Miracle-dz/UniFAR-FTUs huggingface dataset:
Unique Decoding of General AG Codes

A unique decoding algorithm for general AG codes, namely multipoint evaluation codes on algebraic curves, is presented. It is a natural generalization of the previous decoding algorithm which was only for one-point AG codes. As such, it retains the same advantages of fast speed, regular structure, and direct message recovery. Upon this generalization, we add a technique from the Guruswami-Sudan list decoding that boosts the decoding speed significantly. Compared with other known decoding algorithms for general AG codes, it has a similar decoding performance and allows streamlined practical implementation by its simple and regular structure.
Device-to-Device Communication in LTE-Advanced Networks: A Survey

Among the LTE-A communication techniques, Device-to-Device (D2D) communication which is defined to directly route data traffic between spatially closely located mobile user equipments (UEs), holds great promise in improving energy efficiency, throughput, delay, as well as spectrum efficiency. As a combination of ad-hoc and centralized communication mechanisms, D2D communication enables researchers to merge together the long-term development achievements in previously disjoint domains of ad-hoc networking and centralized networking. To help researchers to have a systematic understanding of the emerging D2D communication, we provide in this paper a comprehensive survey of available D2D related research works ranging from technical papers to experimental prototypes to standard activities, and outline some open research problems which deserve further studies.
Low prevalence of haemosporidian parasites in the introduced house sparrow (Passer domesticus) in Brazil

Species that are introduced to novel environments can lose their native pathogens and parasites during the process of introduction. The escape from the negative effects associated with these natural enemies is commonly employed as an explanation for the success and expansion of invasive species, which is termed the enemy release hypothesis (ERH). In this study, nested PCR techniques and microscopy were used to determine the prevalence and intensity (respectively) of Plasmodium spp. and Haemoproteus spp. in introduced house sparrows and native urban birds of central Brazil. Generalized linear mixed models were fitted by Laplace approximation considering a binomial error distribution and logit link function. Location and species were considered as random effects and species categorization (native or non-indigenous) as fixed effects. We found that native birds from Brazil presented significantly higher parasite prevalence in accordance with the ERH. We also compared our data with the literature, and found that house sparrows native to Europe exhibited significantly higher parasite prevalence than introduced house sparrows from Brazil, which also supports the ERH. Therefore, it is possible that house sparrows from Brazil might have experienced a parasitic release during the process of introduction, which might also be related to a demographic release (e.g. release from the negative effects of parasites on host population dynamics).
Neuron Dysfunction Is Induced by Prion Protein with an Insertional Mutation via a Fyn Kinase and Reversed by Sirtuin Activation in Caenorhabditis elegans

Although prion propagation is well understood, the signaling pathways activated by neurotoxic forms of prion protein (PrP) and those able to mitigate pathological phenotypes remain largely unknown. Here, we identify src-2, a Fyn-related kinase, as a gene required for human PrP with an insertional mutation to be neurotoxic in Caenorhabditis elegans, and the longevity modulator sir-2.1/SIRT1, a sirtuin deacetylase, as a modifier of prion neurotoxicity. The expression of octarepeat-expanded PrP in C. elegans mechanosensory neurons led to a progressive loss of response to touch without causing cell death, whereas wild-type PrP expression did not alter behavior. Transgenic PrP molecules showed expression at the plasma membrane, with protein clusters, partial resistance to proteinase K (PK), and protein insolubility detected for mutant PrP. Loss of function (LOF) of src-2 greatly reduced mutant PrP neurotoxicity without reducing PK-resistant PrP levels. Increased sir-2.1 dosage reversed mutant PrP neurotoxicity, whereas sir-2.1 LOF showed aggravation, and these effects did not alter PK-resistant PrP. Resveratrol, a polyphenol known to act through sirtuins for neuroprotection, reversed mutant PrP neurotoxicity in a sir-2.1-dependent manner. Additionally, resveratrol reversed cell death caused by mutant PrP in cerebellar granule neurons from prnp-null mice. These results suggest that Fyn mediates mutant PrP neurotoxicity in addition to its role in cellular PrP signaling and reveal that sirtuin activation mitigates these neurotoxic effects. Sirtuin activators may thus have therapeutic potential to protect from prion neurotoxicity and its effects on intracellular signaling.
Semiconductive Materials with Tunable Electrical Resistance and Surface Polarity Obtained by Asymmetric Functionalization of Janus Nanoparticles

