Miracle-dz/UniFAR-FTUs huggingface dataset:
Study On Frequency Content Of Provided Strong Ground Motion In West Azerbaijan And East Azerbaijan

This study aims to better reveal the characteristics of the assessed ground motion in west and east Azerbaijan. Due to existence of happened great earthquakes and large number of potential seismic sources in North-West of Iran which is located in junction of Alborz and Zagros seismotectonic provinces, it is an interesting area for seismologists. Considering to population and existence of large cities like Tabriz, Ardabil and Orumiyeh which play crucial role in industry and economy of Iran, authors decided to focus on study of frequency content of strong ground motion to achieve ground acceleration in different frequencies indicate critical frequencies in the studied area. in this study have been applied is professional industrial software which has been written in 2009 and provided by authors; Because This applied software can cover previous software weak points very well. Obtained hazard maps illustrate that maximum accelerations will be experienced in North West to South East direction which increased by frequency reduction from 100 Hz to 10 Hz then decreased by frequency reduce (to 0.25 Hz). Maximum acceleration will be occurred in the basement in 10 Hz.
Sustained Lung Inflation at Birth for Preterm Infants: A Randomized Clinical Trial

BACKGROUND: Studies suggest that giving newly born preterm infants sustained lung inflation (SLI) may decrease their need for mechanical ventilation (MV) and improve their respiratory outcomes. METHODS: We randomly assigned infants born at 25 weeks 0 days to 28 weeks 6 days of gestation to receive SLI (25 cm H2O for 15 seconds) followed by nasal continuous positive airway pressure (nCPAP) or nCPAP alone in the delivery room. SLI and nCPAP were delivered by using a neonatal mask and a T-piece ventilator. The primary end point was the need for MV in the first 72 hours of life. The secondary end points included the need for respiratory supports and survival without bronchopulmonary dysplasia (BPD). RESULTS: A total of 148 infants were enrolled in the SLI group and 143 in the control group. Significantly fewer infants were ventilated in the first 72 hours of life in the SLI group (79 of 148 [53%]) than in the control group (93 of 143 [65%]); unadjusted odds ratio: 0.62 [95% confidence interval: 0.38–0.99]; P = . 04). The need for respiratory support and survival without BPD did not differ between the groups. Pneumothorax occurred in 1% (n = 2) of infants in the control group compared with 6% (n = 9) in the SLI group, with an unadjusted odds ratio of 4.57 (95% confidence interval: 0.97–21.50; P = .06). CONCLUSIONS: SLI followed by nCPAP in the delivery room decreased the need for MV in the first 72 hours of life in preterm infants at high risk of respiratory distress syndrome compared with nCPAP alone but did not decrease the need for respiratory support and the occurrence of BPD.
Power control for turbo coded symmetrical collaborative networks

Optimal power allocation for pure relay networks utilizing repetition codes has drawn a great deal of attention. However, power allocation in a cooperative network, where users who act as relays for each other and who utilize non-trivial codes, remains a challenge. With the aid of theoretical frame error rate expressions, we explore the performance of adaptive power control for decode-and-forward (DF) collaborative networks containing M users, employing turbo codes over statistically similar Rayleigh block faded channels. We conclude that power control can greatly benefit a DF collaborative network in a block fading environment.
A Bone‐Seeking Clone Exhibits Different Biological Properties from the MDA‐MB‐231 Parental Human Breast Cancer Cells and a Brain‐Seeking Clone In Vivo and In Vitro

