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Lead poisoning remains the leading cause of diagnosed death for critically endangered California condors, which are annually monitored for lead exposure via blood tests. Blood tests are generally reflective of acute lead exposure. Since condors are victims to both chronic and acute lead exposure, measuring bone, which in humans is reflective of years to decades worth of exposure, is a valuable biomarker. In this study, we measured bone Pb of the tibiotarsus of 64 condors in vivo using a portable x-ray fluorescence device. The average uncertainty for measurements, typically reflective of how effective the device performed, was found to be 3.8 ± 2.2 µg/g bone mineral. The average bone lead level was found to be 26.7 ± 24.5 µg/g bone mineral. Bone lead correlated significantly with a sum of all blood lead measures over the lifetime of each condor. In the future, bone lead can potentially be used to inform treatment planning and address the chronic health implications of lead in the species. [ABSTRACT FROM AUTHOR]

The growing demand for high-quality video requires complex coding techniques that cost resource consumption and increase encoding time which represents a challenge for real-time processing on Embedded Systems. Kvazaar and x265 encoders are two efficient implementations of the High-Efficient Video Coding (HEVC) standard. In this paper, the performance of All Intra Kvazaar and x265 encoders on the Nvidia Jetson platform was evaluated using two coding configurations; highspeed preset and high-quality preset. In our work, we used two scenarios, first, the two encoders were run on the CPU, and based on the average encoding time Kvazaar proved to be 65.44% and 69.4% faster than x265 with 1.88% and 0.6% BD-rate improvement over x265 at high-speed and high-quality preset, respectively. In the second scenario, the two encoders were run on the GPU of the Nvidia Jetson, and the results show the average encoding time under each preset is reduced by half of the CPU-based scenario. In addition, Kvazaar is 54.5% and 56.70% faster with 1.93% and 0.45% BD-rate improvement over x265 at high-speed and high-quality preset, respectively. Regarding the scalability, the two encoders on the CPU are linearly scaled up to four threads and speed remains constant afterward. On the GPU, the two encoders are scaled linearly with the number of threads. The obtained results confirmed that, Kvazaar is more efficient and that it can be used on Embedded Systems for real-time video applications due to its high speed and performance over the x265 HEVC encoder [ABSTRACT FROM AUTHOR]

In the context of emergency response applications, real-time situational awareness is vital. Unmanned aerial vehicles (UAVs) with imagers have emerged as crucial tools for providing timely information in such scenarios. Convolutional neural networks (CNN) are effective in image processing. However, the deployment of CNN models in UAVs faces significant challenges. The CNN models involve large number of parameters and energy-costly floating-point computations beyond the memory and power available on-board the UAVs. To address these challenges, we propose a co-design optimization approach for deploying the EmergencyNet CNN model on resource-constrained UAVs. Our strategy includes channel-wise pruning to reduce the size and optimize the network architecture. Additionally, we apply additive powers-of-two (APoT) quantization to further compress the model and enhance computational efficiency. Using channel-wise network pruning we derive TinyEmergencyNet that is only 155KB in memory size and 50% smaller than EmergencyNet. This proposed approach is evaluated on Aerial Image Disaster Event Recognition (AIDER) dataset. We have achieved an F1-score of 93.6% with 4-bit APoT quantization that closely approaches the full precision (32-bit) accuracy of 94%. Furthermore, hardware-friendly bit-shifting operations as a result of APoT quantization present an added advantage in hardware accelerator implementations. This work pioneers the joint application of channel-wise pruning and non-uniform APoT quantization on EmergencyNet, presenting a suitable solution tailored for UAV-based emergency response applications. [ABSTRACT FROM AUTHOR]

