Miracle-dz/UniFAR-FTUs huggingface dataset:
An adaptive macroblock-group coding algorithm for progressive and interlaced video

The paper proposes a new data structure called macroblock group (MBG). The MBG structure unifies the progressive and interlaced date into one general data format, thus enables a unifying process framework to conduct the progressive and interlaced video coding. Upon the new data structure, an adaptive MBG coding (A-MBG) method undertakes two-stage coding process, and it can well use the calculated and estimated encoding cost to select the best one among the MBG types, thus can finely adapt to the local contents of the pictures. The experiments are taken in comparison with the newly finalized H.264 standard. A-MBG shows an outperforming result to that of MBAFF in coding efficiency. In addition, because of using the same structure for both progressive and interlaced video, the structure complexity of A-MBG would be lower than that of MBAFF.
GASPP: A GPU-Accelerated Stateful Packet Processing Framework

Graphics processing units (GPUs) are a powerful platform for building high-speed network traffic processing applications using low-cost hardware. Existing systems tap the massively parallel architecture of GPUs to speed up certain computationally intensive tasks, such as cryptographic operations and pattern matching. However, they still suffer from significant overheads due to critical-path operations that are still being carried out on the CPU, and redundant inter-device data transfers. In this paper we present GASPP, a programmable network traffic processing framework tailored to modern graphics processors. GASPP integrates optimized GPU-based implementations of a broad range of operations commonly used in network traffic processing applications, including the first purely GPU-based implementation of network flow tracking and TCP stream reassembly. GASPP also employs novel mechanisms for tackling control flow irregularities across SIMT threads, and sharing memory context between the network interface and the GPU. Our evaluation shows that GASPP can achieve multi-gigabit traffic forwarding rates even for computationally intensive and complex network operations such as stateful traffic classification, intrusion detection, and packet encryption. Especially when consolidating multiple network applications on the same device, GASPP achieves up to 16.2× speedup compared to standalone GPU-based implementations of the same applications.
Interactions between Obsessional Symptoms and Interpersonal Ambivalences in Psychodynamic Therapy: An Empirical Case Study

The classical symptom specificity hypothesis (Blatt, 1974) particularly associates obsessional symptoms to interpersonal behavior directed at autonomy and separation from others. Cross-sectional group research, however, has yielded inconsistent findings on this predicted association, and a previous empirical case study (Cornelis et al., in press; see Chapter 2) documented obsessional pathology to be rooted in profound ambivalences between autonomous and dependent interpersonal dynamics. Therefore, in the present empirical case study, concrete operationalizations of the classical symptom specificity hypothesis are contrasted to alternative hypotheses based on the observed complexities in Chapter 2. Dynamic associations between obsessional symptoms and interpersonal functioning is further explored, aiming at further contribution to theory building (i.e., through suggestions for potential hypothesis-refinement; Stiles, 2009). Similar to the first empirical case study (Chapter 1), Consensual Qualitative Research for Case studies is used to quantitatively and qualitatively describe the longitudinal, clinical interplay between obsessional symptoms and interpersonal dynamics throughout the process of supportive-expressive psychodynamic therapy. In line with findings from Chapter 1, findings reveal close associations between obsessions and interpersonal dynamics, and therapist interventions focusing on interpersonal conflicts are documented as related to interpersonal and symptomatic alterations. Observations predominantly accord to the ambivalence-hypothesis rather than to the classical symptom specificity hypothesis. Yet, meaningful differences are observed in concrete manifestations of interpersonal ambivalences within significant relationships. Findings are again discussed in light of conceptual and methodological considerations; and limitations and future research indications are addressed.
Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance

Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non–Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2–5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial.
The TALP Ngram-based SMT systems for IWSLT 2006

This paper describes TALPtuples, the 2006 Ngrambased statistical machine translation system developed at the TALP Research Center of the UPC (Universitat Polit ecnica de Catalunya) in Barcelona. Emphasis is put on improvements and extensions of the system of previous years, being highlighted and empirically compared. Mainly, these include a novel and much more efcient word ordering strategy based on reordering patterns, a linguistically-guided tuple segmentation criterion and improved optimization procedures. The paper provides details of this system participation in the third International Workshop on Spoken Language Translation (IWSLT) held in Kyoto, Japan in November 2006. Results on four translation directions are reported, namely from Arabic, Chinese, Italian and Japanese into English for the open data track, thoroughly explaining all language-related preprocessing and optimization schemes.
Production of Mallee Biomass in Western Australia: Life Cycle Greenhouse Gas Emissions

