Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Efficiency of Intrusion Detection Based on Intelligent Immune Method in MANET

In order to enhance efficiency of intrusion detection in the Mobile Ad hoc NETwork (MANET), an intrusion prediction method based on intelligent immune threshold matching algorithm was presented. Using a dynamic load-balancing algorithm, wireless network data packet was distributed to a set of analysis subsystem by the balance subsystem; it could avoid packet loss and false negatives in high-performance wireless network with handling heavy traffic loads in real-time. In addition, adopting the dynamic threshold value, which was generated from variable network speed, the mature antibody could better match the antigen of the database subsystem, and consequently the accuracy of detection was increased. Experiment shows this intrusion detection method has relatively low false positive rate and false negative rate, so it effectively resolves the shortage of intrusion detection in MANET.
Artificial Intelligence: The Bumpy Path Through Defense Acquisition

The use of artificial intelligence systems is ready to transition from basic science research and a blooming commercial industry to strategic implementation in the Defense Acquisition system. The purpose of this research is to determine the problems awaiting artificial intelligence (AI) systems inherent to defense acquisition. AI is a field of scientific study focused on the construction of systems that can act rationally, behave humanly, and adapt. To achieve AI behavior takes AI essentials, which consider mobility, system perspective, and algorithms. Unfortunately, AI essentials are under addressed in the concept of operations that fuels the Joint Capabilities Integration and Development System. Influences to the concept of operations analyzed in this research include strategic documentation, joint technology demonstrations, and exercises that aim to capture technology-based lessons learned. Failure to address AI essentials causes problems in defense acquisition: system requirements are impossible to define; transition of AI technology fails; testing cannot be evaluated with confidence; and life cycle planning is at best a guess. To address these issues, the Department of Defense needs improved planning, acquisition personnel training, and AI-supported acquisition processes to achieve cost, schedule, and performance goals.
Somatostatin receptor expression in thyroid disease

Somatostatin analogues are commercially available and used for the management of acromegaly and neuroendocrine tumours, but the expression of the receptors as a target in thyroid disease has not been explored. To assess somatostatin (SST) and somatostatin receptor (SSTR1‐5) expression in both normal and thyroid disorders, as a potential target for somatostatin analogue therapy, 67 thyroid tissue specimens were reviewed: 12 differentiated thyroid carcinomas, 14 follicular adenomas, 17 multinodular goitres, 14 Graves disease, 10 Hashimotos thyroiditis specimens and five normal thyroids. Tissue was immunostained for SST and SSTR1‐5. Positivity and the degree of positivity were recorded by double‐blinded observers. Somatostatin receptor expression was highly expressed in normal tissue for SSTR1, 3, 4 and 5 (5 of 5, 4 of 5, 4 of 5 and 5 of 5 respectively) whilst SST and SSTR 2a and b were not expressed at all. The commonest receptor expressed for all pathological subtypes grouped together was SSTR2b (63 specimens). The commonest receptors expressed in differentiated thyroid cancer were SSTR5 (11 of 12 specimens) and SSTR2b (10 of 12 specimens). The commonest receptor expressed in benign disease was SSTR2b (53 of 55 specimens). SSTR5 was significantly under‐expressed in Graves disease (P < 0.05). This study illustrates that SSTR 1, 3, 4 and 5 are highly expressed in normal, benign and malignant thyroid tissue. SSTR 2a and 2b appear absent in normal tissue and present in benign and malignant thyroid tissue (P < 0.02). This suggests that focussed SSTR2 treatment may be a potential therapeutic target.
Hybrid Space Vector Modulation Strategy for Torque Ripple Minimization in Three-Phase Four-Switch Inverter-Fed PMSM Drives

