Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hierarchical ASM/AAM Approach in a Stochastic Framework for Fully Automatic Tracking and Recognition

This paper deals with the fully automatic extraction of classifiable person features out of a video stream with challenging background. Basically the task can be split in two parts: Tracking the object and extracting distinctive features. In order to track a person, a system composed of an active shape model embedded in a particle filter framework has been built. The output-a shape representing the position and the geometry of the human's head-serves as an initial guess for the following active appearance model, which enables high precision matching of the head's texture. In this way raw features are transformed into appearance parameters, which finally can be used for a variety of classification tasks. The novelty of this framework is the hierarchical combination using the similarities of the models as well as exploiting their differences to enhance robustness and performance in complex scenarios.
Modeling separation dynamics in a multi-tray bio-ethanol distillation column

The high energy consumption of popularly used distillation columns has motivated development of energytracking dynamic models with the ultimate objective for potential better energy and quality control of these separation facilities. A dynamic model being able to explicitly describe both the product quality and energy consumption in a typical bio-ethanol distillation column is proposed in this paper. The proposed model is derived based on mass and energy balance principles, with an empirical model of the evaporation dynamics of liquids on column trays. The model parameters are identified based on some available test data. General consistencies between the developed model and field data are clearly observed, even though some further tuning and improvement of this developed model is still needed.
Empirical studies of information visualization: a meta-analysis

A meta-analysis is conducted on a set of empirical studies of information visualization. To be included in the meta-analysis, a study must meet a set of selection criteria. The meta-analysis synthesizes significant levels and effect sizes, tests the heterogeneity of findings from individual studies included and tests the linear trends over a range of information visualization features with ascending visual-spatial complexity. Recommendations for future experimental studies of information visualizations are included.
DSA with SHA-1 for space telecommands authentication

The problem of securing data communications in civil and commercial space missions has been debated within the Security Working Group of the Consultative Committee for Space Data Systems since several months. In the context of Telecommand transmissions, the interest is mainly focused on authentication, more than encryption. The object of this paper is to investigate the applicability of a standard scheme, Digital Signature Algorithm with SHA-1, to the authentication of Telecommand segments, and to discuss the pros and cons related to its adoption in such a peculiar context.
Using partial evaluation to enable verification of concurrent software

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Reduced low-frequency heart rate variability relates to greater intimal–medial thickness of the carotid wall in two samples

IntroductionWe investigated the relationship between heart rate variability and preclinical carotid intima–media thickening, a putative index of atherosclerosis. MethodsA sample of 350 men and women (mean age 56.8 years) selected for the presence or absence of untreated hypertension was assessed for heart rate variability at rest and separately for carotid intima–media thickness using duplex ultrasonography (Pittsburgh study). Findings from this sample were cross-validated in a subsample of 68 men drawn from the Kuopio Ischemic Heart Disease Risk Factor trial and selected for the presence or absence of angina. ResultsIn both samples, regression analyses, controlling for known risk factors, showed a significant negative relationship between mean carotid intima–media thickness and low-frequency (0.05–0.15 Hz) heart rate variability, but not high-frequency variability. DiscussionThe mechanism underlying this relationship remains unclear. The absence of difference in high-frequency variation questions any interpretation in terms of vagal function; the difference in low-frequency variation may implicate vessel wall characteristics or decreased sympathetic nervous system influence. ConclusionDecreased amplitude of low-frequency heart rate variability seems associated with a preclinical atherosclerotic index.
DHR-Trees: A Distributed Multidimensional Indexing Structure for P2P Systems

Supporting range query over peer-to-peer systems has attracted many research efforts in recent years. In this paper, we propose a new multidimensional indexing structure for P2P systems called distributed Hilbert R-trees (DHR-trees). DHR-trees enables multidimensional range query to be executed similarly as in overlapping regions tree in P2P systems. Its distributed structure makes it fault-tolerant and scalable to dynamic network environment with a large number of peers as well. Our experiments shows that it performs well on multidimensional range query while the maintenance cost is reasonably low
A Contextual Bandit Approach for Stream-Based Active Learning

