Miracle-dz/UniFAR-FTUs huggingface dataset:
f-Cal: Aleatoric uncertainty quantification for robot perception via calibrated neural regression

While modern deep neural networks are performant perception modules, performance (accuracy) alone is insufficient, particularly for safety-critical robotic applications such as self-driving vehicles. Robot autonomy stacks also require these otherwise blackbox models to produce reliable and calibrated measures of confidence on their predictions. Existing approaches estimate uncertainty from these neural network perception stacks by modifying network architectures, inference procedure, or loss functions. However, in general, these methods lack calibration, meaning that the predictive uncertainties do not faithfully represent the true underlying uncertainties (process noise). Our key insight is that calibration is only achieved by imposing constraints across multiple examples, such as those in a mini-batch; as opposed to existing approaches which only impose constraints per-sample, often leading to overconfident (thus miscalibrated) uncertainty estimates. By enforcing the distribution of outputs of a neural network to resemble a target distribution by minimizing an $f$ -divergence, we obtain significantly better-calibrated models compared to prior approaches. Our approach, f-Cal, outperforms existing uncertainty calibration approaches on robot perception tasks such as object detection and monocular depth estimation over multiple real-world benchmarks.
Online Learning of Centroidal Angular Momentum towards Enhancing DCM-based Locomotion

Gait generation frameworks for humanoid robots typically assume a constant centroidal angular momentum (CAM) throughout the walking cycle, which induces undesirable contact torques in the feet and results in performance degradation. In this work, we present a novel algorithm to learn the CAM online and include the obtained knowledge within the closed-form solutions of the Divergent Component of Motion (DCM) locomotion framework. To ensure a reduction of the contact torques at the desired center of pressure position, a CAM trajectory is generated and explicitly tracked by a whole-body controller. Experiments with the humanoid robot TORO demonstrate that the proposed method significantly increases step length and walking speed during locomotion.
Insight into the Inclusion Complexation of Fluconazole with Sulfonatocalix[4]naphthalene in Aqueous Solution, Solid-State, and Its Antimycotic Activity

The study aims to assess the interaction between fluconazole and sulfonatocalix[4]naphthalene towards enhancing its dissolution performance and antimycotic activity. A solubility study was carried out at different pH conditions, and the results revealed the formation of a 1:1 molar ratio fluconazole-sulfonatocalix[4]naphthalene inclusion complex with an AL type phase solubility diagrams. The solid powder systems of fluconazole-sulfonatocalix[4]naphthalene were prepared using kneaded and co-evaporation techniques and physical mixtures. DCS, PXRD, TGA-DTG, FT-IR, and in vitro dissolution performance characterize the prepared systems. According to physicochemical characterization, the co-evaporation approach produces an amorphous inclusion complex of the drug inside the cavity of sulfonatocalix[4]naphthalene. The co-evaporate product significantly increased the drug dissolution rate up to 93 ± 1.77% within 10 min, unlike other prepared solid powders. The antimycotic activity showed an increase substantially (p ≤ 0.05, t-test) antimycotic activity of fluconazole co-evaporate mixture with sulfonatocalix[4]naphthalene compared with fluconazole alone against clinical strains of Candida albicans and Candida glabrata. In conclusion, sulfonatocalix[4]naphthalene could be considered an efficient complexing agent for fluconazole to enhance its aqueous solubility, dissolution performance, and antimycotic activity.
The Transmission Route and Selection Pressure in HCV Subtype 3a and 3b Chinese Infections: Evolutionary Kinetics and Selective Force Analysis

