Miracle-dz/UniFAR-FTUs huggingface dataset:
Complementary Layered Learning

Layered learning is a machine learning paradigm used to develop autonomous robotic-based agents by decomposing a complex task into simpler subtasks and learns each sequentially. Although the paradigm continues to have success in multiple domains, performance can be unexpectedly unsatisfactory. Using Boolean-logic problems and autonomous agent navigation, we show poor performance is due to the learner forgetting how to perform earlier learned subtasks too quickly (favoring plasticity) or having difficulty learning new things (favoring stability). We demonstrate that this imbalance can hinder learning so that task performance is no better than that of a suboptimal learning technique, monolithic learning, which does not use decomposition. Through the resulting analyses, we have identified factors that can lead to imbalance and their negative effects, providing a deeper understanding of stability and plasticity in decomposition-based approaches, such as layered learning. To combat the negative effects of the imbalance, a complementary learning system is applied to layered learning. The new technique augments the original learning approach with dual storage region policies to preserve useful information from being removed from an agent’s policy prematurely. Through multi-agent experiments, a 28% task performance increase is obtained with the proposed augmentations over the original technique.
Pain and Anxiety Management in Minimally Invasive Repair of Pectus Excavatum

The Nuss procedure for the correction of Pectus Excavatum (PE) is associated with intense postoperative pain. Our strategy to control early postoperative pain is to combine epidural with intravenous analgesia. Our aim was to analyse our pain control strategy by reviewing all the PE cases treated at our institution. Sixty consecutive patients, aged between 12 and 26 years old, received the PE operation at our institution from January, 2007 to September, 2010. The median age was 16 (12-27) with a male/female ratio of about 7/1. An epidural catheter was employed in all the cases, with 38 patients (63%) requiring additional drugs to control pain, which remained in place for 74 hours (72-96). The pain score was higher in male patients, but lower in those younger than 16 years old. Moreover, patients that consumed benzodiazepines had a significant decrease in cumulative opioid intake (P = 0.0408). Both gender and age had an impact on pain control, while we noticed a synergistic effect between opiates and tranquillizers.
Receptor for Advanced Glycation End Products Mediates Inflammation and Enhanced Expression of Tissue Factor in Vasculature of Diabetic Apolipoprotein E–Null Mice

Abstract—Advanced glycation end products (AGEs) and their cell surface receptor, RAGE, have been implicated in the pathogenesis of diabetic complications. Here, we studied the role of RAGE and expression of its proinflammatory ligands, EN-RAGEs (S100/calgranulins), in inflammatory events mediating cellular activation in diabetic tissue. Apolipoprotein E– null mice were rendered diabetic with streptozotocin at 6 weeks of age. Compared with nondiabetic aortas and kidneys, diabetic aortas and kidneys displayed increased expression of RAGE, EN-RAGEs, and 2 key markers of vascular inflammation, vascular cell adhesion molecule (VCAM)-1 and tissue factor. Administration of soluble RAGE, the extracellular domain of the receptor, or vehicle to diabetic mice for 6 weeks suppressed levels of VCAM-1 and tissue factor in the aorta, in parallel with decreased expression of RAGE and EN-RAGEs. Diabetic kidney demonstrated increased numbers of EN-RAGE–expressing inflammatory cells infiltrating the glomerulus and enhanced mRNA for transforming growth factor-&bgr;, fibronectin, and &agr; 1 (IV) collagen. In mice treated with soluble RAGE, the numbers of infiltrating inflammatory cells and mRNA levels for these glomerular cytokines and components of extracellular matrix were decreased. These data suggest that activation of RAGE primes cells targeted for perturbation in diabetic tissues by the induction of proinflammatory mediators.
Shape recognition on a Riemannian manifold

In this paper, we propose to perform shape recognition on a Riemannian manifold. Shape representation on a manifold have the advantage to be intrinsically invariant to shape preserving transformation, such as scaling and translation. Also, shape distance can be naturally computed because Riemannian manifolds are metric spaces. We propose to use the square-root velocity manifold (SRV), which model the shape external contour as a unit-length curve. We detail a dynamic programming algorithm for curve alignment w.r. t. parameterization, which respects the unit-length constraint. Then, we increase the robustness of the SRV representation to shape deformations with additional features. In order to be resilient to occlusion, the distance between two curves is performed in two steps. First the curves are aligned and the less matching parts are removed; then the resulting curves are aligned and the distance is evaluated. Finally, a support vector machine classifier is trained based on the pairwise shape distance for a robust recognition. Promising results are obtained using state-of-the-art benchmarks.
Exploring the effectiveness of engagement in a broad range of disciplinary practices on learning of Turkish high-school chemistry students

