Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure kNN Query Processing in Untrusted Cloud Environments

Now days a Wireless devices which having geo-positioning facility like GPS enable users to give information about their current location. Users are interested in querying in their physical location like restaurants, college, home, etc. Such data may be important due to their information. Furthermore, storing such relevent information regularly to the users tedious task, so the author of such information will make the data access only to paying users. The users are send their proper location as the query parameter, and wish to accept as result the nearest position, i.e., nearest-neighbors (NNs). But actual data owners do not have the technical knowledge to support processed query on a large data, so they outsource information storage and querying to a main dataset. Many such cloud providers exist offer powerful storage and computational structures at less cost. However, such a dataset providers are not completely trusted, and typically behave in an cusial fashion. Specifically they uses the some rules to answer queries perfectly, but they also collect the locations of the users and the subscribers for other uses. Giving this information of locations can lead to security breaches and financial losses to the data provider, for whom the dataset is an important source of revenue. The importance of user locations leads to privacy and may refer subscribers from using the service altogether. In this paper, we propose a set of ideas that allow NN queries in an unsecured outsourced structure, while at the same time provide security to both the location and querying users’ positions. Our ideas focuses on only secure order-preserving encryption method which is known to-date. We also provide performance measurements to reduce the processing cost inherent to processing on secured data, and we consider the problem of incrementally updating these datasets. We present an extensive performance measurement of our ideas to illustrate their use in practice.
IMPROVING COMPUTATIONAL EFFICIENCY OF PARTICLE SWARM OPTIMIZATION FOR OPTIMAL STRUCTURAL DESIGN

This paper attempts to improve the computational efficiency of the well known particle swarm optimization (PSO) algorithm for tackling discrete sizing optimization problems of steel frame structures. It is generally known that, in structural design optimization applications, PSO entails enormously time-consuming structural analyses to locate an optimum solution. Hence, in the present study it is attempted to lessen the computational effort of the algorithm, using the so called upper bound strategy (UBS), which is a recently proposed strategy for reducing the total number of structural analyses involved in the course of design optimization. In the UBS, the key issue is to identify those candidate solutions which have no chance to improve the search during the optimum design process. After identifying those non-improving solutions, they are directly excluded from the structural analysis stage, diminishing the total computational cost. The performance of the UBS integrated PSO algorithm (UPSO) is evaluated in discrete sizing optimization of a real scale steel frame to AISC-LRFD specifications. The numerical results demonstrate that the UPSO outperforms the original PSO algorithm in terms of the computational efficiency.
Opinion Mining Using Frequent Pattern Growth Method from Unstructured Text

In the last one decade, the area of opinion mining has experienced a major growth because of the increase in online unstructured data which are contributed by reviewers over different topics and subjects. These data sometimes become important for users who want to take their decision based on opinions of actual users of the product. In this paper, we present the FP-growth method for frequent pattern mining from review documents which act as a backbone for mining the opinion words along with their relevant features by experimental data over two different domains which are very different in their nature.
ALDH1A1 Maintains Ovarian Cancer Stem Cell-Like Properties by Altered Regulation of Cell Cycle Checkpoint and DNA Repair Network Signaling

Objective Aldehyde dehydrogenase (ALDH) expressing cells have been characterized as possessing stem cell-like properties. We evaluated ALDH+ ovarian cancer stem cell-like properties and their role in platinum resistance. Methods Isogenic ovarian cancer cell lines for platinum sensitivity (A2780) and platinum resistant (A2780/CP70) as well as ascites from ovarian cancer patients were analyzed for ALDH+ by flow cytometry to determine its association to platinum resistance, recurrence and survival. A stable shRNA knockdown model for ALDH1A1 was utilized to determine its effect on cancer stem cell-like properties, cell cycle checkpoints, and DNA repair mediators. Results ALDH status directly correlated to platinum resistance in primary ovarian cancer samples obtained from ascites. Patients with ALDHHIGH displayed significantly lower progression free survival than the patients with ALDHLOW cells (9 vs. 3 months, respectively p<0.01). ALDH1A1-knockdown significantly attenuated clonogenic potential, PARP-1 protein levels, and reversed inherent platinum resistance. ALDH1A1-knockdown resulted in dramatic decrease of KLF4 and p21 protein levels thereby leading to S and G2 phase accumulation of cells. Increases in S and G2 cells demonstrated increased expression of replication stress associated Fanconi Anemia DNA repair proteins (FANCD2, FANCJ) and replication checkpoint (pS317 Chk1) were affected. ALDH1A1-knockdown induced DNA damage, evidenced by robust induction of γ-H2AX and BAX mediated apoptosis, with significant increases in BRCA1 expression, suggesting ALDH1A1-dependent regulation of cell cycle checkpoints and DNA repair networks in ovarian cancer stem-like cells. Conclusion This data suggests that ovarian cancer cells expressing ALDH1A1 may maintain platinum resistance by altered regulation of cell cycle checkpoint and DNA repair network signaling.
Mid-IR emission of galaxies in the Virgo cluster and in the Coma supercluster IV. The nature of the dust heating sources