Three-phase four-switch (TPFS) inverters are generally applied as cost-reduction topologies for permanent-magnet synchronous motor (PMSM) drives because of their reduced number of switching devices. However, undesirable torque ripples are produced by the inverter-fed PMSMs due to the application of nonsinusoidal voltages. Because the torque ripples are strongly influenced by the employed pulse width modulation (PWM) strategy, two commonly used switching sequences in TPFS inverter-fed PMSM drives are fully investigated based on the root mean square value of the torque ripples, in which the effects of the different equivalent zero vectors on the torque ripples are presented. Then, a hybrid space vector modulation (SVM) strategy is proposed to minimize the torque ripples by alternatively using the two equivalent zero vector synthesis approaches during a fundamental period. The sector division of the proposed hybrid SVM strategy is determined by the location of the stator current vector, which is quite different from the methods used in other SVM methods. Then, a simplified sector identification method is proposed to reduce the computational burden. The experimental results demonstrate that the proposed hybrid PWM strategy can effectively reduce torque ripples in TPFS inverter-fed PMSM drives.
Fluticasone propionate induced alterations to lung function and the immunopathology of asthma over time

BACKGROUND Inhaled corticosteroids are the most widely used treatment for asthma, a disease characterised by both functional and immunopathological abnormalities. This study investigated the relative effects of inhaled corticosteroids on these two features of asthma over time. METHODS A randomised, double blind, placebo controlled, parallel group study with inhaled fluticasone propionate, (FP 2 mg daily) was conducted in 27 patients with asthma. Following baseline analysis, the study tested the effects of short term (two weeks) and longer term (eight weeks) treatment. At each time point (0, 2, and 8 weeks) lung function tests were performed and endobronchial biopsy specimens obtained to determine the distribution and number of lymphocyte, macrophage and eosinophil subsets using immunohistological analysis. Twenty three patients completed the study, 11 on FP and 12 placebo. RESULTS FEV1, ΔFEV1, FEF25–75, and FEV1/FVC all improved after two weeks of FP treatment. This improvement was maintained but not increased after eight weeks. PC20FEV1 showed a trend to increase but was not significantly improved at eight weeks. No significant changes were seen in the placebo group. The numbers of T cells, macrophages, and eosinophils in the bronchial wall were reduced by two weeks of treatment with FP but were unaltered by placebo. The improvement offered by FP continued over the eight week period. Reductions in CD4:CD8 ratio and numbers of activated (EG2+) eosinophils were only significant after eight weeks of treatment. CONCLUSIONS These results reveal that FP influences both functional and immunopathological parameters of asthma. Temporal relationships suggest that these are parallel but not necessarily interrelated effects. While short term treatment is effective in “normalising” the functional abnormalities in asthma, the impact of FP on bronchial inflammation appears to be progressive, taking up to eight weeks and more.
Changes in Brain Perfusion in Patients with Unilateral Lower-limb Paresis, before and after Training on a Pedaling Wheelchair: A Feasibility Study

Our aim was to evaluate the effects of a 4-week training program using a self-powered pedaling wheelchair on brain perfusion in patients presenting with lower limb hemiparesis due to stroke, brain injury, or spinal cord injury. Our cross-sectional observational study included seven patients with lower limb hemiparesis ( ve men, two women; mean age, 68.3 ± 17.5 years), due to the following causes: cerebral hemorrhage (n = 1), stroke (n = 4), brain contusion (n = 1), and spinal cord injury (n = 1). The control group consisted of eight healthy participants (3 men, 5 women; mean age 62 ± 8 years). The training program consisted of ve bouts of 3-min continuous pedaling per day (total, 15 min/day). The outcome variable of interest was blood ow velocity in the middle cerebral artery (time average peak [TAP], cm/s) measured using Doppler. TAP was measured at rest and after a 3-min pedaling bout, before and after the training program. In the patient group, TAP was signi cantly greater after the 3-min bout than at rest, both before and after the training program (p < 0.05). There was no effect of pedaling identi ed in the control group. In the patient group, TAP increased signi cantly (p < 0.05) after training, both at rest (36.9 ± 16.9 to 47.6 ± 13.8 cm/s), and after the 3-min bout (43.3 ± 13.3 to 50.5 ± 15.1 cm/s). Our pedaling wheelchair provided a safe and effective intervention to improve brain perfusion in this patient population.
FGF control of E-cadherin targeting in the Drosophila midgut impacts on primordial germ cell motility