ABSTRACT This study examines the influence of laboratory instruction that engages students in a wide range of the practices of science on Turkish high-school students’ chemistry learning. In this mixed methods study, student learning in two different laboratory settings was compared, one that featured an instruction that engaged students in a wide range of disciplinary practices (through Argument-driven Inquiry – ADI) and similar laboratories in which a more traditional Structured Inquiry (SI) approach was employed. The data sources included a Chemistry Concept test, an Argumentative Writing Assessment, and Semi-structured interviews. After seven weeks of chemistry instruction, students experiencing ADI instruction scored higher on the Chemistry Concept test and the Argumentative Writing Assessment than students experiencing SI instruction. Furthermore, girls who experienced ADI instruction scored higher on the assessments than their majority peers in the same class. The results suggest that Turkish students can substantially improve their chemistry proficiency if they have an opportunity to engage in instruction featuring a broad array of the practices of science.
The Measurement of Blood Pressure During Sleep

The measurement of blood pressure (BP) variations during sleep can provide very useful information for diagnosing and managing hypertension, and for assessing cardiovascular function in general. This paper gives an overview of the clinical significance of nocturnal BP and of the technical challenges involved in measuring it, and compares technologies that perform intermittent measurements with technologies that measure the continuous BP waveform. It also identifies likely future developments in this field, including the convergence of ambulatory monitoring and the measurement of the continuous waveform, and the wider use of polysomnography (in which other cardio-respiratory signals are also recorded) as a screening tool for detecting sleep apnea in the management of hypertension.
The last of the seven-parton tree amplitudes

We compute the four-quark plus three-gluon and six-quark plus one-gluon tree level amplitudes using on-shell recursion relations. They are needed for the calculation of the 5-jet cross-section at the Born level, and constitute an essential ingredient for next-to-leading order 4-jet and next-to-next-to-leading order 3-jet production at hadronic colliders. Very compact expressions for all possible helicity configurations are provided, allowing direct implementation in computer codes. With the results presented in this paper, the full set of seven-parton tree amplitudes becomes available.
Quality of Service Architectures

The article covers the two most important architectures for providing Quality of Service at the network and transport layer, the Integrated Services (IntServ) and the Differentiated Services (DiffServ) architecture, both proposed by the Internet Engineering Task Force (IETF). It describes the basic characteristics of each architecture, provides a comparison between them and outlines the current trend and the status of the implementations in network equipment and networks. INTRODUCTION IP networks are built around the idea of best effort networking, which makes no guarantees regarding the delivery, the speed and the accuracy of the transmitted data. While this model is suitable for a large number of applications and works well for almost all applications when the network load is low (and therefore there is no congestion), there are two main factors that lead to the need for an additional capability of quality of service guarantees. One is the fact that an increasing number of Internet applications are related to real-time and other multimedia data, which have greater service requirements in order to be satisfying to the user. The other is that Internet usage is steadily increasing, and although the network infrastructure is often also updated, it is not always certain that network resources offering will be ahead of network usage demand. In order to deal with this situation, IETF has developed two architectures in order to enable QoS based handling of data flows in IP networks. This article describes and compares these two architectures.
An Efficient Google Datastore Adapter for Rich Internet Applications

In this article we present the design of a database adapter for the Google Datastore and the Vaadin Rich Internet Application Framework. The adapter allows us to develop Vaadin applications that can use different database systems and can be deployed in a private infrastructure as well as in the Google App Engine platform. The adapter uses a two-level cache schema to improve performance and reduce operation costs. Experimental results show that the use of the adapter does not hinder the ability of the Google App Engine platform to scale web applications on-demand to high loads.
An Adaptive Information Dispersal Algorithm for Time-critical Reliable Communication

AIDA { a novel elaboration on Michael O. Rabin's IDA 21] { is a communication protocol that uses redundancy to achieve both timeliness and reliability. In AIDA redundancy is used to tackle several crucial problems. In particular, redundancy is used to tolerate failures, to increase the likelihood of meeting tight time-constraints, and to ration (based on task priorities) the limited bandwidth in the system. AIDA is a probabilistic protocol in the sense that it does not guarantee the fullllment of hard time constraints. Instead, it guarantees a lower bound on the probability of fulllling such constraints. Such a bound could be lowered so as to satisfy any level of conndence in the timeliness and reliability of the system. In this paper we present AIDA and contrast it with traditional communication scheduling techniques used in conjunction with time-critical applications in general, and distributed multimedia systems in particular. The suitability of AIDA-based bandwidth allocation for a variety of time-critical applications is established and plans for future research experiments are mentioned.
MAP Classifier with BDA Features