Janus nanoparticles (JNPs) can offer significant potential for synthesis of multifunctional materials, due to their inherent property contrast between the lobes. Asymmetric surface chemical modifications on JNPs can be performed such that each lobe can carry different surface and/or bulk‐like properties, which could be combined in surprising ways. In this work, it is shown that snowman‐type polymeric JNPs can be used to make conductive materials with tunable resistance and surface polarity. By changing the relative size between a conductive and an electrically insulating lobe, the bulk powder conductivity within a series of JNPs by a factor of 10 without changing the intrinsic conductivity of the polymer can be tuned. In the same time, the surface polarity of the powder material decreased by a factor of 5. The possibility to synthesize multifunctional materials from JNPs building blocks that enable the coupling of a bulk‐like property with a surface functionality is therefore demonstrated.
Episodic but not semantic order memory difficulties in autism spectrum disorder: Evidence from the Historical Figures Task

Considerable evidence suggests that the episodic memory system operates abnormally in autism spectrum disorder (ASD) whereas the functions of the semantic memory system are relatively preserved. Here we show that the same dissociation also applies to the domain of order memory. We asked adult participants to order the names of famous historical figures either according to their chronological order in history (probing semantic memory) or according to a random sequence shown once on a screen (probing episodic memory). As predicted, adults with ASD performed less well than age- and IQ-matched comparison individuals only on the episodic task. This observation is of considerable importance in the context of developmental theory because semantic and episodic order memory abilities can be dissociated in typically developing infants before they reach the age at which the behavioural markers associated with ASD are first apparent. This raises the possibility that early emerging memory abnormalities play a role in shaping the developmental trajectory of the disorder. We discuss the broader implications of this possibility and highlight the urgent need for greater scrutiny of memory competences in ASD early in development.
Acid-etching and Hydration Influence on Dentin Roughness and Wettability

Adhesion of restorative and protective materials to dentin is an important requirement for operative and preventive dentistry. Wettability and roughness are dentin substrate conditions that are critical to establishing good adhesion. This study examined superficial and deep dentin for variations in water contact angle measurements and roughness for polished, etched, dehydrated, and rehydrated states. Superficial and deep dentin disks from 6 non-carious third molars were prepared for AFM (Atomic Force Microscope) observation, roughness measurement, and contact angle measurements following specific treatments: hydrated and polished, etched (10% H3P04), dehydrated (desiccator for 24 hrs); and rehydrated (in water for 24 hrs). Contact angles were measured by means of the ADSA (Axisymmetric Drop Shape Analysis) technique with filtered and purified water of surface tension 72.79 ergs/cm2. The AFM was used to quantify the intertubular roughness. Mean and SD of roughness and contact angle were calculated for each dentin state, and two-way Repeated Measures ANOVA with Tukey's HSD multiple comparisons were performed at p < 0.05. Wetting and roughness both increased after etching, with roughness tending to increase further while wettability dramatically decreased after desiccation. After rehydration, water contact angle values were equivalent to those of the etched condition. Although intertubular roughness did not depend on depth, lower water contact angles were found for deep dentin. Depth and dehydration resulted in altered dentin substrates with exposed hydrophobic moieties that could interfere with bonding to hydrophilic primer coats.
Effects of Poly(ADP-Ribose) Polymerase Inhibition in Bladder Damage Caused by Cyclophosphamide in Rats

It was previously shown that nitric oxide produced by inducible nitric oxide synthase (iNOS) and peroxynitrite are responsible for cyclophosphamide (CP)-induced cystitis. Since endogenous production of peroxynitrite is known to lead to poly(ADP-ribose) polymerase (PARP) activation, in this study, the aim was to evaluate whether the PARP activation pathway is also included in the pathogenesis of CP-induced bladder ulceration in rats. A total of 48 male albino Wistar rats were divided into 5 groups. Group 1 served as control and was given 2 ml saline; four groups received a single dose of CP (200 mg/kg) with the same time intervals. Group 2 received CP only; Group 3, selective iNOS inhibitor 1400W (20 mg/kg); Group 4, peroxynitrite scavenger ebselen (30 mg/kg); and Group 5, PARP inhibitor 3-aminobenzamide (20 mg/kg). CP injection resulted in severe cystitis with continuous macroscopic hemorrhage, strong edema, inflammation, and ulceration. Moreover, bladder iNOS activation and urine nitrite-nitrate levels were dramatically increased. Histologically, 1400W protected bladder against CP damage and decreased urine nitrite-nitrate levels and bladder iNOS induction. Ebselen has shown similar histologic results with 1400W without changing urinary nitrite-nitrate level and iNOS activity. Furthermore in the 3-aminobenzamide group, beneficial effects had also occurred including decreased ulceration. These results suggest that PARP activation involves pathogenesis of CP-induced bladder ulceration. Furthermore, PARP is not only important for ulceration but also for bladder edema, hemorrhage, and inflammation because of broken uroepithelial cellular integrity.
Unlocking the Potential of Simulators: Design with RL in Mind

