Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision-Theoretic Approaches for Robotic Environmental Monitoring - A Survey

Robotics has dramatically increased our ability to gather data about our environments, creating an opportunity for the robotics and algorithms communities to collaborate on novel solutions to environmental monitoring problems. To understand a taxonomy of problems and methods in this realm, we present the first comprehensive survey of decision-theoretic approaches that enable efficient sampling of various environmental processes. We investigate representations for different environments, followed by a discussion of using these presentations to solve tasks of interest, such as learning, localization, and monitoring. To efficiently implement the tasks, decision-theoretic optimization algorithms consider: (1) where to take measurements from, (2) which tasks to be assigned, (3) what samples to collect, (4) when to collect samples, (5) how to learn environment; and (6) who to communicate. Finally, we summarize our study and present the challenges and opportunities in robotic environmental monitoring.
Selective 4D modelling framework for spatial-temporal land information management system

This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.
Primary bone lymphoma: Treatment results and prognostic factors with long‐term follow‐up of 82 patients

To the authors' knowledge, there is limited information on the preferred treatment and long‐term prognosis of primary bone lymphomas (PBLs). All PBL cases treated at the study center between 1963 and 2003 were analyzed to determine patient, disease, and treatment factors that could affect outcome measured by overall survival (OS), cause‐specific survival (CSS), and freedom‐from‐treatment failure (FFTF).
Simple Rule Injection for ComplEx Embeddings

Recent works in neural knowledge graph inference attempt to combine logic rules with knowledge graph embeddings to benefit from prior knowledge. However, they usually cannot avoid rule grounding, and injecting a diverse set of rules has still not been thoroughly explored. In this work, we propose InjEx, a mechanism to inject multiple types of rules through simple constraints, which capture definite Horn rules. To start, we theoretically prove that InjEx can inject such rules. Next, to demonstrate that InjEx infuses interpretable prior knowledge into the embedding space, we evaluate InjEx on both the knowledge graph completion (KGC) and few-shot knowledge graph completion (FKGC) settings. Our experimental results reveal that InjEx outperforms both baseline KGC models as well as specialized few-shot models while maintaining its scalability and efficiency.
The effects of aerosols on precipitation and dimensions of subtropical clouds: a sensitivity study using a numerical cloud model

Numerical experiments were carried out using the Tel-Aviv University 2-D cloud model to investigate the effects of increased concentrations of Cloud Condensation Nuclei (CCN), giant CCN (GCCN) and Ice Nuclei (IN) on the development of precipitation and cloud structure in mixed-phase sub-tropical convective clouds. In order to differentiate between the contribution of the aerosols and the meteorology, all simulations were conducted with the same meteorological conditions. The results show that under the same meteorological conditions, polluted clouds (with high CCN concentrations) produce less precipitation than clean clouds (with low CCN concentrations), the initiation of precipitation is delayed and the lifetimes of the clouds are longer. GCCN enhance the total precipitation on the ground in polluted clouds but they have no noticeable effect on cleaner clouds. The increased rainfall due to GCCN is mainly a result of the increased graupel mass in the cloud, but it only partially offsets the decrease in rainfall due to pollution (increased CCN). The addition of more effective IN, such as mineral dust particles, reduces the total amount of precipitation on the ground. This reduction is more pronounced in clean clouds than in polluted ones. Polluted clouds reach higher altitudes and are wider than clean clouds and both produce wider clouds (anvils) when more IN are introduced. Since under the same vertical sounding the polluted clouds produce less rain, more water vapor is left aloft after the rain stops. In our simulations about 3.5 times more water evaporates after the rain stops from the polluted cloud as compared to the clean cloud. The implication is that much more water vapor is transported from lower levels to the mid troposphere under polluted conditions, something that should be considered in climate models.
Spatial and Temporal Characterization of Sea Surface Temperature Response to Tropical Cyclones

AbstractThe spatial structure and temporal evolution of the sea surface temperature (SST) anomaly (SSTA) associated with the passage of tropical cyclones (TCs), as well as their sensitivity to TC characteristics (including TC intensity and translation speed) and oceanic climatological conditions (represented here by latitude), are thoroughly examined by means of composite analysis using satellite-derived SST data. The magnitude of the TC-generated SSTA is larger for more intense, slower-moving, and higher-latitude TCs, and it occurs earlier in time for faster-moving and higher-latitude storms. The location of maximum SSTA is farther off the TC track for faster-moving storms, and it moves toward the track with time after the TC passage. The spatial extension of the cold wake is greater for more intense and for slower-moving storms, but its shape is quite independent of TC characteristics. Consistent with previous studies, the calculations show that the mean SSTA over a TC-centered box nearly linearly corre.
SCD inhibition preferentially eradicates AML displaying high de novo fatty acid desaturation and synergizes with chemotherapy

