Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Throat Length and Flow Parameters on a Venturi as an Aerator

Venturi system helps to air drawn into a flowing stream of water transferring the oxygen from air to water till they reach the water surface and burst due to Bernoulli’s principle in form of bubbles. The efficacy of venturi as an aeration device is primarily dependent on the geometry and the flow conditions prevailing inside. Presently, the diameter and placement of holes in a venturi under different flow conditions was studied to determine the performance of the venturi as an aerator. To evaluate the results, SOTR and SAE were calculated and compared for analyse their performance. The study involved selecting 5 different throat lengths each having multiple hole of 1 mm diameter. The hole distance from the start of the throat section, which has been characterised as the effective distance (ED) has been so selected that all the ED’s are different. The ED’s selected for study varied from 2 mm to 46 mm under three different discharges of 1.72 m3/h, 2.02 m3/h and 2.38 m3/h. Firstly, it was observed from the experiments that the venturi performs best when the ED is less. Secondly, it was also observed that both SOTR and SAE are more for higher discharge. Next, it was also found that increasing the throat length beyond a certain value has a negative effect on the SOTR and SAE. It was also observed that among all the possible combinations the best was for the 10 mm throat section with the hole situated just adjacent to the start of the throat section and performing at a high discharge.
Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files

Abstract Background Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. Findings In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)–based high-performance computing (HPC) implementation, and the popular VCFTools. Conclusions Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems.
Layer- and strain-dependent optoelectronic properties of hexagonal AlN

Motivated by the recent synthesis of layered hexagonal aluminum nitride ($h$-AlN), we investigate its layer- and strain-dependent electronic and optical properties by using first-principles methods. Monolayer $h$-AlN is a wide-gap semiconductor, which makes it interesting especially for usage in optoelectronic applications. The optical spectra of 1-, 2-, 3-, and 4-layered $h$-AlN indicate that the prominent absorption takes place outside the visible-light regime. Within the ultraviolet range, absorption intensities increase with the number of layers, approaching the bulk case. On the other hand, the applied tensile strain gradually redshifts the optical spectra. The many-body effects lead to a blueshift of the optical spectra, while exciton binding is also observed for 2D $h$-AlN. The possibility of tuning the optoelectronic properties via thickness and/or strain opens doors to novel technological applications of this promising material.
Early electrical field stimulation prevents the loss of spinal cord anterior horn motoneurons and muscle atrophy following spinal cord injury

Our previous study revealed that early application of electrical field stimulation (EFS) with the anode at the lesion and the cathode distal to the lesion reduced injury potential, inhibited secondary injury and was neuroprotective in the dorsal corticospinal tract after spinal cord injury (SCI). The objective of this study was to further evaluate the effect of EFS on protection of anterior horn motoneurons and their target musculature after SCI and its mechanism. Rats were randomized into three equal groups. The EFS group received EFS for 30 minutes immediately after injury at T10. SCI group rats were only subjected to SCI and sham group rats were only subjected to laminectomy. Luxol fast blue staining demonstrated that spinal cord tissue in the injury center was better protected; cross-sectional area and perimeter of injured tissue were significantly smaller in the EFS group than in the SCI group. Immunofluorescence and transmission electron microscopy showed that the number of spinal cord anterior horn motoneurons was greater and the number of abnormal neurons reduced in the EFS group compared with the SCI group. Wet weight and cross-sectional area of vastus lateralis muscles were smaller in the SCI group to in the sham group. However, EFS improved muscle atrophy and behavioral examination showed that EFS significantly increased the angle in the inclined plane test and Tarlov’s motor grading score. The above results confirm that early EFS can effectively impede spinal cord anterior horn motoneuron loss, promote motor function recovery and reduce muscle atrophy in rats after SCI.
Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space

