Miracle-dz/UniFAR-FTUs huggingface dataset:
Post-Stall Navigation with Fixed-Wing UAVs using Onboard Vision

Recent research has enabled fixed-wing unmanned aerial vehicles (UAVs) to maneuver in constrained spaces through the use of direct nonlinear model predictive control (NMPC) [1]. However, this approach has been limited to a priori known maps and ground truth state measurements. In this paper, we present a direct NMPC approach that leverages NanoMap [2], a light-weight point cloud mapping framework, to generate collision-free trajectories using onboard stereo vision. We first explore our approach in simulation and demonstrate that our algorithm is sufficient to enable vision-based navigation in urban environments. We then demonstrate our approach in hardware using a 42-inch fixed-wing UAV and show that our motion planning algorithm is capable of navigating around a building using a minimalistic set of goal-points. We also show that point cloud history is important for navigating in these types of constrained environments.
Classifying Autism from Crowdsourced Semi-Structured Speech Recordings: A Machine Learning Approach

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder which results in altered behavior, social development, and communication patterns. In past years, autism prevalence has tripled, with 1 in 54 children now affected. Given that traditional diagnosis is a lengthy, labor-intensive process which requires the work of trained physicians, significant attention has been given to developing systems that automatically diagnose and screen for autism. Objective: Prosody abnormalities are among the most clear signs of autism, with affected children displaying speech idiosyncrasies (including echolalia, monotonous intonation, atypical pitch, and irregular linguistic stress patterns). In this work, we present a suite of machine learning approaches to detect autism in self-recorded speech audio captured from autistic and neurotypical (NT) children in home environments. Methods: We consider three methods to detect autism in child speech: first, Random Forests trained on extracted audio features (including Mel-frequency cepstral coefficients); second, convolutional neural networks (CNNs) trained on spectrograms; and third, fine-tuned wav2vec 2.0—a state-of-the-art Transformer-based speech recognition model. We train our classifiers on our novel dataset of cellphone-recorded child speech audio curated from Stanford’s Guess What? mobile game, an app designed to crowdsource videos of autistic and neurotypical children in a natural home environment. Results: The Random Forest classifier achieves 70% accuracy, the fine-tuned wav2vec 2.0 model achieves 77% accuracy, and the CNN achieves 79% accuracy when classifying children’s audio as either ASD or NT. We use five-fold cross-validation to evaluate model performance. Conclusions: Our models were able to predict autism status when training on a varied selection of home audio clips with inconsistent recording qualities, which may be more generalizable to real world conditions. The results demonstrate that machine learning methods offer promise in detecting autism automatically from speech without specialized equipment.
Deriving discriminative classifiers from generative models

—We deal with Bayesian generative and discriminative classifiers. Given a model distribution 𝑝(𝑥,𝑦) , with the observation 𝑦 and the target 𝑥 , one computes generative classifiers by firstly considering 𝑝(𝑥,𝑦) and then using the Bayes rule to calculate 𝑝(𝑥|𝑦) . A discriminative model is directly given by 𝑝(𝑥|𝑦) , which is used to compute discriminative classifiers. However, recent works showed that the Bayesian Maximum Posterior classifier defined from the Naive Bayes (NB) or Hidden Markov Chain (HMC), both generative models, can also match the discriminative classifier definition. Thus, there are situations in which dividing classifiers into “generative” and “discriminative” is somewhat misleading. Indeed, such a distinction is rather related to the way of computing classifiers, not to the classifiers themselves. We present a general theoretical result specifying how a generative classifier induced from a generative model can also be computed in a discriminative way from the same model. Examples of NB and HMC are found again as particular cases, and we apply the general result to two original extensions of NB, and two extensions of HMC, one of which being original. Finally, we shortly illustrate the interest of the new discriminative way of computing classifiers in the Natural Language Processing (NLP) framework.
FLiMS: A Fast Lightweight 2-Way Merger for Sorting

In this paper, we present FLiMS, a highly-efficient and simple parallel algorithm for merging two sorted lists residing in banked and/or wide memory. On FPGAs, its implementation uses fewer hardware resources than the state-of-the-art alternatives, due to the reduced number of comparators and elimination of redundant logic found on prior attempts. In combination with the distributed nature of the selector stage, a higher performance is achieved for the same amount of parallelism or higher. This is useful in many applications such as in parallel merge trees to achieve high-throughput sorting, where the resource utilisation of the merger is critical for building large trees and internalising the workload for fast computation. Also presented are efficient variations of FLiMS for optimizing throughput for skewed datasets, achieving stable sorting or using fewer dequeue signals. Additionally, FLiMS is shown to perform well as conventional software on modern CPUs supporting single-instruction multiple-data (SIMD) instructions, surpassing the performance of some standard libraries for sorting.
Views of Schizophrenia Among Future Healthcare Professionals: Differences in Relation to Diagnostic Labelling, Causal Explanations, and Type of Academic Degree Program