In Western Australia (WA), mallee eucalypts are being developed to provide woody crops for wheat belt farmers as part of a strategy to tackle a range of conservation issues including dry land salinity. Our recent study shows that mallee production achieves strong energy gain with an energy ratio of 41.7 and an energy productivity of 206.3 GJ/(ha year). However, the viability of mallee biomass as a resource for bioenergy and industrial products is not only determined by the energy performance, but also the economic and environmental performances. This study continues our work and focuses on the analysis of life cycle greenhouse gas (GHG) emissions during mallee biomass production in WA, in order to evaluate the potential of mallee biomass in GHG emission reduction as feedstock for the production of bioenergy and biofuels. The life cycle GHG emissions analysis during mallee biomass production exhaustively accounts for all activities and processes which may involve direct or indirect GHG emissions. Our results show that the total GHG emissions during mallee biomass production for farm size of 7 km 7 km and road transport distance of 70 km are estimated to be 535.5 kg CO2{-e} per hectare per year, equivalent to 27.9 kg CO2{-e}e per green tonne mallee biomass. The total GHG sequestered by above-ground mallee biomass is 19394.4 kg CO2{-e} per hectare per year, equivalent to 1010.1 kg CO2{-e} per green tonne mallee biomass. Non-renewable GHG emissions during the full life cycle of biomass production is less than 3% of the GHG sequestered by above-ground mallee biomass, indicating mallee biomass production in WA is close to carbon neutral. It is also important to note that 72% of total non-renewable GHG emissions during mallee biomass production occur in biomass harvest and transport, arising mainly from the use of fossil fuels. GHG emissions from soil due to the use of fertilisers also contribute to 23% (8% from fertilizer production, and 15% from fertilizer application) of the total non-renewable GHG emissions during the full life cycle. The biomass produced per hectare per year leads to the GHG reduction of 18.86 tonnes CO2{-e}, providing great GHG mitigation potential. Road transport distance is found to have significant influence on total GHG emissions for delivered mallee biomass. With road transport distance increasing from 10 to 250 km, GHG emissions from road transport increase from 2.3 to 36.2 kg CO2{-e} per green tonne, leading to total GHG emissions increasing from 19.5 to 53.4 kg CO2{-e}/gt. GHG emissions for different plant capacities and proportions of land planted to mallee are also analysed based on a discrete transport model.
Abnormal Chloride Homeostasis in the Substancia Nigra Pars Reticulata Contributes to Locomotor Deficiency in a Model of Acute Liver Injury

Background Altered chloride homeostasis has been thought to be a risk factor for several brain disorders, while less attention has been paid to its role in liver disease. We aimed to analyze the involvement and possible mechanisms of altered chloride homeostasis of GABAergic neurons within the substantia nigra pars reticulata (SNr) in the motor deficit observed in a model of encephalopathy caused by acute liver failure, by using glutamic acid decarboxylase 67 - green fluorescent protein knock-in transgenic mice. Methods Alterations in intracellular chloride concentration in GABAergic neurons within the SNr and changes in the expression of two dominant chloride homeostasis-regulating genes, KCC2 and NKCC1, were evaluated in mice with hypolocomotion due to hepatic encephalopathy (HE). The effects of pharmacological blockade and/or activation of KCC2 and NKCC1 functions with their specific inhibitors and/or activators on the motor activity were assessed. Results In our mouse model of acute liver injury, chloride imaging indicated an increase in local intracellular chloride concentration in SNr GABAergic neurons. In addition, the mRNA and protein levels of KCC2 were reduced, particularly on neuronal cell membranes; in contrast, NKCC1 expression remained unaffected. Furthermore, blockage of KCC2 reduced motor activity in the normal mice and led to a further deteriorated hypolocomotion in HE mice. Blockade of NKCC1 was not able to normalize motor activity in mice with liver failure. Conclusion Our data suggest that altered chloride homeostasis is likely involved in the pathophysiology of hypolocomotion following HE. Drugs aimed at restoring normal chloride homeostasis would be a potential treatment for hepatic failure.
Boost SAT Solver with Hybrid Branching Heuristic

Most state-of-the-art satisfiability (SAT) solvers are capable of solving large application instances with efficient branching heuristics. The VSIDS heuristic is widely used because of its robustness. This paper focuses on the inherent ties in VSIDS and proposes a new branching heuristic called TBVSIDS, which attempts to break the ties with the consideration of the interplay between the branching heuristic and learned clauses. However, a branching heuristic cannot cover all problems, and its performance improves when combined with an appropriate configuration. Therefore, we also propose a hybrid model of branching heuristics based on random forest. The efficiencies of TBVSIDS and hybrid branching heuristics are evaluated on benchmarks in SAT Competitions. By constructing a model that reduces the overfitting problem, we hope to realize a hybrid branching heuristic that is widely applicable to other solvers.
High performance embedded domain specific languages