Hepatitis C virus (HCV) genotype 3 (GT-3) represents 22–30% of all infections and is the second most common genotype among all HCV genotypes. It has two main subtypes, GT-3a and GT-3b, that present epidemiological differences in transmission groups. This report generated 56 GT-3a and 64 GT-3b whole-genome sequences to conduct an evolutionary kinetics and selective force analysis with reference sequences from various countries. Evolutionary analysis showed that HCV GT-3a worldwide might have been transmitted from the Indian subcontinent to South Asia, Europe, North America and then become endemic in China. In China, GT-3a may have been transmitted by intravenous drug users (IDUs) and become endemic in the general population, while GT-3b may have originated from IDUs and then underwent mutual transmission between blood donors (BDs) and IDUs, ultimately becoming independently endemic in IDUs. Furthermore, the spread of GT-3a and GT-3b sequences from BD and IDU populations exhibit different selective pressures: the proportion of positively selected sites (PPSs) in E1 and E2 from IDUs was higher than in BDs. The number of positive selection sites was higher in GT-3b and IDUs. These results indicate that different selective constraints act along with the GT-3a and GT-3b genomes from IDUs and BDs. In addition, GT-3a and GT-3b have different transmission routes in China, which allows us to formulate specific HCV prevention and control strategies in China.
Le développement de la richesse flexionnelle d'enfants porteurs d'un implant cochléaire et d'enfants normo-entendants

Dans la littérature, les études qui concernent le développement grammatical d'enfants porteurs d'un implant cochléaire se sont concentrées surtout sur des tests standardisés. La présente étude a pour objectif d'analyser la richesse flexionnelle d'enfants porteurs d'un implant cochléaire dans leur langage direct et spontané en la comparant avec celle d'enfants normo-entendants. Neuf enfants porteurs d'un implant cochléaire ont été suivis annuellement entre l'âge de deux et sept ans. A chaque âge, il y avait un groupe de contrôle de 10 enfants normo-entendants. La richesse flexionnelle est analysée en utilisant l'indice « Mean Size of Paradigm » (MSP). Les résultats indiquent que la richesse flexionnelle (MSP) d'enfants porteurs d'un implant cochléaire est moins élevée que celle d'enfants normo-entendants jusqu'à l'âge de quatre ans. Cependant, dès l'âge de cinq ans la richesse flexionnelle est comparable dans les deux groupes, ce qui indique que les enfants porteurs d'un implant cochléaire ont rattrapé leur décalage par rapport aux enfants normoentendants.
Water Level Measurement Altitude Trainer Integrated With Human Machine Interface

This research aims to design a trainer simulator wake height of the water level measurement using microcontroller arduino mega integrated with Human Machine Interface (HMI). This tool is designed to describe a working system of water level elevation measurements as a learning medium HMI. By using a microcontroller arduino mega , all process es in both input and output can be integrated to the HMI using a 7-inch LCD screen.
Multidisciplinary team approach on tracheoesophageal fistula in a patient with home ventilator

A 68-year-old man was transferred to our tertiary hospital. Ten years ago, he received radiation therapy for tonsil cancer, and while there was no evidence of recurrence, he suffered from recurrent aspiration. We treated his aspiration pneumonia in the intensive care unit. Prior to his discharge, he received percutaneous dilatational tracheostomy (PDT) before he was transferred to a nursing hospital. Nine months later, he was readmitted owing to tracheoesophageal fistula (TEF). However, he was considered unsuitable for conservative intervention after a multidisciplinary team discussion. Esophageal stent insertion was impossible due to the high level of TEF in the esophagus. Additionally, the size of the TEF could not be covered by an endosponge and endoluminal vacuum therapy, and there was no tracheal stent that could cover his large trachea. The preceding percutaneous enteral gastrostomy (PEG) procedure was required for the primary closure operation of the esophagus; however, family’s consent could not be obtained. After 1month, the patient and his family changed their minds and agreed to the procedure and we attempted to perform PEG procedure. However, we could not proceed with PEG owing to stenosis in the inlet of the esophagus. Then, the patient deteriorated clinically and died due to pneumonia with septic shock.
Urinary Metabolites of Polycyclic Aromatic Hydrocarbons in Firefighters: A Systematic Review and Meta-Analysis

