Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Language to Generate State Abstractions for Long-Range Planning in Outdoor Environments

Robots that process navigation instructions in large outdoor environments will need to operate at different levels of abstraction. For example, a land-surveying aerial robot receiving the instruction “go to Boston and go through the state forest on the way” must reason about a long-range goal like “go to Boston” while also processing a finer-grained constraint like “go through the state forest. ” Existing approaches struggle to plan such commands because of the immense number of locations and constraints that can be expressed in language. We introduce a hierarchical representation of outdoor environments and a planning approach that dynamically compacts the robot's state space to enable tractable planning in city and state-scale environments. Our approach leverages natural abstractions in real-world map data, coupled with abstractions generated from users' instructions, to generate filtered environment views that accelerate planning while supporting a robot's ability to obey complex temporal goals and constraints at different levels of abstraction. We evaluate our approach on seven templates of LTLJ formulas and in an 80 kilometer-radius environment containing over 250,000 locations downloaded from OpenStreetMap. The results show our approach enables planning in seconds or minutes in a large outdoor environment while still satisfying the task specification.
IDENTIFICATION OF SCRIBES FROM HISTORICAL MANUSCRIPTS

Computerized analysis of historical documents has remained an interesting research area for the pattern classification community for many decades. From the perspective of computerized analysis, key challenges in the historical manuscripts include automatic transcription, dating, retrieval, classification of writing styles and identification of scribes etc. The focus of our current study lies on identification of writers from the digitized historical manuscripts. The documents are first pre-processed to segment handwriting from the background. For feature extraction and subsequent classification, we extract small patches of handwriting. These patches are extracted in two different ways, by a dense sampling of handwriting using small windows as well as by finding the key points in handwriting and using these key points as centers of small windows to extract writing fragments. Features are extracted from writing windows using a two-step fine-tuning of convolutional neural networks. First, the ConvNets are trained on contemporary handwriting samples and then fine-tuned to the limited set of historical manuscripts (Papyrus). Decisions on patches are combined using a majority vote to decide the authorship of a query document. Preliminary experiments on a set of challenging and degraded manuscripts report promising performance.
The Effect of Perceived Risk, Brand Image and Perceived Price Fairness on Customer Satisfaction

Abstrack: This study aims to analyze the effect of perceived risk, brand image and perceived price fairness on customer satisfaction at Japanese restaurants in Jakarta, Indonesia. The target population of this research was all Japanese restaurant customers in Jakarta and its surroundings during the period of October 2021. There was a total of 208 respondents participated in this study. The sampling technique used was snowball sampling. The data was collected using a questionnaire distributed online through Google Form. The data was analyzed using partial least square-structural equation modeling (PLSSEM) approach in WarpPls 7.0 program. The results show that the perceived risk has no negative effect on customer satisfaction. The brand image also has a positive effect on customer satisfaction.The perceived price fairness has a positive effect on customer satisfaction. The more affordable the price of Japanese restaurant food products, the higher the customer satisfaction.
Associations of H2O and CH3OH masers at milli-arcsec angular resolution in two high-mass YSOs

Context. While high-angular resolution observations have clarified that water masers originate from shocks associated with protostellar jets, different environments have been proposed in several sources to explain the origin of CH3OH masers. Aims. We wish to investigate the nature of the CH3OH maser birthplace in SFRs and the association between the H2O and CH3OH maser emission in the same YSO. Methods. We have conducted phase-reference VLBI observations of H2O and CH3OH masers toward two high-mass SFRs, Sh 2-255 IR and AFGL 5142. Results. In Sh 2-255 IR water masers are aligned along a direction close to the orientation of the molecular outflow observed on angular scales of 1–10 arcsec, tracing possibly the disk-wind emerging from the disk atmosphere. In AFGL 5142 water masers trace expansion at the base of a protostellar jet, whilst methanol masers are more probably tracing infalling than outflowing gas. Conclusions. The results for AFGL 5142 suggest that water and methanol masers trace different kinematic structures in the circumstellar gas.
The MUSE Hubble Ultra Deep Field Survey

