Miracle-dz/UniFAR-FTUs huggingface dataset:
Colchicine protects rat skeletal muscle from ischemia/reperfusion injury by suppressing oxidative stress and inflammation

Objective(s): Neutrophils play an important role in ischemia/reperfusion (IR) induced skeletal muscle injury. Microtubules are required for neutrophil activation in response to various stimuli. This study aimed to investigate the effects of colchicine, a microtubule-disrupting agent, on skeletal muscle IR injury in a rat hindlimb ischemia model. Materials and Methods: Twenty-one Sprague-Dawley rats were randomly allocated into three groups IR group, colchicine treated-IR (CO) group and sham operation (SM) group. Rats of both the IR and CO groups were subjected to 3 hr of ischemia by clamping the right femoral artery followed by 2 hr of reperfusion. Colchicine (1 mg/kg) was administrated intraperitoneally prior to hindlimb ischemia in the CO group. After 2 hr of reperfusion, we measured superoxide dismutase (SOD) and myeloperoxidase (MPO) activities, and malondialdehyde (MDA), tumor necrosis factor (TNF)-α and interleukin (IL)-1β levels in the muscle samples. Plasma creatinine kinase (CK) and lactate dehydrogenase (LDH) levels were measured. We also evaluated the histological damage score and wet/dry weight (W/D) ratio. Results: The histological damage score, W/D ratio, MPO activity, MDA, TNF-α and IL-1β levels in muscle tissues were significantly increased, SOD activity was decreased, and plasma CK and LDH levels were remarkably elevated in both the IR and CO groups compared to the SM group (P<0.05). Colchicine treatment significantly reduced muscle damage and edema, oxidative stress and levels of the inflammatory parameters in the CO group compared to the IR group (P<0.05). Conclusion: Colchicine attenuates IR-induced skeletal muscle injury in rats.
PHYSICAL BROWSING

Physical browsing is a user interaction paradigm for associating physical objects with digital information in an ambient intelligence setting. In this paper, I look at existing work in the area and review the research we have carried out at VTT Technical Research Centre of Finland. Our research evolves from designing ambient intelligence scenarios with physical browsing as one of the basic user interaction patterns. We have defined physical selection methods for pointing, touching and scanning and built a prototype system for studying the user interaction. Last I describe my approach to a further study of physical browsing.
A new APE1/Ref-1-dependent pathway leading to reduction of NF-κB and AP-1, and activation of their DNA-binding activity

APE1/Ref-1 is thought to be a multifunctional protein involved in reduction-oxidation (redox) regulation and base excision DNA repair, and is required for early embryonic development in mice. APE1/Ref-1 has redox activity and AP endonuclease activity, and is able to enhance DNA-binding activity of several transcription factors, including NF-kappaB, AP-1 and p53, through reduction of their critical cysteine residues. However, it remains elusive exactly how APE1/Ref-1 carries out its essential functions in vivo. Here, we show that APE1/Ref-1 not only reduces target transcription factors directly but also facilitates their reduction by other reducing molecules such as glutathione or thioredoxin. The new activity of APE1/Ref-1, termed redox chaperone activity, is exerted at concentration significantly lower than that required for its redox activity and is neither dependent on its redox activity nor on its AP endonuclease activity. We also show evidence that redox chaperone activity of APE1/Ref-1 is critical to NF-kappaB-mediated gene expression in human cells and is mediated through its physical association with target transcription factors. Thus, APE1/Ref-1 may play multiple roles in an antioxidative stress response pathway through its different biochemical activities. These findings also provide new insight into the mechanism of intracellular redox regulation.
AN EVALUATION O F SUBJECTIVE POVERTY DEFINITIONS: COMPARING RESULTS FROM THE U.S. AND THE NETHERLANDS

