Miracle-dz/UniFAR-FTUs huggingface dataset:
Hospital case-volume is associated with case-fatality after aneurysmal subarachnoid hemorrhage

Background Inverse association between hospital case-volume and case-fatality has been observed for various nonsurgical interventions and surgical procedures. Aims To study the impact of hospital case-volume on outcome after aneurysmal subarachnoid hemorrhage (aSAH). Methods We included aSAH patients who underwent aneurysm coiling or clipping from tertiary care medical centers across three continents using the Dr Foster Stroke GOAL database 2007–2014. Hospitals were categorized by annual case-volume (low volume: <41/year; intermediate: 41–70/year; high: >70/year). Primary outcome was 14-day in-hospital case-fatality. We calculated proportions, and used multiple logistic regression to adjust for age, sex, differences in comorbidity or disease severity, aneurysm treatment modality, and hospital. Results We included 8525 patients (2363 treated in low volume hospitals, 3563 treated in intermediate volume hospitals, and 2599 in high-volume hospitals). Crude 14-day case-fatality for hospitals with low case-volume was 10.4% (95% confidence interval (CI) 9.2–11.7%), for intermediate volume 7.0% (95% CI 6.2–7.9%; adjusted odds ratio (OR) 0.63 (95%CI 0.47–0.85)) and for high volume 5.4% (95% CI 4.6–6.3%; adjusted OR 0.50 (95% CI 0.33–0.74)). In patients with clipped aneurysms, adjusted OR for 14-day case-fatality was 0.46 (95% CI 0.30–0.71) for hospitals with intermediate case-volume and 0.42 (95% CI 0.25–0.72) with high case-volume. In patients with coiled aneurysms, adjusted OR was 0.77 (95% CI 0.55–1.07) for hospitals with intermediate case-volume and 0.56 (95% CI 0.36–0.87) with high case-volume. Conclusions Even within a subset of large, tertiary care centers, intermediate and high hospital case-volume is associated with lower case-fatality after aSAH regardless of treatment modality, supporting centralization to higher volume centers.
The Going to Stay at Home program: combining dementia caregiver training and residential respite care

ABSTRACT Background: Caring for persons with dementia is stressful for family caregivers. Caregiver training programs and respite care can reduce this stress and help maintain persons with dementia living longer in the community. We evaluated a program that combines caregiver training with a residential respite stay. Methods: In total, 90 dyads of persons with dementia and their caregivers, in groups of 3–6 dyads, volunteered to participate in a five-day residential training program and were followed-up 6 and 12 months later. The primary outcome was caregiver depression; secondary outcomes were measures of caregiver burden, unmet needs, person with dementia behavioral symptoms, and the quality of life and function. Results: Caregiver depression and burden were unchanged, despite decreasing function in persons with dementia. Caregivers’ unmet needs and behavioral symptoms in persons with dementia decreased significantly. Compared to a group of persons with dementia admitted for routine residential respite care, there was a marked reduction in permanent placement over 12 months. Conclusions: The Going to Stay at Home Program is a feasible and practicable model with benefits for caregivers and persons with dementia. It may lead to delay in institutionalization and may be applicable to other chronic conditions.
Prognostic role of the sialyltransferase ST6GAL1 in ovarian cancer

Aberrant sialylation of glycoproteins has been detected in many tumors, and upregulation of the beta-galactosamide alpha-2,6-sialyltransferase 1 (ST6GAL1) has been implicated with tumor aggressiveness and chemoresistance in experimental models. In our present study, we aimed to study the prognostic or predictive role of ST6GAL1 in ovarian carcinoma, using two independent ovarian cancer cohorts. ST6GAL1 mRNA levels were retrieved from a publicly available database (n = 517), and ST6GAL1 protein levels were analyzed by western blot analysis in a cohort of 204 ovarian tumor samples. The results were correlated with clinical and histological tumor parameters and follow-up information. High ST6GAL1 mRNA levels significantly correlated with lymphovascular invasion and shorter survival, whereas high ST6GAL1 protein expression was associated with advanced stage, distant metastasis and shorter recurrence-free intervals. In both cohorts the prognostic role was most pronounced in tumors without macroscopically visible residual tumor after surgery. In these cases, ST6GAL1 expression levels might help to identify cases with a higher risk of chemoresistance and metastatic relapse that might require an adapted therapeutic regime.
2 Sample Selection Models in R : Package sampleSelection

