LLukas22/scidocs huggingface dataset:
RankClus: integrating clustering with ranking for heterogeneous information network analysis

As information networks become ubiquitous, extracting knowledge from information networks has become an important task. Both ranking and clustering can provide overall views on information network data, and each has been a hot topic by itself. However, ranking objects globally without considering which clusters they belong to often leads to dumb results, e.g., ranking database and computer architecture conferences together may not make much sense. Similarly, clustering a huge number of objects (e.g., thousands of authors) in one huge cluster without distinction is dull as well.
 In this paper, we address the problem of generating clusters for a specified type of objects, as well as ranking information for all types of objects based on these clusters in a multi-typed (i.e., heterogeneous) information network. A novel clustering framework called RankClus is proposed that directly generates clusters integrated with ranking. Based on initial K clusters, ranking is applied separately, which serves as a good measure for each cluster. Then, we use a mixture model to decompose each object into a K-dimensional vector, where each dimension is a component coefficient with respect to a cluster, which is measured by rank distribution. Objects then are reassigned to the nearest cluster under the new measure space to improve clustering. As a result, quality of clustering and ranking are mutually enhanced, which means that the clusters are getting more accurate and the ranking is getting more meaningful. Such a progressive refinement process iterates until little change can be made. Our experiment results show that RankClus can generate more accurate clusters and in a more efficient way than the state-of-the-art link-based clustering methods. Moreover, the clustering results with ranks can provide more informative views of data compared with traditional clustering.
Case Based Reasoning and TRIZ : a coupling for Innovative conception in Chemical Engineering

With the evolutions of the surrounding world market, researchers and engineers have to propose technical innovations. Nevertheless, Chemical Engineering community demonstrates a small interest for innovation compared to other engineering fields. In this paper, an approach to accelerate inventive preliminary design for Chemical Engineering is presented. This approach uses case-based reasoning (CBR) method to model, to capture, to store and to make available the knowledge deployed during design. CBR is a very interesting method coming from artificial intelligence, for routine design. Indeed, in CBR the main assumption is that a new problem of design can be solved with the help of past successful ones. Consequently, the problem solving process is based on past successful solutions, therefore, the design is accelerated but creativity is limited and not stimulated. Our approach is an extension of the CBR method from routine design to inventive design. One of the main drawbacks of this method is that it is restricted in one particular domain of application. To propose inventive solution, the level of abstraction for problem resolution must be increased. For this reason CBR is coupled with the TRIZ theory (Russian acronym for Theory of Solving Inventive Problem). TRIZ is a problem solving method that increases the ability to solve creative problems thanks to its capacity to give access to the best practices in all the technical domains. The proposed synergy between CBR and TRIZ combines the main advantages of CBR (ability to store and to reuse rapidly knowledge) and those of TRIZ (no trade-off during resolution, inventive solutions). Based on this synergy, a tool is developed and a mere example is treated.
Prevalence and characteristics of body piercing and tattooing among high school students.

BACKGROUND
Although body piercing and tattooing seem to be gaining popularity among a diversity of social and age groups, studies of these practices in general adolescent populations are scarce. This study establishes the prevalence of body modification (tattooing and body piercing) among high school students in grades 7-11 (aged 12 to 18).


METHODS
Data come from a 2002 in-school survey conducted among a representative sample of 2,180 students (81% response rate) enrolled in the 23 high schools of the Outaouais region in Quebec. Systematic sampling was performed. Specific data on tattooing and body piercing are available for 2,145 students (1% non-response rate).


RESULTS
A prevalence of 27% for body piercing and 8% for tattooing is observed among high school students. Differences between girls and boys are observed in many ways: i.e., frequency and number of tattoos or piercings; aftercare practices. While most teens say that a "professional" in a studio performed their body modification and that they received aftercare instruction, a high percentage of students report health complications following the procedure.


CONCLUSION
Results show that tattooing and body piercing are common among adolescents and may involve health risks. Consequently, appropriate preventive measures should be adopted by professionals such as school counsellors, nurses, physicians and others who are in contact with teenagers to help them make informed choices.
New techniques for geographic routing