We study the relationship between the mid-IR (5-18 $\\mu$m) emission of late-type galaxies and various other star formation tracers in order to investigate the nature of the dust heating sources in this spectral domain. The analysis is carried out using a sample of 123 normal, late-type, nearby galaxies with available data at several frequencies. The mid-IR luminosity (normalized to the H-band luminosity) correlates better with the far-IR luminosity than with more direct tracers of the young stellar population such as the H$\\alpha$ and the UV luminosity. The comparison of resolved images reveals a remarkable similarity in the H$\\alpha$ and mid-IR morphologies, with prominent HII regions at both frequencies. The mid-IR images, however, show in addition a diffuse emission not associated with HII regions nor with the diffuse H$\\alpha$ emission. This evidence indicates that the stellar population responsible for the heating of dust emitting in the mid-IR is similar to that heating big grains emitting in the far-IR, including relatively evolved stars responsible for the non-ionizing radiation. The scatter in the mid-IR vs. H$\\alpha$, UV and far-IR luminosity relation is mostly due to metallicity effects, with metal-poor objects having a lower mid-IR emission per unit star formation rate than metal-rich galaxies. Our analysis indicates that the mid-IR luminosity is not an optimal star formation tracer in normal, late-type galaxies.
Clinical utility of positron emission tomography with 18F-fluorodeoxyglucose in detecting residual/recurrent squamous cell carcinoma of the head and neck.

PURPOSE The use of positron emission tomography with 18F-fluorodeoxyglucose (FDG-PET) to detect residual/recurrent squamous cell carcinoma of the head and neck has been tested only in small groups of patients. Our purpose, therefore, was to evaluate the ability of this technique to detect the presence of tumor at both primary and nodal sites in a large cohort of patients. METHODS All patients referred for PET scanning over a 2.5-year period with a question of residual or recurrent squamous cell carcinoma of the head and neck were identified. Thirty-five of 44 patients had sufficient follow-up to be meaningful to our analysis (range, 6-33 months). PET scans were interpreted visually with knowledge of the clinical history and correlative anatomic imaging findings. Detection of disease involving primary and nodal sites was assessed independently. Additionally, because each patient had been referred in an attempt to resolve a specific clinical problem, the usefulness of PET in accurately addressing these questions was assessed. RESULTS At the primary site, sensitivity and specificity for residual/recurrent disease were 100% and 64%, respectively; for nodal disease, sensitivity and specificity were 93% and 77%, respectively. In helping to resolve the clinical question being asked, the positive predictive value of the test result was 65% and the negative predictive value was 91%. CONCLUSION The high sensitivity and negative predictive value of PET scanning in our cohort of patients suggest an important role for this technique in the care of patients with suspected residual/recurrent head and neck carcinoma. The lower figures obtained for specificity and positive predictive value reflect the fact that increased FDG uptake may be due to either tumor or inflammation.
Preventing medical errors in point-of-care testing: security, validation, safeguards, and connectivity..

OBJECTIVES o prevent medical errors, improve user performance, and enhance the quality, safety, and connectivity (bidirectional communication) of point-of-care testing. PARTICIPANTS Group A included 37 multidisciplinary experts in point-of-care testing programs in critical care and other hospital disciplines. Group B included 175 professional point-of-care managers, specialists, clinicians, and researchers. The total number of participants equaled 212. EVIDENCE This study followed a systems approach. Expert specifications for prevention of medical errors were incorporated into the designs of security, validation, performance, and emergency systems. Additional safeguards need to be implemented through instrument software options and point-of-care coordinators. Connectivity will be facilitated by standards that eliminate deficiencies in instrument communication and device compatibility. Assessment of control features on handheld, portable, and transportable point-of-care instruments shows that current error reduction features lag behind needs. CONCENSUS PROCESS: Step 1: United States national survey and collation of group A expert requirements for security, validation, and performance. Step 2: Design of parallel systems for these functions. Step 3: Written critique and improvement of the error-prevention systems during 4 successive presentations to group B participants over 9 months until system designs stabilized into final consensus form. CONCLUSIONS The consensus process produced 6 conclusions for preventing medical errors in point-of-care testing: (1) adopt operator certification and validation in point-of-care testing programs; (2) implement security, validation, performance, and emergency systems on existing and new devices; (3) require flexible, user-defined error-prevention system options on instruments as a prerequisite to federal licensing of new diagnostic tests and devices; (4) integrate connectivity standards for bidirectional information exchange; (5) preserve fast therapeutic turnaround time of point-of-care test results; and (6) monitor invalid use, operator competence, quality compliance, and other performance improvement indices to reduce errors, thereby focusing on patient outcomes. (Arch Pathol Lab Med. 2001;1307-1315)
A new model for Online Social Networks case of Facebook