This introduction to the R package sampleSelection is a slightly modified version of Toomet and Henningsen (2008b), published in the Journal of Statistical Software. This paper describes the implementation of Heckman-type sample selection models in R. We discuss the sample selection problem as well as the Heckman solution to it, and argue that although modern econometrics has nonand semiparametric estimation methods in its toolbox, Heckman models are an integral part of the modern applied analysis and econometrics syllabus. We describe the implementation of these models in the package sampleSelection and illustrate the usage of the package on several simulation and real data examples. Our examples demonstrate the effect of exclusion restrictions, identification at infinity and misspecification. We argue that the package can be used both in applied research and teaching.
Holography and criticality in matchgate tensor networks

We explore tensor network models of holography through an efficiently contractible framework of matchgate tensors. The AdS/CFT correspondence conjectures a holographic duality between gravity in a bulk space and a critical quantum field theory on its boundary. Tensor networks have come to provide toy models to understand these bulk-boundary correspondences, shedding light on connections between geometry and entanglement. We introduce a versatile and efficient framework for studying tensor networks, extending previous tools for Gaussian matchgate tensors in 1 + 1 dimensions. Using regular bulk tilings, we show that the critical Ising theory can be realized on the boundary of both flat and hyperbolic bulk lattices, obtaining highly accurate critical data. Within our framework, we also produce translation-invariant critical states by an efficiently contractible tensor network with the geometry of the multiscale entanglement renormalization ansatz. Furthermore, we establish a link between holographic quantum error–correcting codes and tensor networks. This work is expected to stimulate a more comprehensive study of tensor network models capturing bulk-boundary correspondences.
Heat Transfer Characteristics of a Focused Surface Acoustic Wave ( F-SAW ) Device for Interfacial Droplet

In this study, we investigate the interfacial droplet jetting characteristics and thermal stability of a focused surface acoustic wave device (F-SAW). An F-SAW device capable of generating a 20 MHz surface acoustic wave by applying sufficient radio frequency power (2–19 W) on a 128◦-rotated YX-cut piezoelectric lithium niobate substrate for interfacial droplet jetting is proposed. The interfacial droplet jetting characteristics were visualized by a shadowgraph method using a high-speed camera, and a heat transfer experiment was conducted using K-type thermocouples. The interfacial droplet jetting characteristics (jet angle and height) were analyzed for two different cases by applying a single interdigital transducer and two opposite interdigital transducers. Surface temperature variations were analyzed with radio frequency input power increases to evaluate the thermal stability of the F-SAW device in air and water environments. We demonstrate that the maximum temperature increase of the F-SAW device in the water was 1/20 of that in the air, owing to the very high convective heat transfer coefficient of the water, resulting in prevention of the performance degradation of the focused acoustic wave device.
Purchase Intention of an Apartment : An Application of Theory of Planned Behavior ( TPB )

The objective of this study was to identify and analyze the factors affecting Theory of Planned Behavior (TPB) on the interest in buying an apartment in Bogor. This study employed online survey method in data collection. Structural Equation Model (SEM) method through Theory of Planned Behavior (TPB) approach as well as descriptive approach were utilized in data analysis. The data were obtained from 153 respondents categorized as having interest and ability to own an apartment in Bogor City. The results showed that there was a positive and significant effect on the interest of buying an apartment in Bogor City. Based on Theory of Planned Behavior (TPB), attitude and subjective norm variable had a significant effect on the purchase interest of an apartment, while perceived behavioral control variable had no significant effect on the purchase intention of an apartment.
Off-resonant emission of photon pairs in nonlinear optical cavities