New geochemical data of the Iron Oxide-Copper–Gold (IOCG) mineralization and its host rocks in the Dara area, North Eastern Desert of Egypt, are investigated for a better understanding of their petrogenesis. The host rocks are classified into metagabbro-diorite and I-type younger granitoids (monzogranite and alkali feldspar granites). The metagabbro-diorite rocks are volcanic arcs with calc-alkaline affinity and were generated by partial melting of mantle related to the subduction zone. The monzogranite and alkali feldspar granite are metaluminous to weakly peraluminous with calc-alkaline and highly fractionated I-type affinity, respectively. The monzogranite was suggested to be generated from the partial melting of the lower mafic crust, whereas the alkali feldspar granites were from the upper continental crust. IOCG mineralization at the Dara prospect is confined along contacts between the metagabbro-diorite and monzogranite rock types in the form of quartz and quartz-carbonate veins surrounded by alteration zones. The IOCG mineralization is structurally controlled where the quartz and quartz-carbonate veins follow rejuvenation NW–SE compressional Najd fault to E-W and NE-SW extensional fault systems. The hydrothermal mineralization consists of magnetite, hematite, specularite, quartz, calcite, chalcopyrite, minor pyrite, and native gold. Hydrothermal alteration is subdivided into inner sericite-rich and outer chlorite-rich zones. Chemical discrimination using CCPI (chlorite-carbonate-pyrite chemical index), AI (alteration index), and mass balance calculation suggests a redistribution of most elements during alteration without extensive elemental changes except for Eu and Ho. The field, mineralogical, and geochemical features advocated that the mineralization is akin to be related to the Iron Oxide-Cu-Au (IOCG) system that could be linked to the post-collisional tectonic setting of the Arabian-Nubian Shield (ANS). [ABSTRACT FROM AUTHOR]

Toxoplasma gondii (T. gondii) is a parasite that obtains the iron it needs for its own metabolism from the host-cell iron pool. In this work, we aimed to investigate if iron supplementation or deficiency affected the course of T. gondii infection. Eighty mice were divided into four groups, each with 20 animals: Group (I): Uninfected control group. Group (II): Infected control group: injected with Phosphate buffered saline. Group (III): Infected group: received iron sucrose treatment. Group (IV): Infected group: treated with deferoxamine. Quantitative PCR studies were performed on days 3 and 8 post-infection to detect the expression of iron metabolism genes (hamp and ferroprotin) and immune-histochemical analysis to study the percentage of TNF-α and TGF-β tissue expression. Iron supplementation induced progressions of infection evident by increased tissue expression of pro-inflammatory cytokine TNF-α and downregulation of TGF-β which is mostly linked to suppression of the inflammatory process caused by T. gondii. Increased expression of TGF-β and decreased expression of TNF-α was noticed when iron deprivation occurred. On day 3, we noticed increased expression in the hamp gene with iron supplementation while it decreases when the iron supply is low. On the contrary, iron deficiency increased ferroprotin gene expression whereas supplementing decreased it. On day 8, the level of expression of these genes returned to normal levels. These observations document the potential role of iron in controlling toxoplasmosis infection and indicate that the transcription of hamp and ferroprotin in T. gondii-infected cells appears to be regulated by a sophisticated indirect mechanism. [ABSTRACT FROM AUTHOR]

Background: Let-7 microRNAs (miRNAs) may contribute to neurodegeneration, including Alzheimer's disease (AD), but, they were not investigated in Streptozotocin (STZ)-induced AD. Letrozole increases the expression of Let-7 in cell lines, with conflicting evidence regarding its effects on memory. This study examined Let-7 miRNAs in STZ-induced AD, their correlation with memory and hyperphosphorylated Tau (p-Tau) and the effects of Letrozole on them. Methods: Seven groups of adult Sprague Dawley rats were used: Negative control, Letrozole, Letrozole Vehicle, STZ (with AD induced by intracerebroventricular injection of STZ in artificial cerebrospinal fluid (aCSF)), CSF Control, STZ + Letrozole (STZ-L), and CSF + Letrozole Vehicle. Alternation percentage in T-maze was used as a measure of working memory. Let-7a, b and e and p-Tau levels in the hippocampus were estimated using quantitative real-time reverse transcription–polymerase chain reaction (qRT–PCR) and enzyme-linked immunosorbent assay (ELISA), respectively. Results: Significant decreases in alternation percentage and increase in p-Tau concentration were found in the STZ, Letrozole and STZ-L groups. Expression levels of all studied microRNAs were significantly elevated in the Letrozole and the STZ-L groups, with no difference between the two, suggesting that this elevation might be linked to Letrozole administration. Negative correlations were found between alternation percentage and the levels of all studied microRNAs, while positive ones were found between p-Tau concentration and the levels of studied microRNAs. Conclusions: This study shows changes in the expression of Let-7a, b and e miRNAs in association with Letrozole administration, and correlations between the expression of the studied Let-7 miRNAs and both the status of working memory and the hippocampal p-Tau levels. These findings might support the theory suggesting that Letrozole aggravates pre-existing lesions. They also add to the possibility of Let-7's neurotoxicity. [ABSTRACT FROM AUTHOR]

