Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Comparative Study of Aquacel and Paraffin Gauze Dressing for Split-Skin Donor Site Treatment

The management of split-thickness skin graft donor sites is targeted towards promoting the healing process, while minimizing adverse effects and complications. The aim of this study was to compare donor site treatment outcome between Aquacel, a carboxymethylcellulose-based hydrofiber dressing, and the standard mesh paraffin gauze dressing. The study included 23 adult patients. Half of the skin graft donor site in the proximal thigh was dressed with paraffin gauze and the rest with Aquacel. The results indicated that patients treated with Aquacel experienced significantly less pain and a more rapid rate of epithelialization compared with patients treated with mesh paraffin gauze dressing. Final scarring (ie, after the 1-year follow-up) was significantly better with the Aquacel dressing. We conclude that Aquacel dressing is superior to the standard mesh paraffin gauze dressing for split-thickness donor site area in pain relief, ease of treatment, promotion of epithelialization, and the quality of scarring.
Evolution of plasmonic response in growing silver thin films with pre-percolation non-local conduction and emittance drop

The optical response of growing silver thin films undergoes a transition dominated by three distinct plasmonic modes, two localized and one delocalized. Their admix as a function of added mass is analysed. The onset of the delocalized or Drude mode occurs before the sharp electrical percolation transition so optically the full insulator–metal transition is broadened. A scaling explanation supported by images shows Ag islands only have to link up over 200–300 nm to yield partial delocalization. The localized modes are (i) from silver nano-islands and (ii) a transitional anomalous mode, peaking near the dc critical percolation point, from islands surrounded by network. Growing silver within a multilayer oxide stack is compared with that on glass. The transition in thermal emittance matches that in the delocalized mode. Its broadening enables practical tuning of intermediate emittance by varying mass.
High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using Health Care Claims Data

Background: Adjusting for large numbers of covariates ascertained from patients’ health care claims data may improve control of confounding, as these variables may collectively be proxies for unobserved factors. Here, we develop and test an algorithm that empirically identifies candidate covariates, prioritizes covariates, and integrates them into a propensity-score-based confounder adjustment model. Methods: We developed a multistep algorithm to implement high-dimensional proxy adjustment in claims data. Steps include (1) identifying data dimensions, eg, diagnoses, procedures, and medications; (2) empirically identifying candidate covariates; (3) assessing recurrence of codes; (4) prioritizing covariates; (5) selecting covariates for adjustment; (6) estimating the exposure propensity score; and (7) estimating an outcome model. This algorithm was tested in Medicare claims data, including a study on the effect of Cox-2 inhibitors on reduced gastric toxicity compared with nonselective nonsteroidal anti-inflammatory drugs (NSAIDs). Results: In a population of 49,653 new users of Cox-2 inhibitors or nonselective NSAIDs, a crude relative risk (RR) for upper GI toxicity (RR = 1.09 [95% confidence interval = 0.91–1.30]) was initially observed. Adjusting for 15 predefined covariates resulted in a possible gastroprotective effect (0.94 [0.78–1.12]). A gastroprotective effect became stronger when adjusting for an additional 500 algorithm-derived covariates (0.88 [0.73–1.06]). Results of a study on the effect of statin on reduced mortality were similar. Using the algorithm adjustment confirmed a null finding between influenza vaccination and hip fracture (1.02 [0.85–1.21]). Conclusions: In typical pharmacoepidemiologic studies, the proposed high-dimensional propensity score resulted in improved effect estimates compared with adjustment limited to predefined covariates, when benchmarked against results expected from randomized trials.
Revenue sharing on hierarchies [ incomplete version , 2018 / April 20 ]

We consider a model of joint venture where agents are organized on a hierarchical network and each agent produces her revenue through collaborating with her superiors. We study the problem of allocating the total revenue among these agents. A hierarchy is represented by a directed tree. We investigate allocation rules that are robust to reallocation of revenues within any coalition that includes all the superiors of its members. We obtain characterizations of such rules imposing standard axioms in the literature of fair allocation theory.
Joint Causal Inference from Multiple Datasets

The gold standard for discovering causal relations is by means of experimentation. Over the last decades, alternative methods have been proposed that can infer causal relations between variables from certain statistical patterns in purely observational data. We introduce Joint Causal Inference (JCI), a novel approach to causal discovery from multiple data sets that elegantly unifies both approaches. JCI is a causal modeling approach rather than a specific algorithm, and it can be used in combination with any causal discovery algorithm that can take into account certain background knowledge. The main idea is to reduce causal discovery from multiple datasets originating from different contexts (e.g., different experimental conditions) to causal discovery from a single pooled dataset by adding a set of auxiliary context variables. JCI offers the following features: it deals with several different types of interventions in a unified fashion, it can learn intervention targets, it pools data across different datasets which improves the statistical power of independence tests, and by exploiting differences in distribution between contexts it improves on the accuracy and identifiability of the predicted causal relations. We evaluate the approach on flow cytometry data.
Semantics-aware Recommender Systems Exploiting Linked Open Data and Graph-based Features