Identification of specific and therapeutically actionable vulnerabilities in acute myeloid leukaemia (AML) is needed to improve patients’ outcome. These features should be ideally present in many patients independently of mutational background. Here we identify de novo fatty acid (FA) desaturation, specifically stearoyl-CoA desaturase (SCD) inhibition, as a therapeutic vulnerability across multiple AML models in vitro and in vivo. We use the novel clinical grade SCD inhibitor SSI-4 to show that SCD inhibition induces AML cell death via pleiotropic effects, and sensitivity is based on their dependency on FA desaturation regardless of mutational profile. SSI-4 efficacy is enhanced by driving FA biosynthesis in vitro while stroma confers protective effects that extend to in vivo models. SCD inhibition increases DNA damage and its combination with standard DNA damage-inducing chemotherapy prolongs survival in aggressive murine AML models. Our work supports developing FA desaturase inhibitors in AML while stressing the importance of identifying predictive biomarkers of response and biologically validated combination therapies to realize their therapeutic potential. One Sentence Summary SCD inhibition is toxic to AML cells with high rates of fatty acid desaturation and in combination with chemotherapy prolongs survival in murine AML models.
Seasonally migratory songbirds have different historic population size characteristics than resident relatives

Modern genomic methods enable estimation of a lineage’s long-term effective population sizes back to its origins. This ability allows unprecedented opportunities to determine how adoption of a major life-history trait affects lineages’ populations relative to those without the trait. We used this novel approach to study the population effects of the life-history trait of seasonal migration in evolutionary time. Seasonal migration is a common life-history strategy, but its effects on long-term population sizes relative to lineages that don’t migrate are largely unknown. Using whole-genome data, we estimated effective population sizes over millions of years in closely related seasonally migratory and resident lineages in a group of songbirds. Our main predictions were borne out: Seasonal migration is associated with larger effective population sizes (Ne), greater long-term variation in Ne, and a greater degree of initial population growth than among resident lineages. Initial growth periods showed phylogenetic signal, and their length (0.75-4.3 Myr) parallels the expansion and adaptation phases of taxon cycles, a framework of lineage expansion and eventual contraction over time encompassing biogeography and evolutionary ecology. Heterogeneity among lineages is noteworthy, despite geographic proximity (including overlap) and close relatedness. Seasonal migration imbues these lineages with fundamentally different population size attributes through evolutionary time compared to closely related resident lineages.
ADAPD: Sensor Adaptativo de Tempo Real para Buracos em Rodovias Baseado em Vibração

O modal rodoviario constitui a principal matriz de transporte para escoamento de producao e circulacao de pessoas no mundo. Problemas estruturais decorrentes de seu estado de conservacao acarretam uma serie de implicacoes socioeconomicas. Os buracos, em especial, constituem uma das deformidades mais recorrentes e perigosas. Dentre os metodos desenvolvidos para sua deteccao, os baseados em vibracao constituem um meio eficaz e de baixo custo. Contudo, estudos correlatos apresentam diversas demandas a serem supridas. Desta forma, este trabalho objetivou o desenvolvimento de um sensor adaptativo com recurso de autocalibracao e combinacoes algoritmicas para aprimorar a deteccao.
Learning Terrain-Adaptive Locomotion with Agile Behaviors by Imitating Animals

In this paper, we present a general learning framework for controlling a quadruped robot that can mimic the behavior of real animals and traverse challenging terrains. Our method consists of two steps: an imitation learning step to learn from motions of real animals, and a terrain adaptation step to enable generalization to unseen terrains. We capture motions from a Labrador on various terrains to facilitate terrain adaptive locomotion. Our experiments demonstrate that our policy can traverse various terrains and produce a natural-looking behavior. We deployed our method on the real quadruped robot $\boldsymbol{Max}$ [1] via zero-shot simulation-to-reality transfer, achieving a speed of 1.1 m/s on stairs climbing.
Multi-representation DeepInsight: an improvement on tabular data analysis

Tabular data analysis is a critical task in various domains, enabling us to uncover valuable insights from structured datasets. While traditional machine learning methods have been employed for feature engineering and dimensionality reduction, they often struggle to capture the intricate relationships and dependencies within real-world datasets. In this paper, we present Multi-representation DeepInsight (abbreviated as MRep-DeepInsight), an innovative extension of the DeepInsight method, specifically designed to enhance the analysis of tabular data. By generating multiple representations of samples using diverse feature extraction techniques, our approach aims to capture a broader range of features and reveal deeper insights. We demonstrate the effectiveness of MRep-DeepInsight on single-cell datasets, Alzheimer’s data, and artificial data, showcasing an improved accuracy over the original DeepInsight approach and machine learning methods like random forest and L2-regularized logistic regression. Our results highlight the value of incorporating multiple representations for robust and accurate tabular data analysis. By embracing the power of diverse representations, MRep-DeepInsight offers a promising avenue for advancing decision-making and scientific discovery across a wide range of fields.
Investigating risk of self-harm and suicide on anniversaries after bereavement by suicide and other causes: a Danish population-based self-controlled case series study

