Miracle-dz/UniFAR-FTUs huggingface dataset:
Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment Supervision

In Vision-and-Language Navigation (VLN) task, an agent is asked to navigate inside 3D indoor environments following given instructions. Cross-modal alignment is one of the most critical challenges in VLN because the predicted trajectory needs to match the given instruction accurately. In this paper, we address the cross-modal alignment challenge from the perspective of ﬁne-grain. Firstly, to alleviate weak cross-modal alignment supervision from coarse-grained data, we introduce a human-annotated ﬁne-grained VLN dataset, namely Landmark-RxR. Secondly, to further enhance local cross-modal alignment under ﬁne-grained supervision, we investigate the focal-oriented rewards with soft and hard forms, by focusing on the critical points sampled from ﬁne-grained Landmark-RxR. More-over, to fully evaluate the navigation process, we also propose a re-initialization mechanism that makes metrics insensitive to difﬁcult points, which can cause the agent to deviate from the correct trajectories. Experimental results show that our agent has superior navigation performance on Landmark-RxR,
Isoductile strengths and strength reduction factors of elasto‐plastic SDOF systems subjected to simple waveforms

The inelastic response of elasto‐plastic SDOF oscillators subjected to 24 simple waveforms was studied. The waveforms contain linear, quadratic, sinusoidal, and triangular acceleration components that repeat for not more than several cycles. Similarities and differences in oscillator response characteristics are presented, organized by a characteristic period. The strengths and corresponding strength reduction factors required for constant ductility responses are discussed. Response data are compared with expectations based on the concepts of equal energy, equal displacement, and preservation of force. Limitations on the applicability of the equal energy concept are identified. Copyright © 2001 John Wiley & Sons, Ltd.
Continuous real-time remote monitoring of severely or chronically ill children

Compared to parents of healthy children, parents of severely or chronically ill children have significantly worse physical and mental health and a lower quality of life, e.g. because of lack of sleep. The proposed solution aims at assisting caregivers by means of a remote monitoring service run by professional nursing staff which should allow parents to get a good night’s sleep. A smart algorithm has been developed to detect if a particular parameter (heart rate, respiration rate or oxygen saturation) has exceeded a pre-defined threshold and thus may imply an emergency. Parents are only alerted after a professional nurse in the monitoring centre has cross-checked vital parameter trends and carried out an audio-visual inspection. The quality and accuracy of the system has been validated through iterative testing including a test performed in a children’s hospital to ensure that the monitoring system is not inferior to a hospital set-up.
CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum

Goal-conditioned reinforcement learning (RL) usually suffers from sparse reward and inefﬁcient exploration in long-horizon tasks. Planning can ﬁnd the shortest path to a distant goal that provides dense reward/guidance but is inaccurate without a precise environment model. We show that RL and planning can collaboratively learn from each other to overcome their own drawbacks. In “ CO-PILOT ”, a learnable path-planner and an RL agent produce dense feedback to train each other on a curriculum of tree-structured sub-tasks. Firstly, the planner recursively decomposes a long-horizon task to a tree of sub-tasks in a top-down manner, whose layers construct coarse-to-ﬁne sub-task sequences as plans to complete the original task. The planning policy is trained to minimize the RL agent’s cost of completing the sequence in each layer from top to bottom layers, which gradually increases the sub-tasks and thus forms an easy-to-hard curriculum for the planner. Next, a bottom-up traversal of the tree trains the RL agent from easier sub-tasks with denser rewards on bottom layers to harder ones on top layers and collects its cost on each sub-task train the planner in the next episode. CO-PILOT repeats this mutual training for multiple episodes before switching to a new task, so the RL agent and planner are fully optimized to facilitate each other’s training. We compare CO-PILOT with RL (SAC, HER, PPO), planning (RRT*, NEXT, SGT), and their combination (SoRB) on navigation and continuous control tasks. CO-PILOT
Identification and Estimation of Joint Probabilities of Potential Outcomes in Observational Studies with Covariate Information

