Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding information sharing about rare diseases: an evaluation of the NIH's website on AATD

ABSTRACT Introduction: People with rare diseases have difficulty accessing high quality information about their conditions, which impedes their ability to be engaged patients. Federal agencies such as the National Institutes of Health (NIH) have created websites to disseminate disease-related information. This study explored how people with a rare disease – Alpha-1 Antitrypsin Deficiency (AATD) – evaluated the NIH's website on AATD and how participants’ evaluation, genetic determinism, and spirituality predicted their intentions to share the website with others. Method: Participants (N = 153) living with AATD made comments about the NIH's website on the disease, and completed a survey about their perceptions of the information, individual characteristics, and intentions to share the NIH website. Results: Qualitative analyses highlighted that participants wanted to access to more complete, high quality, and interesting information on AATD on a more user-friendly website. Quantitative analyses showed that participants were more likely to share the website if they judged the information as higher quality and more interesting, with a range of such responses appearing in relation to the same website, making it evident that the meaning of quality and interest varies. Participants with severe deficiency perceived the information as lower quality and less interesting than participants with mild deficiency. Participants with stronger genetic determinism beliefs and spirituality were more likely to share the NIH's website. Conclusions: We discuss how federal agencies can craft messages that assist people with rare diseases in learning more about their conditions and dealing with the burden of sharing high quality information with providers and the public.
Comparison of Chemical Shift MR Imaging Findings between Vertebral Benign and Metastatic Lesions

Objectives: To establish a cut-oﬀ value for signal intensity ratio (SIR) in dual-phase chemical shift MRI and also to evaluate the sensitivity and speciﬁcity of this method in order to diﬀerentiate benign from malignant focal vertebral lesions. Methods: Totally 51 patients (28 men and 23 women) with a mean ( ± SD) age of 52.61 ± 13.52 years (range, 27 - 81 years) with 116 ver-tebralfocallesionswerestudied. MRimaginingwasperformedusinga1.5-Teslasuperconductingsystem. Chemicalshiftsequences forsagittalin-phase(IP)wereobtainedatRT/ET100-165/4.2andout-phase(OP)100-165/2.4. Allimagesweresenttoapicturearchiv-ing and communication system (PACS) work station and areas with abnormal SI on the T1 and T2 sequences were identiﬁed on the IP/OP. An elliptical cursor to deﬁne region of interest was used to describe the area with abnormality on the IP and OP images. We calculated the signal intensity ratio or SIR (SI of OP/SI of IP) to compare the OP with the IP images. Air was selected as the reference contrast as not inﬂuenced by fatty inﬁltration. Results: SIR of 0.73 (OP images compared with IP images) can be used as the best cut-oﬀ value to identify benign (SIR < 0.73) vs. malignant (SIR ≥ 0.73) lesions with 100% sensitivity and 89.7% speciﬁcity. Conclusions: SIRvaluesfromout-phaseandin-phaseimages(chemicalshiftMRimaging)maybeusefulforquantitativelydiﬀeren-tiatingbenignfrommalignantfocalvertebrallesionswithhighspeciﬁcityandsensitivity. SIRvaluesinneoplasticfocallesionswere greater than benign lesion and a value of 0.73 can be used as a cut oﬀ to diﬀerentiate between benign and malignant focal lesions.
Effect of aerobic exercise and low-carbohydrate high-fat diet on glucose tolerance and android/gynoid fat in overweight/obese women: A randomized controlled trial