Modelling Online Social Networks (OSNs) can be very useful to study many concepts such as viral marketing, human behaviour or information propagation. Most existing studies on OSNs are based on models that are outdated and do not reflect the reality of the structure and characteristics of OSNs. In this paper, we present a new model that represents OSNs more accurately. Facebook being currently the most used Online Social Network in the world, we give its model as an example.
SPN OS: Managing network services with virtual network objects

This paper presents the design and implementation of a new controller platform, called the software-programmed networking (SPN) operating system (OS). SPN OS separates distributed control of virtual network services from the centralized management of network-wide resources. The key abstraction provided in SPN OS is a virtual network object (VNO), which encapsulates multiple layers of network stack as well as their associated resource constraints and service behaviors. VNOs are created by a VNO Arbiter, which handles provisioning of global network resources, but are managed independently by tenants through an intuitive object-oriented interface. This separation provides flexibility and scalable performance. We describe the design of SPN OS and VNOs, present a prototype implementation on top of the high-level language NetKAT, and discuss use cases.
Estimating the divergence point: a novel distributional analysis procedure for determining the onset of the influence of experimental variables

The divergence point analysis procedure is aimed at obtaining an estimate of the onset of the influence of an experimental variable on response latencies (e.g., fixation duration, reaction time). The procedure involves generating survival curves for two conditions, and using a bootstrapping technique to estimate the timing of the earliest discernible divergence between curves. In the present paper, several key extensions for this procedure were proposed and evaluated by conducting simulations and by reanalyzing data from previous studies. Our findings indicate that the modified versions of the procedure performed substantially better than the original procedure under conditions of low experimental power. Furthermore, unlike the original procedure, the modified procedures provided divergence point estimates for individual participants and permitted testing the significance of the difference between estimates across conditions. The advantages of the modified procedures are illustrated, the theoretical and methodological implications are discussed, and promising future directions are outlined.
Enumeration of three-dimensional convex polygonsMireille

A self-avoiding polygon (SAP) on a graph is an elementary cycle. Counting SAP on the hypercubic lattice ZZ d , with d 2, is a well-known unsolved problem, which is studied both for its combinatorial and probabilistic interest and its connections with statistical mechanics. Of course, polygons on ZZ d are deened up to a translation, and the relevant statistic is their perimeter. A SAP on ZZ d is said to be convex if its perimeter is`minimal', that is, is exactly twice the sum of the side lengths of the smallest hyper-rectangle containing it. In 1984, Delest and Viennot enumerated convex SAP on the square lattice, but no result was available in higher dimension. We present an elementary approach to enumerate convex SAP in any dimension. We rst obtain a new proof of Delest and Viennot's result, which explains combinatorially the form of the generating function. We then compute the generating function for convex SAP on the cubic lattice. In dimension larger than 3, the details of the calculations become very cumbersome. However, our method suggests that the generating function for convex SAP on ZZ d is always a quotient of diierentially nite power series.
Detecting cross site scripting vulnerabilities introduced by HTML5

Recent years, HTML5 is widely adopted in popular browsers. Unfortunately, as a new Web standard, HTML5 may expand the Cross Site Scripting (XSS) attack surface as well as improve the interactivity of the page. In this paper, we identified 14 XSS attack vectors related to HTML5 by a systematic analysis about new tags and attributes. Based on these vectors, a XSS test vector repository is constructed and a dynamic XSS vulnerability detection tool focusing on Webmail systems is implemented. By applying the tool to some popular Webmail systems, seven exploitable XSS vulnerabilities are found. The evaluation result shows that our tool can efficiently detect XSS vulnerabilities introduced by HTML5.
Contribution of murine innate serum inhibitors toward interference within influenza virus immune assays

Please cite this paper as: Cwach et al. (2011) Contribution of murine innate serum inhibitors toward interference within influenza virus immune assays. Influenza and Other Respiratory Viruses DOI: 10.1111/j.1750‐2659.2011. 00283.x.
Primed Polymorphonuclear Leukocytes, Oxidative Stress, and Inflammation Antecede Hypertension in the Sabra Rat

