Miracle-dz/UniFAR-FTUs huggingface dataset:
Engine Load Prediction during Take-Off for the V2500 Engine

The aviation industry faces an ever increasing pressure to reduce its cost in order to gain competitive advantages. Since aircraft maintenance contributes strongly with about 17% to the overall direct operating cost (DOC), maintenance providers are required to continuously reduce their cost share as well. As a result, a lot of effort is put into the exploitation of the potential of emerging digitalization technologies to predict upcoming system faults and, therefore, reduce the projected maintenance impact. The detection of early stage faults and prediction of remaining useful lifetimes (RUL) for various systems, including aircraft engines as high-value assets, has been a focal point for many research activities already. A key aspect – necessary for an accurate prediction of future behavior – is the correct mapping of ambient conditions that have led to the respective system condition. Therefore, it is necessary to combine data information throughout an aircraft’s life from different stakeholders to gain valuable insights. However, as the aviation industry is strongly segregated with many parties involved, trying to gain their own competitive advantage, the required information about the operating condition is often not available to independent maintenance providers. Thus, modeling engine degradation often needs to rely on estimated nominal conditions, limiting the ability to precisely predict engine faults. With this paper, we will develop a model that allows users to estimate the experienced engine load during take-off by only using publicly available information, i.e. airport weather information reports and public flight data. The calculated engine load factors are computed in terms of an engine pressure ratio (EPR) derate. The results are benchmarked with the actual engine derate, obtained for different operators and various ambient conditions, to enable an identification of challenges for the load prediction and areas of improvement. The developed model will help to adjust engine failure projections according to the experienced ambient conditions and, therefore, supports the development of better engine degradation models.
Identifying “slow” and “fast” movers in a travel preference space: Application of a synthetic pseudo-panel approach

We present a new approach to studying travel preference dynamics based on constructing a synthetic pseudo-panel (SPP) from repeated cross-sectional data. This is accomplished by creating a high-dimensional probabilistic model representation of the entire data set, which allows sampling from the probabilistic model in such a way that all of the intrinsic correlation properties of the original data are preserved. The key to this is the use of novel deep learning algorithms based on the Conditional Variational Autoencoder (CVAE) framework. We use the presented approach to reveal the dynamics of transport preferences for a fixed pseudo-panel of individuals based on a large Danish cross-sectional data set from 2006 to 2016. The model is utilized to classify individuals into 'slow' and 'fast' movers with respect to the speed of which their preferences change over time. It is found that the prototypical fast mover is a young woman who lives as single in a large city whereas the typical slow mover is a middle-aged man with high income from a nuclear family that lives in a detached house outside a city.
Impact of Corporate Governance on Firm’s Performance: A Case of Micro-Financing Institutions in Sialkot, Pakistan ======================================================================

This research paper attempts to evaluate the relationship between corporate governance and performance of the microfinance institutions in Sialkot employing primary source of data. A representative sample of 80 respondents from the top-level management such as board of directors, chief executive officers, managing directors and all the related staff who are responsible for the growth and progress of the microfinance institutions was selected using stratified random sampling technique. The findings of the study revealed that the CEO duality, board independence and ownership structure were the significant variables affecting the firm performance whereas the variables (board size and audit committee independence) showed insignificant impact. The analysis of the research suggested that micro finance institutions should have good and solid governance framework in order to enhance decision making and minimize the possibilities of the management failures ultimately improvement in the firm’s performance.
Rural Inhabitants and Patronage of Traditional Medicine: A Study of Pregnant Mothers (Women) in Ona-Ara Local Government Area of Oyo State, Nigeria

-The use of traditional medicine has been on the increase in many developing and industrialized countries. This high use may be due to accessibility, affordability, availability and acceptability by majority of the population especially among the rural dwellers who have a strong perception of its efficacy in overcoming a myriad of health challenges including maternity issues. With the hybrid of quantitative and qualitative research techniques, this study examined Rural Inhabitants and the Utilization of Traditional Medicine among Pregnant Mothers in Ona-Ara Local Government Area of Oyo State. One Hundred and Fifty Five (155) questionnaires were administered among the respondents out of which One Hundred and Forty-Four (144) valid responses were obtained. In addition, twenty-one (21) IDIs and fifteen (15) KIIs were conducted to further ascertain the findings. Data were analyzed using descriptive and inferential analysis. Qualitative data were analyzed using content analysis, the result showed that the respondents had positive disposition towards traditional medicine, perceived traditional medicine to be effective in tackling the pregnancy-related challenges, and that traditional medicine does not lead to fetus-maternal complications. Recommendations is that health care providers should take into consideration the prevailing cultural practices in the communities in designing health education and messages that will promote the positive cultural practices and reduce the impact of negative ones among pregnant women. In addition, efforts should be intensified towards explore willingness towards co-operation, assess failures and successes of both health systems and advocate clarity in dosages.
Unravelling System Optimum Structure by trajectory data analysis

