Miracle-dz/UniFAR-FTUs huggingface dataset:
Guided search for task and motion plans using learned heuristics

Tasks in mobile manipulation planning often require thousands of individual motions to complete. Such tasks require reasoning about complex goals as well as the feasibility of movements in configuration space. In discrete representations, planning complexity is exponential in the length of the plan. In mobile manipulation, parameters for an action often draw from a continuous space, so we must also cope with an infinite branching factor. Task and motion planning (TAMP) methods integrate logical search over high-level actions with geometric reasoning to address this challenge. We present an algorithm that searches the space of possible task and motion plans and uses statistical machine learning to guide the search process. Our contributions are as follows: 1) we present a complete algorithm for TAMP; 2) we present a randomized local search algorithm for plan refinement that is easily formulated as a Markov decision process (MDP); 3) we apply reinforcement learning (RL) to learn a policy for this MDP; 4) we learn from expert demonstrations to efficiently search the space of high-level task plans, given options that address different (potential) infeasibilities; and 5) we run experiments to evaluate our system in a variety of simulated domains. We show significant improvements in performance over prior work.
Analyzing and Improving Performance of a Class of Anomaly-based Intrusion Detectors

Anomaly-based intrusion detection (AID) techniques are useful for detecting novel intrusions into computing resources. One of the most successful AID detectors proposed to date is stide, which is based on analysis of system call sequences. In this paper, we present a detailed formal framework to analyze, understand and improve the performance of stide and similar AID techniques. Several important properties of stide-like detectors are established through formal proofs, and validated by carefully conducted experiments using test datasets. Finally, the framework is utilized to design two applications to improve the cost and performance of stide-like detectors which are based on sequence analysis. The first application reduces the cost of developing AID detectors by identifying the critical sections in the training dataset, and the second application identifies the intrusion context in the intrusive dataset, that helps to fine-tune the detectors. Such fine-tuning in turn helps to improve detection rate and reduce false alarm rate, thereby increasing the effectiveness and efficiency of the intrusion detectors.
Microbes, immunoregulation, and the gut

Two distinct, but rapidly converging, areas of research (the hygiene hypothesis and the study of probiotic/prebiotic effects) have emphasised the need to understand, and ultimately to manipulate, our physiological interactions with commensal flora, and with other transient but harmless organisms from the environment that affect immunoregulatory circuits. The story began with allergic disorders but now inflammatory bowel disease is increasingly involved.
A Coherent Statistical Model for Coastal Flood Frequency Analysis Under Nonstationary Sea Level Conditions

Flood exposure is increasing in coastal communities due to rising sea levels. Understanding the effects of sea level rise (SLR) on frequency and consequences of coastal flooding and subsequent social and economic impacts is of utmost importance for policymakers to implement effective adaptation strategies. Effective strategies may consider impacts from cumulative losses from minor flooding as well as acute losses from major events. In the present study, a statistically coherent Mixture Normal‐Generalized Pareto Distribution model was developed, which reconciles the probabilistic characteristics of the upper tail as well as the bulk of the sea level data. The nonstationary sea level condition was incorporated in the mixture model using Quantile Regression method to characterize variable Generalized Pareto Distribution thresholds as a function of SLR. The performance validity of the mixture model was corroborated for 68 tidal stations along the Contiguous United States (CONUS) coast with long‐term observed data. The method was subsequently employed to assess existing and future coastal minor and major flood frequencies. The results indicate that the frequency of minor and major flooding will increase along all CONUS coastal regions in response to SLR. By the end of the century, under the “Intermediate” SLR scenario, major flooding is anticipated to occur with return period less than a year throughout the coastal CONUS. However, these changes vary geographically and temporally. The mixture model was reconciled with the property exposure curve to characterize how SLR might influence Average Annual Exposure to coastal flooding in 20 major CONUS coastal cities.
A Dynamic Programming Approach for Privacy Preserving Collaborative Data Publishing