Chronic and acute implants of multi-electrode arrays that cover several mm$^2$ of neural tissue provide simultaneous access to population signals like extracellular potentials and the spiking activity of 100 or more individual neurons. While the recorded data may uncover principles of brain function, its interpretation calls for multiscale computational models with corresponding spatial dimensions and signal predictions. Such models can facilitate the search of mechanisms underlying observed spatiotemporal activity patterns in cortex. Multi-layer spiking neuron network models of local cortical circuits covering ~1 mm$^2$ have been developed, integrating experimentally obtained neuron-type specific connectivity data and reproducing features of in-vivo spiking statistics. With forward models, local field potentials (LFPs) can be computed from the simulated spiking activity. To account for the spatial scale of common neural recordings, we extend a local network and LFP model to 4x4 mm$^2$. The upscaling preserves the neuron densities, and introduces distance-dependent connection probabilities and delays. As detailed experimental connectivity data is partially lacking, we address this uncertainty in model parameters by testing parameter combinations within biologically plausible bounds. Based on model predictions of spiking activity and LFPs, we find that the upscaling procedure preserves the overall spiking statistics of the original model and reproduces asynchronous irregular spiking across populations and weak pairwise spike-train correlations observed in sensory cortex. In contrast with the weak spike-train correlations, the correlation of LFP signals is strong and distance-dependent, compatible with experimental observations. Enhanced spatial coherence in the low-gamma band may explain the recent experimental report of an apparent band-pass filter effect in the spatial reach of the LFP.
Switching-Off Adora2b in Vascular Smooth Muscle Cells Halts the Development of Pulmonary Hypertension

Background: Pulmonary hypertension (PH) is a devastating and progressive disease characterized by excessive proliferation of pulmonary artery smooth muscle cells (PASMCs) and remodeling of the lung vasculature. Adenosine signaling through the ADORA2B receptor has previously been implicated in disease progression and tissue remodeling in chronic lung disease. In experimental models of PH associated with chronic lung injury, pharmacological or genetic inhibition of ADORA2B improved markers of chronic lung injury and hallmarks of PH. However, the contribution of ADORA2B expression in the PASMC was not fully evaluated. Hypothesis: We hypothesized that adenosine signaling through the ADORA2B receptor in PASMC mediates the development of PH. Methods: PASMCs from controls and patients with idiopathic pulmonary arterial hypertension (iPAH) were characterized for expression levels of all adenosine receptors. Next, we evaluated the development of PH in ADORA2Bf/f-Transgelin (Tagln)cre mice. These mice or adequate controls were exposed to a combination of SUGEN (SU5416, 20 mg/kg/b.w. IP) and hypoxia (10% O2) for 28 days (HX-SU) or to chronic low doses of bleomycin (BLM, 0.035U/kg/b.w. IP). Cardiovascular readouts including right ventricle systolic pressures (RVSPs), Fulton indices and vascular remodeling were determined. Using PASMCs we identified ADORA2B-dependent mediators involved in vascular remodeling. These mediators: IL-6, hyaluronan synthase 2 (HAS2) and tissue transglutaminase (Tgm2) were determined by RT-PCR and validated in our HX-SU and BLM models. Results: Increased levels of ADORA2B were observed in PASMC from iPAH patients. ADORA2Bf/f-Taglncre mice were protected from the development of PH following HX-SU or BLM exposure. In the BLM model of PH, ADORA2Bf/f- Taglncre mice were not protected from the development of fibrosis. Increased expression of IL-6, HAS2 and Tgm2 was observed in PASMC in an ADORA2B-dependent manner. These mediators were also reduced in ADORA2Bf/f- Taglncre mice exposed to HX-SU or BLM. Conclusions: Our studies revealed ADORA2B-dependent increased levels of IL-6, hyaluronan and Tgm2 in PASMC, consistent with reduced levels in ADORA2Bf/f- Taglncre mice exposed to HX-SU or BLM. Taken together, our data indicates that ADORA2B on PASMC mediates the development of PH through the induction of IL-6, hyaluronan and Tgm2. These studies point at ADORA2B as a therapeutic target to treat PH.
Hybrid precoding for mmWave massive MIMO systems with generalized triangular decomposition

Hybrid precoding schemes have recently gained a great attention for millimeter wave (mmWave) massive multiple-input-multiple-output (massive MIMO) communication systems because of offered cost and low-power consumption advantages. The singular value decomposition (SVD) method which is exploited in the design of hybrid precoding causes several problems on system design, especially on bit allocation, precoding and equalizing processes. On the other hand, the previous works show that generalized triangular decomposition (GTD) method can present asymptotically optimal performance in conventional MIMO systems. In the light of this, we propose the use of GTD method for designing hybrid precoding operating in mmWave massive MIMO systems. The proposed design is analyzed via performed simulation studies including different system configurations. Moreover, the archived results are compared with the standard orthogonal matching pursuit (OMP) algorithm based hybrid precoding scheme. The simulation results show that the proposed hybrid precoding scheme can reach up to the performance of optimal precoding scheme.
Physiological responses of drought stress in Tomato: A review

