Miracle-dz/UniFAR-FTUs huggingface dataset:
The influence of selected variables on the attitudes of Canadian adolescents towards marriage and family life

The purposes were to investigate the attitudes of Canadian adolescents toward marriage and family life and to determine how these are influenced by family structure, perception of family conflict, gender and age and to investigate the influence of family structure on adolescent self-esteem. Seven hundred and ninety-two students ages 13-19 in a Western Canadian high school responded to the questionnaire. Multivariate and Univariate analyses reveal that family structure and perception of family conflict have a greater influence on adolescent attitudes towards marriage and family life than age and gender. Length of time living in a remarried family did not appear to influence adolescent attitudes. The remarried family structure most negatively affected adolescent attitudes. Older males in the remarried family appeared to have higher self-esteem than subjects in other family structures. ii
Corporate Social Performance and Corporate Financial Performance: A Link for the Indian Firms

The present study addresses the issue of the relationship in the midst of Corporate Financial Performance (CFP) and Corporate Social performance (CSP) or Corporate Social Responsibility (CSR) in Indian connection under good management theory. The study utilized S&P ESG India Index as a substitute of CSP/CSR of Indian firms for the first time over the 2005-2011 periods. We outlined econometric models and controlled industry particular traits and performed Weighted Least Square technique for the investigation. General results show unbiased however unobtrusive negative connection between these which in the long run advises that if there would be any relationship, it would be negative.
Randomized controlled clinical trial on the evaluation of bacteriostatic and cariostatic effects of a novel povidone-iodine/fluoride foam in children with high caries risk.

OBJECTIVE To investigate the bacteriostatic and cariostatic effect of a novel povidone-iodine/fluoride foam in children at high risk for caries. METHOD AND MATERIALS Sixty-one 6- to 9-year-old children with at least 1 active dental caries lesion were randomly assigned to 2 groups and treated weekly with either povidone-iodine/fluoride foam (n = 30, experimental group) or placebo fluoride foam (n = 31, control group) for 4 weeks. Stimulated saliva samples were collected for bacteriostatic assessment before each treatment and at 2 and 6 months during the experiment. In addition, laser fluorescence readings of the permanent first molars were taken for the evaluation of cariostatic effect before the treatment and at 2, 6, and 12 months during the experiment. RESULTS Both groups showed a constant decrease of salivary mutans streptococci over 6 months. Significantly lower laser fluorescence readings were observed for both groups at the 6th month, although with a slight reverse at the 12th month. However, no statistically significant difference was achieved between the 2 groups either for salivary bacteria levels over 6 months or laser fluorescence readings within 1 year. CONCLUSION As far as bacteriostatic and cariostatic effects are concerned, clinical application of povidone-iodine/fluoride foam shows no superiority over the regular fluoride foam during a 1-year period. Evidence is still lacking for the combination use of povidone-iodine and fluoride to achieve a better caries-prevention effect in a high-caries-risk population.
Black-Box Marine Vehicle Identification with Regression Techniques for Random Manoeuvres

As a critical step to efficiently design control structures, system identification is concerned with building models of dynamical systems from observed input–output data. In this paper, a number of regression techniques are used for black-box marine system identification of a scale ship. Unlike other works that train the models using specific manoeuvres, in this work the data have been collected from several random manoeuvres and trajectories. Therefore, the aim is to develop general and robust mathematical models using real experimental data from random movements. The techniques used in this work are ridge, kernel ridge and symbolic regression, and the results show that machine learning techniques are robust approaches to model surface marine vehicles, even providing interpretable results in closed form equations using techniques such as symbolic regression.
Industry sponsored anti-smoking ads and adolescent reactance: test of a boomerang effect

