Miracle-dz/UniFAR-FTUs huggingface dataset:
End-to-End Text Recognition with Hybrid HMM Maxout Models

The problem of detecting and recognizing text in natural scenes has proved to be more challenging than its counterpart in documents, with most of the previous work focusing on a single part of the problem. In this work, we propose new solutions to the character and word recognition problems and then show how to combine these solutions in an end-to-end text-recognition system. We do so by leveraging the recently introduced Maxout networks along with hybrid HMM models that have proven useful for voice recognition. Using these elements, we build a tunable and highly accurate recognition system that beats state-of-the-art results on all the sub-problems for both the ICDAR 2003 and SVT benchmark datasets.
Spare Me: Towards an Empathetic Tool for Helping Adolescents &amp; Teenagers Cope with Sickle Cell

Sickle cell disease (SCD) is a painful blood disorder that affects hemoglobin in red blood cells causing them to sickle and clog the veins of its sufferers. More than 100,000 people live with SCD in the U.S. And more' than a million people are living with the disease world-wide. 60% of SCD patients, aged ten to nineteen, experience one or more painful events a year. Mobile health applications can improve the overall well-being of patients with chronic diseases by lowering costs, improving quality and access of care, and shifting behavior to prevention of hospital stays. Spare Me is a mobile health tool, that once complete, will help to predict sickle cell crises and communicate with its users on how to cope and remain healthy. This paper describes the affective communication strategy called Spare Me How. Spare Me How uses heart rate variability, pain-levels, diet, and fluid intake to create affective messages to send empathetic messages through instant message (IM).
Traffic offloading under outage QoS constraint in heterogeneous cellular networks

Heterogeneous cellular networks offload the mobile data traffic to small cell base stations to reduce the workload on the macro base stations. Our objective is to maximize the sum rate of the down-links for the whole network under outage QoS constraint. To achieve the objective, we have to jointly solve the user association problem and resource allocation problem. We formulate the two problems into a joint optimization problem and convert it into an equivalent game theoretic formulation. We employ payoff based log linear learning and propose an algorithm that converges to one of the existing Nash equilibrium. We then provide extensive simulation results to verify the performance of our proposed algorithm.
Will searching for meaning bring well-being？

: Studies on well-being have been derived from two general perspectives: the hedonic approach and the eudaimonic approach. “Flourishing”, being a newly holistic, comprehensive and structural standard for evaluating well-being, is receiving increasing attentions among researchers. Meaning in life is closely related to well-being. It reflects the value of existence and the purpose of life of an individual, has implications on one's motivation, and can be realized in one's actions. Meaning in life includes two dimensions, presence of meaning and search for meaning. “Presence of meaning” is positively related to increased well-being. While the relation between searching for meaning and well-being is negative, the negative relation has variability and transience characteristics. From the perspective of eudaimonia, although negative experiences and feelings reduce individual's current happiness, individuals can achieve their goals and self-worth in the process of searching for meaning, thus acquiring lasting well-being internally.
Methods, Challenges and Potentials of Single Cell RNA-seq

