Miracle-dz/UniFAR-FTUs huggingface dataset:
Grounded theory method of research: A practical application

In 1996 Maree, Joubert and Prinsloo identified the grounded theory method of research as a workable research method for criminological research. They gave an exposition of the methodological substructure that illustrated a tapestry of different scientific philosophical perspectives, such as the qualitative approach, interactionistic perspective (symbolic interactionism) and the grounded theory approach.
Spectrum fitting to improve the vertical resolution of ground penetrating radar

The resolution restricts the resolving power of ground penetrating radar. Based on the analyses results of thin layer reflection wave, a spectrum fitting method is been presented to improve the vertical resolution of GPR. At first, the reflection from three-layer media is been studied, and then the four-layer spectrum transmission function is been built. The spectrum of detecting wave is been fit by computing reflection wave spectrum of different thickness layers. According to the curve of fitting error, the thickness of target layer can be picked up. This method avoids the vices of traditional deconvolution. By dealing with the simulation data and experiment data, the effectiveness of this method to improve the vertical resolution of GPR is been proved.
Multiple P-TEFbs cooperatively regulate the release of promoter-proximally paused RNA polymerase II

The association of DSIF and NELF with initiated RNA Polymerase II (Pol II) is the general mechanism for inducing promoter-proximal pausing of Pol II. However, it remains largely unclear how the paused Pol II is released in response to stimulation. Here, we show that the release of the paused Pol II is cooperatively regulated by multiple P-TEFbs which are recruited by bromodomain-containing protein Brd4 and super elongation complex (SEC) via different recruitment mechanisms. Upon stimulation, Brd4 recruits P-TEFb to Spt5/DSIF via a recruitment pathway consisting of Med1, Med23 and Tat-SF1, whereas SEC recruits P-TEFb to NELF-A and NELF-E via Paf1c and Med26, respectively. P-TEFb-mediated phosphorylation of Spt5, NELF-A and NELF-E results in the dissociation of NELF from Pol II, thereby transiting transcription from pausing to elongation. Additionally, we demonstrate that P-TEFb-mediated Ser2 phosphorylation of Pol II is dispensable for pause release. Therefore, our studies reveal a co-regulatory mechanism of Brd4 and SEC in modulating the transcriptional pause release by recruiting multiple P-TEFbs via a Mediator- and Paf1c-coordinated recruitment network.
Smart and Automatic Car Parking Through Obstacle Detection and Motion Identification

This paper introduces an intelligent parking slot detection and tracking with ARM7LPC2148 microcontroller. The parking problem in big cities, especially the mega-cities, has become one of the key causes of the city traffic congestion. The Vacant Parking slot detection and tracking is considered to be an effective way to improve parking situation. The parking slot occupancy classification stage identifies vacancies of detected parking slots using ultrasonic sensor data. Parking slot occupancy is probabilistically calculated by treating each parking slot region as a single cell of the occupancy grid. The parking slot marking tracking stage continuously estimates the position of the selected parking slot while the ego-vehicle is moving into it. In the experiments, it is shown that the proposed method can recognize the positions and occupancies of various types of parking slot markings and stably track them under practical situations in a real-time manner. The proposed system is expected to help drivers conveniently select one of the available parking slots and support the parking control system by continuously updating the designated target positions. Keyword: LPC2148, ZIGBEE, RFID READER, REFLECTION SENSORS, WIFI.
Computational studies to investigate the fuel feeding point in fluidized bed reactor

As the world is concerned with the dependence of the transportation fuel on fossil fuels and its impact on greenhouse gas emissions, all regions in the world are driven to deploy bio-oil as the alternative transportation fuel. Pyrolysis, a process in which the organic materials undergo thermal degradation in the absence of oxygen, has shown great potential to be competitive with the conventional petroleum production in terms of economy and quality. With the advancement of computational fluid dynamics (CFD), it allows detailed analysis and optimization of a pyrolysis process to be carried out easily and thus indirectly minimizes all the expensive and time-consuming experiment. As different biomass species show varied physical and chemical properties, feeding point of the biomass in the fluidized bed reactor (FBR) requires careful consideration. This is because the feeding point will affect the conversion efficiency of the biomass, the heat transfer of the biomass particles and also the residence time in the reactor. In this paper, the influence of the fuel feeding point on the products’ yield is investigated in a pyrolysis FBR using ANSYS Fluent 14.0 simulation. The biomass feeding point will be focused on 3 different zones – the freeboard, the splash zone and the dense bed. The reactor’s dimension, boundary conditions and initial conditions are similar as described in the selected benchmark paper by Xue et al. (2012). Simulation result is compared with the result reported in the benchmark paper for validation. With the validated model, the effect of feeding point was studied and it is observed that for pure cellulose feedstock the optimum feeding point is at the dense bed zone and for red oak the optimum feeding point is at the splash zone. Overall, this study provides a fundamental understanding of the influence of the fuel feeding point on the products yield and reactor temperature distribution during the pyrolysis process in a FBR.
The effect of maternal age on chromosomal anomaly rate and spectrum in recurrent miscarriage.