Breast cancer has a predilection for spreading to bone. The mechanism of preferential metastasis of breast cancer to bone is unknown. We hypothesize that breast cancer cells that develop bone metastases have the capacity to facilitate their colonization in bone. To examine this hypothesis, we established bone‐seeking (MDA‐231BO) and brain‐seeking (MDA‐231BR) clones of the human breast cancer cell line MDA‐MB‐231 by repeated sequential passages in nude mice and in vitro of metastatic cells obtained from bone and brain metastases, respectively. These clones were examined for distinguishing biological characteristics and compared with the MDA‐231 parental cells (MDA‐231P) in vivo and in vitro. Both the MDA‐231BR and the MDA‐231BO showed identical tumorigenicity to MDA‐231P at the orthotopic site. MDA‐231P that was inoculated into the heart developed metastases in bone, brain, ovary, and adrenal glands. On the other hand, MDA‐231BO exclusively metastasized to bone with larger osteolytic lesions than MDA‐231P. MDA‐231BR exclusively disseminated to brain and failed to develop bone metastases. In culture, MDA‐231BO produced greater amounts of parathyroid hormone‐related protein (PTH‐rP) than MDA‐231BR and MDA‐231P in the absence or presence of transforming growth factor β (TGF‐β). Furthermore, the anchorage‐independent growth of MDA‐ 231BO in soft agar was not inhibited by TGF‐β, whereas TGF‐β profoundly inhibited the growth of MDA‐231P and MDA‐231BR. Insulin‐like growth factor I (IGF‐I) markedly promoted the anchorage‐independent growth of MDA‐231BO, whereas marginal or no stimulation was observed in MDA‐231BR or MDA‐231P, respectively. Our data suggest that these phenotypic changes allow breast cancer cells to promote osteoclastic bone resorption, survive, and proliferate in bone, which consequently leads to the establishment of bone metastases.
ESWT - tracking organs during focused ultrasound surgery

We report here our results in a multi-sensor setup reproducing the conditions of an automated focused ultrasound surgery environment. The aim is to continuously predict the position of an internal organ (here the liver) under guided and non-guided free breathing, with the accuracy required by surgery. We have performed experiments with 16 healthy human subjects, two of those taking part in full-scale experiments involving a 3 Tesla MRI machine recording a volume containing the liver. For the other 14 subjects we have used the optical tracker as a surrogate target. All subjects where volunteers who agreed to participate in the experiments after being thoroughly informed about it. For the MRI sessions we have analyzed semi-automatically offline the images in order to obtain the ground truth, the true position of the selected feature of the liver. The results we have obtained with continuously updated random forest models are very promising, we have obtained good prediction-target correlation coefficients for the surrogate targets (0.71 ± 0.1) and excellent for the real targets in the MRI experiments (over 0.91), despite being limited to a lower model update frequency, once every 6.16 seconds.
Designing of a PSO-Based Adaptive SMC With a Multilevel Inverter for MPPT of PV Systems Under Rapidly Changing Weather Conditions

This study discusses the widespread problem of chattering phenomena and high frequency oscillations in sliding mode controllers (SMCs) used for maximum power point (MPP) tracking (MPPT) in photovoltaic (PV) systems. Moreover, this study introduces an adaptive sliding mode controller (ASMC) made just for PV panels with MPPT capability to address these problems. The main goal of the control method is to make PV systems more reliable and effective by precisely tracking the MPP, even when the weather quickly changes. This strategy demonstrates superior static and dynamic responsiveness compared with traditional methods. The particle swarm optimization (PSO) algorithm is employed to determine the best gains for the SMC method, specifically for controlling the variable step of the standard perturb and observe (P&O) algorithm. This algorithm used in the study with a Soltech 1STH-250-WH module is linked to a boost DC-DC converter. The aforementioned converter provided power to a resistive load, which was then controlled by a voltage regulator. Subsequently, the research highlights the utilization of a new voltage source inverter: a 9-level diode clamp inverter (DCI) employed to mitigate harmonics, hence enhancing power quality through the reduction of its components and generating a sinusoidal AC voltage that has multiple uses.
The Himalayan Foreland Basin from collision onset to the present: a sedimentary–petrology perspective

