Miracle-dz/UniFAR-FTUs huggingface dataset:
Inter-domain Communication Protocol for Real-time File Access Monitor of Virtual Machine

Leveraging hypervisor for security purpose such as malware analysis has been well researched. There still remain two challenges for analyzing security incidents on virtual machine: real-time monitoring and semantic gap. First, current active monitoring methods need to be improved for real-time protection of virtual machine. Second, semantic gap between virtual machine and hypervisor poses a significant impediment on security analyst. In this paper, we propose an inter-domain communication protocol for real-time monitoring of virtual machine and bridging semantic gap. We have deployed the inter-domain communication module between a guest Windows OS and a hypervisor in two ways. While the one is a register based transfer using vCPU context, the other is a shared memory based communication. Our protocol is event driven, which makes the proposed system enable to monitor the file access of a guest Windows OS in real-time without suspending it. We have implemented our system on XEN virtual machine monitor and KVM (Kernel Virtual Machine). We have measured the resource utilization of these two systems in the case of decompressing files and receiving HTTP requests. On the guest OS, the KVM based system outperforms the processor idle time by about 30-50% in decompressing file and the memory usage by about 35% in receiving HTTP requests. We conclude that our system can monitor file access inside virtual machine without suspension and also with reasonable resource usage.
HEDGING STRATEGIES AND MINIMAL VARIANCE PORTFOLIOS FOR EUROPEAN AND EXOTIC OPTIONS IN A LÉVY MARKET

This paper presents hedging strategies for European and exotic options in a Lévy market. By applying Taylor’s theorem, dynamic hedging portfolios are constructed under different market assumptions, such as the existence of power jump assets or moment swaps. In the case of European options or baskets of European options, static hedging is implemented. It is shown that perfect hedging can be achieved. Delta and gamma hedging strategies are extended to higher moment hedging by investing in other traded derivatives depending on the same underlying asset. This development is of practical importance as such other derivatives might be readily available. Moment swaps or power jump assets are not typically liquidly traded. It is shown how minimal variance portfolios can be used to hedge the higher order terms in a Taylor expansion of the pricing function, investing only in a risk‐free bank account, the underlying asset, and potentially variance swaps. The numerical algorithms and performance of the hedging strategies are presented, showing the practical utility of the derived results.
Human olfactory consciousness and cognition: its unusual features may not result from unusual functions but from limited neocortical processing resources

Human and animal olfactory perception is shaped both by functional demands and by various environmental constraints seemingly peculiar to chemical stimuli. These demands and constraints may have generated a sensory system that is cognitively distinct from the major senses. In this article we identify these various functional demands and constraints, and examine whether they can be used to account for olfaction's unique cognitive features on a case-by-case basis. We then use this as grounds to argue that specific conscious processes do have functional value, a finding that naturally emerges when a comparative approach to consciousness across the senses is adopted. More generally, we conclude that certain peculiar features of olfactory cognition may owe more to limited neocortical processing resources, than they do to the challenges faced by perceiving chemical stimuli.
Automatic Calibration of Multiple Coplanar Sensors

This paper describes an algorithm for recovering the rigid 3-DOF transformation (offset and rotation) between pairs of sensors mounted rigidly in a common plane on a mobile robot. The algorithm requires only a set of sensor observations made as the robot moves along a suitable path. Our method does not require synchronized sensors; nor does it require complete metrical reconstruction of the environment or the sensor path. We show that incremental pose measurements alone are sufficient to recover sensor calibration through nonlinear least squares estimation. We use the Fisher Information Matrix to compute a Cramer-Rao lower bound (CRLB) for the resulting calibration. Applying the algorithm in practice requires a non-degenerate motion path, a principled procedure for estimating per-sensor pose displacements and their covariances, a way to temporally resample asynchronous sensor data, and a way to assess the quality of the recovered calibration. We give constructive methods for each step. We demonstrate and validate the end-to-end calibration procedure for both simulated and real LIDAR and inertial data, achieving CRLBs, and corresponding calibrations, accurate to millimeters and milliradians. Source code is available from http://rvsn.csail. mit.edu/calibration.
GUCY2C lysosomotropic endocytosis delivers immunotoxin therapy to metastatic colorectal cancer

