Miracle-dz/UniFAR-FTUs huggingface dataset:
Early predictors of Guillain-Barré syndrome in the life course of women.

Background We sought to determine if immune disorders early in life were associated with the later risk of Guillain-Barré syndrome, a neurological disorder thought to be infection-related. Methods We conducted a longitudinal cohort study with 16 108 819 person-years of follow-up for a population of 1 108 541 parous women in Quebec, Canada (1989-2014). The outcome was Guillain-Barré syndrome. We identified women with potential risk factors for future Guillain-Barré syndrome, including immune-mediated and rheumatological diseases, cancer, transfusion, surgical procedures and pregnancy-specific disorders. We estimated hazard ratios (HR) and 95% confidence intervals (CI) for the association of risk factors with later onset of Guillain-Barré syndrome, adjusted for personal characteristics of women. Results The overall incidence of Guillain-Barré syndrome was 1.42 per 100 000 person-years. Incidence was higher for women with immune-mediated (8.79 per 100 000 person-years) and rheumatological disorders (9.84 per 100 000 person-years), transfusion (4.41 per 100 000 person-years), and preeclampsia (2.62 per 100 000 person-years). Immune-mediated disorders were associated with six times the risk of Guillain-Barré syndrome (HR 6.57, 95% CI 3.58 to 12.04), rheumatological disorders with seven times the risk (HR 7.23, 95% CI 3.21 to 16.28), transfusion three times the risk (HR 3.58, 95% CI 1.83 to 6.98) and preeclampsia two times the risk (HR 2.01, 95% CI 1.29 to 3.12). Women with other potential risk factors did not have an increased risk of Guillain-Barré syndrome. Conclusions Immune-related conditions that occur early in life are associated with an increased risk of Guillain-Barré syndrome. The pathophysiology of Guillain-Barré syndrome may extend beyond infectious triggers.
PEMANFAATAN TEPUNG KIMPUL (Xanthosoma sagittifolium) SEBAGAI BAHAN BAKU COOKIES (KAJIAN PROPORSI TEPUNG DAN PENAMBAHAN MARGARIN) Utilization of Taro Flour (Xanthosoma sagittifolium) as Cookies's Raw Material (Study of Flour Proportion and Margarine Addition)

This research is aimed to study effect of addition tapioca flour and margarine on taro cookies production. Factorial Randomized Block Design (RAK) is used in this research. Two factors are taro flour and tapioca flour proportion (60:40, 70:30, 80:20) % and addition of margarine (50,60,70)%. Data are analyzed by ANOVA and followed by BNT test on DMRT test at 5% level. Result of research indicates that the proportion of taro flour and tapioca flour and the addition of margarine have a significant interaction (α=0.05) on starch, water, lipid, tensile strength, taste, flavor, crispiness, brightness (L) and yellowness (b*).
Warwick Medical School: A four dimensional curriculum

Abstract Medical curricula vary hugely across the world. Notions of horizontal and vertical integration and spiral curricula are present in many modern curricula although true integration happens to a varying degree. By seeing the development of a curriculum as fundamentally about integration, rather than as a process of seeking to integrate separate elements, we have developed a program that prepares students well for the complexities and rate of change of practice. The risks inherent in bringing forward the point at which learners need to deal with such substantive and fundamental complexity produces challenges. Such challenges are ones that our students have shown they can not only deal with, they are often better equipped than faculty to provide solutions for themselves, their peers and those who follow them. We present the three dimensions of integration in the Warwick Medical School curriculum and note the fourth dimension provided by our students, being student led teaching and support far beyond what is normally found in medical courses.
Facebook Groups as a Powerful and Dynamic Tool in Medical Education: Mixed-Method Study