The study was designed to compare the effects of weight loss induced by a low-carbohydrate-high-fat diet or a normal diet, with and without exercise, on glucose tolerance measured as area under the curve (AUC), and android (A) and gynoid (G) fat distribution. The study was registered at clinicaltrials.gov; NCT04100356. In total, 57 women classified as overweight or obese (age 40 ± 3.5 years, body mass index 31.1 ± 2.6 kg/m2) were randomly assigned and completed a 10-week intervention using a low-carbohydrate high-fat diet or a normal diet, with or without aerobic interval exercise. An equal deficit of 700 kcal/day was prescribed, either restricting the diet only, or moderately restricting diet and including three 50-min high-intensity bicycle sessions per week. There were thus four groups: normal diet (NORM); low-carbohydrate-high-fat diet (LCHF); normal diet with exercise (NORM-EX); and low-carbohydrate-high-fat diet with exercise (LCHF-EX). Linear mixed models was used to assess differences between groups. With all groups pooled, the intervention resulted in a weight loss of 6.7 ± 2.5% (p < 0.001). The intervention did not result in differences between groups in AUC glucose, nor in fasting glucose or indicis for insulin resistance such as Homeostatic Model Assessment, Matsuda Insulin Sensitivity Index, insulinogenic index and disposition index. Post-intervention android fat was lower in LCHF than NORM (3,223 ± 727 vs. 2,533 ± 535 g, p = 0.041). LCHF reached a lower A/G ratio than NORM (0.94 ± 0.12 vs. 1.04 ± 0.09, p = 0.011) and LCHF-EX (0.94 ± 0.12 vs. 1.09 ± 0.09, p < 0.001) after the intervention. LCHF resulted in lower android fat mass compared to NORM and the lowest A/G ratio compared to the other matched groups, but with no accompanying improvement in AUC glucose. In conclusion, although all groups achieved improvements in glucose tolerance, no superior effect was observed with the LCHF diet, neither with nor without exercise.
Brief communication (Original). Trends in neonatal sepsis in a neonatal intensive care unit in Thailand before and after construction of a new facility

Abstract Background: Neonatal sepsis is a cause of mortality and long-term morbidity worldwide. Objectives: To describe longitudinal trends in the cumulative incidence of early- and late-onset sepsis (EOS and LOS), mortality, and causative organisms in a Thai Hospital before and after construction of a new neonatal intensive care unit (NICU). Methods: Review of NICU admissions with blood cultures positive for bacteria or fungi for the periods 1995 to 2002 (preconstruction) and 2004 to 2010 (postconstruction). Sepsis was categorized into EOS (within first 3 days of life) and LOS (after first 3 days of life). Results: Of 5,570 admissions, 241 (4.3%) neonates with 276 episodes of sepsis were identified. There was no difference in the rate of sepsis overall (P = 0.90), LOS (P = 0.30), or sepsis-related mortality (P = 0.61) over the two periods, but the rate of EOS increased significantly from 0.34% to 0.81% (P = 0.04). Rates of Klebsiella species and Escherichia coli sepsis increased from 13.6% to 25.6% (P = 0.01) and from 5.3% to 12.2% (P = 0.04), respectively, while rates of Staphylococcus aureus sepsis decreased from 12.9% to 4.3% (P < 0.007). Sepsisrelated mortality was 1.8%. Conclusions: Although direct causality cannot be proven, the rate of EOS and the pattern of causative organisms changed following construction of the new NICU. Building a new unit does not necessarily result in a reduction in the rate of sepsis. This data may provide a baseline for implementing evidence-based infection control strategies to prevent/reduce sepsis and improve neonatal care.
Aspect-based Sentiment Analysis for Social Recommender System

Social recommender systems harness knowledge from social content, experiences and interactions to provide recommendations to users. The retrieval and ranking of products, using similarity knowledge, is central to the recommendation architecture. To enhance recommendation performance, having an effective representation of products is essential. Social content such as product reviews contain experiential knowledge in the form of user opinions centred on product aspects. Making sense of these for recommender systems requires the capability to reason with text. However, Natural Language Processing (NLP) toolkits trained on formal text documents encounter challenges when analysing product reviews, due to their informal nature. This calls for novel methods and algorithms to capitalise on textual content in product reviews together with other knowledge resources. In this thesis, methods to utilise user purchase preference knowledge - inferred from the viewed and purchased product behaviour - are proposed to overcome the challenges encountered in analysing textual content. This thesis introduces three major methods to improve the performance of social recommender systems. First, an effective aspect extraction method that combines strengths of both dependency relations and frequent noun analysis is proposed. Thereafter, this thesis presents how extracted aspects can be used to structure opinionated content enabling sentiment knowledge to enrich product representations. Second, a novel method to integrate aspect-level sentiment analysis and implicit knowledge extracted from users' product purchase preferences analysis is presented. The role of sentiment distribution and threshold analysis on the proposed integration method is also explored. Third, this thesis explores the utility of feature selection techniques to rank and select relevant aspects for product representation. For this purpose, this thesis presents how established dimensionality reduction approaches from text classification can be employed to select a subset of aspects for recommendation purposes. Finally, a comprehensive evaluation of all the proposed methods in this thesis is presented using a computational measure of 'better' and Mean Average Precision (MAP) with seven real-world datasets.
A survey of oral hygiene practices amongst dental students