RNA-sequencing (RNA-seq) has become the tool of choice for transcriptomics. Several recent studies demonstrate its successful adaption to single cell analysis. This allows new biological insights into cell differentiation, cell-to-cell variation and gene regulation, and how these aspects depend on each other. Here, I review the current single cell RNA-seq (scRNA-seq) efforts and discuss experimental protocols, challenges and potentials.
A single nucleotide polymorphism in primary-microRNA-146a reduces the expression of mature microRNA-146a in patients with Alzheimer's disease and is associated with the pathogenesis of Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and is the most common form of dementia among the aging population. Although the incidence of the disease continues to increase, no cure has been developed. Effective treatment is restricted not only due to the lack of curative medicine, but also due to limited understanding of the underlying mechanisms and the diffculties in accurately diagnosing AD in its earliest stages prior to clinical symptoms. Micro (mi) RNAs (miR) have gained increasing attention in the investigation of neurodegenerative diseases. Previous reports have demonstrated that deregulation of miR-146a-5p is associated with the pathogenesis of human AD. In the present study, the coding region of primary (pri)-miR-146a in patients with AD was scanned and the rare C allele of rs2910164 was found to be associated with AD. Using reverse transcription quantitative polymerase chain reaction, it was demonstrated that site variation reduced the expression of mature miR-146a-5p. Notably, a reduction in the expression of miR-146a-5p led to less effcient inhibition of target genes, including Toll-like receptor (TLR)2, which is important in the pathogenesis of AD. Biological function investigations in RAW264.7 cells indicated that, compared with the G allele, the rare C allele upregulated the expression of tumor necrosis factor-α following stimulation with β-amyloid. These findings suggested that one common polymorphism in pri-miR-146a may contribute to the genetic predisposition to AD by disrupting the production of miR-146a-5p and affecting the expression and function of TLR2.
Decomposing the ASASA Block Cipher Construction

We consider the problem of recovering the internal specification of a general SP-network consisting of three linear layers (A) interleaved with two Sbox layers (S) (denoted by ASASA for short), given only black-box access to the scheme. The decomposition of such general ASASA schemes was first considered at ASIACRYPT 2014 by Biryukov et al. which used the alleged difficulty of this problem to propose several concrete block cipher designs as candidates for white-box cryptography. In this paper, we present several attacks on general ASASA schemes that significantly outperform the analysis of Biryukov et al. As a result, we are able to break all the proposed concrete ASASA constructions with practical complexity. For example, we can decompose an ASASA structure that was supposed to provide 64-bit security in roughly 2 steps, and break the scheme that supposedly provides 128-bit security in about 2 time. Whenever possible, our findings are backed up with experimental verifications.
Groupwise Recursive Channel Estimation for Space-Frequency Block Coded OFDM Systems in Doubly Selective Fading Channels

In this paper, we propose two computationally efficient groupwise recursive channel estimation algorithms for channel encoded SFBC-OFDM systems in doubly (i.e., frequency and time) selective fading channels. The first of these algorithms is based on the recursive least squares (RLS) principle whereas the second one employs the minimum mean square error (MMSE) criterion. To reduce the computational complexity associated with the groupwise recursive channel estimation schemes, we propose an inverse QR decomposition (IQR) algorithm based on scaled Givens rotations. The performance of the proposed algorithms is evaluated via simulations and compared to the case with perfect channel state information (CSI) knowledge at the receiver. The simulations show that the proposed algorithms perform reasonably close to the perfect CSI case under various channel conditions.
Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks

Scalable and effective exploration remains a key challenge in reinforcement learning (RL). While there are methods with optimality guarantees in the setting of discrete state and action spaces, these methods cannot be applied in high-dimensional deep RL scenarios. As such, most contemporary RL relies on simple heuristics such as epsilon-greedy exploration or adding Gaussian noise to the controls. This paper introduces Variational Information Maximizing Exploration (VIME), an exploration strategy based on maximization of information gain about the agent's belief of environment dynamics. We propose a practical implementation, using variational inference in Bayesian neural networks which efficiently handles continuous state and action spaces. VIME modifies the MDP reward function, and can be applied with several different underlying RL algorithms. We demonstrate that VIME achieves significantly better performance compared to heuristic exploration methods across a variety of continuous control tasks and algorithms, including tasks with very sparse rewards.
Molecular and functional diversity of mammalian Gs‐stimulated adenylyl cyclases