Tomato has important role in food and commercial utilization in the whole world. It is an undetached part of food due to its taste and nutritional value. It is full of minerals, vitamin and antibiotic characteristics. Climate change produces so many natural hazards such as abiotic and biotic stress in the plant. Drought is an important natural phenomenon which affects morphological, physiological, biochemical and yield attributes of plants leading to death. During water stress many physiological and molecular processes are disturbed such as root-shoot growth, water relation, mineral absorption, leaf expansion and orientation, stometal behavior, transpiration rate, photosynthesis and respiration rate, solute translocation, etc. Toxic elements such as reactive oxygen species (ROS) produced during stress period create oxidative damage to the cellular organization. Plants have its antioxidant system to scavenge such harmful element and accumulate osmoprotectants such as proline, glycien betaine, etc to maintain osmotic adjustment. All these and many more aspects have been discussed in case of tomato plants in this review.
TSPO–PET imaging using [18F]PBR06 is a potential translatable biomarker for treatment response in Huntington’s disease: preclinical evidence with the p75NTR ligand LM11A-31

Abstract Huntington’s disease (HD) is an inherited neurodegenerative disorder that has no cure. HD therapeutic development would benefit from a non-invasive translatable biomarker to track disease progression and treatment response. A potential biomarker is using positron emission tomography (PET) imaging with a translocator protein 18 kDa (TSPO) radiotracer to detect microglial activation, a key contributor to HD pathogenesis. The ability of TSPO–PET to identify microglial activation in HD mouse models, essential for a translatable biomarker, or therapeutic efficacy in HD patients or mice is unknown. Thus, this study assessed the feasibility of utilizing PET imaging with the TSPO tracer, [18F]PBR06, to detect activated microglia in two HD mouse models and to monitor response to treatment with LM11A-31, a p75NTR ligand known to reduce neuroinflammation in HD mice. [18F]PBR06-PET detected microglial activation in striatum, cortex and hippocampus of vehicle-treated R6/2 mice at a late disease stage and, notably, also in early and mid-stage symptomatic BACHD mice. After oral administration of LM11A-31 to R6/2 and BACHD mice, [18F]PBR06-PET discerned the reductive effects of LM11A-31 on neuroinflammation in both HD mouse models. [18F]PBR06-PET signal had a spatial distribution similar to ex vivo brain autoradiography and correlated with microglial activation markers: increased IBA-1 and TSPO immunostaining/blotting and striatal levels of cytokines IL-6 and TNFα. These results suggest that [18F]PBR06-PET is a useful surrogate marker of therapeutic efficacy in HD mice with high potential as a translatable biomarker for preclinical and clinical HD trials.
Collaborative Filtering Recommendation Based on All-Weighted Matrix Factorization and Fast Optimization

Collaborative filtering recommendation with implicit feedbacks (e.g., clicks, views, and plays) is regarded as one of the most challenging issues in both academia and industry. From implicit feedbacks, we can only get a small fraction of observed data (positive examples), and the massive unobserved data are the mixture of negative examples and unlabeled positive examples. However, most of the existing efforts either treat unobserved data equally by assigning a uniform weight or uniformly weight observed data while ignoring the hidden information (i.e., visit frequency) in implicit feedbacks. This assumption may not hold in real-life scenarios since they cannot distinguish the contributions of the whole data and it easily leads to prediction bias. Besides, those approaches still suffer from low-efficiency issue. To this end, we propose an all-weighted matrix factorization and fast optimization strategy for effective and efficient recommendation. We first design a frequency-aware weighting scheme for observed data and a user-oriented weighting scheme for unobserved data nonuniformly. Then, the weighting schemes of both observed and unobserved data are combined in a unified way to form an all-weighted matrix factorization model. Afterwards, we present a surrogate objective function and develop a fast optimization strategy to enhance the efficiency. Extensive experimental results on real-world datasets demonstrate that our method outperforms the competitive baselines on several evaluation metrics.
A new multi-port active DC-link for PMG-based WECSs

