Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology Development and Initial Results of CFD Simulations of Methane Distribution in the Working of a Longwall Ventilated in a Short “Y” Manner

The mining in seams with a high methane content by means of a longwall system, under conditions of high extraction concentration, results in exceeding methane concentrations allowed by the regulations at workings of the longwall environment, with the effect of mining machines’ standstill periods. The paper is a part of a study supporting the development of a system for shearing cutting speed control at the longwall, which should substantially reduce the production standstills due to exceeded limits and switching off the supply of electric equipment. Such a control system may be appropriate for longwalls ventilated using “y” and “short y” methods. Efficient computer simulations of the 3D airflow and methane propagation may assist the design and initial evaluation of the control system performance. First chapters present studies that are necessary for a proper formulation of the properties of the longwall model. Synthetic analysis of production during the period of longwall operation allowed one to choose the input assumptions to carry out ventilation-methane computations in a cFD numerical model of longwall z-11. This study is followed by a description of the model that is used for a case study, considering three variants of the shearer position. Finally, initial simulation results and directions of further studies are discussed.
Yeast Models of Amyotrophic Lateral Sclerosis Type 8 Mimic Phenotypes Seen in Mammalian Cells Expressing Mutant VAPBP56S

Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease that results in the loss of motor neurons and can occur sporadically or due to genetic mutations. Among the 30 genes linked to familial ALS, a P56S mutation in VAPB, an ER-resident protein that functions at membrane contact sites, causes ALS type 8. Mammalian cells expressing VAPBP56S have distinctive phenotypes, including ER collapse, protein and/or membrane-containing inclusions, and sensitivity to ER stress. VAPB is conserved through evolution and has two homologs in budding yeast, SCS2 and SCS22. Previously, a humanized version of SCS2 bearing disease-linked mutations was described, and it caused Scs2-containing inclusions when overexpressed in yeast. Here, we describe a yeast model for ALS8 in which the two SCS genes are deleted and replaced with a single chromosomal copy of either wild-type or mutant yeast SCS2 or human VAPB expressed from the SCS2 promoter. These cells display ER collapse, the formation of inclusion-like structures, and sensitivity to tunicamycin, an ER stress-inducing drug. Based on the phenotypic similarity to mammalian cells expressing VAPBP56S, we propose that these models can be used to study the molecular basis of cell death or dysfunction in ALS8. Moreover, other conserved ALS-linked genes may create opportunities for the generation of yeast models of disease.
Prediction-based phase unwrapping for differential interferograms of coal mining areas using a stochastic medium model

ABSTRACT This paper presents a novel phase unwrapping method for differential interferograms of coal mining areas, which takes full account of the mechanism of mining subsidence. The model uses a predicted deformation value for deformation caused by underground coal mining to assist the phase unwrapping and improve its accuracy. This method can overcome the defects of existing phase unwrapping algorithms that are not applicable to regions experiencing rapid deformation. The availability of the proposed method is first verified with noise-free simulated data, and then further tested with 3D laser scanning data and real synthetic aperture radar interferometry images. The results show that the prediction-based phase unwrapping method is able to realize phase unwrapping of differential interferograms covering coal mining areas that experience rapid deformation, and the results obtained are reasonable.
A Random Effect Model Approach to Survey Data Integration

Combining information from several surveys, or survey integration, is an important practical problem in survey sampling. When the samples are selected from similar but different populations, random effect models can be used to describe the sample observations and to borrow strength from multiple surveys. In this paper, we consider a prediction approach to survey integration assuming random effect models. The sampling designs are allowed to be informative. The model parameters are estimated using a version of EM algorithm accounting for the sampling design. The mean squared error estimation is also discussed. Two limited simulation studies are used to investigate the performance of the proposed method.
IC87201, a PSD-95/nNOS Inhibitor, Ameliorates Heart Rate Variability in the Rat Model of Middle Cerebral Artery Occlusion