As wireless sensor networks continue to grow in size, we are faced with the prospect of emerging wireless networks with hundreds or thousands of nodes. Geographic routing algorithms are a promising alternative to tradition ad hoc routing algorithms in this new domain for point-to-point routing, but deployments of such algorithms are currently uncommon because of some practical difficulties. This dissertation explores techniques that address two major issues in the deployment of geographic routing algorithms: (i) the costs associated with distributed planarization and (ii) the unavailability of location information. We present and evaluate two new algorithms for geographic routing: Greedy Distributed Spanning Tree Routing (GDSTR) and Greedy Embedding Spring Coordinates (GSpring). Unlike previous geographic routing algorithms which require the planarization of the network connectivity graph, GDSTR switches to routing on a spanning tree instead of a planar graph when packets end up at dead ends during greedy forwarding. To choose a direction on the tree that is most likely to make progress towards the destination, each GDSTR node maintains a summary of the area covered by the subtree below each of its tree neighbors using convex hulls. This distributed data structure is called a hull tree. GDSTR not only requires an order of magnitude less bandwidth to maintain these hull trees than CLDP, the only distributed planarization algorithm that is known to work with practical radio networks, it often achieves better routing performance than previous planarization-based geographic routing algorithms. GSpring is a new virtual coordinate assignment algorithm that derives good coordinates for geographic routing when location information is not available. Starting from a set of initial coordinates for a set of elected perimeter nodes, GSpring uses a modified spring relaxation algorithm to incrementally adjust virtual coordinates to increase the convexity of voids in the virtual routing topology. This reduces the probability that packets will end up in dead ends during greedy forwarding, and improves the routing performance of existing geographic routing algorithms. The coordinates derived by GSpring yield comparable routing performance to that for actual physical coordinates and significantly better performance than that for NoGeo, the best existing algorithm for deriving virtual coordinates for geographic routing. Furthermore, GSpring is the first known algorithm that is able to derive coordinates that achieve better geographic routing performance than actual physical coordinates for networks with obstacles. Thesis Supervisor: Barbara Liskov Title: Ford Professor of Engineering
Privacy, Social Network Sites, and Social Relations

With the growth of the Internet comes a growth in a ubiquitous networked society. Common Web 2.0 applications include a rapidly growing trend for social network sites. Social network sites typically converged different relationship types into one group of ‘‘friends.’’ However, with such vast interconnectivity, convergence of relationships, and information sharing by individual users comes an increased risk of privacy violations. We asked a small sample of participants to discuss what friendship and privacy meant to them and to give examples of a privacy violation they had experienced. A thematic analysis was conducted on the interviews to determine the issues discussed by the participants. Many participants experienced privacy issues using the social network site Facebook. The results are presented here and discussed in relation to online privacy concerns, notably social network site privacy concerns and managing such information.
Variation in newborn size according to pregnancy weight change by trimester.

BACKGROUND
The timing of maternal weight change in pregnancy may be an important determinant of the newborn's size.


OBJECTIVE
The purpose was to identify effects of maternal weight change by trimester on newborn size, under the hypothesis that low weight gain early in pregnancy predicts proportionately smaller newborns.


DESIGN
Women planning to become pregnant were followed by clinic visits and questionnaires through delivery. This study includes 389 women and their singleton infants born at a gestational age of > or = 241 d.


RESULTS
In multiple regression analyses including a variety of potential confounders, maternal weight gain in the first and second trimesters predicted newborn weight (1-kg weight gain in the first trimester predicted a 31-g increase in newborn weight, P < 0.0007, and 1-kg weight gain in the second trimester predicted a 26-g increase in newborn weight, P < 0.007), but weight gain in the third trimester did not. Newborn ponderal index (in kg/m(3)) was predicted by weight gain in the first (1-kg weight gain predicted an added 0.21 units, P < 0.0003) and third (1-kg weight gain predicted an added 0.12 units, P < 0.03) trimesters but not in the second trimester. Newborn weight was 211 g lower (P < 0.006) and ponderal index 1.2 units lower (P < 0.02) in infants born to women who lost weight in the first trimester.


CONCLUSIONS
The use of measured prepregnancy weight in tests of the effect on newborn size of weight gain by time in pregnancy produces different results than does the use of recalled prepregnancy weight. Maternal weight change in the first trimester of pregnancy more strongly influences newborn size than does weight change in the second or third trimester.
Using Encryption for Authentication in Large Networks of Computers

Use of encryption to achieve authenticated communication in computer networks is discussed. Example protocols are presented for the establishment of authenticated connections, for the management of authenticated mail, and for signature verification and document integrity guarantee. Both conventional and public-key encryption algorithms are considered as the basis for protocols.
Predicting Mouse Liver Microsomal Stability with “Pruned” Machine Learning Models and Public Data

Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability. Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism). “Pruning” out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h. Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources. Graphical Abstract ᅟ
Randomized controlled trial for an effect of green tea-extract powder supplementation on glucose abnormalities