Background Social networking sites, in particular Facebook, are not only predominant in students’ social life but are to varying degrees interwoven with the medical curriculum. Particularly, Facebook groups have been identified for their potential in higher education. However, there is a paucity of data on user types, content, and dynamics of study-related Facebook groups. Objective The aim of this study was to identify the role of study-related Facebook group use, characterize medical students that use or avoid using Facebook groups (demographics, participation pattern, and motivation), and analyze student posting behavior, covered topics, dynamics, and limitations in Facebook groups with regards to educational usage. Methods Using a multi-method approach (interviews, focus groups, and qualitative and quantitative analysis of Facebook posts), we analyzed two representative Facebook groups of medical preclinical semesters at Ludwig-Maximilians-University (LMU) Munich. Facebook primary posts and replies over one semester were extracted and evaluated by using thematic content analysis. We developed and applied a coding scheme for studying the frequency and distribution of these posts. Additionally, we interviewed students with various degrees of involvement in the groups, as well as “new minorities,” students not registered on Facebook. Results Facebook groups seem to have evolved as the main tool for medical students at LMU to complement the curriculum and to discuss study-related content. These Facebook groups are self-organizing and quickly adapt to organizational or subject-related challenges posed by the curriculum. A wide range of topics is covered, with a dominance of organization-related posts (58.35% [6916/11,853] of overall posts). By measuring reply rates and comments per category, we were able to identify learning tips and strategies, material sharing, and course content discussions as the most relevant categories. Rates of adequate replies in these categories ranged between 78% (11/14) and 100% (13/13), and the number of comments per post ranged from 8.4 to 13.7 compared with the average overall reply rate of 68.69% (1167/1699) and 3.9 comments per post. User typology revealed social media drivers (>30 posts per semester) as engines of group function, frequent users (11-30 posts), and a majority of average users acting rather as consumers or lurkers (1-10 posts). Conclusions For the moment, the medical faculty has no active involvement in these groups and therefore no influence on accuracy of information, professionalism, and ethical issues. Nevertheless, faculty could in the future benefit by extracting relevant information, identifying common problems, and understanding semester-related dynamics.
Visual-Inertial Odometry on Resource-Constrained Systems

Author(s): Li, Mingyang | Advisor(s): Mourikis, Anastasios | Abstract: In this work, we focus on the problem of pose estimation in unknown environments, using the measurements from an inertial measurement unit (IMU) and a single camera. We term this estimation task visual-inertial odometry (VIO), in analogy to the well-known visual-odometry (VO) problem. Our focus is on developing VIO algorithms for high-precision, consistent motion estimation in real time. The majority of VIO algorithms proposed to date have been developed for systems which are equipped with high-end processors and high-quality sensors. By contrast, we are interested in tracking the motion of systems that are small and inexpensive, and are equipped with limited processing and sensing resources.Such resource-constrained systems are common in application areas such as micro aerial vehicles, mobile phones, and augmented reality (AR) devices. Endowing such systems with the capability to accurately track their poses will create a host of new opportunities for commercial applications, and lower the barrier to entry in robotics research and development.Performing accurate motion estimation on resource-constrained systems requires novel methodologies to address the challenges caused by the limited sensing and processing capabilities, and to provide guarantees for the optimal utilization of these resources. To this end, in this work, we focus on developing novel, resource-adaptive VIO algorithms based on the extended Kalman filter (EKF) formulation. Specifically, we (i) analyze the properties and performance of existing EKF-basedVIO approaches, and propose a novel estimator design method, which ensures the correct observability properties of the linearized system models to improve the estimates' accuracy and consistency, (ii) present a methodology for minimizing the computational cost of the EKF-VIO algorithms, which relies on online optimization of the estimator's parameters based on the properties of the environment, (iii) propose an algorithm for joint online calibration of the spatial and temporal relationship between the visual and inertial sensors, and (iv) propose high-fidelity sensor models that enable us to process the measurements captured by rolling-shutter cameras and low-cost inertial sensors. We evaluate our estimators with various simulated and real-world data sets, which demonstrate that our proposed formulations are able to consistently and accurately track the pose of resource-constrained systems in real time.
How High Can You Count? Probing the Limits of Children’s Counting

While much research has focused on understanding the process by which young children learn to count, little work has explored the effects of direct instruction on this process. In the current study, we explored the impacts of training children in an explicit counting procedure on two distinct cardinality tasks. Two- to 5-year-old children first participated in a Give-N task in which counting proficiency was assessed, and then participated in a short instruction session where explicit counting was modeled and encouraged. Following training, children were significantly better at identifying which of two cards contained a set size outside of their range of counting mastery (Huang, Spelke, & Snedeker, 2010) and were more likely to improve on a secondary numerical production task (Give-N; Wynn, 1990, 1992) compared with children in the control group. Not surprisingly, a greater proportion of children in the count training condition overtly counted during the cardinality task, a strategy that was found to be the strongest indicator of performance. Together, results reveal that even 5 min of counting instruction greatly increases the likelihood that a child will engage in counting behavior and results in improvements in cardinality judgments in two distinct numerical tasks.
Water Bacterial and Fungal Community Compositions Associated with Urban Lakes, Xi’an, China

