Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of Different Window Functions for STDFT Based Exon Prediction Technique Taking Paired Numeric Mapping Scheme

During the last two decades, significant progresses have been made on advancing potential DNA sequencing techniques that generate huge amount of genomic data. Consequently, a great deal of research is being focused on investigating these data using mathematical and computational tools. Short time discrete Fourier transform (STDFT) is often used for spectral analysis of genomic signals that further help in retrieving useful information of molecular biology such as locating protein coding regions i.e. exons in a eukaryotic genome. However, identification accuracy of STDFT based exon prediction technique is highly influenced by the background noise present in its spectrum which sometimes masks the distinctive period-3 feature of protein-coding regions. Selection of proper window function play vital role in background noise reduction and therefore it is important to evaluate the performance of different window functions for exon predictions. Earlier, Voss mapping is used by researchers to test the window performances which is computationally costly and less informative. In this paper, performance of five important window functions is tested on different genes using paired numeric (PN) mapping scheme which is comparatively more advanced and computationally efficient than Voss mapping. Results are compared in terms of two parameters i.e. signal to noise ratio (SNR) and area under the ROC curve (AUC). It is found that the use of the Blackman window provides better prediction performance than other window functions with paired numeric mapping scheme. MATLAB 2013a is used for the simulation process.
Combining Satellite Imagery and Open Data to Map Road Safety

Improving road safety is critical for the sustainable development of cities. A road safety map is a powerful tool that can help prevent future traffic accidents. However, accurate mapping requires accurate data collection, which is both expensive and labor intensive. Satellite imagery is increasingly becoming abundant, higher in resolution and affordable. Given the recent successes deep learning has achieved in the visual recognition field, we are interested in investigating whether it is possible to use deep learning to accurately predict road safety directly from raw satellite imagery. To this end, we propose a deep learning-based mapping approach that leverages open data to learn from raw satellite imagery robust deep models able to predict accurate city-scale road safety maps at an affordable cost. To empirically validate the proposed approach, we trained a deep model on satellite images obtained from over 647 thousand traffic-accident reports collected over a period of four years by the New York city Police Department. The best model predicted road safety from raw satellite imagery with an accuracy of 78%. We also used the New York city model to predict for the city of Denver a city-scale map indicating road safety in three levels. Compared to a map made from three years' worth of data collected by the Denver city Police Department, the map predicted from raw satellite imagery has an accuracy of 73%.
Investigation of Skewing Effects on the Vibration Reduction of Three-Phase Switched Reluctance Motors

Switched reluctance motors (SRMs) are gaining in popularity because of their robustness, low cost, and excellent high-speed characteristics. However, they are known to cause vibration and noise primarily due to the radial pulsating force resulting from their double-saliency structure. This paper investigates the effect of skewing the stator and/or rotor on the vibration reduction of the three-phase SRMs by developing four 12/8-pole SRMs, including a conventional SRM, a skewed rotor-SRM (SR-SRM), a skewed stator-SRM (SS-SRM), and a skewed stator and rotor-SRM (SSR-SRM). The radial force distributed on the stator yoke under different skewing angles is extensively studied by the finite-element method and experimental tests on the four prototypes. The inductance and torque characteristics of the four motors are also compared, and a control strategy by modulating the turn-ON and turn-OFF angles for the SR-SRM and the SS-SRM are also presented. Furthermore, experimental results validate the numerical models and the effectiveness of the skewing in reducing the motor vibration. Test results also suggest that skewing the stator is more effective than skewing the rotor in the SRMs.
Large-scale PV Voltage Regulation: Survey of Recent Practice

Large-scale PV system is increasingly being installed in transmission and sub-transmission network around the world. It is anticipated that this trend will continue with the advancement of power electronic devices and the lower cost of such devices. This paper provides a literature survey of large-scale PV interconnection standards and voltage control issues in the large interconnected power system. The literature indicates a clear progression from theoretical research to practical implementation regarding voltage regulation by the PV system. There is already the practical implementation of a number of interconnection standards and voltage control in proto-type large-scale PV system. However, the advanced voltage control algorithms are still in the research stage. As a conclusion, this paper identifies some open questions that remain to be tackled by researchers and control and operation engineers.
Hybrid Isolator for Mutual-Coupling Reduction in Millimeter-Wave MIMO Antenna Systems