Abstract Aims To investigate mechanisms of suicide risk in people bereaved by suicide, prompted by observations that bereaved people experience higher levels of distress around dates of emotional significance. We hypothesised that suicide-bereaved first-degree relatives and partners experience an increased risk of self-harm and suicide around dates of (i) anniversaries of the death and (ii) the deceased’s birthday, compared with intervening periods. Methods We conducted a self-controlled case series study using national register data on all individuals living in Denmark from 1 January 1980 to 31 December 2016 and who were bereaved by the suicide of a first-degree relative or partner (spouse or cohabitee) during that period, and who had the outcome (any episode of self-harm or suicide) within 5 years and 6 weeks of the bereavement. We compared relative incidence of suicidal behaviour in (i) the first 30 days after bereavement and (ii) in the aggregated exposed periods (6 weeks either side of death anniversaries; 6 weeks either side of the deceased’s birthdays) to the reference (aggregated unexposed intervening periods). As an indirect comparison, we repeated these models in people bereaved by other causes. Results We found no evidence of an elevated risk of suicidal behaviour during periods around anniversaries of a death or the deceased’s birthdays in people bereaved by suicide (adjusted incidence rate ratio [IRRadj] = 1.00; 95% confidence interval [CI] = 0.87–1.16) or other causes (IRRadj = 1.04; 95% CI = 1.00–1.08) compared with intervening periods. Rates were elevated in the 30 days immediately after bereavement by other causes (IRRadj: 1.95, 95% CI: 1.77–2.22). Conclusions Although people bereaved by suicide are at elevated risk of self-harm and suicide, our findings do not suggest that this risk is heightened around emotionally significant anniversaries. Bereavement care should be accessible at all points after a traumatic loss as needs will differ over the grief trajectory.
Highly scalable and standardized organ-on-chip platform with TEER for biological barrier modeling

The development of new therapies is hampered by the lack of predictive, and patient-relevant in vitro models. Organ-on-chip (OOC) technologies can potentially recreate physiological features and hold great promise for tissue and disease modeling. However, the non-standardized design of these chips and perfusion control systems has been a barrier to quantitative high-throughput screening (HTS). Here we present a scalable OOC microfluidic platform for applied kinetic in vitro assays (AKITA) that is applicable for high, medium, and low throughput. Its standard 96-well plate and 384-well plate layouts ensure compatibility with existing laboratory workflows and high-throughput data collection and analysis tools. The AKITA plate is optimized for the modeling of vascularized biological barriers, primarily the blood-brain barrier, skin, and lung, with precise flow control on a custom rocker. The integration of trans-epithelial electrical resistance (TEER) sensors allows rapid and repeated monitoring of barrier integrity over long time periods. Together with automated confocal imaging and compound permeability testing analyses, we demonstrate the flexibility of the AKITA platform for establishing human-relevant models for preclinical drug and precision medicine’s efficacy, toxicity, and permeability under physiological conditions.
Clinical and Basic Cardiology

Non-selective beta-blockers tend to increase triglycerides and low-density lipoprotein (LDL) cholesterol while decreasing the atheroprotective high-density lipoprotein (HDL) cholesterol, particularly the HDL 2 cholesterol subfraction. The aim of this study was to investigate whether the highly beta 1 -selective beta-blocker bisoprolol shares with non-selective beta-blockers these effects on blood lipids in patients treated for mild or moderate essential hypertension. In particular, HDL cholesterol and its subfractions HDL 2 cholesterol and HDL 3 cholesterol as well as apolipoproteins A1 and B were investigated. In a multicentre outpatient trial, 86 hypertensive patients received bisoprolol for eight weeks. Diastolic blood pressure was reduced from a baseline of 102 ± 7 mmHg (mean ± SD) to 87 ± 8 mmHg after 8 weeks of therapy with bisoprolol. Systolic blood pressure decreased from 159 ± 17 mmHg to 139 ± 14 mmHg. Blood pressure was normalized in 69 % of patients with 5 mg bisoprolol once daily and, after increasing the dosage to 10 mg bisoprolol once daily in non-responders, in 80 % of patients. Treatment with bisoprolol decreased triglycerides by 4.8 % and LDL cholesterol by 1.7 %, whereas HDL cholesterol increased by 5.2 %, which was attributable to an increase by 9.2 % of HDL 2 cholesterol and by 3.0 % of HDL 3 cholesterol, respectively. None of these single changes were significant at the p < 0.05 level. Surprisingly, however, all lipid effects were in the favourable direction and opposite to the changes usually observed with non-selective beta-blockers. In a mathematical model derived from angiographic studies, the improvement of lipid risk factors brought about by bisoprolol equalled that of a decrease in age by 3.5 years. We thus conclude that effective antihypertensive doses of bisoprolol do not exert the typical dyslipidaemic effects of beta-blockers but rather tend to induce small but favourable changes in plasma triglycerides, LDL and HDL cholesterol, and especially in the atheroprotective HDL 2 cholesterol subfraction. J Clin Basic Cardiol 2001; 4: 57–60.
Clinical and Basic Cardiology