Cavity-assisted spontaneous parametric down-conversion (SPDC) and spontaneous four-wave mixing (SFWM) in nonlinear optical materials are practical and versatile methods to generate narrowband time-energy entangled photon pairs. Time-energy entangled photons with tailored spectro-temporal properties are particularly useful for efficient quantum optical interfaces. In this work we study the generation of photon pairs in cavity-assisted SPDC and SFWM for the general case of off-resonant conversion, namely, when the frequencies of the generated photons do not match the cavity resonances. Such a frequency mismatch in particular depends on temperature and requires an additional control in the experiment. First, we propose a generic model, for description of cavity-assisted SPDC and SFWM. We show that in both processes the mismatch reduces the generation rate of photons, distorts the spectrum and the auto-correlation function of the generated fields, as well as affects the photon generation dynamics. Second, we verify the results experimentally using parametric generation of photon pairs in a nonlinear whispering gallery mode resonator (WGMR) as an experimental platform with controlled frequency mismatch. Our work reveals the role of the frequency mismatch in the photon generation process and shows a way to control it. Obtained results constitute one more step in the direction of full control over the spectro-temporal properties of entangled photon pairs and the heralded generation of single-photon pulses with a tailored temporal mode.
The Rewards and Costs of Stronger Passwords in a University: Linking Password Lifetime to Strength

We present an opportunistic study of the impact of a new password policy in a university with 100,000 staff and students. The goal of the IT staff who conceived the policy was to encourage stronger passwords by varying password lifetime according to password strength. Strength was measured through Shannon entropy (acknowledged to be a poor measure of password strength by the academic community, but still widely used in practice). When users change their password, a password meter informs them of the lifetime of their new password, which may vary from 100 days (50 bits of entropy) to 350 days (120 bits of entropy). We analysed data of nearly 200,000 password changes and 115,000 resets of passwords that were forgotten/expired over a period of 14 months. The new policy took over 100 days to gain traction, but after that, average entropy rose steadily. After another 12 months, the average password lifetime increased from 146 days (63 bits) to 170 days (70 bits). We also found that passwords with more than 300 days of lifetime are 4 times as likely to be reset as passwords of 100 days of lifetime. Users who reset their password more than once per year (27% of users) choose passwords with over 10 days fewer lifetime, and while they also respond to the policy, maintain this deficit. We conclude that linking password lifetime to strength at the point of password creation is a viable strategy for encouraging users to choose stronger passwords (at least when measured by Shannon entropy).
Duplicate ACK SYN ? Rate-limited ? Set Not Set Send Challenge ACK No RST ? RST ? Not Set Not Set SEQ match ?

In this study, we discover a subtle yet serious timing side channel that exists in all generations of half-duplex IEEE 802.11 or Wi-Fi technology. Previous TCP injection attacks stem from software vulnerabilities which can be easily eliminated via software update, but the side channel we report is rooted in the fundamental design of IEEE 802.11 protocols. This design flaw means it is impossible to eliminate the side channel without substantial changes to the specification. By studying the TCP stacks of modern operating systems and their potential interactions with the side channel, we can construct reliable and practical off-path TCP injection attacks against the latest versions of all three major operating systems (macOS, Windows, and Linux). Our attack only requires a device connected to the Internet via a wireless router, and be reachable from an attack server (e.g., indirectly so by accessing to a malicious website). Among possible attacks scenarios, such as inferring the presence of connections and counting exchanged bytes, we demonstrate a particular threat where an off-path attacker can poison the web cache of an unsuspecting user within minutes (as fast as 30 seconds) under realistic network conditions.
Bi Objective Optimization for Bug Triage