Objective Stereotyped beliefs about schizophrenia are well-established in the society and relatively common among healthcare professionals and students. The aim of this study was to investigate the opinions about the causes, treatment, and outcome of schizophrenia among healthcare students. Method Undergraduate nursing and psychology students completed selected items of the Opinion on Mental Illness Questionnaire after reading a clinical vignette of undiagnosed schizophrenia. Results Students who labelled the description as schizophrenia were more pessimistic regarding full recovery from the disorder. Those who acknowledged greater relevance to biogenetic risk factors were more convinced of the efficacy of medications. Respondents’ opinions on the efficacy of psychological interventions were more positive among psychology students than among nursing students. Conclusions The study confirmed the associations of schizophrenia labelling with prognostic pessimism and beliefs about the efficacy of pharmacological treatment among future healthcare professionals. Students’ opinions were less influenced by differences between academic degree programs. Information about current recovery rate and comprehensive care for schizophrenia may support future healthcare professionals in the relationship and the clinical management of PWS.
Big-Data Security

Big data implies performing computation and database operations for massive amounts of data, remotely from the data owner‟s enterprise. Since a key value proposition of big data is access to data from multiple and diverse domains, security and privacy will play a very important role in big data research and technology. The limitations of standard IT security practices are well-known, making the ability of attackers to use software subversion to insert malicious software into applications and operating systems a serious and growing threat whose adverse impact is intensified by big data. So, a big question is what security and privacy technology is adequate for controlled assured sharing for efficient direct access to big data. Making effective use of big data requires access from any domain to data in that domain, or any other domain it is authorized to access. Several decades of trusted systems developments have produced a rich set of proven concepts for verifiable protection to substantially cope with determined adversaries, but this technology has largely been marginalized as “overkill” and vendors do not widely offer it.
The effect of per os colchicine administration in combination with fenofibrate and N-acetylcysteine on triglyceride levels and the development of atherosclerotic lesions in cholesterol-fed rabbits.

OBJECTIVE Atherosclerosis is a chronic inflammatory disease promoted by pro-inflammatory cytokines produced by NOD-, LRR- and pyrin domain-containing protein 3 (NLRP 3) inflammasome. Colchicine is an anti-inflammatory agent that inhibits inflammasome's action and stabilizes atherosclerotic lesions. N-acetylcysteine (NAC) reduces low-density lipoprotein (LDL) oxidation, metalloproteinase levels, and foam cell count and volume. Fenofibrate also has antioxidant, anti-inflammatory, and anticoagulant properties while also having a beneficial effect on the vasomotor function of the endothelium. The purpose of this study is to investigate the effect of per os colchicine administration in combination with fenofibrate and NAC on triglyceride levels and the development of atherosclerotic lesions in cholesterol-fed rabbits. MATERIALS AND METHODS Twenty-eight male, 2 months old New Zealand White rabbits were separated into four groups and were fed with different types of diet for 7 weeks: standard, cholesterol 1% w/w, cholesterol 1% w/w plus colchicine 2 mg/kg body weight plus 250 mg/kg body weight/day fenofibrate, and cholesterol 1% w/w plus colchicine 2 mg/kg body weight plus 15 mg/kg body weight/day NAC. Blood samples were drawn from all animals. Lipid profiles were assessed, and interleukin 6 (IL-6) measurements were performed using an enzyme-linked immunosorbent assay (ELISA) kit. Histologic examination was performed on aorta specimens stained with eosin and hematoxylin. Aortic intimal thickness was evaluated using image analysis. RESULTS Colchicine administration in combination with fenofibrate or NAC statistically significantly reduced the extent of atherosclerotic lesions in aortic preparations. Co-administration of colchicine with NAC has a stronger anti-atherogenic effect than the colchicine plus fenofibrate regimen. Triglerycide levels were decreased in the colchicine plus fenofibrate group and the colchicine plus NAC group at the end of the experiment (p < 0.05), whereas the Cholesterol group had increased levels. A favorable significant lower concentration of IL-6 was detected in the colchicine plus NAC group vs. the other groups. CONCLUSIONS In an experimental rabbit model, it appears that colchicine statistically significantly reduces the development of atherosclerosis of the aorta, especially in combination with NAC. Colchicine, as an NLRP3 inflammasome inhibitor, and NAC, as an agent that directly targets IL-6 signaling, can reduce the inflammatory risk. Fenofibrate enhances the attenuating role of colchicine on triglyceride levels. Clinical studies should investigate whether similar effects can be observed in humans.
Using Normative Rhetorical Theory to Identify Dilemmas and Responses in Internal Medicine Patient-Provider Communication

