Miracle-dz/UniFAR-FTUs huggingface dataset:
D-Branes at Singularities : A Bottom-Up Approach to the String Embedding of the Standard Model

We propose a bottom-up approach to the building of particle physics models from string theory. Our building blocks are Type II D-branes which we combine appropriately to reproduce desirable features of a particle theory model: 1) Chirality ; 2) Standard Model group ; 3) N =1 orN = 0 supersymmetry ; 4) Three quark-lepton generations. We start such a program by studying congurations of D = 10, Type IIB D3-branes located at singularities. We study in detail the case of ZZN N =1 ; 0 orbifold singularities leading to the SM group or some left-right symmetric extension. In general, tadpole cancellation conditions require the presence of additional branes, e.g. D7-branes. For the N =1s upersymmetric case the unique twist leading to three quark-lepton generations is ZZ3, predicting sin 2 W =3 =14 = 0:21. The models obtained are the simplest semirealistic string models ever built. In the non-supersymmetric case there is a three-generation model for each ZZN, N> 4, but the Weinberg angle is in general too small. One can obtain a large class of D =4 compact models by considering the above structure embedded into a Calabi Yau compactication. We explicitly construct examples of such compact models using ZZ3 toroidal orbifolds and orientifolds, and discuss their properties. In these examples, global cancellation of RR charge may be achieved by adding anti-branes stuck at the xed points, leading to models with hidden sector gravity-induced supersymmetry breaking. More general frameworks, like F-theory compactications, allow completely N = 1 supersymmetric embeddings of our local structures, as we show in an explicit example.
Darwinism renewed : contemporary studies of plant adaptation

One hundred fifty years after On the origin of species was first published (Darwin, 1859), biologists continue to share Darwin’s fascination with the adaptive traits of organisms, and to theoretically and empirically expand his initial formulation of natural selection as the process that shapes those traits. In this special issue of the journal, New Phytologist recognizes this continuing legacy by bringing together current ideas and findings about plant adaptation from an accomplished, multi-national group of researchers studying a wide array of plant systems. Many of these studies make use of the formidable set of research tools now available to examine the molecular and genomic bases of adaptive traits and their selective dynamics, and these tools have certainly provided critical insights. But the most exciting aspect of contemporary work on adaptation is not these new techniques per se, but rather the way researchers are combining diverse tools in robust, richly informative interdisciplinary approaches. Genomic data from model organisms are being used in new ways to inform studies of naturally evolved systems, and a rigorous phylogenetic context has become standard across sub-disciplines to refine population, species, and higher-level comparisons. The studies presented here address questions at all levels from the molecular to the macroevolutionary, drawing on information ranging from transgenic functional assays, transcriptomics, and quantitative genetics trait matrices to GISbased niche modeling, field explant studies of recombinant inbred lines, and distribution data from herbarium sheets. This new work makes clear how these sophisticated interdisciplinary approaches are illuminating some of the most fundamental and long-standing questions about plant adaptation and the process of selective change. It also reflects an increasing awareness that the study of adaptation has important bearing on biodiversity conservation, invasion biology, and potential constraints on adaptive evolution in the face of rapidly changing environments. Here, a brief overview of the feature points to some of the key findings with respect to several areas of shared focus: co-evolutionary interactions; floral and mating system evolution; geographic patterns of adaptive evolution; genetic architecture of adaptation; and evolution of functional traits. Co-evolutionary interactions
Efficient Elimination of Cancer Cells by Deoxyglucose-ABT-263/737 Combination Therapy

