Miracle-dz/UniFAR-FTUs huggingface dataset:
Tiered Byzantine-Fault Tolerance for Long-Term Integrity ∗

Long-term services that operate reliably are hard to construct. In this paper, we argue that for long-term services we need a stronger service property called Healthy-WriteImplies-Correct-Read (HWICR): once a value is written in a healthy period (i.e., when the system’s fault assumption is not violated), the value is correctly read despite intervening unhealthy periods. To build services with the HWICR property, we adapt the traditional Byzantine-fault model to atiered fault model, that allows customizing fault assumptions to different system components; the refined fault model allows services with a long-term horizon to handle the inevitable but rare violations of more traditional fault assumptions. As a specific case study, we present TimeMachine, a Byzantine-fault tolerant keyvalue store that provides the HWICR property under a three-tier fault model. We justify the design and tiered fault model behind TimeMachine, present an implementation, and show experimental results suggesting it is a practical solution to the long-open problem of long-term archival storage integrity.
A new type of quaternionic frame in ℝ4

In this paper, we obtain a new version of Serret-Frenet formulae for quaternionic curve in [Formula: see text] by using a method similar to the method given by Bharathi and Nagaraj and called it Type 2-Quaternionic Frame. Also, we give an application of this new type of the quaternionic frame by an example.
Coalition formation with spatial and temporal constraints

The coordination of emergency responders and robots to undertake a number of tasks in disaster scenarios is a grand challenge for multi-agent systems. Central to this endeavour is the problem of forming the best teams (coalitions) of responders to perform the various tasks in the area where the disaster has struck. Moreover, these teams may have to form, disband, and reform in different areas of the disaster region. This is because in most cases there will be more tasks than agents. Hence, agents need to schedule themselves to attempt each task in turn. Second, the tasks themselves can be very complex: requiring the agents to work on them for different lengths of time and having deadlines by when they need to be completed. The problem is complicated still further when different coalitions perform tasks with different levels of efficiency. Given all these facets, we define this as The Coalition Formation with Spatial and Temporal constraints problem (CFSTP). We show that this problem is NP-hard---in particular, it contains the well-known complex combinatorial problem of Team Orienteering as a special case. Based on this, we design a Mixed Integer Program to optimally solve small-scale instances of the CFSTP and develop new anytime heuristics that can, on average, complete 97% of the tasks for large problems (20 agents and 300 tasks). In so doing, our solutions represent the first results for CFSTP.
Does Self-Efficacy Mediate the Relationship between Parenting Style and Adolescent Fruit and Vegetable Consumption?

Background: Inadequate fruit and vegetable (FV) consumption is a serious public health issue in children and adolescents that is influenced by the type of parenting style and one’s self-efficacy. Purpose: The purpose of the study was to determine the association between parenting style and adolescent FV consumption and whether adolescent self-efficacy mediates this relationship. Methods: Data retrieved from the Family, Life, Activity, Sun, Health, and Eating (FLASHE) study were used to perform statistical analyses on 1,382 parent – adolescent dyads. A mediation analysis using the causal steps approach was used to determine whether adolescent self-efficacy mediated the effect of parenting style on adolescent FV consumption. Multiple linear regression and binary logistic regression were used, adjusting for confounding due to demographics. Results: There was a significant positive association between authoritative parenting style and adolescent FV consumption (B = .127, 95% CI = .052, .203, p = .001); however, after controlling for adolescent self-efficacy, the parenting style effect was attenuated and no longer statistically significant (B = .061, 95% CI = -.011, .133, p = .095). The reduction in the beta coefficient indicated a partial mediation of self-efficacy on the association between parenting style and adolescent FV consumption. Conclusion: The study showed a positive significant association between authoritative parenting and adolescent fruit and vegetable consumption, partially mediated by adolescent self-efficacy. More authoritative parenting was associated with greater adolescent FV consumption. Healthcare professionals should encourage parents to practice an authoritative parenting style and emphasize the benefits associated with parental support and affection.
Metachronous pancreatic cancer originating from disseminated founder pancreatic intraductal neoplasias (PanINs)