Today, all high-performance computer architectures are parallel and heterogeneous; a combination of multiple CPUs, GPUs and specialized processors. This creates a complex programming problem for application developers. Domain-specific languages (DSLs) are a promising solution to this problem because they provide an avenue for application-specific abstractions to be mapped directly to low level architecture-specific programming models providing high programmer productivity and high execution performance. In this talk I will describe our approach to building high performance DSLs, which is based on embedding in Scala, light-wieght modular staging and a DSL infrastructure called Delite. I will describe how we transform impure functional programs into efficient first-order low-level code using domain specific optimization, parallelism optimization, locality optimization, scalar optimization, and architecture-specific code generation. All optimizations and transformations are implemented in an extensible DSL compiler architecture that minimizes the programmer effort required to develop a new DSL.
Monocyte rolling, arrest and spreading on IL-4-activated vascular endothelium under flow is mediated via sequential action of L-selectin, beta 1-integrins, and beta 2-integrins

Leukocyte interactions with vascular endothelium at sites of inflammation can be dynamically regulated by activation-dependent adhesion molecules. Current models, primarily based on studies with polymorphonuclear leukocytes, suggest the involvement of multiple members of the selectin, integrin, and immunoglobulin gene families, sequentially, in the process of initial attachment (rolling), stable adhesion (arrest), spreading and ultimate diapedesis. In the current study, IL-4-activated human umbilical vein endothelium, which selectively expresses VCAM-1 and an L-selectin ligand but not E- selectin, and appropriate function blocking monoclonal antibodies, were used to study monocyte-endothelial interactions in an in vitro model that mimics microcirculatory flow conditions. In this system, L- selectin mediates monocyte rolling and also facilitates alpha 4 beta 1- integrin-dependent arrest, whereas beta 2-integrins are required for spreading of firmly attached monocytes on the endothelial cell surface but not their arrest. These findings provide the first in vitro evidence for human monocyte rolling on cytokine-activated endothelium, and suggest a sequential requirement for both beta 1- and beta 2- integrin-dependent adhesive mechanisms in monocyte-endothelial interactions.
BinCFP: Efficient Multi-threaded Binary Code Control Flow Profiling

In many tasks of reverse engineering and binary code analysis (e.g., hybrid disassembly, resolving indirect jump, and decoupled taint analysis), the knowledge of detailed dynamic control flow can be of great value. However, the high runtime overhead beset the complete collection of dynamic control flow. The previous efforts on efficient path profiling cannot be directly applied to the obfuscated binary code in which an accurate control flow graph is typically absent. To address these challenges, we present BinCFP, an efficient multi-threaded binary code control flow profiling tool by taking advantage of pervasive multi-core platforms. BinCFP relies on dynamic binary instrumentation to work with the unmodified binary code. The key of BinCFP is a multi-threaded fast buffering scheme that supports processing trace buffers asynchronously. To achieve better performance gains, we also apply a set of optimizations to reduce control flow profile size and instrumentation overhead. Our design enables the complete dynamic control flow collection for an obfuscated binary execution. We have implemented BinCFP on top of Pin. The comparative experiments on SPEC2006 and obfuscated common utility programs show BinCFP outperforms the previous work in several ways. In addition, BinCFP's control flow profile sizes are only about 49.2% that of the conventional design.
Lightweight Jammer Localization in Wireless Networks: System Design and Implementation

Jamming attacks have become prevalent during the last few years, due to the shared nature and the open access to the wireless medium. Finding the location of a jamming device is of great importance for restoring normal network operations. After detecting the malicious node we want to find its position, in order for further security actions to be taken. Our goal in this paper is the design and implementation of a simple, lightweight and generic localization algorithm. Our scheme is based on the principles of the gradient descent minimization algorithm. The key observation is that the Packet Delivery Ratio (PDR) has lower values as we move closer to the jammer. Hence, the use of a gradient-based scheme, operating on the discrete plane of the network topology, can help locate the jamming device. The contributions of our work are the following: (a) We demonstrate, through analysis and experimentation, the way that the jamming effects propagate through the network in terms of the observed PDR. (b) We design a distributed, lightweight jammer localization system which does not require any modifications to the driver/firmware of commercial NICs. (c) We implement and evaluate our localization system on our 802.11 indoor testbed. An attractive and important feature of our system is that it does not rely on special hardware.
Toward Beneficial Transformation of Enterprise Workloads to Hybrid Clouds