Objective: Assessment of heart rate variability (HRV) is a non-invasive and reliable method to evaluate autonomic disorders after cerebral ischemia. The present study was conducted to investigate the therapeutic potential of IC87201 in reducing post-stroke cardiac dysfunction. Materials and methods: Cerebral ischemia was induced by the middle cerebral artery occlusion (MCAO) method in 15 anesthetized adult male rats in three MCAO, MCAO+ DXM, and MCAO+ IC87201 groups, for one hour. Electrocardiogram was recorded before, and 48 hours after ischemia and drug administration, and HRV parameters were calculated from R-R intervals. In the treatment groups, IC87201 and Dextromethorphan hydrobromide monohydrate (DXM) were injected after an ischemic period. Results: After brain ischemia, the R-R interval decreased and consequently heart rate increased. The R-R intervals were used to extract the HRV frequency and time domains, including normalized low frequency (LF), high frequency (HF), LF/HF ratio, and standard deviation of R-R interval (SDRR). Normalized LF and LF/HF ratio enhanced 48 hours after ischemia, while normalized HF and SDRR significantly reduced compared to the pre-ischemic state. All HRV parameters had returned to their pre-ischemic level 48 hours after IC87201 and DXM administration, except SDRR, which recovered only in the IC87201 administered group. Conclusion: Based on our findings, it can be concluded that cerebral ischemia significantly worsens HRV parameters as a result of sympathetic overactivity. These changes were reversed by administering DXM and IC87201, but IC87201 has generally been more effective in lowering lesions. As a result, IC87201 can be introduced as an effective substance for the treatment of post-ischemic cardiac side effects.
Capability of the SMAP Mission to Measure Ocean Surface Winds in Storms

AbstractThe National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission was launched in January 2015 and has been providing science data since April 2015. Though designed to measure soil moisture, the SMAP radiometer has an excellent capability to measure ocean winds in storms at a resolution of 40 km with a swath width of 1,000 km. SMAP radiometer channels operate at a very low microwave frequency (L band, 1.41 GHz, 21.4 cm), which has good sensitivity to ocean surface wind speed even in very high winds and with very little impact by rain. This gives SMAP a distinct advantage over many spaceborne ocean wind sensors such as C-band [Advanced Scatterometer (ASCAT)] or Ku-band [Rapid Scatterometer (RapidScat)] scatterometers and radiometers operating at higher frequencies [Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), WindSat, Advanced Microwave Scanning Radiometer (AMSR), and Global Precipitation Measurement (.
Laboratory Investigation of Astrophysical Collimated Jets with Intense Lasers

One of the remarkable dynamic features of the Herbig–Haro (HH) object is its highly collimated propagation far away from the accretion disk. Different factors are proposed to give us a clearly physical explanation behind these fascinating phenomena, including magnetic field, radiation cooling, surrounding medium, and so on. Laboratory astrophysics, as a new complementary method of studying astrophysical issues, can provide an insight into these behaviors in a similar and controllable laboratory environment. Here we report the scaled laboratory experiments that a well-collimated radiative jet with high Mach number is successfully created to mimic the evolution of HH objects. According to our results, we find that the radiation cooling effect within the jet and the outer rare surrounding plasmas from the X-ray (>keV) photoionized target contribute to the jet collimation. The local nonuniform density structures along the collimated radiative jet axis are caused by the pressure competition between the inner jet and the outer plasmas. The corresponding simulations performed with radiation-hydrodynamic codes FLASH reveal how the radiative jet evolves.
Effect of Brewing Conditions on Antioxidant Properties of Ginkgo biloba Leaves Infusion

Due to the growing awareness of the importance of healthy eating in society, there is an increasing interest in the use of herbs and low-processed, natural products. Ginkgo biloba is a raw material with a high pro-health potential, which is related to the high content of antioxidant compounds. The aim of the study was to determine the relationship between the antioxidant activity of Ginkgo biloba leaf infusions and the weighted amount of leaves and brewing time. In addition, a sensory analysis of the infusions obtained was carried out. The innovation is to determine the migration of micro- and macroelements to the infusion prepared from Ginkgo biloba depending on the leaves’ weight used and the brewing time. The research showed the dependence of the antioxidant activity of the infusions and the migration of microelements on the size of the dried material and the brewing time. In the publication, the main factors influencing the quality of infusions were analysed, their mutual correlations were determined, and combinations showing the highest antioxidant activity and, at the same time, the highest sensory acceptability were selected.
Performance Comparisons Between MFDFA and EMD Using Neural Network and Support Vector Machine