As single agents, ABT-263 and ABT-737 (ABT), molecular antagonists of the Bcl-2 family, bind tightly to Bcl-2, Bcl-xL and Bcl-w, but not to Mcl-1, and induce apoptosis only in limited cell types. The compound 2-deoxyglucose (2DG), in contrast, partially blocks glycolysis, slowing cell growth but rarely causing cell death. Injected into an animal, 2DG accumulates predominantly in tumors but does not harm other tissues. However, when cells that were highly resistant to ABT were pre-treated with 2DG for 3 hours, ABT became a potent inducer of apoptosis, rapidly releasing cytochrome c from the mitochondria and activating caspases at submicromolar concentrations in a Bak/Bax-dependent manner. Bak is normally sequestered in complexes with Mcl-1 and Bcl-xL. 2DG primes cells by interfering with Bak-Mcl-1 association, making it easier for ABT to dissociate Bak from Bcl-xL, freeing Bak to induce apoptosis. A highly active glucose transporter and Bid, as an agent of the mitochondrial apoptotic signal amplification loop, are necessary for efficient apoptosis induction in this system. This combination treatment of cancer-bearing mice was very effective against tumor xenograft from hormone-independent highly metastasized chemo-resistant human prostate cancer cells, suggesting that the combination treatment may provide a safe and effective alternative to genotoxin-based cancer therapies.
High-dose oral N-acetylcysteine fails to improve respiratory health status in patients with chronic obstructive pulmonary disease and chronic bronchitis: a randomized, placebo-controlled trial

Background Clinical outcomes are worse in patients with COPD and chronic bronchitis. N-acetylcysteine (NAC) is commonly prescribed for such patients but with uncertain clinical benefits. We postulated that oral NAC, at much larger doses than those ordinarily prescribed, would improve clinical outcomes in a subset of patients with COPD and chronic bronchitis. Objective The aim of this study was to determine whether very high-dose NAC would improve respiratory health status in patients with COPD and chronic bronchitis. Methods Patients with COPD and chronic bronchitis were enrolled in a randomized, controlled, double-blinded trial. Patients received oral NAC (1,800 mg) or matching placebo twice daily for 8 weeks in addition to their usual respiratory medications. The primary outcome, respiratory health status, was assessed by changes in the St George’s Respiratory Questionnaire. The effects of NAC on lung function and circulating markers of oxidative stress and inflammation were also evaluated. Results We terminated the study prematurely because new external information suggested the possibility of a safety issue. Of the planned 130 patients, 51 were randomized and 45 (22 in the placebo arm and 23 in the NAC arm) completed the study. There was no statistically significant difference between changes in the St George’s Respiratory Questionnaire total score, comparing NAC to placebo (adjusted mean difference, 0.1 U; 95% CI, −7.8 to 8.18 U; P=0.97). There were also no significant NAC-related improvements in any of the secondary outcomes. Conclusion In this 8-week trial, we were unable to show any clinical benefit from a very high dose of NAC in patients with COPD and chronic bronchitis.
Effects of Aliasing and Mis-Registration on Pan-Sharpening Methods Based on Either Component Substitution or Multi-Resolution Analysis

In this paper, the characteristics of multi-spectral (MS) and panchromatic (P) image fusion, or pan-sharpening, methods, will be investigated. Depending on the way spatial details are extracted from P, such methods can be broadly labelled into two main classes, roughly corresponding to component substitution (CS), also known as projection substitution , and methods based on multi-resolution analysis (MRA), i.e. on digital filtering. Experimental results carried out on QuickBird and Ikonos data sets evidence that CS-based fusion is far less sensitive than MRA-based fusion to: a) registration errors, i.e. spatial misalignments between MS and P images, possibly originated by cartographic projection and resampling of individual data sets; b) aliasing occurring in MS bands and stemming from a modulation transfer function (MTF) of each MS channels that is excessively broad relatively to the spatial sampling interval. Simulated misalignments, carried out at full scale by means of a suitable quality evaluation protocol, have evidenced the quality-shift trade-off of the two classes: MRA methods yield a slightly superior quality in the absence of misalignments, but are more penalized, whenever shifts between MS and P are present, than CS methods, which produce a slightly lower quality in the ideal case, but are intrinsically more shift tolerant.
MDS-Tree and MDS-Matrix for High Dimensional Data Visualization