Clonal populations originated from benign‐looking ‘founder cells' may spread widely within pancreas instead of being localized in situ before frank pancreatic ductal adenocarcinoma (PDA) can be detected. Metachronous PDA is not common event, and we here sought to define potent origin of multiple PDAs developed in a woman using advanced genetics technologies. Curative resection of pancreatic head tumour was performed; however, ‘recurrent' lesions in the remnant pancreas were found 3.5 years later and total pancreatectomy was subsequently performed. The metachronous lesions were morphologically similar to the primary PDA. Using a next‐generation sequencing and digital PCR, all three PDAs were shown to possess rare somatic mutations in KRAS (p.T58I & p.Q61H). Curiously, identical KRAS mutations were found in low‐grade ‘intraepithelial' lesions, which localized in normal area of the pancreas and one of them possessed p53 mutation, which was also found in the PDAs. The footprint of the tumour evolution marked by mutational profiling supports a human correlate to the mouse models of ‘dissemination' occurring at the earliest stages of pancreatic neoplasia.
Distortion-Resistant Hashing for rapid search of similar DNA subsequence

One of the basic tasks in bioinformatics is localizing a short subsequence $S$, read while sequencing, in a long reference sequence $R$, like the human geneome. A natural rapid approach would be finding a hash value for $S$ and compare it with a prepared database of hash values for each of length $|S|$ subsequences of $R$. The problem with such approach is that it would only spot a perfect match, while in reality there are lots of small changes: substitutions, deletions and insertions. This issue could be repaired if having a hash function designed to tolerate some small distortion accordingly to an alignment metric (like Needleman-Wunch): designed to make that two similar sequences should most likely give the same hash value. This paper discusses construction of Distortion-Resistant Hashing (DRH) to generate such fingerprints for rapid search of similar subsequences. The proposed approach is based on the rate distortion theory: in a nearly uniform subset of length $|S|$ sequences, the hash value represents the closest sequence to $S$. This gives some control of the distance of collisions: sequences having the same hash value.
Double Updating Online Learning

In most kernel based online learning algorithms, when an incoming instance is misclassified, it will be added into the pool of support vectors and assigned with a weight, which often remains unchanged during the rest of the learning process. This is clearly insufficient since when a new support vector is added, we generally expect the weights of the other existing support vectors to be updated in order to reflect the influence of the added support vector. In this paper, we propose a new online learning method, termed Double Updating Online Learning, or DUOL for short, that explicitly addresses this problem. Instead of only assigning a fixed weight to the misclassified example received at the current trial, the proposed online learning algorithm also tries to update the weight for one of the existing support vectors. We show that the mistake bound can be improved by the proposed online learning method. We conduct an extensive set of empirical evaluations for both binary and multi-class online learning tasks. The experimental results show that the proposed technique is considerably more effective than the state-of-the-art online learning algorithms. The source code is available to public at http://www.cais. ntu.edu. sg/~chhoi/DUOL/.
Efficient VLSI design of a pulse shaping filter and DAC interface for W-CDMA transmission

This paper presents the design and VLSI implementation of a pulse shaping filter architecture for FDD W-CDMA transmission satisfying 3GPP specifications. We first study a filter design method to find the minimum number of coefficients and bits per coefficients to achieve the 3GPP requirements. Then, we propose a multiplierless linear phase FIR filter architecture implemented with an oversampling factor of four and minimizing size and power consumption. Design and requirements of the postfiltering elements and DAC interface are also defined. The implementation has been tested with an overall baseband transmission chain and results concerning the hardware complexity are given.
Dual-Space Feedforward Control of a Redundantly Actuated Parallel Manipulator for Very High Speed Applications