In this contribution we propose a hybrid recommendation framework based on classification algorithms such as Random Forests and Naive Bayes, which are fed with several heterogeneous groups of features. We split our features into two classes: classic features, as popularity-based, collaborative and content-based ones, and extended features gathered from the Linked Open Data (LOD) cloud, as basic ones (i.e. genre of a movie or the writer of a book) and graph-based features calculated on the ground of the different topological characteristics of the tripartite representation connecting users, items and properties in the LOD cloud. In the experimental session we evaluate the effectiveness of our framework on varying of different groups of features, and results show that both LOD-based and graph-based features positively affect the overall performance of the algorithm, especially in highly sparse recommendation scenarios. Our approach also outperforms several state-of-the-art recommendation techniques, thus confirming the insights behind this research. This extended abstract summarizes the content of the journal paper published on Knowledge-based Systems.
The Frequency of A1298C and C677T Polymorphisms of the Methylentetrahydrofolate Gene in Turkish Patients with Rheumatoid Arthritis: Relationship with Methotrexate Toxicity

The C677T and A1298C polymorphisms of methylenetatrahydrofolate reductase (MTHFR) gene are reported to have a relationship to methotrexate (MTX) metabolism, with conflicting results. The aim of this study was to determine the frequency of MTHFR C677 T and A1298C gene polymorphisms in a group of Turkish RA patients and evaluate its association with MTX toxicity. Sixty-four patients with RA and 31 control subjects with a mean age of 48.7 ±12.5 and 46.2 ± 13.4 years, were enrolled to the study. Demographic characteristics were obtained and MTX-related adverse effects were recorded in the patient group. The A1298C and C677T polymorphisms of the MTHFR gene were analyzed and the distribution of genotypes according side effects, were determined. The frequency of MTHFR C677T and A1298C polymorphisms were similar in the patient and control groups. Folic acid supplementation with a mean dose of 5mg folic acid/week, was present in all patients. Thirty-six of the 64 patients showed adverse effects to MTX treatment, and MTX had been discontinued in 12 (18.8%) patients due to side effects and/or inefficacy. MTHFR C677T and A1298C gene polymorphisms were found to be similar in patients with and without MTX-related adverse events. In conclusion, A1298C and C677T polymorphisms in the MTHFR gene, were not related with MTX-related toxicity in RA patients receiving folate supplementation. Further studies are needed to illuminate the polymorphisms in other enzymes that might be responsible from the MTX toxicity in patients suffering from RA.
Construction and Validation of Swimming Constraint Factors of the Disabled in Swimming Pools of Public Universities

This study aims to explore swimming of the disabled in swimming pools of public universities. By open-ended questionnaires, it collects swimming constraint factors of the disabled in swimming pools of public universities. Upon data obtained, according to experts’ and scholars’ opinions and related literature review, this study designs questionnaire on constraint factors of the disabled to swim in swimming pools of public universities and by Confirmatory Factor Analysis, it tests reliability and validity of scale. Research subjects are the disabled in northern, central and southern Taiwan. Through purposive sampling, it distributes 450 questionnaires and return rate is 100%; after deleting invalid questionnaires, this study obtains 400 valid ones. Valid questionnaire rate is 88.8%. According to research findings, the scale of the swimming constraint factors of the disabled in swimming pools of public universities includes “self-ability factor”, “personal internal factor”, “facility and environment quality factor”, “information factor”, “time pressure factor”, “professional factor” and “transportation factor” and 26 items. Scale developed by this study shows positive reliability and validity and it can be applied to evaluate constraint factors of the disabled to swim in swimming pools of public universities.
Real-world treatment and outcomes among older adults with chronic lymphocytic leukemia before the novel agents era

Chronic lymphocytic leukemia (CLL) is the most common leukemia among adults in Western countries, with a median age at diagnosis of 70 years. [1][1] Until 2014, chemoimmunotherapy combinations were the mainstay treatment, particularly for physically fit patients. [2][2],[3][3] However, older
Rational design of helical architectures

Nature has mastered the art of creating complex structures through self-assembly of simpler building blocks. Adapting such a bottom-up view provides a potential route to the fabrication of novel materials. However, this approach suffers from the lack of a sufficiently detailed understanding of the noncovalent forces that hold the self-assembled structures together. Here we demonstrate that nature can indeed guide us, as we explore routes to helicity with achiral building blocks driven by the interplay between two competing length scales for the interactions, as in DNA. By characterizing global minima for clusters, we illustrate several realizations of helical architecture, the simplest one involving ellipsoids of revolution as building blocks. In particular, we show that axially symmetric soft discoids can self-assemble into helical columnar arrangements. Understanding the molecular origin of such spatial organisation has important implications for the rational design of materials with useful optoelectronic applications.
Environmental equity is child's play: mapping public provision of recreation opportunities in urban neighbourhoods

