Miracle-dz/UniFAR-FTUs huggingface dataset:
Setting up new standards in aviation industry with the help of artificial intelligent – machine learning application

In these times, dominated by innovation, technology is an important asset in optimizing maintenance, aircraft operations and even the investigation process of aviation accidents, with unprecedented results so far. All the information related to an aircraft, generated over time, can be included in a database, in order to be analyzed for better technical insights. The same approach can be applied in analyzing evidence and reports generated after an aircraft accident occurred. Aircraft investigation involves tones of hard-working hours and evidence analysis. This research aims to identify a new tool to improve the investigation process of aircraft incidents caused by human factors errors. Using artificial intelligence to process the resulted evidence during the aircraft accidents investigation, will shed light on the root cause of the incident much faster. Accelerating an investigation means huge benefits for all parties involved. In this sense, a proof-of-concept software has been developed to emphasize the power of artificial intelligent in the aircraft accidents investigation. Using machine learning algorithms, a program was trained with data, to develop an application capable of automatically determining the root cause of an accident based on witness statements. All data was derived from the Aviation Safety Reporting System database from the U.S, which was queried for incidents, occurred between 2000 and 2020. This application is not only about automating a stage in an aircraft accident investigation, is rather about setting up new standards in aviation industry with the help of artificial intelligence.
Interstellar Scintillation of PSR J2048−1616

We report on the interstellar scintillation from pulsar J2048−1616 for the first time at 732, 1369, and 3100 MHz observed with the Parkes 64 m radio telescope. Dynamic spectra are obtained and diffractive parameters are derived from two-dimensional autocorrelation analyses. The frequency dependencies of the observed diffractive scintillation timescale and decorrelation bandwidth indicate that the electron density fluctuations in the interstellar medium (ISM) do not follow the Kolmogorov spectrum. The secondary spectra are calculated by forming the Fourier power spectra of the corresponding dynamic spectra. Prominent parabolic arcs are revealed in the secondary spectra at three frequencies, which indicate that they originated from scattering by a thin screen. The scattering screen is approximately located centrally between the pulsar and Earth assuming that the ISM is stationary.
Fault diagnosis technology based on hybrid structure tree

Based on structure tree and fault tree of complex product, the concept of hybrid structure tree and the corresponding intelligent fault-diagnosis method were proposed. Some basic contents, which shared similar characteristics, were constructed as diagnosis kernel, and these contents were differentiated from concrete diagnosis objectives so as to make it suitable for different objects. Aimed at knowledge management in intelligent diagnosis, a set of coding rules was proposed to implement effective management and utilization of diagnosis knowledge by making use of existing advanced coding management methods. Finally, the corresponding inference algorithms of fault diagnosis were developed. All above-mentioned methods have been applied in research and development of the fault-diagnosis system for automatic door of high-speed train.
Does long-term indoor exposure to thermoneutral environments impair human body thermal acclimatization abilities?

The goal of this short communication is to analyze a published discussion that states that longterm residing at a thermoneutral indoor temperature condition hinders human thermal acclimation capacities. According to current research, human thermal acclimation and acclimatization capacities can be easily gained through repeated heat and cold exposures mixed with physical activity over a period of days (often 3–21 days). Furthermore, heat and cold adaptations are not permanent, and heat acclimation would progressively fade away if frequent heat exposures (associated with physical work/exercise) were discontinued. People who have been heat acclimatized for a long period and live in tropical places may progressively lose their physiological and perceptual benefits when they shift to temperate zones. On the other hand, the decay of cold acclimation and cold acclimatization has not been well examined, demanding future research on this area. To summarize, there is no evidence to support the claim that extended exposure to thermoneutral conditions impairs human acclimatization abilities.
Unveiling and Conceptual-Logical Modeling of Phase Sequences in Data Engineering

The acceptance of the concept, according to which object types of the conceptual level are differed by functional heterogeneity, leads to the realization of the fact that there are no entity types that wouldn’t exchange their instances and wouldn’t form numerous sequences in their domains-phase sequences. Formally, such sequences are the directed graphs, in nodes of which are placed entity types, and arcs set sources and receivers of moving instances. The article aims at developing the method for revealing phase sequences at conceptual schemas by means of using a number of types of adjunct categories and subsequent representation of found sequences in databases logical structures. Along with simplest sequences with disjoint types the paper concerns the issuers of formalization and logical modeling of sequences, whose items can simultaneously be present in several types.
[Tool] Designing Replicable Networking Experiments With Triscale