ABSTRACT Embryo formation requires tight regulation and coordination of adhesion in multiple cell types. By undertaking imaging, three-dimensional (3D) reconstructions and genetic analysis during posterior midgut morphogenesis in Drosophila, we find a new requirement for the conserved fibroblast growth factor (FGF) signaling pathway in the maintenance of epithelial cell adhesion through FGF modulation of zygotic E-cadherin. During Drosophila gastrulation, primordial germ cells (PGCs) are transported with the posterior midgut while it undergoes dynamic cell shape changes. In embryos mutant for the FGF signaling pathway components Branchless and Breathless, zygotic E-cadherin is not targeted to adherens junctions, causing midgut pocket collapse, which impacts on PGC movement. We find that the ventral midline also requires FGF signaling to maintain cell–cell adhesion. We show that FGF signaling regulates the distribution of zygotic E-cadherin during early embryonic development to maintain cell–cell adhesion in the posterior midgut and the ventral midline, a role that is likely crucial in other tissues undergoing active cell shape changes with higher adhesive needs. Summary: FGF signaling modulates zygotic E-cadherin distribution to maintain posterior midgut epithelial 3D architecture, impacting on primordial germ cell motility during Drosophila early embryonic development.
Doppler radar sensing of multiple subjects in single and multiple antenna systems

Doppler radar life sensing has shown promise in medical and security applications, however the problems of motion artifacts and presence of multiple subjects limit the usefulness of this technique. By leveraging recent advances in signal processing and wireless communications technologies, the Doppler radar technique has the potential to overcome these limitations. We explore the single and multiple antenna systems and SIMO/MIMO signal processing to isolate desired radar return signals from multiple subjects. It has been experimentally demonstrated that up to two subjects can be separated in a single antenna systems. Simulations have also shown that in case two subjects have identical cardiovascular behavior, it is possible to distinguish them using MIMO techniques.
A homotopic Galerkin approach to the solution of the Fokker-Planck-Kolmogorov equation

In this paper, we present a homotopic Galerkin approach to the solution of the Fokker-Planck-Kolmogorov equation. We argue that the ideal Hilbert space to approximate the exact solution, psi* is the space L2(dPsi*) where dPsi* is the probability measure induced on Rn by the solution psi* itself. We show that given an initial approximation of the exact solution which is sufficiently close to the exact solution, we can obtain the exact solution iteratively by propagating the solution over sufficiently small time intervals using the Galerkin projection method. Further, we show that given a family of dynamical systems, DP, indexed by the homotopy parameter p isin [0,1], where the dynamical system corresponding to p = 0 is a system whose associated Fokker-Planck equation can be solved and p = 1 is the dynamical system of interest, and such that the associated solutions to the corresponding Fokker-Planck equations can be changed smoothly by slowly varying the homotopy parameter, the exact solution can be obtained recursively, using the Galerkin projection method, starting with the solution to the Fokker-Planck equation associated with the dynamical system D0
Privacy Protection in Personalized Web Search Via Taxonomy Structure

Web search engine has long become the most important portal for ordinary people looking for useful information on the web. User might experience failure when search engine return irrelevance information due to enormous variety of user's context and ambiguity of text. The Existing System failed to resist ambiguity of text. Our Proposed System aim at removing ambiguity of text and provide the relevance information to the User. We learn privacy protection in PWS applications that model user preferences as hierarchical user profiles (via taxonomy Structure). We propose a PWS framework called UPS that can adaptively generalize profiles by queries while respecting user-specified privacy requirements via taxonomy structure. Our runtime generalization aims at striking a balance between two predictive metrics that evaluate the utility of personalization and the privacy risk of exposing the generalized profile. For runtime generalization greedy algorithms GreedyDP and GreedyIL are used. For deciding whether to personalizing a query is beneficial online mechanism is provided.
Contraction and AICAR Stimulate IL-6 Vesicle Depletion From Skeletal Muscle Fibers In Vivo

