Miracle-dz/UniFAR-FTUs huggingface dataset:
Circulating microRNAs in osteoporosis

Osteoporosis is the most common age-related bone disease. It is clinically symptomless until the first fracture happens and once diagnosed it is often found to be associated with low bone mineral density (LBMD) of T-Score ≤ -2.5. Circulating microRNAs (miRNAs) have been used successfully as promising biomarkers to diagnose and assess the progression of complex diseases such as cancer and cardiovascular diseases, as well as the effectiveness of treatment. This research aims to identify circulatory miRNAs associated with the progression of osteoporosis in a test group of patients using advanced PCR arrays initially and the identified differentially-expressed miRNAs were validated in individual clinical specimens using RT-qPCR. The potential target genes were analyzed using bioinformatics tools. Ethical approval was obtained prior to patient recruitment. A total of 161 participants were recruited and assigned to five groups: Non-Osteoporosis control group (T-Score ≥-1), osteopenia (T-Score -2.5 SD), osteopenia with fracture (T-Score -2.5 SD), osteoporosis (T-Score ≤ -2.5 SD) and osteoporosis with fracture (T-Score ≤ -2.5 SD). RNAs were extracted and analyzed from all serum and plasma samples. A panel of 49 differentially expressed miRNAs (up or down by >3 fold) between osteopenia and osteoporosis patient groups was identified using a miRNA PCR Array. Six miRNAs: miR-215-5p, miR-99a-5p, miR-100, miR-373-5p, miR-4516 and miR-122-5P, were significantly differentially-expressed between osteoporosis and osteopenia patients by initial RT-qPCR screening. Further analysis showed that the levels of circulating miRNAs: hsa-miR-373-5p, hsa-miR-122-5p and hsa-miR-215-5p and plasma hsa-4516 were associated with fragility fracture, and correlated with low bone mineral density. The results suggest that these miRNAs could be potential diagnostic biomarkers for osteoporosis in the future. Potential target genes of these miRNAs were also analyzed using bioinformatics tools. The project demonstrated that circulating miRNAs can be purified from serum and plasma and could be developed as critical diagnostic tools for osteoporosis.
Assessment of CT Saturation Caused By Switching Transient

This paper presents an approach for assessment of effect of different switching transient on current transformer saturation. This has been achieved by wavelet transform. Secondary signal of current transformer is captured and decomposed wherefrom approximate and detail coefficients have been estimated. Then different useful parameter like Skewness of approximate and detail coefficients are determined. Simulated result shows significant changes of those values for different conditions, wherefrom, saturation of current transformer is detected and switching time corresponding to the switching transients at the primary side which causes the saturation is assessed.
Negative Similarities

Two experiments were carried out for the present investigation. The first experiment was an exact replication of an experiment by Ekman (1955), where the subjects had been requested to estimate positive similarity between pairs of emotional terms. The second experiment was carried out in the same way except that the subjects were also requested to give negative estimations when they considered that a pair of words described feelings which were opposite to each other. Using factor analysis it was found that the negative estimations obtained in the second experiment were represented as zero ratings in the first one. The second experiment also yielded some additional information which was considered to be psychologically meaningful. A reanalysis of Ekman's data (1955) gave almost exactly the same result as the first experiment in the present study.
Cellular Neural Networks with Switching Two Templates by Local Features of Neighborhood

Cellular Neural Networks (CNN) was introduced by L. O. Chua and L. Yang in 1988 [1]. The idea of CNN was inspired from the architecture of the cellular automata and Neural Network. CNN consists of analog circuit and it is capable of high-speed parallel processing. CNN has local connectivity property and its structure resembles the retina of human. Hence, CNN has been successfully used for various high-speed parallel signals processing applications such as image processing, pattern recognition and so on [2]. The performance of CNN depends on the parameters which is called the template. The template represents strength of connection between cells. If the template influences exactly, CNN can perform complex processing. In image processing of CNN, it is difficult to process complex parts of the input image; edge, background, etc. In this study, we propose a CNN method of switching two templates by using the maximum and the minimum output values surrounding the center cell. We apply the proposed method to some image processing and investigate its performance.
Fuzzy/PSO Based Washout Filter for Inertial Stimuli Restitution in Flight Simulation

—The aim of this study is to present a new approach using Particle Swarm Optimization (PSO) algorithm and fuzzy logic for motion cueing considering both the physical limits of restitution platforms and realistic sensations. We added the necessary software in order to restitute the speciﬁc force based on a virtual aircraft. We used Microsoft Flight Simulator software (MSFS) and built-in data structure and methods. Results using the overall simulation are presented and evaluated on a motion platform. Interesting sensations have been recorded, which enhance the realism of the simulation. The obtained results indicate that the proposed PSO/Fuzzy approach improves the performance of the classical washout ﬁlter based motion cueing algorithm.
Production, purification and characterization of tannase from Aspergillus tamarii