When designing their performance evaluations, networking researchers often encounter questions such as: How long should a run be? How many runs to perform? How to account for the variability across multiple runs? What statistical methods should be used to analyze the data? Despite their best intentions, researchers often answer these questions differently, thus impairing the replicability of their evaluations and the conﬁdence in their results. In this paper, we propose a concrete methodology for the design and analysis of performance evaluations. Our approach hierarchically partitions the performance evaluation into three timescales, following the principle of separation of concerns. The idea is to understand, for each timescale, the temporal characteristics of variability sources, and then to apply rigorous statistical methods to derive performance results with quantiﬁable conﬁdence in spite of the inherent variability. We implement this methodology in a software framework called TriScale . For each performance metric, TriScale computes a variability score that estimates, with a given conﬁdence, how similar the results would be if the evaluation were replicated; in other words, TriScale quantiﬁes the replicability of evaluations. We showcase the practicality and usefulness of TriScale on four different case studies demonstrating that TriScale helps to generalize and strengthen published results. Improving the standards of replicability in networking is a complex challenge. This paper is an important contribution to this endeavor; it provides networking researchers with a rational and concrete experimental methodology rooted in sound statistical foundations. The ﬁrst of its kind.
Mobile App Malware Detection Using Deep Learning

: Latest smartphone stages built on new operating systems, such as iOS, Android, or Windows Phone, have been a vast achievement in recent years and built-up various new opportunities. Unfortunately, 2011 also indicated us that the new machineries and the privacy-related documents on smartphones are also gradually fascinating for attackers. In this project mobile app malware detection, which contains a Recurrent Neural Network (RNN) classification algorithm is implemented. The malware detection data set is analyzed that contains 35 features to study the viability of classification algorithm and malware detection is made by using LSTM method to achieve more accuracy. The unique malware dataset patterns obtained by this method is converted to their binary form and it is applied to the deep learning algorithm to classify the malware and benign files. In this method the malware can be predicted with 98.89% accuracy using Long Short-Term Memory (LSTM) which outperforms Malware detection-based methods.
Parameter-free HE-friendly Logistic Regression

Privacy in machine learning has been widely recognized as an essential ethical and legal issue, because the data used for machine learning may contain sensitive information. Homomorphic encryption has recently attracted attention as a key solution to preserve privacy in machine learning applications. However, current approaches on the training of encrypted machine learning have relied heavily on hyperparameter selection, which should be avoided owing to the extreme difﬁculty of conducting validation on encrypted data. In this study, we propose an effective privacy-preserving logistic regression method that is free from the approximation of the sigmoid function and hyperparameter selection. In our framework, a logistic regression model can be transformed into the corresponding ridge regression for the logit function. We provide a theoretical background for our framework by suggesting a new generalization error bound on the encrypted data. Experiments on various real-world data show that our framework achieves better classiﬁcation results while reducing latency by ∼ 68% , compared to the previous models.
Airborne route and bad use of ventilation systems as non-negligible factors in SARS-CoV-2 transmission

The world is facing a pandemic of unseen proportions caused by a corona virus named SARS-CoV-2 with unprecedent worldwide measures being taken to tackle its contagion. Person-to-person transmission is accepted but WHO only considers aerosol transmission when procedures or support treatments that produce aerosol are performed. Transmission mechanisms are not fully understood and there is evidence for an airborne route to be considered, as the virus remains viable in aerosols for at least 3 h and that mask usage was the best intervention to prevent infection. Heating, Ventilation and Air Conditioning Systems (HVAC) are used as a primary infection disease control measure. However, if not correctly used, they may contribute to the transmission/spreading of airborne diseases as proposed in the past for SARS. The authors believe that airborne transmission is possible and that HVAC systems when not adequately used may contribute to the transmission of the virus, as suggested by descriptions from Japan, Germany, and the Diamond Princess Cruise Ship. Previous SARS outbreaks reported at Amoy Gardens, Emergency Rooms and Hotels, also suggested an airborne transmission. Further studies are warranted to confirm our hypotheses but the assumption of such way of transmission would cause a major shift in measures recommended to prevent infection such as the disseminated use of masks and structural changes to hospital and other facilities with HVAC systems.
First Experience Using the Sheathless Hyperion Guiding Catheter System Designed for Direct Insertion