Using Reinforcement Learning (RL) in simulation to construct policies useful in real life is challenging. This is often attributed to the sequential decision making aspect: inaccuracies in simulation accumulate over multiple steps, hence the simulated trajectories diverge from what would happen in reality. In our work we show the need to consider another important aspect: the mismatch in simulating control. We bring attention to the need for modeling control as well as dynamics, since oversimplifying assumptions about applying actions of RL policies could make the policies fail on real-world systems. We design a simulator for solving a pivoting task (of interest in Robotics) and demonstrate that even a simple simulator designed with RL in mind outperforms high-fidelity simulators when it comes to learning a policy that is to be deployed on a real robotic system. We show that a phenomenon that is hard to model - friction - could be exploited successfully, even when RL is performed using a simulator with a simple dynamics and noise model. Hence, we demonstrate that as long as the main sources of uncertainty are identified, it could be possible to learn policies applicable to real systems even using a simple simulator. RL-compatible simulators could open the possibilities for applying a wide range of RL algorithms in various fields. This is important, since currently data sparsity in fields like healthcare and education frequently forces researchers and engineers to only consider sample-efficient RL approaches. Successful simulator-aided RL could increase flexibility of experimenting with RL algorithms and help applying RL policies to real-world settings in fields where data is scarce. We believe that lessons learned in Robotics could help other fields design RL-compatible simulators, so we summarize our experience and conclude with suggestions.
Articulatory synthesis using corpus-based estimation of line spectrum pairs

An attempt to define a new articulatory synthesis method, in which the speech signal is generated through a statistical estimation of its relation with articulatory parameters, is presented. A corpus containing acoustic material and simultaneous recordings of the tongue and facial movements was used to train and test the articulatory synthesis of VCV words and short sentences. Tongue and facial motion data, captured with electromagnetic articulography and three-dimensional optical motion tracking, respectively, define articulatory parameters of a talking head. These articulatory parameters are then used as estimators of the speech signal, represented by line spectrum pairs. The statistical link between the articulatory parameters and the speech signal was established using either linear estimation or artificial neural networks. The results show that the linear estimation was only enough to synthesize identifiable vowels, but not consonants, whereas the neural networks gave a perceptually better synthesis.
Adaptive stochastic approximation by the simultaneous perturbation method

Stochastic approximation (SA) has long been applied for problems of minimizing loss functions or root-finding with noisy input information. As with all stochastic search algorithms, there are adjustable algorithm coefficients that must be specified and that can have a profound effect on algorithm performance. It is known that picking these coefficients according to an SA analogue of the deterministic Newton-Raphson algorithm provides an optimal or near-optimal form of the algorithm. This paper presents a general adaptive SA algorithm that is based on an easy method for estimating the Hessian matrix at each iteration while concurrently estimating the primary parameters of interest. The approach applies in both the gradient-free optimization (Kiefer-Wolfowitz) and root-finding/stochastic gradient-based (Robbins-Monro) settings and is based on the "simultaneous perturbation" idea introduced previously.
Visibility-Based Pursuit-Evasion in Three-Dimensional Environments

The problem of visibility-based pursuit-evasion was first introduced in 1992 by Suzuki and Yamashita [19]. Since then, it has attracted considerable attention in the communities of robot motion planning and computational geometry. Researchers have considered many variations of the problem, including curved environments[11]; pursuers equipped with one or two “flashlights”, or rays of visibility[12, 15, 16]; and pursuers guarding “rooms”[13] and “corridors”[2]. The complexity of pursuit-evasion with omnidirectional visibility has remained an unsolved problem for almost a decade, and was settled only recently[16]. With all this effort focused on the twodimensional case, the three-dimensional case has remained completely unexplored. However, many of the tools to reason about 3D visibility already exist in literature from computer vision and graphics. Data structures for maintaining global visibility information have been studied for several decades within the framework of aspect graphs[9, 17, 18], and, more recently, visibility complexes[4]. The present paper leverages this body of work to reason about visibility issues for the pursuit-evasion problem in 3D. We develop a visibility framework similar to the conservative regions decomposition of Guibas et. al.[7] for both polyhedral and curved environments. Part of the reason for the apparent previous “neglect” of pursuit-evasion in 3D is that visibility issues are perceived to be a lot more complex than in 2D. As we will show in our paper, this impression is not entirely unjustified. In 2D, there are only two kinds of critical events that change the state of visibility-based information about the environment, and the changes they
Information-based risk assessment software architecture