Context. The Lyα emitter (LAE) fraction, XLAE, is a potentially powerful probe of the evolution of the intergalactic neutral hydrogen gas fraction. However, uncertainties in the measurement of XLAE are still under debate. Aims. Thanks to deep data obtained with the integral field spectrograph Multi Unit Spectroscopic Explorer (MUSE), we can measure the evolution of the LAE fraction homogeneously over a wide redshift range of z ≈ 3–6 for UV-faint galaxies (down to UV magnitudes of M1500 ≈ −17.75). This is a significantly fainter range than in former studies (M1500 ≤ −18.75) and it allows us to probe the bulk of the population of high-redshift star-forming galaxies. Methods. We constructed a UV-complete photometric-redshift sample following UV luminosity functions and measured the Lyα emission with MUSE using the latest (second) data release from the MUSE Hubble Ultra Deep Field Survey. Results. We derived the redshift evolution of XLAE for M1500 ∈ [ − 21.75; −17.75] for the first time with a equivalent width range EW(Lyα) ≥ 65 Å and found low values of XLAE ≲ 30% at z ≲ 6. The best-fit linear relation is XLAE = 0.07+0.06−0.03z − 0.22+0.12−0.24. For M1500 ∈ [ − 20.25; −18.75] and EW(Lyα) ≥ 25 Å, our XLAE values are consistent with those in the literature within 1σ at z ≲ 5, but our median values are systematically lower than reported values over the whole redshift range. In addition, we do not find a significant dependence of XLAE on M1500 for EW(Lyα) ≥ 50 Å at z ≈ 3–4, in contrast with previous work. The differences in XLAE mainly arise from selection biases for Lyman Break Galaxies (LBGs) in the literature: UV-faint LBGs are more easily selected if they have strong Lyα emission, hence XLAE is biased towards higher values when those samples are used. Conclusions. Our results suggest either a lower increase of XLAE towards z ≈ 6 than previously suggested, or even a turnover of XLAE at z ≈ 5.5, which may be the signature of a late or patchy reionization process. We compared our results with predictions from a cosmological galaxy evolution model. We find that a model with a bursty star formation (SF) can reproduce our observed LAE fractions much better than models where SF is a smooth function of time.
Future Changes in Rainy Season over East Asia Projected by Massive Ensemble Simulations with a High-Resolution Global Atmospheric Model

In this study, future changes in the rainy season in East Asia are projected based on massive ensemble simulations of about 100 members with a 60-km mesh global atmospheric model (the 60-km model hereinafter) called the “Database for Policy Decision-Making for Future Climate Change (d4PDF)”. For the present-climate, historical observed sea surface temperatures (SSTs) are prescribed to the 60-km model. In the future, 4°C warmer climate relative to the preindustrial climate, six different SST distributions projected by Atmosphere–Ocean General Circulation Models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are given to the 60-km model. In the future, summer precipitation will generally increase in most regions of East Asia, but will decrease over western Japan. Precipitation decreases in June around 30 – 35°N over China, Korea and Japan. The Probability Density Function directly was derived from the massive ensemble simulations at each grid point in June and revealed that the most intense precipitation increase will occur in some regions where moderate precipitation decreases will take place in terms of the simple ensemble average. In western Japan, the onset of rainy season will delay and the retreat will occur earlier, resulting in a shorter rainy season. The decrease of precipitation in June over western Japan may be attributed to the counter-effect of the convergence of moisture to the south of Japan, originating in the southward shift of the western North Pacific subtropical high. The projected decrease in June precipitation over western Japan is confirmed to be robust, regardless of model differences in horizontal resolution, convection schemes, and with/without air-sea interactions.
FACTORS INFLUENCING INVESTMENT IN MANUFACTURING INDUSTRY IN KARNATAKA, INDIA

Professor and Director, School of Research and Innovation, CMR University ABSTRACT: Karnataka is one of the major states which has been pursuing economic reforms to accelerate industrialisation. The state government has been pursuing a progressive industrial policy. It is the endeavour of the state government to improve its ranking in the industrial map of the country and become one of the foremost industrialised states by the turn of the century. In tune with the liberalised New Industrial / Economic and Trade Policy measures announced by the government of India since July 1991, the government of Karnataka has announced its New Industrial Policy and Package of Incentives and Concessions – 1993. Manufacturing dominates investment proposals that have come to the state. Steel and cement are major industries in terms of investment value. Though Bangalore is known as the software capital of India, the quantum of investment proposed for such projects is small (9 per cent) in relative terms. Karnataka has the best manufacturing process ratio of 2.63 with maximum value of goods being converted into finished goods valuing over Rs. 2,000 crores. The study analyses the investment determinates and their relationship with investment during periods 1990-2000, 2000-10 and 2010-17 in three phases. The data required is obtained from the secondary courses. The study concludes that the sustainable growth of the manufacturing sector largely depends upon the existence of sound financial infrastructure as a major determinant along with Telecommunication and Land allotment schemes by the govt.
Mitigation of Drought Stress in Wheat by Bio-priming by PGPB Containing ACC Deaminase Activity