This work investigates network-related trajectory features to unravel trips that the most contribute to the system under-performance. When such trips are identiﬁed, features analysis also permits to identify the best alternatives in terms of routes to make the system to its optimum. First, data mining is carried out on trajectories obtained from reference dynamic traﬃc assignment (DTA) simulations in a real-world network, based on User-Equilibrium (UE) and System-Optimum (SO). This helps us (i) to target the trajectories to be changed, and (ii) to identify their main features (trip lengths, experienced travel time, path marginal costs, and network-related features such as betweenness centrality and traﬃc light parameters, etc.). Similarity analysis based on Longest Common Subsequence, Principle Component Analysis are the main methods that are performed to carry out descriptive analysis of trajectories. Supported Vector Machine is then used to determinate the features with regards to their contribution to better network performance.
Correlation Between Bio-Chemical Composition of Castor Leaf with Bio- Energetics and Economic Parameters of Selected Eco-Races of Eri Silkworm

An attempt has been made to work out the correlation co-efficients between bio-chemical composition of castor leaf (DCH-177 hybrid and Local Pink variety) with bio-energetics and economic parameters of selected eco-races (Borduar, Dhanubanga, Khanapara, Kokrajhar, Mendipathar and Titabar) of eri silkworm (Samia cynthia ricini Boisduval) and bioenergetics with economic parameters. The study established that, the bio-chemical composition of castor leaf viz., leaf moisture, total chlorophyll, total protein, sugars, nitrogen, phosphorous, potassium, calcium, magnesium and sulphur were found to have highly significant positive relationship with the bio-energetic indices viz., food consumption, food digestion, consumption index, approximate digestibility, growth rate, efficiency of conversion of ingesta, efficiency of conversion of digesta, coefficient of metabolism, reference ratio and metabolic rate except with that of total protein and total sugars on food consumption, food digestion, ECD and reference ratio. Further, biochemical constituents of leaf found significant positive relation with economic characters i.e., matured larval weight, cocoon yield, shell weight, shell yield, shell ratio, silk productivity, rate of pupation and fecundity, while it was significant negative correlation with cocoon weight and rate of pupation and non-significant negative correlation with pupal weight. On the other hand, bio-energetic parameters did show highly significant positive relationship with economic parameters of eri silkworm except for pupal weight, shell yield and fecundity which showed negative significant correlation. The study inferred that, biochemical composition of castor leaf and bio-energetic indices of eri silkworm did play a major role in determining the economic characters and hence efforts must be made to improve the quality of castor leaf and conversion efficiency of food in eri silkworm to improve the economic parameters.
Liposomal Lactoferrin as Potential Preventative and Cure for COVID-19

A prospective observational study was performed in 75 patients with typical symptoms of COVID-19 who tested positive to IgM/IgG rapid test. Patients were isolated and treated at home using remote systems, reviewed twice a day for 10 days, and followed up to 1 month. A liposomal bovine lactoferrin (LLF) nutritional syrup food supplement (32 mg of LF/10 ml plus 12 mg of vitamin C) was administered orally in 4 to 6 doses per day for 10 days. In addition, a zinc solution was administered at the dose of 10 mg/10 ml twice or three times a day. A control group of 12 patients who took only LLF was included. All family members in contact with patients (256 persons) were also treated with half of this dose. The treatment allowed a complete and fast recovery in all patients (100%) within the first 4-5 days. Same treatment at lower dose prevented the disease in healthy persons directly related with the affected patients. Weakness (95%) followed by a dysfunction in the perception of smelling and tasting (88%), cough (83%), muscular pain (67%) were the most frequent complains. LF possess antiviral, immunomodulatory and anti-inflammatory effects which might be important for the treatment of COVID-19 infection. We conclude that LLF potentially prevent and cure COVID 19 infection. ©2020 Serrano G. This is an open-access article distributed under the terms of the Creative Commons Attribution (CCBY 4.0), which permits unrestricted use, distribu-tion, and reproduction in any medium, provided the original author and source are credited Gabriel Serrano1,*, Iulia Kochergina1, Arturo Albors2, Eva Diaz3, Mar Oroval3, Guillen Hueso3, Juan M Serrano3 1Dr. Serrano Dermatology Clinic, Valencia, Spain 2Medical Department of Sesderma Laboratories, Valencia, Spain 3Research Department of Sesderma Laboratories, Valencia, Spain Corresponding author: Dr. Gabriel Serrano Dr. Serrano Dermatology Clinic, Valencia, Spain. E-mail: gabriels@sesderma.com DOI: 10.5530/ijrhs.8. 1.3 Received: 07-04-2020; Accepted: 20-04-2020; Published: 22-04-2020.
Dissociative Phenomenology and General Health in Normal Population