Objective: To examine whether adolescents’ exposure to youth smoking prevention ads sponsored by tobacco companies promotes intentions to smoke, curiosity about smoking, and positive attitudes toward the tobacco industry. Design: A randomised controlled experiment compared adolescents’ responses to five smoking prevention ads sponsored by a tobacco company (Philip Morris or Lorillard), or to five smoking prevention ads sponsored by a non-profit organisation (the American Legacy Foundation), or to five ads about preventing drunk driving. Setting: A large public high school in California’s central valley. Subjects: A convenience sample of 9th and 10th graders (n = 832) ages 14–17 years. Main outcome measures: Perceptions of ad effectiveness, intention to smoke, and attitudes toward tobacco companies measured immediately after exposure. Results: As predicted, adolescents rated Philip Morris and Lorillard ads less favourably than the other youth smoking prevention ads. Adolescents’ intention to smoke did not differ as a function of ad exposure. However, exposure to Philip Morris and Lorillard ads engendered more favourable attitudes toward tobacco companies. Conclusions: This study demonstrates that industry sponsored anti-smoking ads do more to promote corporate image than to prevent youth smoking. By cultivating public opinion that is more sympathetic toward tobacco companies, the effect of such advertising is likely to be more harmful than helpful to youth.
Cardiotoxicity, inflammation, and immune response after rattlesnake envenomation in the horse.

BACKGROUND Cardiac abnormalities are reported in rattlesnake-bitten horses. The prevalence and cause are unknown. OBJECTIVES To detect cardiac damage in rattlesnake-bitten horses by measuring cardiac troponin I (cTnI) and evaluating ECG recordings for presence of arrhythmias, and explore causes of this cardiac damage by measuring venom excretion, anti-venom antibodies, and tumor necrosis factor alpha (TNFα). ANIMALS A total of 20 adult horses with a clinical diagnosis of rattlesnake bite and 6 healthy adult horses. METHODS In a prospective clinical study, bite site swabs, blood samples, and urine samples were collected at various time points from 20 horses with a clinical diagnosis of snake bite. Continuous ECG recordings were obtained on the 20 affected horses and 6 normal control horses using 24-hour holter monitors. Plasma samples were assayed for cTnI, serum samples were assayed for TNFα and anti-venom antibodies, and bite site swabs and urine were assayed for venom. RESULTS Forty percent of rattlesnake-bitten horses (8/20) experienced myocardial damage (increased cTnI). Seventy percent (14/20) experienced a cardiac arrhythmia. There was a positive correlation between cTnI and TNFα (P < .02). Horses with cTnI ≥ 2 ng/mL were more likely to have antibody titers >5,000 (P < .05). No correlations were found between venom concentration and cTnI, anti-venom antibody titers, TNFα, or presence of arrhythmias. CONCLUSIONS AND CLINICAL IMPORTANCE Cardiac abnormalities in this population of horses indicate that cardiac damage after rattlesnake bite is common. Rattlesnake-bitten horses should be monitored for signs of cardiac damage and dysfunction. Long-term follow-up should be encouraged to detect delayed cardiac dysfunction.
Thiols in the αIIbβ3 integrin are necessary for platelet aggregation

Sulfhydryl groups of platelet surface proteins are important in platelet aggregation. While p‐chloromercuribenzene sulphonate (pCMBS) has been used in most studies on platelet surface thiols, the specific thiol‐proteins that pCMBS reacts with to inhibit aggregation have not been well defined. Since the thiol‐containing P2Y12 ADP receptor is involved in most types of platelet aggregation, we used the ADP scavenger apyrase and the P2Y12 receptor antagonist 2‐MeSAMP to examine thiol‐dependent reactions in the absence of contributions from this receptor. We provide evidence for a non‐P2Y12 thiol‐dependent reaction near the final αIIbβ3‐dependent events of aggregation. We then used 3‐(N‐maleimidylpropionyl)biocytin (MPB) and pCMBS to study thiols in αIIbβ3. As previously reported, disruption of the receptor was required to obtain labelling of thiols with MPB. Specificity of labelling for thiols in the αIIb and β3 subunits was confirmed by identification of the purified proteins by mass spectrometry and by inhibition of labelling with 5,5′‐dithiobis‐(2‐nitrobenzoic acid). In contrast to MPB, pCMBS preferentially reacted with thiols in αIIbβ3 and blocked aggregation under physiological conditions. Similarly, pCMBS preferentially inhibited signalling‐independent activation of αIIbβ3 by Mn2+. Our results suggest that the thiols in αIIbβ3 that are blocked by pCMBS are important in the activation of this integrin.
Mycobacterium leprae