Open Source Software development is self-organizing and dynamic in nature. Software maintenance is subject to error, cost and time overruns. Issue tracking is the major component of software maintenance. The bug triager, is an individual who chooses what to do with an approaching bug report and to whom to prescribe the bug. The number of bug reports submitted day by day increases. The physical prescribing work becomes troublesome and fault prone. The bug prescribed to a developer may get tossed to another developer. The Bug Tossing Graph codifies the tossing relation that exists among the developers. Automated support is needed to find the optimal set of developers who can address the bug. The existing techniques that work on Bug Toss Graph relies on the Weight based Breadth First Search (WBFS) Algorithm. This technique tries to reduce the number of hops between the first assignee of the bug to the final developer, but ignores the transition probability information present in the edges. To this end, this paper presents a technique based on Bi-objective Optimization that maximizes transition probability and minimizes the number of hops. In order to validate the proposed technique experiments were conducted using the bug dataset of Eclipse project. The various parameters including (i) Precision, (ii) Recall and (ii) Mean Steps to Resolve (MSTR) are considered. The results indicate that the proposed technique is better than the existing techniques.
Understanding Spatial and Temporal Gait Asymmetries in Individuals Post Stroke

Gait asymmetry in spatial and temporal parameters and its impacts on functional activities have always raised many interesting questions in research and rehabilitation. The aim of this topical review is threefold: 1) to examine different equations of asymmetry of gait parameters and make recommendations for standardization, 2) to deepen the understanding of the relationships between sensorimotor deficits, spatiotemporal (step length, swing time and double support time) and biomechanical (kinematic, kinetic, muscular activity) parameter asymmetries during gait and, 3) to summarize the impacts of gait asymmetry on walking speed, falls, and energy cost in individuals post stroke. In light of current literature, we recommend quantifying spatiotemporal asymmetries by calculating symmetry ratios. However, for other gait parameters (such as kinetic or kinematic data), the choice will depend on the variability of the data and the objective of the study. Regardless of the selected asymmetry equation, we recommend presenting the asymmetry values in combination with the mean value of each side to facilitate comparisons between studies. This review also revealed that sensorimotor deficits clinically measured are not sufficient to explain the large variability of spatiotemporal asymmetries (particularly for step length and double support time) in individuals post stroke. Biomechanical analysis has been identified as a relevant approach to understanding gait deviations. Studies that linked biomechanical impairments to spatiotemporal asymmetries suggest that a balance issue and an impaired paretic forward propulsion could be among the important factors underlying spatiotemporal asymmetries. In our opinion, this paper provides meaningful information to aid in better understanding gait deviations in persons after stroke and establishes the need for future studies regrouping individuals post stroke according to their spatiotemporal asymmetries. Furthermore, further studies targeting efficacy of locomotor rehabilitation and the impacts of gait asymmetry on risk of falls and energy expenditure are needed.
Addressing the need to capture scenarios, intentions and preferences: interactive intentional programming in the smart home

The Internet of Things (IoT) and connected products have become part of the advance of ubiquitous technology into personal and professional living spaces, such as the smart home. What connectivity and distributed computing have made possible, is still programmed only according to more or less simplified rule systems (or in traditional code); the mapping between what end users intend or would value and what can be expressed in rules is not straightforward. This article analyzes the temporal, preferential, technical, and social complexity of mapping end-user intent to rules, and it suggests new concepts to better frame information that needs to be captured to create smart-home systems that better match users’ intents. We need a new approach aimed at first capturing end users’ intentions and potential usage scenarios, then providing this information to a control system that learns to resolve intentions and scenarios for available devices in the context. The new approach should deconstruct and rebuild IoT-related programming at a higher level of abstraction that allows end users to express long-term intentions and short-term preferences, instead of programming rules. Based on related work, a first-person perspective and analysis of current smart-home programming practices, the concept of Interactive Intentional Programming (IIP), is introduced and discussed.
TorontoCL at the CLEF 2018 eHealth Challenge Task 1