Multifractal detrended fluctuation analysis (MFDFA) is a powerful tool for discovering dynamics hidden in complex data. Similarly, empirical mode decomposition (EMD) is a typical method for time-frequency analysis of nonstationary data. Many works have applied MFDFA and EMD to get insight into nature of machine vibration signals. However, comparisons of performance of MFDFA and EMD in feature extraction have rarely been performed so far. To fill this gap, this paper benchmarked the performance of MFDFA against EMD by neural network (NN) and support vector machine (SVM) using a group of gearbox vibration signals containing gear faults in different types and severity levels. In this way, five characteristic parameters were obtained using MFDFA. For comparison, an eleven-dimension feature vector was acquired using EMD. Following this, either of NN and SVM served to distinguish between gearbox conditions characterized by the features extracted above. The results indicated that MFDFA is comparable to EMD in discrimination between gearbox conditions. In addition, this paper demonstrated that the integration of MFDFA and SVM is promising in fault diagnosis of gearboxes.
Single Image 3D Face Reconstruction Based on Statistical Model

Single image 3D face reconstruction technology has a broad application in the life, also has a high technical difficulties. This paper proposes a single image 3D face reconstruction technology based on statistical model. The method established 3D face statistical model based on 3D face database in advance, and trained 2D facial feature points parameter model based on the 2D face database using the algorithm of SDM. when reconstruct 3D face model from single image, first we use 2D facial feature points parameter model to extract face feature points; Then, according to 3D face model, we use adaptive learning factor gradient descent method to iteratively optimize the energy function, to get statistical model parametric vector, namely got the 3D face model corresponding to the 2D face images. The results show that use the proposed method to rebuild the faces have high similarity.
Cerrado cashew (Anacardium othonianum Rizz) apple pomace: chemical characterization and optimization of enzyme-assisted extraction of phenolic compounds

Cerrado cashew (Anacardium othonianum Rizz) pomace is the main by-product from the processing of cashew apples. This study aimed to (i) investigate the difference between the chemical compositions of the pomaces of yellow (YCP), orange (OCP), and red (RCP) cashew apples based on their mineral, monosaccharide, and polyphenolic compositions; and (ii) optimize enzyme-assisted extraction of the phenolic compounds from Cerrado cashew apple pomace. Potassium and iron were the main macro- and microelements found in residue, and significant differences were noted in the profiles of the samples. The predominant monosaccharides in the samples included glucose (52.7–60.6 mol%) and uronic acid (12.5–14.5% mol). The complete three-level factorial design allowed the optimization of pH, extraction time, and temperature, leading to an optimal extraction of polyphenols at pH 5.5, an extraction time of 120 min, and a temperature of 55°C. Myricetin (43.03–44.26 mg/kg), vanillic acid (30.96–32.32 mg/kg), and gallic acid (11.34–29.25 mg/kg) were the major polyphenols found in the samples. These results confirmed that regardless of the color of Cerrado cashew apple pomace, this by-product is a potential source of phytochemicals for application in sustainable and functional food products.
Automatic identification of malfunctions of large turbomachinery during transient states with genetic algorithm optimization