Urban lakes play a vital role in the sustainable development of urbanized areas. In this freshwater ecosystem, massive microbial communities can drive the recycling of nutrients and regulate the water quality. However, water bacterial and fungal communities in the urban lakes are not well understood. In the present work, scanning electron microscopy (SEM) was combined with community level physiological profiles (CLPPs) and Illumina Miseq sequence techniques to determine the diversity and composition of the water bacterial and fungal community in three urban lakes, namely Xingqing lake (LX), Geming lake (LG) and Lianhu lake (LL), located in Xi’an City (Shaanxi Province, China). The results showed that these three lakes were eutrophic water bodies. The highest total nitrogen (TN) was observed in LL, with a value of 12.1 mg/L, which is 2 times higher than that of LG. The permanganate index (CODMn) concentrations were 21.6 mg/L, 35.4 mg/L and 28.8 mg/L in LG, LL and LX, respectively (p < 0.01). Based on the CLPPs test, the results demonstrated that water bacterial communities in the LL and LX urban lakes had higher carbon source utilization ability. A total of 62,742 and 55,346 high quality reads were grouped into 894 and 305 operational taxonomic units (OTUs) for bacterial and fungal communities, respectively. Water bacterial and fungal community was distributed across 14 and 6 phyla. The most common phyla were Proteobacteriaand Cyanobacteria. Cryptomycota was particularly dominant in LL, while Chytridiomycota and Entomophthormycota were the most abundant fungal phyla, accounting for 95% of the population in the LL and 56% in the LG. Heat map and redundancy analysis (RDA) highlighted the dramatic differences of water bacterial communities among three urban lakes. Meanwhile, the profiles of fungal communities were significantly correlated with the water quality parameters (e.g., CODMn and total nitrogen, TN). Several microbes (Legionella sp. and Streptococcus sp.) related to human diseases, such as infectious diseases, were also found. The results from this study provides useful information related to the water quality and microbial community compositions harbored in the aquatic ecosystems of urban lakes.
Evaluation of the threshold value for the modified early warning score (MEWS) in medical septic patients: a secondary analysis of an Italian multicentric prospective cohort (SNOOPII study)

Background Due to aging and resources limitation, septic patients are often admitted to medical wards (MWs). Early warning deterioration is a relevant issue in this setting. Unfortunately, a suitable prognostic score has not been identified, yet. Aim To explore the ability of Modified Early Warning Score (MEWS) to predict the in-hospital mortality in septic patients admitted to MWs. Design Secondary analysis of a multicentric prospective study. Methods Consecutive septic patients with positive blood culture admitted to 31 Italian MWs were included. Baseline characteristics, clinics, isolates, rate of transfer to ICU, MEWS was collected on admission according to the study protocol. The accuracy of MEWS in predicting the in-hospital mortality was assessed with the area under the receiver-operating characteristic curves. Sensitivity, specificity, positive and negative predictive value (PPV and NPV), likelihood ratio (LR) were calculated for different MEWS cut-offs and age/comorbidities subgroups. Results In total 526 patients were included in this analysis. Median MEWS was (range 0-11). In-hospital mortality was 14.8% and transfer to ICU 1.3%. Mortality progressively increased according to MEWS (3% in MEWS 0 vs. 27% in MEWS >5; Chi square for trend P < 0.05). The AUC of MEWS in predicting in-hospital mortality was 0.596 (95% CI, 0.524, 0.669). MEWS did not appear to have an adequate sensitivity, sensibility, PPV, NPV and LR both in the whole population and in the pre-specified subgroups. Conclusions Our findings do not seem to support the use of MEWS to predict the in-hospital mortality risk of sepsis in MWs.
Fingerprinting through Deep Learning

Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets. By capturing traffic traces between users and their Tor entry guard, a network eavesdropper can leverage this meta-data to reveal which website Tor users are visiting. The success of such attacks heavily depends on the particular set of traffic features that are used to construct the fingerprint. Typically, these features are manually engineered and, as such, any change introduced to the Tor network can render these carefully constructed features ineffective. In this paper, we show that an adversary can automate the feature engineering process, and thus automatically deanonymize Tor traffic by applying our novel method based on deep learning. We collect a dataset comprised of more than three million network traces, which is the largest dataset of web traffic ever used for website fingerprinting, and find that the performance achieved by our deep learning approaches is comparable to known methods which include various research efforts spanning over multiple years. The obtained success rate exceeds 96% for a closed world of 100 websites and 94% for our biggest closed world of 900 classes. In our open world evaluation, the most performant deep learning model is 2% more accurate than the state-ofthe-art attack. Furthermore, we show that the implicit features automatically learned by our approach are far more resilient to dynamic changes of web content over time. We conclude that the ability to automatically construct the most relevant traffic features and perform accurate traffic recognition makes our deep learning based approach an efficient, flexible and robust technique for website fingerprinting.
Eye Gaze-driven Prediction of Cognitive Differences during Graphical Password Composition

Evidence suggests that individual cognitive differences affect users' memorability, visual behavior, and graphical passwords' security. Such knowledge denotes the added value of personalizing graphical password schemes towards the unique cognitive characteristics of the users. However, real-time and accurate cognition-based predictive user models are necessary to reach such a breakthrough. In this paper, we present the results of such an attempt, where an in-lab eye-tracking study was conducted with 36 participants who completed a recall-based graphical password composition task. We adopted a credible cognitive style theory, and investigated a variety of eye-tracking metrics to predict participants' cognitive styles. Results' analysis reveals that inferring individual cognitive differences in real-time during graphical password composition is feasible within a few seconds and that specific eye-tracking metrics correlate stronger with certain cognitive style groups. The findings further support the vision of incorporating real-time adaptive mechanisms in graphical password schemes for the benefit of service providers and end-users.
Suppression of Lipogenesis via Reactive Oxygen Species-AMPK Signaling for Treating Malignant and Proliferative Diseases.

