Miracle-dz/UniFAR-FTUs huggingface dataset:
RES: Regularized Stochastic BFGS Algorithm

RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method, is proposed to solve strongly convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second-order methods, on the other hand, is impracticable because the computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost, RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian eigenvalues of the sample functions are sufficient to guarantee almost sure convergence of a subsequence generated by RES and convergence of the sequence in expectation to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.
M-MENTOR: a design algorithm for IP networks with mixed traffic

The design of IP networks to support traffic engineering for both unicast and multicast traffic is a very difficult problem. This paper proposes a heuristic design algorithm called M-MENTOR that concern routing of both types of traffic. However, since multicast traffic model could be employed in many situations and could be managed by various kinds of multicast routing protocols, this paper consider only the design process of the IP networks with following features: (1) network of within the same Autonomous System (AS), (2) routing protocol support multiple weight on each link, (3) the multicast traffic from different sources share the same multicast tree. The efficiency of M-MENTOR is evaluated for various traffic demands and networks of 10, 30 and 50 node and compared with MENTOR-II. The experimental results show that, in almost all cases, M-MENTOR give better performance in term of installation cost.
IL-3-Mediated TNF Production Is Necessary for Mast Cell Development1

Mouse mast cell development and survival are largely controlled by the cytokines IL-3 and stem cell factor (SCF). We have found that IL-3 stimulation of bone marrow cells induces the production of TNF via a PI3K- and MAPK kinase/ERK-dependent pathway. Specifically, Mac-1-positive cells were responsible for TNF production, which peaked on days 7–10 of culture and decreased rapidly thereafter. The importance of IL-3-induced TNF secretion was demonstrated by the failure of TNF-deficient bone marrow cells to survive for >3 wk when cultured in IL-3 and SCF, a defect that was reversed by the addition of soluble TNF. The development of human mast cells from bone marrow progenitors was similarly hampered by the addition of TNF-blocking Abs. Cell death was due to apoptosis, which occurred with changes in mitochondrial membrane potential and caspase activation. Apoptosis appeared to be due to loss of IL-3 signaling, because TNF-deficient cells were less responsive than their wild-type counterparts to IL-3-mediated survival. In vitro cultured mast cells from TNF-deficient mice also demonstrated reduced expression of the high affinity IgE receptor, which was restored to normal levels by the addition of soluble TNF. Finally, TNF-deficient mice demonstrated a 50% reduction in peritoneal mast cell numbers, indicating that TNF is an important mast cell survival factor both in vitro and in vivo.
Coarse-grained Bubble Razor to exploit the potential of two-phase transparent latch designs

Timing margin to cover process variation is one of the most critical factors that limit the amount of supply voltage reduction thereby power consumption. To remove too conservative timing margin, Bubble Razor was introduced to dynamically detect and correct errors in two-phase transparent latch designs [13]. However, it does not fully exploit the potential of two-phase transparent latch design, e.g. time borrowing. Thus, especially at low supply voltage where the effect of process variation becomes significant, the existing Bubble Razor can suffer from significant overhead in performance and power consumption due to too frequent occurrence of bubble generations. We present a design methodology for coarse-grained Bubble Razor which exploits the time-borrowing characteristic of two-phase transparent latch design. By selectively inserting error checkpoints, i.e., shadow latches and error management logic, in the circuit, time borrowing can be applied between error checkpoints thereby avoiding bubbles which could occur in the existing Bubble Razor design with a checkpoint at every latch on the critical path. We present a methodology to choose the grain size (the number of stages between error checkpoints) based on 3-sigma delay distribution. We also verify the benefits of coarse-grained Bubble Razor with a real microprocessor, Core-A design [15] using 20nm Predictive Technology Model (PTM) [16]. The proposed methodology offers 62% improvement in performance (MIPS) and 49% less energy consumption (per instruction) at 0.6V operation (zero frequency margin) over the original Bubble Razor scheme. In addition, it gives 25% area reduction in core design.
Interpretations of Cluster Sampling by Swendsen-Wang

