Miracle-dz/UniFAR-FTUs huggingface dataset:
Framework for Context-Aware Applications on the Brazilian Digital TV

Context-aware applications use context information in order to adapt services according to the user situations and needs. One of the promising scenarios for the development and use of these applications is provided by the interactive digital television environment, in particular by the Brazilian Digital Television System (SBTVD). However, Ginga, the middleware standard of the SBTVD, still lacks context management mechanisms to facilitates the development of complex, domain independent and reuse driven context-aware applications. To answer these needs, this article describes, a new framework for the development of context-aware applications for the SBTVD. Some steps to drive the development of such applications using the framework are also presented.
Using Embedding Masks for Word Categorization

Word embeddings are widely used nowadays for many NLP tasks. They reduce the dimensionality of the vocabulary space, but most importantly they should capture (part of) the meaning of words. The new vector space used by the embeddings allows computation of semantic distances between words, while some word embeddings also permit simple vector operations (e.g. summation, difference) resembling analogical reasoning. This paper proposes a new operation on word embeddings aimed to capturing categorical information by first learning and then applying an embedding mask for each analyzed category. Thus, we conducted a series of experiments related to categorization of words based on their embeddings. Several classical approaches were compared together with the one introduced in the paper which uses different embedding masks learnt for each category.
K-MEANS CLUSTER ANALYSIS AND MAHALANOBIS METRICS: A PROBLEMATIC MATCH OR AN OVERLOOKED OPPORTUNITY?

In this paper we consider the performance of the widely adopted K-means clustering algorithm when the classification variables are correlated. We measure performance in terms of recovery of the true data structure. As expected, performance worsens considerably if the groups have elliptical instead of spherical shape. We suggest some modifications to the standard K-means algorithm which considerably improve cluster recovery. Our approach is based on a combination of careful seed selection techniques and use of Mahalanobis instead of Euclidean distances. We show that our method performs well in a number of examples where the standard algorithm fails. In such applications our nonparametric technique is seen to be competitive when compared to parametric model-based clustering methods. Hence, our conclusion is that use of the Mahalanobis distance should become a standard option of the available K-means routines for non-hierarchical cluster analysis. This goal can be achieved by minor modifications in popular commercial software.
Multi-label software behavior learning

Software behavior learning is an important task in software engineering. Software behavior is usually represented as a program execution. It is expected that similar executions have similar behavior, i.e. revealing the same faults. Single-label learning has been used to assign a single label (fault) to a failing execution in the existing efforts. However, a failing execution may be caused by several faults simultaneously. Hence, it needs to assign multiple labels to support software engineering tasks in practice. In this paper, we present multi-label software behavior learning. A well-known multi-label learning algorithm ML-KNN is introduced to achieve comprehensive learning of software behavior. We conducted a preliminary experiment on two industrial programs: flex and grep. The experimental results show that multi-label learning can produce more precise and complete results than single-label learning.
Efficiency and diversity of protein localization by random signal sequences

Three randomly derived sequences that can substitute for the signal peptide of Saccharomyces cerevisiae invertase were tested for the efficiency with which they can translocate invertase or beta-galactosidase into the endoplasmic reticulum. The rate of translocation, as measured by glycosylation, was estimated in pulse-chase experiments to be less than 6 min. When fused to beta-galactosidase, these peptides, like the normal invertase signal sequence, direct the hybrid protein to a perinuclear region, consistent with localization to the endoplasmic reticulum. The diversity of function of random peptides was studied further by immunofluorescence localization of proteins fused to 28 random sequences: 4 directed the hybrid to the endoplasmic reticulum, 3 directed it to the mitochondria, and 1 directed it to the nucleus.
Evidence of long recurrence times and low slip rate along the 1668 Tancheng earthquake fault