Assessment of regional wall motion plays a major role in daily routine echocardiography. However, reliable visual analysis remains challenging in a significant number of patients. Tissue Doppler and strain rate imaging are new techniques which provide velocities of the myocardial wall during the cardiac cycle and therefore allow quantification of both regional and global systolic and diastolic function. J Clin Basic Cardiol 2002; 5: 125–32.
NNVISR: Bring Neural Network Video Interpolation and Super Resolution into Video Processing Framework

We present NNVISR - an open-source filter plugin for the VapourSynth video processing framework, which facilitates the application of neural networks for various kinds of video enhancing tasks, including denoising, super resolution, interpolation, and spatio-temporal super-resolution. NNVISR fills the gap between video enhancement neural networks and video processing pipelines, by accepting any network that enhances a group of frames, and handling all other network agnostic details during video processing. NNVISR is publicly released at https://github.com/tongyuantongyu/vs-NNVISR.
Assessing the impact of emergency department short stay units using length-of-stay prediction and discrete event simulation

Accurately predicting hospital length-of-stay at the time a patient is admitted to hospital may help guide clinical decision making and resource allocation. In this study we aim to build a decision support system that predicts hospital length-of-stay for patients admitted to general internal medicine from the emergency department. We conduct an exploratory data analysis and employ feature selection methods to identify the attributes that result in the best predictive performance. We also develop a discrete-event simulation model to assess the performances of the prediction models in a practical setting. Our results show that the recommendation performances of the proposed approaches are generally acceptable and do not benefit from the feature selection. Further, the results indicate that hospital length-of-stay could be predicted with reasonable accuracy (e.g., AUC value for classifying short and long stay patients is 0.69) using patient admission demographics, laboratory test results, diagnostic imaging, vital signs and clinical documentation.
Expert Panel on Neurological Imaging and Musculoskeletal Imaging:

The ACR Committee on Appropriateness Criteria and its expert panels have developed criteria for determining appropriate imaging examinations for diagnosis and treatment of specified medical condition(s). These criteria are intended to guide radiologists, radiation oncologists and referring physicians in making decisions regarding radiologic imaging and treatment. Generally, the complexity and severity of a patient’s clinical condition should dictate the selection of appropriate imaging procedures or treatments. Only those examinations generally used for evaluation of the patient’s condition are ranked. Other imaging studies necessary to evaluate other co-existent diseases or other medical consequences of this condition are not considered in this document. The availability of equipment or personnel may influence the selection of appropriate imaging procedures or treatments. Imaging techniques classified as investigational by the FDA have not been considered in developing these criteria; however, study of new equipment and applications should be encouraged. The ultimate decision regarding the appropriateness of any specific radiologic examination or treatment must be made by the referring physician and radiologist in light of all the circumstances presented in an individual examination.
DNAPL Dissolution in Bedrock Fractures And Fracture Networks

Abstract : This project focused on measuring and evaluating the architecture, dissolution rate, and impact on groundwater quality of residually trapped tetrachloroethene (PCE) dense non-aqueous phase liquid (DNAPL) from discrete bedrock fractures and fracture networks constructed at the bench-scale. Results demonstrated that residual DNAPL in rock fractures is not well contacted by migrating water. This resulted in reduced dissolution rates, and persistence of DNAPL sources within the bedrock fractures. Bioaugmentation was effective at substantially enhancing the rate of DNAPL removal, despite dissolved PCE concentrations that were near solubility. Chemical oxidation was shown to be ineffective for treating DNAPL sources in bedrock fractures. This ineffectiveness was due to decreases in the effective DNAPL-water interfacial area (as measured using interfacial tracers) that were likely caused by oxidation reaction byproducts.