Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining the incidence of familiality in ALS

Objective To assess temporal trends in familial amyotrophic lateral sclerosis (FALS) incidence rates in an Irish population and to determine factors influencing FALS ascertainment. Methods Population-based data collected over 23 years, using the Irish amyotrophic lateral sclerosis (ALS) register and DNA biobank, were analyzed and age-standardized rates of FALS and associated familial neuropsychiatric endophenotypes were identified. Results Between 1994 and 2016, 269 patients with a family history of ALS from 197 unique families were included on the register. Using stringent diagnostic criteria for FALS, the mean age-standardized FALS incidence rate for the study period was 11.1% (95% confidence interval [CI], 8.8–13.4). The FALS incidence rate increased steadily from 5.2% in 1994 to 19.1% in 2016, an annual increase of 0.7% (95% CI, 0.5–0.9, p < 0.0001). Inclusion of the presence of neuropsychiatric endophenotypes within kindreds increased the FALS incidence rate to 30%. The incidence of FALS in newly diagnosed individuals from known families increased significantly with time, accounting for 50% of all FALS diagnoses by 2016. The mean annual rate of recategorization from “sporadic ALS” to “FALS” was 3% (95% CI, 2.6–3.8). Conclusions The true population-based rate of FALS is at least 20%. Inclusion of extended endophenotypes within kindreds increases the rate of FALS to 30%. Cross-sectional analysis of clinic-based cohorts and stringent definitions of FALS underestimate the true rate of familial disease. This has implications for genetic counseling and in the recognition of presymptomatic stages of ALS.
The scale of life and its lessons for humanity

The scale of life on Earth is shaped by a confluence of biophysical, evolutionary, ecological, and, recently, human forces. Measuring the scale of life offers insights about these forces and raises many more questions. In PNAS, Bar-On et al. (1) offer the most comprehensive quantification to date of the biomass of life on Earth, broken down by major taxonomic groups, ecological strategies, and environments. Despite high uncertainty in some estimates, their findings shed fascinating light on how biomass is distributed. Although many of the detailed findings will likely surprise most readers, the study also builds a foundation for exploring major ecological, evolutionary, and environmental questions. We highlight two such questions as examples of the future impact of this work. One of the findings is the striking contrast between marine and terrestrial biomes. Can we account for the differences on the basis of what we know about how these disparate ecosystems function? The findings also raise important questions about the future. What scale of human activities can be supported by marine and terrestrial environments, looking forward? How will climate change alter the answers? Total primary productivity in the oceans [48.5 Gt C/y net primary production (NPP)] is similar to that on land (56.4 Gt C/y NPP), even though the oceans have more than twice as much surface area (2). However, despite similar total primary productivity, Bar-On et al. (1) estimate that there is roughly 80 times more biomass on land than in the oceans. Terrestrial plants—which comprise ∼80% of the total biomass on Earth—make up most of this difference. In striking contrast to the land’s dominance of producer biomass, Bar-On et al. (1) estimate that more than 70% of global animal biomass is found in the ocean. Earth has a plant-dominated landscape and an animal-dominated seascape. What could explain these fundamental … [↵][1]1To whom correspondence may be addressed. Email: mburgess{at}ucsb.edu or gaines{at}ucsb.edu. [1]: #xref-corresp-1-1
Preparation and drug-loading properties of human hair keratin nanoparticles

Human hair keratin (HHK) solution was first prepared by using a modified reduction method. Based on self-assembly and electrostatic interaction of the HHK solution, a novel nano drug delivery system for HHK/mupirocin was also prepared by adjusting the ratio and concentration between mupirocin and HHK. The morphology, particle size, drug-loading capacity and entrapment efficiency of the nanoparticles were also discussed. The results showed that the mutual hydrophobic aggregation between HHK and mupirocin was the main reason for forming nano drug delivery system. The average particle size of the nanoparticles was 74.78 nm. The drug-loading capacity of MPC for the nanoparticles was increased but entrapment efficiency of MPC was decreased with an increase of MPC concentration.
Diagnostic markers for CNS lymphoma in blood and cerebrospinal fluid: a systematic review