In this paper, results of applying the subjective definition of poverty, introduced by Goedhart et al. (1977), in the U S . and the Netherlands are compared. This definition focuses on the monetary amounts which people consider necessary to make ends meet for their households as provided in response to the Minimum Income Question (MIQ). National data from both countries in the early 1980s are analyzed. In regressions of reported minimum income, corrections are made for the omission of income components and selective non-response. For the first time the relationship between fixed expenditures and the MIQ is examined. Factors significantly related to reported minimum income include household income, household composition, age, education, sex, region, fixed expenditures, and whether the household experienced recent income changes. The income elasticity appears to be smaller in the U S . than in the Netherlands, while the effects of other socioeconomic factors are greater. On average, the resulting subjective income thresholds are above official poverty lines, but more so in the U S . than in the Nerherlands. Whether thresholds based on answers to MIQs should be regarded as poverty lines remains open to question.
Handling constraints as objectives in a multiobjective genetic based algorithm

In this paper, a novel approach based on handling constraints as objectives together with a modified Parks & Miller elitist technique, to solve constrained multiobjective optimization problems, is analyzed with Niched Pareto Genetic Algorithm. The performance of this approach is compared with the classical procedure of handling constraints that is the exterior penalty function method. Results are obtained applying both procedures of handling constraints, with and without elitism. Especially when using the modified elitist technique, simulation results suggest the effectiveness of the proposed technique.
Towards modular instrumentation of interpreters in JavaScript

With an initial motivation based on the security of web applications written in JavaScript, we consider the instrumentation of an interpreter for a dynamic analysis as a crosscutting concern. We define the instrumentation problem — an extension to the expression problem with a focus on modifying interpreters. We then illustrate how we can instrument an interpreter for a simple language using only the bare language features provided by JavaScript.
Identity based hybrid signcryption revisited

Signcryption is a cryptographic primitive which combines both the functions of digital signature and public key encryption logically in single step, and with a computational cost significantly less than required by the traditional signature-then-encryption approach. Identity based cryptosystem is a public key cryptosystem in which public key can be any arbitrary string. Hybrid cryptosystem combines the convenience of a public key cryptosystem with the efficiency of a symmetric cryptosystem. Dent [4] has given security models for hybrid signcryption scheme with insider security. He has given two security models for hybrid signcryption KEM: key indistinguishability and message indistinguishability model. Hybrid signcryption in identity base setting was given by Fagen Li et al. [10]. In this paper [10] only one security model key indistinguishability is considered. Our contribution in this paper is three fold: First we give new proof for IDB hybrid signcryption in Dent [4] security model. Second for the confidentiality of hybrid signcryption, we improve the bound as compared to Dent [4]. Third we also give the example of identity based hybrid signcryption based on [11].
POTSHARDS—a secure, recoverable, long-term archival storage system

Users are storing ever-increasing amounts of information digitally, driven by many factors including government regulations and the public's desire to digitally record their personal histories. Unfortunately, many of the security mechanisms that modern systems rely upon, such as encryption, are poorly suited for storing data for indefinitely long periods of time; it is very difficult to manage keys and update cryptosystems to provide secrecy through encryption over periods of decades. Worse, an adversary who can compromise an archive need only wait for cryptanalysis techniques to catch up to the encryption algorithm used at the time of the compromise in order to obtain “secure” data. To address these concerns, we have developed POTSHARDS, an archival storage system that provides long-term security for data with very long lifetimes without using encryption. Secrecy is achieved by using unconditionally secure secret splitting and spreading the resulting shares across separately managed archives. Providing availability and data recovery in such a system can be difficult; thus, we use a new technique, approximate pointers, in conjunction with secure distributed RAID techniques to provide availability and reliability across independent archives. To validate our design, we developed a prototype POTSHARDS implementation. In addition to providing us with an experimental testbed, this prototype helped us to understand the design issues that must be addressed in order to maximize security.
Uncertainty relationships in many-body systems