The joint probabilities of potential outcomes are fundamental components of causal inference in the sense that (i) if they are identifiable, then the causal risk is also identifiable, but not vise versa (Pearl, 2009; Tian and Pearl, 2000) and (ii) they enable us to evaluate the probabilistic aspects of “necessity”, “sufficiency”, and “necessity and sufficiency”, which are important concepts of successful explanation (Watson, et al., 2020). However, because they are not identifiable without any assumptions, various assumptions have been utilized to evaluate the joint probabilities of potential outcomes, e.g., the assumption of monotonicity (Pearl, 2009; Tian and Pearl, 2000), the independence between potential outcomes (Robins and Richardson, 2011), the condition of gain equality (Li and Pearl, 2019), and the specific functional relationships between cause and effect (Pearl, 2009). Unlike existing identification conditions, in order to evaluate the joint probabilities of potential outcomes without such assumptions, this paper proposes two types of novel identification conditions using covariate information. In addition, when the joint probabilities of potential outcomes are identifiable through the proposed conditions, the estimation problem of the joint probabilities of potential outcomes reduces to that of singular models and thus they can not be evaluated by standard statistical estimation methods. To solve the problem, this paper proposes a new statistical estimation method based on the augmented Lagrangian method and shows the asymptotic normality of the proposed estimators. Given space constraints, the proofs, the details on the statistical estimation method, some numerical experiments, and the case study are provided in the supplementary material.
Arthroscopic evaluat ion of potential s tructure modifying act ivity of hyaluronan ( Hyalgan ® ) in osteoarthrit is of the knee

Arthroscopic evaluat ion of potential s tructure modifying act ivity of hyaluronan (Hyalgan ®) in osteoarthrit is of the knee BY VI~RONIQUE LISTRAT, XAVIER AYRAL, FRANCESCA PATARNELLO*, JEAN-PAuL BONVARLET, JEAN SIMONNET, BERNARD AMOR AND MAXIME DOUGADOS Clinique de Rhumatologie HSpital Cochin, 27 rue du Fg Saint-Jacques 75014 Paris, France; and *Department Medical, Fidia s.p.A. Abano Terme, Italy
Karst Ecosystems in the Vortex of Capital: A Paradigmatic Study of the Commune Link Law Politics

Exokarst, endokarst ecosystems, a unit that supplies carbondioksida beyond forest.the geological, ecological fungtions of the karst, as a safe habitat for fauna, flora and rare spesies. Limestone regulates water input and out, guards the endokarst ground water basins where the uterus and the chain of life of chreatures. The exploitation of limestone, about massive damage 9,5% of the national karst area. This fact raises the problem of why the poltical construction of karst law is less fair and democratic and how is the political construction of karst law based on the karst environment. This problem is studied using a normative juridical methodology which results in that modernism is representated by positivism that iprecedes growth, is not sufficient to solve the problem of the karst ecosystem,requires a holistic link commune approach, synergyzing the consept of karst governance between juridical anthropocentric, ecocentric and biocentric.karst policy, regional spatial planning is not synchronous between the center and the regions, which is a karst problem.karst is irreplaceable, the exploitation of limestone is reviewed, empowerment of alternative ecoturism, agriculture, religious tourism, culture, science is developed, so that a country with mega bidodiversity in a suistainable environment is
[110] silicon etching for high aspect ratio comb structures

The characteristics of [110] silicon anisotropic bulk etching for fabrication of comb structure are studied with varied temperature and concentration of aqueous KOH solution The etch rates of [110] and (111) planes increase with increasing temperature but decrease with increasing concentration. The maximum etch rate ratio is above 150 at 45 exact wt. % and 60/spl deg/C of aqueous KOH solution. Surface roughness varies greatly with concentration, and the minimum roughness is observed in an aqueous KOH solution of 41 exact wt. %. The mechanism of beam reduction is also studied and modelled simply. Considering the etching characteristics, comb structure have been fabricated which are 8 /spl mu/m wide, 150 /spl mu/m high and separated by 7 /spl mu/m gaps, using a comb mask pattern 10 /spl mu/m wide with 5 /spl mu/m gaps in 41 exact wt. % aqueous KOH solution at 65/spl deg/C.
Parallel Training of Knowledge Graph Embedding Models: A Comparison of Techniques