Abstract This paper examines the spatial distribution of recreational opportunities for children and youth in a mid-sized Canadian city (London, Ontario), in relation to the socioeconomic status of neighbourhoods and estimated local need for publicly provided recreation spaces. Public recreation facilities (N = 537) throughout the city were identified, mapped and analysed in a geographic information system. To explore potential socio-environmental inequities, neighbourhoods (N = 22) were characterized by socioeconomic and environmental variables, an index of neighbourhood social distress, a neighbourhood play space needs index, and measures of the prevalence and density of recreational opportunities. The results of the spatial analysis indicate there is no systematic socioenvironmental inequity with respect to the prevalence and density of publicly provided neighbourhood recreation spaces; however, there are several areas in the city where youth do not have access to formal play spaces. We argue that to promote physical activity among urban children and youth, city planners and health policy analysts should consider carefully the geographical distribution of existing recreational opportunities and ensure that new publicly funded recreation spaces are provided to neighbourhoods with the greatest need. Further research should seek to identify what kinds of recreation spaces are most effective for promoting healthy behaviours among vulnerable children and youth.
Surface enhanced Raman spectroscopy distinguishes amyloid Β‐protein isoforms and conformational states

Amyloid β‐protein (Aβ) self‐association is one process linked to the development of Alzheimer's disease (AD). Aβ peptides, including its most abundant forms, Aβ40 and Aβ42, are associated with the two predominant neuropathologic findings in AD, vascular and parenchymal amyloidosis, respectively. Efforts to develop therapies for AD often have focused on understanding and controlling the assembly of these two peptides. An obligate step in these efforts is the monitoring of assembly state. We show here that surface‐enhanced Raman spectroscopy (SERS) coupled with principal component analysis (PCA) readily distinguishes Aβ40 and Aβ42. We show further, through comparison of assembly dependent changes in secondary structure and morphology, that the SERS/PCA approach unambiguously differentiates closely related assembly stages not readily differentiable by circular dichroism spectroscopy, electron microscopy, or other techniques. The high discriminating power of SERS/PCA is based on the rich structural information present in its spectra, which comprises not only on interatomic resonances between covalently associated atoms and hydrogen bond interactions important in controlling secondary structure, but effects of protein orientation relative to the substrate surface. Coupled with the label‐free, single molecule sensitivity of SERS, the approach should prove useful for determining structure activity relationships, suggesting target sites for drug development, and for testing the effects of such drugs on the assembly process. The approach also could be of value in other systems in which assembly dependent changes in protein structure correlate with the formation of toxic peptide assemblies.
Sexual side effects of psychiatric medications in women.

Sexual side dficts ofpsychiatric medications have been estimated to occur in 60% ofmale clients (1) and 30%offemale clients (2). Despite a bodyofliterature relating individual medications to specific sexual side dficts, fe to studies have satisfactorily addressed the psychotropic-induced sexual dysfunctions in women. The spectrum ofknoton sexual sidedficts resultingfrompsychopharmacologic interventions will be reviewed. GuidelinesJOr appropriately addressing the possibility qf sexual side effects within a therapeutic relationship.for maximizing reporting ofsexual side dficts, andfor possible treatment approaches to sexual sidedficts will be described.
Inner amenability and approximation properties of locally compact quantum groups

We introduce an appropriate notion of inner amenability for locally compact quantum groups, study its basic properties, related notions, and examples arising from the bicrossed product construction. We relate these notions to homological properties of the dual quantum group, which allow us to generalize a well-known result of Lau--Paterson, resolve a recent conjecture of Ng--Viselter, and prove that, for inner amenable quantum groups $\mathbb{G}$, approximation properties of the dual operator algebras can be averaged to approximation properties $\mathbb{G}$. Similar homological techniques are used to prove that $\ell^1(\mathbb{G})$ is not relatively operator biflat for any non-Kac discrete quantum group $\mathbb{G}$; a discrete Kac algebra $\mathbb{G}$ with Kirchberg's factorization property is weakly amenable if and only if $L^1_{cb}(\widehat{\mathbb{G}})$ is operator amenable, and amenability of a locally compact quantum group $\mathbb{G}$ implies $C_u(\widehat{\mathbb{G}})=L^1(\widehat{\mathbb{G}})\widehat{\otimes}_{L^1(\widehat{\mathbb{G}})}C_0(\widehat{\mathbb{G}})$ completely isometrically. The latter result allows us to partially answer a conjecture of Voiculescu when $\mathbb{G}$ has the approximation property.
Monitoring the pollution level in istanbul coast of the Sea of Marmara using algal species Ulva lactuca L