Firefighters are intermittently exposed to complex, mixed pollutants in random settings. Of those pollutants, PAHs (polycyclic aromatic hydrocarbons) are the most commonly studied and best understood. PAH exposure can occur via multiple routes; therefore, the levels of hydroxylated metabolites of PAHs in urine have been used as a biomonitoring tool for risk assessment. We performed a systematic review and meta-analysis of the literature to estimate the levels of urinary hydroxylated PAH (OHPAH) among firefighters, determine risk attributions, and, finally, evaluate the scope of preventive efforts and their utility as diagnostic tools. The meta-regression confirmed increases in OHPAH concentrations after fire activities by up to 1.71-times (p-values: <0.0001). Samples collected at a time point of 2–4 h after a fire suppression showed a consistent, statistically significant pattern as compared with baseline samples. The National Fire Protection Association (NFPA) standard 1582 Standard on Comprehensive Occupational Medical Program for Fire Departments lists various health examinations, including a urinalysis for occupational chemical exposure if indicated and medical screening for cancers and cardiovascular diseases. Biomonitoring is a valuable screening tool for assessing occupational exposure and the results of this meta-analysis support their inclusion in regular health screenings for firefighters.
MT-e&R: NMEA Protocol-Assisted High-Accuracy Navigation Algorithm Based on GNSS Error Estimation Using Multitask Learning

Accurate location data of ground vehicles is very important for various intelligent transportation applications. As one of the most commonly-used navigation solutions at present, the GNSS/INS integrated navigation still cannot meet the accuracy and stability command of current applications. This paper presents a National Marine Electronics Association (NMEA) protocol data-assisted high-accuracy navigation algorithm based on GNSS position error estimation using multi-task learning (MT-e&R), which can accurately estimate the GNSS position error and GNSS measurement noise covariance matrix with the assistance of protocol data and a multi-task learning model. Extensive experimental results on practical navigation data collected in various urban environments of Beijing demonstrate that our proposed approach can improve the performance of integrated navigation system. The positioning errors of integrated navigation equipped with single-frequency receiver are reduced by 36.17% and 39.58% for double-frequency receiver, which confirms the reasonable environmental adaptability of our proposed MT-e&R algorithm.
A Modified $Q-\dot{V}$ Droop Control for Accurate Reactive Power Sharing in Distributed Generation Microgrid

The droop-control technology, which can achieve an autonomous power sharing among distributed resources interface converters, provides the advantages of enhanced system reliability and reduced complexity. However, the reactive power sharing accuracy of the conventional <inline-formula><tex-math notation="LaTeX">$Q-V$</tex-math></inline-formula> droop method can be degraded due to its dependence on the line impedances. The <inline-formula><tex-math notation="LaTeX">$Q-\dot{V}$</tex-math></inline-formula> droop-control method was proposed to reduce the influence of line impedance. The reactive power sharing accuracy is improved but still affected by the <inline-formula><tex-math notation="LaTeX">$\dot{V}$</tex-math></inline-formula> restoration operation. In this paper, a modified <inline-formula><tex-math notation="LaTeX">$\dot{V}$</tex-math></inline-formula> restoration mechanism is proposed. Its influence on the power sharing is theoretically explained and analyzed. Both simulation and experiment results are presented to verify the proposed method.
A design of height - based terrain - following coordinates in the atmospheric numerical model: Theoretical analysis and idealized tests

Several kinds of typical height-based terrain-following coordinates, such as Gal-Chen&Somerville coordinate (hereafter ‘Gal.C.S’ coordinate), smoothed level vertical coordinate (hereafter SLEVE coordinate) and a new coordinate called as cosine-smoothed coordinate(hereafter ‘COS’ coordinate),were theoretically analyzed and intercompared with each other in the induced errors by calculations of the PGF(Pressure Gradient Force) for a rest atmosphere and the 2D-ADV(2-dimensional mass advection) tests. The results of calculation of the PGF showed that the errors of the calculation of the PGF induced by using a terrain following coordinates, were significantly decreased by using SLEVE1, SLEVE2 and COS coordinates in comparison to Gal.C. S coordinate.SLEVE2 and COS coordinates were relatively better in reduction of the errors of the PGF calculation. The decaying coefficient ‘b’ and its Jocabian derivative played a deterministic role in reduction of the errors. The similar remarks could be made for the tests of 2D-ADV calculation. The errors of the 2D-ADV calculation by using the COS coordinate were the smallest as those of the reference test in which there were no terrain. The COS coordinate was most advantageous to other coordinates in tests.
Comparative Efficacy of Tyrosine Kinase Inhibitors and Antibody–Drug Conjugates in HER2-Positive Metastatic Breast Cancer Patients with Brain Metastases: A Systematic Review and Network Meta-Analysis