Fault slip rates and recurrence intervals of large earthquakes for active faults are important parameters for better understanding active faults and assessing their seismic hazard. The Tanlu fault, located in the densely populated and economically developed area of eastern China is thought to be the source of the M 7 Anqiu earthquake in 70 BC, and M 8½ Tancheng earthquake in 1668. Understanding the recurrence interval of paleoearthquakes and fault slip rates for the Tancheng earthquake fault is critical for assessing the potential for seismic risk and assessment for the Tanlu fault. However, the only published study used several trenches and a single trench does not completely record the sequence of paleoearthquake events, leaving a large uncertainty of seismic hazard. GPS observations in North China show that there is no significant velocity gradient across the Tanlu fault, yet the long-term slip rate of the Tancheng segment of the fault is estimated to be significantly higher, up to 2 mm/a. Therefore, it is critical to conduct further research on the paleoearthquake history and slip rates of this fault segment to reconcile these contrasting results. In this study, we utilize aerial photographs and high-resolution satellite imagery, combined with field investigations of a surface rupture formed by the 1668 earthquake. The earthquake rupture is ~80 m long and ~2.5 m high, located in the Huaqiao village of northeastern Tancheng County. A gully across the rupture reveals a right lateral dislocation of approximately 36 m. We excavated two trenches on both sides of the rupture. Trench 1 reveals a positive flower structure and is consistent with a right lateral strike-slip fault with a thrust component consistent with the modern regional stress field. Trench 2 reveals a colluvial wedge formed by the latest paleoearthquake with a fine-grained deposit overlapping the colluvial wedge. The latest paleoearthquake should occur prior to deposition of the fine-grained deposit. AMS-14 C radiocarbon dating was used to determine the age of the event and is approximately 12.8+4.0/−3.7 ka, indicating a recurrence interval of large earthquakes greater than 10 ka, consistent with the results from other segments of the Tanlu fault. Combined with an average slip of ~9 m for the 1668 Tancheng earthquake, the dextral slip rate along the Tancheng earthquake fault since the end of the late Pleistocene is estimated to be 0.7 mm/a, consistent with low interseismic strain accumulation based on geodetic observations across the North China region
Ground segmentation and occupancy grid generation using probability fields

This paper proposes a novel technique for segmenting the ground plane and at the same time estimating the occupancy probability of each point in a scene. Using a stereo camera rig, our system first calculates a disparity map and transforms it to a v-disparity map, which is then filtered and processed to generate a corresponding probability field. The probability field generated is then used for precise segmentation of ground planes as well as for the generation of occupancy grids. Unlike what is proposed in the prior art, our system requires minimal initialization and is independent of the stereo sensor characteristics as well as the parameters of the disparity algorithm. More importantly, our technique does not require any prior assumption about the terrain visual characteristics. Experimental results using sequences of images from two different data sets are presented to validate the proposed methods.
Visual Spike Coding Using a Statistically Optimized Overcomplete Representation

In order to explore visual coding strategies, we use a wavelet-like transform which output is sparse, as is observed in the primary visual areas [ 6]. This transform is defined in the context of a feed-forward spiking neural network, and the output is the list of its neurons’ spikes: it is recursively constructed using a greedy matching pursuit scheme which first selects best matches and then laterally interacts with its correlated neighbors. We study the quality of this algorithm and its enhancement by the prior knowledge of the statistics of its input, namely natural images. An application to image compression is shown which is comparable to other techniques such as JPEG at low bit compression.
An integrated approach to developing sensor network solutions

This paper describes a prototype sensor networking platform and its associated development environment. Key elements of the system are the ESB sensor hardware, the Contiki operating system, and the communication stack, which includes a MAC layer and a highly optimized TCP/IP. Because the work is driven by prototype applications being developed by project partners, particular attention is paid to the development environment and to practical deployment issues. Three prototype applications are also presented.
Voice conversion in high-order eigen space using deep belief nets

This paper presents a voice conversion technique using Deep Belief Nets (DBNs) to build high-order eigen spaces of the source/target speakers, where it is easier to convert the source speech to the target speech than in the traditional cepstrum space. DBNs have a deep architecture that automatically discovers abstractions to maximally express the original input features. If we train the DBNs using only the speech of an individual speaker, it can be considered that there is less phonological information and relatively more speaker individuality in the output features at the highest layer. Training the DBNs for a source speaker and a target speaker, we can then connect and convert the speaker individuality abstractions using Neural Networks (NNs). The converted abstraction of the source speaker is then brought back to the cepstrum space using an inverse process of the DBNs of the target speaker. We conducted speakervoice conversion experiments and confirmed the efficacy of our method with respect to subjective and objective criteria, comparing it with the conventional Gaussian Mixture Model-based method.
The TAT-RasGAP317-326 anti-cancer peptide can kill in a caspase-, apoptosis-, and necroptosis-independent manner

Tumor cell resistance to apoptosis, which is triggered by many anti-tumor therapies, remains a major clinical problem. Therefore, development of more efficient therapies is a priority to improve cancer prognosis. We have previously shown that a cell-permeable peptide derived from the p120 Ras GTPase-activating protein (RasGAP), called TAT-RasGAP317-326, bears anti-malignant activities in vitro and in vivo, such as inhibition of metastatic progression and tumor cell sensitization to cell death induced by various anti-cancer treatments. Recently, we discovered that this RasGAP-derived peptide possesses the ability to directly kill some cancer cells. TAT-RasGAP317-326 can cause cell death in a manner that can be either partially caspase-dependent or fully caspase-independent. Indeed, TAT-RasGAP317-326-induced toxicity was not or only partially prevented when apoptosis was inhibited. Moreover, blocking other forms of cell death, such as necroptosis, parthanatos, pyroptosis and autophagy did not hamper the killing activity of the peptide. The death induced by TAT-RasGAP317-326 can therefore proceed independently from these modes of death. Our finding has potentially interesting clinical relevance because activation of a death pathway that is distinct from apoptosis and necroptosis in tumor cells could lead to the generation of anti-cancer drugs that target pathways not yet considered for cancer treatment.
Hyperexcitability, Interneurons, and Loss of GABAergic Synapses in Entorhinal Cortex in a Model of Temporal Lobe Epilepsy