In this paper, we derive a maximum a posteriori (MAP) classifier using the features extracted by biased discriminant analysis (BDA) in multi-class classification problems. Using the one-against-the-rest scheme we construct several feature spaces, where the MAP classifier is formulated. Although the maximum likelihood (ML) classifier is generally equivalent to the MAP classifier when the prior probability of each class is the same, an additional assumption is needed for the ML classifier to have the same results as the MAP classifier using the features extracted by BDA. We also show that the ML classifier is the same as the nearest to the mean classifier under some assumption. In order to estimate the distribution of negative samples in each reduced space, we can use the Parzen window density estimation or the Gaussian mixture model. Experimental results on several data sets indicate that the MAP classifier with BDA features provides better classification result than using the features extracted by linear discriminant analysis (LDA) or LDA using the Chrenoff criterion.
Causes of cyberbullying in multi-player online gaming environments: Gamer perceptions

Cyberbullying has received much attention in recent years due to a variety of resulting tragic events, including cyberbully victim suicides. However, research on cyberbullying in online gaming environments is relatively new and limited. Furthermore, existing research primarily focuses on young adolescents, leaving research gaps for analyzing cyberbullying among older gamers. This is particularly important since it is estimated that 68% of gamers are 18 years of age or older. Finally, causes of aggressive behavior, such as cyberbullying, are still unclear and cannot simply be linked to violent video games. Therefore, in order to develop strategies to mitigate cyberbullying in online gaming environments, we need to better understand what the biggest causes of cyberbullying are in this environment. This exploratory research investigates gamer perceptions regarding the causes of cyberbullying in online multi-player gaming environments. A survey was developed for this study and 936 respondents answered several open ended questions related to causes of cyberbullying in gaming environments. Content analysis of these questions revealed that gamers perceive the biggest causes are: anonymity, the cyberbully not seeing the real life effects of their behaviors, and no fear of punishment.
Symbol error probability analysis of MIMO-relay multiplexing scheme in IEEE 802.16j systems

This paper presents the symbol error probability (SEP) analysis of MIMO-relay multiplexing configuration for IEEE 802.16j systems. The availability of multiple MIMO relay paths in IEEE 802.16j motivates two relay configurations: i) Relay Diversity and ii) Relay Multiplexing. Existing works have focused on the relay diversity methods. In this paper, we explore the relay multiplexing alternative where relay stations (RSs) are deployed to act as independent data pipes for transmitting multiple independent data streams from the Base Station (BS) to the Mobile Station (MS). We derive analytical expressions for the SEP performance of the proposed scheme, and also complement the analysis with simulations. It is observed from our SEP results that MIMO-relay multiplexing approach is practicable, when the number of antennas at the BS and MS are equal or greater than the total number of antennas on all RSs. In such scenarios, parallel relaying of independent data streams via different RSs offers acceptable SEP performance while boosting the capacity of the system linearly with the number of parallel RSs.
Serotonin 1B Receptor Gene (HTR1B) Methylation as a Risk Factor for Callous-Unemotional Traits in Antisocial Boys

The serotonin system is thought to play a role in the aetiology of callous-unemotional (CU) traits in children. Previous research identified a functional single nucleotide polymorphism (SNP) from the promoter region of the serotonin 1B receptor gene as being associated with CU traits in boys with antisocial behaviour problems. This research tested the hypothesis that CU traits are associated with reduced methylation of the promoter region of the serotonin 1B receptor gene due to the influence of methylation on gene expression. Participants (N = 117) were boys with antisocial behaviour problems aged 3-16 years referred to University of New South Wales Child Behaviour Research Clinics. Participants volunteered a saliva sample from which the genotype of a SNP from the promoter region of the serotonin 1B receptor gene and the methylation levels of 30 CpG sites from 3 CpG regions surrounding the location of this polymorphism were assayed. Lower levels of serotonin 1B receptor gene methylation were associated with higher levels of CU traits. This relationship, however, was found to be moderated by genotype and carried exclusively by two CpG sites for which levels of methylation were negatively associated with overall methylation levels in this region of the gene. Results provide support to the emerging literature that argues for a genetically-driven system-wide alteration in serotonin function in the aetiology of CU traits. Furthermore, the results suggest that there may be two pathways to CU traits that involve methylation of the serotonin 1B receptor gene; one that is driven by a genotypic risk and another that is associated with risk for generally increased levels of methylation. Future research that aims to replicate and further investigate these results is required.
Using Recommenders for Discretionary Access Control