Organizations share their data about customers for exploring potential business avenues. The sharing of data has posed several threats leading to individual identification. Owing to this, privacy preserving data publication has become an important research problem. The main goals of this problem are to preserve privacy of individuals while revealing useful information. An organization may implement and follow its privacy policy. But when two companies share information about a common set of individuals, and if their privacy policies differ, it is likely that there is privacy breach unless there is a common policy. One such solution was proposed for such a scenario, based on k-anonymity and cut-tree method for 2-party data. This paper suggests a simple solution for integrating nparty data using dynamic programming on subsets. The solution is based on thresholds for privacy and informativeness based on k-anonymity. General Terms Security, Human Factors
Architecture for an unmanned ground vehicle

This paper describes architecture for an autonomous land vehicle for high-speed driving without human intervention. This is a model proposed for the DARPA Grand Challenge in 2004, which was to make a robotic vehicle that will drive a desert terrain of 132 miles autonomously. In comparison to other challenges in the robotics domain, this challenge was really different because it encompassed making a robust vehicle that could survive in the desert for long hours and travel the pre-designated path without going into obstacles. Research in this area brings out many new ideas and new concepts in the fields of Robotics and AI. There are also direct advantages of research here: There are a hug number of road accidents. Making driving a car autonomous can make travelling much safer, since, an autonomous machine is making all the decisions instead of a human. We can think of a future, when nearby overtaking or crossing vehicles will communicate with each other, coordinate, and then decide to overtake or cross. This will make driving more reliable. Autonomous vehicles can also be used in harsh warlike situation for transporting infantry and arms. The wide range of applications, the difficulty of the problem and the technology's usefulness makes this an interesting topic.
Psychological adaptation and adjustment of mothers of children with congenital heart disease: stress, coping, and family functioning.

OBJECTIVE Investigate support for the transactional stress and coping model for mothers of children with congenital heart defects, in accounting for the variance in maternal adjustment. METHODS Participants were 52 mothers of children recruited from a university medical center. Measures included illness variables, cognitive processes (i.e., appraisals of stress, expectations, methods of coping, family functioning, and maternal psychological adjustment). RESULTS Maternal adjustment was associated with high levels of daily stress and palliative coping techniques and was not significantly associated with severity of the cardiac defect. Together, the variables of the model accounted for approximately 38% of the variance in maternal adjustment. CONCLUSIONS The findings are in accord with previous research among other chronically ill populations in suggesting an association between stress, coping, and maternal adjustment. Within the limitations of the study, the data were interpreted to support the utility of theoretical models in identifying areas in need of intervention across chronic illness groups.
Key Technology for Constructing Mobile System of Water Purification System in Eutrophic Lakes and Reservoirs

The present paper proposes the treatment technology of mobile water purification system for in-situ treatment in lake and reservoir eutrophication water. This system was composed of water purification unit, mainly including adsorptions unit, microporous aeration unit, micro-current electrolysis unit, instruction control unit, water quality on-line detection unit and power supply unit. The goal of excessive nutrient reduction and harmful algal blooms control could be achieved by nitrogen and phosphorus removal by adsorptions unit and microporous aeration unit, and algal inhibition by micro-current electrolysis unit. The optimal dosage of adsorption material, in-situ adsorption time, aeration intensity, current density, electrolytic time and other technical parameters were achieved by the experiment of adsorption, microporous aeration and micro-current electrolysis using high-performance adsorbents, optimal aeration way and electrode material. Finally, the present study prospects the way to improve the water purification performance and enhance the operation management of mobile water purification system was discussed according to the experimental results and subsequent practical application. Overall, the technology of mobile water purification system is a new and effective technology for eutrophication treatment and will provide solutions for prevention and control of nutrient overloading and algae blooms.
Perceived health status and environmental quality in the assessment of external costs of waste disposal facilities. An empirical investigation