This paper presents the development and performance evaluation of a new active multi-port dc-link for applications in permanent magnet generator (PMG)-based wind energy conversion systems (WECSs). The proposed dc-link is developed as a mid-stage between a three phase (3φ) multilevel ac-dc generator-side power electronic converter (PEC) and a 3φ 6-pulse dc-ac grid-side PEC. The design of the dc-link is based on a multi-port converter (MPC) topology with two dc-dc PECs, which have their outputs connected in parallel. Each dc-dc PEC is operated and controlled independently, in order to achieve separate voltage-transfer ratios, along with the possibility of processing continuous or discontinuous input dc voltages. The performance of the MPC active dc-link is evaluated in experiments for a 7.5 kW PMG-based WECS under different operating conditions. Test results show that the proposed dc-link is capable of producing a high quality regulated dc voltage over a wide range of wind speeds, and increasing the extracted power from the PMG. Performance results also demonstrate that the operation of the MPC active dc-link has minor impacts on the harmonic distortion at the terminals of the PMG, along with negligible impacts on the operation and control of the grid-side PEC.
Two-Step Markov Update Algorithm for Accuracy-Based Learning Classifier Systems

In this paper, we investigate the impact of a two-step Markov update scheme for the reinforcement component of XCS, a family of accuracybased learning classifier systems. We use a mathematical framework using discrete-time dynamical system theory to analyze the stability and convergence of the proposed method. We provide frequency domain analysis for classifier parameters to investigate the achieved improvement of the XCS algorithm, employing a two-step update rule in the transient and steady-state stages of learning. An experimental analysis is performed to learn to solve a multiplexer benchmark problem to compare the results of the proposed update rules with the original XCS. The results show faster convergence, better steady-state training accuracy and less sensitivity to variations in learning rates.
Development of a signal generator for study programs dedicated to electronic engineering

In courses dedicated to electronic engineering, theoretical knowledge and hands-on exercises are mandatory. The University of Applied Sciences (UAS) Technikum Wien offers various bachelor degree programs focused on electronic engineering. These degree programs are available in the form of full-time and distance learning. Moreover, the university promotes these degree programs to be adaptable for handicapped students as well. Due to the fact, that distance-learning and handicapped students do not attend the university on a regular basis, it is necessary that they have the opportunity to complete their hands-on exercises and assignments at home. These tasks often require the measurement and analysis of analog- and digital circuits. In fact for this kind of tasks, it is necessary to have access to a signal generator. To be able to equip every student with this device, it is necessary to be affordable for the university. Another important aspect is that the application of the signal generator is operating-system independent and available to the open-source community to enable further development. This paper introduces the development of a low-cost, open-source soundcard based signal generator and its usage within courses. Furthermore, this paper will give an overview about the developed hardware component, the required software architecture and the arbitrary waveform generation.
A formação via PNQ e inserção produtiva dos CRAS: a reposição empobrecida e emergencial da qualificação de trabalhadores

Apresentamos aqui reflexoes sobre a formacao inicial e continuada dos trabalhadores que ocuparao as tarefas menos complexas do mundo do trabalho. Analisamos a execucao da qualificacao profissional iniciada e continuada de trabalhadores - terminologias contidas na Lei de Diretrizes e Bases da Educacao n. 9.494/96 - no Brasil contemporâneo, viabilizada atraves do Ministerio do Trabalho e Emprego, pela via do Plano Nacional de Qualificacao (PNQ). Nas margens dessa experiencia, apresentamos ainda a aprendizagem que objetiva a geracao de renda e a superacao da condicao de "assistido", denominada de insercao produtiva, executada nos Centros de Referencia da Assistencia Social (Cras), vinculados ao Ministerio do Desenvolvimento Social e do Combate a Fome.
Real-Time Guidance and Anatomical Information by Image Projection onto Patients

The Image Projection onto Patients (IPoP) system is work in progress intended to assist medical practitioners perform procedures such as biopsies, or provide a novel anatomical education tool, by projecting anatomy and other relevant information from the operating room directly onto a patient's skin. This approach is not currently used widely in hospitals but has the benefit of providing effective procedure guidance without the practitioner having to look away from the patient. Developmental work towards the alpha-phase of IPoP is presented including tracking methods for tools such as biopsy needles, patient tracking, image registration and problems encountered with the multi-mirror effect.
Past, present and future of gene expression-tailored therapy for lung cancer.

"Variability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions which we know as disease. " Sir William Osler (1849-1919). All human beings are different and some of these differences are the variations in response to xenobiotics. Personalized medicine means: the right patient population, the right drug, the right dose, the right indication, and administration at the right time. This review provides an update on concepts of personalized therapy for lung cancer.