Markov chain Monte Carlo (MCMC) methods have been used in many fields (physics, chemistry, biology, and computer science) for simulation, inference, and optimization. The essence of these methods is to simulate a Markov chain whose state X follows a target probability X ∼ π(X). In many applications, π(X) is defined on a graph G whose vertices represent elements in the system and whose edges represent the connectivity of the elements. X is a vector of variables on the vertices which often take discrete values called labels or colors. Designing rapid mixing Markov chain is a challenging task when the variables in the graph are strongly coupled. Methods, like the single-site Gibbs sampler, often experience long waiting time. A well-celebrated algorithm for sampling on graphs is the Swendsen-Wang (1987) (SW) method. The SW method finds a cluster of vertices as a connected component after turning off some edges probabilistically, and flips the color of the cluster as a whole. It is shown to mix rapidly under certain conditions. It has polynomial mixing time when the graph is a O(1) connectivity, i.e. the number of neighbors of each vertex is constant and does not grow with the graph size. In the literature, there are several ways for interpreting the SW-method which leads to various analyses or generalizations, including 1. A Metropolis-Hastings perspective: using auxiliary variables to propose the moves and accepting with probability 1. 2. Data augmentation: sampling a joint probability whose marginal probability is π(X). 3. Slice sampling and partial decoupling. Then we generalize SW from Potts model to arbitrary probabilities on graphs following the Metropolis-Hastings perspective, and derive a generalized Gibbs sampler.
Evaluating the Usefulness of Content Addressable Storage

Content Addressable Storage (CAS) is increasingly being used as a technique to provide for space savings when storing datasets. In this paper we analyze the performance of CAS on real-world applications and discuss the effects on space savings, savings in network bandwidth and on resultant error resilience of data. We find that a chunksize of 1 KB can provide up to 84% space savings and even higher savings in network bandwidth whilst trading off error resilience. We also find that a chunksize of 1 KB or larger provides good file-system performance while incurring about 14% overhead from use of a CAS based naming scheme.
The Effect of Paramilitary Protest Policing on Protestors' Trust in the Police: The Case of the “Occupy Israel” Movement

The use of paramilitary methods in civil policing tasks has become common in Western police agencies. Despite propositions that such methods should undermine the relationship between the police and the public, the effect of paramilitary policing on public trust in the police has not been empirically tested. In the present study, we examine this question in the context of protest policing, which has become a major concern for Western police agencies. Using a survey of 470 protesters who participated in “Occupy” protest events in Israel in 2012, we find that the perceived use of paramilitary methods has an independent and negative effect on trust, stronger than that of police effectiveness and the “neutrality” component of procedural justice. In-depth interviews suggest that the significance of paramilitarism may be the result of a sense of alienation and criminalization it elicits among protesters who generally perceive themselves as law-abiding citizens.
Genetics-Based Machine Learning Approach for Rule Acquisition in an AGV Transportation System

We propose an autonomous decentralized method for multiple AGV robots under uncertain delivery requests. Transportation route plans of AGV robots are expected to minimize the transportation time without collisions among the robots in the systems. In our proposed methods, each robot as an agent computes its transportation route by referring to the static path information, and it exchanges its route plan each other. Once collisions are detected, one of the two agents chosen by a negotiation rule modifies its route plan. The rule consists of a condition-part and an action-part, and one rule which matches to the conditions of two agents under negotiation is selected from a set of rules. The rules are generated and improved by a genetic based machine learning approach, where a set of rules is represented symbolically as an individual of genetic algorithms, and fitness of each individual is determined according to the total travel time of the AGVs and the adequacy of the condition-parts of the rules.
Smart textile objects and conductible ink as a context for arts based teaching and learning of computational thinking at primary school

The shaping of Smart Textile artefacts brings together a variety of learning activities, such as imagining, designing, drawing, constructing, wiring, programming, controlling, testing, debugging and presenting self-made, invented media objects, realized in project- and team based arrangements. A variety of human senses are addressed when pupils develop and sketch their project ideas to be realized. In the paper, we discuss the topic of self-made Smart Textile objects as a learning content for primary school level, towards the development of curriculum modules for project learning in the classroom as well as teacher training. It was developed in the 'Teachers Aids on Creating Contents for Learning Environments' TACCLE3 coding project.
Author ' s response to reviews Title : Spider phobia is associated with decreased left amygdala volume : a cross-sectional study

Kathleen M Mc Carty (kmccarty@hohp.harvard.edu) Louise Ryan (lryan@hsph.harvard.edu) E. ANDRES Houseman (ahousema@hsph.harvard.edu) Paige Williams (paige@hsph.harvard.edu) David P Miller (dmiller@hohp.harvard.edu) Quazi Quamruzzaman (dch@bangla.net) Mahmuder Rahman (dch@bangla.net) Golam Mahiuddin (dch@bangla.net) Thomas Smith (tsmith@hohp.harvard.edu) Ernesto Gonzalez (egonzalez1@partners.org) Li Su (lisu@hohp.harvard.edu) David C Christiani (dchristi@hsph.harvard.edu)
Tree-Based Routing Protocol for Cognitive Wireless Access Networks