Background Use of sheathless guiding catheters for transradial PCI has the potential to reduce radial trauma and allow use of larger catheters to facilitate complex PCI. The new sheathless Hyperion guide catheter (SHGC) system allows direct insertion of the SHGC using a 20G needle or IV cannula, a 0.025″ Silverway wire, and a dilator. We report the first clinical experience. Methods We prospectively evaluated outcomes in consecutive patients undergoing PCI using radial access and the SHGC catheter at our institution between June 2020 and June 2021. There were no exclusion criteria. Results The study included 120 patients, mean age 67 ± 12.6 years, 79.2% male. Insertion of a SHGC was attempted in 128 radial arteries and was successful in all cases. The SHGC was inserted directly in 74 (57.8%), following initial sheath removal in 24 (20.5%) and through the initial sheath in 30 (26.2%). Coronary artery engagement with a SHGC was successful in 126 (98.4%). A total of 150 lesions were treated, the majority being complex: 16.1% chronic total occlusions, 37.1% calcified, 30.6% bifurcation, and 43.5% long lesions. Angiographic success was achieved in 149 (99.2%) lesions. Periprocedural myocardial infarction occurred in 5 (4.2%) patients. There was no in-hospital urgent revascularisation or death and no major bleeding or vascular complications. Occlusion occurred in 2 (1.6%) radial arteries. Conclusion This first clinical experience with the SHGC demonstrates that direct insertion is safe and effective and that the use of the SHGC allows complex interventions to be undertaken transradially with a high success rate.
SPiNCAR: A systematic model to evaluate and guide actions for tackling AMR

Background Italy records very alarming levels antimicrobial resistance (AMR), so a National Action Plan on Antimicrobial resistance (PNCAR) was developed, adopting the AMR European Union’s recommendations based on the results of the ECDC site visit of January 2017. For achieving PNCAR objectives, it is necessary to support and harmonize the implementation of recommendations in all the different healthcare levels (regional authorities and local trusts), so the SPiNCAR project was launched to create a tool for reaching this goal. Methods We developed a framework based on a scientific literature and national and international guidelines. Firstly, we identified the major intervention areas for tackling AMR, then, for each area, we built a set of standards, both for regional authorities than for local trusts. Every standard is composed by a set of essential and additional criteria, which refer to a minimum or supplemental performance level respectively. The contents were firstly discussed by the project’s team during face-to-face kick-off meetings, then confirmed with Delphi methodology and finally validated through a pilot study. Results The final framework consists of seven different areas that reflect the PNCAR structure: Governance, Surveillance and Monitoring, Appropriate Use of antimicrobials, Healthcare-associated Infections (HAIs) control and prevention, Education and Training, Alliance among Stakeholders, Implementation. The total number of standards for the regional framework was 34 with 264 criteria and for the local version 36 criteria with 279 standards. Conclusion The ongoing use of this tool, developed on international evidences and recommendations that were tailored on the Italian specific context, allows monitoring the improvement achieved over time and plan the next steps.
Plant migration under long-lasting hyperaridity - phylogenomics unravels recent biogeographic history in one of the oldest deserts on Earth.

The post-Miocene climatic histories of arid environments have been identified as key drivers of dispersal and diversification. Here, we investigate how climatic history correlates with the historical biogeography of the Atacama Desert genus Cristaria (Malvaceae). We analyze phylogenetic relationships and historical biogeography by using next-generation sequencing (NGS), molecular clock dating, Dispersal Extinction Cladogenesis and Bayesian sampling approaches. We employ a novel way to identify biogeographically meaningful regions as well as a rarely utilized program permitting the use of dozens of ancestral areas. Partial incongruence between the established taxonomy and our phylogenetic data, argue for a complex historical biogeography with repeated introgression and incomplete lineage sorting. Cristaria originated in the central southern part of the Atacama Desert, from there the genus colonized other areas from the late Miocene onwards. The more recently diverged lineages appear to have colonized different habitats in the Atacama Desert during pluvial phases of the Pliocene and early Pleistocene. We show that NGS combined with near-comprehensive sampling can provide an unprecedented degree of phylogenetic resolution and help to correlate the historical biogeography of plant communities with cycles of arid and pluvial phases.
A neurobiological perspective on social influence: Serotonin and social adaptation

Humans are inherently social beings. Being suggestible to each other's expectations enables pro‐social skills that are crucial for social learning and adaptation. Despite their high relevance for psychiatry, the neurobiological mechanisms underlying social adaptation are still not well understood. This review, therefore, provides a conceptual framework covering various distinct mechanisms underlying social adaptation and explores the neuropharmacology — in particular the role of the serotonin (5‐HT) system — in modulating these mechanisms. This article reviews empirical results on social influence processing and reconciles them with recent findings from psychedelic research on social processing to elucidate neurobiological and neuropharmacological underpinnings of social adaptation. Various computational, neurobiological, and neurochemical processes are involved in distinct mechanisms underlying social adaptation such as the multisensory process of social information integration that is crucial for the forming of self‐representation and representations of social norms. This is again associated with self‐ and other‐perception during social interactions as well as value‐based decision‐making that guides our behavior in daily interactions. We highlight the critical role of 5‐HT in these processes and suggest that 5‐HT can facilitate social learning and may represent an important target for treating psychiatric disorders characterized by impairments in social functioning. This framework also has important implications for psychedelic‐assisted therapy as well as for the development of novel treatment approaches and future research directions.
Probiotics combined with zinc and selenium preparation in the treatment of child rotavirus enteritis.