Contextual bandit algorithms -- a class of multi-armed bandit algorithms that exploit the contextual information -- have been shown to be effective in solving sequential decision making problems under uncertainty. A common assumption adopted in the literature is that the realized (ground truth) reward by taking the selected action is observed by the learner at no cost, which, however, is not realistic in many practical scenarios. When observing the ground truth reward is costly, a key challenge for the learner is how to judiciously acquire the ground truth by assessing the benefits and costs in order to balance learning efficiency and learning cost. From the information theoretic perspective, a perhaps even more interesting question is how much efficiency might be lost due to this cost. In this paper, we design a novel contextual bandit-based learning algorithm and endow it with the active learning capability. The key feature of our algorithm is that in addition to sending a query to an annotator for the ground truth, prior information about the ground truth learned by the learner is sent together, thereby reducing the query cost. We prove that by carefully choosing the algorithm parameters, the learning regret of the proposed algorithm achieves the same order as that of conventional contextual bandit algorithms in cost-free scenarios, implying that, surprisingly, cost due to acquiring the ground truth does not increase the learning regret in the long-run. Our analysis shows that prior information about the ground truth plays a critical role in improving the system performance in scenarios where active learning is necessary.
Comparison of Maximal Oxygen Uptake and Anaerobic Threshold in Soccer and Handball Players

Ackground/Objective: The purpose of this study was to compare maximal oxygen uptake and anaerobic threshold values between soccer and handball players. Methods: 10 male professional soccer players and 10 male professional handball players took part in the study. Maximal oxygen uptake (VO2max) and anaerobic threshold (AT) were assessed using an incremental treadmill test. AT was estimated noninvasively using the V-slope method. The values of VO2 (ATVO2), heart rate (ATHR), time (ATTIME) and running speed (ATSPEED) corresponding to the AT were identified. AT was recorded as a percentage of VO2max (AT %VO2max) and HRmax (AT %HRmax). Time to exhaustion was determined as the total duration of the test. Results: There were no significant difference between the time to exhaustion(min), HRmax, absolute VO2max (ml min-1) and relative VO2max (ml kg-1min-1) of soccer and handball players compared to each other (p> 0.05). Similarly there were no significant difference between the two groups in the ATSPEED (km h-1), ATTIME (min), ATHR, absolute ATVO2 (ml min-1), relative ATVO2 (ml kg-1min-1), AT %VO2max and AT %HRmax (P> 0.05). Conclusion: Although soccer and handball require different movement patterns, they may exhibit similar aerobic endurance capacity. Hence physiological requirements in both branches may be expected to be similar in relation to training volume and intensity.
Single-molecule FRET reveals sugar-induced conformational dynamics in LacY

The N- and C-terminal six-helix bundles of lactose permease (LacY) form a large internal cavity open on the cytoplasmic side and closed on the periplasmic side with a single sugar-binding site at the apex of the cavity near the middle of the molecule. During sugar/H+ symport, an outward-facing cavity is thought to open with closing of the inward-facing cavity so that the sugar-binding site is alternately accessible to either face of the membrane. In this communication, single-molecule fluorescence (Förster) resonance energy transfer is used to test this model with wild-type LacY and a conformationally restricted mutant. Pairs of Cys residues at the ends of two helices on the cytoplasmic or periplasmic sides of wild-type LacY and the mutant were labeled with appropriate donor and acceptor fluorophores, single-molecule fluorescence resonance energy transfer was determined in the absence and presence of sugar, and distance changes were calculated. With wild-type LacY, binding of a galactopyranoside, but not a glucopyranoside, results in a decrease in distance on the cytoplasmic side and an increase in distance on the periplasmic side. In contrast, with the mutant, a more pronounced decrease in distance and in distance distribution is observed on the cytoplasmic side, but there is no change on the periplasmic side. The results are consistent with the alternating access model and indicate that the defect in the mutant is due to impaired ligand-induced flexibility on the periplasmic side.
Attendance system based on face recognition using eigen face and PCA algorithms

The attendance maintaining system is difficult process if it is done manually. The smart and automated attendance system for managing the attendance can be implemented using the various ways of biometrics. Face recognition is one of them. By using this system, the issue of fake attendance and proxies can be solved. In the previous face recognition based attendance system, there were some disadvantages like intensity of light problem and head pose problem. Therefore to overcome these issues, various techniques like illumination invariant, Viola and Jones algorithm, Principle component analysis are used. The major steps in this system are detecting the faces and recognizing them. After these, the comparison of detected faces can be done by crosschecking with the database of student's faces. This smart system will be an effective way to maintain the attendance and records of students.
On the binding affinity of macromolecular interactions: daring to ask why proteins interact