Turbines and generators operating in the power generation industry are a major source of electrical energy worldwide. These are critical machines and their malfunctions should be detected in advance in order to avoid catastrophic failures and unplanned shutdowns. A maintenance strategy which enables to detect malfunctions at early stages of their existence plays a crucial role in facilities using such types of machinery. The best source of data applied for assessment of the technical condition are the transient data measured during start-ups and coast-downs. Most of the proposed methods using signal decomposition are applied to small machines with a rolling element bearing in steady-state operation with a shaft considered as a rigid body. The machines examined in the authors’ research operate above their ﬁrst critical rotational speed interval and thus their shafts are considered to be ﬂexible and are equipped with a hydrodynamic sliding bearing. Such an arrangement introduces signiﬁcant complexity to the analysis of the machine behavior, and consequently, analyzing such data requires a highly skilled human expert. The main novelty proposed in the paper is the decomposition of transient vibration data into components responsible for particular failure modes. The method is automated and can be used for identiﬁcation of turbogenerator malfunctions. Each parameter of a particular decomposed function has its physical representation and can help the maintenance staﬀ to operate the machine properly. The parameters can also be used by the managing personnel to plan overhauls more precisely. The method has been validated on real-life data originating from a 200 MW class turbine. The real-life ﬁeld data, along with the data generated by means of the commercial software utilized in GE’s engineering department for this particular class of machines, was used as the reference data set for an unbalanced response during the transients in question.
Pulmonary Function Tests in the Evaluation of Early Lung Disease in Cystic Fibrosis

Background: Properly evaluating respiratory system dysfunction is essential in children with cystic fibrosis (CF). This prospective study aimed to assess the course of early lung disease based on multiple breath nitrogen washout (MBNW), impulse oscillometry (IOS), and conventional techniques, such as spirometry and body plethysmography. Methods: Over a 2 year recruitment period, subjects with CF aged 7–18 performed pulmonary function tests (PFTs). Moreover, the nutritional and microbiological status, frequency of pulmonary exacerbations (PExs), and patients’ health-related quality of life (HRQoL) were assessed. Results: The mean age of the children (n = 69) was 14.09 ± 3.26 years; F/M 37/32. Spirometry-based diagnoses of normal lung function (forced expiratory volume in 1 s, FEV1 ≥ 90%pred), mild (FEV1 70–89%pred) and moderate (FEV1 40–69%pred) lung diseases were established in 34 (49.3%), 25 (36.2%), and 10 (14.5%) patients, respectively. An elevated lung clearance index (LCI > 6.98) was observed in 85% of the subjects with normal FEV1. The presence of Pseudomonas aeruginosa infection (n = 16) and the number of PExs treated with IV antibiotics were associated with significantly worse PFT results. Conclusions: MBNW and IOS are more helpful tools than conventional techniques in assessing early lung disease in CF. LCI is a more useful parameter for detecting functional abnormalities than FEV1 in school-age children.
Aktivnosti za preprečevanje osamljenosti starejših odraslih v domovih za starejše

Uvod: Osamljenost je mednarodni problem javnega zdravja. Povzroča boleč in skrb vzbujajoč občutek čustvene ali socialne izolacije in je vzrok težavam, povezanim z duševnim zdravjem. Osamljenost je pogosto prisotna pri starejših odraslih, tudi pri tistih, ki bivajo v domovih za starejše. S pregledom literature želimo predstaviti aktivnosti in njihovo učinkovitost pri zmanjševanju osamljenosti pri starejših odraslih v domovihza starejše. Metode: Izvedli smo sistematični pregled znanstvene literature. Iskanje s ključnimi besedami v angleškem jeziku je potekalo v mednarodnih bazah podatkov: PubMed, CINAHL in SAGE. Za prikaz pregleda ter izbire vključenih člankov smo uporabili diagram poteka. Vključene članke smo kritično ocenili z orodjem Joanna Briggs Institutes in zbrane podatke analizirali po metodi tematske analize.Rezultati: V končno analizo je bilo vključenih 20 člankov. Oblikovali smo dve glavni temi. Prva tema »aktivnosti za preprečevanje osamljenosti« odraža dve podtemi: gibalne in družabne aktivnosti. Druga tema »vpliv aktivnosti na preprečevanje osamljenosti« prikazuje fizične, psihološke in socialne vplive aktivnosti na preprečevanje osamljenosti.Diskusija in zaključek: Pri zmanjševanju osamljenosti so najučinkovitejše vodene in usmerjene aktivnosti: telesne vadbe, umetniško ustvarjanje, vrtnarjenje, pogovorne skupine, pa tudi terapija smeha in obujanje spominov.
A Novel Gravity Optimization Algorithm for Extractive Arabic Text Summarization

