Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracing Error Propagation in C/C++ Applications

Software error propagation behaviors often cause system failure by propagating a local error to other components till system failure. Error propagation path consists of faulty modules that fault spread via. Study on error propagation path can assist in fault localization, evaluating the validity of fault injection, and understanding mechanism of error propagation. This paper proposes an approach for tracing error propagation in C/C++ applications working on the Linux platform. A framework on how to trace error propagation in applications is proposed as a guideline. This paper proposes a software execution path modeling method, which can be used to extract error propagation in our approach. Then, an automatic instrumentation and data collection technique is proposed to obtain execution path model parameters. Finally, a method on how to extract error propagation path from execution path model is proposed. A case study with grep shows the feasibility of this approach.
Automatic checkerboard detection for camera calibration using self-correlation

Abstract. The checkerboard is a frequently used pattern in camera calibration, an essential process to get intrinsic parameters for more accurate information from images. An automatic checkerboard detection method that can detect multiple checkerboards in a single image is proposed. It contains a corner extraction approach using self-correlation and a structure recovery solution using constraints related to adjacent corners and checkerboard block edges. The method utilizes the central symmetric feature of the checkerboard crossings as well as the spatial relationship of neighboring checkerboard corners and the grayscale distribution of their neighboring pixels. Five public datasets are used in the experiments to evaluate the method. Results show high detection rates and a short average runtime of the proposed method. In addition, the camera calibration accuracy also presents the effectiveness of the proposed detection method with reprojected pixel errors smaller than 0.5 pixels.
Effect of Different Head-Neck Postures on the Respiratory Function in Healthy Males

Normal respiration is a very intricate function that comprises mechanical as well as nonmechanical components. It is shown to be affected by various factors including age, lifestyle, disease, and change in posture. With the increased use of hand held devices, everyone is prone to poor sitting postures like forward head posture. The purpose of this study was to evaluate the effect of assumed forward head posture and torticollis on the diaphragm muscle strength. A sample of 15 healthy males, aged 18-35 years, was recruited for this study. All subjects performed spirometry to measure the forced expiratory volume in 1 second (FEV1), the forced vital capacity (FVC), and FEV1/FVC ratio. SNIP was measured during upright sitting, induced forward head posture, and torticollis. Subject's mean age (SD) was 23(6) years. The SNIP score of the subjects during sitting with FHP was lower as compared to that during upright sitting. It decreased significantly during induced right torticollis position. This is the first study exploring the impact of different head and neck positions on respiratory function. Alteration of head and neck positions had an immediate negative impact on respiratory function. Clinicians should be prompted to assess respiratory function when assessing individuals with mal-posture.
A Probability Distribution Based Cooperative Search Approach for Stochastic Source Localization

This paper copes with the problem of signal source seeking by proposing a cooperative search approach based on the probability distribution of the source position. For this method, each robot is regarded as a particle and the sensor installed on the robot can measure the strength of the signal filed. Moreover, each robot can generate a probability map of the source position by the proposed approach. Depending on the fusion of multiple probability maps, the multi-robot system can move toward the position. In addition, on the way to the source, the probability map can be updated in terms of new measurements. Finally, simulation results illustrate the performance capabilities of the proposed cooperative search approach.
Contextual Prediction of Communication Flow in Social Networks

The paper develops a novel computational framework for predicting communication flow in social networks based on several contextual features. The problem is important because prediction of communication flow can impact timely sharing of specific information across a wide array of communities. We determine the intent to communicate and communication delay between users based on several contextual features in a social network corresponding to (a) neighborhood context, (b) topic context and (c) recipient context. The intent to communicate and communication delay are modeled as regression problems which are efficiently estimated using Support Vector Regression. We predict the intent and the delay, on an interval of time using past communication data. We have excellent prediction results on a real-world dataset from MySpace.com with an accuracy of 13-16%. We show that the intent to communicate is more significantly influenced by contextual factors compared to the delay.
Exploring the Application of Artificial Neural Network in Rural Streamflow Prediction - A Feasibility Study

Streams and rivers play a critical role in the hydrologic cycle with their management being essential to maintaining a balance across social, economic and environmental outcomes. Accurate streamflow predictions can provide benefits in many different ways such as water allocation decision making, flood forecasting and environmental watering regimes. This is particularly important in regional areas of Australia where rivers can play a critical role in irrigated agriculture, recreation and social wellbeing, major floods and sustainable environments. There are several hydrological parameters that effect stream flows in rivers and a major challenge with any prediction methodology, is to understand these parameter interdependencies, correlations and their individual effects. A robust methodology is, thus, required for accurate prediction of streamflow under usually unique, waterway-specific conditions using available data. This research employs an approach based on Artificial Neural Network (ANN) to provide this robust methodology. Data from readily available sources has been selected to provide appropriate input and output parameters to train, validate and optimise the neural network. The optimisation steps of the methodology are discussed and the predicted outputs are compared and analysed with respect to the actual collected values.
Crystal Structure of a ligand-bound LacY–Nanobody Complex