A novel millimeter-wave (MMW) hybrid isolator is presented to reduce the mutual-coupling (MC) between two closely-spaced dielectric resonators (DR) antennas at 60 GHz. The proposed hybrid isolator consists of a combination of a new uni-planar compact electromagnetic band-gap (EBG) structure and an MMW choke absorber. The design of the proposed EBG unit-cell is based on the stepped-impedance resonator (SIR) technique. The results show that the proposed EBG structure provides a wide frequency bandgap in the 60 GHz band with miniaturization factors of 0.79 and 0.66 compared to conventional uni-planar EBG and uni-planar compact (UC-EBG) structures, respectively. The proposed EBG is then placed between two Multiple-Input Multiple-Output (MIMO) DR antennas to reduce the MC level. As a result, an average of 7 dB level reduction is obtained. To further reduce the MC level, a thin MMW choke absorber wall is mounted vertically between the two DR antennas and above the EBG structure. An average of 22 dB MC reduction is achieved over the suggested bandwidth while maintaining good radiation characteristics. The measured isolation of the prototype antenna varies from −29 to −49 dB in the frequency range from 59.3 to 64.8 GHz. In fact, the proposed hybrid isolator outperforms other hybrid isolation techniques reported in the literature.
Attention Dense-U-Net for Automatic Breast Mass Segmentation in Digital Mammogram

Breast mass is one of the most distinctive signs for the diagnosis of breast cancer, and the accurate segmentation of masses is critical for improving the accuracy of breast cancer detection and reducing the mortality rate. It is time-consuming for a physician to review the film. Besides, traditional medical segmentation techniques often require prior knowledge or manual extraction of features, which often lead to a subjective diagnosis. Therefore, developing an automatic image segmentation method is important for clinical application. In this paper, a fully automatic method based on deep learning for breast mass segmentation is proposed, which combines densely connected U-Net with attention gates (AGs). It contains an encoder and a decoder. The encoder is a densely connected convolutional network and the decoder is the decoder of U-Net integrated with AGs. The proposed method is tested on the public and authoritative database—Digital Database for Screening Mammography (DDSM) database. F1-score, mean intersection over union, sensitivity, specificity, and overall accuracy are used to evaluate the effectiveness of the proposed method. The experimental results show that dense U-Net integrated AGs achieve better segmentation results than U-Net, attention U-Net, DenseNet, and state-of-the-art methods.
Evaluation of BFRP RC beams under flexure

This paper aims to study the flexural behavior of concrete beams reinforced with the newly revealed BFRP bars. A four-point loading setup was utilized to conduct flexure tests on three concrete beams reinforced longitudinally with 2 #10, 2 #12, and 3 #16 BFRP bars. The concrete used to cast the beams had a compressive strength of 30 MPa, and the beams were over-reinforced in design to ensure concrete compression failure before FRP bar rupture. The effect of the BFRP reinforcement ratio on the flexure response of BFRP RC beams were scrutinized in terms of the moment versus mid-span deflection response, the load at first concrete crack (cracking moment), stiffness, ultimate moment capacity, ductility and failure modes. The test results showed that the beam with the highest reinforcement ratio had the highest capacity, while the beams with the lowest reinforcement ratio had the highest mid-span deflection. Also, the non-linear increasing trend of the ultimate moment capacity with reinforcement ratio matched the ACI 440 equation. These test results will be utilized as a control for a long-term durability study on the performance of BFRP bars exposed to harsh environments.
VM-aware Flush Mechanism for Mitigating Inter-VM I/O Interference