Out of stress management strategies used for drought, inoculation of plant growth-promoting bacteria holds a major position due to sustainable, low-cost, and versatile properties. The plant growth-promoting bacteria, particularly containing 1-aminocyclopropane-1-carboxylic acid deaminase activity, have a critical location since they restrict ethylene synthesis under stress conditions thereby improving stress tolerance index. In this experiment, seeds of two wheat cultivars were primed with three bacterial strains and seedlings were grown under stress and nonstress conditions. The study was laid out in completely randomized factorial design with three replications. While plant growth achieved top performance with synthetic fertilizer in 80% of field capacity, increasing drought stress restricted the efficiency of synthetic fertilizer. In contrast, plant growth-promoting bacteria-priming promoted plant growth and dry matter accumulation under optimum and drought conditions. Increase of dry matter accumulation in treatments as control plants varied between 17.1% and 57.1% under 80% of field capacity while it changed between 0.2% and 35.1% under drought conditions. TV126C and TV24C induced stress tolerance index in sensitive and tolerant cultivars under drought and optimum conditions. In conclusion, it is considered that bio-priming with plant growth-promoting bacteria involving 1-aminocyclopropane1-carboxylic acid deaminase enzyme activity might be an effective and sustainable management strategy to drought stress in wheat cultivation.
Premature Cardiovascular Death and its Modifiable Risk Factors: Protocol of a Systematic Review and Meta-Analysis

Introduction: The burden of cardiovascular disease (CVDs), in the number of premature deaths, continues to increase globally and alarmingly, especially in almost all countries outside high income countries. An accurate estimate of premature CVD death is of crucial importance for planning, implementing, and evaluating cardiovascular prevention and care interventions. However, existing literature reported the evidence on premature CVD death from selected regions, and there has been less evidence of systematic review with meta analysis estimating the global premature death. This paper reports the protocol for a systematic review and meta analysis to derive solid and updated estimates on global and setting specific premature CVD death prevalence and its associated risk factors. Methods and analysis: PUBMED, EMBASE, Web of Science, CINAHL, and Cochrane Central Register of Controlled Trials (CENTRAL) will be used as the literature database. Retrieved records will be independently screened by two authors and relevant data will be extracted from studies that report data on premature mortality (death before the age of 70 years) related to CVD. Study selection and reporting will follow the Preferred Reporting Items for Systematic Review and Meta analyses (PRISMA) guideline. Pooled estimates of premature CVD mortality (based on standardised mortality ratio and years of life lost) and the effect size of modifiable risk factors will be computed applying random-effects meta-analysis. Heterogeneity among selected studies will be assessed using the I2 statistic and explored through meta regression and subgroup analyses. Depending on data availability, we propose to conduct subgroup analyses by geographical area, CVD events, and socio-demographic variables of interest study. The risk of bias for the studies included in the systematic review or meta analysis will be assessed by the Newcastle Ottawa Quality Assessment Scale. Ethics and dissemination: Ethics approval is not required as the data used in this systematic review will be extracted from published studies. The systematic review will focus on the premature CVD mortality rate and its associated factors. The findings of the final report will be disseminated to the scientific community through publication in a peer-reviewed journal and presentation at conferences. PROSPERO registration number: CRD42021288415
A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data

Large collaborative research networks provide opportunities to jointly analyze multicenter electronic health record (EHR) data, which can improve the sample size, diversity of the study population, and generalizability of the results. However, there are challenges to analyzing multicenter EHR data including privacy protection, large-scale computation, heterogeneity across sites, and correlated observations. In this paper, we propose a federated algorithm for generalized linear mixed models (Fed-GLMM), which can flexibly model multicenter longitudinal or correlated data while accounting for site-level heterogeneity. Fed-GLMM can be applied to both federated and centralized research networks to enable privacy-preserving data integration and improve computational efficiency. By communicating only a limited amount of summary statistics, Fed-GLMM can achieve nearly identical results as the gold-standard method where the GLMM is directly fitted on the pooled dataset. We demonstrate the performance of Fed-GLMM in both numerical experiments and an application to longitudinal EHR data from multiple healthcare facilities.
Physical, Psychological, and Cognitive Profile of Post-COVID Conditions in Healthcare Workers, Quebec, Canada