Significance The lactose permease of Escherichia coli (LacY), a model Major Facilitator Superfamily transporter, catalyzes galactoside/H+ symport by an alternating access mechanism that involves multiple conformational transitions. Nanobodies (Nbs) generated against a double mutant (LacYWW) that exists in an outward-open conformation stabilize the periplasmic-open conformer of wild-type LacY, block lactose transport, and lead to a 5–50-fold increase in the on-rate for galactoside binding to WT LacY. The galactoside-binding site in galactoside/LacYww/Nb9047 is superimposable with other sugar-bound LacYww structures and therefore is not perturbed due to crystal contacts or nanobody; thus, comparison with apo-LacYwwNb demonstrates that it most likely represents a transport intermediate primarily seen on the periplasmic side in response to the initial galactoside-binding. The lactose permease of Escherichia coli (LacY), a dynamic polytopic membrane transport protein, catalyzes galactoside/H+ symport and operates by an alternating access mechanism that exhibits multiple conformations, the distribution of which is altered by sugar-binding. Camelid nanobodies were made against a double-mutant Gly46 → Trp/Gly262 → Trp (LacYWW) that produces an outward-open conformation, as opposed to the cytoplasmic open-state crystal structure of WT LacY. Nanobody 9047 (Nb9047) stabilizes WT LacY in a periplasmic-open conformation. Here, we describe the X-ray crystal structure of a complex between LacYWW, the high-affinity substrate analog 4-nitrophenyl-α-d-galactoside (NPG), and Nb9047 at 3-Å resolution. The present crystal structure demonstrates that Nb9047 binds to the periplasmic face of LacY, primarily to the C-terminal six-helical bundle, while a flexible loop of the Nb forms a bridge between the N- and C-terminal halves of LacY across the periplasmic vestibule. The bound Nb partially covers the vestibule, yet does not affect the on-rates or off-rates for the substrate binding to LacYWW, which implicates dynamic flexibility of the Nb–LacYWW complex. Nb9047-binding neither changes the overall structure of LacYWW with bound NPG, nor the positions of side chains comprising the galactoside-binding site. The current NPG-bound structure exhibits a more occluded periplasmic vestibule than seen in a previous structure of a (different Nb) apo-LacYWW/Nb9039 complex that we argue is caused by sugar-binding, with major differences located at the periplasmic ends of transmembrane helices in the N-terminal half of LacY.
Dose-Dependent Antifibrotic Effect of Chrysin on Regression of Liver Fibrosis: The Role in Extracellular Matrix Remodeling

Liver fibrosis represents an overaccumulation of extracellular matrix (ECM). This study was designed to investigate the effect of chrysin on established ECM overproduction in carbon tetrachloride (CCl4) mouse liver fibrosis. Experimental fibrosis was induced by intraperitoneal injection of 2 mL/kg CCl4 twice a week, for 7 weeks. Mice were orally treated with 3 doses of chrysin (5,7-dihydroxyflavone). For the assessment of the spontaneous reversion of fibrosis, CCl4-treated mice were investigated after 2 weeks of recovery time. Silymarin was used as a standard of liver protection. In fibrotic livers, the results showed the upregulation of collagen I (Col I) and tissue inhibitors of metalloproteinase 1 (TIMP-1) and modulation of matrix metalloproteinases (MMPs), which led to an altered ECM enriched in Col, confirmed as well by electron microscopy investigations. Treatment with chrysin significantly reduced ultrastructural changes, downregulated Col I, and restored TIMP-1/MMP balance, whereas in the group observed for the spontaneous regression of fibrosis, they remained in the same pattern with fibrotic livers. In this study, we have shown chrysin efficacy to attenuate dose-dependent CCl4-stimulated liver ECM accumulation by regulation of MMP/TIMP imbalance and inhibition of Col production. We have shown the dose-dependent chrysin efficiency in attenuation of CCl4-induced liver ECM accumulation by regulation of MMP/TIMP imbalance and inhibition of Col production. Our findings suggest that chrysin oral administration may introduce a new strategy for treating liver fibrosis in humans.
Multilevel optimal λ decision for low-delay rate control in high-efficiency video coding