Introduction: Oral hygiene measures are put into practice in order to maintain an oral environment free of germs and diseases. Oral diseases have a high prevalence and they pose a great threat to an individual’s quality of life. Oral self-practices of dental students allow them to become a role model to others, thus propagating the importance of oral hygiene. Aim was to investigate the awareness of oral hygiene habits and practices amongst the dental students. Material and Methods: All undergraduate students enrolled at the dental section of Islamabad medical and dental college were given a self- administered structured, anonymous questionnaire after taking verbal consent. The answers of the filled questionnaires were entered and analyzed through SPSS version 22. Results: Out of a total of 196 dental students included in the study many were not practicing the oral hygiene etiquette properly. No noteworthy differences were found when comparing the results for students in the pre-clinical and clinical years. Conclusions: Dental students of this study expressed lack of oral self-hygiene practices with increasing year of their education. Students should be encouraged to include oral self-care practices in their daily lives, to promulgate the importance of a disease free mouth and to become role models for the patients and society.
Risk factors for the diabetic foot infection with multidrug-resistant microorganisms in South India

India has the second largest number of patients living with diabetes world wide, with as many as 82 million adults suffering from this disease and its complications. Development of foot ulcers is seen in 15% of all diabetic patients during their lifetime. This is associated with a significant economic burden. The health expenditure is 5 times more in diabetics with foot ulcers than in those without foot ulcers. Infection of foot ulcers is often due to more than one organism and it is, therefore, imperative that appropriate antibiotic therapy is instituted. Infection with multidrug resistance organisms will increase the morbidity and consequently, the finances involved, to a significant extent. Emergence of multi-drug resistance organisms (MDRO) is the area of major concern in both developing and developed countries. In India, a lack of adherence to protocol in prescribing antibiotics leads to the emergence of these super bugs. Also patient related factors also play ABSTRACT
Frecuencia de neoplasias de piel en caninos remitidos a un laboratorio de patología veterinaria de Bogotá : Estudio retrospectivo en el periodo 2015-2016

Neoplasms are one of the main pathologies associated with the integumentary system. This study included a total of 2008 cases, 458 corresponded to cutaneous neoplasms diagnosed in canines of different ages, sex and breed presented at different locations in the city of Bogota in the period between January 2015 and March 2016. Neoplasms of mesenchymal origin were the most frequent with (51.5%), followed by epithelial origin (41.3%) and finally Vascular origin (7.2%). According to the biological behavior benign neoplasms were more frequent (57%), followed by malignant (43%). The most common neoplasms were low-grade malignancy mastocytoma (13,5%), histiocytoma (10.9%), lymphangioma (9%) and lipoma( 7.6%). The most predisposed breeds to to suffer cutaneous neoplasms were mixed breeds (11.3%), retriever (10.9%), Golden retriever (10.9%) and Schnauzer (10.4%) without association between the type of breed and type of neoplasms. Animals older than 8 years had a percentage of presentation of neoplasms (60.5%) finding statistically significant association (p<0.001) between age and the type of neoplasm , with an average of presentation of 7 years, this being the age of increased risk of skin neoplasms presentation.Males are more affected, with a percentage of (58.5%), pedigreed canines showed more skin neoplasms with a score of (87.1%), followed by mixed breeds (11.1%), no statistical association was found between pedigree and type of neoplasm
Dynamic Programming and Optimal Control 3rd Edition, Volume II