Importance. Most adults with COVID-19 do not require hospitalization, but the subsequent risk of post-COVID condition, including associated psychological and cognitive dysfunction, remains poorly understood among non-hospitalized versus hospitalized cases. Objective. To assess the prevalence and duration of post-COVID condition, including physical, psychological and cognitive symptoms. Design. Case series and case-control study between December 2020 and May 2021 Setting. Healthcare workers in Quebec, Canada Participants. Eligible cases were symptomatic healthcare workers with PCR-confirmed COVID-19 between July 2020 and May 2021. Among 17,717 contacted cases, 6061 (34%) participated. A random sample of symptomatic healthcare workers with negative PCR result between November 2020 and May 2021 served as controls. Among 11,498 contacted controls, 4390 (38%) participated. Exposures. In multivariable models, sociodemographic and clinical characteristics, as well as vaccine history, were evaluated as potential risk factors. Prevalence ratios compared self-reported cognitive dysfunctions (difficulty concentrating; difficulty organizing oneself; forgetfulness; loss of necessary items) among cases with post-COVID condition to controls, adjusting for psychological distress and fatigue. Outcomes. Post-COVID condition was defined by symptoms persisting [≥]4 weeks or [≥]12 weeks after COVID-19 onset. Results. Four-week and 12-week post-COVID condition prevalences of 46% (2,746/5,943) and 40% (653/1,746), respectively, were observed among non-hospitalized cases and 76% (90/118) and 68% (27/37), respectively, among hospitalized cases. Hospitalization, female sex and age were associated with higher risk. A substantial proportion of non-hospitalized cases with 4-week post-COVID condition often or very often reported cognitive dysfunction, including concentration (33%) or organizing (23%) difficulties, forgetfulness (20%) and loss of necessary items (10%), with no decline at 12 weeks. All four aspects of cognitive dysfunction were 2.2 to 3.0 times more prevalent among cases with post-COVID condition than in controls, but also independently associated with psychological distress and fatigue. Conclusions and relevance. Post-COVID condition may be a frequent sequela of ambulatory COVID-19 in working-age adults, with important effects on cognition. With so many healthcare workers infected since the beginning of the COVID-19 pandemic, the ongoing implications for quality healthcare delivery could be profound should cognitive dysfunction and other severe post-COVID symptoms persist in a professionally-disabling way over the longer term.
Factors Associated With Post-craniotomy Headache After Microvascular Decompression in Hemifacial Spasm? A Retrospective Study

Abstract Objective: Patients who undergo microvascular decompression (MVD) often experience post-craniotomy headache (PCH), while the PCH is always neglected. This study is aimed to describe the natural course and risk factors of PCH. Methods The severity and duration of PCH in 87 patients who undergo MVD were recorded. Factors related to the severity and duration of PCH were analyzed. Results Most patients (63.2%) had at least one assessment of moderate to severe PCH. Almost all patients (92%) would gradually decrease to disappear within 7 days. A small number of patients (25.5%) had PCH at the incision, and other patients had PCH inside the head. Younger age and gas in the prepontine cistern were the salient features of patients in the severe group. Younger, higher SAS, gas in the prepontine cistern area, and postoperative fever were independent risk factors that affect the duration of PCH. Conclusions PCH is the most common and self-limiting complication after MVD among patients with HFS. Young age, temperature > 38{ring}C after MVD within 24h, and gas around the TN are associated may predict the severity and duration of PCH. Significance This is the first study to describe the severity, duration, location, and risk factors of PCH.
Experimental Study on the Restoring Force Model of Reactive Powder Concrete Hollow Piers

Low cyclic loading tests of five large-scale rectangular RPC hollow pier specimens were made and the failure patterns and hysteretic properties of the specimens were studied.The characteristics of the skeleton curves of the specimens were analyzed,those factors affecting the restoring force models of the specimens were considered and the numerical regressive analysis method was used.Then the bilinear degradation restoring force model of RPC hollow piers is established.Numerical simulation analysis was performed with the program compiled with the strip method,and the calculation results agree well with the experimental results.The research results may serve as theoretical references for seismic design of RPC hollow piers.
Numerical study on the electromechanical behavior of dielectric elastomer with the influence of surrounding medium

ABSTRACT The considerable electric-induced shape change, together with the attributes of lightweight, high efficiency, and inexpensive cost, makes dielectric elastomer, a promising soft active material for the realization of actuators in broad applications. Although, a number of prototype devices have been demonstrated in the past few years, the further development of this technology necessitates adequate analytical and numerical tools. Especially, previous theoretical studies always neglect the influence of surrounding medium. Due to the large deformation and nonlinear equations of states involved in dielectric elastomer, finite element method (FEM) is anticipated; however, the few available formulations employ homemade codes, which are inconvenient to implement. The aim of this work is to present a numerical approach with the commercial FEM package COMSOL to investigate the nonlinear response of dielectric elastomer under electric stimulation. The influence of surrounding free space on the electric field is analyzed and the corresponding electric force is taken into account through an electric surface traction on the circumstances edge. By employing Maxwell stress tensor as actuation pressure, the mechanical and electric governing equations for dielectric elastomer are coupled, and then solved simultaneously with the Gent model of stain energy to derive the electric induced large deformation as well as the electromechanical instability. The finite element implementation presented here may provide a powerful computational tool to help design and optimize the engineering applications of dielectric elastomer.