This paper deals with dual-space control of R4 redundantly actuated parallel manipulator for very high acceleration applications. This controller consists in a PID in the Cartesian space complied with a feedforward of the desired acceleration in both Cartesian and articular spaces for tracking performance improvements: models show that this “dual-space” control strategy is an efficient way to implement computed torque control. For comparison purposes, experiments were made with a Cartesian PID until 20G. Experimental results show that the proposed control scheme is considerably better than the PID in the Cartesian space, and that a good tracking performance could be achieved even for the very high acceleration of 40G (equivalent to more than 425 pick-and-place cycles per minute).
USE OF A MULTI-OFFSET BOREHOLE-RADAR REFLECTION METHOD IN FRACTURED CRYSTALLINE BEDROCK AT MIRROR LAKE, GRAFTON COUNTY,

Multi-offset, single-hole, borehole-radar reflection surveys were conducted at the U.S. Geological Survey Fractured Rock Research Site at Mirror Lake, in Grafton County, New Hampshire. The study was conducted to evaluate the benefits of applying multi-offset seismic processing techniques to borehole-radar reflection surveys in fractured rock. The multi-offset reflection surveys were conducted in conjunction with a saline tracerinjection experiment. During injection, a sodium chloride (NaCl) solution was continuously pumped into a hydraulically conductive zone that was isolated by specially constructed, reusable, PVC straddle packers suspended from PVC casing. Eight common-offset borehole reflection profiles were collected within the PVC-sleeved portion of the borehole before and during the tracer injection. The offset between the transmitter and receiver antennas ranged from 6.4 to 9.9 m (meters). The common offset data were filtered, sorted into common distance-point (CDP) gathers, normal move-out (NMO) corrected, and stacked to produce a zero-offset borehole CDP profile. Comparison of the common-offset and CDP profiles indicates that multi-offset data acquisition and CDP processing; (1) increases the resolution of reflectors near the borehole, (2) decreases the effects of direct wave coupling, antenna ringing, and system noise, and (3) improves the clarity of difference images used to identify the effects of saline tracer on reflections from transmissive fractures.
Piecewise Toeplitz matrices-based sensing for rank minimization

This paper proposes a set of piecewise Toeplitz matrices as the linear mapping/sensing operator A : R<sup>n</sup><sub>1</sub>×<sup>n</sup><sub>2</sub> → R<sup>M</sup> for recovering low rank matrices from few measurements. We prove that such operators efficiently encode the information so there exists a unique reconstruction matrix under mild assumptions. This work provides a significant extension of the compressed sensing and rank minimization theory, and it achieves a tradeoff between reducing the memory required for storing the sampling operator from O(n<sub>1</sub>n<sub>2</sub>M) to O(max(n<sub>1</sub>, n<sub>2</sub>)M) but at the expense of increasing the number of measurements by r. Simulation results show that the proposed operator can recover low rank matrices efficiently with a reconstruction performance close to the cases of using random unstructured operators.
Local Linear Models adaptation for a 4 Inj — 2PP common-rail pressure system

The implementation of a Neuro-Fuzzy nonlinear adaptive structure, with Local Linear Models (LLM), designed for fuel pressure estimation in diesel common-rail (CR) hydraulic system, represents the main topic. Hydraulic systems, in general, are nonlinear and engineers have often struggled to find the best solution to approximate the input-output dependencies. Powerful tools are necessary for splitting the input space in smaller pieces where linear approximations can be considered satisfactory. Neuro-Fuzzy networks, combined with LLM represent the best solution in this case. Using appropriate numerical models, these architectures can be implemented in a real-time environment designed for on-line adaptation of the linear models parameters. The paper demonstrates that the LLMs, and hence, the whole dynamic models parameters of the CR's NeuroFuzzy developed architecture, can be adapted in an on-line environment. The practical results are favorable.
Production of HIV-1 by resting memory T lymphocytes

