Miracle-dz/UniFAR-FTUs huggingface dataset:
ON A DEFICIENCY OF THE FCI ALGORITHM LEARNING BAYESIAN NETWORKS FROM DATA

Causally insufficient structures (models with latent or hidden variables, or with confounding etc.) of joint probability distributions have been subject of intense study not only in statistics, but also in various AI systems. In AI, belief networks, being representations of joint probability distribution with an underlying directed acyclic graph structure, Eire paid special attention due to the fact that efficient reasoning (uncertainty propagation) methods have been developed for belief network structures. Algorithms have been therefore developed to acquire the belief network structure from data. As artifacts due to variable hiding negatively influence the performance of derived belief networks, models with latent variables have been studied and several algorithms for learning belief network structure under causal insufficiency have also been developed. Regrettably, some of them are known already to be erroneous (e.g. IC algorithm of [12]). This paper is devoted to another algorithm, the Feist Causal Inference (FCI) Algorithm of [17]. It is proven by a specially constructed example that this algorithm, as it stands in [17], is also erroneous. Fundamental reason for failure of this algorithm is the temporary introduction of non-real links between nodes of the network with the intention of later removal. While for trivial dependency structures these non-real links may be actually removed, this may not be the case for complex ones, e.g. for the case described in this paper. A remedy of this failure is proposed.
Single-phase modular multilevel inverter based grid-connected photovoltaic system

This paper presents a control scheme for single-phase grid-connected modular five-level inverter applied to photovoltaic (PV) system. The five-level topology considered consists of two series connected H-bridge cells popularly known as cascaded H-bridge inverter. The reason that it requires an isolated dc sources makes it very attractive and its inherent modularity, easy scalability makes the system more reliable. One of the main challenges associated with multilevel converter is to control the drift in dc-link voltage caused by the power imbalance of the cells. A two loop control scheme is proposed to combat this issue; it consists of an asynchronous frame or proportional resonant (PR) for regulating the grid current and a proportional integral (PI) controller for regulating dc-link voltage. The proposed scheme regulates the dc-link voltage independently, in accordance with the reference value generated by the maximum power point tracking (MPPT) algorithm enabling the extraction of maximum power from each module. The inverter injects current which is in phase with the grid voltage ensures the unitary power factor operation with zero reactive power and less total harmonic distortion. The proposed control scheme can be extended to any number of cells connected in series for increasing the number of level in output voltage. Simulation results are presented to validate the analytical expectations and the control scheme developed.
Exploring our understanding of fatigue among adolescents living with HIV: Highlighting the unknown

Due to antiretroviral therapies, HIV is now a chronic illness rather than a terminal disease. Chronic symptoms, including fatigue, should be identified and managed to prevent or minimise their potential negative consequences. We apply a Symptom Management Model to conceptualise fatigue among adolescents with HIV. In the context of minimal research, we seek to identify a research agenda for resource-constrained contexts, where HIV prevalence remains high and treatment adherence is a significant problem. By better understanding and addressing the symptom of fatigue, treatment adherence, occupational, social and emotional functioning could be improved. We highlight conceptual, methodological and measurement-related caveats.
The average-case complexity of counting distinct elements

We continue the study of approximating the number of distinct elements in a data stream of length n to within a (1 ± ε) factor. It is known that if the stream may consist of arbitrary data arriving in an arbitrary order, then any 1-pass algorithm requires Ω(1/ε2) bits of space to perform this task. To try to bypass this lower bound, the problem was recently studied in a model in which the stream may consist of arbitrary data, but it arrives to the algorithm in a random order. However, even in this model an Ω(1/ε2) lower bound was established. This is because the adversary can still choose the data arbitrarily. This leaves open the possibility that the problem is only hard under a pathological choice of data, which would be of little practical relevance. We study the average-case complexity of this problem under certain distributions. Namely, we study the case when each successive stream item is drawn independently and uniformly at random from an unknown subset of d items for an unknown value of d. This captures the notion of random uncorrelated data. For a wide range of values of d and n, we design a 1-pass algorithm that bypasses the Ω(1/ε2) lower bound that holds in the adversarial and random-order models, thereby showing that this model admits more space-efficient algorithms. Moreover, the update time of our algorithm is optimal. Despite these positive results, for a certain range of values of d and n we show that estimating the number of distinct elements requires Ω(1/ε2) bits of space even in this model. Our lower bound subsumes previous bounds, showing that even for natural choices of data the problem is hard.
Aberrant temporal and spatial brain activity during rest in patients with chronic pain