Consolidating multiple servers into a physical machine is now commonplace in cloud infrastructures. The virtualized systems often arrange virtual disks of multiple virtual machines (VMs) on the same underlying storage device while striving to guarantee the performance service level objective (SLO) for each VM. Unfortunately, sync operations called by a VM make it hard to satisfy the performance SLO by disturbing I/O activities of other VMs. We reveal that the disk cache flush command is a root cause of this problem and present a novel VM-aware flush mechanism, called vFLUSH, which supports the VM-based persistency control of the disk cache flush command. Our evaluation shows that vFLUSH reduces the average latency of disk cache flush commands by up to 52.0% and improves the overall I/O performance by up to 59.6% on real workloads.
Performance Modulation for Back-Illuminated AlGaN Ultraviolet Avalanche Photodiodes Based on Multiplication Scaling

Back-illuminated Al0.1Ga0. 9N ultraviolet avalanche photodiodes (APDs) of various multiplication widths were fabricated on AlN templates with a separate absorption and multiplication structure. The impacts of an increased multiplication scale on a device performance were investigated. The avalanche breakdown voltage was found to increase as the multiplication layer thickness (MLT) increases. The APD with 230-nm-MLT achieved a superior maximum multiplication gain of 5.4 × 104, higher than that obtained in devices with 150-nm- and 300-nm-MLT. Theoretical simulations demonstrated that the critical electric field intensity in an avalanche region would decrease as the rising of MLT, indicating the modulating ability of multiplication scaling on the AlGaN APD performance. In addition, APDs fabricated on different AlN templates were employed to study the effects of crystalline quality on device properties.
High-affinity phosphate-binding protein (PBP) for phosphorous recovery: proof of concept using recombinant Escherichia coli.

Phosphorus (P) is a critical, non-renewable nutrient; yet excess discharges can lead to eutrophication and deterioration of water quality. Thus, P removal from water must be coupled with P recovery to achieve sustainable P management. P-specific proteins provide a novel, promising approach to recover P from water. Bacterial phosphate-binding proteins (PBPs) are able to effectively remove phosphate, achieving extremely low levels in water (i.e. 0.015 mg-P L-1). A prerequisite of using PBP for P recovery, however, is not only removal, but also controlled P release, which has not yet been reported. Phosphate release using recombinant PBP-expressing Escherichia coli was explored in this study. Escherichia coli was genetically modified to overexpress PBP in the periplasmic space. The impacts of ionic strength, temperature and pH on phosphate release were assessed. PBP-expressed E. coli demonstrated consistently superior ability to adsorb more phosphate from liquid and release more phosphate under controlled conditions relative to negative controls (unexpressed PBP E. coli and E. coli K12). Lower pH (3.8), higher temperature (35ºC) and higher ionic strength (100 mM KCl) facilitated increased phosphate release, providing a maximum of 2.1% P recovery within 3 h. This study provides proof of concept of the feasibility of using PBP to recover P.
Znf703, a novel target of Pax3 and Zic1, regulates hindbrain and neural crest development in Xenopus

The transcription factors Pax3 and Zic1 are critical to specify the neural plate border and to promote neural crest formation. In a microarray screen designed to identify genes regulated by Pax3 and Zic1 in Xenopus we isolated Znf703/Nlz1 a transcriptional repressor member of the NET (NocA/Nlz, Elbow, and TLP‐1) protein family. At early neurula stage znf703 is expressed in the dorsal ectoderm, spanning the neural plate and neural plate border, with an anterior boundary of expression corresponding to rhombomeres 3 and 4 (r3/r4) in the prospective hindbrain. As a bonafide target of Pax3 and Zic1, znf703 is activated by neural plate border inducing signals, and its expression depends on Pax3 and Zic1 function in the embryo. Znf703 morpholino‐mediated knockdown expanded several posterior hindbrain genes, while Znf703 overexpression completely obliterated the expression of these segmental genes, signifying that the transcriptional repressor activity of Znf703 is critical to pattern the hindbrain. Furthermore, snai2 and sox10 expression was severely impaired upon manipulation of Znf703 expression levels in the embryo suggesting that Znf703 participates in neural crest formation downstream of Pax3 and Zic1 in Xenopus.
Analyzing Real and Fake users in Facebook Network based on Emotions