Enterprises increasingly subscribe to Software as a Service (SaaS) applications for collaboration. In the past, enterprise organizational boundaries have been key to the controls on sharing, providing both a social and technical boundary that can slow or stop potentially inappropriate sharing. However, SaaS collaboration technology is often used to across enterprise boundaries. One of the key security concerns with this migration of in-enterprise, on-premises applications to application clouds is that of information flow across enterprise boundaries and specifically how this may be monitored and controlled. Business use of collaboration systems requires end-users to rapidly make a multitude of discretionary access control decisions. Many of the features that lower friction in collaboration can encourage user slip ups, and traditional notions of access control, such as RBAC are not very usable by people without information security experience, nor is it amenable for low overhead business collaborations. This paper proposes using recommender systems for proposing discretionary access control policies. Specifically, to notice similar patterns of use for similar content and to suggest access control policies derived from context and prior communication patterns based on past interactions.
Enriched Environment Prevents Hypobaric Hypoxia Induced Memory Impairment and Neurodegeneration: Role of BDNF/PI3K/GSK3β Pathway Coupled with CREB Activation

Adverse environmental conditions such as hypobaric hypoxia (HH) cause memory impairment by affecting cellular machinery leading to neurodegeneration. Providing enriched environment (EE) is found to be beneficial for curing several neurodegenerative disorders. The protective role of EE in preventing HH induced neuronal death has been reported previously but the involved mechanism is still not clearly understood. The present study is an attempt to verify the impact of EE on spatial memory during HH and also to explore the possible role of neurotrophin in EE mediated neuroprotection. Signaling mechanism involved in neuroprotection was also explored. Male Sprague Dawley rats were simulated to HH condition in an Animal Decompression Chamber at an altitude of 25000 feet in standard and enriched cages for 7 days. Spatial memory was assessed through Morris Water Maze. Role of different neurotrophins was explored by gene silencing and inhibitors for their respective receptors. Further, using different blockers signaling pathway was also explored. Finding of the present study suggested that EE prevents HH mediated memory impairment and neurodegeneration. Also brain-derived neurotrophic factor (BDNF) plays a major role in EE mediated neuroprotection and it effectively prevented neurodegeneration by activating PI3K/AKT pathway resulting in GSK3β inactivation which further inhibits apoptosis. Moreover GSK3β phosphorylation and hence its inactivation upregulates CREB phosphorylation which may also accounts for activation of survival machinery in cells and provides neuroprotection. From these observations it can be postulated that EE has a therapeutic potential in amelioration of HH induced memory impairment and neurodegeneration. Hence it may be used as a non invasive and non pharmacological intervention against various neurological disorders.
Downregulation of DAB2IP results in cell proliferation and invasion and contributes to unfavorable outcomes in bladder cancer

The DOC‐2/DAB2 interactive protein (DAB2IP) is a member of the Ras GTPase‐activating protein family. It has been shown to be often downregulated and a poor prognostic factor in several human malignancies. In this study, we analyzed the clinicopathological features and outcomes of DAB2IP expression in 135 patients with urothelial carcinoma of the bladder (UCB) treated by radical cystectomy plus bilateral lymph node dissection, and evaluated the effect of DAB2IP knockdown in vitro using the MTT method, colony formation assay, cell cycle assay, and cell migration and invasive assay. We found low expression of DAB2IP was significantly associated with high pathological stage (P = 0.002), high pathological grade (P = 0.02), tumor size more than 3 cm (P = 0.04), and presence of histological variants (P = 0.01). DAB2IP was an independent prognostic factor of disease recurrence (hazard ratio, 2.67; P = 0.034) and cancer‐specific survival (hazard ratio, 2.79; P = 0.038). Knockdown of DAB2IP could promote cell proliferation, migration, and invasion. Downregulation of DAB2IP could activate the ERK and Akt pathways and was correlated with the expression of epithelial–mesenchymal transition markers, such as E‐cadherin and vimentin. In conclusion, downregulation of DAB2IP is associated with features of biologically aggressive UCB and results in cell proliferation, migration, and invasion of bladder cancer. DAB2IP may serve as a promising biomarker in patients with UCB treated by radical cystectomy and bilateral lymph node dissection.
Multipath routing over wireless mesh networks for multiple description video transmission

In the past few years, wireless mesh networks (WMNs) have drawn significant attention from academia and industry as a fast, easy, and inexpensive solution for broadband wireless access. In WMNs, it is important to support video communications in an efficient way. To address this issue, this paper studies the multipath routing for multiple description (MD) video delivery over IEEE 802.11 based WMN. Specifically, we first design a framework to transmit MD video over WMNs through multiple paths; we then investigate the technical challenges encountered. In our proposed framework, multipath routing relies on the maximally disjoint paths to achieve good traffic engineering performance. However, video applications usually have strict delay requirements, which make it difficult to find multiple qualified paths with the least joints. To overcome this problem, we develop an enhanced version of Guaranteed-Rate (GR) packet scheduling algorithm, namely virtual reserved rate GR (VRR-GR), to shorten the packet delay of video communications in multiservice network environment. Simulation study shows that our proposed approach can reduce the latency of video delivery and achieve desirable traffic engineering performance in multipath routing environment.