Knowledge graph embedding (KGE) models represent the entities and relations of a knowledge graph (KG) using dense continuous representations called embeddings. KGE methods have recently gained traction for tasks such as knowledge graph completion and reasoning as well as to provide suitable entity representations for downstream learning tasks. While a large part of the available literature focuses on small KGs, a number of frameworks that are able to train KGE models for large-scale KGs by parallelization across multiple GPUs or machines have recently been proposed. So far, the benefits and drawbacks of the various parallelization techniques have not been studied comprehensively. In this paper, we report on an experimental study in which we presented, re-implemented in a common computational framework, investigated, and improved the available techniques. We found that the evaluation methodologies used in prior work are often not comparable and can be misleading, and that most of currently implemented training methods tend to have a negative impact on embedding quality. We propose a simple but effective variation of the stratification technique used by PyTorch BigGraph for mitigation. Moreover, basic random partitioning can be an effective or even the best-performing choice when combined with suitable sampling techniques. Ultimately, we found that efficient and effective parallel training of large-scale KGE models is indeed achievable but requires a careful choice of techniques.
Glitazone Treatment Rescues Phenotypic Deficits in a Fly Model of Gaucher/Parkinson’s Disease

Parkinson’s Disease (PD) is the most common movement disorder, and the strongest genetic risk factor for PD is mutations in the glucocerebrosidase gene (GBA). Mutations in GBA also lead to the development of Gaucher Disease (GD), the most common type of lysosomal storage disorder. Current therapeutic approaches fail to address neurological GD symptoms. Therefore, identifying therapeutic strategies that improve the phenotypic traits associated with GD/PD in animal models may provide an opportunity for treating neurological manifestations of GD/PD. Thiazolidinediones (TZDs, also called glitazones) are a class of compounds targeted for the treatment of type 2 diabetes, and have also shown promise for the treatment of neurodegenerative disease, including PD. Here, we tested the efficacy of glitazone administration during development in a fly GD model with deletions in the GBA homolog, dGBA1b (GBA1ΔTT/ΔTT). We observed an optimal dose of pioglitazone (PGZ) at a concentration of 1 μM that reduced sleep deficits, locomotor impairments, climbing defects, and restoration of normal protein levels of Ref(2)P, a marker of autophagic flux, in GBA1ΔTT/ΔTT mutant flies, compared to GBA1+/+ control flies. These data suggest that PGZ may represent a potential compound with which to treat GD/PD by improving function of lysosomal-autophagy pathways, a cellular process that removes misfolded or aggregated proteins.
Variable expression of eighteen common housekeeping genes in human non-cancerous kidney biopsies

Housekeeping, or reference genes (RGs) are, by definition, loci with stable expression profiles that are widely used as internal controls to normalize mRNA levels. However, due to specific events, such as pathological changes, or technical procedures, their expression might be altered, failing to fulfil critical normalization pre-requisites. To identify RG genes suitable as internal controls in human non-cancerous kidney tissue, we selected 18 RG candidates based on previous data and screen them in 30 expression datasets (>800 patients), including our own, publicly available or provided by independent groups. Datasets included specimens from patients with hypertensive and diabetic nephropathy, Fabry disease, focal segmental glomerulosclerosis, IgA nephropathy, membranous nephropathy, and minimal change disease. We examined both microdissected and whole section-based datasets. Expression variability of 4 candidate genes (YWHAZ, SLC4A1AP, RPS13 and ACTB) was further examined by qPCR in biopsies from patients with hypertensive nephropathy (n = 11) and healthy controls (n = 5). Only YWHAZ gene expression remained stable in all datasets whereas SLC4A1AP was stable in all but one Fabry dataset. All other RGs were differentially expressed in at least 2 datasets, and in 4.5 datasets on average. No differences in YWHAZ, SLC4A1AP, RPS13 and ACTB gene expression between hypertensive and control biopsies were detected by qPCR. Although RGs suitable to all techniques and tissues are unlikely to exist, our data suggest that in non-cancerous kidney biopsies expression of YWHAZ and SLC4AIAP genes is stable and suitable for normalization purposes.
The Patient, the Physician, or the Relationship: Who or What Is “Difficult”, Exactly? an Approach for Managing Conflicts between Patients and Physicians