Simple Summary Comparisons between the efficacy of tyrosine kinase inhibitors (TKIs) and antibody–drug conjugates (ADCs) in treating HER2-positive breast cancer brain metastasis (BCBM) patients have not previously been conducted. We performed a systematic review and Bayesian-based network meta-analysis to pool the estimates of progression-free survival, overall survival, and incidence of central nervous system (CNS) disease progression. The current study indicated that both T-DXd and T-DM1 presented better efficacy than TKIs regarding survival outcomes. Treatments containing neratinib or T-DM1 tended to rank the best in reducing the recurrent rate of CNS. Our study provides more evidence for the clinical decision making for patients with HER2-positive BCBM. More high-quality studies with standardized entry criteria and comparable CNS-related endpoints are warranted in the future. Abstract HER2-positive breast cancer brain metastasis (BCBM) is an important clinical problem. A systematic review and network meta-analysis were conducted to compare the efficacy of tyrosine kinase inhibitors (TKIs) and antibody–drug conjugates (ADCs), two categories of emerging agents in this field. We implemented a comprehensive literature search of PubMed, Embase, the Cochrane Library, ClinicalTrials.gov, and abstracts of oncology conferences. A network meta-analysis following Bayesian approaches was performed. Pooled hazard ratios (HRs) and odds ratios (ORs) with credible intervals (CrIs) were calculated to estimate progression-free survival (PFS), overall survival (OS), and the incidence of central nervous system (CNS) disease progression. Sixteen studies were included. Pairwise comparisons of PFS showed salient divergency between T-DXd and the physician’s choice of treatment (HR 0.17; 95% CrI 0.03–0.82) or afatinib (HR 0.14; 95% CrI 0.02–1.00). T-DXd and T-DM1 ranked first regarding PFS and OS, respectively, followed by TKI-containing regimens. The incidence of CNS disease progression was analyzed separately according to baseline BCBM status, among which neratinib-containing regimens were most likely to rank the best. In conclusion, ADCs including T-DXd and T-DM1 showed better efficacy than TKIs in the survival outcomes for HER2-positive BCBM patients. Treatments based on neratinib or T-DM1 revealed favorable results in reducing the recurrent rate of CNS.
Adaptace škály Sense of National Coherence

Cílem tohoto příspěvku je nahlédnout na Sense of Coherence v současných podmínkách pandemie Covid-19, jejíž zvládání je do určité míry národním tématem. Antonovského smysl pro koherenci (Sense of Coherence, SOC) je považován za jednu z hlavních koncepcí psychické odolnosti. Tento koncept sloužil jako inspirace pro vytvoření teorie národní koherence – Sense of National Coherence (SONC), kterou se rozumí způsob, jakým lidé nahlíží na svůj národ v kontextu srozumitelnosti, smysluplnosti a ovladatelnosti, což jsou tří dimenze konceptu Sense of Coherence. Původní verze dotazníku SONC byla vytvořená na izraelském vzorku, kde se vysoký SONC ukázal jako potenciální bariéra při smiřovaní palestinsko-izraelského konfliktu. Data byla sbíraná před a po válce v Gaze. Původní verzi z angličtiny jsme převedli do českého jazyka a administrovali v čase třetí vlny pandemie Covid-19 na vzorku 499 respondentů. Příspěvek na konferenci představí základní psychometrické charakteristiky dotazníku a srovnání s původní izraelskou verzí. SONC je sebeposuzovací nástroj, který se skládá z 8 položek a využívá sedmi bodovou Likertovou škálu, jejíž verbalizace je vždy přizpůsobená znění položky. Konfirmační faktorová analýza potvrdila jednodimenzionální strukturu modelu (α = 0.693, ω = 0.711). Průměrný skór SONC byl 3.6 (SD = 0.82). Korelační analýza poukazuje na statisticky významný vztah mezi hladinami SONC a rokem narození (r = -0.305, p < 0.01). Dotazník má v tuto chvíli využití především v komparativních studiích sledujících faktory duševního zdraví v kontextu pandemie Covid-19 v různých populacích.
The CruCES Project: A Consideration of Service Learning and Intercultural Sensitivity Among Heritage Learners