The production of tannases by Aspergillus tamarii was evaluated in submerged cultures using tannic acid and gallic acid as substrates. Two tannases, designated as TAH I and TAH II were produced in gallic acid submerged cultures. TAH I, responsible for 70% of the total tannase activity was purified to apparent electrophoretic homogeneity with 18.35% yield. The enzyme is a homodimeric protein with molecular mass of 180 kDa and 40.5% of its weight corresponds to carbohydrates. TAH I exhibited optimal activity at 30°C and pH 5.5 and was stable over a large pH range (3.0 to 9.0) and at temperatures up to 40°C. With methyl gallate as substrate, the enzyme presented a K M of 0.77 mM and a V max of 682.8 U/mg proteins. The enzyme was inhibited by metal ions but showed relative resistance to organic solvents and surfactants. Since the enzyme is active over a wide range of pH and temperature, it is potentially useful in food and pharmaceutical industries. Key words : Aspergillus tamarii , enzyme purification, submerged culture, tannase.
Seria Fizică MODELS IN SPINTRONICS: DRUDE, MOTT, GIANT MAGNETORESISTANCE AND VALET-FERT, SPIN TRANSFER AND TORQUE

1. Giant Magnetoresistance in metallic multilayers: Introduction, spin-dependent scattering, simple picture with resistance model: Giant magnetoresistance (GMR) was discovered in 1988 [1]. Very quickly, it was understood that GMR originates from spin-dependent scattering due to different density of states at Fermi levels for spin up and spin down electrons. A simple resistance model based on Mott’s twocurrent model was proposed to qualitatively explain the phenomenon Modeling the in-plane transport (CIP: Current-in-plane) with Boltzmann equation, application to spin-valves GMR can be measured in two geometries: Current-in-plane (CIP) or current-perpendicular-toplane (CPP) as illustrated below.
Integrated Control-Fluidic Codesign Methodology for Paper-Based Digital Microfluidic Biochips

Paper-based digital microfluidic biochips (P-DMFBs) have recently emerged as a promising low-cost and fast-responsive platform for biochemical assays. In P-DMFBs, electrodes and control lines are printed on a piece of photograph paper using an inkjet printer and carbon nanotubes (CNTs) conductive ink. Compared with traditional digital microfluidic biochips (DMFBs), P-DMFBs enjoy significant advantages, such as faster in-place fabrication with printer and ink, lower costs, and better disposability. Since electrodes and CNT control lines are printed on the same side of this paper, a critical design challenge for P-DMFB is to prevent control interference between moving droplets and the voltages on CNT control lines. Control interference may result in unexpected droplet movements and thus incorrect assay outputs. To address this design challenge, a control-fluidic codesign methodology is proposed in this paper, along with two demonstrative design flows integrating both fluidic design and control design, i.e., the droplet-oriented codesign flow and the electrode-oriented codesign flow. The droplet-oriented flow is suitable for designing biochips with sparse electrodes and relatively larger number of droplets, whereas the electrode-oriented flow is suitable for biochips with dense electrodes and smaller number of droplets. The computational simulation results of real-life bioassays demonstrate the effectiveness of the proposed codesign flows.
Growth of Verticillium dahliae Kleb. hyphae and of bacteria along the roots of rape (Brassica napus L.) seedlings

Bacterial density and the hyphal density of Verticillium dahliae were determined along the roots of sand-grown rape seedlings. Verticillium dahliae microsclerotia were trapped in nylon nets which were placed in front of the growing root tip. The growing hyphae on the nets were stained with fluorescein diacetate and rhodamine B isothiocyanate. Bacteria on the petri dish lids adjacent to the nets were stained with acridine orange. Both fungal and bacterial densities increased exponentially over a distance of 15–20 mm from the root tip. Further back along the root, the densities of microorganisms stabilized, but in some cases the fluorescein diacetate active hyphal density increased. The hyphal densities stopped increasing before bacterial densities, suggesting an increasing bacterial competition for root exudates as their population grew. The hyphal activity, measured as the proportion of flurescein diacetate to rhodamine B isothioicyanate stained hyphae, increased during the exponential growth phase of the bacteria, then decreased, and finally increased again as the lateral roots appeared. (Less)
Improving Drought Tolerance by Exogenous Application of Glycinebetaine and Salicylic Acid in Sunflower