We assign ICD-10 codes to cause-of-death phrases in multiple languages by creating rich and relevant word embedding models. We train 100-dimensional word embeddings on the training data provided, combined with language-specific Wikipedia corpora. We then use n-gram matching of the raw text to the provided ICD dictionary followed by an ensemble model which includes predictions from a CNN classifier and a GRU encoder-decoder model.
Matrix metalloproteinases in impaired wound healing

Cutaneous wound healing is a complex tissue response that requires a coordinated interplay of multiple cells in orchestrated biological processes to finally re-establish the skin's barrier function upon injury. Proteolytic enzymes and in particular matrix metalloproteinases (MMPs) contribute to all phases of the healing process by regulating immune cell influx, facili - tating migration of fibroblasts and keratinocytes, and remodeling of the scar tissue. As a result of these pleiotropic functions in the healing skin wound, uncontrolled activities of MMPs are associated with impaired wound healing, a growing health problem in Western countries due to increased life expectancies and rising rates of underlying diseases, such as diabetes. However, detailed mechanisms have been only partially unraveled, and new diagnostic tools and more targeted therapies are urgently needed. In this review, we discuss the roles of MMPs in acute and chronic wound healing and summarize current therapeutic approaches aiming at inhibiting aberrant MMP activities in healing disorders.
An Efficient Cloud Storage Batch Auditing without Key Exposure Resistance using Public Verifier

: Cloud Computing is a paradigm which provides services over network. In Cloud computing, data is usually audited by an external auditor in public cloud. Naive solution and slightly better solution are the two methods that authenticates client with key. Using build in key, previously stored data can be verified but the problems due to key exposure are not addressed. In proposed system, Cloud storage auditing is done without key exposure. Public Aware data sharing Public Verifier (PAPV) algorithm is employed to private users before exposing data. In addition to this,Batch system is allocated to organize time period independently which is an abstraction to the tenant’ s secret key in public cloud. Further, block verification is developed to support data security. By implementing this, the high end secure data can be obtained to any user who stores and manipulates data in cloud. Hereby, the proof analysis developed reveal that our proposed is efficient to tenants in public cloud
Improving Association Rule based Data Mining Algorithms with Agents Technology in Distributed Environment

Applying distribution in the form of agents technology and improving association rule based data mining algorithms, agents are the best for doing the continuous data mining efficiently reducing network load and carrying the code to remote locations and the types of mobile agent which having the energy of moving from one place to another itself ,and interacting with the other mining agents for the purpose of data mining as component based communication, so working with communication agents for improvement of apriori algorithm for quality. By proposing architecture for improvement of apriori mining in distributed environment, this architecture can facilitate the services of instantaneous real time messaging; this study includes the issue of constantly executing queries on continuous data in heterogeneous platforms or environments.
Heat capacity of a thermally squeezed optomechanical oscillator at strong coupling

Coherent quantum oscillators are basic physical system both in quantum statistical physics and quantum thermodynamics. We discuss and compare two thermodynamic coefficients (generalized heat capacities) characterizing optomechanical oscillator strongly coupled to a thermal bath. The coupling is strong enough for the observed oscillator energy levels to be dependent on bath temperature. The capacities are related to two different experiments. One measurement is a differential scanning calorimetry, the second probes the second statistical moment of the oscillator position. As we analyze, the strong coupling allows both localization and purification of the oscillator induced by increasing the bath temperature. The capacities can be negative and can witness certain types of the energy-levels temperature dependence. Our findings are stimulating for current development of optomechanical and thermomechanical experiments.
Population Structuring of Land and Coastal Ducks ( Anas platyrhynchos ) Using Microsatellite Markers

Twenty-four polymorphic and ubiquitously distributed microsatellite loci were utilized to genotype four populations of indigenous Mallard ducks in India using Khaki campbell as an out-group. The data was used to establish population parameters and genetic relationship among the populations. All the selected loci exhibited high polymorphic information content and gene diversity. F -statistics revealed population structure in four indigenous duck populations. There was not much differentiation among the duck populations along coastline, while land birds were found to be distinct from coastline ducks. The data presented here will be useful for undertaking duck improvement programmes in future.