Receptor‐regulated adenylyl cyclase in mammalian systems is among the best‐studied of the cell surface signaling pathways that utilize G‐proteins as transducers. In addition to the multiplicity of receptors and Gs proteins that function in this pathway, recent studies have shown that substantial molecular diversity exists in the effector as well. Full‐length cDNAs encoding six different G‐protein‐regulated adenylyl cyclases have been isolated, and partial sequences identifying two more are known. These eight mammalian adenylyl cyclases can be grouped into five distinct families. The different types share some common properties such as stimulation by Gs and the diterpene forskolin. They show very distinct patterns of regulation by the βγ‐subunits of G‐proteins and protein kinases such as protein kinase C. The different types also appear to be localized in a tissue‐specific manner. This diversity of regulatory features indicates that the effector can play an important role in determining the routing of signals to the cAMP pathway. The tissue and cell type‐specific localization of the individual forms suggests that effectors such as adenylyl cyclase could be potential targets for a new generation of cell and tissue‐specific drugs. —Iyengar, R. Molecular and functional diversity of mammalian Gs‐stimulated adenylyl cyclases. FASEB J. 7: 768‐775; 1993.
Molecular Cloning and Characterization of G Alpha Proteins from the Western Tarnished Plant Bug, Lygus hesperus

The Gα subunits of heterotrimeric G proteins play critical roles in the activation of diverse signal transduction cascades. However, the role of these genes in chemosensation remains to be fully elucidated. To initiate a comprehensive survey of signal transduction genes, we used homology-based cloning methods and transcriptome data mining to identity Gα subunits in the western tarnished plant bug (Lygus hesperus Knight). Among the nine sequences identified were single variants of the Gαi, Gαo, Gαs, and Gα12 subfamilies and five alternative splice variants of the Gαq subfamily. Sequence alignment and phylogenetic analyses of the putative L. hesperus Gα subunits support initial classifications and are consistent with established evolutionary relationships. End-point PCR-based profiling of the transcripts indicated head specific expression for LhGαq4, and largely ubiquitous expression, albeit at varying levels, for the other LhGα transcripts. All subfamilies were amplified from L. hesperus chemosensory tissues, suggesting potential roles in olfaction and/or gustation. Immunohistochemical staining of cultured insect cells transiently expressing recombinant His-tagged LhGαi, LhGαs, and LhGαq1 revealed plasma membrane targeting, suggesting the respective sequences encode functional G protein subunits.
A Location Based Heuristic for General Routing Problems

We present a general framework for modeling routing problems based on formulating them as a traditional location problem called the capacitated concentrator location problem. We apply this framework to two classical routing problems: the capacitated vehicle routing problem and the inventory routing problem. In the former case, the heuristic is proven to be asymptotically optimal for any distribution of customer demands and locations. Computational experiments show that the heuristic performs well for both problems and, in most cases, outperforms all published heuristics on a set of standard test problems.
REVIEW OF REMOTE SENSING IMAGE SEGMENTATION TECHNIQUES

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. Image segmentation by region merging follows a particular order in the choice of regions. The target of segmentation is always to simplify and/or change the representation of a graphic into something that is more meaningful and simpler to analyze. Image segmentation is normally used to locate objects and boundaries (lines, curves, etc.) in images. To improve segmentation accuracy and the correctness, this paper proposed a Dynamic Statistical Region Merging (DSRM) algorithm to find the automatically select scale value. The purpose of this paper is to gather various segmentation techniques that can be used for the segmentation of remote sensing images (RSI). The paper provides good starting for researchers to find automatically select scale value using the combination of DSRM and fuzzy logic.
Semantic Web-marketing 3.0: Advertisement transformation by modeling

In this paper we have focused on the evolution of the Web-marketing meaning the passage of the Web-marketing 2.0 to 3.0, baptized “Semantic Web-marketing”, the main idea being to make easier to the Internet user to use a huge and disrupting stream of information and make it organized and easily accessible. As so, we have chosen to use the N-tiers applications and the MDA (Model Driving Architecture) transformation. In this paper we are going to present a model-driven approach to the development of N-tiers web applications based on the UML class diagram. The transformation language is the MOF 2.0 QVT (Meta-Object Facility 2.0 Query-View-Transformation) standard which defines the meta-model for the development of model transformation.
Association of cerebral microbleeds in acute ischemic stroke with high serum levels of vascular endothelial growth factor.