The effect of multiple intradermal injections (four to six) of 10 pg of interferon y on the number of Mycobacterium leprae in the skin of patients with polar lepromatous leprosy and borderline lepromatous leprosy was evaluated. To achieve a maximum zone of induration and cell emigration a preparatory dose ofthe lymphokine was required. A second group of three injections, given 3-4 days after the initial series, resulted in lesser degrees of induration and was more in keeping with a partial local hyporesponsive state. A marked emigration of T cells and monocytes into the dermis resulted from injections of interferon y and persisted for >21 days. A preponderance of CD4' cells in the infiltrate was seen within a few days and CD4/CD8 ratios remained elevated for >3 weeks. The bacillary load ofinjected sites evaluated 21 days after lymphokine administration was reduced in 14/17 patients by factors ranging from 5- to 1000-fold. This occurred pre-dominantly within diffuse lesions and occurred rarely in nodular sites. Biopsy samples of injected sites taken 6 months later demonstrated progressive 10-fold reductions in bacilli and the continued presence of a granulomatous response.
Proteomic analysis of microvesicles derived from human colorectal cancer ascites

The presence of malignant ascites in the peritoneal cavity is a poor prognostic indicator of low survival rate. Various cancer cells, including those of colorectal cancer (CRC), release microvesicles (exosomes) into surrounding tissues and peripheral circulation including malignant ascites. Although recent progress has revealed that microvesicles play multiple roles in tumor progression, the protein composition and the pathological function of malignant ascites‐derived microvesicles are still unknown. Here, we report the first global proteomic analyses of highly purified microvesicles derived from human CRC ascites. With 1‐D SDS‐PAGE and nano‐LC‐MS/MS analyses, we identified a total of 846 microvesicular proteins from ascites of three CRC patients with high confidence; 384 proteins were identified in at least two patients. We identified proteins that might function in tumor progression via disruption of epithelial polarity, migration, invasion, tumor growth, immune modulation, and angiogenesis. Furthermore, we identified several potential diagnostic markers of CRC including colon‐specific surface antigens. Our proteomic analyses will help to elucidate diverse functions of microvesicles in cancer progression and will aid in the development of novel diagnostic tools for CRC.
Disentangling the emergence of perceived environmental uncertainty among technology entrepreneurs

Purpose – The purpose of this paper is to examine how network externalities impact on perception of environmental uncertainties. Design/methodology/approach – The source of sample comes from the Science & Technology Parks database, a major association of corporate information of new technology ventures in Iran. The sampling frame comprises a wide range of industry segments including electronics, chemicals, agriculture, computer equipment, pharmaceuticals and medicines, telecommunication equipment, and others. The author used the conventional method of back-translation to translate the measures from English to Persian. There were 380 NTVs that the author could reach to send the survey. Among 380 NTVs, 177 entrepreneurs fully completed all the items (46 percent response rate). Findings – The findings showed that what might decrease the state uncertainty perception, at same time it can give arise to other types of uncertainty. Thus, the result confirmed that the three types of uncertainty are differentiable. Research limitations/implications – In the study, the author used cross-sectional self-report data, which cannot suggest causal relationships very well. Practical implications – Investigating factors that influence the perception of environmental uncertainty may help explain why organizations, under the same environment, can behave heterogeneously. Originality/value – By providing a clear picture about the relationship between market with network effect and perception of environmental uncertainty, this study contributes to the theoretical and empirical understanding of the emergence of environmental uncertainty perception.
Dietary therapy is the best option for refractory nonsurgical epilepsy