A cognitive wireless network is mostly deployed as wireless access network to optimize the utilization efficiency of radio resource by using multiple wireless systems. In such deployment, the network topology based on a tree structure can be efficiently and quickly constructed among the cognitive terminals (CT) by using the cognitive base station (CBS) as a root, to support the multihop communication. However, the original tree-based routing (TBR) protocol is designed to handle a single wireless system such as IEEE802.11a or lib, and thus can not be applied to the cognitive networks configured with multiple wireless systems, which may have the different bandwidths and transmission ranges. To solve this problem, we propose in this paper an efficient and practical protocol, called cognitive tree-based routing (CTBR) protocol, which extends and significantly enhances the ability of the known TBR protocol to enable it to support multiple wireless systems such as IEEE802.11g and IEEE802.11j. Simulation results reveal that our proposed CTBR protocol that utilizes the cognitive-aware link metric to select a route with the best end-to-end metric and an interface with the least local load for any source-destination pair, achieves much higher performance than the utilization of normal metric associated with the hop count.
VFC-RTS: Vector-Field Consistency para Real-Time-Strategy Multiplayer Games

Although massive multiplayer online games have been gaining most popularity over the years, real-time strategy (RTS) has not been considerate a strong candidate for using this model because of the limited number of players supported, large number of game entities and strong consistency requirements. To deal with this situation, concepts such as continuous consistency and location-awareness have proven to be extremely useful in order to conﬁne areas with consistency requirements. The combination between these two concepts results on a powerful technique in which the player’s location and divergence boundaries are directly linked, providing the player the most accurate information about objects inside his area-of-interest. TheVFCmodel achieves a balance between the notions of continuous consistency and location-awareness by deﬁning multiple zones of consistency around the player’s location (pivot) with diﬀerent divergence boundaries. In this work we propose VFC-RTS, an adaptation of the VFC model, characterized for establishing consistency degrees, to the RTS scenario. We describe how the concepts of the original VFC model were adapt to the RTS paradigm and propose an architecture for a generic middleware. Later, we apply our solution to an open source, multi-platform RTS game with full consistency requirements and evaluate the results to deﬁne the success of this work.
Likelihood adjustment among multiple targets for particle dependent tracking in particle filters

A problem arising at multiple target tracking with particle filters typically in vision has been claimed and a likelihood adjustment method has been proposed. First, classify tracking methods by particle filters into two categories, detection first tracking and particle dependent tracking. Then this research focus on the particle dependent tracking. It involves the problem in case of multiple target tracking that difference of likelihood among target leads to unintended convergence of particles to one target. This is a phenomenon in particle filters that particles prefer easier target having large likelihood value than the difficult target to track having small likelihood value. To overcome this problem, the author proposes to adjust the likelihood among the targets by taking difference in log-likelihood to local maximum of them in each target. Performance of the proposed method has been shown in visual target tracking experiment based on color region.
Meanings and Applications of Compassion in Teaching: A Practical Review of the Bible and Educational Literature

Compassionate teaching is not new; however, the topic is receiving renewed interest as educators around the world endeavour to respond empathetically and practically to students' complex holistic needs. This review provides practical insights from the Bible and secular educational literature that will appeal to Christian teachers in a wide range of educational contexts including church-based ministries. One implication from this study is that teachers and leaders within church educational ministries and Christian schools might critically reflect on how authentically compassion is experienced within their communities. The report concludes by emphasizing that judicious and relational expressions of compassion can have a transformational effect in people's behavior and learning, supporting the injunction in Jude 1:22: “and of some have compassion, making a difference” (KJV).
Methamphetamine Enhances Cryptococcus neoformans Pulmonary Infection and Dissemination to the Brain