Abstract This chapter summarizes the available stratigraphic, petrographical and mineralogical evidence from sediments and sedimentary rocks on the evolution of the Himalayan belt and its associated foreland basin. The use of compositional signatures of modern sediments to unravel provenance changes and palaeodrainage evolution through time is hampered by a poor match with detrital modes of ancient strata markedly affected by selective chemical dissolution of unstable minerals during diagenesis. Only semi-quantitative diagnoses can thus be attempted. Volcanic detritus derived from Transhimalayan arcs since India–Asia collision onset at c. 60 Ma was deposited onto the Indian lower plate throughout the Protohimalayan stage, with the exception of the Tansen region of Nepal that is characterized by quartz-arenites yielding orogen-derived zircon grains. During the Eohimalayan stage, begun in the late Eocene when most sedimentation ceased in the Tethys Himalayan domain, low-rank metasedimentary detritus was overwhelming in the central foreland basin, where a widespread unconformity developed spanning locally as much as 20 myr. Volcanic detritus from Transhimalayan arcs remained significant in northern Pakistan. Arrival of higher-rank metamorphic detritus since the earliest Miocene, and the successive occurrence of garnet, staurolite, kyanite and finally sillimanite, characterized the Neohimalayan stage, when repeated compositional changes in the foreland-basin succession document the stepwise propagation of crustal deformation across the Indian Plate margin and widening of the thrust belt with exhumation of progressively more external tectonic units. The correspondence in time between the activity of major thrusts and petrofacies changes indicates a promising approach to accurately reconstruct the geological evolution of the coupled orogen–basin system. Conversely, a poor conceptual framework and the general reliance on ad hoc mechanisms to explain phenomena unpredicted by simplified models represent major factors limiting the robustness of palaeotectonic interpretations. Improved knowledge requires taking into full account the dynamic role played by still poorly understood subduction processes – rather than exclusively the effect of passive loading – as well as the role played by the presence of inherited structures on the downgoing Indian Plate, which control both lateral variability of orogenic deformation and the location of depocentres in the foreland basin.
A Study of the Adsorption Properties of Individual Atoms on the Graphene Surface: Density Functional Theory Calculations Assisted by Machine Learning Techniques

In this research, the adsorption performance of individual atoms on the surface of monolayer graphene surface was systematically investigated using machine learning methods to accelerate density functional theory. The adsorption behaviors of over thirty different atoms on the graphene surface were computationally analyzed. The adsorption energy and distance were extracted as the research targets, and the basic information of atoms (such as atomic radius, ionic radius, etc.) were used as the feature values to establish the dataset. Through feature engineering selection, the corresponding input feature values for the input-output relationship were determined. By comparing different models on the dataset using five-fold cross-validation, the mathematical model that best fits the dataset was identified. The optimal model was further fine-tuned by adjusting of the best mathematical ML model. Subsequently, we verified the accuracy of the established machine learning model. Finally, the precision of the machine learning model forecasts was verified by the method of comparing and contrasting machine learning results with density functional theory. The results suggest that elements such as Zr, Ti, Sc, and Si possess some potential in controlling the interfacial reaction of graphene/aluminum composites. By using machine learning to accelerate first-principles calculations, we have further expanded our choice of research methods and accelerated the pace of studying element–graphene interactions.
Patient, Caregiver and Regimen Characteristics Associated With Adherence to Highly Active Antiretroviral Therapy Among HIV-Infected Children and Adolescents

Background: This study assesses the relationship between child and caregiver perceptions of medication responsibility, disease knowledge, regimen complexity and adherence to highly active antiretroviral therapy among HIV-positive children. We also examine the association of adherence to child and caregiver demographic characteristics and surrogate markers of HIV disease. Methods: For this 6-month longitudinal study, 24 HIV-positive children (mean age = 14.0 years) being treated with highly active antiretroviral therapy and their caregivers completed measures of medication responsibility and disease knowledge. Medication Event Monitoring System caps calculated adherence across months 1 through 3 (time 1) and 4 through 6 (time 2). Results: Medication Event Monitoring System data revealed adherence rates of 81% at time 1 and 79% at time 2. Only 8% (n = 2) of child–caregiver pairs reported complete agreement regarding who held responsibility for medication-related tasks. Patients' responsibility for medication was correlated with age based on child (r = .51) and caregiver (r = .57; Ps < 0.05) perceptions, although their regimen knowledge was not. Greater regimen knowledge among caregivers and fewer child–caregiver discrepancies about medication responsibility predicted better adherence (adjusted R2 = .45). Finally, adherence was correlated with CD4 percentages at time 1 (r = .50) and viral load at time 1 (r = −.56) and time 2 (r= −.68; Ps < 0.05). Conclusions: Medication adherence among HIV-infected children is lower than required for optimal viral suppression. Adherence is related to surrogate markers of HIV disease but not to child or caregiver demographic variables. Responsibilities for medication-related tasks should be clarified among family members, regimen knowledge should be emphasized and caregivers should avoid assigning treatment responsibility to a child prematurely.
Assessing Text Semantic Similarity Using Ontology