STUDY QUESTION Is there any effect of maternal age on chromosomal anomaly rate and spectrum in recurrent miscarriage? SUMMARY ANSWER There was no significant difference in the chromosome abnormality rate between sporadic and recurrent miscarriage but the chromosome abnormality rate increased significantly with maternal age. WHAT IS KNOWN ALREADY About 50-70% of non-recurrent miscarriages occur because of a chromosomal anomaly, but no agreement about the effect of either maternal age or the number of previous miscarriages on the chromosomal anomaly rate has been reached. STUDY DESIGN, SIZE, DURATION A retrospective cohort of 353 miscarriages successfully karyotyped in the same center between 2002 and 2011, grouped according to the number of miscarriages and maternal age. PARTICIPANTS/MATERIALS, SETTING, METHODS Among the 353 women, 153 were below 35 years (73 with sporadic, 48 with two and 32 with recurrent miscarriage) and 200 were 35 years or more (81 with sporadic, 55 with two and 64 with recurrent miscarriage). The chromosomal anomaly rate and the anomaly spectrum were compared between sporadic and recurrent miscarriage, within the two maternal age groups, using the chi-square test and the Bonferroni correction for all the P-values. Risk of chromosomal anomaly was estimated for maternal age, number of miscarriages and previous live births by multivariate binary logistic regression analysis. MAIN RESULTS AND THE ROLE OF CHANCE Sporadic and recurrent miscarriage did not show significantly different chromosomal anomaly rates (68 versus 60%) and maternal age was the only statistically significant predictor of the chromosomal anomaly risk we identified. Some trends were observed in the chromosomal anomaly spectrum when sporadic was compared with recurrent miscarriage: recurrent miscarriage exhibited a decrease in viable trisomies (37 versus 11%) and an increase in non-viable trisomies (38 versus 57%) in women >35 years, together with an increase in unbalanced structural anomalies (4.9 versus 29%) in younger women. LIMITATION, REASONS FOR CAUTION The mixed origin of our study population, and the limited number of recurrent miscarriages, particularly in the younger group, limits statistical power to detect differences. WIDER IMPLICATIONS OF THE FINDINGS The most commonly observed chromosomal anomaly type in recurrent miscarriage depends on maternal age: non-viable autosomal trisomies in older women and unbalanced structural anomalies in younger women. When a chromosomal anomaly is identified as the cause of miscarriage, additional maternal evaluation may be avoided. STUDY FUNDING/COMPETING INTERESTS No competing interests declared.
Scintilla : Cluster Computing with SCI

The Scintilla project at UCSB studies SCI-based cluster computing. The Scalable Coherent Interface (SCI) is a recent communication standard for cluster interconnects. We focus on non-coherent SCI, using our cluster setup of SBus-based and PCI-based workstations connected via Dolphin SCI adapters. Our motivation for choosing SCI as network fabric is the very low latency and high bandwidth. We study how to map a variety of programming models efficiently onto the SCI hardware, focusing on message passing and global address space support, implementing Active Messages and Split-C. We present implementation trade-offs, present performance measurements and compare the PCI and SBus adapters. We found that the user-level load/store programming interface of SCI is very convenient to use, achieves low latencies, and is fully virtualized, simultaneously supporting multiple parallel programs and communication channels. On the other hand, neither of the programming models studied maps directly to SCI. Issues such as notification, atomic operations, and virtual address space limitations represent major implementation challenges, which we address with a combination of compiler and run-time support. Overall, we found the SCI network a good substrate for high-performance cluster computing.
DWDM millimeter-wave radio-on-fiber systems

We describe some of our recent results on DWDM mm-wave radio-on-fiber (RoF) technology for future broadband wireless systems. A supercontinuum (SC) light source is a promising multiwavelength light source for the system with photonic up-conversion. Multiplexing and demultiplexing schemes for optical frequency interleaving in order to extend the number of antenna base stations can be constructed using a properly designed arrayed-waveguide grating (AWG). We demonstrate a full-duplex WDM mm-wave RoF system using a SC light source. The periodic nature of AWG, where the period is free spectral range (FSR), is used for utilizing the full bandwidth of the SC light source. Half of the SC output modes are used for downlink transmission with photonic upconversion. Another half of the SC output modes are used for uplink transmission with photonic downconversion. These techniques are effective to use a wealth of optical frequency resources from the SC light source. Two-channel downlink and one-channel uplink 60- GHz band RoF signals were simultaneously transmitted over 25-km standard single-mode fiber with error-free and no noticeable power penalty.
Characterization and clinical application of mesenchymal stem cells from equine umbilical cord blood