In this work, we propose MDS-Tree and MDS-Matrix as novel high dimensional data visualization methods to gain insight in both the data aspect and dimension aspect of the data. Dimension metrics of the high dimensional dataset are first computed to create a hierarchy. In an MDS-Tree, each node is an MDS projection of the original data items on a specific subset of dimensions associated with the dimension hierarchy. While the MDS-Tree visualizes the subspace structure of the data under exploration, MDSMatrix provides cross comparison between different combination of subspaces. In the MDS-Matrix construction, each pair of the subspaces are plotted as an MDS plot in the MDS-Matrix. In both MDS-Tree and MDS-Matrix, a full spectrum of user interaction has been designed, including drilling down to explore different levels of the data, merging or splitting the nodes to adjust the dimension hierarchy, applying brushing to select data clusters. Our proposed MDS-Tree and MDS-Matrix reveal the data from different aspects. They enable a simultaneous exploration on the data correlation and dimension correlation for data with high dimensions.
Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space

Let H be an infinite-dimensional real separable Hilbert space. Given an unknown mapping M:H (r)H that can only be observed with noise, we consider two modified Robbins-Monro procedures to estimate the zero point ? o ( H of M. These procedures work in appropriate finite dimensional sub-spaces of growing dimension. Almost-sure convergence, functional central limit theorem (hence asymptotic normality), law of iterated logarithm (hence almost-sure loglog rate of convergence), and mean rate of convergence are obtained for Hilbert space-valued mixingale, (-dependent error processes.
Near-optimal Downlink precoding of a MISO system for a secondary network under the SINR constraints of a primary network

In this paper, we study a multiple-input single-output cognitive radio (CR) system where only the primary base station (BS) has multiple antennas. We consider a rate maximization problem of the secondary network under signal-to-interference-plus-noise-ratio constraints on the primary network in order to guarantee the quality-of-service for the latter network. While the interference due to the secondary transmission in the conventional underlay CR approach may severely degrade the performance of the primary network, we propose a primary BS-aided approach in which the primary BS helps relay the secondary users' signals instead of allowing them to communicate with each other via a direct path between them. In addition, an algorithm to find a near-optimal beamforming solution at the primary BS is proposed. Finally, based on some selected numerical results, we show that the proposed scheme outperforms the conventional underlay CR configuration over a wide transmit power range.
Effect of Ultimate pH on Postmortem Myofibrillar Protein Degradation and Meat Quality Characteristics of Chinese Yellow Crossbreed Cattle

This paper describes the complex effects of postmortem ultimate pH (pHu) on Chinese Yellow crossbreed cattle quality during postmortem ageing and provides an explanation of how pHu affects beef tenderness. High pHu beef had the highest initial tenderness (P < 0.05) compared with other groups at 1 day postmortem. Intermediate and low pHu beef had similar initial WBSF at 1 day postmortem, but intermediate pHu beef had slower tenderization rate than low pHu beef (P < 0.05). Purge loss, cooking loss, L*, a*, and b* values decreased with increasing pHu during ageing (P < 0.05). Myofibril fragmentation index (MFI) was higher in high pHu beef than intermediate and low pHu beef throughout ageing (P < 0.05). Protein degradation studies found that desmin and troponin-T appeared degraded within 0.5 h postmortem for high and low pHu beef, compared to >2 days for intermediate pHu beef. Overall, Chinese Yellow crossbred cattle tenderness is related to pHu, which may be affected by proteolytic enzymatic activity. Therefore, pHu may be used to predict beef tenderness and other quality characteristics during postmortem ageing. To achieve consistent tenderness, different ageing times should be used, depending on pHu.
Analytical model of susceptibility‐induced MR signal dephasing: Effect of diffusion in a microvascular network