Water shortage is a severe threat to the sustainability of crop production. Exogenous application of glycinebetaine (GB) and salicylic acid (SA) has been found very effective in reducing the adverse affects of drought stress. This study was conducted to examine the possible role of exogenous GB and SA application in improving the yield of hybrid sunflower (Helianthus annuus L.) under different irrigation regimes. There were three levels of irrigation, viz. control (normal irrigations), water stress at vegetative stage (irrigation missing at vegetative stage) and water stress at flowering stage (irrigation missing at flowering stage). GB and SA were applied exogenously at 100 and 0.724 mm, respectively, each at the vegetative and at the flowering stage. Control plants did not receive application of GB and SA. Water stress reduced the head diameter, number of achene, 1000-achene weight, achene yield and oil yield. Nevertheless, exogenous GB and SA application significantly improved these attributes under water stress. However, drought stress increased the free leaf proline and GB, and were further increased by exogenous application of GB and SA. However, exogenous GB application at the flowering stage was more effective than other treatments. Oil contents were also reduced under water stress; however, GB and SA application could not ameliorate the negative effect of water stress on achene oil contents. The effects of water stress and foliar application of GB were more pronounced when applied at the flowering stage than at the vegetative stage. Moreover, exogenous GB application was only beneficial under stress conditions.
PERFORMANCE OF DIFFERENT FADING CHANNEL OVER SVD DETECTION BASED SPECTRUM SENSING IN COGNITIVE RADIO NETWORK

One of the most challenging issues in cognitive radio system is to sense the spectrum environment accurately and determine whether the primary user is active, or not over a specific band reliably. So, there is need of good sensing algorithm have the property have low sensing time, ability to detect primary signal at low SNR. In this paper, Singular Value Decomposition (SVD) spectrum sensing methodologies for cognitive radio are studied over different fading channels as AWGN channel, Rayleigth fading channel, Rician fading channel & Nakagami Fading Channel Energy detection method is classical method of detection but it requires knowledge of noise power for signal detection and it gives poor performance under low SNR The proposed detection method overcomes the drawback of energy detection method. SVD does not require the knowledge of signal properties, channel and uncertainty noise parameter in such a way it is suitable for blind spectrum sensing. Threshold is computed using random matrix theory (RMT) is exploited to formulate the detection method depending on sample covariance matrix of received signal. The Singular Value Decomposition (SVD) based detection algorithm is simulated by using MATLAB Software Platform. In this Paper, Simulation Result shows that SVD algorithm using Covariance matrix approach over Nakagami fading channel gives approx. 0.025 to 0.035 better performance of detection at low SNR with compare to reference AWGN & other different fading channel.
Ethnic Enclaves and Self-employment among Middle Eastern Immigrants in Sweden – Ethnic Capital or Enclave Size?

We employ geocoded data to explore the effects of ethnic enclaves in Swedish<br>cities on the propensity of Middle Eastern immigrants to use business<br>ownership as a vehicle to transcend from labor market outsiders to insiders. We<br>demonstrate a robust tendency for immigrants to leave non-employment for<br>self-employment if many co-ethnic peers in the enclave are business owners,<br>while we observe weak effects emanating from business owners in other<br>groups. Net of these effects, overall enclave size, measured by the local<br>concentration of co-ethnic peers, has a negative influence on the propensity for<br>an outsider to become self-employed.
Effect of Perches and Stocking Density on Tibial Dyschondroplasia and Bone Mineralization as Measured by Bone Ash in Broiler Chickens

SUMMARY Exercise through perching has been suggested as a method to reduce the impact of leg problems in broiler chickens. The goal of this research was to determine the effects of stocking density and perch availability on the incidence of tibial dyschondroplasia (TD) and the level of bone ash in broiler chickens. The incidence of TD was lowest in birds raised at the higher densities with 20 and 15 birds/m 2 and highest at stocking densities of 10 birds/m 2 . This pattern was positively correlated with the perching frequency of chickens, as observed at the different experimental densities and reported previously. Except for controls, which had no TD lesions compared to birds with access to perches, TD incidence was lowest in pens with horizontal perches and highest in pens with a combination of horizontal and sloping perches. These differences were not statistically significant. Percentage bone ash was lower in birds with TD than in normal birds (P < 0.05). Bone ash was not affected by stocking density or perch treatment. TD incidence was similar for both sexes; however, percentage bone ash was significantly lower in males than in females (P < 0.02). These results suggest that TD and faster growth rate in males may have a negative impact on bone mineralization in broiler chickens. However, it is unclear from our results whether providing broilers with access to perches can actually improve bone mineralization or prevent TD.
Alleviation of nickel toxicity in wheat (Triticum aestivum L.) seedlings by selenium supplementation