It is the patient who consults, often at the last minute, the one you sigh over when you see his or her name on your list, the one who makes you feel powerless, and whom you would like to refer to a colleague. Every practicing physician has experienced being involved in a dialog of the deaf, with a patient refusing physicians’ recommendations, in a therapeutic dead end. Faced with such patients, the physician tries to convey scientific evidence to untangle the situation. When it does not work, he looks for other arguments, raises his voice, and avoids looking the patient in the eyes. When he is out of resources, trying to sound professional, he uses a sentence such as “I understand and respect your beliefs, but I am telling you what I learned in medical school! ”. At the same time, his non-verbal behavior betrays more than a hint of irritation. Far from being caricatures, such situations generally result in the physician diagnosing or labeling the patient as “difficult. ” This label is affixed on more than one patient in ten, and for all sorts of reasons. How, then, do you re-establish a relationship of trust? Or, even better, how do you avoid such labeling?
Microbial proteasomes as drug targets

Proteasomes are compartmentalized, ATP-dependent, N-terminal nucleophile hydrolases that play essentials roles in intracellular protein turnover. They are present in all 3 kingdoms. Pharmacological inhibition of proteasomes is detrimental to cell viability. Proteasome inhibitor rugs revolutionize the treatment of multiple myeloma. Proteasomes in pathogenic microbes such as Mycobacterium tuberculosis (Mtb), Plasmodium falciparum (Pf), and other parasites and worms have been validated as therapeutic targets. Starting with Mtb proteasome, efforts in developing inhibitors selective for microbial proteasomes have made great progress lately. In this review, we describe the strategies and pharmacophores that have been used in developing proteasome inhibitors with potency and selectivity that spare human proteasomes and highlight the development of clinical proteasome inhibitor candidates for treatment of leishmaniasis and Chagas disease. Finally, we discuss the future challenges and therapeutical potentials of the microbial proteasome inhibitors.
Raphia-Microorganism Composite Biosorbent for Lead Ion Removal from Aqueous Solutions

This study investigated the possibility of obtaining a raphia-microorganism composite for removing lead ions from aqueous solutions using immobilized yeast cells Saccharomyces cerevisiae on Raphia farinifera fibers. The obtained biocomposite was characterized using scanning electron microscopy and Fourier transform infrared spectroscopy. Studies were conducted to determine the influence of contact time, initial concentration of Pb(II), and pH allowed for the selection of nonlinear equilibrium and kinetic models. The results showed that the biocomposite had a better Pb(II) removal capacity in comparison to the raphia fibers alone, and its maximum Pb(II) adsorption capacity was 94.8 mg/g. The model that best describes Pb(II) sorption was the Temkin isotherm model, while kinetic studies confirmed the chemical nature of the sorption process following the Elovich model. The obtained research results provide new information on the full use of the adsorption function of biomass and the ubiquitous microbial resources and their use in the remediation of aqueous environments contaminated with heavy metals.
Local Characteristics Related to SARS-CoV-2 Transmissions in the Seoul Metropolitan Area, South Korea