A deterministic analytical model that describes the time course of magnetic resonance signal relaxation due to magnetic field inhomogeneity induced by a vascular network is developed. Both static and diffusion dephasing are taken into account. The contribution of the diffusion dephasing is calculated for relatively large vessels (R > 10μm) or short measurement times when the diffusion length is smaller than the vessel radius. The signal is found to possess the following features: a) an initial deviation from the monoexponential relaxation which is more pronounced for the imaginary part of the signal; b) a deviation from monoexponential relaxation at short echo times for the spin‐echo (SE) signal measured as a function of the echo time; c) the echo maximum of the SE signal shifted from the nominal echo time to a shorter time; and d) a diffusion effect much stronger for the SE than for the free induction decay experiment. The model presented agrees within its validity domain with a known Monte Carlo simulation. Magn Reson Med 41:499–509, 1999. © 1999 Wiley‐Liss, Inc.
Wearable Device-based Fall Detection System for Elderly Care Using Support Vector Machine (SVM) classifier

Fall is an increasing problem as people ageing. It may happen to anyone, but their incidence does increase with age. Hence, the elderly will be facing catastrophic consequences due to falls. Nevertheless, there are still vulnerable in its accuracy in categorizing and differentiating the Activities Daily Living (ADL) and falls as most of the existing systems cause false alarm. This paper presents the research and simulation of wearable device-based fall detection approach by addressing the building of wearable device-based fall detection system for elderly care by using mobile devices. Two main phases involve in this research: online phase and offline phase. Online phase covers in data acquisition step whereby the raw data of simulated fall by participants is collected via built-in-tri-axial accelerometer in a smartphone, then automatically sent towards the computer via wireless communication. Meanwhile, offline phase covers data pre-processing, feature extraction and selection and data classification where these steps are handled in offline mode. Support Vector Machine (SVM) classifier was employed, and evaluated in the analysis. Overall accuracy rate, sensitivity, specificity as well as False Positive Rate (FPR) and False Negative Rate (FNR) were calculated. The findings suggest that SVM with Polynomial (order 5) method which achieved 68.91% overall accuracy as well as producing only 24.46% FPR is the most precise model for fall detection system in this paper. This approach has the potential to be implemented and deploy in real mobile application in future.
Inteligência emocional: revisão internacional da literatura

The concept of emotional intelligence (EI), understood as the ability to process one's own and others' feelings and emotions and use them adaptively, has just completed twenty-six years old. Different conceptions about the construct have been proposed since then. The examination of the research scenario on the topic, in the international scope, promotes understanding of the current state of development of the area. Thus, this article is concerned with an analysis of articles published in PsycArticles database of the American Psychological Association (APA), from keyword emotional intelligence, was carried out having 44 out of 79 articles meeting the established inclusion criteria. All articles found referred to empirical studies. The majority of studies sought to relate the EI to other constructs or to examine psychometric properties of instruments to its measurement. Recent studies on intervention programmes for promoting EI and evaluation of its effectiveness are suggested.
Resolving Leadership Conceptual Ambiguities: A Postmodern Sociological Resolution

The authors conducted a content analysis of transformational and charismatic leadership concepts from a sample of social and behavioral sciences research published in refereed journals from 1988 to 2008. The content analysis revealed a logical weakness in the measurement and operationalization of leadership traits. To resolve the conceptual ambiguities a postmodern theoretical approach provided salient sociological constructs that allowed a disambiguation of the often-ascribed leadership traits. Additionally, a survey of leadership texts and essays provided an epistemological foundation of leadership narratives. From the literature, the authors identified 10 distinctive intrapersonal (organizational beliefs) and interpersonal (social beliefs) referents linked to emergent leader and follower self-reports and behaviors. Additionally, the authors propose a habitus schema of leader and worker perceptions as an alternative methodology to better identify the likelihood of successful performances in an organizational setting.
P2PTV Traffic Localization by Deep Packet Inspection