With the promise of providing flexible and elastic computing resources on demand, the cloud computing has been attracting enterprises and individuals to migrate workloads in the legacy environment to the public/private/hybrid clouds. However, the workload migration is often interpreted as an image migration or re-installation/data copying as the exact snapshot of the source machine, and the various cloud platforms and service models are rarely taken into consideration during migration planning. Thus, the cloud migration techniques have not provided enough options that can satisfy the various migration requirements. In this paper, we propose a model to tackle the migration challenges that transforms one resource into the same or another resource in hybrid clouds. We formulate the problem as a constraint satisfaction problem, and iteratively decompose the server components and consolidate the servers. Furthermore, we propose a compute-network mapping algorithm to match computing resources with network resources to guarantee network affinity. The ultimate goal is to recommend the optimal target cloud platform with network affinity and the minimum cost. Through the evaluation of the proposed model using real enterprise datasets (up to 2012 machines), we prove that the proposed model satisfies the goal. We show that when migrating into virtualized cloud environments, thorough resource planning can reduce 16% of current resources, 5%-10% servers can be consolidated, and more than 60% servers are possible candidates for server decomposition.
Excitable and Synaptic Properties of Neurons of Mouse Bed Nucleus of the Stria Terminalis: Differential Dorsal and Ventral Distribution of Excitable Properties

The bed nucleus of the stria terminalis (BNST) is a structure uniquely positioned to integrate stress information and regulate both stress and reward systems. Consistent with this arrangement, evidence suggests that the BNST, and in particular the noradrenergic input to this structure, is a key component of affective responses to drugs of abuse. We have utilized an in vitro slice preparation from adult mouse to determine synaptic and membrane properties of these cells, focusing on the dorsal and ventral subdivisions of the anterolateral BNST (dBNST and vBNST) because of the differential noradrenergic input to these two regions. We find that while resting membrane potential and input resistance are comparable between these subdivisions, excitable properties, including a low-threshold spike (LTS) likely mediated by T-type calcium channels and an Ih dependent potential are differentially distributed. IPSPs and EPSPs are readily evoked in both dBNST and vBNST. The fast IPSP is predominantly GABAA-receptor mediated and is partially blocked by the AMPA/kainate-receptor antagonist CNQX. In the presence of the GABAA-receptor antagonist picrotoxin, cells in dBNST but not vBNST are more depolarized and have a higher input resistance, suggesting tonic GABAergic inhibition of these cells. The EPSPs elicited in BNST are monosynaptic, exhibit paired pulse facilitation, and contain both an AMPAand an NMDA-receptor mediated component. These data support the hypothesis that neurons of the dorsal and ventral BNST differentially integrate synaptic input, which is likely of behavioral significance. The data also suggest mechanisms by which information may flow through stress and reward circuits. Electrophysiological properties of the BNST
An Intercomparison of Methods for Finding Coupled Patterns in Climate Data

Abstract This paper introduces a conceptual framework for comparing methods that isolate important coupled modes of variability between time series of two fields. Four specific methods are compared: principal component analysis with the fields combined (CPCA), canonical correlation analysis (CCA) and a variant of CCA proposed by Barnett and Preisendorfer (BP), principal component analysis of one single field followed by correlation of its component amplitudes with the second field (SFPCA), and singular value decomposition of the covariance matrix between the two fields (SVD). SVD and CPCA are easier to implement than BP, and do not involve user-chosen parameters. All methods are applied to a simple but geophysically relevant model system and their ability to detect a coupled signal is compared as parameters such as the number of points in each field, the number of samples in the time domain, and the signal-to-noise ratio are varied. In datasets involving geophysical fields, the number of sampling times ma.
Application of GSA optimized PI controller parameters in automatic generation control for interconnected power system

Gravitational search algorithm (GSA) based Proportional-Integral (PI) controller for Automatic Generation Control (AGC) of an interconnected power system are analyzed the performance of the proposed two area non-reheat thermal system. GSA optimization employed to search for optimization controller parameters by minimizing the objective function. The objective function uses Integral Time multiply Absolute Error (ITAE) in order to increase the performance of the controller. The performance of the proposed PI controller is compared by tuning the GSA technique and best controller is compared to GA optimized PI controller over wide range of operating condition and change in system parameter.