Diagnosing central nervous system (CNS) lymphoma remains a challenge. Most patients have to undergo brain biopsy to obtain tissue for diagnosis, with associated risks of serious complications. Diagnostic markers in blood or cerebrospinal fluid (CSF) could facilitate early diagnosis with low complication rates. We performed a systematic literature search for studies on markers in blood or cerebrospinal fluid for the diagnosis CNS lymphoma and assessed the methodological quality of studies with the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS‐2). We evaluated diagnostic value of the markers at a given threshold, as well as differences between mean or median levels in patients versus control groups. Twenty‐five studies were included, reporting diagnostic value for 18 markers in CSF (microRNAs ‐21, ‐19b, and ‐92a, RNU2‐1f, CXCL13, interleukins ‐6, ‐8, and ‐10, soluble interleukin‐2‐receptor, soluble CD19, soluble CD27, tumour necrosis factor‐alfa, beta‐2‐microglobulin, antithrombin III, soluble transmembrane activator and calcium modulator and cyclophilin ligand interactor, soluble B cell maturation antigen, neopterin and osteopontin) and three markers in blood (microRNA‐21 soluble CD27, and beta‐2‐microglobulin). All studies were at considerable risk of bias and there were concerns regarding the applicability of 15 studies. CXCL‐13, beta‐2‐microglobulin and neopterin have the highest potential in diagnosing CNS lymphoma, but further study is still needed before they can be used in clinical practice.
1 Substrate-induced response in biogas process 2 performance and microbial community relates back 3 to inoculum source 4

This study investigated whether biogas reactor performance, including microbial 12 community development, in response to a change in substrate composition is influenced by initial 13 inoculum source. Test reactors were first started with two different inocula and operated with the 14 same grass-manure mixture for more than 120 days. These reactors initially showed great 15 differences depending on inoculum source, but eventually showed similar performance and overall 16 microbial community structure. At the start of the present experiment, the substrate was 17 complemented with milled feed wheat, added all at once or divided into two portions. The starting 18 hypothesis was that process performance depends on initial inoculum source and microbial 19 diversity, and thus that reactor performance is influenced by the feeding regime. In response to the 20 substrate change, all reactors showed increases and decreases in volumetric and specific methane 21 production, respectively. However, specific methane yield and development of the microbial 22 community showed differences related to initial inoculum source, confirming the hypothesis. The 23 different feeding strategies had however only minor effects on process performance and overall 24 community structure, but still induced differences in the cellulose-degrading community and in 25 cellulose degradation. 26
"How to rate a video game?" - A prediction system for video games based on multimodal information

Video games have become an integral part of most people's lives in recent times. This led to an abundance of data related to video games being shared online. However, this comes with issues such as incorrect ratings, reviews or anything that is being shared. Recommendation systems are powerful tools that help users by providing them with meaningful recommendations. A straightforward approach would be to predict the scores of video games based on other information related to the game. It could be used as a means to validate user-submitted ratings as well as provide recommendations. This work provides a method to predict the G-Score, that defines how good a video game is, from its trailer (video) and summary (text). We first propose models to predict the G-Score based on the trailer alone (unimodal). Later on, we show that considering information from multiple modalities helps the models perform better compared to using information from videos alone. Since we couldn't find any suitable multimodal video game dataset, we created our own dataset named VGD (Video Game Dataset) and provide it along with this work. The approach mentioned here can be generalized to other multimodal datasets such as movie trailers and summaries etc. Towards the end, we talk about the shortcomings of the work and some methods to overcome them.
Socially-driven persuasive health intervention design: Competition, social comparison, and cooperation