BackgroundThe persistence of HIV-1 within resting memory CD4 T cells constitutes a major obstacle in the control of HIV-1 infection. ObjectiveTo examine the expression of HIV-1 in resting memory CD4 T cells, using an in-vitro model. Design and methodsPhytohaemagglutinin-activated peripheral blood mononuclear cells were challenged with T cell-tropic and macrophage-tropic HIV-1 clones, and with a replication-incompetent and non-cytotoxic HIV-1-derived vector (HDV) pseudotyped by the vesicular stomatitis virus glycoprotein G. To obtain resting memory CD4 T cells containing HIV-1 provirus, residual CD25+, CD69+ and HLA-DR+ cells were immunodepleted after a 3 week cultivation period. ResultsIn spite of the resting phenotype, the majority of provirus-harbouring T cells expressed HIV-1 genomes and produced infectious virus into cell-free supernatant. The expression of HDV dropped by only 30% during the return of activated HDV-challenged cells into the quiescent phase. Although resting memory T cells generated in vitro expressed HIV-1 and HDV genome when infected during the course of the preceding T cell activation, they were resistant to HIV-1 and HDV challenge de novo. The infected culture of resting memory T cells showed a higher resistance to the cytotoxic effects of HIV-1 in comparison with the same cultures after reactivation by phytohaemagglutinin. ConclusionThe majority of resting memory T cells infected during the course of a preceding cell activation produces virus persistently, without establishing a true HIV-1 latency. The described system could be used as a model for testing new drugs able to control residual HIV-1 replication in resting memory T cells.
Jackal, A Compiler Based Implementation of Java for Clusters of Workstations

This paper describes the design of Jackal, a compiler-driven distributed shared memory implementation of the Java programming language. Our goal is to efficiently execute (unmodified) multithreaded Java programs on a cluster of workstations. Jackal consists of a native Java compiler and a runtime system that implements a distributed shared memory protocol for variable sized memory regions. The Jackal compiler stores Java objects in shared regions and augments the programs it compiles with access checks. These access checks drive the memory consistency protocol. The Jackal compiler implements several optimizations to reduce the overhead of these software access checks. The main contributions of this paper are: techniques to allow a (Java) compiler to target a fine-grained allsoftware DSM using access-checks and compiler optimizations to achieve good efficiency.
Attentional performance is correlated with the local regional efficiency of intrinsic brain networks

Attention is a crucial brain function for human beings. Using neuropsychological paradigms and task-based functional brain imaging, previous studies have indicated that widely distributed brain regions are engaged in three distinct attention subsystems: alerting, orienting and executive control (EC). Here, we explored the potential contribution of spontaneous brain activity to attention by examining whether resting-state activity could account for individual differences of the attentional performance in normal individuals. The resting-state functional images and behavioral data from attention network test (ANT) task were collected in 59 healthy subjects. Graph analysis was conducted to obtain the characteristics of functional brain networks and linear regression analyses were used to explore their relationships with behavioral performances of the three attentional components. We found that there was no significant relationship between the attentional performance and the global measures, while the attentional performance was associated with specific local regional efficiency. These regions related to the scores of alerting, orienting and EC largely overlapped with the regions activated in previous task-related functional imaging studies, and were consistent with the intrinsic dorsal and ventral attention networks (DAN/VAN). In addition, the strong associations between the attentional performance and specific regional efficiency suggested that there was a possible relationship between the DAN/VAN and task performances in the ANT. We concluded that the intrinsic activity of the human brain could reflect the processing efficiency of the attention system. Our findings revealed a robust evidence for the functional significance of the efficiently organized intrinsic brain network for highly productive cognitions and the hypothesized role of the DAN/VAN at rest.
Carbon nanotube circuits: Living with imperfections and variations

Carbon Nanotube Field-Effect Transistors (CNFETs) can potentially provide significant energy-delay-product benefits compared to silicon CMOS. However, CNFET circuits are subject to several sources of imperfections. These imperfections lead to incorrect logic functionality and substantial circuit performance variations. Processing techniques alone are inadequate to overcome the challenges resulting from these imperfections. An imperfection-immune design methodology is required. We present an overview of imperfection-immune design techniques to overcome two major sources of CNFET imperfections: metallic Carbon Nanotubes (CNTs) and CNT density variations.
Movement Prediction Assisted Fast Handovers for Seamless IP Mobility