Taxation for urban waste management has been reformed in Italy by the introduction of an environmental law in 2006. In the planning phase of waste management, externalities generated by new facilities remain widely unaccounted, with a consequent distortion for prices, often raising local conflicts. The paper presents a survey based on the choice modelling methodology, aimed to evaluate on a monetary scale the disamenity effect perceived by incinerator and landfills in an Italian urban context: the city of Turin. In a random utility framework the behaviour of respondents, whose choices are found to be driven by the endowment of information about technological options, socio-economic characteristics as income, education, family composition, and also by their health status was modelled. Furthermore, empirical evidence that the behaviour in residential location choices is affected by different aspects of the respondent life and in particular by the health status was found. Distinct estimates of willingness to accept compensation for disamenity effects of incinerator (€2670) and landfill (€3816) are elicited. The effect of health status of the respondents, their level of information about the waste disposal infrastructure, the presence of a subjective strong aversion (NIMBY) and the actual endowment and concentration of infrastructures are demonstrated to be significant factors determining the choice behaviour, but differentiated and specific for incinerators and landfills.
Noun sense induction using web search results

This paper presents an algorithm for unsupervised noun sense induction, based on clustering of Web search results. The algorithm does not utilize labeled training instances or any other external knowledge source. Preliminary results on a small dataset show that this technique provides two advantages over other techniques in the literature: it detects real-world senses not found in dictionaries or other lexical resources, and it does not require that the number of word senses be specified in advance.
Low-power operation of a barometric pressure sensor for use in an automatic fall detector

The use of a barometric pressure sensor in a wearable fall detector has been shown to improve the detection accuracy by determining the altitude change associated with the fall event. However, the barometer is a high-power-consuming sensor. This paper proposes a fall detection approach using a hermetically sealed and waterproof enclosure incorporating a small window covered by a semi-permeable membrane (SPM) to delay the equilibrium of internal and external pressures. This feature can be utilized to limit the time the barometer is powered but still capturing critical pressure information to discriminate fall and non-fall events. The proposed fall detection system is evaluated with an existing data set of simulated fall and activities of daily living in which the barometric pressure data are delayed using a mathematical model of the enclosure and SPM assembly. Also, a benchtop test is performed to estimate the power and battery life. The proposed fall detection system achieves 94.0% sensitivity and 90.0% specificity with an estimated battery life of 995.7 days.
Post-traumatic arthritis: overview on pathogenic mechanisms and role of inflammation

Post-traumatic arthritis (PTA) develops after an acute direct trauma to the joints. PTA causes about 12% of all osteoarthritis cases, and a history of physical trauma may also be found in patients with chronic inflammatory arthritis. Symptoms include swelling, synovial effusion, pain and sometimes intra-articular bleeding. Usually, PTA recoveries spontaneously, but the persistence of symptoms after 6 months may be considered pathological and so-called chronic PTA. A variety of molecular, mechanobiological and cellular events involved in the pathogenesis and the progression of PTA have been identified. The activation of inflammatory mechanisms during the PTA acute phase appears to play a critical role in the chronic disease onset. Human studies and experimental models have revealed that a series of inflammatory mediators are released in synovial fluid immediately after the joint trauma. These molecules have been proposed as markers of disease and as a potential target for the development of specific and preventative interventions. Currently, chronic PTA cannot be prevented, although a large number of agents have been tested in preclinical studies. Given the relevance of inflammatory reaction, anticytokines therapy, in particular the inhibition of interleukin 1 (IL-1), seems to be the most promising strategy. At the present time, intra-articular injection of IL-1 receptor antagonist is the only anticytokine approach that has been used in a human study of PTA. Despite the fact that knowledge in this area has increased in the past years, the identification of more specific disease markers and new therapeutic opportunities are needed.
A New Method for Accurate Extraction of Source Resistance and Effective Mobility in Nanoscale Multifinger nMOSFETs