Abstract Hydroponically grown wheat seedlings were treated with 50 μM N i and/or 15 μM Se. After a 7-day culture period, their growth parameters, N i, Se, F e, and M g contents, electrolyte leakage, photosynthetic pigment concentrations, and photochemical activity of photosystem II were determined. Exposure of wheat seedlings to N i alone resulted in reduction in the total shoot and root lengths, by 22% and 50%, respectively. Addition of Se to the N i-containing medium significantly improved the growth of these organs, compared to the seedlings subjected to N i alone. Application of Se decreased the accumulation of N i in shoots and roots and partially alleviated the N i-induced decrease in F e and M g concentations in shoots. Electrolyte leakage increased in response to N i stress, but in shoots it was diminished by Se supplementation. Exposure to N i led to a decrease in chlorophyll a and b contents and enhancement of chlorophyll a/b ratio, but did not influence the concentration of carotenoids. Enrichment of the N i-containing medium with Se significantly increased chlorophyll b content, compared to the seedlings treated with N i alone. Photochemical activity, estimated in terms of the maximum quantum yield of photosystem II , decreased in response to N i treatment but was significantly improved by simultaneous addition of Se. Results of our study suggest that alleviation of N i toxicity in wheat seedlings by Se supplementation may be related to limitation of N i uptake.
Web Based Digital Image Processing Tool for Body Shape Detection

Digital image processing technique is used in many application areas; whereas use of this method for body shape detection can be proposed as a new approach. 3D body scanners are used to get 3D copies of human bodies, and by using these copies measurements of human body can be extracted, which help to identify body shapes. However, body scanners are still expensive and difficult to access for everyone. In this study, a method is proposed to identify female body shapes from a 2D image taken by a conventional camera for the use of clothing industry. Front body shapes are detected with image processing by capturing photographs of human subjects. The photographs are taken with a conventional camera in home environment, and then female body shapes are categorized with the proportions of front body widths. This method is also integrated with a web based application.
DRL360: 360-degree Video Streaming with Deep Reinforcement Learning

360-degree videos have gained more popularity in recent years, owing to the great advance of panoramic cameras and head-mounted devices. However, as 360-degree videos are usually in high resolution, transmitting the content requires extremely high bandwidth. To protect the Quality of Experience (QoE) of users, researchers have proposed tile-based 360-degree video streaming systems that allocate high/low bit rates to selected tiles of video frames for streaming over the limited bandwidth. It is challenging to determine which tiles should be allocated with a high/low rate, because (1) the video playbacks include too many features that dynamically change over time when making the rate allocation; (2) most of the state-of-the-art systems focus on a fixed set of heuristics to optimize a specific QoE objective, while users may have various QoE objectives that need to be optimized in different ways. This paper presents a Deep Reinforcement Learning (DRL) based framework for 360-degree video streaming, named DRL360. The DRL360 framework helps improve the system performance by jointly optimizing multiple QoE objectives across a broad set of dynamic features. The DRL-based model adaptively allocates rates for the tiles of the future video frames based on the observations collected by client video players. We compare the proposed DRL360 to the existing systems by trace-driven evaluations as well as conducting a realworld experiment over a wide variety of network conditions. Evaluation results reveal that DRL360 can adapt to all considered scenarios, and outperform the state-of-the-art approaches by 20%–30% on average given different QoE objectives.
Degradation of Trace Ibuprofen in Water by a Novel Adsorption- Desorption-Biodegradation Process

The objective of this study is to test the feasibility of the adsorption-desorptionbiodegradation (ADB) process for the removal of trace organics in water, exemplified by ibuprofen, a well-known emerging contaminants frequently found in wastewater effluents. In adsorption, activated carbon (F-400) is employed to adsorb ibuprofen. Then, ozonated water produced by the micro-bubble reactor is injected to the column to remove ibuprofen by oxidative desorption. Finally, the desorbed solution is fed to a bioreactor to further remove residual organic byproducts. The rationale behind the ADB concept is to effectively treat concentrated ibuprofen, to efficiently minimize ozone usage, and to produce byproducts eligible for low-cost biodegradation. In experiments, adsorption isotherms at pH 5, 7, and 9 have been obtained, and desorption efficiencies at these respective pHs have also been tested. It was found that at pH 7, a desorption efficiency of over 90% can be achieved. In addition, the rate of biodegradation is significantly enhanced as a result of ozonation treatment. A mineralization of 72% was attained. From our results, it seems promising that this easy and low-cost ADB process can be used in future water reclamation processes when trace emerging contaminants are of high concerns.
Artificial intelligence and machine learning in spine research

Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, and many other fields in which the availability of automated solution may benefit the accuracy and repeatability of the execution of critical tasks. In this narrative review, we first present a brief description of the various techniques that are being developed nowadays, with special focus on those used in spine research. Then, we describe the applications of AI and ML to problems related to the spine which have been published so far, including the localization of vertebrae and discs in radiological images, image segmentation, computer‐aided diagnosis, prediction of clinical outcomes and complications, decision support systems, content‐based image retrieval, biomechanics, and motion analysis. Finally, we briefly discuss major ethical issues related to the use of AI in healthcare, namely, accountability, risk of biased decisions as well as data privacy and security, which are nowadays being debated in the scientific community and by regulatory agencies.