Abstract. By considering the rate distortion optimization (RDO) characteristics, a multilevel optimal λ decision algorithm for the rate control is proposed. With the process of getting the optimal λ for the group of picture (GoP)-level rate control, the frame-level rate control, and the coding tree unit (CTU)-level rate control, a special relationship of the current level λ and the next level λ can be built. First, an approximate linear bit allocation relationship is used between the bit rate and the motion compensation prediction error to assign the bit rate more reasonably for every frame. Second, the multilevel optimal λ decision scheme is proposed. To minimize the whole distortion of a sequence, an effective way is to get the optimal RDO of every GoP. Then, with the RDO process of the GoP-level rate control, an optimal frame λ ratio for each frame in current GoP can be obtained. For the optimal frame λ ratio, its value is mainly decided by the distortion effect, which is calculated by an employed source distortion propagation chain. Finally, an optimal CTU λ clip scheme is proposed to get the optimal RDO of every CTU. The experimental results show that the coding quality of the proposed rate control algorithm is improved significantly with little loss of the bit rate accuracy.
Indications for root canal treatment in a Swedish county dental service: patient‐ and tooth‐specific characteristics

AIM To study patient- and tooth-specific characteristics of teeth indicated for root canal treatment, in the public dental service of the county of Västra Götaland, Sweden. METHODOLOGY During a designated 8-week period, general dental practitioners working at 20 different public dental clinics consecutively registered indications for undertaking root canal treatment. The patients' subjective level of pain was also registered (visual analogue scale) at the very first appointment. The following information was retrieved from computerized dental records and radiographs: gender, age, number of remaining teeth, tooth group, previous restoration, number of restored surfaces, dental caries and tooth substance loss. Gender and age were compared using both descriptive and analytical statistics. RESULTS The material comprised 243 teeth in 243 patients: 128 (52.7%) women and 115 (47.3%) men, mean age 48.3 years. Molar teeth predominated (47.7%). Most of the teeth (83.5%) had previously been restored and exhibited significant loss of tooth substance, more than a third of the crown (71.3%). Dental caries was present in 127 teeth (62.9%). Dental trauma was implicated in only seven cases (2.9%). Initial treatment was frequently undertaken at an emergency visit, for relief of symptoms (64.9%). The most commonly registered indication was pulpal necrosis with apical periodontitis (38.1%), followed by pulpitis (37.7%). Retreatment of a root filled tooth was reported in 18 teeth (7.4%). CONCLUSIONS In the general Public Dental Service of Sweden, root canal treatment is most frequently undertaken in molars. The primary indication is relief of symptoms. Retreatment of root filled teeth is uncommon.
Updates in Rhea – an expert curated resource of biochemical reactions

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset.
SPARTA: Security & Privacy Architecture Through Risk-Driven Threat Assessment

The development of secure and privacy-preserving software systems entails the continuous consideration of the security and privacy aspects of the system under development. While contemporary software development practices do support such a continuous approach towards software development, existing threat modeling activities are commonly executed as single-shot efforts leading to a single, historic, and quickly obsolete view on the security and privacy of the system. This disconnect leads to undetected new issues and wasted efforts on already resolved problems, effectively accruing technical debt. The presented SPARTA prototype facilitates the consideration of security and privacy by providing support for: (i) capturing security and privacy design decisions in a DFD-based architectural abstraction, (ii) continuous threat elicitation on this knowledge-enriched abstraction, and (iii) risk analysis of the elicited threats for prioritizing security and privacy efforts. By capturing and continuously assessing the impact of security and privacy design decisions on the elicited threats, the progress towards securing the system can be assessed and alternatives can be compared, taking into account past and present design decisions.
Structural basis for Scc3-dependent cohesin recruitment to chromatin

The cohesin ring complex is required for numerous chromosomal transactions including sister chromatid cohesion, DNA damage repair and transcriptional regulation. How cohesin engages its chromatin substrate has remained an unresolved question. We show here, by determining a crystal structure of the budding yeast cohesin HEAT-repeat subunit Scc3 bound to a fragment of the Scc1 kleisin subunit and DNA, that Scc3 and Scc1 form a composite DNA interaction module. The Scc3-Scc1 subcomplex engages double-stranded DNA through a conserved, positively charged surface. We demonstrate that this conserved domain is required for DNA binding by Scc3-Scc1 in vitro, as well as for the enrichment of cohesin on chromosomes and for cell viability. These findings suggest that the Scc3-Scc1 DNA-binding interface plays a central role in the recruitment of cohesin complexes to chromosomes and therefore for cohesin to faithfully execute its functions during cell division.
A Cross-Tier Scheduling Scheme for Multi-Tier Millimeter Wave Wireless Networks