This is an updated version of the research-oriented Chapter 6 on Approximate Dynamic Programming. It will be periodically updated as new research becomes available, and will replace the current Chapter 6 in the book’s next printing. In addition to editorial revisions, rearrangements, and new exercises, the chapter includes an account of new research, which is collected mostly in Sections 6.3 and 6.8. Furthermore, a lot of new material has been added, such as an account of post-decision state simplifications (Section 6.1), regression-based TD methods (Section 6.3), feature scaling (Section 6.3), policy oscillations (Section 6.3), λ-policy iteration and exploration enhanced TD methods, aggregation methods (Section 6.4), new Q-learning algorithms (Section 6.5), and Monte Carlo linear algebra (Section 6.8). This chapter represents “work in progress. ” It more than likely contains errors (hopefully not serious ones). Furthermore, its references to the literature are incomplete. Your comments and suggestions to the author at dimitrib@mit.edu are welcome. The date of last revision is given below.
Burnout among Saudi board residents: comparison between Family Medicine and Internal Medicine

Background: Many previous studies reported high burnout rates among medical professionals in different fields, from students and nurses to surgeons, specialists and consultants. The current study was performed to compare the prevalence of burnout in family medicine and internal medicine residents and to reveal the risk predictors of high burnout. Methodology: It is a cross sectional, analytical study. 130 family and internal medicine residents were given Maslach Burnout Inventory to assess the mean score and prevalence of three domains of burnout i.e. emotional exhaustion, depersonalization and personal achievement. Chi Square and t-test were used to analyze the prevalence and mean scores respectively. Results: Mean scores of emotional exhaustion, depersonalization and personal achievement were 16.55 and 17.15, 15.42 and 9.15, 24.83 and 29.80 respectively. Depersonalization and personal achievement scores were high among family residents. 75% of family medicine participants and only 20% of internal medicine participants had a high level of depersonalization burnout (p = 0.001). Conclusions: Emotional exhaustion, depersonalization and personal achievement burnout were found at an alarmingly high rate among family medicine and internal medicine residents. Mean scores and prevalence of depersonalization and personal achievement burnout were significantly higher among family medicine residents than internal medicine residents.
The Effect of Aerobic Training on Some Bone Formation Markers (Osteocalcin, Alkaline Phosphatase) in Asthma Treated with Inhaled Corticosteroids

Background and Objectives: Some recent studies have proven that an association between inhaled glucocorticostroid and osteoporosis in asthma patients. The present study aimed to evaluate the effect of aerobic training program on serum osteocalcin and alkaline phosphatase as formation bone indicators in asthma patients. Methods: In this semi-experimental study, twenty four sedentary middle-aged asthma males treatment with inhaled glucocorticostroid aged 38 ± 6 years; BMI, 31.5 ± 3 kg/m2 were randomized to aerobic training (n = 12) and control (n = 12) groups. Fasting blood samples (8:00 - 9:00 a.m.) were collected from the antecubital vein before and after aerobic training for measure serum osteocalcin and alkaline phosphatase of 2 groups. Anthropometrical markers were also measured in all subjects before and after training program. The exercise program consisted of 40 - 60 minutes on treadmill at intensity range of 55 - 75 (%) of maximal heart rate, 3 times per week for 3 months. Student’s t-tests (Version 15.0, SPSS Inc., IL, USA) were performed to determine whether there were significant within-group changes in the outcomes. Results: Aerobic intervention improved anthropometric parameters (P < 0.05). Compared to pre-training, serum osteocalcin increased significantly (P = 0.011) after exercise program but was not changed in control subjects. Serum alkaline phosphatase did not significant change in response to aerobic training. Conclusions: Based on these results, our finding indicates that a regular aerobic exercise program is a compensation intervention for osteoporosis in asthma patients with inhaled glucocorticostroid.
Effect of surgical menopause on serum lipid profile-a prospective study