OBJECTIVE To determine whether vascular endothelial growth factor (VEGF) levels are associated with the presence of cerebral microbleeds (CMBs) in patients after acute ischemic stroke. DESIGN A cross-sectional study that used blood samples obtained within 24 hours of symptom onset from patients who experienced acute stroke to measure VEGF levels by enzyme immunoassay. A validated CMB rating scale was used to analyze acutely acquired magnetic resonance images, with the rater blind to clinical details and VEGF levels. SETTING Accident and Emergency Department at University College Hospital, London, England. PATIENTS Twenty patients who experienced acute ischemic stroke. MAIN OUTCOME MEASURES Presence of CMBs and serum level of VEGF. RESULTS Five of the 20 patients with acute ischemic stroke (25%) had CMBs. The median VEGF level in the CMB group was significantly higher than that in the group without CMBs (P = .003). CONCLUSION An increase in vascular permeability secondary to a raised VEGF level may have a role in the genesis of CMBs in patients with acute ischemic stroke.
A Virtual Head Driven by Music Expressivity

In this paper, we present a system that visualizes the expressive quality of a music performance using a virtual head. We provide a mapping through several parameter spaces: on the input side, we have elaborated a mapping between values of acoustic cues and emotion as well as expressivity parameters; on the output side, we propose a mapping between these parameters and the behaviors of the virtual head. This mapping ensures a coherency between the acoustic source and the animation of the virtual head. After presenting some background information on behavior expressivity of humans, we introduce our model of expressivity. We explain how we have elaborated the mapping between the acoustic and the behavior cues. Then, we describe the implementation of a working system that controls the behavior of a human-like head that varies depending on the emotional and acoustic characteristics of the musical execution. Finally, we present the tests we conducted to validate our mapping between the emotive content of the music performance and the expressivity parameters.
Time-bounded adaptive A

In this paper, we investigate real-time path planning in static terrain, as needed in video games. We introduce the game time model, where time is partitioned into uniform time intervals, an agent can execute one movement during each time interval, and search and movements are done in parallel. The objective is to move the agent from its start location to its goal location in as few time intervals as possible. For known terrain, we show experimentally that Time-Bounded A* (TBA*), an existing real-time search algorithm for undirected terrain, needs fewer time intervals than two state-of-the-art real-time search algorithms and about the same number of time intervals as A*. TBA*, however, cannot be used when the terrain is not known initially. For initially partially or completely unknown terrain, we thus propose a new search algorithm. Our Time-Bounded Adaptive A* (TBAA*) extends TBA* to on-line path planning with the freespace assumption by combining it with Adaptive A*. We prove that TBAA* either moves the agent from its start location to its goal location or detects that this is impossible - an important property since many existing realtime search algorithms are not able to detect efficiently that no path exists. Furthermore, TBAA* can eventually move the agent on a cost-minimal path from its start location to its goal location if it resets the agent into its start location whenever it reaches its goal location. We then show experimentally in initially partially or completely unknown terrain that TBAA* needs fewer time intervals than several state-of-the-art complete and real-time search algorithms and about the same number of time intervals as the best compared complete search algorithm, even though it has the advantage over complete search algorithms that the agent starts to move right away.
Wireless Magnetoelastic Monitoring of Biliary Stents