Objective:We examined whether green tea-extract powder supplementation improves glucose abnormality.Methods:The study was conducted for volunteers who resided in eastern communities of Shizuoka Prefecture and who had fasting blood glucose levels of ⩾6.1 mmol/l or nonfasting blood glucose levels of ⩾7.8 mmol/l in a recent health check-up. Sixty subjects aged 32–73 years (49 males and 11 females) participated in the trial. The Early intervention group consumed a packet of green tea-extract powder containing 544 mg polyphenols (456 mg catechins) daily for the first 2 months and then entered the 2-month nonintervention period. The Later intervention group was observed for the first 2 months and then consumed green tea-extract powder as described above for the subsequent 2 months. Using the two-period crossover design, we analyzed the changes in fasting hemoglobin A1c level and other biomarkers in blood samples collected at baseline, 2 months and 4 months.Results:A significant reduction in hemoglobin A1c level and a borderline significant reduction in diastolic blood pressure were associated with the intervention. The intervention caused no significant changes in weight, body mass index, body fat, systolic blood pressure, fasting serum glucose level, homeostasis model assessment index, serum lipid level or hypersensitive C-reactive protein.Conclusion:Daily supplementary intake of green tea-extract powder lowered the hemoglobin A1c level in individuals with borderline diabetes.
The costs and benefits of the Dark Triad: Implications for mate poaching and mate retention tactics

The Dark Triad – narcissism, Machiavellianism, and psychopathy – have traditionally been considered to be undesirable traits. However, emerging work suggest that not only may there be a positive side to possessing these traits but they may also serve important adaptive functions, even if the strategies associated with them are viewed as socially undesirable. In an online survey (N = 336), we investigated the costs and benefits of the Dark Triad within the domain of mating psychology. The social style and lower order personality traits of the Dark Triad traits facilitated increased mateships in the form of poaching mates from others and being poached oneself to form mateships, pointing to possible benefits of possessing the Dark Triad traits. However, the costside was evidenced with rates of mates abandoning their current relationship for a new one. Mate retention is a problem faced by those with these traits and the tactics used to retain mates were characteristic of the Dark Triad: aggressive and narcisstic. Results are discussed using an adaptionist paradigm. Published by Elsevier Ltd.
Implementation of a telephone-based secondary preventive intervention after acute coronary syndrome (ACS): participation rate, reasons for non-participation and 1-year survival

BACKGROUND
Acute coronary syndrome (ACS) is a major cause of death from a non-communicable disease. Secondary prevention is effective for reducing morbidity and mortality, but evidence-based targets are seldom reached and new interventional methods are needed. The present study is a feasibility study of a telephone-based secondary preventive programme in an unselected ACS cohort.


METHODS
The NAILED (Nurse-based Age-independent Intervention to Limit Evolution of Disease) ACS trial is a prospective randomized controlled trial. All eligible patients admitted for ACS were randomized to usual follow-up by a general practitioner or telephone follow-up by study nurses. The intervention was made by continuous telephone contact, with counseling on healthy living and titration of medicines to reach target values for blood pressure and blood lipids. Exclusion criteria were limited to physical inability to follow the study design or participation in another study.


RESULTS
A total of 907 patients were assessed for inclusion. Of these, 661 (72.9%) were included and randomized, 100 (11%) declined participation, and 146 (16.1%) were excluded. The main reasons for exclusion were participation in another trial, dementia, and advanced disease. "Excluded" and "declining" patients were significantly older with more co-morbidity, decreased functional status, and had more seldom received education above compulsory school level than "included" patients. Non-participants had a higher 1-year mortality than participants.


CONCLUSIONS
Nurse-led telephone-based follow-up after ACS can be applied to a large proportion in an unselected clinical setting. Reasons for non-participation, which were associated with increased mortality, include older age, multiple co-morbidities, decreased functional status and low level of education.


TRIAL REGISTRATION
International Standard Randomized Controlled Trial Number (ISRCTN): ISRCTN96595458 (archived by WebCite at http://www.webcitation.org/6RlyhYTYK). Application date: 10 July 2011.
Robust Forecasting with Exponential and Holt-Winters Smoothing

Robust versions of the exponential and Holt–Winters smoothing method for forecasting are presented. They are suitable for forecasting univariate time series in the presence of outliers. The robust exponential and Holt–Winters smoothing methods are presented as recursive updating schemes that apply the standard technique to pre-cleaned data. Both the update equation and the selection of the smoothing parameters are robustifi ed. A simulation study compares the robust and classical forecasts. The presented method is found to have good forecast performance for time series with and without outliers, as well as for fat-tailed time series and under model misspecifi cation. The method is illustrated using real data incorporating trend and seasonal effects. Copyright © 2009 John Wiley & Sons, Ltd. key words forecasting; Holt–Winters smoothing; robust methods; time series
A pilot study of omalizumab to facilitate rapid oral desensitization in high-risk peanut-allergic patients.

