Miracle-dz/UniFAR-FTUs huggingface dataset:
DHTrust: A Robust and Distributed Reputation System for Trusted Peer-to-Peer Networks

The anonymity and dynamic characters of Peer-to-Peer (P2P) system makes it an ideal medium for selfish and vicious action. In order to solve this problem, P2P reputation systems are proposed to evaluate the trustworthiness of peers and to prevent the selfish, dishonest, and malicious peers' behaviors, which collects local reputation scores and aggregates them into the global reputation. In this paper we propose a DHT trust overlay network (DHTON) to model the network structure and the storage of reputation information. We also design a robust and distributing reputation system, DHTrust, which takes full advantage of the Distributed Hash Table (DHT) to distribute local reputation to trade off the damage of fake reputation information by genuine reputation information. By using the trust evaluation towards two reputation scores, we can also distinguish and evaluate the fundamental behaviors of peers in P2P network, i.e., providing service and issuing reputation scores. Through the simulation experiments, we find our system makes significant performance gains in convergence speed and aggregation accuracy, and the most important, is robust to malicious peers.
The key science drivers for MICHI: a thermal-infrared instrument for the TMT

With the imminent launch of the JWST, the field of thermal-infrared (TIR) astronomy will enjoy a revolution. It is easy to imagine that all areas of infrared (IR) astronomy will be greatly advanced, but perhaps impossible to conceive of the new vistas that will be opened. To allow both follow-up JWST observations and a continuance of work started on the ground-based 8m’s, we continue to plan the science cases and instrument design for a TIR imager and spectrometer for early operation on the TMT. We present the current status of our science cases and the instrumentation plans, harnessing expertise across the TMT partnership. This instrument will be proposed by the MICHI team as a second-generation instrument in any upcoming calls for proposals.
Classification of computed tomography scanner manufacturer using support vector machine

Computed tomography (CT) is useful to investigate the presence and severity of injury during acute stage of traumatic brain injury (TBI) due to its availability and short image acquisition time. Recently, quantitative CT analysis have shown promising results in objective and accurate assessment of lesion and the prediction of outcome. To conduct further multicenter, longitudinal follow-up studies using quantitative analysis, the effect of CT scanner manufacturer should be investigated. In this study, CT images were acquired from 326 subjects without any apparent intracranial abnormalities. The images were scanned by three different scanner manufacturers. The quantitative analysis was performed and plotted as density distribution. The acquired density distributions were served as input features of support vector machine (SVM) using Gaussian kernel function, which is designed for classifying the CT images based on the scanner manufacturers. The optimal hyperparameters were explored via grid search test and the model increased the robustness by 5-fold cross validation. The best predictive performance was obtained when C = 100 and γ = 0.1 (accuracy = 91.1 %). The results showed significant difference in density distribution according to the scanner manufacturers, and thus suggest that the manufacturer should be standardized to conduct the quantitative analysis on the brain CT images.
A Q-Learning Approach to Flocking With UAVs in a Stochastic Environment

In the past two decades, unmanned aerial vehicles (UAVs) have demonstrated their efficacy in supporting both military and civilian applications, where tasks can be dull, dirty, dangerous, or simply too costly with conventional methods. Many of the applications contain tasks that can be executed in parallel, hence the natural progression is to deploy multiple UAVs working together as a force multiplier. However, to do so requires autonomous coordination among the UAVs, similar to swarming behaviors seen in animals and insects. This paper looks at flocking with small fixed-wing UAVs in the context of a model-free reinforcement learning problem. In particular, Peng's Q(λ)$with a variable learning rate is employed by the followers to learn a control policy that facilitates flocking in a leader-follower topology. The problem is structured as a Markov decision process, where the agents are modeled as small fixed-wing UAVs that experience stochasticity due to disturbances such as winds and control noises, as well as weight and balance issues. Learned policies are compared to ones solved using stochastic optimal control (i.e., dynamic programming) by evaluating the average cost incurred during flight according to a cost function. Simulation results demonstrate the feasibility of the proposed learning approach at enabling agents to learn how to flock in a leader-follower topology, while operating in a nonstationary stochastic environment.
Model-Driven Consistency Checking of Behavioural Specifications

For the development of software intensive systems different types of behavioural specifications are used. Although such specifications should be consistent with respect to each other, this is not always the case in practice. Maintainability problems are the result. In this paper we propose a technique for assessing the consistency of two types behavioural specifications: scenarios and state machines. The technique is based on the generation of state machines from scenarios. We specify the required mapping using model transformations. The use of technologies related to the model driven architecture enables easy integration with widely adopted (UML) tools. We applied our technique to assess the consistency of the behavioural specifications for the embedded software of copiers developed by Oce. Finally, we evaluate the approach and discuss its generalisability and wider applicability
Prediction of influenza epidemics at the province level in China using search query from “Haosou”