An automatic text summarization system mimics how humans summarize by picking the most significant sentences in a source text. However, the complexities of the Arabic language have become challenging to obtain information quickly and effectively. The main disadvantage of the traditional approaches is that they are strictly constrained (especially for the Arabic language) by the accuracy of sentence feature functions, weighting schemes, and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature that tolerates imprecision, gets prohibited results, and is not strictly bound by the above restrictions. This paper used the Gravitational Optimization Algorithm (GOA), a powerful metaheuristic approach based on the law of gravity, to address the challenge of extractive summarizing Arabic texts. The objective function of the GOA algorithm is derived based on sentence significance, such as its length, similarity degree, position, statistical term frequency, and named entity ownership. Essex Arabic Summaries Corpus (EASC) was used to evaluate the proposed method and measured by the Recall-Oriented Understudy for Gisting Evaluation (ROUGE). The proposed approach achieved 68.04% Recall, 58.49% Precision, and 60.05% F1-measure using ROUGE-1, higher than standard summarizers and metaheuristic approaches.
Random Beam-Based Non-Orthogonal Multiple Access for Massive MIMO Low Earth Orbit Satellite Networks

In this paper, we propose random beam-based non-orthogonal multiple access (NOMA) for massive multiple-input multiple-output (MIMO) low earth orbit (LEO) satellite communication systems that operate with frequency-division duplexing (FDD). Our system model consists of a massive-antenna satellite and multiple single-antenna users within its coverage area. The satellite selectively serves a subset of users based on a target signal-to-interference-plus-noise power ratio (SINR). In the random beam-based NOMA, the satellite utilizes random beams, where each beam can support multiple users using NOMA. To facilitate user selection and power allocation, each user provides several scalar values obtained from statistical channel state information (CSI) as feedback to the satellite. This allows us to reduce the computational complexity of beamforming design and minimize the feedback overhead for channel acquisition. We propose two random beam-based NOMA schemes with varying complexities and feedback overheads. We optimize these schemes by solving joint user selection and power allocation problems. The numerical results demonstrate that our proposed schemes outperform conventional random beamforming, specifically orthogonal multiple access (OMA) at each beam, by supporting a greater number of users.
Molecular docking and dynamic study with polyphenolic constituents as inhibitors of human tyrosinase enzyme for hyperpigmentation therapy and skin complexion management

This research has revealed the molecular docking and dynamics study with few phytomolecules against the human tyrosinase enzyme protein in order to control hyperpigmentation and skin tone in the future. This study set out to find certain phytomolecules that have the capacity to attach to the protein model for the tyrosinase enzyme and block the enzyme's ability to function. We took into account all nine molecules in total, coupled with a protein model of the tyrosinase enzyme, for docking, with energy ranges between -5.3 and -7.4 Kcal/mol. The greatest lowest binding energy for quercetin was -7.4 Kcal/mol. With a model protein, this molecule displayed a variety of interactions, including Van der Waals, conventional hydrogen bonds, covalent bonds, and carbon hydrogen bonds. In this interaction, 3 hydrogen bonds were discovered. The other compounds, such as kaempferol and chlorogenic acid, also demonstrated correct binding with the model tyrosinase and had -7.2 Kcal/mol energy with 3 and 5 hydrogen bonds, respectively. Quercetin, Kaempferol, and Chlorogenic acid are therefore thought to be far more potent than Benztropine and may be used in further clinical research.
Phase inpainting in time-frequency plane

We propose a new problem of missing data reconstruction in the time-frequency plane. This problem called phase inpainting, consists in reconstructing a signal from time-frequency observations where all amplitudes and some phases are known while the remaining phases are missing. A mathematical formulation of this problem is given. We propose three alternatives of existing algorithms. An iterative algorithm: Griffin and Lim and two semidefinite programming optimization algorithms: PhaseLift and PhaseCut. The obtained results show that knowledge of certain phases improves the reconstruction's quality.