Temporal lobe epilepsy is the most common type of epilepsy in adults, and its pathophysiology remains unclear. Layer II stellate cells of the entorhinal cortex, which are hyperexcitable in animal models of temporal lobe epilepsy, provide the predominant synaptic input to the hippocampal dentate gyrus. Previous studies have ascribed the hyperexcitability of layer II stellate cells to GABAergic interneurons becoming “dormant” after disconnection from their excitatory synaptic inputs, which has been reported to occur during preferential loss of layer III pyramidal cells. We used whole-cell recording from slices of entorhinal cortex in pilocarpine-treated epileptic rats to test the dormant interneuron hypothesis. Hyperexcitability appeared as multiple action potentials and prolonged depolarizations evoked in layer II stellate cells of epileptic rats but not controls. However, blockade of glutamatergic synaptic transmission caused similar percentage reductions in the frequency of spontaneous IPSCs in layer II stellate cells of control and epileptic rats, suggesting similar levels of excitatory synaptic input to GABAergic interneurons. Direct recordings and biocytin labeling revealed two major types of interneurons in layer III whose excitatory synaptic drive in epileptic animals was undiminished. Interneurons in layer III did not appear to be dormant; therefore, we tested whether loss of GABAergic synapses might underlie hyperexcitability of layer II stellate cells. Stereological evidence of fewer GABAergic interneurons, fewer gephyrin-immunoreactive punctae, and reduced frequency of spontaneous IPSCs and miniature IPSCs (recorded in tetrodotoxin) confirmed that layer II stellate cell hyperexcitability is attributable, at least in part, to reduced inhibitory synaptic input.
Assets and Poverty Traps in Rural Bangladesh

Using longitudinal survey from rural Bangladesh, this article examines the determinants of land and asset accumulation over time and explores why some households may be trapped in asset poverty. Non-parametric and parametric methods are used to discern the shape of the asset accumulation path, and whether unique or multiple equilibria exist. We find evidence for concavity of the dynamic asset frontier but no evidence for multiple equilibria. It is suggested that the existence of well-functioning factor markets in rural Bangladesh and elsewhere in South Asia explain the contrasts between our results and those for several African countries.
Bootstrapping the Semantic Web of Social Online Communities

Mining and searching the social web is hardly possible without a noteworthy amount of data available in an interoperable format. This paper enumerates and compares several techniques which can be applied to obtain large quantities of RDF data describing social web sites. Advantages, drawbacks and potential issues of each of these methods are discussed. Practical experimentation permits to illustrate and to discuss the convenience of each approach.
Performance analysis of traffic behavior in base station network — from complex network's perspective

Many research results show that in real world, networks are neither regular nor random but ones with the feature of scale-free characteristic. Applying this feature in telephone network, traffic behavior has been proved to have significant relationship with the user network. However, in a particular scenario, objective existence of user network cannot be changed and each user can only be occupied in one call, so the traffic behavior under this scenario is determined, which means no improvement strategies can be proposed. Based on this point, base station network is proposed: its relation can be changed by adding some new base stations; what's more, base station can support many calls simultaneously, then the limitation factor is subject to the number of capacity at each base station node, which can also be controlled. In this situation, some configurations can be proposed to improve the system performance. In this paper, we establish the base station network with weighted scale-free property. Through comparing with fully-connected base station network which was widely used in the previous model, we research on the effects of network relation on traffic behavior. Then a channel capacity distribution strategy is proposed to improve the system performance, which also verifies the advantage of base station network establishment.
High-Performance and Ultra-Broadband Metamaterial Absorber Based on Mixed Absorption Mechanisms