The Seoul metropolitan area is one of the most populated metropolitan areas in the world; hence, Seoul’s COVID-19 cases are highly concentrated. This study identified local demographic and socio-economic characteristics that affected SARS-CoV-2 transmission to provide locally targeted intervention policies. For the effective control of outbreaks, locally targeted intervention policies are required since the SARS-CoV-2 transmission process is heterogeneous over space. To identify the local COVID-19 characteristics, this study applied the geographically weighted lasso (GWL). GWL provides local regression coefficients, which were used to account for the spatial heterogeneity of SARS-CoV-2 outbreaks. In particular, the GWL pinpoints statistically significant regions with specific local characteristics. The applied explanatory variables involving demographic and socio-economic characteristics that were associated with higher SARS-CoV-2 transmission in the Seoul metropolitan area were as follows: young adults (19~34 years), older population, Christian population, foreign-born population, low-income households, and subway commuters. The COVID-19 case data were classified into three periods: the first period (from January 2020 to July 2021), the second period (from August to November 2020), and the third period (from December 2020 to February 2021), and the GWL was fitted for the entire period (from January 2020 to February 2021). The result showed that young adults, the Christian population, and subway commuters were the most significant local characteristics that influenced SARS-CoV-2 transmissions in the Seoul metropolitan area.
Needs for International Benchmarking of Road Safety Management Based on Mobility Exposure Measures and Risk Patterns

Each year, 1.35 million people worldwide die due to Road Traffic Injuries (RTI), highlighting the need for further research. The risk of RTI is usually estimated as the number of casualties divided by the level of exposure in a population. Identifying the most appropriate exposure measures is one of the most important current challenges in this field. This paper presents an analysis of exposure measures used in empirical studies on road accidents. The results show a large variability in the exposure measures used, ranging from more general measures (such as population figures or vehicle fleet) to more specific measures related to mobility (such as number of trips, distances or travel time). A comparison of the risk patterns found shows that there is a partial consensus on the profiles with the highest risk of road traffic injuries. In conclusion, there is a need for the international standardization of criteria and data to be recorded, at least injury severity and measures of exposure to mobility, as the travel time disaggregated by socio-demographic variables and mode of transport. Such data would provide higher-quality results on risk profiles and facilitate the implementation of more effective, knowledge-based road safety policies.
Genome-wide host methylation profiling of anal and cervical carcinoma

HPV infection results in changes in host gene methylation which, in turn, are thought to contribute to the neoplastic progression of HPV-associated cancers. The objective of this study was to identify joint and disease-specific genome-wide methylation changes in anal and cervical cancer as well as changes in high-grade pre-neoplastic lesions. Formalin-fixed paraffin-embedded (FFPE) anal tissues (n = 143; 99% HPV+) and fresh frozen cervical tissues (n = 28; 100% HPV+) underwent microdissection, DNA extraction, HPV genotyping, bisulfite modification, DNA restoration (FFPE) and analysis by the Illumina HumanMethylation450 Array. Differentially methylated regions (DMR; t test q<0.01, 3 consecutive significant CpG probes and mean Δβ methylation value>0.3) were compared between normal and cancer specimens in partial least squares (PLS) models and then used to classify anal or cervical intraepithelial neoplasia-3 (AIN3/CIN3). In AC, an 84-gene PLS signature (355 significant probes) differentiated normal anal mucosa (NM; n = 9) from AC (n = 121) while a 36-gene PLS signature (173 significant probes) differentiated normal cervical epithelium (n = 10) from CC (n = 9). The CC progression signature was validated using three independent publicly available datasets (n = 424 cases). The AC and CC progression PLS signatures were interchangeable in segregating normal, AIN3/CIN3 and AC and CC and were found to include 17 common overlapping hypermethylated genes. Moreover, these signatures segregated AIN3/CIN3 lesions similarly into cancer-like and normal-like categories. Distinct methylation changes occur across the genome during the progression of AC and CC with overall similar profiles and add to the evidence suggesting that HPV-driven oncogenesis may result in similar non-random methylomic events. Our findings may lead to identification of potential epigenetic drivers of HPV-associated cancers and also, of potential markers to identify higher risk pre-cancerous lesions.