The use of cross layer communication in the form of link-layer triggers is a growing trend in mobility management schemes because traditional movement detection techniques are no longer suitable for fast handover protocols. Achieving seamless mobility is a major challenge for current and future wireless networks and is the focus of much research. This paper presents a prediction assisted fast handover protocol (PA-FMIP) that uses a data mining based prediction algorithm to replace the need for a pre-trigger. It is a continuation of previous work that aims to improve the packet loss problem inherent in reactive handovers. We further evaluate PA-FMIP through simulation and focus on the capabilities of the mobility prediction algorithm, particularly when faced with random mobility. The impact of a PA-FMIP handover for real-time and TCP application performance is also thoroughly evaluated. It is found that the data mining based prediction algorithm can achieve 100% accuracy for regular mobility. It is also found that the type of TCP used by the user significantly influences throughput. The improvement in the number of lost packets by PA-FMIP increases the overall throughput for any TCP variant.
Mediated Apoptosis T-Suppressor Cells from Tumors via FasL + Foxp3 + CD25 + Eliminate CD4 T-Effector/Memory Cells + Activated CD8

Tumor-resident CD8 (cid:1) T cells display a quiescent effector/memory phenotype that is maintained in part by inﬁltrating CD4 (cid:1) CD25 (cid:1) Foxp3 (cid:1) T-suppressor cells. Intratumoral delivery of IL-12, in contrast, can restore cytotoxic function to tumor-associated CD8 (cid:1) T cells and induce the apoptotic death of T-suppressor cells. Depletion of CD8 (cid:1) T cells from tumors before IL-12 treatment resulted in the abrogation of treatment-mediated T-suppressor cell apoptosis revealing a link between CD8 (cid:1) T cell activation and T-suppressor elimination. Furthermore, IL-12 failed to induce T-suppressor cell loss in IFN- (cid:2) - or FasL-deﬁcient mice demonstrating a requirement for IFN- (cid:2) and FasL in this process. Adoptive transfer of wild-type CD8 (cid:1) T cells to FasL-knockout mice restored posttherapy T-suppressor cell elimination from tumors establishing that expression of FasL on CD8 (cid:1) T cells was sufﬁcient to promote T-suppressor cell death. IL-12 failed to induce FasL on T-effectors in IFN- (cid:2) -knockout mice demonstrating a requirement for IFN- (cid:2) in FasL up-regulation. Adoptive transfer of wild-type CD8 (cid:1) T cells induced T-suppressor cell death in IFN- (cid:2) -knockout mice conﬁrming that autocrine IFN- (cid:2) was sufﬁcient for CD8 (cid:1) T cell FasL expression. These ﬁndings i.p. sterile PBS microsphere injec-tions
Treatment with the Antipsychotic Agent, Risperidone, Reduces Disease Severity in Experimental Autoimmune Encephalomyelitis

Recent studies have demonstrated that atypical antipsychotic agents, which are known to antagonize dopamine D2 and serotonin 5-HT2a receptors, have immunomodulatory properties. Given the potential of these drugs to modulate the immune system both peripherally and within the central nervous system, we investigated the ability of the atypical anti-psychotic agent, risperidone, to modify disease in the animal model of multiple sclerosis (MS)4, experimental autoimune encephalomyelitis (EAE). We found that chronic oral administration of risperidone dose-dependently reduced the severity of disease and decreased both the size and number of spinal cord lesions. Furthermore, risperidone treatment substantially reduced antigen-specific interleukin (IL)-17a, IL-2, and IL-4 but not interferon (IFN)-γ production by splenocytes at peak disease and using an in vitro model, we show that treatment of macrophages with risperidone alters their ability to bias naïve T cells. Another atypical antipsychotic agent, clozapine, showed a similar ability to modify macrophages in vitro and to reduce disease in the EAE model but this effect was not due to antagonism of the type 1 or type 2 dopamine receptors alone. Finally, we found that while risperidone treatment had little effect on the in vivo activation of splenic macrophages during EAE, it significantly reduced the activation of microglia and macrophages in the central nervous system. Together these studies indicate that atypical antipsychotic agents like risperidone are effective immunomodulatory agents with the potential to treat immune-mediated diseases such as MS.