Hypertension is accompanied by systemic oxidative stress, inflammation, and priming of peripheral polymorphonuclear leukocytes (PMNLs), yet the involvement of these factors in the pathophysiology of hypertension is incompletely understood. We investigated the relationship between oxidative stress, primed PMNLs, and inflammation and the development of hypertension in the Sabra rat model of salt-sensitive hypertension. Sabra hypertension-resistant rats (SBN/y) (salt-resistant) and Sabra hypertension-prone rats (SBH/y) (salt-sensitive) were studied under normal conditions or during salt loading. Systolic blood pressure (BP) was measured by the tail-cuff method. The extent of oxidative stress was evaluated by the rate of superoxide release from PMNLs, plasma-reduced glutathione (GSH) levels, malondialdehyde (MDA) levels (estimated by thiobarbituric acid–reacting substances), and plasma-carbonylated fibrinogen (Western blotting). Plasma fibrinogen levels and the peripheral PMNL count served as indices of inflammation. In SBH/y and SBN/y provided regular chow without salt loading, BP did not rise above baseline values, yet superoxide release, plasma MDA, carbonylated fibrinogen, and PMNL count were higher in SBH/y than in SBN/y, whereas GSH levels were lower in SBH/y. Four weeks of salt loading resulted in a gradual increase in systolic BP in SBH/y to 205±3 mm Hg, whereas BP remained in SBN/y at baseline normotensive levels. All the parameters reflecting oxidative stress and inflammation were further aggravated with the development of hypertension in salt-loaded SBH/y. We conclude that primed PMNLs, oxidative stress, and inflammation antecede the development of hypertension in this experimental model of hypertension.
Metabolic control of diabetes is associated with an improved response of diabetic retinopathy to panretinal photocoagulation.

OBJECTIVE To study the influence of glycemic control and the presence of microalbuminuria on the initial response to panretinal photocoagulation (PRP) in patients with a high-risk proliferative diabetic retinopathy (PDR). RESEARCH DESIGN AND METHODS This was a prospective cohort study with a two-by-two factorial design. We used full-scattered PRP to treat 115 eyes of type 2 diabetic patients who have high-risk PDR. HbA1c (A1C) and albumin levels in 24-h urine were constantly monitored during the pre-enrollment, treatment, and posttreatment periods. At a follow-up visit 12 weeks after the last PRP session, the fundus was examined for characteristics of regression from high-risk PDR and the response to PRP was determined to be successful or unsuccessful. The eyes were categorized into four groups based on average A1C levels and the presence or absence of microalbuminuria. The data were analyzed using a logistic regression model. Our statistical analysis determined the probability of achieving a satisfactory response to PRP in association with A1C levels and the presence or absence of microalbuminuria. RESULTS Of the 115 eyes examined, 65 (56.5%) had a successful initial response to PRP and 50 (43.5%) did not. The probability of a satisfactory response to PRP was related to A1C levels (P < 0.05) but not to microalbuminuria and its interaction with hemoglobin glycosylation (P > or = 0.05). CONCLUSIONS Low levels of hemoglobin glycosylation (A1C <8%) during the pretreatment, treatment, and posttreatment periods are associated with a regression of proliferative diabetic retinopathy after PRP.
From DSM to 3D building models : a quantitative evaluation

The paper reviews the state-of-the-art in 3D city models and building block generation, with a description of the most common solutions and approaches. Then the digital reconstruction and comparison of LoD1 and LoD2 building models obtained with commercial packages and using different input data are presented. As input data, a DSM at 1m resolution derived from a GeoEye-1 stereo-pair, a DSM from an aerial block at 50 cm GSD and a LiDAR-based DSM at 1m resolution are used. The geometric buildings produced with each dataset are evaluated with respect to some ground-truth measurements but also compared between them. Problems such as the quality of the input DSM, the accuracy of the necessary vector datasets containing the building footprints, the flexibility of the approaches and the potentialities of each dataset will be discussed. As reconstruction of the building models is largely influenced by the quality of the building footprints, which may be out-of-date or slightly shifted with respect to the employed DSMs/DTMs, an in-house method is being developed to derive them starting from the produced DSMs.
Probabilistic Model Checking for Complex Cognitive Tasks - A case study in human-robot interaction

This paper proposes to use probabilistic model checking to synthesize optimal robot policies in multi-tasking autonomous systems that are subject to human-robot interaction. Given the convincing empirical evidence that human behavior can be related to reinforcement models, we take as input a well-studied Q-table model of the human behavior for flexible scenarios. We first describe an automated procedure to distill a Markov decision process (MDP) for the human in an arbitrary but fixed scenario. The distinctive issue is that -- in contrast to existing models -- under-specification of the human behavior is included. Probabilistic model checking is used to predict the human's behavior. Finally, the MDP model is extended with a robot model. Optimal robot policies are synthesized by analyzing the resulting two-player stochastic game. Experimental results with a prototypical implementation using PRISM show promising results.