Ketogenic diet therapies for epilepsy have been described since the fifth century and published in scientific literature since the early 1900s. Since that time, the diet's popularity has waxed and waned as newer drugs and other treatments have been introduced. However, in recent years, dietary therapy for epilepsy has been increasingly accepted by physicians and desired by patients as an alternative to new drugs and neurostimulation. The introduction of less restrictive versions of the classic ketogenic diet, such as the modified Atkins diet (MAD), have led to increased numbers of adult patients with refractory epilepsy who are initiating dietary treatment. Approximately half of adults and children who start a ketogenic diet have a >50% seizure reduction, which is impressive given that these patients typically have medically refractory epilepsy. We believe that ketogenic dietary treatment is the best option for children and adults with refractory nonsurgical epilepsy due to its efficacy, rapid seizure reduction, synergistic effects with other antiseizure treatments, known and treatable side effects, potential to treat comorbid medical conditions, and worldwide availability.
Degradation of proteins during the fermentation of African locust bean (Parkia biglobosa) by strains of Bacillus subtilis and Bacillus pumilus for production of Soumbala.

AIMS To examine isolates of Bacillus subtilis and B. pumilus predominant in Soumbala for their ability to degrade African locust bean proteins (ALBP). METHODS AND RESULTS Agar diffusion test in casein and ALBP agar was used for screening of isolates. The profiles of water-soluble proteins and free amino acids (FAA) during the fermentation of ALBP by the Bacillus isolates were studied by SDS-PAGE and cation exchange chromatography. The profile of soluble proteins changed with the fermentation time and varied depending on the isolate. The quantity of total FAA and essential FAA such as lysine was increased sharply between 24 and 48 h of fermentation and differed among the isolates. Simultaneously, a pH increase was observed. Cysteine, methionine, leucine, isoleucine, tyrosine and phenylalaline appeared during fermentation. CONCLUSION The Bacillus isolates studied degraded ALBP leading to a profile of soluble proteins and FAA specific for each isolate. SIGNIFICANCE AND IMPACT OF THE STUDY This study contributes to the selection of Bacillus strains to be used as starter cultures for controlled production of Soumbala.
Characterization of Fibrinogen Binding by Glycoproteins Srr1 and Srr2 of Streptococcus agalactiae

Background: The serine-rich repeat glycoproteins Srr1 and Srr2 are surface adhesins of Streptococcus agalactiae important for pathogenicity. Results: Both Srrs bind tandem repeats of the fibrinogen Aα chain, but Srr2 has greater affinity explained by structure-function analysis of the Srrs. Conclusion: A dock, lock, and latch mechanism describes the Srr-fibrinogen interaction. Significance: The higher affinity of Srr2 may contribute to the hypervirulence of Srr2-expressing strains. The serine-rich repeat glycoproteins of Gram-positive bacteria comprise a large family of cell wall proteins. Streptococcus agalactiae (group B streptococcus, GBS) expresses either Srr1 or Srr2 on its surface, depending on the strain. Srr1 has recently been shown to bind fibrinogen, and this interaction contributes to the pathogenesis of GBS meningitis. Although strains expressing Srr2 appear to be hypervirulent, no ligand for this adhesin has been described. We now demonstrate that Srr2 also binds human fibrinogen and that this interaction promotes GBS attachment to endothelial cells. Recombinant Srr1 and Srr2 bound fibrinogen in vitro, with affinities of KD = 2.1 × 10−5 and 3.7 × 10−6 m, respectively, as measured by surface plasmon resonance spectroscopy. The binding site for Srr1 and Srr2 was localized to tandem repeats 6–8 of the fibrinogen Aα chain. The structures of both the Srr1 and Srr2 binding regions were determined and, in combination with mutagenesis studies, suggest that both Srr1 and Srr2 interact with a segment of these repeats via a “dock, lock, and latch” mechanism. Moreover, properties of the latch region may account for the increased affinity between Srr2 and fibrinogen. Together, these studies identify how greater affinity of Srr2 for fibrinogen may contribute to the increased virulence associated with Srr2-expressing strains.
Bayesian Classifiers Applied to the Tennessee Eastman Process