The Video Coding Joint Collaboration team (JCT-VC) has been working on an emerging standard for screen content coding (SCC) as an extension of high efficiency video coding (HEVC) standard known as HEVC-SCC. The two powerful coding mechanisms used in HEVC-SCC are intra block copy (IBC) and palette coding (PLT). These techniques achieve the best coding efficiency at the expense of extremely high computational complexity. Therefore, we propose a new technique to minimize computational complexity by skipping undesired modes and retaining coding efficiency. A fast intra mode decision approach is suggested based on efficient CU classification. Our proposed solution depends on categorizing a CU as a natural content block (NCB) or a screen content block (SCB). Two classifiers are used for the classification process. The first one is a neural network (NN) classifier, and the other is an AdaBoost classifier, which depends on a boosted decision stump algorithm. The two classifiers predict the CU type individually and the final decision for CU classification depends on both of them. The experimental results reveal that the suggested technique significantly decreases encoding time without sacrificing coding efficiency. The suggested framework can achieve a 26.13% encoding time reduction on average with just a 0.81% increase in Bjontegaard Delta bit-rate (BD-Rate). Furthermore, the suggested framework saves encoding time by 51.5% on average for a set of NC sequences recommended for standard HEVC tests with minimal performance degradation. The proposed strategy has been merged with an existing methodology to accelerate the process even further. [ABSTRACT FROM AUTHOR]

The present article aims to shows that obtaining the best estimator does not depend on estimators' terms and functions. To prove this situation, it is shown that there is no difference between the existing estimators and the proposed estimator by proposing new sophisticated estimators. Besides, theoretical, graphical, empirical and simulation studies are conducted to confirm the efficiency of these proposed estimators with the help of the method used by Wolter (2007). Also, the MSE values are evaluated by using the power coefficient of the interested estimators. In data sets with the known correlation coefficient, it is possible to determine which power coefficient estimator is better without computing the MSE value. [ABSTRACT FROM AUTHOR]

A comprehensive reaction kinetics study was conducted on a new single phase acid system comprised of a pre-engineered blend of an alkyl sulfonic acid and a strong mineral acid. The experiments were performed at 3000 psi and temperature range (180–350°F) using a rotating disk apparatus. The diffusion coefficient was found to be similar to that of 15 wt% HCl-emulsified acid systems. The single phase acid is a blend of two aqueous acids; therefore, the preparation is fast, and the resulted quality is consistent. The low viscosity helps reduce friction losses when pumping at high rates through tubular, maximizing the downhole pressure. [ABSTRACT FROM AUTHOR]

The Screen Content Coding Extension in High-Efficiency Video Coding standard (HEVC-SCC) promotes the capabilities of HEVC in coding screen content videos (SCVs) using new techniques, which improves coding efficiency dramatically. These new techniques depend on the distinguished features of SCV such as repeated patterns, limited number of colors, sharp edges, and non-noisy regions. Nonetheless, this coding efficiency comes at the cost of enormous computational complexity. In this paper, a new technique is proposed to save encoding time while conserving coding efficiency. The proposed algorithm selects the suitable mode for each Coding Unit (CU) and skips unhelpful modes by two methods. Two methods depend on skipping unwanted modes by Neural Network Classifiers. The first classifier is Neural Network Classifier Based on Current Depth Features (NNC_CF), which depends on the CU current depth features. The second one is Neural Network Classifier Based on Parent Depth Features (NNC_PF); the Parent depth features are considered the input of this classifier. The simulation results demonstrate the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