ABSTRACT Drawing on normative rhetorical theory (NRT), we examined communication dilemmas that internal medicine residents (IMRs) experience when interacting with patients and responses they adopt to manage these dilemmas. We conducted semi-structured, intensive interviews with 15 IMRs and analyzed the data using the phronetic iterative approach. Findings suggested that IMRs experienced two interpersonal dilemmas: (a) asserting expertise while respecting patients and (b) discussing patient behaviors without indicating deviance. The two dilemmas were more salient for international IMRs who were less familiar with the local culture and embraced a different perspective of the IMR-patient relationship. The two interpersonal dilemmas were connected to a supra-level dilemma of practicing tasks required by evidence-based medicine while being patient-centered. IMRs reported engaging in an interpretive lens to view patients as “people” and communicative responses to manage the dilemmas. By applying NRT to a novel context, our findings demonstrate the impact of macro-level paradigms on IMRs’ conflicting purposes in medical encounters and offer practical implications for communication interventions for IMRs.
Covert contrasts and categorical perception: a comparison of two measurement tools

ABSTRACT This study considers adults’ perception of subtle differences in the error productions of /r/ and /l/ in young children. Given that these two phonemes share a common substitution [w], the potential covert contrast between these three sounds was investigated. The utility of two perceptual rating scales was compared: a linear visual analogue scale (VAS) and a triangular scale that considered the possibility of covert contrast among /r,l,w/. Adult listeners rated speech productions from children with cochlear implants (CIs) and speech age-matched children with normal hearing (NH) as they produced VCV or CV productions with /r,l,w/ in syllable-initial position. Mahalanobis distances of the listener ratings for each stimulus on each rating scale were calculated for analysis. Ultimately, there was no difference between the ratings of the two speaker populations. However, there was a significant difference in the amount of variability captured with each scale. The triangular scale reliably captured more variability in the productions than the linear VAS. The significant effect of scale type on the spread of listeners’ responses provides support for the claim that the type of rating system used can capture different aspects of a listener’s perceptions, thereby suggesting that the type of rating system used in a study may significantly influence that study’s findings.
Spiritual aspects of the family caregivers' experiences when caring for a community-dwelling adult with severe mental illness: a systematic review of qualitative evidence.

INTRODUCTION Deinstitutionalization of individuals with severe mental illness transferred the responsibility of care to the relatives who need to adapt their personal life. Caregivers often develop coping strategies which involve the relationship with oneself, others, or the transcendent/God or nature and may include religious/spiritual practices. QUESTION/AIM This review aims to identify the spiritual aspects of the family caregivers' experiences when caring for a community-dwelling adult with severe mental illness. METHOD The review was conducted in accordance with the Joanna Briggs Institute methodology for systematic reviews of qualitative evidence. Search was conducted in March 2019, updated in August 2020, limited to English, Spanish and Portuguese. RESULTS A total of 26 studies were included. Two synthesized findings emerged: spiritual coping strategies are used by family caregivers; spiritual needs are expressed by family caregivers. The findings are based on the experiences of 467 caregivers, from 14 countries. DISCUSSION In stressful times, family caregivers question the meaning in life and acknowledge hopelessness. To cope, caregivers mention a turn to the sacred and the use of spiritual/religious practices. IMPLICATIONS FOR PRACTICE Spirituality should be considered according to caregivers' individual beliefs and needs, as may represent important resources for the sense of meaning and overall wellbeing.
Fabrication of Host-Guest Complexes between Adamantane-Functionalized 1,3,4-Oxadiazoles and β-Cyclodextrin with Improved Control Efficiency against Intractable Plant Bacterial Diseases.