The emergence of targeted cancer therapy has been limited by the paucity of determinants which are tumor-specific and generally associated with disease, and have cell dynamics which effectively deploy cytotoxic payloads. Guanylyl cyclase C (GUCY2C) may be ideal for targeting because it is normally expressed only in insulated barrier compartments, including intestine and brain, but over-expressed by systemic metastatic colorectal tumors. Here, we reveal that GUCY2C rapidly internalizes from the cell surface to lysosomes in intestinal and colorectal cancer cells. Endocytosis is independent of ligand binding and receptor activation, and is mediated by clathrin. This mechanism suggests a design for immunotoxins comprising a GUCY2C-directed monoclonal antibody conjugated through a reducible disulfide linkage to ricin A chain, which is activated to a potent cytotoxin in lysosomes. Indeed, this immunotoxin specifically killed GUCY2C-expressing colorectal cancer cells in a lysosomal- and clathrin-dependent fashion. Moreover, this immunotoxin reduced pulmonary tumors >80% (p<0.001), and improved survival 25% (p<0.001), in mice with established colorectal cancer metastases. Further, therapeutic efficacy was achieved without histologic evidence of toxicity in normal tissues. These observations support GUCY2C-targeted immunotoxins as novel therapeutics for metastatic tumors originating in the GI tract, including colorectum, stomach, esophagus, and pancreas.
Inactivation of NF1 in CNS causes increased glial progenitor proliferation and optic glioma formation

The gene responsible for neurofibromatosis type 1 (NF1) encodes a tumor suppressor that functions as a negative regulator of the Ras proto-oncogene. Individuals with germline mutations in NF1 are predisposed to the development of benign and malignant tumors of the peripheral and central nervous system (CNS). Children with this disease suffer a high incidence of optic gliomas, a benign but potentially debilitating tumor of the optic nerve; and an increased incidence of malignant astrocytoma, reactive astrogliosis and intellectual deficits. In the present study, we have sought insight into the molecular and cellular basis of NF1-associated CNS pathologies. We show that mice genetically engineered to lack NF1 in CNS exhibit a variety of defects in glial cells. Primary among these is a developmental defect resulting in global reactive astrogliosis in the adult brain and increased proliferation of glial progenitor cells leading to enlarged optic nerves. As a consequence, all of the mutant optic nerves develop hyperplastic lesions, some of which progress to optic pathway gliomas. These data point to hyperproliferative glial progenitors as the source of the optic tumors and provide a genetic model for NF1-associated astrogliosis and optic glioma.
QuestMonitor: A Visualization Platform for Declarative Network Protocols

We present the QuestMonitor system, which al- lows to visualize dynamic networks, and monitor the execu- tion of protocols written in a data centric and declarative language: Netlog. This language allows to write protocols, which are two orders of magnitude shorter than imperative programs. Nevertheless, their behavior is sometimes tricky to understand in dynamic networks. QuestMonitor, allows to monitor all the communication between the nodes, the evolution of the data stores on each node, as well as the execution of the declarative code. It also allows to color the virtual data structures, such as routes, backbones, etc. It allowed us to identify flaws in programs. Together with the code editing facility, it constitutes a good tool for rapid prototyping.
Efficient Fitness Estimation and Genetic Operation in Dynamic Environments