Rigorous relationships among radial and logarithmic expectation values of an N- body system are obtained by means of information-theoretic methods. Especially interesting are the uncertainty expressions in terms of the product (r")'/n(pB)'/p, which generalize the well known relation (r2)(p2) 2 9N2/4. Additionally, an inequality involving the uncertainty in the logarithmic radius and the logarithmic momentum is shown. For illustration the aocmcy of the inequalities found are numerically analysed in a HameeFock framework for atomic systems. Finally, it is pointed out how these inequalities are improved in atoms by raking into account other physical quantities or by considering some semiempirical results on atomic information entropies. The one-particle density p(r) is a fundamental quantity in the study of the physical and chemical properties of many-fermion systems parr and Yang 1989). Since Hohenberg and Kohn (1964) formulated their theorem about the existence of a universal functional E(pl for the energy of the many-fermion system, much effort has been paid in the study of the function p(~).
Towards evasive maneuvers with quadrotors using dynamic vision sensors

We present a method to predict collisions with objects thrown at a quadrotor using a pair of dynamic vision sensors (DVS). Due to the micro-second temporal resolution of these sensors and the sparsity of their output, the object's trajectory can be estimated with minimal latency. Unlike standard cameras that send frames at a fixed frame rate, a DVS only transmits pixel-level brightness changes (“events”) at the time they occur. Our method tracks spherical objects on the image plane using probabilistic trackers that are updated with each incoming event. The object's trajectory is estimated using an Extended Kalman Filter with a mixed state space that allows incorporation of both the object's dynamics and the measurement noise in the image plane. Using error-propagation techniques, we predict a collision if the 3σ-ellipsoid along the predicted trajectory intersects with a safety sphere around the quadrotor. We experimentally demonstrate that our method allows initiating evasive maneuvers early enough to avoid collisions.
Lifetime-improved Collection Tree Protocol for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are generally deployed in remote sites in order to sense the environment and acquire a set of data useful for analysis, monitoring and optimization algorithms. The use of the WSNs in remote and rugged areas, where battery replacement is not practical, requires extending the network lifetime. The proposed solution in this work, is using low-power Raspberry Pi platform alongside TinyOS operating system. This platform utilizes the novel Lifetime Improved CTP (LICTP), an enhanced version of the Collection Tree Protocol (CTP) presented in this work. The LICTP's performance is analyzed and studied by various simulations using different numbers of MEMSIC IRIS motes. Further, simulation results are verified by an experiment using a network composed of 25 IRIS motes. A demonstration of the LICTP lifetime improvement is presented and evaluated. The proposed WSN improvements achieved a significant enhancement in lifetime duration. For the implemented case-study, the lifetime improvement with LICTP utilization is by a factor of 2.
Building Web-Base SIP Analyzer with Ajax Approach

Web applications are generally less interactive than desktop applications. Due to the simple request-response model between Web browsers and Web servers, users usually experience frequent waiting during a session whenever the Web applications need to get data from the server. After a browser sends out a request and await the response to return from the server, no further requests can be taken during this waiting time. In this paper we propose integrating the Ajax approach to the design of a Web-base analyzer for session initiation protocol (SIP), which is a popular protocol in IP telephony industry. By getting data asynchronously from the server, this Web-base analyzer can monitor the SIP messages on the server in real-time without reloading.
DeepSketch2Image: Deep Convolutional Neural Networks for Partial Sketch Recognition and Image Retrieval

Freehand sketches are an interesting universal form of visual representation. Sketching has become easily accessible with many of the devices that we use on a daily basis. In this paper, we propose a system for real-time sketch recognition and similarity search. Our system is able to recognize partial sketches from 250 object categories. It is then able to retrieve similar sketches but also images/photographs. In this work, we propose to use deep convolutional neural networks (ConvNets) for partial sketch recognition and feature extraction. Features are extracted from sketches and image contours in order to be used as a basis for similarity search using k-Nearest Neighbors (kNN). Our system demonstrates promising results in identifying similar images, and could be integrated in larger content-based search engines.
MRMAC: Medium Reservation MAC Protocol for Reducing End-to-End Delay and Energy Consumption in Wireless Sensor Networks