Influenza (Flu) has caused and will continue to cause large morbidity and mortality to human society. Surveillance is critical for prevention and control of it. Traditional methods for influenza surveillance are based on hierarchical surveillance networks, which are costly and time-consuming. The Internet-based method is a useful supplement to traditional methods in influenza surveillance. Here, we attempted to predict the daily influenza epidemics, represented as the number of influenza-like illness (ILI) cases, in three representative provinces in China (Beijing, Shanghai and Guangdong) based on the “Haosou” search engine. The search queries for several keywords related to influenza were observed to have medium to weak correlations to influenza epidemics in these provinces. Two kinds of statistical model, the multiple linear regression and regression tree, were built to predict the influenza epidemics based on the search queries of these keywords. Both of them achieved moderate performance in the cross-validation and retrospective-testing for each province, with the Pearson Correlation Coefficients between the predicted and observed influenza epidemics ranging from 0.35 to 0.78. Further, the unified models were built for prediction of influenza epidemics for all three provinces. Their poor performances suggest the difficulty of building a unified model for prediction of influenza epidemics for all provinces in China. Overall, this work shows the potential of predicting the daily influenza epidemics at the province level in China based on the search engine data. More efforts are needed to improve the statistical models for their use in practical influenza surveillance.
Optimization of Resource Scheduling in Cloud Computing

Resource scheduling based on SLA (Service Level Agreement) in cloud computing is NP-hard problem. There is no efficient method to solve it. This paper proposes a new method to solve the problem by applying stochastic integer programming for optimal resource scheduling in cloud computing. Applying Gr\"{o}bner bases theory for solving the stochastic integer programming problem and the experimental results of the implementation are also presented.
Impaired Clearance of Influenza A Virus in Obese, Leptin Receptor Deficient Mice Is Independent of Leptin Signaling in the Lung Epithelium and Macrophages

Rationale During the recent H1N1 outbreak, obese patients had worsened lung injury and increased mortality. We used a murine model of influenza A pneumonia to test the hypothesis that leptin receptor deficiency might explain the enhanced mortality in obese patients. Methods We infected wild-type, obese mice globally deficient in the leptin receptor (db/db) and non-obese mice with tissue specific deletion of the leptin receptor in the lung epithelium (SPC-Cre/LepRfl/fl) or macrophages and alveolar type II cells (LysM-Cre/Leprfl/fl) with influenza A virus (A/WSN/33 [H1N1]) (500 and 1500 pfu/mouse) and measured mortality, viral clearance and several markers of lung injury severity. Results The clearance of influenza A virus from the lungs of mice was impaired in obese mice globally deficient in the leptin receptor (db/db) compared to normal weight wild-type mice. In contrast, non-obese, SP-C-Cre+/+/LepRfl/fl and LysM-Cre+/+/LepRfl/fl had improved viral clearance after influenza A infection. In obese mice, mortality was increased compared with wild-type mice, while the SP-C-Cre+/+/LepRfl/fl and LysM-Cre+/+/LepRfl /fl mice exhibited improved survival. Conclusions Global loss of the leptin receptor results in reduced viral clearance and worse outcomes following influenza A infection. These findings are not the result of the loss of leptin signaling in lung epithelial cells or macrophages. Our results suggest that factors associated with obesity or with leptin signaling in non-myeloid populations such as natural killer and T cells may be associated with worsened outcomes following influenza A infection.
An alert correlation algorithm based on the sequence pattern mining

Sequence correlation method has limits in unknown attacks identification and requires pre-defining the causal relationship between attack behavior. To solve this problem, an alert correlation algorithm, denoted as TPrefixSpan, based on the sequence pattern mining is proposed in this paper, based on PrefixSpan algorithm, TPrefixSpan algorithm introduces time interval that can thoroughly narrow, the search space, then time cost on repeated dataset scan in the sequence pattern mining is greatly saved, the efficiency of the PrefixSpan algorithm is ensured. Compared with PrefixSpan algorithm, TPrefixSpan algorithm generates much precise attacks identification. In order to visualize the correlation rules better, a sequence diagram generation algorithm of attack behavior is put forward.
Multiple Regulatory Roles of the Mouse Transmembrane Adaptor Protein NTAL in Gene Transcription and Mast Cell Physiology