This paper introduces efficient fitness estimation and particle swarm operations for dynamic optimization problems in evolutionary computation. This fitness estimation method allows static evolutionary optimization approaches to be extended to efficiently explore global and better local optimal areas in dynamic fitness landscapes. It represents a single individual as a pair of real-valued vector (x, r)âˆˆR^n x R^2 in the evolutionary search population. The first vector x corresponds to a point in the n-dimensional search space (an object variable vector), while the second vector r represents the dynamic fitness value and the dynamic tendency of the individual x in the dynamic environment. r is the control variable (also called strategy variable), which allow self-adaptation. The object variable vector x is operated by different genetic operations according to its corresponding r. As a case study, we have integrated the new fitness estimation method into Particle Swarm Optimization (PSO), yielding an Particle Swarm Optimization in dynamic environments (PSODE). PSODE is experimentally tested with 5 benchmark dynamic problems. The results all demonstrate that PSODE outperforms other PSO on dynamic optimization problems.
FDMA-PON and NG-PON2: Performance and cost comparison

FABULOUS is an EU project pertaining to the 7th framework program with the aim of proving the effectiveness of a Passive Optical Network adopting WDM FDM/FDMA approach, able to grant increased bandwidth, flexibility and cost savings with respect to the recently approved NG-PON2 architecture. In this paper we will show a system management, power and cost comparison among the FABULOUS and the NG-PON2 architectures.
1 Behavioural Approach for Multi-Robot Exploration

Control strategies for mapping of unknown environments require a tradeoff between exploration and accuracy. One approach to balance these conflicting requirements is to use schema based behaviours to provide a means of exploration and manipulate the parameters controlling such schema to maintain the desired localisation and mapping accuracy. This paper provides such a behaviour based strategy for multi-robot exploration. Beyond the coordination of forces attracting agents to unexplored frontiers and repulsing against obstacles, as well as fellow agents, the proposed reactive approach is coupled with frontier based path planning to escape local minma otherwise encountered in a solely potential field based solution. The proposed behaviour based approach is designed so that it can be augmented to moderate movement based on criteria such as localisation accuracy in mapping applications. One planned application is the integration of proposed mechanism with probabilistic filtering for the mapping of indoor environments.
On Equivalence and Uniformisation Problems for Finite Transducers

Transductions are binary relations of finite words. For rational transductions, i.e., transductions defined by finite transducers, the inclusion, equivalence and sequential uniformisation problems are known to be undecidable. In this paper, we investigate stronger variants of inclusion, equivalence and sequential uniformisation, based on a general notion of transducer resynchronisation, and show their decidability. We also investigate the classes of finite-valued rational transductions and deterministic rational transductions, which are known to have a decidable equivalence problem. We show that sequential uniformisation is also decidable for them.
More female patients and fewer stimuli per session are associated with the short-term antidepressant properties of repetitive transcranial magnetic stimulation (rTMS): a meta-analysis of 54 sham-controlled studies published between 1997–2013

Background Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) appears to have short-term antidepressant properties. The aim of the current study was to update our previous meta-analysis and to investigate factors associated with the antidepressant properties of rTMS. Method Following a systematic literature search conducted in Medline and PsycInfo, N=14 sham-controlled, parallel design studies (published after 2008 to August 2013) that had utilized rTMS of the DLPFC in major depression were included in the current meta-analysis. The sensitivity and moderator analyses also included data from N=40 studies (published in 1997–2008) from our previous meta-analysis. The effect size (Cohen’s d) in each study was the standardized difference in mean depression scores (on Hamilton Depression Rating Scale, Beck Depression Inventory, Montgomery Åsberg Depression Rating Scale) from baseline to final (after last session) in rTMS compared to sham groups. Results According to a random-effects model with inverse-variance weights, depression scores were significantly reduced after rTMS compared to sham in studies published from 2008–2013 based on N=659 patients (overall mean weighted d=−0.42, 95% confidence interval: −0.66, −0.18, P=0.001). Combining studies from our past and current meta-analyses (published in 1997–2013; N=54) revealed that depression was significantly reduced after left-fast (>1 Hz), right-slow (≤1 Hz), and bilateral (or sequential) rTMS of DLPFC compared to sham. Significant antidepressant properties of rTMS were observed in studies with patients who were treatment resistant, unipolar (or bipolar), non-psychotic, medication-free (or started on antidepressants concurrently with rTMS). According to univariate meta-regressions, depression scores were significantly lower in studies with more female patients and fewer stimuli per session. There was little evidence that publication bias occurred in the analysis. Conclusion According to this study, the largest meta-analysis to date, short-term antidepressant properties of rTMS are independent of concurrent antidepressants and might depend on sex and the number of stimuli per session.
Measuring Operating System Overhead on CMT Processors