Recently, peer-to-peer has been becoming a promising architecture for developing video streaming services because it can reduce the bottlenecks and the load at the server side. However, P2P systems implement their own routing protocols on overlay networks, which are largely independent of the Internet routing. As a result, the traffic generated by P2P systems is immense and unpredictable. Controlling the P2P traffic is therefore becoming a big challenge for internet service providers (ISPs). Considering the P2P traffic localization is one of the most efficient solutions to optimize the traffic. The existing approaches, however, require several modifications of the application software. In this paper, we propose a novel traffic localization method for P2P streaming application (P2PTV) by deep packet inspection. Based on the peer list and the geographical location of the listed peers, we propose two mechanisms for localizing the traffic: the modification of the peer list packets and the redirection of the video request packets at network routers. Since our method is implemented on the network routers, it can be applied for all P2P applications without any software modifications. The experiments evaluated on a popular P2PTV, namely PPStream, prove the effectiveness of our proposed method on the problem of traffic localization.
New models of pulmonary hypertension based on VEGF receptor blockade-induced endothelial cell apoptosis

In spite of treatment, severe angioproliferative pulmonary arterial hypertension (PAH) remains a disease characterized by great morbidity and shortened survival. New treatment strategies for patients with PAH are needed, and after drug development, preclinical studies are best conducted in animal models which present with pulmonary angio-obliterative disease and right heart failure. A rat model of severe pulmonary hypertension and right heart failure, described a decade ago, continues to be investigated and provide insight into the nature of the lung vascular lesions and mechanisms of cardiac adaptation to an altered lung circulation. This rat model is based on the combination of VEGF receptor blockade with Su5416 and chronic hypoxia; use of this pulmonary hypertension induction strategy led to developing the concept of apoptosis-dependent compensatory vascular cell growth. Although, often employed in experimental designs, chronic hypoxia is not necessary for the development of angio-obliterative pulmonary hypertension. Left pneumonectomy combined with Su5416 also results in severe pulmonary hypertension in normoxic conditions. Similarly, the immune insufficiency component of severe PAH can be modeled in athymic rats (lacking T-lymphocytes). In these rats housed under normoxic conditions, treatment with the VEGFR receptor blocker results in angioproliferative pulmonary hypertension; cardiopulmonary disease in these animals can be prevented by immune reconstitution of regulatory T-cells (Tregs). Finally, chronic hypoxia can be replaced with another stimulator of HIF-1α: Ovalbumin (Ova). Immunization of rats with Ova increases lung tissue HIF-1α protein expression, and in Su5416-treated rats causes lethal pulmonary hypertension. Finally, we postulate that these models may also be useful for “reverse translation”; that is, the mechanisms of lung vascular cell death and growth and the modifying influences of immune and bone marrow cells that have been identified in the Su5416 VEGFR inhibitor models can be informative about heretofore undescribed processes in human PAH.
On contextual photo tag recommendation

Image tagging is a growing application on social media websites, however, the performance of many auto-tagging methods are often poor. Recent work has exploited an image's context (e.g. time and location) in the tag recommendation process, where tags which co-occur highly within a given time interval or geographical area are promoted. These models, however, fail to address how and when different image contexts can be combined. In this paper, we propose a weighted tag recommendation model, building on an existing state-of-the-art, which varies the importance of time and location in the recommendation process, based on a given set of input tags. By retrieving more temporally and geographically relevant tags, we achieve statistically significant improvements to recommendation accuracy when testing on 519k images collected from Flickr. The result of this paper is an important step towards more effective image annotation and retrieval systems.
A sliding mode controller using neural networks for robot manipulator

This paper proposes a new sliding mode controller using neu- ral networks. Multilayer neural networks with the error back-propagation learning algorithm are used to compensate for the system uncertainty in order to reduce tracking errors and control torques. The stability of the proposed control scheme is proved with the Lyapunov function method. Computer simulation shows that the proposed neuro-controller yields better control performance than the conventional sliding mode controller in the view of tracking errors and overall control torque.
Generalized Kraft Inequality and Arithmetic Coding

Algorithms for encoding and decoding finite strings over a finite alphabet are described. The coding operations are arithmetic involving rational numbers li as parameters such that Σi2-l i≤2-∈. This coding technique requires no blocking, and the per-symbol length of the encoded string approaches the associated entropy within ∈. The coding speed is comparable to that of conventional coding methods.