Miracle-dz/UniFAR-FTUs huggingface dataset:
Immortal time bias in the study of effectiveness of interferon‐β in multiple sclerosis

We read with interest Trojano and colleagues’ observational study reporting an important decrease in the rates of secondary progression, Expanded Disability Status Scale scores of 4 and 6 for patients treated with interferon (IFN) compared with nontreated patients (adjusted rate ratios: 0.38, 0.70, and 0.60, respectively). We believe that the study is subject to immortal time bias, which has been described in other study cohorts of drug effects in several diseases. The bias arises from the different definitions of cohort entry for treated and nontreated patients. Patients treated with IFN entered the cohort at the time of the first administration of IFN, whereas nontreated patients entered the cohort at the time of their first admission in the multiple sclerosis center. The time period between first admission and first administration of IFN for the treated cohort corresponds to “immortal time. ” Indeed, no outcome event could have occurred during this time period in the treated cohort. Had an event occurred during this period, patients would have been excluded from the analysis. This immortal person-time period should have been accounted for as nontreated until the time of treatment and as treated afterward using techniques for time-dependent exposures and included in the rate denominator of the nontreated cohort. By not accounting for this immortal person-time period, the authors introduced a bias because the rate of outcome in the nontreated cohort is artificially inflated so that the rate ratio is biased downward. Using data from Trojano and colleagues’ article, we reproduced the biased analysis together with the correct approach, using the same cohort entry for the treated and nontreated cohort as the time of the first admission in the multiple sclerosis department, thus properly accounting for immortal time (Table). We used a mean follow-up of 5.7 years, with an equal proportion of excluded patients between the two cohorts. The number of events was estimated from the percentages of patients with events (numbers of subjects and events for each analysis were not provided in the article). Using the biased approach with our extracted data, we determined the estimated rate ratios to be 0.40 and 0.73 for secondary progression and Expanded Disability Status Scale 4, respectively, similar to those that Trojano and colleagues found. Correcting for immortal time bias, the rate ratios increased to 1.03 and 2.02, respectively due exclusively to the increase in the person-years denominator of the no IFNgroup. For Expanded Disability Status Scale score of 6, biased and unbiased estimated rate ratios were 0.62 and 1.6 (data not shown). The presence of immortal time bias in this study is sufficiently important to explain the apparent benefit of IFN in multiple sclerosis patients reported in this paper.
A Multimodal Examination of Emotional Responding to a Trauma-Relevant Film Among Traumatic Motor Vehicle Accident Survivors

The Facial Action Coding System (Ekman & Friesen) has shown promise as a behavioral measure of emotional experience. The current study examined the degree of (de)synchrony between self-reported and facial expressions of fear, disgust, and sadness in response to a traumatic event–relevant film among individuals who had experienced a traumatic motor vehicle accident. Given high rates of comorbidity between posttraumatic stress symptoms (PTSS) and depressive symptoms, the potential impacts of both PTSS and depressive symptoms on emotional responding were examined. Results demonstrated synchrony between self-reported and facial expressions of disgust and sadness; however, no association between measures of fear was observed. Furthermore, depressive symptoms were associated with greater fear responding and PTSS were associated only with self-reported fear. Together, results support the importance of examining discrete negative emotions, rather than broad valence categories, when examining fear-based responding in traumatic event–exposed populations. Additional research examining the psychometric properties of the Facial Action Coding System as a measure of discrete emotional experiences among traumatic event–exposed individuals is needed to advance multimodal assessment approaches that yield incremental information for understanding emotional responding in this population.
MEMS Based Differential Scanning Calorimeter for Biomolecular Study

This paper presented a MEMS based differential scanning calorimeter (DSC) for biomolecular characterization. In this MEMS based DSC, PDMS (Polydimethylsiloxane) and Flexdyne thin film were used to construct the microfluidic chamber. Polyimide were used to fabricate the flexible substrate and temperature sensitive vanadium oxide was used as the thermistor material. A heating stage was used to heat the sample and reference up at a certain rate. The resolution study and step response characterization indicated the high sensitivity (6.1V/W) of the device. The test with Bovine Serum Albumin (BSA) samples showed clear phase transitions and the data was confirmed to be reasonable by comparing it with the results of commercial DSC’s test. This device used 0.63uL sample amount and could complete the scanning process in 3 minutes, significantly increasing the throughput of the biomolecular thermodynamics study like protein denaturation process compared to the traditional DSC (1 to 2 hours).
Protein stability curves