Background: Human leukocyte antigen (HLA)-G molecule has been suggested to have a potential immunomodulatory role in multiple sclerosis (MS). Genetic variant sites of HLA-G molecule have been reported to be associated with autoimmune diseases. Identifying the genetic risk factors of MS may help in preventive strategies and anticipating disease progression. The aim of this work was to investigate the effect of HLA-G 14-base-pair insertion/deletion (14-bp INS/DEL) genetic polymorphism on MS risk and clinical characteristics and to observe the clinical characteristics of the MS patients' group. The study included 48 MS patients and 50 cross-matched healthy controls, who were recruited from Sohag and Assiut university hospitals. Genetic testing (14-bp Ins/Del gene polymorphism) using polymerase chain reaction (PCR) was performed for patients and control groups. All patients had a detailed clinical assessment and have undergone measurement of disability using the Expanded Disability Status Scale (EDSS). Results: No statistically significant difference was found between MS patients and healthy controls (HC) in genotypic and allelic frequencies of HLA-G 14-bp INS/DEL polymorphism (P=0.305). No significant association was found between HLA-G 14-bp INS/DEL polymorphism genotypes and clinical characteristics or degree of disability of MS patients. The most frequent presenting symptoms of MS were motor symptoms. Fatigue was the most reported symptom along the course of MS disease. Conclusion: Although it has been long known that HLA-G represents an important MS susceptibility locus, in this study, no significant relation could be detected between the 14-bp INS/DEL polymorphism genotype and MS susceptibility. MS risk susceptibility may be not linked to a single allele but may depend on the combination of different polymorphic genetic sites. In this study, the lack of genetic susceptibility may be attributed to ethnic factor. [ABSTRACT FROM AUTHOR]

Background: Detecting the genetic and physiological variations in two Japanese quail strains could be used to suggest a new avian model for future breeding studies. Consequently, two estimations were performed on two Japanese quail strains: gray quail strain (GJQS) and white jumbo quail strain (WJQS). The first estimation was conducted on carcass characteristics, breast muscles, breast concentration of collagen type I, and body measurements. In contrast, blood samples were collected for the second estimation for genomic DNA extraction and genetic analysis. Results: A total of 62 alleles out of 97 specific alleles (63.92%) were detected overall loci (14 microsatellite loci) for the two strains. A total of 27 specific alleles of WJQS were observed, and 35 were obtained for GJQS. The percentage of similarity was 48.09% ranged from 4.35 with UBC001 to 100% with GUJ0051. WJQS had greater body weights and a higher value of pectoral muscle and supracoracoideus muscle than GJQS. The breast muscles of GJQS exhibited a higher concentration of type I collagen than the WJQS. Furthermore, males showed higher concentrations of collagen type I than females. WJQS showed a higher body length, chest girth, chest length, thigh length, thigh girth, drumstick length, and drumstick girth (cm) than GJQS. WJQS showed more significant differences in carcass traits compared with GJQS. Conclusion: The physiological differences between WJQS and GJQS were ascertained with microsatellite markers, which indicated high polymorphism between these strains. These observations provided a scientific basis for evaluating and utilizing the genetic resources of WJQS and GJQS in a future genetic improvement program. [ABSTRACT FROM AUTHOR]

Anther culture is the most effective tool for doubled haploid production of wheat. This investigation was conducted to estimate genetic parameters of anther culture response in wheat and identification of putative Quantitative trait loci (QTLs) associated with response traits. Two varieties of wheat, namely ICR-DH (P1) and Sle 1 × 15 (P2) and their F1 and F2 progenies were used in the present investigation to estimate genetic parameters of anther culture response. Two molecular marker systems, SRAP and SSR markers were used to detect the polymorphism between two anther donor parents. Single marker analysis (SMA) and Composite interval mapping (CIM) were used to localize the putative QTL associated with four anther culture response in wheat using 100 plants of F2 population derived from F1 cross 'ICR-DH' × 'Sel 1 × 15'. Analyses of variance indicated significant differences between four populations (P1, P2, F1 and F2) for callus induction (CAL), number of green plants per 100 anther (GR), number of albino plant per 100 anther (AR) and total regenerated plants per 100 anther (TR). The additive effects were more important than dominance effects in controlling these traits. The two molecular marker systems were sufficient in detecting polymorphism between two parents. Thirty two putative QTLs were detected on eight linkage groups. Our study indicated that the additive effects of genes and detection of new QTLs permit marker-assisted selection of genotypes with high green plantlet regeneration efficiency in anther culture, and therefore favor efficient use of anther culture in wheat breeding programs [ABSTRACT FROM AUTHOR]