Non-T cell activation linker (NTAL; also called LAB or LAT2) is a transmembrane adaptor protein that is expressed in a subset of hematopoietic cells, including mast cells. There are conflicting reports on the role of NTAL in the high affinity immunoglobulin E receptor (FcεRI) signaling. Studies carried out on mast cells derived from mice with NTAL knock out (KO) and wild type mice suggested that NTAL is a negative regulator of FcεRI signaling, while experiments with RNAi-mediated NTAL knockdown (KD) in human mast cells and rat basophilic leukemia cells suggested its positive regulatory role. To determine whether different methodologies of NTAL ablation (KO vs KD) have different physiological consequences, we compared under well defined conditions FcεRI-mediated signaling events in mouse bone marrow-derived mast cells (BMMCs) with NTAL KO or KD. BMMCs with both NTAL KO and KD exhibited enhanced degranulation, calcium mobilization, chemotaxis, tyrosine phosphorylation of LAT and ERK, and depolymerization of filamentous actin. These data provide clear evidence that NTAL is a negative regulator of FcεRI activation events in murine BMMCs, independently of possible compensatory developmental alterations. To gain further insight into the role of NTAL in mast cells, we examined the transcriptome profiles of resting and antigen-activated NTAL KO, NTAL KD, and corresponding control BMMCs. Through this analysis we identified several genes that were differentially regulated in nonactivated and antigen-activated NTAL-deficient cells, when compared to the corresponding control cells. Some of the genes seem to be involved in regulation of cholesterol-dependent events in antigen-mediated chemotaxis. The combined data indicate multiple regulatory roles of NTAL in gene expression and mast cell physiology.
A literature review with statistical analysis of electricity price forecasting methods

In today's liberalized and competitive power market, electric utilities, power producers and traders are exposed to increasing price risks and volatility. The growing reliance on renewable sources and their dependence on weather, nuclear uncertainty, market coupling and global financial instability are contributing to importance of accurate price forecast. Considering the fact that power markets are not equally developed, different price forecasting methods have arose. This paper provides an overview of notable price forecasting methods that have been published in research papers. The paper also includes statistical review of applied methods embracing timeframe, geographical background, statistical errors and other specific data. Finally, results are discussed with respect to qualitative and quantitative statistical analysis, with emphasis on the price forecasting accuracy.
Postnatal development of layer III pyramidal cells in the primary visual, inferior temporal, and prefrontal cortices of the marmoset

Abnormalities in the processes of the generation and/or pruning of dendritic spines have been implicated in several mental disorders including autism and schizophrenia. We have chosen to examine the common marmoset (Callithrix jacchus) as a primate model to explore the processes. As a first step, we studied the postnatal development of basal dendritic trees and spines of layer-III pyramidal cells in the primary visual sensory cortex (V1), a visual association cortex (inferior temporal area, TE), and a prefrontal cortex (area 12, PFC). Basal dendrites in all three areas were longer in adulthood compared with those in the newborn. In particular, rapid dendritic growth occurred in both TE and PFC around the second postnatal month. This early growth spurt resulted in much larger dendritic arbors in TE and PFC than in V1. The density of the spines along the dendrites peaked at 3 months of age and declined afterwards in all three areas: the degree of spine pruning being greater in V1 than in TE and PFC. The estimates of the total numbers of spines in the basal dendrites of a single pyramidal cell were larger in TE and PFC than in V1 throughout development and peaked around 3 months after birth in all three areas. These developmental profiles of spines and dendrites will help in determining assay points for the screening of molecules involved in spinogenesis and pruning in the marmoset cortex.
INFERRING THE RATES OF BRANCHING AND EXTINCTION FROM MOLECULAR PHYLOGENIES

Molecular techniques provide ancestral phylogenies of extant taxa with estimated branching times. Here we studied the pattern of ancestral phylogeny of extant taxa produced by branching (or cladogenesis) and extinction of taxa, assuming branching processes with time‐dependent rates. (1) If the branching rate b and extinction rate c are constant, the semilog plot of the number of ancestral lineages over time is not a straight line but is curvilinear, with increasing slope toward the end, implying that ancestral phylogeny shows apparent increase in the branching rate near the present. The estimate of b and c based on nonlinear fitting is examined by computer simulation. The estimate of branching rate can be usable for a large phylogeny if b is greater than c, but the estimate of extinction rate c is unreliable because of large bias and variance. (2) Gradual decrease in the slope of the semilog plot of the number of ancestral lineages over time, as was observed in a phylogeny of bird families based on DNA hybridization data, can be explained equally well by either the decreasing branching rate or the increasing extinction rate. Infinitely many pairs of branching and extinction rates as functions of time can produce the same ancestral phylogeny. (3) An explosive branching event in the past would appear as a quick increase in the number of ancestral lineages. In contrast, mass extinction occurring in a brief period, if not accompanied by an increase in branching rate, does not produce any rapid change in the number of ancestral lineages at the time. (4) The condition in which the number of ancestral lineages of extant species changes in parallel with the actual number of species in the past is derived.
Clarity from Confusion: Using Intended Interactions to Design Information Systems