Numerous studies have shown that operating system (OS)noise is one of the reasons for significant performance degradation in clustered architectures. Although many studies examine the OS noise for high performance computing (HPC),especially in multi-processor/core systems, most of them focus on 2- or 4-core systems. In this paper, we analyze the major sources of OS noise on a massive multithreading processor, the Sun UltraSPARC T1,running Linux and Solaris. Since a real system is too complex to analyze, we compare those results with a low-overhead runtime environment: the Netra Data Plane Software Suite (Netra DPS). Our results show that the overhead introduced by the OStimer interrupt in Linux and Solaris depends on the particular core and hardware context in which the application is running. This overhead is up to 30% when the application is executed on the same hardware context of the timer interrupt handler and up to 10% when the application and the timer interrupt handler run on different contexts but on the same core.We detect no overhead when the benchmark and the timer interrupt handler run on different cores of the processor.
The Stueckelberg Extension and Milli Weak and Milli Charged Dark Matter

A overview is given of the recent developments in the U(1)X Stueckelberg extensions of the Standard Model and of MSSM where all the Standard Model particles are neutral under the U(1)X, but an axion which is absorbed is charged under both U(1)X and U(1)Y and acts as the connector field coupling the Standard Model sector with the Stueckelberg sector. Coupled with the usual Higgs mechanism that breaks the SU(2)L×U(1)Y gauge symmetry, this scenario produces mixings in the neutral gauge boson sector generating an extra Z′ boson. The couplings of the extra Z′ to the Standard Model particles are milli weak but its couplings to the hidden sector matter, defined as matter that couples only to the gauge field of U(1)X, can be of normal electro‐weak strength. It is shown that such extensions, aside from the possibility of leading to a sharp Z′ resonance, lead to two new types of dark matter: milli weak (or extra weak) and milli charged. An analysis of the relic density shows that the WMAP‐3 constraints can be satis.
A spheroid-based 3-D culture model for pancreatic cancer drug testing, using the acid phosphatase assay

Current therapy for pancreatic cancer is multimodal, involving surgery and chemotherapy. However, development of pancreatic cancer therapies requires a thorough evaluation of drug efficacy in vitro before animal testing and subsequent clinical trials. Compared to two-dimensional culture of cell monolayer, three-dimensional (3-D) models more closely mimic native tissues, since the tumor microenvironment established in 3-D models often plays a significant role in cancer progression and cellular responses to the drugs. Accumulating evidence has highlighted the benefits of 3-D in vitro models of various cancers. In the present study, we have developed a spheroid-based, 3-D culture of pancreatic cancer cell lines MIAPaCa-2 and PANC-1 for pancreatic drug testing, using the acid phosphatase assay. Drug efficacy testing showed that spheroids had much higher drug resistance than monolayers. This model, which is characteristically reproducible and easy and offers rapid handling, is the preferred choice for filling the gap between monolayer cell cultures and in vivo models in the process of drug development and testing for pancreatic cancer.
A block chain based architecture for asset management in coalition operations

To support dynamic communities of interests in coalition operations, new architectures for efficient sharing of ISR assets are needed. The use of blockchain technology in wired business environments, such as digital currency systems, offers an interesting solution by creating a way to maintain a distributed shared ledger without requiring a single trusted authority. In this paper, we discuss how a blockchain-based system can be modified to provide a solution for dynamic asset sharing amongst coalition members, enabling the creation of a logically centralized asset management system by a seamless policy-compliant federation of different coalition systems. We discuss the use of blockchain for three different types of assets in a coalition context, showing how blockchain can offer a suitable solution for sharing assets in those environments. We also discuss the limitations in the current implementations of blockchain which need to be overcome for the technology to become more effective in a decentralized tactical edge environment.
A Study on Anxiety , Depression and Mental Health Status among Old Age People