Post-stroke cognitive impairment (PSCI) is a major source of disability, affecting up to two thirds of stroke survivors with no available therapeutic options. The condition remains understudied in preclinical models due to its delayed presentation. Although hypertension is a leading risk factor for dementia, how ischemic stroke contributes to this neurodegenerative condition is unknown. In this study, we used a model of hypertension to study the development of PSCI and its mechanisms. Spontaneously hypertensive rats (SHR) were compared to normotensive rats and were subjected to 1-h middle cerebral artery occlusion or sham surgery. Novel object recognition, passive avoidance test and Morris water maze were used to assess cognition. In addition, brain magnetic resonance images were obtained 12-weeks post-stroke and tissue was collected for immunohistochemistry and protein quantification. Stroked animals developed impairment in long-term memory at 4-weeks post-stroke despite recovery from motor deficits, with hypertensive animals showing some symptoms of anhedonia. Stroked SHRs displayed grey matter atrophy and had a two-fold increase in apoptosis in the ischemic borderzone and increased markers of inflammatory cell death and DNA damage at 12 weeks post-stroke. This indicates that preexisting hypertension exacerbates the development of secondary neurodegeneration after stroke beyond its acute effects on neurovascular injury. [ABSTRACT FROM AUTHOR]

With the recent advances in the deep learning field, the use of deep convolutional neural networks (DCNNs) in biomedical image processing becomes very encouraging. This paper presents a new classification model for breast cancer masses based on DCNNs. We investigated the use of transfer learning from AlexNet and GoogleNet pre-trained models to suit this task. We experimentally determined the best DCNN model for accurate classification by comparing different models, which vary according to the design and hyper-parameters. The effectiveness of these models were demonstrated using four mammogram databases. All models were trained and tested using a mammographic dataset from CBIS-DDSM and INbreast databases to select the best AlexNet and GoogleNet models. The performance of the two proposed models was further verified using images from Egyptian National Cancer Institute (NCI) and MIAS database. When tested on CBIS-DDSM and INbreast databases, the proposed AlexNet model achieved an accuracy of 100% for both databases. While, the proposed GoogleNet model achieved accuracy of 98.46% and 92.5%, respectively. When tested on NCI images and MIAS databases, AlexNet achieved an accuracy of 97.89% with AUC of 98.32%, and accuracy of 98.53% with AUC of 98.95%, respectively. GoogleNet achieved an accuracy of 91.58% with AUC of 96.5%, and accuracy of 88.24% with AUC of 94.65%, respectively. These results suggest that AlexNet has better performance and more robustness than GoogleNet. To the best of our knowledge, the proposed AlexNet model outperformed the latest methods. It achieved the highest accuracy and AUC score and the lowest testing time reported on CBIS-DDSM, INbreast and MIAS databases. [ABSTRACT FROM AUTHOR]

A disabling consequence of stroke is cognitive impairment, occurring in 12%–48% of patients, for which there is no therapy. A critical barrier is the lack of understanding of how post-stroke cognitive impairment (PSCI) develops. While 70% of stroke victims present with comorbid diseases such as diabetes and hypertension, the limited use of comorbid disease models in preclinical research further contributes to this lack of progress. To this end, we used a translational model of diabetes to study the development of PSCI. In addition, we evaluated the application of compound 21 (C21), an angiotensin II Type 2 receptor agonist, for the treatment of PSCI by blinding the treatment assignment, setting strict inclusion criteria, and implementing a delayed administration time point. Diabetes was induced by a high-fat diet (HFD) and low-dose streptozotocin (STZ) combination. Control and diabetic rats were subjected to 1 h middle cerebral artery occlusion (MCAO) or sham surgery. Adhesive removal task (ART) and two-trial Y-maze were utilized to test sensorimotor and cognitive function. Three days post-stroke, rats that met the inclusion criteria were administered C21 or vehicle in drinking water at a dose of 0.12 mg/kg/day for 8 weeks. Samples from freshly harvested brains were analyzed by flow cytometry and immunohistochemistry (IHC). Diabetes exacerbated the development of PSCI and increased inflammation and demyelination. Delayed administration of C21 3 days post-stroke reduced mortality and improved sensorimotor and cognitive deficits. It also reduced inflammation and demyelination through modulation of the M1:M2 ratio in the diabetic animals. [ABSTRACT FROM AUTHOR]