ABSTRACT Methamphetamine (METH) is a major addictive drug of abuse in the United States and worldwide, and its use is linked to HIV acquisition. The encapsulated fungus Cryptococcus neoformans is the most common cause of fungal meningitis in patients with AIDS. In addition to functioning as a central nervous system stimulant, METH has diverse effects on host immunity. Using a systemic mouse model of infection and in vitro assays in order to critically assess the impact of METH on C. neoformans pathogenesis, we demonstrate that METH stimulates fungal adhesion, glucuronoxylomannan (GXM) release, and biofilm formation in the lungs. Interestingly, structural analysis of the capsular polysaccharide of METH-exposed cryptococci revealed that METH alters the carbohydrate composition of this virulence factor, an event of adaptation to external stimuli that can be advantageous to the fungus during pathogenesis. Additionally, we show that METH promotes C. neoformans dissemination from the respiratory tract into the brain parenchyma. Our findings provide novel evidence of the impact of METH abuse on host homeostasis and increased permissiveness to opportunistic microorganisms. IMPORTANCE Methamphetamine (METH) is a major health threat to our society, as it adversely changes people’s behavior, as well as increases the risk for the acquisition of diverse infectious diseases, particularly those that enter through the respiratory tract or skin. This report investigates the effects of METH use on pulmonary infection by the AIDS-related fungus Cryptococcus neoformans. This drug of abuse stimulates colonization and biofilm formation in the lungs, followed by dissemination of the fungus to the central nervous system. Notably, C. neoformans modifies its capsular polysaccharide after METH exposure, highlighting the fungus’s ability to adapt to environmental stimuli, a possible explanation for its pathogenesis. The findings may translate into new knowledge and development of therapeutic and public health strategies to deal with the devastating complications of METH abuse. Methamphetamine (METH) is a major health threat to our society, as it adversely changes people’s behavior, as well as increases the risk for the acquisition of diverse infectious diseases, particularly those that enter through the respiratory tract or skin. This report investigates the effects of METH use on pulmonary infection by the AIDS-related fungus Cryptococcus neoformans. This drug of abuse stimulates colonization and biofilm formation in the lungs, followed by dissemination of the fungus to the central nervous system. Notably, C. neoformans modifies its capsular polysaccharide after METH exposure, highlighting the fungus’s ability to adapt to environmental stimuli, a possible explanation for its pathogenesis. The findings may translate into new knowledge and development of therapeutic and public health strategies to deal with the devastating complications of METH abuse.
Oracle's Self-Tuning Architecture and Solutions

Performance tuning in modern database systems requires a lot of expertise, is very time consuming and often misdirected. Tuning attempts often lack a methodology that has a holistic view of the database. The absence of historical diagnostic information to investigate performance issues at first occurrence exacerbates the whole tuning process often requiring that problems be reproduced before they can be correctly diagnosed. Even when the problem root cause is identified, fixing it often requires a very high level of expertise that very few DBA possess. This is especially true for the inherently complex activity of SQL Tuning, requiring a high level of expertise in several domains: query optimization, access design, and SQL design. In this paper we describe how Oracle overcomes these challenges and provides a way to perform automatic performance diagnosis and tuning. The ability to self-tune is a critical aspect towards building a self-managed database, which was one of the key objectives for the latest version of Oracle, Oracle10g, that was released in early 2004.
Through the looking glass: Emotional abuse, self-blame and their relationship with temperament and depression in adolescents

Background: Temperament plays an important role in the development and maintenance of adolescent psychopathology, particularly in depression. The temperament dimensions of negative or positive emotionality are associated with depression in childhood, adolescence, and in adult life. Early traumatic experiences, such as emotional abuse, constitute risk factors for the development of negative cognitive styles and depressive symptoms. The use of dysfunctional regulation strategies (e.g., self-blame) seems to be a significant factor in the onset and exacerbation of depressive symptoms in multiple samples. Nevertheless, the contribution of these variables for the maintenance of depression remains inadequately studied. Objectives: The present study explored the mediator role of early emotional traumatic experiences and self-blame in the relationship between negative emotionality trait and depressive symptoms in an adolescent sample. Method: A sample of 2318 adolescents from a general community population completed several self-report questionnaires measuring depressive symptomatology (CDI), adolescent temperament (EATQ-R Short Form), early emotional traumatic experiences (CTQ-SF), and emotional regulation strategies (CERQ). Results: Results revealed that early emotional traumatic experiences and self-blame mediated the relationship between negative emotionality and depressive symptoms. Nevertheless, the negative emotionality trait is still directly associated with depressive symptoms. These data seem to suggest that adolescents with negative emotionality trait that recall early traumatic experiences and tend to self-blame are more vulnerable to depression. Conclusions: Some important clinical implications should be addressed. Treatment should include therapeutic strategies focused on self-blame and early traumatic experiences (emotional abuse) in order to diminish negative affect. Cognitive contextual approaches seem appropriate.