Though intercultural competence (ICC), community service learning (CSL), languages for specific purposes (LSP), and heritage learners (HLs) have respectively received increasing attention by language scholars within the previous twenty years, much remains to be done in the way of research concerning the relationship between them. The term HLs is used by academics in the United States in reference to students with previous knowledge of the target language and culture as a result of their cultural heritage and upbringing. This article considers the relevance of CSL to HL intercultural competence through a discussion of a 2015 community service learning project and study titled Creating Communities, Engaged Scholarship (CruCES). The project involved students and faculty from the University of Memphis, local non-profit organizations, and community members from the linguistically and ethnically diverse neighborhood of West Binghampton in Memphis, Tennessee (USA). CruCES sought to build capacity and foster community through the development of sustainable micro-economy projects centered on the arts. During the project, students also participated in a study on ISD. This paper considers the implications of the study’s findings for HLs specifically. In total, eight of the fifteen participating students self-identified as HLs. The CruCES project outcomes and study data for participating HLs are most telling with regards to their unique subjective positioning and language learning. Specifically, the study found that participating HLs demonstrated a higher degree of cultural sensitivity at the outset of the project and experienced an increase in self confidence and self-esteem related to the purposeful application of their language skills. A transformational experience for many of the HLs, the CruCES study findings hold significant implications for the development and integration of CSL in LSP courses and HL education.
On the internal physical conditions in dust probes: transport, heating and evaporation of fragmented dust particles

We study the conditions within, and dynamics of fragmented mesospheric dust particles inside, the Faraday-cup type dust probe MUDD using numerical simulations with a dedicated model. The transport of singly charged fragments from impacting NLC particles on the main grid in MUDD, have been calculated on the basis of supplementary models of the neutral gas conditions and electric field structure within the probe. The theoretical model includes the e↵ects of drag from neutral molecules, electric forces, as well as heating of – and evaporation from – the fragments. The model equations have been improved to be valid for nanoscale particles with a broad range of intrinsic properties, in the molecular flow regime. We find that the size range for unambiguous detection of pure MSP fragments of mass density ⇢s = 3000 kgm 3, is limited to fragments of radii between 1.5 nm and 2.1 nm with a 0.3 nm resolution; i.e. for the two existing detection modes of retarding potentials 10 V and 20 V. In the zero potential reference mode, fragments with radii smaller than 0.8 nm are stopped completely by neutrals. Fragments of pure ice content are found to evaporate rapidly, and will not contribute significantly to the measured currents at the bottom plate. Ice particles which contribute to the currents have to be larger than 3 nm, which renders the common assumption that ice particles smaller than 3 nm in radius must stick to probe surfaces [Tomsic, 2001; Havnes and Næsheim, 2007] redundant. From the study of alternative potential modes in MUDD, it is found that is is possible to improve the detectable size distribution of MUDD significantly by using lower retarding or accelerating potentials than the modes which already exist. Results from the E-field modeling suggest that the production of secondary charges have been somewhat underestimated due to very strong field anomalies near the edges of the probe. We also find plausibly large uncertainty factors from the investigations of initial fragment velocity, dynamic shape and heating of fragments during collisions with G2.
Multi-class Fault Diagnosis in Gears Using Machine Learning Algorithms Based on Time Domain Data

The support vector machine, as a powerful machine learning algorithm, is recognized to have good generalization ability in its application to multi class machine fault classification problems. In this paper, an application of the SVM in the multi class gear fault diagnosis has been performed based on the gear vibration data in time domain. From time domain data the statistical features are extracted and fed to the SVM for the training/testing. When the training and testing data are at the same running speed, it is found that the SVM classifier has excellent multiclass classification accuracy. Though, this approach relies on the availability of both the training and testing data at that particular speed of the machine operation; it is expected that features of time domain data would change with operating speeds. Moreover, the training data may not always be available continuously at all operating speeds of gears, especially for variable drive systems. Thus, a novel technique of interpolation/extrapolation has been proposed in the present work that helps the SVM classifier to carryout multi class gear fault diagnosis with appreciable accuracy even in the absence of the training data at a given running speed. It also investigates the speed bandwidth of the training data for which interpolation/extrapolation predictions are reasonably good. The similar analysis is also extended to artificial neural networks (ANN) as the classifier and predictions are noted, and compared with the SVM.