This letter proposes a novel medium reservation MAC protocol that reduces both end-to-end delay and energy consumption for wireless sensor networks. MRMAC reduces end-to-end delay by informing the intended receiver of NPAT (next packet arrival time) and MRI (medium reservation information) to reserve the medium in advance. Through this medium reservation phase, following packets can be delivered with reduced delay in multihop streaming phase. A simulation shows that the result of the proposed protocol outperforms previous works.
Multiple Moving Object Detection for Fast Video Content Description in Compressed Domain

Indexing deals with the automatic extraction of information with the objective of automatically describing and organizing the content. Thinking of a video stream, different types of information can be considered semantically important. Since we can assume that the most relevant one is linked to the presence of moving foreground objects, their number, their shape, and their appearance can constitute a good mean for content description. For this reason, we propose to combine both motion information and region-based color segmentation to extract moving objects from an MPEG2 compressed video stream starting only considering low-resolution data. This approach, which we refer to as "rough indexing," consists in processing P-frame motion information first, and then in performing I-frame color segmentation. Next, since many details can be lost due to the low-resolution data, to improve the object detection results, a novel spatiotemporal filtering has been developed which is constituted by a quadric surface modeling the object trace along time. This method enables to effectively correct possible former detection errors without heavily increasing the computational effort.
External Memory Data Structures for 3 and 4-Sided Queries

In this paper, we experimentally evaluate the relative performance of 3 external memory query structures. The R and Priority R (PR) Trees are compared using 4-sided rectangle queries in R. For 3-sided point queries in R, we compare the two structures mentioned above to the External Priority Search (EPS) Tree. While the PR and EPS Trees possess optimal I/O bounds, they are largely theoretical works. The R-tree, on the other hand, is a simpler heuristic data structure that is commonly used in practise but is inefficient in the worst case. After comparing wall times and I/O efficiency of queries, updates and bulk loads of the three structures on a variety of simulated and real data, we find the R-Tree variants to generally outperform the EPS and PR trees in R. In higher dimensions, however, the PR-Tree is most efficient.
On-the-Fly Verification of Erasure-Encoded File Transfers (Extended Abstract)

The quality of peer-to-peer content distribution can suffer from the malicious behavior of participants that corrupt or mislabel content. While systems using simple block-byblock downloading can verify blocks using traditional cryptographic signatures, these same techniques may not be applied to more elegant systems that rely on erasure codes for efficient multi-source download. This paper presents a practical scheme, based on homomorphic hashing, that enables a downloader to perform on-the-fly verification of erasureencoded blocks.
Bayesian optimisation of Gaussian processes for identifying the deteriorating patient

Patient deterioration in the hospital ward is typically preceded by several hours of deranged physiology, as measured by the patient's vital signs. Estimation of the expected trajectory of a patient's future vital signs can allow us determine the degree of risk of physiological deterioration for that patient. Gaussian processes (GPs) offer a principled means of estimating vital-sign trajectories within a probabilistic framework. The automated estimation of GP parameters in this setting is difficult, due to the (often substantial) variation in physiology between patients, and also due to any changes in physiology that may occur for individual patients. Population-based techniques for fitting models to patient vital-sign data may be inferior compared with patient-specific approaches. We here propose the use of Bayesian optimisation to learn patient-specific models that are effective for estimating future physiological data, based on previously-observed data for the individual patient. We show how patient-specific values of GP hyperparameters may be learned using Bayesian optimisation, based on data observed during the first day of a patient's stay on an acute ward. We then demonstrate the benefit of using such methods in terms of forecasting accuracy for monitoring the patient during their subsequent two days on the ward.
Intrusion detection technique by using k-means, fuzzy neural network and SVM classifiers