This paper presents a system for wirelessly monitoring the accumulation of sludge in a biliary stent. Two generations of the system are detailed. The first-generation system utilizes a 2 × 37.5-mm ribbon sensor with a mass of 18 mg, along with 0.8-mm-thick × 1.6-mm-diameter neodymium magnets to bias the sensor. Both components are integrated with a 4-mm-diameter stainless steel stent. The second-generation system comprises a sensor and a magnetic layer [consisting of strontium ferrite particles suspended in polydimethylsiloxane (PDMS)] that conform to the meshed topology and tubular curvature of a 5-mm-diameter Elgiloy stent. The second-generation sensors have an active area of 7.5 × 29 mm and a mass of 9.1 mg. The sensors in both generations are fabricated from 28-¿m -thick foils of magnetoelastic 2826 MB Metglas, an amorphous Ni-Fe alloy. Analytical and finite-element models that predict sensor response in the dynamic biological environment are presented. The response of each system to viscosity changes that precede and accompany biliary sludge accumulation is tested, with resonant frequency changes of 2.8% and 6.5% over a 10-cP range for each respective generation. Sludge accumulation is simulated with successive coatings of either paraffin or an acrylate terpolymer. Resonant frequency response to this mass loading effect is similar for both generations of the system, showing a 40% decrease after applying a mass load of 2.5× the mass of the sensor.
Particle-based modelling of aggregation and fragmentation processes in chaotic advection: Fractal aggregates

The incorporation of particle inertia into the usual mean field theory for particle aggregation and fragmentation in fluid flows is still an unsolved problem. We therefore suggest an alternative approach that is based on the dynamics of individual inertial particles and apply this to study steady state particle size distributions in a paradigmatic 2d flow. We show how a fractal structure, typical for aggregates in natural systems, can be incorporated in an approximate way into the aggregation and fragmentation model by introducing effective densities and radii. Based on this model we investigate numerically the impact of three different modes of fragmentation: large-scale splitting, where fragments have similar sizes, erosion, where one of the fragments is much smaller than the other and uniform fragmentation, where all sizes of fragments occur with the same probability. We find that the steady state particle size distribution depends strongly on the mode of fragmentation. In the case of erosion, a multimodal distribution evolves, whereas the resulting size distribution for large-scale fragmentation is exponential. As some aggregate distributions found in published measurements share this latter characteristic, this may indicate that large-scale fragmentation is the primary mode of fragmentation in these cases.
Prolonged Nitric Oxide Exposure Enhances Anoikis Resistance and Migration through Epithelial-Mesenchymal Transition and Caveolin-1 Upregulation

Nitric oxide (NO) in tumor microenvironment may have a significant impact on metastatic behaviors of cancer. Noncytotoxic doses of NO enhanced anoikis resistance and migration in lung cancer H23 cells via an increase in lamellipodia, epithelial-mesenchymal transition (EMT) markers including vimentin and snail, and caveolin-1 (Cav-1). However, the induction of EMT was found in Cav-1-knock down cells treated with NO, suggesting that EMT was through Cav-1-independent pathway. These effects of NO were consistently observed in other lung cancer cells including H292 and H460 cells. These findings highlight the novel role of NO on EMT and metastatic behaviors of cancer cells.
Space-efficient, byte-wise incremental and perfectly private encryption schemes

The problem raised by incremental encryption is the overhead due to the larger storage space required by the provision of random blocks together with the ciphered versions of a given document. Besides, permitting variable-length modifications on the ciphertext leads to privacy preservation issues. In this paper we present incremental encryption schemes which are space-efficient, byte-wise incremental and which preserve perfect privacy in the sense that they hide the fact that an update operation has been performed on a ciphered document. For each scheme, the run time of updates performed turns out to be very efficient and we discuss the statistically adjustable trade-off between computational cost and storage space required by the produced ciphertexts.
Cooperation in Multi-hop Cellular Networks with Extended Security Analysis 1 ∗

In multi-hop cellular networks, the existence of a communication link between the mobile station and the base station is not required: a mobile station that has no direct connection with a base station can use other mobile stations as relays. Compared with conventional (single-hop) cellular networks, this new generation can lead to a better usage of the available spectrum and to a reduction of infrastructure costs. However, these benefits would vanish if the mobile nodes did not properly cooperate and forward packets for other nodes. In this paper, we propose a charging and rewarding scheme to encourage the most fundamental operation, namely packet forwarding. We analyse the robustness of our protocols against rational and malicious attacks. We show that our protocols thwart rational attacks and detect malicious attacks. We also show that our solution makes collaboration rational for selfish nodes.