Persuasive technologies are tools for motivating behaviour change using persuasive strategies. socially-driven persuasive technologies employ three common socially-oriented persuasive strategies in many health domains: competition, social comparison, and cooperation. Research has shown the possibilities for socially-driven persuasive interventions to backfire by demotivating behaviour, but we lack knowledge about how the interventions could motivate or demotivate behaviours. To close this gap, we studied 1898 participants, specifically Socially-oriented strategies and their comparative effectiveness in socially-driven persuasive health interventions that motivate healthy behaviour change. The results of a thematic analysis of 278 pages of qualitative data reveal important strengths and weaknesses of the individual socially-oriented strategies that could facilitate or hinder their effectiveness at motivating behaviour change. These include their tendency to simplify behaviours and make them fun, challenge people and make them accountable, give a sense of accomplishment and their tendency to jeopardize user’s privacy and relationships, creates unnecessary tension, and reduce self-confidence and self-esteem, and provoke a health disorder and body shaming, respectively. We contribute to the health informatics community by developing 15 design guidelines for operationalizing the strategies in persuasive health intervention to amplify their strengths and overcome their weaknesses.
Examining government-citizen interactions on Twitter using visual and sentiment analysis

The goal of this paper is to propose a methodology comprising a range of visualization techniques to analyze the interactions between government and citizens on the issues of public concern taking place on Twitter, mainly through the official government or ministry accounts. The methodology addresses: 1) the level of government activity in different countries and sectors; 2) the topics that are addressed through such activities; 3) the resources shared between government and citizens as part of interactions; 4) the intensity of citizen response to government announcements; 5) the sentiment expressed by citizens when providing such responses; and 6) the combinations of such issues. Example combinations include identifying topics that generated the largest Twitter activity by government but received the least interest from citizens, identifying topics that generated the most polarized reactions from citizens, or determining correlation between policy announcements and trust, fear and other negative emotions expressed by citizens. The methodology uses visual analytics to reveal patterns and trends associated with various questions, complemented with sentiment analysis to study government-citizen interactions on Twitter. The methodology is validated by examining Twitter presence in five sectors --- health, social development, education, environment and work, in five Latin American countries with mature e-Participation capabilities --- Argentina, Chile, Colombia, Mexico and Uruguay.
Genetics of Cardiovascular Disease: Fishing for Causality

Cardiovascular disease (CVD) is still the leading cause of death in all western world countries and genetic predisposition in combination with traditional risk factors frequently mediates their manifestation. Genome-wide association (GWA) studies revealed numerous potentially disease modifying genetic loci often including several SNPs and associated genes. However, pure genetic association does not prove direct or indirect relevance of the modifier region on pathogenesis, nor does it define within the associated region the exact genetic driver of the disease. Therefore, the relevance of the identified genetic disease associations needs to be confirmed either in monogenic traits or in experimental in vivo model system by functional genomic studies. In this review, we focus on the use of functional genomic approaches such as gene knock-down or CRISPR/Cas9-mediated genome editing in the zebrafish model to validate disease-associated genomic loci and to identify novel cardiovascular disease genes. We summarize the benefits of the zebrafish for cardiovascular research and highlight examples demonstrating the successful combination of GWA studies and functional genomics in zebrafish to broaden our knowledge on the genetic and molecular underpinnings of cardiovascular diseases.
Smoking and Physical Activity Explain the Increased Mortality Risk Following Marital Separation and Divorce: Evidence From the English Longitudinal Study of Ageing.