A new method is is developed for accurate extraction of the effective mobility (μ<sub>eff</sub>) in the multifinger nMOSFETs with various poly-to-poly (PO-PO) spaces. The wide PO-PO space intends to increase the tensile stress from a contact etching stop layer (CESL) and yields higher μ<sub>eff</sub> in the nMOSFETs. However, the source resistance (R<sub>S</sub>) emerges as a critical parasitic element in the multifinger devices with a large finger number. The wide PO-PO space generally leads to the further increase of R<sub>S</sub>, which may offset μ<sub>eff</sub> improvement and degrade transconductance (g<sub>m</sub>). A two-end source line is proposed to reduce RS and the impact on g<sub>m</sub>. The complicated layout-dependent effects containing the CESL strain, R<sub>S</sub>, and 3-D fringing capacitances bring a crucial challenge to the μ<sub>eff</sub> extraction. In this paper, a distributed transmission line model is derived for a reliable determination of R<sub>S</sub>, which is a key to the realization of accurate extraction of μ<sub>eff</sub> and layout-dependent effects in multifinger devices.
MOLECULAR EVENT EXTRACTION FROM LINK GRAMMAR PARSE TREES IN THE BIONLP’09 SHARED TASK

The BioNLP’09 Shared Task deals with extracting information on molecular events, such as gene expression and protein localization, from natural language text. Information in this benchmark are given as tuples including protein names, trigger terms for each event, and possible other participants such as bindings sites. We address all three tasks of BioNLP’09: event detection, event enrichment, and recognition of negation and speculation. Our method for the first two tasks is based on a deep parser; we store the parse tree of each sentence in a relational database scheme. From the training data, we collect the dependencies connecting any two relevant terms of a known tuple, that is, the shortest paths linking these two constituents. We encode all such linkages in a query language to retrieve similar linkages from unseen text. For the third task, we rely on a hierarchy of hand‐crafted regular expressions to recognize speculation and negated events. In this paper, we added extensions regarding a post‐processing step that handles ambiguous event trigger terms, as well as an extension of the query language to relax linkage constraints. On the BioNLP Shared Task test data, we achieve an overall F1‐measure of 32%, 29%, and 30% for the successive Tasks 1, 2, and 3, respectively.
Transmit beamformer and quantization design for multi-carrier CRAN CoMP

We consider the problem of designing transmit beamformers for a multi-carrier joint processing coordinated multi-point (CoMP) transmission with finite backhaul capacity. We assume a Cloud Radio access network (CRAN) wherein the beamformers are designed centrally, quantized and sent via the backhaul to the respective base stations (BSs). The beamformer design becomes a nonconvex combinatorial problem with the user selection, which is also modeled as a part of our problem. In order to avoid the combinatorial search, we relax the binary association variable by a linear one and the nonconvex sets by a sequence of convex subsets by the successive convex approximation (SCA) method. Thereby, we design the beamformers by iteratively solving a convex subproblem in each SCA iteration. Additionally, to enforce sparsity in the relaxed binary variable, we regularize the objective with the associated entropy measure to enforce a binary solution. Since the beamformers are notified via backhaul to the respective BSs, we include the beamformer overhead also in the backhaul usage in addition to data sharing. Numerical results are provided to illustrate the performance of the proposed designs.
Multisensor-Based Human Detection and Tracking for Mobile Service Robots

One of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In this paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based leg detection using the onboard laser range finder (LRF). The approach is based on the recognition of typical leg patterns extracted from laser scans, which are shown to also be very discriminative in cluttered environments. These patterns can be used to localize both static and walking persons, even when the robot moves. Furthermore, faces are detected using the robot's camera, and the information is fused to the legs' position using a sequential implementation of unscented Kalman filter. The proposed solution is feasible for service robots with a similar device configuration and has been successfully implemented on two different mobile platforms. Several experiments illustrate the effectiveness of our approach, showing that robust human tracking can be performed within complex indoor environments.
Superoxide differentially controls pulmonary and systemic vascular tone through multiple signalling pathways