Interactions between proteins are orchestrated in a precise and time-dependent manner, underlying cellular function. The binding affinity, defined as the strength of these interactions, is translated into physico-chemical terms in the dissociation constant (Kd), the latter being an experimental measure that determines whether an interaction will be formed in solution or not. Predicting binding affinity from structural models has been a matter of active research for more than 40 years because of its fundamental role in drug development. However, all available approaches are incapable of predicting the binding affinity of protein–protein complexes from coordinates alone. Here, we examine both theoretical and experimental limitations that complicate the derivation of structure–affinity relationships. Most work so far has concentrated on binary interactions. Systems of increased complexity are far from being understood. The main physico-chemical measure that relates to binding affinity is the buried surface area, but it does not hold for flexible complexes. For the latter, there must be a significant entropic contribution that will have to be approximated in the future. We foresee that any theoretical modelling of these interactions will have to follow an integrative approach considering the biology, chemistry and physics that underlie protein–protein recognition.
Relation between $M_{BH}$ and $M_{bulge}$: A simulation study

The dynamical evolution of super star clusters (SSCs) moving in the background of dark matter halo has been investigated as a possible event causing the observed correlation between the mass of galactic bulge, $M_{bulge}$, and the mass of its central black hole, $M_{BH}$. The involved physical processes are the sinking of SSCs due to the dynamical friction, and the stripping of SSCs on their way to the center. Model calculations show that only sinking of circumnuclear SSCs contribute to both the growth of the central object and the formation of the galactic bulge at the early stage. On the assumption of a universal density profile for the dark matter halo, and an isothermal model for the SSCs, our simulations have yielded the mass ratio of the central objects to the bulges formed this way to be about a few times $10^{-4}$, less than the observed median value for early type galaxies. It is, however, consistent with the observed mass ratio for disk spirals, implying that the proposed scenario might be a possible event for the formation of bulges and central black holes of late type galaxies and for $M_{BH} - M_{bulge}$ correlation of disk galaxies.
Stevioside from Stevia rebaudiana Bertoni Increases Insulin Sensitivity in 3T3-L1 Adipocytes

Stevioside from Stevia rebaudiana has been reported to exert antihyperglycemic effects in both rat and human subjects. There have been few studies on these effects in vitro. In this paper, radioactive glucose uptake assay was implemented in order to assess improvements in insulin sensitivity in 3T3-L1 cells by elevation of glucose uptake following treatment with stevioside. Oil Red-O staining and MTT assay were utilized to confirm adipocyte differentiation and cell viability, respectively. Findings from this research showed a significant increase in absorbance values in mature adipocytes following Oil Red-O staining, confirming the differentiation process. Stevioside was noncytotoxic to 3T3-L1 cells as cell viability was reduced by a maximum of 17%, making it impossible to determine its IC50. Stevioside increased glucose uptake activities by 2.1 times (p < 0.001) in normal conditions and up to 4.4 times (p < 0.001) in insulin-resistant states. At times, this increase was higher than that seen in positive control group treated with rosiglitazone maleate, an antidiabetic agent. Expressions of pY20 and p-IRS1 which were measured via Western blot were improved by stevioside treatment. In conclusion, stevioside has direct effects on 3T3-L1 insulin sensitivity via increase in glucose uptake and enhanced expression of proteins involved in insulin-signalling pathway.
A Case Study on Hardware-Accelerated Lagrangian-Eulerian Texture Advection for Flow Visualization

A hardware-based approach for visualizing unsteady flow fields by means of Lagrangian-Eulerian advection is presented. The implementation allows texture advection to be performed completely on the graphics hardware in a single-pass rendering. We discuss experiences with the interactive visualization of unsteady flow fields that become possible due to the high visualization speed of the hardware-based approach.
Succinct Functional Encryption and Applications: Reusable Garbled Circuits and Beyond

Functional encryption is a powerful primitive: given an encryption Enc(x) of a value x and a secret key skf corresponding to a circuit f , it enables efficient computation of f(x) without revealing any additional information about x. Constructing functional encryption schemes with succinct ciphertexts that guarantee security for even a single secret key (for a general function f ) is an important open problem with far reaching applications, which this paper addresses. Our main result is a functional encryption scheme for any general function f of depth d, with succinct ciphertexts whose size grows with the depth d rather than the size of the circuit for f . We prove the security of our construction based on the intractability of the learning with error (LWE) problem. More generally, we show how to construct a functional encryption scheme from any public-index predicate encryption scheme and fully homomorphic encryption scheme. Previously, the only known constructions of functional encryption were either for specific inner product predicates, or for a weak form of functional encryption where the ciphertext size grows with the size of the circuit for f . We demonstrate the power of this result, by using it to construct a reusable circuit garbling scheme with input and circuit privacy: an open problem that was studied extensively by the cryptographic community during the past 30 years since Yao’s introduction of a one-time circuit garbling method in the mid 80’s. Our scheme also leads to a new paradigm for general function obfuscation which we call token-based obfuscation. Furthermore, we show applications of our scheme to homomorphic encryption for Turing machines where the evaluation runs in input-specific time rather than worst case time, and to publicly verifiable and secret delegation.
Efficient jamming strategies on a MIMO Gaussian channel with known target signal covariance