Vaccinating dogs against rabies is an effective means of reducing human rabies. We subjected 1327 clinically diagnosed human rabies death and mass dog vaccination (MDV) data during 2006–2018 to quantify the impacts of MDV on human rabies incidence in Bangladesh and a subset of rabies death data (422) for clinico-epidemiological analysis. A positive and increasing trend of MDV (p = 0.01 and tau = 0.71) and a negative and declining trend (p < 0.001 and tau = −0.88) of human rabies cases (Correlation coefficient: −0.82) have been observed. Among 422 deaths, the majority (78%) of the victims sought treatment from traditional healers, and 12% received post-exposure prophylaxis (PEP). The mean incubation period of rabies in cases with exposure sites on the head & neck (35 days) was shorter than the upper limb (mean = 64 days, p = 0.02) and lower limb (mean = 89 days, p < 0.01). MDV has been found to be effective for reducing human rabies cases in Bangladesh. Creating awareness among the animal bite victims to stop reliance on traditional healers rather seeking PEP, addressing the role of traditional healers through awareness education programme with respect to the treatment of dog bites, ensuring availability of PEP, and continuing to scale up MDV may help to prevent human rabies deaths. [ABSTRACT FROM AUTHOR]

Detection of breast cancer masses in mammogram images is an essential step in any computer-aided system for breast cancer diagnosis. In this paper, we propose a novel technique for breast cancer masses detection in mammograms based on the feature matching of different regions using Maximally Stable Extremal Regions (MSER). Firstly, a pre-processing step is applied to the original mammogram image to produce an enhanced version of this image. Then, MSER regions are extracted from both the original image and its enhanced version using MSER detector. Finally, feature matching process is applied between these regions to detect the mass area. The proposed algorithm has been tested on a collected set of 300 mammogram images containing abnormalities (i.e. benign and malignant masses) from four different databases. The proposed algorithm is able to accurately detect locations of masses with an accuracy of 95%. There aren't any processing steps for pectoral muscle removal, this results in reducing the processing time. The average time taken by the proposed method to process one mammogram image is 0.14 s. The proposed method is fully automated and there is no need for user intervention or any readjustment. The proposed algorithm is robust against noise and it is not affected by the image quality, breast density category, or mass nature. The results show that the proposed algorithm has higher accuracy than the state of the art approaches. [ABSTRACT FROM AUTHOR]

False discrimination between earthquakes and quarry blasts may lead to an unrealistic characterization of the natural seismicity of a region. The similarity in seismograms between earthquakes and quarry blasts is the primary reason for incorrect discrimination. Therefore, in this paper, we propose a discriminative algorithm utilizing wavelet filter bank to extract unique features between earthquakes and quarry blasts. The discriminative features are found to be in the first five seconds after the onset time. The proposed algorithm is divided into two stages: first, wavelet filter bank extracts the features of the seismic signals; then, support vector machine classifies the event based on these extracted features. The proposed algorithm achieves a discrimination accuracy of 98.5% when applied to 900 earthquakes and quarry blast waveforms. [ABSTRACT FROM AUTHOR]