Background: Dissociative symptoms are most commonly found in females and adolescents, and when discussing their background, they can be from lower socio-economic backgrounds and rural areas. They are always preceded by psychosocial stressors. Dissociative disorders previously known as “hysteria” have been described since antiquity and Hippocrates even hypothesised “wandering uterus” to be the cause for dissociation in females. With the advances in science, there has been shift from these religious and spiritual concepts to a scientific basis for dissociation. Aim: To assess the dissociative phenomenology in normal population and to assess the subjective health in normal population. Methods: A group of 100 (50 females & 50 males) were selected from the community using a snowball sampling technique. Tools: Socio-demographic data sheet, General Health Questionnaire-12 and Dissociative Experience Scale-II were used. Results: The study found that females differ from males in the reporting of subjective health rating (X=5.76, p=0.01) and similar results shown in terms of dissociative phenomenology (X=67.76, p=0.001). Discussion: It has been found that only 4% from the female group and 2% from the male group rated their health under the “normal” category. 52% of females and 64% of males were categorised under “mild ill health” and 24% to 26% were in “moderate ill health”, whereas 20% of female participants and 8% of male participants rated their health as “severely ill”. In another domain of the study, dissociative phenomenology, 32% of female participants reported severe dissociative symptoms and 38% of male participants also showed similar results. Conclusion: Dissociative disorder significantly affects the population but it is hard to diagnose due to factors such as; cultural factors, socio-economic factors etc. The study shows clearly that dissociative symptoms are found in the general population also.
Reducing the number of Ransomware attacks on networks using machine learning pattern analysis

Later overall cybersecurity assaults brought about by Cryptographic Ransomware contaminated frameworks crosswise over nations and associations with a large number of dollars lost in paying blackmail sums. This type of malevolent programming takes client documents prisoner by encoding them and requests a huge payment installment for giving the unscrambling key. Mark based strategies utilized by Antivirus Software are deficient to dodge Ransomware assaults because of code muddling methods and making of new polymorphic variations regular. Conventional Malware Attack vectors are additionally not strong enough for discovery as they don't totally follow the particular personal conduct standards appeared by Cryptographic Ransomware families. This work dependent on examination of a broad dataset of Ransomware families presents RansomWall, a layered safeguard framework for insurance against Cryptographic Ransomware. It pursues a Hybrid methodology of consolidated Static and Dynamic examination to create a novel reduced arrangement of highlights that portrays the Ransomware conduct. Nearness of a Strong Trap Layer helps in early discovery. It uses Machine Learning for uncovering zero-day interruptions. At the point when introductory layers of RansomWall label a procedure for suspicious Ransomware conduct, documents changed by the procedure are upheld in the mood for protecting client information until it is delegated Ransomware or Benign. We will execute RansomWall for Microsoft Windows working framework (the most assaulted OS by Cryptographic Ransomware) and assessed it against numerous examples from various Cryptographic Ransomware families in genuine client situations. The testing of RansomWall with different Machine Learning calculations will give great outcomes with Gradient Tree Boosting Algorithm.
Molecular Dynamic Simulation of Centella asiatica Compound as an Inhibitor of Advanced Glycation End Products

Lili Legiawati1, Fadilah Fadilah2, Kusmarinah Bramono1, Siti Setiati3*, Em Yunir3 1Department of Dermatology and Venereology, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia. 2Department of Pharmacy, Faculty of Medicine, Universitas Indonesia, Depok Beji, Indonesia. 3Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia, Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
Heterosis studies in diallel crosses of maize for yield and yield attributing traits in maize (Zea mays L.) over locations