The problem of jamming on a multiple-input multiple-output (MIMO) Gaussian channel is investigated. We show that the existing result based on the simplification of the system model by neglecting the jamming channel leads to losing important insights regarding the effect of jamming power and jamming channel on the jamming strategy. We find a closed-form optimal solution for the problem under some positive semidefinite condition without considering simplifications in the model. If the condition is not satisfied and the optimal solution may not exist in closed-form, we find a suboptimal solution in closed-form as a close approximation of the optimal solution. Simulation results verify the effectiveness of the proposed solutions.
How artificial intelligence will affect the practice of law

Abstract:Artificial intelligence is exerting an influence on all professions and industries. We have autonomous vehicles, instantaneous translation among the world's leading languages, and search engines that rapidly locate information anywhere on the web in a way that is tailored to a user's interests and past search history. Law is not immune from disruption by new technology. Software tools are beginning to affect various aspects of lawyers' work, including those tasks that historically relied upon expert human judgment, such as predicting court outcomes. These new software tools present new challenges and new opportunities. In the short run, we can expect greater legal transparency, more efficient dispute resolution, improved access to justice, and new challenges to the traditional organization of private law firms delivering legal services on a billable hour basis through a leveraged partner-associate model. With new technology, lawyers will be empowered to work more efficiently, deepen and broaden their areas of expertise, and provide more value to clients. These developments will predictably transform both how lawyers do legal work and resolve disputes on behalf of their clients. In the longer term, it is difficult to predict what the impact of artificially intelligent tools will be, as lawyers incorporate them into their practice and expand their range of services on behalf of clients.
Development of a direct current power system for a multi-node cabled ocean observatory system

Due to the shortage of suitable research methods for real-time and long-term observation of oceans, an innovative approach that can provide abundant power and wide bandwidth is being developed worldwide for undersea instruments. In this paper, we develop a direct current (DC) power system which is applied to a multi-node cabled ocean observatory system named ZERO (Zhejiang University Experimental and Research Observatory). The system addresses significant issues ranging from terrestrial facility to subsea infrastructure, and focuses on using appropriate methods to deal with several key challenges, including delivery, conversion, distribution, and management of power, and heat dissipation in pressure vessels. A basic laboratory platform consisting of a shore station, a primary node in a water tank, and a secondary node in a deep-sea simulation chamber under 42 MPa pressure was built and fully tested. An improved secondary node was deployed in Monterey Bay in California for a deep-sea trial. An 11-day laboratory test and a half-year sea trial proved that the DC power system based on our proposed methods is viable for the underwater multi-node observatory system.
Doubly robust imputation of incomplete binary longitudinal data

Estimation in binary longitudinal data by using generalized estimating equation (GEE) becomes complicated in the presence of missing data because standard GEEs are only valid under the restrictive missing completely at random assumption. Weighted GEE has therefore been proposed to allow the validity of GEE's under the weaker missing at random assumption. Multiple imputation offers an attractive alternative, by which the incomplete data are pre-processed, and afterwards the standard GEE can be applied to the imputed data. Nevertheless, the imputation methodology requires correct specification of the imputation model. Dual imputation method provides a new way to increase the robustness of imputations with respect to model misspecification. The method involves integrating the so-called doubly robust ideas into the imputation model. Focusing on incomplete binary longitudinal data, we combine DIM and GEE (DIM-GEE) and study the relative performance of the new method in a case study of obesity among children, as well as a simulation study.
Crossband filtering for stereophonic acoustic echo suppression

In this paper, we propose a novel stereophonic acoustic echo suppression (SAES) technique based on crossband filtering in the short-time Fourier transform (STFT) domain. The proposed algorithm considers spectral correlations among components in adjacent frequency bins, and estimates the extended power spectral density (PSD) matrices and cross PSD vectors from the signal statistics for more precise echo estimation. In the STFT domain, the echo spectra are estimated by performing the technique without any distinguishable double-talk detector. According to the experimental results, the proposed algorithm has been found to show better performances compared with the conventional SAES method.