Recent studies suggest that interleukin 6 (IL-6) is released from contracting skeletal muscles; however, the cellular origin, secretion kinetics, and signaling mechanisms regulating IL-6 secretion are unknown. To address these questions, we developed imaging methodology to study IL-6 in fixed mouse muscle fibers and in live animals in vivo. Using confocal imaging to visualize endogenous IL-6 protein in fixed muscle fibers, we found IL-6 in small vesicle structures distributed throughout the fibers under basal (resting) conditions. To determine the kinetics of IL-6 secretion, intact quadriceps muscles were transfected with enhanced green fluorescent protein (EGFP)-tagged IL-6 (IL-6-EGFP), and 5 days later anesthetized mice were imaged before and after muscle contractions in situ. Contractions decreased IL-6-EGFP–containing vesicles and protein by 62% (P < 0.05), occurring rapidly and progressively over 25 min of contraction. However, contraction-mediated IL-6-EGFP reduction was normal in muscle-specific AMP-activated protein kinase (AMPK) α2-inactive transgenic mice. In contrast, the AMPK activator AICAR decreased IL-6-EGFP vesicles, an effect that was inhibited in the transgenic mice. In conclusion, resting skeletal muscles contain IL-6–positive vesicles that are expressed throughout myofibers. Contractions stimulate the rapid reduction of IL-6 in myofibers, occurring through an AMPKα2-independent mechanism. This novel imaging methodology clearly establishes IL-6 as a contraction-stimulated myokine and can be used to characterize the secretion kinetics of other putative myokines.
Data Mining of Causal Relations from Text: Analysing Maritime Accident Investigation Reports

Text mining is a process of extracting information of interest from text. Such a method includes techniques from various areas such as Information Retrieval (IR), Natural Language Processing (NLP), and Information Extraction (IE). In this study, text mining methods are applied to extract causal relations from maritime accident investigation reports collected from the Marine Accident Investigation Branch (MAIB). These causal relations provide information on various mechanisms behind accidents, including human and organizational factors relating to the accident. The objective of this study is to facilitate the analysis of the maritime accident investigation reports, by means of extracting contributory causes with more feasibility. A careful investigation of contributory causes from the reports provide opportunity to improve safety in future. Two methods have been employed in this study to extract the causal relations. They are 1) Pattern classification method and 2) Connectives method. The earlier one uses naive Bayes and Support Vector Machines (SVM) as classifiers. The latter simply searches for the words connecting cause and effect in sentences. The causal patterns extracted using these two methods are compared to the manual (human expert) extraction. The pattern classification method showed a fair and sensible performance with F-measure(average) = 65% when compared to connectives method with F-measure(average) = 58%. This study is an evidence, that text mining methods could be employed in extracting causal relations from marine accident investigation reports.
Surface density profiles of collisionless disc merger remnants

We present a detailed surface density analysis of a large sample of simulated collisionless mergers of disc galaxies with bulges (mass ratios 1:1, 2:1, 3:1, 4:1 and 6:1) and without bulges (mass ratios 1:1 and 3:1). A dissipative component was not included. The randomly projected remnants were fit with a single Sersic function and a Sersic function plus an exponential. They were classified, according to their bulge-to-total (B/T) ratio, either as a one-component system or as a two-component system. In general, projection effects change the classification of a remnant. Only merger remnants of discs with bulges show properties similar to observed early-type galaxies. Their B/T ratios are in the range 0.2 < B/T < 1. Surprisingly, the initial mass ratio has a weak influence on the distributions of B/T, effective radius and Sersic index n. For all one-component projections (≈60 per cent of all projections), the Sersic index distribution peaks at 3 < n < 4. However, the mass ratio is tightly linked to the properties of the outer exponential components which resemble pressure-supported, spheroidal haloes for 1:1 and 2:1 remnants and elongated heated discs for 6:1 remnants. We found distinct correlations between the fitting parameters which are very similar to observed relations (e.g. larger bulges have lower effective surface densities). No indications for a correlation between the surface density profiles and other global parameters like remnant masses, isophotal shapes or central velocity dispersions are found. The remnants have properties similar to giant elliptical galaxies in the intermediate-mass regime. A binary disc merger origin for all early-type galaxies, especially the most massive ones, is unlikely. Observed nearby merger remnants have properties similar to the simulated remnants. They can have formed from binary disc mergers and might evolve into early-type galaxies within a few Gyr.
Radar Stationary and Moving Indoor Target Localization with Low-rank and Sparse Regularizations