With the impending era of internet, the network security has become the key foundation for lot of financial and business web applications. Intrusion detection is one of the looms to resolve the problem of network security. Imperfectness of intrusion detection systems (IDS) has given an opportunity for data mining to make several important contributions to the field of intrusion detection. In recent years, many researchers are using data mining techniques for building IDS. Here, we propose a new approach by utilizing data mining techniques such as neuro-fuzzy and radial basis support vector machine (SVM) for helping IDS to attain higher detection rate. The proposed technique has four major steps: primarily, k-means clustering is used to generate different training subsets. Then, based on the obtained training subsets, different neuro-fuzzy models are trained. Subsequently, a vector for SVM classification is formed and in the end, classification using radial SVM is performed to detect intrusion has happened or not. To illustrate the applicability and capability of the new approach, the results of experiments on KDD CUP 1999 dataset is demonstrated. Experimental results shows that our proposed new approach do better than BPNN, multiclass SVM and other well-known methods such as decision trees and Columbia model in terms of sensitivity, specificity and in particular detection accuracy.
Analysing the effectiveness of COMA++ on the mapping between Traditional Malay Textile (TMT) knowledge model and CIDOC CRM

The existence of state-of-the art mapping tools facilitate in finding correspondences between ontology entities. COMA++ among others is a tool that accommodates both schemas and ontologies matching with additional enhancements and provides a platform to evaluate different match algorithms. COMA++ is asserted to be a useful support tool due to its availability online, capability to integrate large variety of similarity algorithms and feasibility for complex metadata management problems. Thus, COMA++ is chosen in this study based on the input type, output type, interaction and availability. The findings show that COMA++ is an effective tool in finding similarity between schemas in terms of element and structural aspects with its single hybrid matchers and combination matchers. However, there are several limitations identified during the experiments that drive this study for further enhancement to be carried out in the future to test its true potential.
Predictors and outcomes of limited resection for early-stage non-small cell lung cancer.

BACKGROUND Lobectomy is considered the standard treatment for early-stage non-small cell lung cancer (NSCLC); however, more limited resections are commonly performed. We examined patient and surgeon factors associated with limited resection and compared postoperative and long-term outcomes between sublobar and lobar resections. METHODS A population- and health system-based sample of patients newly diagnosed with stage I or II NSCLC between 2003 and 2005 in five geographically defined regions, five integrated health-care delivery systems, and 15 Veterans Affairs hospitals was observed for a median of 55 months, through May 31, 2010. Predictors of limited resection and postoperative outcomes were compared using unadjusted and propensity score-weighted analyses. All P values are from two-sided tests. RESULTS One hundred fifty-five (23%) patients underwent limited resection and 524 (77%) underwent lobectomy. In adjusted analyses of patient-specific factors, smaller tumor size (P = .004), coverage by Medicare or Medicaid, no insurance or unknown insurance (P = .02), more severe lung disease (P < .001), and a history of stroke (P = .049) were associated with receipt of limited resection. In adjusted analyses of surgeon characteristics, thoracic surgery specialty (P = .02), non-fee-for-service compensation (P = .008), and National Cancer Institute cancer center designation (P = .006) were associated with higher odds of limited resection. Unadjusted 30-day mortality was higher with limited resection than with lobectomy (7.1% vs 1.9%, difference = 5.2%, 95% confidence interval [CI] = 1.5% to 10.8%, P = .003), and the adjusted difference was not statistically significant (6.5% vs 2.9%, difference = 3.6%, 95% CI = -.1% to 9.2%, P = .09). Postoperative complications did not differ by type of surgery (all P > .05). Over the course of the study, a non-statistically significant trend toward improved long-term survival was evident for lobectomy, compared with limited resection, in adjusted analyses (hazard ratio of death = 1.35 for limited resection, 95% CI = 0.99 to 1.84, P = .05). CONCLUSIONS Evidence is statistically inconclusive but suggestive that lobectomy, compared with limited resection, is associated with increased long-term survival for early-stage lung cancer. Clinical, socioeconomic, and surgeon factors appear to be associated with the choice of surgical resection.