BACKGROUND Marital separation and divorce are associated with an increased risk of early mortality, but the specific biobehavioral pathways that explain this association remain largely unknown. PURPOSE This study sought to identify the putative psychological, behavioral, and biomarker variables that can help explain the association of being separated or divorced and increased risk for early mortality. METHODS Using data from the English Longitudinal Study of Ageing, a representative community sample of aging adults (N = 5,786), we examined the association of marital status and life satisfaction, health behaviors measured 2 years later, biomarkers measured 4 years later, and mortality outcomes from the subsequent 4 years. RESULTS Consistent with prior literature, older adults who were separated/divorced evidenced greater risk of mortality relative to those in intact marriages over the study period, OR = 1.46, 95% CI [1.15, 1.86]. Marital status was associated with lower levels of life satisfaction, β = -0.22 [-0.25, -0.19] and greater likelihood of smoking 2 years later β = 0.17 [0.13, 0.21]. Lower life satisfaction predicted less frequent physical activity 2 years later, β = 0.07 [0.03, 0.10]. Smoking, but not physical activity, predicted poorer lung functioning 2 years later, β = -0.43 [-0.51, -0.35], and poorer lung function predicted increased likelihood of mortality over the following 4 years, β = -0.15 [-0.27, -0.03]. There was a significant total indirect effect of marital status on mortality through these psychological, behavioral, and biomarker variables, β = 0.03 [0.01, 0.05], which fully explained this mortality risk. CONCLUSIONS For separated/divorced adults, differences in life satisfaction predict health behaviors associated with poorer long-term lung function, and these intermediate variables help explain the association between marital dissolution and increased risk of earlier mortality.
Clinical Characteristics, Etiology and Phylogenetic Distribution of Bacteremia in Patients with Malignancies in Basrah Province

This is the first study in Basrah province/Iraq to detect the geographical distribution of adult oncology patients with bacteremia and the bacterial etiology. From 176 patients’ samples, the highest incidence of cancer cases was recorded in central 62 (35.22%) followed by western 45 (25.56%), northern 34 (19.31%), southern 24 (13.63%) and eastern 11 (6.25%) regions. The majority of cancer with bacteremic episodes (64) were located in the central 23 (35.93%), western 16 (25%) and southern 13 (20.31%) regions, while they were less likely to occur in the northern 7 (10.93%) and eastern 5 (7.81%) regions. Some clinical characteristics, including age (30-60 year), leukemia (64.06%), healthcare exposure (73.43%), neutropenia (71.87%), non-antibiotic administration (81.25%) and fever (100%) were associated with bacteremic episodes. Sixty-three (98.43%) of these episodes were caused by Gram-positive pathogens, especially 48 (75 %) Bacillus spp. , these were 21 B. licheniformis, 19 B. cereus, 3 B. subtillus, 3 B. sonorensis, 1 B. aeruius and 1 B. toyonensis. On the other hand, 3 Staphylococcus epidermidis, 1 isolate of S. warneri, Lysinibacillus sphaericus, Lysinibacillus xylanilyticus, Enterobacter cancerogenous and 9 other of Gram-positive bacteria (unidentified). Exclusively, this is the first study isolated Gr-ve Enterobacter cancerogenous from cancer patients with bacteremia. Three isolates Bacillus licheniformis “IRQBAS18”, Bacillus licheniformis “IRQBAS19” and Bacillus licheniformis “IRQBAS20” were reported as new global bacterial strains. RAPD analysis showed four patients from different regions, each two (9.5% for each) had the same strain of Bacillus licheniformis and other four (19.04%) patients from different regions had closely related strains of Bacillus licheniformis, these results confirm that the bacteremic infections were coming from the same source.
Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis

Preventing psychosis in patients at clinical high risk may be a promising avenue for pre‐emptively ameliorating outcomes of the most severe psychiatric disorder. However, information on how each preventive intervention fares against other currently available treatment options remains unavailable. The aim of the current study was to quantify the consistency and magnitude of effects of specific preventive interventions for psychosis, comparing different treatments in a network meta‐analysis. PsycINFO, Web of Science, Cochrane Central Register of Controlled Trials, and unpublished/grey literature were searched up to July 18, 2017, to identify randomized controlled trials conducted in individuals at clinical high risk for psychosis, comparing different types of intervention and reporting transition to psychosis. Two reviewers independently extracted data. Data were synthesized using network meta‐analyses. The primary outcome was transition to psychosis at different time points and the secondary outcome was treatment acceptability (dropout due to any cause). Effect sizes were reported as odds ratios and 95% confidence intervals (CIs). Sixteen studies (2,035 patients, 57% male, mean age 20.1 years) reported on risk of transition. The treatments tested were needs‐based interventions (NBI); omega‐3 + NBI; ziprasidone + NBI; olanzapine + NBI; aripiprazole + NBI; integrated psychological interventions; family therapy + NBI; D‐serine + NBI; cognitive behavioural therapy, French & Morrison protocol (CBT‐F) + NBI; CBT‐F + risperidone + NBI; and cognitive behavioural therapy, van der Gaag protocol (CBT‐V) + CBT‐F + NBI. The network meta‐analysis showed no evidence of significantly superior efficacy of any one intervention over the others at 6 and 12 months (insufficient data were available after 12 months). Similarly, there was no evidence for intervention differences in acceptability at either time point. Tests for inconsistency were non‐significant and sensitivity analyses controlling for different clustering of interventions and biases did not materially affect the interpretation of the results. In summary, this study indicates that, to date, there is no evidence that any specific intervention is particularly effective over the others in preventing transition to psychosis. Further experimental research is needed.
Quantum Chaos and Mesoscopic Systems.