Aims The aim of this study was to determine the relative importance of Ca2+ sensitization, ion channels, and intracellular Ca2+ ([Ca2+]i) in the mixed constrictor/relaxation actions of superoxide anion on systemic and pulmonary arteries. Methods and results Pulmonary and mesenteric arteries were obtained from rat. Superoxide was generated in arteries and cells with 6-anilino-5,8-quinolinequinone (LY83583). Following pre-constriction with U46619, 10 μmol/L LY83583 caused constriction in pulmonary and relaxation in mesenteric arteries. Both constrictor and relaxant actions of LY83583 were inhibited by superoxide dismutase and catalase. LY83583 caused Rho-kinase-dependent constriction in α-toxin-permeabilized pulmonary but not mesenteric arteries. Phosphorylation of myosin phosphatase-targeting subunit-1 (MYPT-1; as determined by western blot), was enhanced by LY83583 in pulmonary artery only. However, in both artery types, changes in tension were closely correlated with changes in phosphorylation of the 20 kDa myosin light chain as well as changes in [Ca2+]i (as measured with Fura PE-3), with LY83583 causing increases in pulmonary and decreases in mesenteric arteries. When U46619 was replaced by 30 mmol/L K+, all changes in [Ca2+]i were abolished and LY83583 constricted both artery types. The KV channel inhibitor 4-aminopyridine abolished the LY83583-induced relaxation in mesenteric artery without affecting constriction in pulmonary artery. However, LY83583 caused a similar hyperpolarizing shift in the steady-state activation of KV current in isolated smooth muscle cells of both artery types. Conclusions Superoxide only causes Rho-kinase-dependent Ca2+ sensitization in pulmonary artery, resulting in constriction, and whilst it opens KV channels in both artery types, this only results in relaxation in mesenteric.
Efficacy and safety of HL301 in the treatment of acute bronchitis and acute exacerbation of chronic bronchitis: a phase 2, randomized, double-blind, placebo-controlled, multicenter study

Abstract Purpose: The efficacy and safety of Chinese herbs for symptomatic treatment of bronchitis is not well established. We evaluated the efficacy and safety of a combination product of seven herbs (HL301) for the treatment of acute bronchitis (AB) and acute exacerbation of chronic bronchitis (AECB) using a randomized, double-blind, placebo-controlled, multicenter trial design. Methods: A total of 160 patients with AB or with AECB were randomized to receive placebo or one of three doses of HL301 (0.6 g/day, 1.2 g/day, or 1.8 g/day) for a total of 7 days. The primary study endpoint was the change in bronchitis severity score (BSS) from the baseline visit (visit 2) to the end of treatment visit (visit 3). Other efficacy variables were percentage BSS systemic sign efficacy after treatment and change in individual BSS parameters after treatment. Findings: Changes in BSS from visit 2 to visit 3 in the three treatment groups (4.63 ± 2.24, 4.08 ± 1.63, and 4.15 ± 1.74 in the HL301 0.6 g/day, 1.2 g/day, and 1.8 g/day groups, respectively) were higher than that of the placebo group (2.88 ± 2.57) in the per protocol set (PPS) (P < .05), and it was also valid in the full analysis set (FAS). The number of participants whose symptoms (measured by BSS) improved at least 30% after treatment was higher in all three treatment groups compared to the placebo group in both the FAS and the PPS (P < .05, for all). Implications: Three different doses of HL301 (0.6 g/day, 1.2 g/day, and 1.8 g/day) were effective in decreasing the BSS index compared to placebo. HL301 may be effective for symptomatic treatment of both AB and AECB. Limitations: Essential components of HL301 have not been delineated in the study and patients with AB and AECB were indiscriminately enrolled in the present study. Respective evaluation of the efficacy of HL301 for AB and AECB will be necessary in the future.