Heavy metal pollution in coastal regions has become a serious problem due to significant environmental degradations. In the present study, an algal species, U. lactuca, was investigated to assess the impact of heavy metal pollution on the six different locations along the coastal line of the Sea of Marmara in Istanbul. Heavy metal and mineral nutrient elements such as Ca, Cd, Cu, Fe, K, Mg, Mn, Pb, and Zn were determined using ICP-OES. The following lowest and highest concentrations (mg/kg; dw) were measured in Ulva samples: 1,751.66-2,465.68 for Ca, 0.45-3.22 for Cd, 6.67-18.32 for Cu, 553.32-989.33 for Fe, 3,264.48-4,301.68 for K, 961.50-1,614.53 for Mg, 8.27-25.32 for Mn, 4.93-19.32 for Pb, and 15.16-41.30 for Zn. The data revealed that U. lactuca is capable of accumulating considerable amounts of metals. Besides, metal deposition in the plant did not alter the mineral nutrient uptake pattern extensively, indicating relatively less contamination risk in the area. Overall, the comparison of heavy metal contents with seawater and sediment samples in the Ulva species showed that U. lactuca is a suitable plant for biomonitoring
Relationship between Salmonella infection, shedding and serology in fattening pigs in low–moderate prevalence areas

Salmonella is a major foodborne pathogen causing important zoonosis worldwide. Pigs asymptomatically infected in mesenteric lymph nodes (MLN) can be intermittent shedders of the pathogen through faeces, being considered a major source of human infections. European baseline studies of fattening pig salmonellosis are based on Salmonella detection in MLN. This work studies the relationship between Salmonella infection in MLN and intestinal content (IC) shedding at slaughter and the relationship between the presence of the pathogen and the serologic status at farm level. Mean Salmonella prevalence in the selected pigs (vertically integrated production system of Navarra, Spain) was 7.2% in MLN, 8.4% in IC and 9.6% in serum samples. In this low–moderate prevalence context, poor concordance was found between MLN infection and shedding at slaughter and between bacteriology and serology. In fact, most of shedders were found uninfected in MLN (83%) or carrying different Salmonella strains in MLN and in IC (90%). The most prevalent Salmonellae were Typhimurium resistant to ACSSuT ± Nx or ASSuT antibiotic families, more frequently found invading the MLN (70%) than in IC (33.9%). Multivariable analysis revealed that risk factors associated with the presence of Salmonella in MLN or in IC were different, mainly related either to good hygiene practices or to water and feed control, respectively. Overall, in this prevalence context, detection of Salmonella in MLN is an unreliable predictor of faecal shedding at abattoir, indicating that subclinical infections in fattening pigs MLN could have limited relevance in the IC shedding.
Toward a structure- and process-integrated view of personality: traits as density distribution of states.

Three experience-sampling studies explored the distributions of Big-Five-relevant states (behavior) across 2 to 3 weeks of everyday life. Within-person variability was high, such that the typical individual regularly and routinely manifested nearly all levels of all traits in his or her everyday behavior. Second, individual differences in central tendencies of behavioral distributions were almost perfectly stable. Third, amount of behavioral variability (and skew and kurtosis) were revealed as stable individual differences. Finally, amount of within-person variability in extraversion was shown to reflect individual differences in reactivity to extraversion-relevant situational cues. Thus, decontextualized and noncontingent Big-Five content is highly useful for descriptions of individuals' density distributions as wholes. Simultaneously, contextualized and contingent personality units (e.g., conditional traits, goals) are needed for describing the considerable within-person variation.
Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers. Keywords—Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.
Genome-wide Association Study of Exercise Behavior in Dutch

Introduction—The objective of this study was to identify genetic variants that are associated with adult leisure-time exercise behavior using genome-wide association in two independent samples. Methods—Exercise behavior was measured in 1,772 unrelated Dutch and 978 unrelated American adults with detailed questions about type, frequency and duration of exercise. Individuals were classified into regular exercisers or non-exercisers using a threshold of 4 METhours (metabolic equivalents*hours per week). Regular exercisers were further divided into 5 categories of METhours, ranging from moderate (>=4 METhours) to highly vigorous (>=40 METhours) exercisers. Genome-wide association analyses with a total of 470,719 SNPs were conducted in both samples independently using regression-based techniques in SNPtest, including sex, age and BMI as covariates. Results—SNPs located in SGIP1, DNASE2B, PRSS16, ERCC2 and PAPSS2 were associated with exercise participation (combined p-value between 0.0004 and 4.5*10 -6 with the same