Sentence and document similarity assessment is key to most NLP applications. This paper presents a novel measure of calculating the similarity between sentences or between documents using ontology. The similarity is assessed using sentence or document concept vector forming from finding the linkage between ontology terms and sentence or document content, the linage can be used to generate semantic indexes of sentences or document and apply them to implement highly efficient searching algorithms to compute sentence or document similarity, and the difference between the sentence and document similarity measurement is articulated. Results were verified through experiments. Experiments show that this technique is efficient and compares favorably to other similarity measures, and it is flexible enough to allow the user to make comparisons without any additional dictionary or corpus information. We believe that this method can be applied in a variety of text knowledge representation and discovery applications.
User-Specific Learning for Recognizing a Singer's Intended Pitch

We consider the problem of automatic vocal melody transcription: translating an audio recording of a sung melody into a musical score. While previous work has focused on finding the closest notes to the singer's tracked pitch, we instead seek to recover the melody the singer intended to sing. Often, the melody a singer intended to sing differs from what they actually sang; our hypothesis is that this occurs in a singer-specific way. For example, a given singer may often be flat in certain parts of her range, or another may have difficulty with certain intervals. We thus pursue methods for singer-specific training which use learning to combine different methods for pitch prediction. In our experiments with human subjects, we show that via a short training procedure we can learn a singer-specific pitch predictor and significantly improve transcription of intended pitch over other methods. For an average user, our method gives a 20 to 30 percent reduction in pitch classification errors with respect to a baseline method which is comparable to commercial voice transcription tools. For some users, we achieve even more dramatic reductions. Our best results come from a combination of singer-specific-learning with non-singer-specific feature selection. We also discuss the implications of our work for training more general control signals. We make our experimental data available to allow others to replicate or extend our results.
New Data on Boletaceae (Agaricomycetes, Basidiomycota) from Central Vietnam with Description of Two New Species and Creation of a New Combination Based on Morphological and Phylogenetic Evidence

Two new species of Boletaceae (Hortiboletus rubroreticulatus and Tylopilus aurantiovulpinus) discovered during an investigation of the mycobiota of Central Vietnam (Kon Chu Rang Nature Reserve; Ta Dung National Park; Bidoup—Nui Ba National Park; Kon Ka Kinh National Park) are described on the basis of molecular and morphological data. Illustrated descriptions of their macro- and microscopic features and discussion on similar taxa are given. Additionally, eight species which were recorded for the first time in Vietnam are listed and illustrated here. A new combination Kgaria virescens was made for one of these species. These results were confirmed by the phylogenetic analysis based on nrITS1-5.8S-ITS2, nrLSU, and tef1α regions.
Gallium Trichloride Fluid: Dimer Dissociation Mechanism, Local Structure, and Atomic Dynamics

Molten gallium trichloride emerges as a promising solvent for oxidative metal recycling. The use of supercritical fluid enhances the performance and kinetics of metal dissolution due to significantly lower viscosity in the reaction media. Additionally, the dual molecular nature of gallium trichloride, existing as edge-sharing ES-Ga2Cl6 dimers at low temperatures and high pressure, or flat trigonal GaCl3 monomers in the vicinity of the critical point and low pressures, creates the possibility to tailor the chemical geometry to a particular metallic species. Nevertheless, the mechanism of dimer dissociation, local structure, and atomic dynamics in supercritical gallium trichloride fluids are not known. Using first-principles molecular dynamics, validated by comparison with our high-energy X-ray diffraction results, we illustrate the elementary steps in dimer dissociation. These include the formation of intermediate corner-sharing CS-Ga2Cl6 dimers, the partial disproportionation of GaCl3 monomers at high temperatures and low pressures, changes in the local environment of molecular entities, and unusual atomic dynamics in supercritical fluids.
Multiple Molecular Pathways Are Involved in the Neuroprotection of GDNF Against Proteasome Inhibitor Induced Dopamine Neuron Degeneration In Vivo