AIMS Systemic diseases often have common characteristics. The aim of this study was to investigate the feasibility of targeting common pathological metabolism to inhibit the progression of malignant and proliferative diseases. RESULTS Gefitinib-resistant (G-R) nonsmall-cell lung cancer (NSCLC) and rheumatoid arthritis (RA) were studied as conditions representative of malignant and proliferative diseases, respectively. Strong lipogenic activity and high expression of sterol regulatory element-binding protein 1 (SREBP1) were found in both G-R NSCLC cells and synovial fibroblasts from RA patients (RASFs). Berberine (BBR), an effective suppressor of SREBP1 and lipogenesis regulated through reactive oxygen species (ROS)/AMPK pathway, selectively inhibited the growth of G-R NSCLC cells and RASFs but not that of normal cells. It effectively caused mitochondrial dysfunction, activated ROS/AMPK pathway, and finally suppressed cellular lipogenesis and cell proliferation. Addition of ROS blocker, AMPK inhibitor, and palmitic acid significantly reduced the effect of BBR. In an in vivo study, treatment of BBR led to significant inhibition of mouse tumor xenograft growth and remarkably slowed down the development of adjuvant-induced arthritis in rats. Innovation and Conclusion: Targeting ROS/AMPK/lipogenesis signaling pathway selectively inhibited the growth of G-R NSCLC cells and the progress of RASFs in vitro and in vivo, which provides a new avenue for treating malignancies and proliferative diseases. Antioxid. Redox Signal. 28, 339-357.
iCONCUR: informed consent for clinical data and bio-sample use for research

Background: Implementation of patient preferences for use of electronic health records for research has been traditionally limited to identifiable data. Tiered e-consent for use of de-identified data has traditionally been deemed unnecessary or impractical for implementation in clinical settings. Methods: We developed a web-based tiered informed consent tool called informed consent for clinical data and bio-sample use for research (iCONCUR) that honors granular patient preferences for use of electronic health record data in research. We piloted this tool in 4 outpatient clinics of an academic medical center. Results: Of patients offered access to iCONCUR, 394 agreed to participate in this study, among whom 126 patients accessed the website to modify their records according to data category and data recipient. The majority consented to share most of their data and specimens with researchers. Willingness to share was greater among participants from an Human Immunodeficiency Virus (HIV) clinic than those from internal medicine clinics. The number of items declined was higher for for-profit institution recipients. Overall, participants were most willing to share demographics and body measurements and least willing to share family history and financial data. Participants indicated that having granular choices for data sharing was appropriate, and that they liked being informed about who was using their data for what purposes, as well as about outcomes of the research. Conclusion: This study suggests that a tiered electronic informed consent system is a workable solution that respects patient preferences, increases satisfaction, and does not significantly affect participation in research.
3D liver membrane system by co-culturing human hepatocytes, sinusoidal endothelial and stellate cells

In this study, a designed approach has been utilized for the development of a 3D liver system. This approach makes use of primary human sinusoidal endothelial cells, stellate cells and hepatocytes that are seeded sequentially on hollow fiber membranes (HF) in order to mimic the layers of cells found in vivo. To this purpose modified polyethersulfone (PES) HF membranes were used for the creation of a 3D human liver system in static and dynamic conditions. In order to verify the positive effect of non-parenchymal cells on the maintenance of hepatocyte viability and functions, homotypic cultures of hepatocytes alone on the HF membranes were further investigated. The membrane surface allowed the attachment and self-assembly of the cells, forming tissue-like structures around and between fibers. Sinusoidal cells formed tube-like structures that surrounded hepatocytes organized in cords within aggregates promoted by stellate cells. The co-culture of hepatocytes with sinusoidal endothelial and hepatic stellate cells preserved structural architecture of the construct and improved the liver-specific functions. Most importantly, cells co-cultured in a HF membrane bioreactor synthesized albumin and urea for 28 days. The liver membrane bioreactor also preserved the drug biotransformation activity with a continuous production of diazepam phase I metabolites for an extended period of time. Additionally, the cell oxygen uptake rates highlighted the maintenance of the actual oxygen concentration at a level compatible with their metabolic functions.