Fake profile detection is one of the critical problems in Online Social Networks (OSNs). So far, studies have mainly focused on profile-based, behavioral-based, network-based and content-based attributes. However, user sentiments have not been explored along this domain. In the present study, we proposed the fake profile detection model that incorporates sentiment-based attributes to differentiate real and fake OSN profiles. The study is grounded in the fact that the posts of real users reveal varied categories of emotions such asjoy, sad, angry, fear, etc. based on their life experiences. On the contrary, fake users share posts to accomplish a specific purpose, and therefore, it is highly likely that their post content will contain similar types of emotions. The experiments are conducted on the posts of Facebook users. The detection model is trained on 12 emotion-based attributes including Plutchik’s eight basic emotions, positivity and negativity. Furthermore, a noise removal technique is presented to remove the outliers from the dataset. Finally, several machine learning techniques including Support Vector Machine (SVM), Naive Bayes, JRip and Random Forest have been used to train the detection model.
A Multiclass Retrial System with Coupled Orbits and Service Interruptions: Verification of Stability Conditions

In this work, we investigate the stability conditions of a multiclass retrial system with coupled orbit queues and service interruptions. We consider a single server system accepting $N$ classes of customers according to independent Poisson inputs and with class-dependent, arbitrarily distributed service times. An arriving customer who finds the server unavailable upon arrival, joins the corresponding orbit queue according to its class. We assume that the first (oldest) blocked customer in an orbit queue attempts to connect with the server after an exponentially distributed service time, which depends both on its class, and on the current state (busy or idle) of the other orbit queues. During service times, interruptions occur according to class-dependent Poisson process, following by class-dependent arbitrarily distributed setup times. We consider both preemptive-repeat identical, and preemptive-resume interruptions. Potential applications of such a system can be found in the modelling of relay-assisted cooperative wireless networks. We focus on the non-symmetrical orbits and perform simulation experiments for the system with three classes of customers to verify stability conditions for both types of the server interruptions.
An Exploratory Study to Investigate Citizens' Experience with E-Government Mobile Services in Saudi Arabia

Governments around the globe have started to utilize technology to deliver government services to their stakeholders by means of e-government. E-government ensures delivery of more effective and efficient public services in easier and more convenient forms. Recent developments in technology provide new ways for citizens to interact with their government. In addition, the innovative expansion of smart phones has motivated governments to deliver their services through mobile platforms. In Saudi Arabia, many organizations offer their services to citizens through mobile applications. However, citizens' experience with governmental mobile applications is still unknown. Experience, as reflected in the way people describe their interaction, is a crucial factor in designing that interaction. Following a review of the relevant literature, and considering the current mobile applications available, this paper explores and investigates empirically citizens' experience of interacting with mobile government e-services in Saudi Arabia. The study involves 33 interviews, using an interpretive approach for data collection and analysis. Findings from the empirical study have revealed a number of factors which may influence citizens' experience. The most obvious finding to emerge from the study is that, although citizens support the shift towards delivery of mobile government services, evidence shows that mobile applications cannot be considered a primary channel of interaction with the government. The study contributes to knowledge by providing new and fresh insights about how citizens interact with government mobile services. Results from this study will help mobile e-services designers to understand the situation in relation to citizens in Saudi Arabia, and can also be invoked in the case of other, similar states.
Study of the Data Exchange Between Programmable Logic and Processor System of Zynq-7000 Devices

Zynq-7000 devices from Xilinx has gained strong popularity in the last years. Several documents and examples about interfaces usage and how to communicate the programmable logic with the processor are available, but some of them are not properly explained and in particular, the maximum throughput is not clearly specified. With this purpose, in this work a measurement method is presented and applied over the five available interfaces, considering the most used alternatives. Tests were carried on a Zybo board, but the results can be easily used to estimate the performance of others systems setups. Special hardware features and functionality are also discussed, providing a better understanding of system performance. Related papers were studied but none of them presents comparable information as to provide a fair comparison.
Effects of rehabilitative exercise on peripheral muscle TNF&agr;, IL-6, IGF-I and MyoD expression in patients with COPD