Two tools are described that help designers visualize the structure of a system in the requirements phase of a project. First, a matrix is constructed that represents the tendency of components to interact. The matrix is derived from sequence diagrams, which in turn are based on textual scenarios. This interaction matrix is transformed into a structure plot of the system, showing a graph of the essential connections between actors. Second, this same matrix is used to generate a sequence plot: a sequence diagram optimized for problem-solving. We illustrate the effectiveness of this approach, first with a simulation study, and later with a participant-based study of inference from diagrams. The results suggest that a similarity-based approach to information systems design can generate new testable tools. Pragmatically, the tools help novices and experts alike by automatically generating candidate system configurations in the form of structural diagrams, and by generating better sequence diagrams.
Cross-domain password-based authenticated key exchange revisited

We revisit the problem of cross-domain secure communication between two users belonging to different security domains within an open and distributed environment. Existing approaches presuppose that either the users are in possession of public key certificates issued by a trusted certificate authority (CA), or the associated domain authentication servers share a long-term secret key. In this paper, we propose a four-party password-based authenticated key exchange (4PAKE) protocol that takes a different approach from previous work. The users are not required to have public key certificates, but they simply reuse their login passwords they share with their respective domain authentication servers. On the other hand, the authentication servers, assumed to be part of a standard PKI, act as ephemeral CAs that “certify” some key materials that the users can subsequently exchange and agree on a session key. Moreover, we adopt a compositional approach. That is, by treating any secure two-party password-based key exchange protocol and two-party asymmetric-key based key exchange protocol as black boxes, we combine them to obtain a generic and provably secure 4PAKE protocol.
Maximum Entropy Boundaries in Lattice Boltzmann Method

We propose a universal approach in the framework of the lattice Boltzmann method (LBM) to modeling constant velocity constraints and constant temperature constraints on curved walls, which doesn�t depend on dimensionality, LBM scheme, boundary geometry; which is numerically stable, accurate and local and has a good physical background. This technique, called a maximum entropy method, utilizes the idea of recovering unknown populations on boundary nodes through minimizing node state deviation from equilibrium while assuring velocity or temperature restrictions. Also, theoretical justifications of a popular Zou-He boundaries technique and isothermal boundaries algorithm are provided on the basis of the method derived. Finally, while conducting numerical benchmarks, typical straight boundaries algorithm (Zou-He) was compared to a typical curved boundaries algorithm (Guo-Zheng).
Convergent Excitation of Dorsal Raphe Serotonin Neurons by Multiple Arousal Systems (Orexin/Hypocretin, Histamine and Noradrenaline)

Dorsal raphe serotonin neurons fire tonically at a low rate during waking. In vitro, however, they are not spontaneously active, indicating that afferent inputs are necessary for tonic firing. Agonists of three arousal-related systems impinging on the dorsal raphe (orexin/hypocretin, histamine and the noradrenaline systems) caused an inward current and increase in current noise in whole-cell patch-clamp recordings from these neurons in brain slices. The inward current induced by all three agonists was significantly reduced in extracellular solution containing reduced sodium (25.6 mm). In extracellular recordings, all three agonists increased the firing rate of serotonin neurons; the excitatory effects of histamine and orexin A were occluded by previous application of phenylephrine, suggesting that all three systems act via common effector mechanisms. The dose–response curve for orexin B suggested an effect mediated by type II (OX2) receptors. Single-cell PCR demonstrated the presence of both OX1 and OX2receptors in tryptophan hydroxylase-positive neurons. The effects of histamine and the adrenoceptor agonist, phenylephrine, were blocked by antagonists of histamine H1 and α1receptors, respectively. The inward current induced by orexin A and phenylephrine was not blocked by protein kinase inhibitors or by thapsigargin. Three types of current–voltage responses were induced by all three agonists but in no case did the current reverse at the potassium equilibrium potential. Instead, in many cases the orexin A-induced current reversed in calcium-free medium at a value (−23 mV) consistent with the activation of a mixed cation channel (with relative permeabilities for sodium and potassium of 0.43 and 1, respectively).
The emergence of attachment following early social deprivation

Abstract This study examined the formation and quality of attachment of 65 postinstitutionalized (PI) toddlers with their parents at 1–3 and 7–9 months postadoption compared to 52 nonadopted (NA) children. The formation of attachment relationships of PI children with adoptive parents occurred relatively quickly. Children exposed to greater preadoption adversity took longer to form an attachment to their adoptive parents, although by 7–9 months postadoption, nearly all (90%) of the children achieved the highest level on an attachment formation rating scale. PI children did not differ from NA children in attachment security, based either on the Attachment Q-Sort or Strange Situation categorical scoring. However, the PI children were more likely to be disorganized in their attachment patterns. Preadoption adversity was related to lower Q-sort security scores especially at the initial assessment 1–3 months postadoption. The results indicated that attachment formation and attachment quality in PI children are differentiable constructs with different precursors.