Fault diagnosis includes the main task of classification. Bayesian networks (BNs) present several advantages in the classification task, and previous works have suggested their use as classifiers. Because a classifier is often only one part of a larger decision process, this article proposes, for industrial process diagnosis, the use of a Bayesian method called dynamic Markov blanket classifier that has as its main goal the induction of accurate Bayesian classifiers having dependable probability estimates and revealing actual relationships among the most relevant variables. In addition, a new method, named variable ordering multiple offspring sampling capable of inducing a BN to be used as a classifier, is presented. The performance of these methods is assessed on the data of a benchmark problem known as the Tennessee Eastman process. The obtained results are compared with naive Bayes and tree augmented network classifiers, and confirm that both proposed algorithms can provide good classification accuracies as well as knowledge about relevant variables.
Prevalence of Abnormal Glucose Tolerance and Risk Factors in Urban and Rural Malaysia

OBJECTIVE To determine the prevalence of prediabetes and diabetes among rural and urban Malaysians. RESEARCH DESIGN AND METHODS This cross-sectional survey was conducted among 3,879 Malaysian adults (1,335 men and 2,544 women). All subjects underwent the 75-g oral glucose tolerance test (OGTT). RESULTS The overall prevalence of prediabetes was 22.1% (30.2% in men and 69.8% in women). Isolated impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were found in 3.4 and 16.1% of the study population, respectively, whereas 2.6% of the subjects had both IFG and IGT. Based on an OGTT, the prevalence of newly diagnosed type 2 diabetes was 12.6% (31.0% in men and 69.0% in women). The prediabetic subjects also had an increased prevalence of cardiovascular disease risk factors. CONCLUSIONS The large proportion of undiagnosed cases of prediabetes and diabetes reflects the lack of public awareness of the disease.
CERGE-EI Tackles Transition

This volume is a collection of articles reprinted from top refereed journals and contains the most influential scholarly papers published by CERGE-EI faculty over the past 20 years. An introduction is by Lubomir Lizal, Associate Professor with Tenure at CERGE-EI and member of the Board of the Czech National Bank.
Investigation of machine learning based network traffic classification

Timely and accurate traffic classification and application characterization are becoming increasingly important with many applications in wired and wireless networks, e.g., traffic engineering, security monitoring, and quality of service (QoS). In particular, Software Defined Networking (SDN) is a new networking paradigm that has great impact on future IP networks and 5G wireless networks. In SDN networks, application awareness is essential for functionalities such as virtual network resource slicing and fast routing. Compared to traditional classification methods such as port-based and payload-based algorithms, machine learning (ML) approaches offer a better choice in Internet traffic characterization by using payload-independent traffic statistics. In this paper, two ML algorithms, namely supervised Support Vector Machine (SVM) and unsupervised K-means clustering, are studied for traffic classification. It has been found that an overall accuracy of over 95% can be achieved. Meanwhile, the system performance can be further improved with model tuning and feature selection.
A multi-label classification algorithm based on triple class support vector machine

Multi-label classification problem is a special learning task in which its classes are not mutually exclusive and each sample may belong to several classes simultaneously. A novel multi-label classification algorithm based on both one-versus-one decomposition method and triple class support vector machine (SVM) is presented in this paper. One-versus-one decomposition technique is used to pairwise divide a multi-label classification problem into many binary class ones, in which some samples possibly are associated with two labels at the same time. Triple class SVM is a generalization of traditional binary class SVM, where those samples with double labels are considered as a mixed class located between positive and negative classes. Experimental results on benchmark datasets Yeast and Scene demonstrate that our proposed algorithm is comparable with some existed methods, such as rank-SVM, binary-SVM, ML-kNN and etc, according to several evaluation criteria of multi-label learning algorithms.
The Role of State and Local Budget Cuts in the Run-Up of For-Profit Attendance and Student Borrowing: Spillovers between the Public and For-Profit Sectors

Between 2000 and 2010, U.S. public postsecondary schools experienced widespread decreases in appropriations funding. We document that every 10 percent cut in appropriations statewide increased for-profit attendance by 2 percent, owing to students who otherwise would have attended public institutions. We hypothesize that public institutions price adjusted in response to funding cuts which, together with a shift in attendance toward a higher-borrowing sector, induced greater reliance on debt financing among students. We estimate a corresponding increase in annual borrowing of 0.7 percent, driven by for-profit borrowers. Finally, we detect meaningful changes in public universities’ tuition, faculty, and competitive admissions slots.