BACKGROUND
Peanut allergy is a major public health problem that affects 1% of the population and has no effective therapy.


OBJECTIVE
To examine the safety and efficacy of oral desensitization in peanut-allergic children in combination with a brief course of anti-IgE mAb (omalizumab [Xolair]).


METHODS
We performed oral peanut desensitization in peanut-allergic children at high risk for developing significant peanut-induced allergic reactions. Omalizumab was administered before and during oral peanut desensitization.


RESULTS
We enrolled 13 children (median age, 10 years), with a median peanut-specific IgE level of 229 kU(A)/L and a median total serum IgE level of 621 kU/L, who failed an initial double-blind placebo-controlled food challenge at peanut flour doses of 100 mg or less. After pretreatment with omalizumab, all 13 subjects tolerated the initial 11 desensitization doses given on the first day, including the maximum dose of 500 mg peanut flour (cumulative dose, 992 mg, equivalent to >2 peanuts), requiring minimal or no rescue therapy. Twelve subjects then reached the maximum maintenance dose of 4000 mg peanut flour per day in a median time of 8 weeks, at which point omalizumab was discontinued. All 12 subjects continued on 4000 mg peanut flour per day and subsequently tolerated a challenge with 8000 mg peanut flour (equivalent to about 20 peanuts), or 160 to 400 times the dose tolerated before desensitization. During the study, 6 of the 13 subjects experienced mild or no allergic reactions, 5 subjects had grade 2 reactions, and 2 subjects had grade 3 reactions, all of which responded rapidly to treatment.


CONCLUSIONS
Among children with high-risk peanut allergy, treatment with omalizumab may facilitate rapid oral desensitization and qualitatively improve the desensitization process.
Supplementation with all three macular carotenoids: response, stability, and safety.

PURPOSE
This study was designed to investigate serum and macular response to, and safety of supplementation with, meso-zeaxanthin (MZ), lutein (L), and zeaxanthin (Z), the carotenoids that constitute macular pigment (MP).


METHODS
Forty-four healthy subjects were recruited into this randomized, placebo-controlled, clinical trial. Subjects consumed one tablet per day containing 10.6 mg MZ, 5.9 mg L, and 1.2 mg Z (intervention, I group) or placebo (P group). The spatial profile of MP optical density (MPOD) was measured with customized heterochromatic flicker photometry (cHFP), and serum concentrations of L and Z were quantified by using high performance liquid chromatography (HPLC). Subjects were assessed at baseline and at 3 and 6 months. Clinical pathology analysis was performed at baseline and 6 months.


RESULTS
Serum concentrations of L and Z increased significantly in the I group (P = 0.001 and 0.003, respectively) and remained stable in the P group (P > 0.05). There was a significant increase in central MPOD in the I group (0.25°: P = 0.001; 0.5°: P = 0.001), with no significant change in the P group (P > 0.05). Clinical pathology analysis confirmed that all variables remained within the normal reference range, with the exception of total cholesterol and low-density lipoprotein (LDL), which exhibited baseline values outside the accepted normal reference range before supplementation.


CONCLUSIONS
Subjects supplemented with MZ, L, and Z exhibited significant increases in serum concentrations of these carotenoids and a subsequent increase in central MPOD. Pathology analysis suggested no adverse clinical implications of consuming these carotenoids. (http://isrctn.org number, ISRCTN60816411).
Local Rules for Global MAP: When Do They Work ?

We consider the question of computing Maximum A Posteriori (MAP) assignment in an arbitrary pair-wise Markov Random Field (MRF). We present a randomized iterative algorithm based on simple local updates. The algorithm, starting with an arbitrary initial assignment, updates it in each iteration by first, picking a random node, then selecting an (appropriately chosen) random local neighborhood and optimizing over this local neighborhood. Somewhat surprisingly, we show that this algorithm finds a near optimal assignment within n log n iterations with high probability for any n node pair-wise MRF with geometry (i.e. MRF graph with polynomial growth) with the approximation error depending on (in a reasonable manner) the geometric growth rate of the graph and the average radius of the local neighborhood – this allows for a graceful tradeoff between the complexity of the algorithm and the approximation error. Through extensive simulations, we show that our algorithm finds extremely good approximate solutions for various kinds of MRFs with geometry.