The stability curve of a protein is defined as the plot of the free energy of unfolding as a function of temperature. For most proteins the change in heat capacity on denaturation, or unfolding, is large but approximately constant. When unfolding is s two‐state process, most of the salient features of the stability curves of proteins can be derived from this fact. A number of relations are obtained, including the special features of low‐temperature denaturation, the properties of the maximum in stability, and the interrelationships of the characteristic temperatures of the protein. The paper closes with a formula that permits one to calculate small changes in stabilization free energy from changes in the melting temperature of the protein.
New designs for improving the efficiency and resilience of natural language watermarking

Contributing our own creativity (in the form of text, image, audio, and video) to the pool of online information is fast becoming an essential part of online experience. However, it is still an open question as to how we, as authors, can control the way that the information we create is distributed or re-used. Rights management problems are serious for text since it is particularly easy for other people to download and manipulate copyrighted text from the Internet and later re-use it free from control. There is a need for a rights protection system that "travels with the content". Digital watermarking is a mechanism that embeds the copyright information in the document. Besides traveling with the content of the documents, digital watermarks can also be imperceptible to the user, which makes the process of removing them from the document challenging. The goal of this thesis is to design practical and resilient natural language watermarking systems. I have designed and implemented several natural language watermarking algorithms that use the linguistic features of the cover text in order to embed information. Using linguistic features provides resilience through making the message an elemental part of the content of the text, and through the judicious use of ambiguity in the usage of natural language and richness of features of natural language constituents. In this thesis, I propose several practical and resilient natural language watermarking systems for a variety of genres of text (short, long, edited and cursory text) and analyze their resilience and feasibility. Significant by-products of this research are as follows: a protocol for improving the stealthiness of information hiding systems; systems for using the proposed information hiding mechanisms to solve the problems of private communication and phishing defense; analysis of the evaluation methodologies and detection techniques for information hiding systems that use natural language text as cover.
NCO-sP(EO-stat-PO) Coatings on Gold Sensors—a QCM Study of Hemocompatibility

The reliability of implantable blood sensors is often hampered by unspecific adsorption of plasma proteins and blood cells. This not only leads to a loss of sensor signal over time, but can also result in undesired host vs. graft reactions. Within this study we evaluated the hemocompatibility of isocyanate conjugated star shaped polytheylene oxide—polypropylene oxide co-polymers NCO-sP(EO-stat-PO) when applied to gold surfaces as an auspicious coating material for gold sputtered blood contacting sensors. Quartz crystal microbalance (QCM) sensors were coated with ultrathin NCO-sP(EO-stat-PO) films and compared with uncoated gold sensors. Protein resistance was assessed by QCM measurements with fibrinogen solution and platelet poor plasma (PPP), followed by quantification of fibrinogen adsorption. Hemocompatibility was tested by incubation with human platelet rich plasma (PRP). Thrombin antithrombin-III complex (TAT), β-thromboglobulin (β-TG) and platelet factor 4 (PF4) were used as coagulation activation markers. Furthermore, scanning electron microscopy (SEM) was used to visualize platelet adhesion to the sensor surfaces. Compared to uncoated gold sensors, NCO-sP(EO-stat-PO) coated sensors revealed significant better resistance against protein adsorption, lower TAT generation and a lower amount of adherent platelets. Moreover, coating with ultrathin NCO-sP(EO-stat-PO) films creates a cell resistant hemocompatible surface on gold that increases the chance of prolonged sensor functionality and can easily be modified with specific receptor molecules.
From social network to safety net: Dementia-friendly communities in rural northern Ontario

Dementia-friendly communities, as communities that enable people with dementia to remain involved and active and have control over their lives for as long as possible, centrally involve social support and social networks for people living with dementia. The purpose of this research was to explore and understand the context of dementia in rural northern communities in Ontario with an emphasis on understanding how dementia friendly the communities were. Using qualitative methods, interviews were conducted with a total of 71 participants, including 37 health service providers, 15 care partners, 2 people living with dementia and 17 other community members such as local business owners, volunteers, local leaders, friends and neighbours. The strong social networks and informal social support that were available to people living with dementia, and the strong commitment by community members, families and health care providers to support people with dementia, were considered a significant asset to the community. A culture of care and looking out for each other contributed to the social support provided. In particular, the familiarity with others provided a supportive community environment. People with dementia were looked out for by community members, and continued to remain connected in their communities. The social support provided in these communities demonstrated that although fragile, this type of support offered somewhat of a safety net for individuals living with dementia. This work provides important insights into the landscape of dementia in rural northern Ontario communities, and the strong social supports that sustain people with dementia remaining in the communities.
Energy-Efficient Activity Recognition Using Prediction