A study was undertaken to estimate the heterotic, heterobeltiotic and standard heterotic effects of 11 characters of 45 maize hybrids developed by ten parents in maize during rabi, 2011–12 over three locations viz., College Farm, Rajendranagar (Hyderabad), Agricultural Research Station, Karimnagar and Agricultural Research Station, Kampasagar, Nalgonda District, T.S. The pooled analysis of variance (Diallel) revealed significant differences among locations and genotypes for all the characters studied. The crosses exhibited significant differences, indicating varying performance of cross combinations. The parent vs crosses which indicates average heterosis, for all the traits, thus considerable amount of average heterosis was reflected in hybrids. Negative standard heterosis was observed for days to 50 per cent tasseling, days to 50 per cent silking and days to maturity due to earliness in three hybrids over checks DHM-117 and 900 M Gold were BML-2782 X BML-5233-5, CM-211 X BML-5233-5 and BML-2486 X BML-2. Five crosses viz. BML-15 X BML-2910, BML-7 X BML-3044, CM-211 X BML-7, BML-6 X BML-2 and BML-2782 X BML-6 were identified as potential hybrids with more than 12% standard heterosis for grain yield over better yielding commercial hybrid check DHM-117. Testing of these hybrids in all India coordinated trials across the different states of the country may result in identification of better hybrids in the near future for commercial exploitation.
Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study

Background Measurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19. Methods We undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis. Results We analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019). Conclusions Post-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19.
Effectiveness of booster BCG vaccination in preventing Covid-19 infection

ABSTRACT The evidence that BCG (bacille Calmette-Guerin) vaccine may increase the ability of the immune system to fight off pathogens other than tuberculosis has been studied in the past. This nonspecific immunity gained our interest, especially after initial reports of less cases in countries with universal BCG vaccination. In hopes of possible protective immunity, all staff of the Emirates International Hospital (United Arab Emirates) were offered a booster BCG vaccine in early March 2020. All the hospital staff were then tested for Covid-19 infection by the end of June 2020. We divided the subjects into two groups: booster vaccinated versus unvaccinated. The rate of Covid-19 infection was compared between the groups. Criteria included all staff who were offered the vaccine. Seventy-one subjects received the booster vaccination. This group had zero cases of positive COVID 19 infection. Two hundred nine subjects did not receive the vaccination, with 18 positive PCR confirmed COVID 19 cases. The infection rate in the unvaccinated group was 8.6% versus zero in the booster vaccinated group (Fisher’s exact test p-value = .004). Our findings demonstrated the potential effectiveness of the booster BCG vaccine, specifically the booster in preventing Covid-19 infections in an elevated-risk healthcare population.
Construction and characterization of the bacteriophage P4 derivatives whose genome size suitable for packaging into a P2 sir3 -sized head

The term “P2 sir-associated helper inefficiency” has been used to define the inefficient helper capability of P2 sir mutants for their satellite bacteriophage P4. The aim of this study was to investigate the factors overcoming P2 sir-associated helper inefficiency. At first, we verified whether the P2 cos region containing P4 sid71 cosP2 could overcome P2 sir-associated helper inefficiency with P2 sir3. The result was that P4 sid71 cosP2 could not overcome P2 sir-associated helper inefficiency with P2 sir3. Instead of cos region of P2, the size of the DNA packaged into a P2 sir -sized head seems to be important for overcoming P2 sir-associated helper inefficiency. In the present work, three kinds of P4 derivatives with packaged DNA sizes between those of P4 ost1 and P4 ost2, were constructed through DNA manipulation. In one P4 derivative, P4 sid71 delRI::apr, the size of the packaged DNA was identified with a CsCl buoyant equilibrium density gradient experiment. According to the burst sizes of the P4 derivatives, they could overcome P2 sir3-associated helper inefficiency. The size of the P4 derivative DNA suitable for packaging into a P2 sir3 -sized head was 28-29 kb.
Retrieving Lab Test Related Questions from Social Q&A Sites by Combining Shallow Features and Deep Representations

Patients face challenges in accurately interpreting their lab test results. To fulfill their knowledge gap, patients often turn to online resources, such as Community Question-Answering (CQA) sites, to seek meaningful information and support from their peers. Retrieving the most relevant information to patients' queries is important to help patients understand lab test results. However, few studies investigated the retrieval of lab test-related questions on CQA platforms. To address this research gap, we build and evaluate a system that automatically ranks questions about lab tests based on their similarity to a given question. The system is tested using diabetes-related questions collected from Yahoo! Answers' health section. Experimental results show that the regression-weighted combination of deep representations and shallow features was most effective in the Yahoo! Answers dataset. The proposed system can be extended to medical question retrieval, where questions contain a variety of lab tests.