Effective system management requires a thorough un- derstanding of risks. As more systems depend on software to provide their functionalities, the need to assess the contribution of software to the risks of such systems becomes inevitable. This paper presents a framework for developing a risk assessment tool that aims to assist users in identifying hazards and risks associ- ated with software and their impacts on its entire system and en- vironment. Our approach employs several modules based on relevant information about the system conditions and environ- ments, a holistic view of a specific application system, hardware fault models, and a library of software component risk profiles. We describe the framework architecture that integrates these in- formation-based modules with inference and task modules to support automated reasoning for risk assessment and analysis. The paper discusses our ongoing preliminary research including the detailed architecture of the proposed framework, its compo- nents and utilization, and future directions of this work.
Bioinformatics Applications Note Phylocom: Software for the Analysis of Phylogenetic Community Structure and Trait Evolution

Motivation: The increasing availability of phylogenetic and trait data for communities of co-occurring species has created a need for software that integrates ecological and evolutionary analyses. Capabilities: Phylocom calculates numerous metrics of phyloge-netic community structure and trait similarity within communities. Hypothesis testing is implemented using several null models. Within the same framework, it measures phylogenetic signal and correlated evolution for species traits. A range of utility functions allow community and phylogenetic data manipulation, tree and trait generation, and integration into scientific workflows.
Neurite Outgrowth on Electrospun Nanofibers with Uniaxial Alignment: The Effects of Fiber Density, Surface Coating, and Supporting Substrate

Electrospun nanofibers with uniaxial alignment have recently gained its popularity as scaffolds for neural tissue engineering. Many studies have demonstrated that the nanofibers could guide the neurites to extend along the direction of alignment, resembling the native hierarchy of the nerve tissue. However, the contact cues provided by the nanofibers can be far more complicated than just guiding the neurites to extend along them. In the current study, we used dorsal root ganglia as a model system to systematically investigate the interactions between neurites and uniaxially aligned nanofibers. We demonstrated, for the first time, that the neurites could not only project along the nanofibers, but also be directed to grow along a direction perpendicular to the aligned nanofibers, depending on the following parameters: (i) the density of nanofibers, (ii) the protein deposited on the surfaces of the nanofibers, and (iii) surface properties of the substrate on which the nanofibers were supported. We also investigated the pharmacological effect of myosin II inhibition on the nanofiber-guided growth of neurites by adding blebbistatin to the culture medium. Our findings offer new insights into the design of nanofiber-based scaffolds for nerve injury repair and will provide new guidelines for the construction of well-defined neuronal network architecture (the so-called neural circuits).
The Application of Multi-sensor Information Fusion by Improved Trust Degree on SLAM

This paper presents a novel multi-sensor information fusion method by improved trust degree for Simultaneous Localization and Mapping (SLAM) on segment-Based maps. The nearest neighbor method is utilized to detect homologous features, and a fuzzy-index belief function is defined to obtain correlation of features detected by various sensors. Then, an objective weight of sensor data Based on trust degree is designed. The paper combines an objective weight with an expert weight to be a fusion weight for acquiring accurate environment features. Finally, Extended Kalman Filter (EKF) is adopted to update robot pose and map. The experimental results show that the algorithm can highly improve the precision of the robot pose and the map.
A mechanism for DNA-PK activation requiring unique contributions from each strand of a DNA terminus and implications for microhomology-mediated nonhomologous DNA end joining

DNA-dependent protein kinase (DNA-PK) is an essential component of the nonhomologous end joining pathway (NHEJ), responsible for the repair of DNA double-strand breaks. Ku binds a DSB and recruits the catalytic subunit, DNA-PKcs, where it is activated once the kinase is bound to the DSB. The precise mechanism by which DNA activates DNA-PK remains unknown. We have investigated the effect of DNA structure on DNA-PK activation and results demonstrate that in Ku-dependent DNA-PKcs reactions, DNA-PK activation with DNA effectors containing two unannealed ends was identical to activation observed with fully duplex DNA effectors of the same length. The presence of a 6-base single-stranded extension resulted in decreased activation compared to the fully duplex DNA. DNA-PK activation using DNA effectors with compatible termini displayed increased activity compared to effectors with noncompatible termini. A strand orientation preference was observed in these reactions and suggests a model where the 3′ strand of the terminus is responsible for annealing and the 5′ strand is involved in activation of DNA-PK. These results demonstrate the influence of DNA structure and orientation on DNA-PK activation and provide a molecular mechanism of activation resulting from compatible termini, an essential step in microhomology-mediated NHEJ.
Yes, one can obtain better quality structures from routine X-ray data collection

Single-crystal X-ray diffraction data should be collected to the highest resolution as this allows for refinement of more reliable structural, thermal and dependent parameters. The results of refinements using a Transferable Aspherical Atomic Model of electron density (TAAM) appear to be in far better agreement with neutron results than the corresponding Independent Atom Model (IAM) results for all parameters, all resolutions and all compounds, and we advocate the use of this approach instead of IAM.