Energy storage is quickly becoming the limiting factor in mobile pervasive technology. For intelligent wearable applications to be practical, methods for low power activity recognition must be embedded in mobile devices. We present a novel method for activity recognition which leverages the predictability of human behavior to conserve energy. The novel algorithm accomplishes this by quantifying activity-sensor dependencies, and using prediction methods to identify likely future activities. Sensors are then identified which can be temporarily turned off at little or no recognition cost. The approach is implemented and simulated using an activity recognition data set, revealing that large savings in energy are possible at very low cost (e.g. 84% energy savings for a loss of 1.2 pp in recognition).
Design and Characterization of an Aequorin‐based Bacterial Biosensor for Detection of Toluene and Related Compounds

An aequorin‐based Escherichia coli strain JM109 biosensor was constructed and characterized for its potential to detect toluene and related compounds in aqueous solutions. The biosensor was constructed based on a PGL2 plasmid carrying the lower pathway promoter (Pu) of the xyl operon of Pseudomonas putida mt‐2, which was incorporated with transcriptional activator xylR and fused to aequorin cDNA named pGL2‐aequorin. Binding of xylR protein to a subset of toluene‐like compounds activates transcription at the Pu promoter, thus expression of aequorin is controlled by xylR and Pu. In this work we have compared the effect of Shine‐Dalgarno (SD) and T2 rrnβ terminator sequence in the expression of aequorin. According to the sensitivity of aequorin and increase in the signal‐to‐noise ratio, this reporter enzyme has reasonable sensitivity compared with other reporter systems. The results indicate higher expression of aequorin in the presence of SD and T2 rrnβ. The activity of aequorin in recombinant whole‐cell biosensor was linear from 1 to 500 μm of toluene. The bioluminescence response was specific for toluene‐like molecules, so this biosensor cells would be able to detect toluene derivative contamination in environmental samples, accurately.
E-government impacts on effectiveness: a survey study of an e-official-document system

Government promulgates directives and disseminates information through official documents. An internet-based official document processing system will not only expedite the document processing flow, which in turn improves administration efficiency, but also result in big savings on paper, envelop, postage, etc. Furthermore, the transport of documents will no longer be affected by the weather or distance, which in turn affords promptness and reliability. This study constructed a research model to measure the effectiveness of an e-official-document system deployed in Pingdong County in Taiwan, in terms of its impact on user satisfaction, individual performance and the performance of subordinate agencies.
Risk factors for liver transplant waitlist dropout in patients with hepatocellular carcinoma

Loco‐regional therapy has been developed to reduce waitlist dropout in patients with hepatocellular carcinoma (HCC) awaiting liver transplantation. We evaluated the probability of transplantation and waitlist dropout, and analyzed risk factors for waitlist dropout, in 76 patients with HCC from September 2004 to August 2006. Seventy‐three (96.1%) patients received one or more preoperative loco‐regional treatments and 55 (72.3%) received an orthotopic liver transplantation with a median wait time of seven months (range, 2–26 months). There were 11 dropouts (14.5%) associated with tumor progression or hepatic decompensation (median waiting time; 5.4 months and range, 0.4–13 months). Cumulative probabilities of transplantation at three, six, nine, 12, 15, and 18 months were 5.4%, 35.4%, 67.5%, 78.8%, 80.7%, and 80.7%, respectively and those of waitlist dropout at three, six, nine, 12, 15, and 18 months were 3.9%, 8.7%, 12.8%, 22.9%, 29.3%, and 29.3%, respectively. A laboratory model for end‐stage liver disease (MELD) score >15 or multiple tumors at the time of UNOS listing were significant risk factors for waitlist dropout (p = 0.006 and 0.026, respectively). Patients with HCC being managed with loco‐regional therapy who have a laboratory MELD score >15 or multiple tumors should be considered for earlier access to liver transplantation to prevent waitlist dropout.
The free and cued selective reminding test for predicting progression to Alzheimer's disease in patients with mild cognitive impairment: A prospective longitudinal study

Amnestic mild cognitive impairment (aMCI) patients carry a greater risk of conversion to Alzheimer's disease (AD). Therefore, the International Working Group (IWG) on AD aims to consider some cases of aMCI as symptomatic prodromal AD. The core diagnostic marker of AD is a significant and progressive memory deficit, and the Free and Cued Selective Reminding Test (FCSRT) was recommended by the IWG to test memory in cases of possible prodromal AD. This study aims to investigate whether the performance on the FCSRT would enhance the ability to predict conversion to AD in an aMCI group. A longitudinal study was conducted on 88 aMCI patients, and neuropsychological tests were analysed on the relative risk of conversion to AD. During follow-up (23.82 months), 33% of the aMCI population converted to AD. An impaired FCSRT TR was significantly associated with the risk of conversion to dementia, with a mean time to conversion of 25 months. The FCSRT demonstrates utility for detecting AD at its prodromal stage, thus supporting its use as a valid clinical marker.
A Haloalkane Dehalogenase from a Marine Microbial Consortium Possessing Exceptionally Broad Substrate Specificity