Abstract : The interplay of classical chaotic properties and of quantum coherence effects is crucially important in mesoscopic physics, as it gives rise to transport fluctuations and quantum localization. We have studied both effects in different models. The results we have obtained are potentially relevant to all fields of Quantum Chaology, with possible experimental applications in the domains of Atomic Physics, Mesoscopic Physics, and Classical wave propagation (e.g. acoustic, microwave and optical resonators.
CENNLP at SemEval-2018 Task 1: Constrained Vector Space Model in Affects in Tweets

This paper discusses on task 1, “Affect in Tweets” sharedtask, conducted in SemEval-2018. This task comprises of various subtasks, which required participants to analyse over different emotions and sentiments based on the provided tweet data and also measure the intensity of these emotions for subsequent subtasks. Our approach in these task was to come up with a model on count based representation and use machine learning techniques for regression and classification related tasks. In this work, we use a simple bag of words technique for supervised text classification model as to compare, that even with some advance distributed representation models we can still achieve significant accuracy. Further, fine tuning on various parameters for the bag of word, representation model we acquired better scores over various other baseline models (Vinayan et al.) participated in the sharedtask.
Low-area implementations of concurrent error detection logarithmic processors

In this paper, low-area implementations of concurrent error detection (CED) logarithmic processors are proposed. By adopting our logarithmic/anti-logarithmic converters with same functions having different architectures, the proposed schemes can perform logarithm-based multiplications/divisions with CED ability. Simulation results show that our proposed CED logarithmic processors can outperform conventional multipliers/dividers in terms of delay and area, which are more suitable for real-time computations with CED ability.
Vertical Distribution of Olympia oyster (Ostrea lurida) larvae in Fidalgo Bay, WA

iv Acknowledgements.vi List of Tables.viii List of Figures.ix Introduction.1 Methods.6 Study location.6 Tidal Currents.6 Larval Abundance and Physical Parameters.7 Larval Identification and Size.8 Data Analysis.9 Results . 11 Tidal Currents.11 Physical Conditions.12 Larval Abundance.12 Larval Weighted Mean Depth.13 Discussion.14 Tables.22 Figures.26 Appendix A.35 References.38
Using Machine Learning to Facilitate the Delivery of Person Centered Care in Nursing Homes

Nursing home providers are moving towards a model of care that is person centered in order to improve the quality of care and quality of life for individuals residing in their communities. The State of Ohio has mandated that providers use the Preferences for Everyday Living Inventory (PELI) to assess resident preferences. This paper and pencil assessment adds to an increasing data management barrier to efﬁciently incorporate preferences into care. We are in the process of developing the Care Preference Assessment of Satisfaction or ComPASS system which supports data collection and reporting in order to better integrate preferences into the everyday care of residents. With this platform we are exploring how machine learning can be used to provide more personalized care in nursing homes by providing insights and recommendations based on resident preferences while lessening the data collection and management burden. In this paper, we describe ComPASS, discuss our initial investigations into using machine learning for long-term care, present initial ﬁndings, and suggest future directions for this research.