Due to abundant frequency resources, millimeter wave (mm-wave) spectrum has drawn much attention as a solution to bandwidth scarcity. However, many characteristics of mm-wave transmissions, such as blockage and reduced coverage, make conventional network architectures very inefficient for use in mm-wave networks. A recently proposed multi-tier mm-wave network architecture allows for relaying around blockages and enlarges the coverage of each base station at an acceptable deployment cost. Nevertheless, this architecture introduces major challenges to the scheduling of each tier. The necessity of both enabling flexible user association and fully exploiting the wireless backhaul requires a cross-tier consideration of the multi-tier mm-wave network. We comprehensively analyze the scheduling problem of a downlink multi-tier mm-wave network by jointly regulating the transmissions in all tiers. The cross-tier optimization problem is NP-hard, but a sub-optimal scheme which iteratively optimizes the schedule in different tiers of the network is proposed with polynomial computational complexity. Simulation results show that our algorithm significantly outperforms the benchmarks in both spectral efficiency and fairness with various user distributions.
Functional Dependency Detection for Integration Test Cases

This paper presents a natural language processing (NLP) based approach that, given software requirements specification, allows the functional dependency detection between integration test cases. We analyze a set of internal signals to the implemented modules for detecting dependencies between requirements and thereby identifying dependencies between test cases such that: module 2 depends on module 1 if an output internal signal from module 1 enters as an input internal signal to the module 2. Consequently, all requirements (and thereby test cases) for module 2 are dependent on all the designed requirements (and test cases) for module 1. The dependency information between requirements (and thus corresponding test cases) can be utilized for test case prioritization and scheduling. We have implemented our approach as a tool and the feasibility is evaluated through an industrial use case in the railway domain at Bombardier Transportation (BT), Sweden.
Interneuron Simplification and Loss of Structural Plasticity As Markers of Aging-Related Functional Decline

Changes in excitatory neuron and synapse structure have been recognized as a potential physical source of age-related cognitive decline. Despite the importance of inhibition to brain plasticity, little is known regarding aging-associated changes to inhibitory neurons. Here we test for age-related cellular and circuit changes to inhibitory neurons of mouse visual cortex. We find no substantial difference in inhibitory neuron number, inhibitory neuronal subtypes, or synapse numbers within the cerebral cortex of aged mice compared with younger adults. However, when comparing cortical interneuron morphological parameters, we find differences in complexity, suggesting that arbors are simplified in aged mice. In vivo two-photon microscopy has previously shown that in contrast to pyramidal neurons, inhibitory interneurons retain a capacity for dendritic remodeling in the adult. We find that this capacity diminishes with age and is accompanied by a shift in dynamics from balanced branch additions and retractions to progressive prevalence of retractions, culminating in a dendritic arbor that is both simpler and more stable. Recording of visually evoked potentials shows that aging-related interneuron dendritic arbor simplification and reduced dynamics go hand in hand with loss of induced stimulus-selective response potentiation (SRP), a paradigm for adult visual cortical plasticity. Chronic treatment with the antidepressant fluoxetine reversed deficits in interneuron structural dynamics and restored SRP in aged animals. Our results support a structural basis for age-related impairments in sensory perception, and suggest that declines in inhibitory neuron structural plasticity during aging contribute to reduced functional plasticity. SIGNIFICANCE STATEMENT Structural alterations in neuronal morphology and synaptic connections have been proposed as a potential physical basis for age–related decline in cognitive function. Little is known regarding aging-associated changes to inhibitory neurons, despite the importance of inhibitory circuitry to adult cortical plasticity and the reorganization of cortical maps. Here we show that brain aging goes hand in hand with progressive structural simplification and reduced plasticity of inhibitory neurons, and a parallel decline in sensory map plasticity. Fluoxetine treatment can attenuate the concurrent age–related declines in interneuron structural and functional plasticity, suggesting it could provide an important therapeutic approach for mitigating sensory and cognitive deficits associated with aging.
MIMO Beamforming Design in Nonorthogonal Multiple Access Downlink Interference Channels

Nonorthogonal multiple access (NOMA) has been considered as a promising technology for fifth-generation wireless communication systems. In this paper, we consider a two-cell multiple-input-multiple-output NOMA downlink interference channel with one multiantenna base station (BS) and multiple multiantenna users in each cell. Each user treats interferences from adjacent cell as additional noises and does not attempt to decode them. This paper aims to design interference channel beamformers to maximize weighted sum capacity of the strongest users in two cells under quality of service requirements at other users and transmit power budget constraint at each BS. Such problem is complicated and nonconvex due to the expression of a logarithm of a determinant $(\log \det)$ minus $\log \det$ in the objective function and constraints. For the nonconvex problem, we put forward a successive convex approximation (SCA) based iterative algorithm. Since the computational complexity of SCA-based iterative algorithm is high, we also put forward an efficient majorization-minimization based iterative algorithm. Based on simulation results, we show that our developed NOMA schemes are superior to the zero-forcing-based NOMA, orthogonal-NOMA, and orthogonal multiple access schemes.