Supramolecular chemistry provides huge potentials and opportunities in agricultural pest management. In an attempt to develop highly bioactive, eco-friendly, and biocompatible supramolecular complexes for managing intractable plant bacterial diseases, herein, a type of interesting adamantane-functionalized 1,3,4-oxadiazole was rationally prepared to facilitate the formation of supramolecular complexes via β-cyclodextrin-adamantane host-guest interactions. Initial antibacterial screening revealed that most of these adamantane-decorated 1,3,4-oxadiazoles were obviously bioactive against three typically destructive phytopathogens. The lowest EC50 values could reach 0.936 (III18), 0.889 (III18), and 2.10 (III19) μg/mL against the corresponding Xanthomonas oryzae pv. oryzae (Xoo), Xanthomonas axonopodis pv. citri (Xac), and Pseudomonas syringae pv. actinidiae (Psa). Next, the representative supramolecular binary complex III18@β-CD (binding mode 1:1) was successfully fabricated and characterized by 1H nuclear magnetic resonance (NMR), isothermal titration calorimetry (ITC), high-resolution mass spectrometry (HRMS), dynamic light scattering (DLS), and transmission electron microscopy (TEM). Eventually, correlative water solubility and foliar surface wettability were significantly improved after the formation of host-guest assemblies. In vivo antibacterial evaluation found that the achieved supramolecular complex could distinctly alleviate the disease symptoms and promote the control efficiencies against rice bacterial blight (from 34.6-35.7% (III18) to 40.3-43.6% (III18@β-CD)) and kiwi canker diseases (from 41.0-42.3% (III18) to 53.9-68.0% (III18@β-CD)) at 200 μg/mL (active ingredient). The current study can provide a feasible platform and insight for constructing biocompatible supramolecular assemblies for managing destructive bacterial infections in agriculture.
Predicting sequence and structural features of effective piRNA target binding sites

Piwi‐interacting RNA (piRNA) targets are usually identified through base pairing between the piRNA seed region and complementary bases on the target mRNAs, which often results in false predictions. Cross‐linking immunoprecipitation (CLIP) study emerges as a promising method that enables accurate identification of PIWI‐clade‐based targets containing RNA‐binding sites. In the present study, we have analyzed the piRNA‐target CLIP‐Seq datasets to uncover the additional characteristic features of piRNA targets. We studied important sequence and structural features using IP+ and IP− set targets that might enhance the accuracy of target site predictions. Analysis has revealed substantial enrichment of AU in target sites as well as in and around the 30 nts upstream and downstream of target sites in IP+ set relative to IP− set that might be contributing to lowering the minimal folding energy of target sites of IP+ set that might be easing the base pairing between piRNA and their targets. We have also found a lower MFE threshold (en) and higher miRanda score for piRNA targets. Interestingly, we have found that majority of the target sites are residing within 3′UTR, suggesting 3′UTR as a preferential target site like that of miRNA targets. Thus, we hypothesize that our findings on additional key features of piRNA target sites might be valuable in identifying the potential targets of piRNA accurately, which will aid in decrypting their functional importance.
Daily variation in performance measures related to anaerobic power and capacity: A systematic review

ABSTRACT Numerous functional measures related to anaerobic performance display daily variation. The diversity of tests and protocols used to assess anaerobic performance related to diurnal effects and the lack of a standardized approach have hindered agreement in the literature. Therefore, the aim of the present study was to investigate and systematically review the evidence relating to time-of-day differences in anaerobic performance measures. The entire content of PubMed (MEDLINE), Scopus, SPORTDiscus® (via EBSCOhost) and Web of Science and multiple electronic libraries were searched. Only experimental research studies conducted in male adult participants aged ≥ 18 yrs before May 2021 were included. Studies assessing tests related to anaerobic capacity or anaerobic power between a minimum of two time-points during the day (morning vs evening) were deemed eligible. The primary search revealed that a total of 55 out of 145 articles were considered eligible and subsequently included. Thirty-nine studies assessed anaerobic power and twenty-five anaerobic capacity using different modes of exercise and test protocols. Forty-eight studies found several of their performance variables to display time-of-day effects, with higher values in the evening than the morning, while seven studies did not find any time-of-day significance in any variables which were assessed. The magnitude of difference is dependent on the modality and the exercise protocol used. Performance measures for anaerobic power found jump tests displayed 2.7 to 12.3% differences, force velocity tests ~8% differences, sprint tests 2.7 to 11.3% differences and 5-m multiple shuttle run tests 3.7 to 13.1% differences in favour of the evening. Performance measures for anaerobic capacity found Wingate test to display 1.8 to 11.7% differences and repeated sprint tests to display 3.4 to 10.2% differences. The only test not to display time-of-day differences was the running based anaerobic sprint test (RAST). Time-of-day variations in anaerobic performance has previously been partially explained by higher core-body and/or muscle temperature and better muscle contractile properties in the afternoon, although recent findings suggest that differences in methodology, motivation/arousal, habitual training times and chronotypes could provide additional explanations. There is a clear demand for a rigorous, standardised approach to be adopted by future investigations which control factors that specifically relate to investigations of time-of-day.