The purpose of the study was to explore the relationships between anxiety, depression and mental health status among old age people. The sample consists of 50 participants within range of 60 to 70 years. Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI) and Mithila Mental Health Status Inventory were administered to all the respondents. The data was analysed by using descriptive statistics i.e. mean and SD, Pearson product moment correlation and step wise multiple regression. The result revealed that anxiety was significantly correlated with depression and alienation and negatively correlated with expression (subcomponent of mental health status). Depression was found to have significant positive relationship with egocentrism, alienation, emotional un-stability and social non-conformity, and negative relationship with expression. The step wise regression analysis found emotional unstability and alienation to be predictors of depression.
Expression of Extracellular Matrix Metalloproteases Inducer on Micrometastatic and Primary Mammary Carcinoma Cells

Purpose: EMMPRIN (extracellular matrix metalloprotease inducer) is a glycosylated member of the immunoglobulin superfamily known to stimulate the production of matrix metalloproteases (MMPs) 1, 2, and 3 and MT1-MMP in peritumoral fibroblasts. We here evaluated whether EMMPRIN expression is related to tumor progression in human breast cancer. Experimental Design: An immunohistochemical study using high-density tissue microarrays (n = 2222 breast cancer samples) and EMMPRIN-specific antibodies HIM6 and MEM-M6/1 was performed, and staining results were statistically correlated with various clinicopathological parameters. To analyze the putative association between EMMPRIN expression and bone marrow (BM) micrometastasis, an additional set of 55 breast tumors from patients with or without micrometastatic cells as determined with anti-cytokeratin antibody A45-B/B3 were included in our study. Cytokeratin-positive cells in BM were costained with EMMPRIN-specific antibody 1G6.2. Results: Positive EMMPRIN staining correlated significantly with various histopathological risk factors (higher tumor grade, increased tumor size, negative estrogen receptor status and progesterone receptor status, and higher mitotic index) as well as decreased tumor-specific survival (log-rank, P = 0.0027). In particular, in patients > 50 years (i.e., postmenopausal women), EMMPRIN expression was an independent prognosticator as shown by Cox regression analysis (relative risk = 1.7, 95% confidence interval 1.4–4.3, P = 0.036). An involvement of EMMPRIN in tumor progression was also supported by the fact that it was expressed on ∼90% of micrometastatic cells in BM. Conclusions: EMMPRIN expression in primary tumor predicts an unfavorable prognosis in breast cancer, suggesting a crucial role of EMMPRIN in progression of human mammary carcinomas.
Computer simulation of hydraulic fractures

We provide a brief historical background of the development of hydraulic fracturing models for use in the petroleum and other industries. We discuss scaling laws and the propagation regimes that control the growth of hydraulic fractures from the laboratory to the field scale. We introduce the mathematical equations and boundary conditions that govern the hydraulic fracturing process, and discuss numerical implementation issues including: tracking of the fracture footprint, the control of the growth of the hydraulic fracture as a function of time, coupling of the equations, and time-stepping schemes. We demonstrate the complexity of hydraulic fracturing by means of an application example based on real data. Finally, we highlight some key areas of research that need to be addressed in order to improve current models. r 2006 Elsevier Ltd. All rights reserved.
Lasalle's Invariance Theorem for Nonsmooth Lagrangian Dynamical Systems

A key condition for the statement of Lasalle's invariance theorem is the continuity of the trajectories of the dynamical systems with respect to initial conditions. Systems with discontinuous ﬂows generally don't present such a continuity, but in the particular case of nonsmooth Lagrangian dynamical systems we will see that in fact this continuity property holds in most cases. We will then be able to propose a a LaSalle's invariance theorem for nonsmooth dynamical systems satisfying this property through the use of general time-invariant ﬂows. orem for nonsmooth dynamical systems still needs to be stated, so we propose here to extend this theorem through the framework of nonsmooth dynamical systems.