OBJECTIVE To investigate clinical effect of probiotics combined with zinc and selenium preparation in the treatment of child rotavirus enteritis. METHODS In this retrospective study, the patients were divided into two groups based on treatment method. The control group (n=42) received probiotic therapy, while the experimental group (n=43) received probiotics combined with zinc and selenium preparation. Clinical efficacy, stool frequency and incidence of adverse reactions after treatment were compared to assess the clinical effect. RESULTS The clinical effect was improved after intervention (P<0.05), and the total effective rate of two groups was 88.4% (38/43), 50% (21/42), respectively. Time to symptom disappearance was significantly decreased in the experimental group as compared to the control group. The myocardial zymogram indices (CK, CK-MB and AST) were decreased after treatment, and the levels in the experimental group were significantly lower than in the control group (P<0.05). Moreover, we observed that the levels of inflammatory factors (IL-6, IL-8 and hsCRP) in the experimental group were significantly lower than those of the control group after intervention (all P<0.05). CONCLUSION Probiotics combined with zinc and selenium preparation can not only significantly improve the clinical effect, but also shorten the course of disease.
Pterostilbene pre-treatment reduces LPS-induced acute lung injury through activating NR4A1

Abstract Context Pterostilbene (PTE), a common polyphenol compound, exerts an anti-inflammatory effect in many diseases, including acute lung injury (ALI). Objective This study explores the potential mechanism of PTE pre-treatment against lipopolysaccharide (LPS)-induced ALI. Materials and methods Sixty Sprague-Dawley rats were divided into control, ALI, 10 mg/kg PTE + LPS, 20 mg/kg PTE + LPS, and 40 mg/kg PTE + LPS groups. At 24 h before LPS instillation, PTE was administered orally. At 2 h before LPS instillation, PTE was again administered orally. After 24 h of LPS treatment, the rats were euthanized. The levels of inflammatory cells and inflammatory factors in the bronchoalveolar lavage fluid (BALF), the expression of nuclear receptor subfamily 4 group A member 1 (NR4A1), and the nuclear factor (NF)-κB pathway-related protein levels were detected. NR4A1 agonist was used to further investigate the mechanism of PTE pre-treatment. Results After PTE pre-treatment, the LPS induced inflammation was controlled and the survival rate was increased to 100% from 70% after LPS treatment 24 h. For lung injury score, it decreased to 1.5 from 3.5 after treating 40 mg/kg PTE. Compared with the control group, the expression of NR4A1 in the ALI group was decreased by 20–40%. However, the 40 mg/kg PTE pre-treatment increased the NR4A1 expression by 20–40% in the lung tissue. The results obtained with pre-treatment NR4A1 agonist were similar to those obtained by pre-treatment 40 mg/kg PTE. Conclusions PTE pre-treatment might represent an appropriate therapeutic target and strategy for preventing ALI induced by LPS.
Depression in nursing home residents and its correlation with meaning of family involvement and depression of family

ABSTRACT Objectives: This study aimed to investigate the relationship between depression in older nursing home residents and family caregivers’ (FCGs) depressive status and reasons for involvement with residents. Design: This study employed a cross-sectional design. Setting: Eight nursing homes in northern Taiwan. Participants: A total of 139 older resident–FCG pairs were recruited. Measurements: Depression was measured with the Geriatric Depression Scale-Short Form for nursing home residents and the Center for Epidemiologic Studies Depression Scale-Short Form for family members. Depression and demographic data were collected with face-to-face interviews. The meaning ascribed to caregivers’ nursing home visits was calibrated using the Family Meaning of Nursing-Home Visits scale. Multiple logistic regression was used to understand the factors related to residents’ depressive symptoms. Results: Depressive symptoms were present in 58.3% of the nursing home residents (n = 81). Depressive status of family members (Chi-square = 1.46, p = 0.23) or family’s visiting frequency (Chi-square = 1.64, p = 0.44) did not differ between residents with or without depressive symptoms. Factors associated with an increased risk of residents having depressive symptoms were age, self-perceived health status, and having a caregiver motivated to visit to assuage their guilt. Conclusions: Visiting a family member to assuage their guilt was the only caregiver variable associated with depressive symptoms for nursing home residents. This finding suggests that developing interventions to improve personal relationships between nursing home residents and family members might facilitate the emotional support of caregivers and psychological support for older nursing home residents in Taiwan.