In the absence of external stimuli, human hemodynamic brain activity displays slow intrinsic variations. To find out whether such fluctuations would be altered by persistent pain, we asked 10 patients with unrelenting chronic pain of different etiologies and 10 sex- and age-matched control subjects to rest with eyes open during 3-T functional MRI. Independent component analysis was used to identify functionally coupled brain networks. Time courses of an independent component comprising the insular cortices of both hemispheres showed stronger spectral power at 0.12 to 0.25 Hz in patients than in control subjects, with the largest difference at 0.16 Hz. A similar but weaker effect was seen in the anterior cingulate cortex, whereas activity of the precuneus and early visual cortex, used as a control site, did not differ between the groups. In the patient group, seed point-based correlation analysis revealed altered spatial connectivity between insulae and anterior cingulate cortex. The results imply both temporally and spatially aberrant activity of the affective pain-processing areas in patients suffering from chronic pain. The accentuated 0.12- to 0.25-Hz fluctuations in the patient group might be related to altered activity of the autonomic nervous system.
MoM validation of the predicted radiated emissions of two signal integrity damping schemes on PCB microstrips

An important consideration in the design of high speed digital systems is the signal integrity of interconnections. Source and destination termination to achieve damping can be effective methods for managing signal integrity. At high signal speeds, emissions from the interconnections play an equally important consideration in terms of electromagnetic compatibility performance of a system. The radiated emissions of interconnections are different for the two damping schemes. Approximate analytical models have been developed for the study of the effects of the two damping methods on emissions and signal integrity. In this paper, a full-wave technique using the method of moments is used to validate the radiated emission predict by the approximate analytical models.
Grounded Objects and Interactions for Video Captioning

We address the problem of video captioning by grounding language generation on object interactions in the video. Existing work mostly focuses on overall scene understanding with often limited or no emphasis on object interactions to address the problem of video understanding. In this paper, we propose SINet-Caption that learns to generate captions grounded over higher-order interactions between arbitrary groups of objects for fine-grained video understanding. We discuss the challenges and benefits of such an approach. We further demonstrate state-of-the-art results on the ActivityNet Captions dataset using our model, SINet-Caption based on this approach.
Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization

By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not consider regularization and their sparsification processes are batch or offline, which hinder their widespread applications in online learning problems. In this paper, we combine the following five techniques and propose two novel kernel recursive LSTD algorithms: (i) online sparsification, which can cope with unknown state regions and be used for online learning, (ii) L 2 and L 1 regularization, which can avoid overfitting and eliminate the influence of noise, (iii) recursive least squares, which can eliminate matrix-inversion operations and reduce computational complexity, (iv) a sliding-window approach, which can avoid caching all history samples and reduce the computational cost, and (v) the fixed-point subiteration and online pruning, which can make L 1 regularization easy to implement. Finally, simulation results on two 50-state chain problems demonstrate the effectiveness of our algorithms.
What Actions are Needed for Understanding Human Actions in Videos?

What is the right way to reason about human activities? What directions forward are most promising? In this work, we analyze the current state of human activity understanding in videos. The goal of this paper is to examine datasets, evaluation metrics, algorithms, and potential future directions. We look at the qualitative attributes that define activities such as pose variability, brevity, and density. The experiments consider multiple state-of-the-art algorithms and multiple datasets. The results demonstrate that while there is inherent ambiguity in the temporal extent of activities, current datasets still permit effective benchmarking. We discover that fine-grained understanding of objects and pose when combined with temporal reasoning is likely to yield substantial improvements in algorithmic accuracy. We present the many kinds of information that will be needed to achieve substantial gains in activity understanding: objects, verbs, intent, and sequential reasoning. The software and additional information will be made available to provide other researchers detailed diagnostics to understand their own algorithms.
HAIR: hierarchical architecture for internet routing

In the light of recent interest in re-designing the Internet, we introduce HAIR, a routing architecture that tackles the problem of routing table growth, restricts the visibility of routing updates, and inherently supports traffic engineering, mobility, and multipath. HAIR separates locators from identifiers. The routing and mapping system rely on a hierarchical scheme that leverages the structure of today's Internet. Contrary to proposals such as LISP [7] and shim6 [18], we use a hybrid edge-based approach where only some lightweight functionality is added within the network, while the majority of tasks are performed as close to the end hosts as possible. To evaluate our architecture, we analyze to what extent routing would be simplified if HAIR were deployed in today's Internet. Finally, we demonstrate the feasibility of our approach by presenting a working proof-of-concept implementation.
Radial photovoltaic junction with single Si nanowire core–shell structure

A single silicon nanowire core–shell structure has been elaborated. Technological stages of the process are presented. The device results in a P-i-N radial junction: the core is a P-type silicon nanowire encapsulated in an intrinsic thin silicon layer and an N-type doped silicon layer. Scanning electron microscopy observations, as well as the electrical I(V) characterisation on single nanowires, are presented.
Fields of finite Morley rank