This paper proposes a low-rank and sparse regularized optimization model to address the problem of wall clutter mitigation, stationary, and moving target indications using through-wall radar. The task of wall clutter suppression and target image reconstruction is formulated as a nuclear and ${\ell _1}$ penalized least squares optimization problem in which the nuclear-norm term enforces for a low-rank wall clutter matrix and the ${\ell _1}$ -norm term promotes the sparsity of the target images. An iterative algorithm based on the proximal gradient technique is introduced to solve the optimization problem. The solution comprises the wall clutter and images of stationary and moving targets. Experiments are conducted on real radar data under compressive sensing scenarios. The results show that the proposed model is very effective at removing unwanted wall clutter, reconstructing stationary targets, and capturing moving targets.
The Relevance of Index Funds for Pension Investment in Equities

The rise of index funds over the past 25 years has been a remarkable phenomenon. The traditional rationale for the success of index funds is market efficiency, net of transaction costs. The authors also focus on the role of agency conflicts between fund managers and investors, which are hard to resolve, given the low power of statistical tests of performance. Most of the empirical evidence about the superiority of index funds comes from the United States. The authors discuss issues associated with the application of index funds in developing countries, as well as policy issues in the financial sector that affect the enabling market infrastructure for index funds. They also apply these ideas to thinking about the relevance of index funds for pension investment. The equity premium provides powerful motivation for equity investment by pension funds. Index funds make it possible to sidestep the complexities of forming contracts and monitoring institutions to govern fund managers. In developing countries that seek to use index funds in pension investment, there are avenues through which policymakers can make index funds more viable. In many countries there are significant avenues for improving construction of the market index as well as market mechanisms used in the equity market.
Integer Programming for Bayesian Network Structure Learning

Abstract Bayesian networks provide an attractive representation of structured probabilistic information. There is thus much interest in ‘learning’ BNs from data. In this paper the problem of learning a Bayesian network using integer programming is presented. The SCIP (Solving Constraint Integer Programming) framework is used to do this. Although cutting planes are a key ingredient in our approach, primal heuristics and efficient propagation are also important.
Familiar and Strange: Gender, Sex, and Love in the Uncanny Valley

Early robotics research held that increased realism should result in increased positivity of the interactions between people and humanoid robots. However, this turned out to be true only to a certain point, and researchers now recognize that human interactions with highly realistic humanoid robots are often marked by feelings of disgust, fear, anxiety, and distrust. This phenomenon is called the Uncanny Valley. In a world in which Artificial Companions are increasingly likely, and even desired, engineering humanoid robots that avoid the Uncanny Valley is of critical importance. This paper examines theories of the uncanny, and focuses on one in particular—that humans subconsciously appraise robots as potential sexual partners. Drawing from work on love, sexuality, and gender from a variety of fields, this paper speculates on possible futures in a world of intimate companionships between humans and machines.
Novel frequency reusing scheme for interference mitigation in D2D uplink underlaying networks

In this paper, the interference mitigation problem in device-to-device (D2D) communication underlaying cellular networks using fractional frequency reuse (FFR) is studied. For such system, we propose a location based channel reusing scheme in which the D2D users in the inner region have a chance to reuse the channel resources of cellular users in the outer region of neighboring cells, and the D2D users in the outer region could reuse the channel resources of particular cellular users in the inner region of the same cell. Two novel concepts are introduced, namely the accessible region and the reusable region. To protect the outage probabilities of both cellular links and D2D links, only the D2D users in the accessible region could reuse the channel resources of cellular users in the reusable region. We present a specific method to calculate the boundary of the accessible region, as well as the reusable region. Simulation results demonstrate that the proposed scheme could effectively alleviate the interference between both users.