Advanced motion vector prediction (AMVP) is a new technique adopted in the latest high efficiency video coding (HEVC) standard. AMVP block predicts an initial motion vector of the current block from a given set of candidates by means of rate distortion (RD) optimization process. Due to the large number of different-sized blocks, simplification of RD optimization process in AMVP block is highly appreciated. Therefore, we present a new RD optimization technique for AMVP block in HEVC encoder. The proposed RD calculation approach finds the best AMVP candidate by processing less number of feature pixels per every block. Experimental results show notable speedup in terms of AMVP processing time with tolerable quality degradation (PSNR) and bitrate requirement. The proposed RD calculation technique reduces the RD computational complexity of the AMVP block by 87.5% as maximum (i.e. 1.7% of the whole encoder complexity). This improvement is accompanied with a modest average PSNR loss of 0.10 dB and an increase by 2.4% in terms of bitrate. On the other hand, we present an FPGA-based architecture for AMVP unit in HEVC encoder. The proposed architecture was prototyped, simulated and synthesized on Xilinx Virtex-7 XC7VX550T FPGA. At 188 MHz clock frequency, the proposed architecture processes 8 K (7680 $$\times $$ 4320) YCrCb resolution at 60 fps while utilizing less than 1% of the FPGA resources. [ABSTRACT FROM AUTHOR]

A multilayered neural network is a multi-input, multi-output nonlinear system in which network weights can be trained by using parameter estimation algorithms. In this paper, a novel training method is proposed. This method is based on the relatively new smooth variable structure filter (SVSF) and is formulated for feed-forward multilayer perceptron training. The SVSF is a state and parameter estimation that is based on the sliding mode concept and works in a predictor-corrector fashion. The SVSF training performance is tested on three benchmark pattern classification problems. Furthermore, a study is presented comparing the popular back-propagation method, the extended Kalman filter, and the SVSF. [ABSTRACT FROM AUTHOR]

This paper proposes a new algorithm for Arabic optical font recognition (AOFR) as the first stage for Arabic optical character recognition. The proposed algorithm uses scale-invariant detector, gradient-based descriptor, and k-means clustering. The scale-invariant detector is used to find key points that identify the font of an image of printed Arabic text. The work in this paper compares between several scale-invariant detectors and selects the best one for AOFR. A gradient-based descriptor similar to the one in the famous scale-invariant feature transform algorithm is used to describe the detected key points. In addition, k-means clustering is used for font classification. In this paper, the mean recognition rate is used to evaluate the performance of the proposed algorithm. The proposed algorithm shows superior performance when compared with recently published algorithms for AOFR. [ABSTRACT FROM AUTHOR]

Shoot and root attributes are essential for plant performance in agriculture. Here, we report detection and validation of quantitative trait loci (QTL) for shoot and root traits in 301 BCDH lines achieved by crossing cultivar Scarlett and wild barley accession ISR42-8. Phenotypic evaluations were made for six traits across 3 years under control and drought conditions. QTL analysis was performed using 371 DNA markers genotyped by different protocols, such as sequence repeats, diversity array technology as well as gene-specific markers. Marker by trait analysis revealed 33 QTL of which 15 and 18 QTL showed trait-improving effects of the exotic and elite alleles, respectively. Two major QTL for plant height (PH) were found on chromosome 2H ( QPh.S42.2H) and 3H ( QPh.S42.3H. b). The strongest QTL QSdw.S42.5H for increasing shoot dry weight was associated with an exotic allele on chromosome 5H. QTL QTkw.S42.1H underlie a novel exotic allele that improved thousand kernel weight. Seven QTL were associated with root dry weight of which at four loci introgression of exotic alleles enhanced traits values. The strongest QTL QRdw.S42.7H was linked to a gene-specific marker VrnH3 on chromosome 7H. At QRl.S42.5H, the exotic allele accounted for a 9 % increase in root length. In addition, 18 epistatic interactions were linked to PH, shoot and root dry weights. QTL validation was performed with 53 introgression lines (ILs) carrying ISR42-8 introgressions in the Scarlett background. Nine novel QTL alleles of exotic origin were validated in the isogenic background. These QTL-bearing ILs provide valuable genetic resources for plant breeding and positional cloning of the underlying genes. [ABSTRACT FROM AUTHOR]