Background: Skeletal muscle wasting commonly occurs in patients with chronic obstructive pulmonary disease (COPD) and has been associated with the presence of systemic inflammation. This study investigated whether rehabilitative exercise training decreases the levels of systemic or local muscle inflammation or reverses the abnormalities associated with muscle deconditioning. Methods: Fifteen patients with COPD (mean (SE) forced expiratory volume in 1 s 36 (4)% predicted) undertook high-intensity exercise training 3 days/week for 10 weeks. Before and after the training programme the concentration of tumour necrosis factor &agr; (TNF&agr;), interleukin-6 (IL-6) and C-reactive protein (CRP) in plasma was determined by ELISA, and vastus lateralis mRNA expression of TNF&agr;, IL-6, total insulin-like growth factor-I (IGF-I) and its isoform mechanogrowth factor (MGF) and myogenic differentiation factor D (MyoD) were assessed by real-time PCR. Protein levels of TNF&agr;, IGF-I and MyoD were measured by Western blotting. Results: Rehabilitation improved peak exercise work rate by 10 (2%) (p = 0.004) and mean fibre cross-sectional area from 4061 (254) &mgr;m2 to 4581 (241) &mgr;m2 (p = 0.001). Plasma inflammatory mediators and vastus lateralis expression of TNF&agr; and IL-6 were not significantly modified by training. In contrast, there was a significant increase in mRNA expression of IGF-I (by 67 (22)%; p = 0.044), MGF (by 67 (15)%; p = 0.002) and MyoD (by 116 (30)%; p = 0.001). The increase observed at the mRNA level was also seen at the protein level for IGF-I (by 72 (36)%; p = 0.046) and MyoD (by 67 (21)%; p = 0.012). Conclusions: Pulmonary rehabilitation can induce peripheral muscle adaptations and modifications in factors regulating skeletal muscle hypertrophy and regeneration without decreasing the levels of systemic or local muscle inflammation.
Effectiveness of Computer games of Emotion Regulation on Social skills of Children with Intellectual Disability

Students with Intellectual Disability have problems in social skills. As a medium for rehabilitation/therapy of these students, a computer game (Emo Galaxy) was designed to help these children in practicing their emotion recognition and regulation. The effectiveness of this intervention was evaluated by a quasi-experimental research with pretest-post-test evaluation, and a control group. 20 students participated in this study from which 10 students were randomly selected to receive the intervention while the rest, i.e. the control group, did not receive any intervention. Teacher form of the Social Skills Rating Scale (Gresham and Elliott, 1990) was used to measure their social skills before and after intervention. The obtained data were analyzed using Analysis of the Covariance. The results showed significant differences ($\boldsymbol{p} < 0.05$) between the experimental and the control group in social skills. At the end, using emotion recognition and regulation games for improving social skills was discussed. Further discussions as well as suggestions for future research are presented.
Epidemiology of Hymenoptera allergy

Purpose of reviewEpidemiology and especially the natural history of Hymenoptera allergy form the background that is essential to improving the clinical management of insect venom allergic patients. This review focuses on the emergence of recent data which could help provide further enlightenment in this field. Recent findingsThe latest data on the extent of the disease, the risk factors for sensitization and for local, systemic and fatal reactions after a hymenoptera sting are reviewed. The emerging problems concerning asymptomatic sensitization, the meaning of constitutively elevated tryptase serum levels and the persisting widespread poor awareness of available therapies in Hymenoptera allergic patients are particularly emphasized. SummaryThe assessment of the risk for systemic reaction in skin-positive subjects with a negative case history, and the suggestion of the baseline serum tryptase level as a risk factor for reaction severity after a sting, are the most important clinical implications of the latest studies. The genetic and environmental factors involved in the persistence of venom specific immunoglobulin E after a sting and the factors which orient towards a systemic or a large local reaction after apparently the same sting remain open questions.