The impairment of ubiquitin-proteasome system (UPS) is a cellular mechanism underlying the neurodegenerative process in Parkinson’s disease (PD). Glial cell line-derived neurotrophic factor (GDNF) is one of the most potent neurotrophic factors promoting the growth and survival of mesencephalic dopamine (DA) neurons. To investigate whether GDNF has neuroprotective effects in a PD model induced by UPS impairment we administered GDNF by osmotic pump in C57BL/6 mice after nigrostriatal lesions with stereotactic injection of proteasome inhibitor lactacystin in the middle forebrain bundle. We found that lactacystin injection severely injured the nigral DA neurons and reduced the striatal levels of DA and its metabolites, while prolonged administration of GDNF at a sustained moderate dose for two weeks can significantly attenuate the lactacystin-induced loss of nigral DA neurons and striatal DA levels by 31% and 40%, respectively. We also investigated the molecular mechanisms for the neuroprotective effects of GDNF showing that lactacystin administration can cause the phosphorylation of extracellular signal-regulated kinase (ERK), p38MAPK (p38), and the c-Jun N-terminal kinase (JNK), whereas GDNF treatment can further enhance the phosphorylation of ERK and Akt but reduce the levels of JNK and p38. These results indicate that prolonged treatment with GDNF can protect the nigral DA neurons from the UPS impairment-induced degeneration. Several signaling path-ways including p38, JNK, Akt and ERK molecules seem to play an important role in this neuroprotection by GDNF.
Nutrition and Cardiovascular Disease: Finding the Perfect Recipe for Cardiovascular Health

The increasing burden of cardiovascular disease (CVD) despite the progress in management entails the need of more effective preventive and curative strategies. As dietary-associated risk is the most important behavioral factor influencing global health, it appears the best target in the challenge against CVD. Although for many years, since the formulation of the cholesterol hypothesis, a nutrient-based approach was attempted for CVD prevention and treatment, in recent years a dietary-based approach resulted more effective in reducing cardiovascular risk worldwide. After the publication of randomized trials on the remarkable effects of the Mediterranean diet and the Dietary Approach to Stop Hypertension (DASH) diet on CVD, new efforts were put on research about the effects of complex dietary interventions on CVD. The purpose of this paper is to review the evidence on dietary interventions in the prevention and disease modification of CVD, focusing on coronary artery disease and heart failure, the main disease responsible for the enormous toll taken by CVD worldwide.
Block Region of Interest Method for Real-Time Implementation of Large and Scalable Image Reconstruction

In field programmable gate array (FPGA)-based reconstruction of high-resolution (several-gigabyte) images, architectures that store the entire source image in block memory are no longer feasible. In this letter, a block region of interest (ROI) method is proposed for large and scalable image reconstruction, using 2D 4 × 4 truncated sinc interpolation by storing only a slice of the source image in block memory. To ensure a high hit rate in block memory for interpolation and improve memory access efficiency, this method provides an effective criterion for partitioning, which subdivides the output image into blocks based on the ROI in the source image. Moreover, a special storage pattern is designed to simultaneously provide 16 pixels for each interpolation to enable real-time implementation by full pipelining with no memory data redundancy. The proposed method was validated by experimental results on an FPGA board along with the corresponding simulations on MATLAB. Various image sizes were tested to prove its flexibility. The time required to reconstruct an output image of 32 k × 32 k at 200 MHz was 2.79 s, thereby achieving a processing speed of 385 Mpixels/s in single floating point precision.
Crowdsourcing Quality Control for Item Ordering Tasks

One of the biggest challenges in crowdsourcing is quality control which is to expect high quality results from crowd workers who are not necessarily very capable nor motivated.In this paper, we consider item ordering questions, where workersare asked to arrange multiple items in the correct order. We propose a probabilistic generative model of crowd answers by extending a distance-based order model to incorporate worker ability, and give an efficient estimation algorithm.