This paper presents interpolation-free fractional-pixel motion estimation (FME) algorithms and efficient hardware prototype of one of the proposed FME algorithms. The proposed algorithms use a mathematical model to approximate the matching error at fractional-pixel locations instead of using the block matching algorithm to evaluate the actual matching error. Hence, no interpolation is required at fractional-pixel locations. The matching error values at integer-pixel locations are used to evaluate the mathematical model coefficients. The performance of the proposed algorithms has been compared with several FME algorithms including the full quarter-pixel search (FQPS) algorithm, which is used as part of the H.264 reference software. The computational cost and the performance analysis show that the proposed algorithms have about 90% less computational complexity than the FQPS algorithm with comparable reconstruction video quality (i.e., approximately 0.2 dB lower reconstruction PSNR values). In addition, a hardware prototype of one of the proposed algorithms is presented. The proposed architecture has been prototyped using the TSMC 0.18 μm CMOS technology. It has maximum clock frequency of 312.5 MHz, at which, the proposed architecture can process more than 70 HDTV 1080p fps. The architecture has only 13,650 gates. The proposed architecture shows superior performance when compared with several FME architectures. [ABSTRACT FROM AUTHOR]

Tyrosinase is a key enzyme in melanin synthesis. Owing to enlargement of availability of edible types of mushrooms in food medicines, we investigated effects of Agaricus blazei (ABE) on tyrosinase activity using l-tyrosine and l-3, 4-dihydroxyphenylalanine ( l-DOPA) as the substrate in normal human epidermal melanocytes (NHEM). ABE inhibited tyrosinase activity similar to arbutin and Vitamin C as two whitening agents in a dose dependent manner. In agreement with this, treatment of the cells with ABE (3-100 μg/ml) reduced melanin content up to 57% of the control in NHEM. In addition, production of nitric oxide (NO) which has the ability of inducing tyrosinase activity in melanocytes was also suppressed by ABE treatment. Furthermore, ABE inhibited NO production in lipopolysaccharides (LPS)-stimulated RAW264.7 macrophages, in a dose dependent manner but without affecting iNOS mRNA expression indicated by reverse transcription-PCR (RT-PCR) technique. These findings suggest that ABE inhibits melanin production via partial inhibition of tyrosinase activity and NO production. This hypopigmenting effect of water soluble Agaricus blazei extract could be useful for the treatment of some skin disorders. [ABSTRACT FROM AUTHOR]

This paper presents a Computational Memory architecture for MPEG-4 applications with mobile devices. The proposed architecture is used for real-time block-based motion estimation, which is the most computational intensive task in the video encoder. It uses the exhaustive block-matching algorithm (EBMA) for motion estimation. The proposed architecture consists of embedded SRAMs and a number of block-matching units working in parallel to process video data while stored in the memory. The block-matching units access the embedded SRAMs simultaneously, which increases the speed of the architecture. The architecture processes CIF format video sequences (i.e., the frame size is 352 × 288 pixels) with block size of 16 × 16 pixels and ±15 pixels search range. The proposed architecture has been designed, prototyped, and simulated for 0.18 μm TSMC CMOS technology. The simulation shows that the proposed architectures processes up to 126 CIF frames per second with clock frequency 100 MHz. The synthesized prototype of the proposed architecture includes 200 KB memory and it has an area of 33.75 mm2 and consumes 986.96 mW @100 MHz. [ABSTRACT FROM AUTHOR]

Alternative splicing is dysregulated in cancer and the reactivation of telomerase involves the splicing of TERT transcripts to produce full-length (FL) TERT. Knowledge about the splicing factors that enhance or silence FL hTERT is lacking. We identified splicing factors that reduced telomerase activity and shortened telomeres using a siRNA minigene reporter screen and a lung cancer cell bioinformatics approach. A lead candidate, NOVA1, when knocked down resulted in a shift in hTERT splicing to non-catalytic isoforms, reduced telomerase activity, and progressive telomere shortening. NOVA1 knockdown also significantly altered cancer cell growth in vitro and in xenografts. Genome engineering experiments reveal that NOVA1 promotes the inclusion of exons in the reverse transcriptase domain of hTERT resulting in the production of FL hTERT transcripts. Utilizing hTERT splicing as a model splicing event in cancer may provide new insights into potentially targetable dysregulated splicing factors in cancer. Splicing of the telomerase transcript, hTERT, can be altered in cancer cells. Here the authors report NOVA1, as a splicing regulator that directly interacts with hTERT pre-mRNA enhancing the number of full-length transcripts and thus telomerase activity in lung cancer cells. [ABSTRACT FROM AUTHOR]