Abstract If K is a field of finite Morley rank, then for any parameter set A ⊆ Keq the prime model over A is equal to the model-theoretic algebraic closure of A. A field of finite Morley rank eliminates imaginaries. Simlar results hold for minimal groups of finite Morley rank with infinite acl(∅).
Design of a Compact Ultra-Wide Band Bow-Tie Slot Antenna System for the Evaluation of Structural Changes in Civil Engineering Works

A compact UWB bowtie-slot antenna (36 £ 23cm 2 ) fed by a CPW transition is proposed for an improved ground-coupling radar. The antenna has an operating frequency band in the range (0:46;4)GHz. Full-wave modeling using the FDTD approach has allowed to study in details the antenna radiation characteristics in air and in the presence of a soil. Afterwards, a radar system made of a pair of independent shielded bowtie antennas has been considered to probe the sub-surface very close to the air-soil interface. The polarization diversity in the E and H-planes is an important aspect which has been studied in order to further detect the orientation of damages (cracks, delaminations .) in civil engineering structures. Measurements in a dry and wet sand in difierent system conflgurations have allowed to flrst characterize the GPR system and to draw comparisons with numerical results. The ability of the radar to detect small buried objects has been investigated.
In Vitro Resistance Development to Nemonoxacin in Streptococcus pneumoniae: A Unique Profile for a Novel Nonfluorinated Quinolone

Selection of resistant strains in Streptococcus pneumoniae was studied in vitro with nemonoxacin, a novel nonfluorinated quinolone (NFQ), in comparison with quinolone benchmarks, ciprofloxacin, garenoxacin, and gatifloxacin. In stepwise resistance selection studies, a 256-fold loss of potency was observed after three to four steps of exposure to ciprofloxacin or garenoxacin. In contrast, the loss of potency was limited to eightfold after three steps of exposure to nemonoxacin and repeated attempts to isolate highly resistant organisms after four steps of exposure yielded isolates that could not be subcultured in liquid medium. The quinolone resistance-determining regions of the target genes, parC, parE, gyrA, and gyrB, were analyzed through DNA sequencing. Known mutations, especially in the hotspots of parC and gyrA, were selected with exposure to garenoxacin, ciprofloxacin, and gatifloxacin. In contrast, mutations selected with nemonoxacin were limited to GyrA, GyrB, and ParE, sparing ParC, which is known as a key driver of resistance in clinical isolates of S. pneumoniae. This observation is consistent with previous data using other NFQs, which showed no loss of potency due to ParC mutations in clinical isolates. This apparently unique feature of nemonoxacin is potentially attributable to the structural uniqueness of the NFQs, distinguishing them from the fluoroquinolones that are commonly prescribed for infections by S. pneumoniae.
Mutations in the Autographa californica multinucleocapsid nuclear polyhedrosis virus 25 kDa protein gene result in reduced virion occlusion, altered intranuclear envelopment and enhanced virus production.

Serial passage of nuclear polyhedrosis viruses (NPVs) through cultured cell lines results in the appearance of mutants with a complex phenotype referred to as the 'few polyhedra' (FP) phenotype. The altered plaque morphology and reduced occlusion production associated with the FP phenotype have been observed in Autographa californica multinucleocapsid nuclear polyhedrosis virus (AcMNPV) bearing mutations in the gene encoding the 25 kDa protein (25K gene). In this study, we sequenced the 25K genes of four spontaneously occurring AcMNPV FP mutants. These mutants, together with an artificially generated FP mutant (AcFP beta gal, in which the gene for beta-galactosidase is fused in frame with the 25K ORF), were examined at the ultrastructural level to see if they exhibited the reduced virion occlusion and intranuclear envelopment which is associated with the FP phenotype. Observations on Spodoptera frugiperda Sf9 cells infected with the FP mutants revealed that all five mutants were impaired in virion occlusion and intranuclear nucleocapsid envelopment. The 25K mutants were also found to release two- to fivefold more infectious virus (p.f.u.) into the media of infected Sf9 cells. Marker rescue of AcFP beta gal restored wild-type virion occlusion, intranuclear envelopment and levels of infectious virus production.
Electrical discharge machining–based hybrid machining processes: A review