ABSTRACT The haloalkane dehalogenase enzyme DmmA was identified by marine metagenomic screening. Determination of its crystal structure revealed an unusually large active site compared to those of previously characterized haloalkane dehalogenases. Here we present a biochemical characterization of this interesting enzyme with emphasis on its structure-function relationships. DmmA exhibited an exceptionally broad substrate specificity and degraded several halogenated environmental pollutants that are resistant to other members of this enzyme family. In addition to having this unique substrate specificity, the enzyme was highly tolerant to organic cosolvents such as dimethyl sulfoxide, methanol, and acetone. Its broad substrate specificity, high overexpression yield (200 mg of protein per liter of cultivation medium; 50% of total protein), good tolerance to organic cosolvents, and a broad pH range make DmmA an attractive biocatalyst for various biotechnological applications. IMPORTANCE We present a thorough biochemical characterization of the haloalkane dehalogenase DmmA from a marine metagenome. This enzyme with an unusually large active site shows remarkably broad substrate specificity, high overexpression, significant tolerance to organic cosolvents, and activity under a broad range of pH conditions. DmmA is an attractive catalyst for sustainable biotechnology applications, e.g., biocatalysis, biosensing, and biodegradation of halogenated pollutants. We also report its ability to convert multiple halogenated compounds to corresponding polyalcohols.
Dynamics in an SIR Model when vaccination demand Follows Prior Levels of disease prevalence

This paper investigates an susceptible, infectious, recovered (SIR) model with childhood vaccination demand modeled as a function of prior levels of disease prevalence. Stability conditions for endemic and disease-free equilibria are uncovered, and both Hopf bifurcations and chaos are found with certain constellations of parameter values. Policy interventions directed toward increasing vaccination are explored, and the implied magnitudes of the external benefit of vaccination are modeled.
A Generalized Island Model Based on Parallel and Cooperating Metaheuristics for Effective Large Capacitated Vehicle Routing Problem Solving

Capacitated Vehicle Routing Problem (CVRP) is among transportation problems that are of the foremost concerns in logistics. Ensuring an effective product distribution over a large distribution network while reducing the required costs represents the scope of the present work. A synergic and interactive environment of parallel meta-heuristics is developed using a generalized island model to deal with large instances of CVRP. In the proposed model, cooperative meta-heuristics, namely genetic algorithms (GA) and ant colony optimization algorithms (ACO), are organized into archipelagoes. They communicate synchronously, globally and locally by exchanging solutions. In order to handle properly the migration of solutions, either between archipelagoes or between islands within the same archipelago, appropriate selection and replacement policies are adopted. Furthermore, the proposed approach uses other new features including a new binary solution representation and different optimization process (i.e GA, ACO) on each island. To prove the efficiency of the present work, tests over the well-known set of benchmarks, comparative studies and experimental analysis have been conducted.
Statistical Mechanics of thermalized ribbons and sheets

In this dissertation, we study the thermal behavior of two-dimensional sheets and ribbons. We study the effects of thermal fluctuations on the crumpling transition of elastic sheets. Existing two-dimensional sheets have a crumpling temperature which is very high and the crumpling transition has not been observed experimentally. We propose a mechanism using which one can tune this crumpling transition by changing the shape and geometry of the sheet. We perform extensive molecular dynamics simulations by perforating the sheet with a dense array of holes and find that the critical temperature is a function of the removed area. Lastly, we look at clamped thermalized ribbons and study thermalized Euler buckling. Again, we perform molecular dynamics simulations by clamping one end and allowing the other end to slide to get the projected thermal length of the ribbon. We compress this system and observe a distinct two-state dynamics of the center of mass along with thermalized Euler buckling. Statistical Mechanics of thermalized ribbons and sheets by Sourav Sanjukta Bhabesh B.Tech. Indian Institute of Technology Madras, 2010 MS Physics, Syracuse University, 2015 DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Physics Syracuse University August 2018 Copyright c © Sourav Sanjukta Bhabesh, August 2018
Estimate of the Functional Size in the Requirements Elicitation

Early measurement of software size allows to estimate costs and effort as well as to plan the development schedule. In previous reports, an approach which applies the Function Points Analysis to the derivative Scenarios of the Language Extended Lexicon was presented. In the process of the validation of that proposal, statistical techniques were applied on a subset of the obtained data from the measurement of several cases of study. In this article, a linear regression analysis which allowed establishing an estimate model of the scenarios functional size and the verification of the validity of that model is presented. The results are encouraging as for the feasibility of the model and its possible subsequent refinements.