant science. Here, we introduce subunit-selective inhibitors and dual-color 40 fluorescent activity-based probes for studying two of the three active catalytic subunits of the 41 plant proteasome. We validate these tools in two model plants and use this to study the 42 proteasome during plant-microbe interactions. Our data reveals that Nicotiana benthamiana 43 incorporates two different paralogs of each catalytic subunit into active proteasomes. 44 Interestingly, both β1 and β5 activities are significantly increased upon infection with pathogenic 45 Pseudomonas syringae pv. tomato DC3000 lacking hopQ1-1 (PtoDC3000(ΔhQ)) whilst the 46 activity profile of the β1 subunit changes. Infection with wild-type PtoDC3000 causes 47 proteasome activities that range from strongly induced β1 and β5 activities to strongly 48 suppressed β5 activities, revealing that β1 and β5 activities can be uncoupled during bacterial 49 infection. These selective probes and inhibitors are now available to the plant science community 50 and can be widely and easily applied to study the activity and role of the different catalytic 51 subunits of the proteasome in different plant species.
Visual mismatch negativity: the detection of stimulus change

Mismatch negativity is an event related potential generated by a mechanism which detects stimulus change. Such a mechanism is important to enable attention to be switched to important changes in the environment. The effect has been extensively studied in the auditory modality. The present investigation was designed to establish whether the enhanced negativity in the visual event related potential evoked by deviant stimuli presented infrequently among a sequence of repeated standard stimuli is really associated with the detection of stimulus change. The experiment set out to distinguish effects associated with stimulus change from those related to the physical attributes of the stimuli or to differences in the refractory state of receptors or neurons. The findings support the hypothesis that deviance-related negativity reflects the operation of a change detection mechanism and not the refractory state of elements of the visual system.
Hybrid Recommender Systems : The Review of State-ofthe-Art Research and Applications

To date, recommender systems are a popular instrument to make personalized suggestions and provide information about items for users. There are many techniques that can be applied for personalization in recommender systems. All these techniques have complementary strengths and weaknesses. A hybrid recommender system combines two or more recommendation techniques to gain better system performance and mitigate the weaknesses of individual ones. Classification of hybrid recommender systems used in this paper is based on the classification proposed by Burke [1]. The need of a systematic review in the area arises from the requirement to summarize all the information about actual methods and algorithms that are used in hybrid recommended system. These materials will be used to support further research activities aiming to develop the auto-switching hybrid recommender system.
INTRODUCING THE INTERACTION APPROACH FOR SUCCESSFUL BUSINESS RELATIONSHIPS

Many countries in the world, including Croatia, are facing crises in their economies. There are numerous reasons for this situation, and problems of the business market present one of them. Nevertheless, successful business relationships are what keeps the market alive. Those relationships, namely buyer-seller relationships, are creating and influencing the market and economy on the whole. However, Croatia is living in the age of neoliberalism. As a dominant ideology of today´s world, it influences how companies behave on the market. On the one hand, it suggests competition as the best solution for existence. On the other hand, the interaction approach, teaches us to change our perspective and to cooperate on the market. In order to benefit the most, the aim of this paper was to review and compare these two approaches, to highlight their features and main differences, and to support them with empirical evidence. The cases of three Croatian companies show the reality of today´s market and an urgent need for a new business theory and practice. Keywords: Neoliberalism, crises, the interaction approach, competition, cooperation, business relationships
Reduction of Astrogliosis by Early Treatment of Pneumococcal Meningitis Measured by Simultaneous Imaging, In Vivo, of the Pathogen and Host Response

ABSTRACT We developed a method for simultaneous in vivo biophotonic monitoring of pneumococcal meningitis and the accompanying neuronal injury in live transgenic mice. Streptococcus pneumoniae engineered for bioluminescence (lux) was used for direct visualization of disease progression and antibiotic treatment in a mouse model of meningitis. The host response was monitored in transgenic mice containing an inducible firefly luciferase (luc) reporter gene under transcriptional control of the mouse glial fibrillary acidic protein (GFAP) promoter. Based on the different spectra of light emission and substrate requirements for lux and luc, we were able to separately monitor the two reporters using a highly sensitive in vivo imaging system. The level of neuronal damage and recovery following antibiotic treatment was dependent on the time of treatment. This model has potential for simultaneous multiparameter monitoring and testing of therapies that target the pathogen or host response to prevent neuronal injury and recovery.
Learning When Serious: Psychophysiological Evaluation of a Technology-Enhanced Learning Game

We report an evaluation study for a novel learning platform, motivated by the growing need for methods to do assessment of serious game efficacy. The study was a laboratory experiment combining evaluation methods from the fields of learning assessment and psychophysiology. 15 participants used the TARGET game platform for 25 minutes, while the bio-signals electrocardiography, electrodermal activity and facial electromyography were recorded. Learning was scored using pre- and post-test question-based assessments Repeated-measures analysis with Generalised Estimating Equations was used to predict scores by tonic psychophysiological data. Results indicate some learning effect, plus a relationship between mental workload (indexed by electrocardiography) and learning. Notably, the game format itself influences the nature of this relationship. We conclude that a high quality of insight is afforded by the combination of subjective self-report and objective psychophysiology, satisfying two of three observable domains.
Role Assorted Community Discovery for Weighted Networks

This paper considers the difficulties in community discovery, and comes up with a community discovery algorithm on the basis of role assorted thoughts. Previous work indicates that a robust approach to community detection is the maximization of inner communication and the minimization of the in-out interaction. Here we show that this problem can be solved accords to the role assorted method which give distinguish labels to vertices in the same community. This method leads us to a number of possible algorithms for detecting community structures in both unweighted and weighted networks. The applicability and expandability of algorithms proposed are illustrated with application to a variety of computer-generated networks and real-world complex networks.
New low-pass split wavelet pyramids and their application to efficient zerotree coding of medical images

We have developed and tested alternative transforms which create different zerotree structures. These new transforms can significantly improve the performance of image compression algorithms that use zerotrees without a significant modification of the latter. A new wavelet pyramid that results in an effective non-integer up- and down-sampling of the high-frequency sub-bands is presented in this paper. Non-integer sub-sampled pyramids can also be used to reduce the data dependency in the compression algorithm, and therefore reduce the execution time in a processor with multiple parallel processing units.
Targeting the proteasome as a therapeutic strategy against haematological malignancies

The ubiquitin–proteasome pathway is responsible for the vast majority of regulated eukaryotic intracellular proteolysis. Inhibition of the proteasome induces beneficial antitumour effects by blocking cell-cycle progression, inducing apoptosis and suppressing angiogenesis. Bortezomib is the first proteasome inhibitor to reach the clinical arena, where Phase I – III trials verified its activity against relapsed/refractory multiple myeloma. Testing is ongoing to determine bortezomib’s role in front-line therapy of this plasma cell dyscrasia, as well as in non-Hodgkin’s lymphoma, in which encouraging single-agent activity has been seen. Proteasome inhibition is also a rational strategy to overcome chemoresistance and induce chemosensitisation. Combinations of bortezomib and other agents have enhanced efficacy, and additional studies are probing the activity of several regimens in lymphoid and myeloid malignancies. The current state of knowledge about the activity of bortezomib, both alone and in combination with standard chemotherapeutics, as part of the emerging armamentarium against haematological malignancies is reviewed.