Perfect absorbers are highly desirable in many military applications, such as radar cross section (RCS) reduction, cloaking devices, and also sensor detectors; however, most approaches (such as wedge and pyramidal absorbers, multi-resonant absorbers) intrinsically suffer from very large size at low-frequency domain, limited bandwidth, as well as low absorption ratio issues. In this paper, we solve these issues via combining the Huygens metasurface and three-layers slab impedance metasurface, with the former satisfying the novel impedance matching theory and the latter exhibiting multi-resonant property and optimized conductivities, which achieve high-efficiency absorption at lower frequency range (1–3 GHz) and higher frequency region (3–18 GHz), respectively. To demonstrate our concept, we design/fabricate a realistic metasurface absorber working in the microwave region, and perform experiments to demonstrate that it can achieve an ultra-broadband (1–18 GHz) performance with absorption rate better than 75%. The numerical simulations are in good agreements with experiments, indicating that the absorption efficiency can be further pushed to 92% within the whole working band by optimizing our designs. More importantly, our device is insensitive for different polarizations and oblique incidences. Our findings can stimulate the realizations of ultra-broadband meta-devices, particularly can enhance the cloaking technology relying on high-efficiency absorption.
Efficient Online Performance Monitoring of Computing Systems Using Predictive Models

Performance monitoring of datacenters provides vital information for dynamic resource provisioning, anomaly detection, capacity planning, and metering decisions. Online monitoring, however, incurs a variety of costs: the very act of monitoring a system interferes with its performance, consuming network bandwidth and disk space. With the goal of reducing these costs, we develop and validate a strategy based on exploiting the underlying structure of the signal being monitored to sparsify it prior to transmission to a monitoring station for analysis and logging. Specifically, predictive models are designed to estimate the signals of interest. These models are then used to obtain prediction errors -- the error between the signal and the corresponding estimate -- that are then treated as a sparse representation of the original signal while retaining key information. This transformation allows for far less data to be transmitted to the monitoring station, at which point the signal is reconstructed by simply using the prediction errors. We show that classical techniques such as principal component analysis (PCA) can be applied to the reconstructed signal for anomaly detection. Experimental results using the Trade6 and RuBBoS benchmarks indicate a significant reduction in overall transmission costs -- greater that 95% in some cases -- while retaining sufficient detection accuracy.
Wet shape memory alloy actuators for active vasculated robotic flesh

A new type of actuator is presented where shape memory alloy (SMA) wires are embedded within artificial "blood vessels. " Fluid flowing through vessels allows the SMA wires to be rapidly cooled by convection, resulting in greater bandwidth than ordinarily possible. Combinations of electric, fluidic, and thermal inputs can be used to control the contraction/extension of the SMA wires within the compliant vessels. These wet vascular SMA actuators can be used as robotic muscle or even embedded in a compliant rubber material to create an active vasculated robotic flesh. This paper begins by proposing a type of biomimetics where robots and machines are imbued with a vasculature or network of blood vessels. The concept of a wet SMA actuator is then introduced as an immediate application of a vasculated robot. A wet SMA actuator is then designed and implemented. Initial prototypes are 3 mm in diameter and are capable of 2% strain at 2 Hz by pulsing 2 A of current and 3 mL/s of water. Reservoirs of hot and cold water are also used to recycle the thermal energy and allow the actuators to exert static force with no electric current. Finally, multiple vascular SMA actuators are imbedded within a 4 mm thick rubber sheet to implement the active vasculated robotic flesh.
The effect of organizational identification on job embeddedness: evidence from new generation of rural migrant workers in China

The purpose of this paper was to examine the relationships among work overload (WO), compensation (COM), organizational identification (OI) and organization embeddedness (OE) in the context of manufacturing industry in China through social identity theory. A 37-item questionnaire was filled by 384 new generation of rural migrant workers. Data were examined through a two-stage of first-order of reflective model and second-order reflective-formative hierarchical model using PLS-SEM. The empirical results indicate that COM and OI positively and significantly predicted OE, while WO was found to have no direct effect on OE. In addition, COM positively and significantly was associated with OI, whereas WO affected OI, negatively. Further examination of the mediation effects of OI revealed that OI could fully mediate the relationship between WO and OE. Moreover, OI also had a partial mediator role in the relationship between COM and OE. The study concluded with several implications and recommendations for future research.
Postschool Engagement Predictors for Youth with Intellectual Disability: Results from South Carolina

ABSTRACT Postschool outcomes of youth with intellectual disability (ID) continue to trouble practitioners and scholars. The purpose of this study was to analyze postschool engagement outcome data for 360 survey respondents with ID in South Carolina in the areas of employment and postsecondary education/training. Specifically, we examined the relationship of special education exit reason, as well as, student, school, and district variables to youth’s postschool engagement. We used logistic regression to estimate probability of engagement one year after exiting high school. Results indicated that special education exit reason, gender, school retention rates, district attendance rates, percentage of students with disabilities within a district, percentage of students within a district receiving free and reduced lunch, district retention rates, and district suspension/expulsion rates were significantly related to three postschool engagement outcomes. Implications for future research and practice are discussed.