Background: Menopause marks the onset of cessation of ovarian function which is associated with changes in cardiovascular risk factors especially an unfavourable change in lipid profile. This is more pronounced is perimenopausal females who have undergone total hysterectomy with bilateral sapingo oopherectomy. This study aimed at looking into the changes occurring in the lipid profile and other cardiovascular risk in patients who have underwent oopherectomy over a 3 months period. Methods: The study was conducted as a case control one. We studied 70 consecutive perimenopausal patients admitted in a tertiary care teaching medical college hospital in Kerala, South India who were admitted for hysterectomy and bilateral oopherectomy over a 1year period. The lipid profile and anthropometric measurement with blood pressure recording was done prior to surgery and the same patients were followed up after 3 months when the cardiovascular risk assessment and lipid profile estimation were repeated. Here, the cases acted as controls after the end of third month. Results: It was found that after the end of 3 months of surgical menopause there was no significant change in body mass index, waist hip ratio or systolic BP. However, the DBP was higher in patients after surgery (78.68±7.94 vs 83.31±11.03, P 0.001). The HDLc was found to be 27% after 3 months of surgical menopause (59.31±8.22 vs 43.73±35 P>0.001. Conclusions: Thus, it was concluded that there was a significant unfavourable effects on lipid profile and diastolic blood pressure 3 months after surgical menopause.
Self‐repulsiveness of energies for closed submanifolds

We show that the regularized Riesz α‐energy for smooth closed submanifolds M in Rn$\mathbb {R}^n$ blows up as M degenerates to have double points if α≤−2dimM$\alpha \le -2\dim M$ . This gives theoretical foundation of numerical experiments to evolve surfaces to decrease the energy that have been carried out since the 90's.
Grayscale Data Construction and Multi-Level Ranking Objective for Dialogue Response Selection

Response selection plays a vital role in building retrieval-based conversation systems. Recent works on enhancing response selection mainly focus on inventing new neural architectures for better modeling the relation between dialogue context and response candidates. In almost all these previous works, binary-labeled training data are assumed: Every response candidate is either positive (relevant) or negative (irrelevant). We propose to automatically build training data with grayscale labels. To make full use of the grayscale training data, we propose a multi-level ranking strategy. Experimental results on two benchmark datasets show that our new training strategy significantly improves performance over existing state-of-the-art matching models in terms of various evaluation metrics.
Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learning

Post-click conversion rate (CVR) estimation is a critical task in e-commerce recommender systems. This task is deemed quite challenging under industrial setting with two major issues: 1) selection bias caused by user self-selection, and 2) data sparsity due to the rare click events. A successful conversion typically has the following sequential events: ”exposure → click → conversion”. Conventional CVR estimators are trained in the click space, but inference is done in the entire exposure space. They fail to account for the causes of the missing data and treat them as missing at random. Hence, their estimations are highly likely to deviate from the real values by large. In addition, the data sparsity issue can also handicap many industrial CVR estimators which usually have large parameter spaces. In this paper, we propose two principled, efficient and highly effective CVR estimators for industrial CVR estimation, namely, Multi-IPW and Multi-DR. The proposed models approach the CVR estimation from a causal perspective and account for the causes of missing not at random. In addition, our methods are based on the multi-task learning framework and mitigate the data sparsity issue. Extensive experiments on industrial-level datasets show that our methods outperform the state-of-the-art CVR models.
Prerequisites for Explainable Machine Reading Comprehension: A Position Paper

Machine reading comprehension (MRC) has received considerable attention in natural language processing over the past few years. However, the conventional task design of MRC lacks the explainability beyond the model interpretation, i.e., the internal mechanics of the model cannot be explained in human terms. To this end, this position paper provides a theoretical basis for the design of MRC based on psychology and psychometrics and summarizes it in terms of the requirements for explainable MRC. We conclude that future datasets should (i) evaluate the capability of the model for constructing a coherent and grounded representation to understand context-dependent situations and (ii) ensure substantive validity by improving the question quality and by formulating a white-box task.