Electrical discharge machining is one of the widely used noncontact-type advanced machining processes in which material removal takes place due to melting and vaporization by thermal energy of electric sparks. Electrical discharge machining has the capability of machining difficult-to-cut materials such as superalloys, advanced ceramics, and composites with complex shapes at both macro- and micro-levels. But its application is limited to electrically conductive materials. Other limitations include low material removal rate, high tool wear rate, recast layer formation, and geometrical inaccuracy in the form of taper and overcut. To overcome such limitations, the mechanism of electrical discharge machining has been combined with the mechanism of one or more other machining/physical/chemical processes. The mechanism of two constituent processes may be applied simultaneously or sequentially to constitute the hybrid machining process. It has been found that the performance of hybrid machining processes is better than the constituent processes. This article presents the comprehensive review of the research work carried out so far in the area of electrical discharge machining–based hybrid machining processes. It discusses about the experimental and theoretical studies of electrical discharge machining–based hybrid machining processes to elucidate the effects of various control factors or input parameters on process performances. This article includes modeling and optimization studies and discusses the future trend of the research work in this area.
Symmetry Is Related to Sexual Dimorphism in Faces: Data Across Culture and Species

Background Many animals both display and assess multiple signals. Two prominently studied traits are symmetry and sexual dimorphism, which, for many animals, are proposed cues to heritable fitness benefits. These traits are associated with other potential benefits, such as fertility. In humans, the face has been extensively studied in terms of attractiveness. Faces have the potential to be advertisements of mate quality and both symmetry and sexual dimorphism have been linked to the attractiveness of human face shape. Methodology/Principal Findings Here we show that measurements of symmetry and sexual dimorphism from faces are related in humans, both in Europeans and African hunter-gatherers, and in a non-human primate. Using human judges, symmetry measurements were also related to perceived sexual dimorphism. In all samples, symmetric males had more masculine facial proportions and symmetric females had more feminine facial proportions. Conclusions/Significance Our findings support the claim that sexual dimorphism and symmetry in faces are signals advertising quality by providing evidence that there must be a biological mechanism linking the two traits during development. Such data also suggests that the signalling properties of faces are universal across human populations and are potentially phylogenetically old in primates.
Stiffness and Thermal Expansion of Short Fiber Composites with Fully Aligned Fibers

Predicting the overall, effective properties of short fiber composites with fully aligned fibers from the properties of the individual phases and the composite's morphology has attracted a great deal of attention during the last decades. In this work, the authors focus on the overall elastic constants and use the finite-element-based numerical procedure developed by them to assess the adequacy of two of the most widely used micromechanics-based models.
The Frames of Reference of the Motor-Visual Aftereffect

Repeatedly performing similar motor acts produces short-term adaptive changes in the agent’s motor system. One striking use-dependent effect is the motor-to-visual aftereffect (MVA), a short-lasting negative bias in the conceptual categorization of visually-presented training-related motor behavior. The MVA is considered the behavioral counterpart of the adaptation of visuomotor neurons that code for congruent executed and observed motor acts. Here we characterize which features of the motor training generate the MVA, along 3 main dimensions: a) the relative role of motor acts vs. the semantics of the task-set; b) the role of muscular-specific vs. goal-specific training and c) the spatial frame of reference with respect to the whole body. Participants were asked to repeatedly push or pull some small objects in a bowl as we varied different components of adapting actions across three experiments. The results show that a) the semantic value of the instructions given to the participant have no role in generating the MVA, which depends only on the motor meaning of the training act; b) both intrinsic body movements and extrinsic action goals contribute simultaneously to the genesis of the MVA and c) changes in the relative position of the acting hand compared to the observed hand, when they do not involve changes to the movement performed or to the action meaning, do not have an effect on the MVA. In these series of experiments we confirm that recent motor experiences produce measurable changes in how humans see each others’ actions. The MVA is an exquisite motor effect generated by two distinct motor sub-systems, one operating in an intrinsic, muscular specific, frame of reference and the other operating in an extrinsic motor space.
Statistical Inference Framework for Source Detection of Contagion Processes on Arbitrary Network Structures

We introduce a statistical inference framework for maximum likelihood estimation of the contagion source from a partially observed contagion spreading process on an arbitrary network structure. The framework is based on simulations of a contagion spreading process from a set of potential sources which were infected in the observed realization. We present a number of different likelihood estimators for determining the conditional probabilities of potential initial sources producing the observed epidemic realization, which are computed in scalable and parallel way. This statistical inference framework is applicable to arbitrary networks with different dynamical spreading processes.
Localization for humanoid robots with sway compensation in indoor environments

This paper discusses and proposes a method to minimize the effect of lateral motion of a humanoid robot's body that hampers localization performance of an adult-size humanoid robot. On a humanoid with a large sway motion, this effect is not negligible and a correction on the position estimation for perception based localization systems is necessary. First, the sway motion will be quantified and different perception configurations will be proposed to reduce the errors caused by this motion. Then, experimental results will be presented to demonstrate that the proposed localization system using a 2D laser scanner is more accurate and reliable when the sway motion is compensated.