Tendinitis of the superficial digital flexor tendon (SDFT) is a significant cause of lameness in horses; however, recent studies have shown that stem cells could be useful in veterinary regenerative medicine. Therefore, we isolated and characterized equine umbilical cord blood mesenchymal stem cells (eUCB-MSCs) from equine umbilical cord blood obtained from thoroughbred mares during the foaling period. Horses that had tendinitis of the SDFT were treated with eUCB-MSCs to confirm the therapeutic effect. After eUCB-MSCs transplantation, the core lesion in the SDFT was found to decrease. These results suggest that transplantation using eUCB-MSCs could be another source of cell treatment.
Virtual Faces Expressing Emotions: An Initial Concomitant and Construct Validity Study

Background: Facial expressions of emotions represent classic stimuli for the study of social cognition. Developing virtual dynamic facial expressions of emotions, however, would open-up possibilities, both for fundamental and clinical research. For instance, virtual faces allow real-time Human–Computer retroactions between physiological measures and the virtual agent. Objectives: The goal of this study was to initially assess concomitants and construct validity of a newly developed set of virtual faces expressing six fundamental emotions (happiness, surprise, anger, sadness, fear, and disgust). Recognition rates, facial electromyography (zygomatic major and corrugator supercilii muscles), and regional gaze fixation latencies (eyes and mouth regions) were compared in 41 adult volunteers (20 ♂, 21 ♀) during the presentation of video clips depicting real vs. virtual adults expressing emotions. Results: Emotions expressed by each set of stimuli were similarly recognized, both by men and women. Accordingly, both sets of stimuli elicited similar activation of facial muscles and similar ocular fixation times in eye regions from man and woman participants. Conclusion: Further validation studies can be performed with these virtual faces among clinical populations known to present social cognition difficulties. Brain–Computer Interface studies with feedback–feedforward interactions based on facial emotion expressions can also be conducted with these stimuli.
A Multi Gigabit FPGA-Based 5-tuple Classification System

Packet classification is one of the most important enabling technologies for next generation network services. Even though many multi-dimensional classification algorithms have been proposed, most of them are precluded from commercial equipments due to their high memory requirements. In this paper, we present an efficient packet classification scheme, called dual stage bloom filter classification engine (2sBFCE). 2sBFC comprises of an innovative 5- field search scheme that decomposes multi-field classification rules into internal single-field rules which are combined using multi-level Bloom filters. The design of 2sBFCE is optimized for the common case based on analysis of real world classification databases. The hardware implementation of this scheme handles 4 K rules while supporting network streams at a rate of 2 Gbps even in the worst case, and more than 6 Gbps in the average case when implemented in an off-the-shelf FPGA.
High-Content Genome-Wide RNAi Screen Reveals CCR3 as a Key Mediator of Neuronal Cell Death

Visual Abstract Neuronal loss caused by ischemic injury, trauma, or disease can lead to devastating consequences for the individual. With the goal of limiting neuronal loss, a number of cell death pathways have been studied, but there may be additional contributors to neuronal death that are yet unknown. To identify previously unknown cell death mediators, we performed a high-content genome-wide screening of short, interfering RNA (siRNA) with an siRNA library in murine neural stem cells after exposure to N-methyl-N-nitroso-N′-nitroguanidine (MNNG), which leads to DNA damage and cell death. Eighty genes were identified as key mediators for cell death. Among them, 14 are known cell death mediators and 66 have not previously been linked to cell death pathways. Using an integrated approach with functional and bioinformatics analysis, we provide possible molecular networks, interconnected pathways, and/or protein complexes that may participate in cell death. Of the 66 genes, we selected CCR3 for further evaluation and found that CCR3 is a mediator of neuronal injury. CCR3 inhibition or deletion protects murine cortical cultures from oxygen-glucose deprivation–induced cell death, and CCR3 deletion in mice provides protection from ischemia in vivo. Taken together, our findings suggest that CCR3 is a previously unknown mediator of cell death. Future identification of the neural cell death network in which CCR3 participates will enhance our understanding of the molecular mechanisms of neural cell death.
Alteration of N-glycans and Expression of Their Related Glycogenes in the Epithelial-Mesenchymal Transition of HCV29 Bladder Epithelial Cells

The epithelial-mesenchymal transition (EMT) is an essential step in the proliferation and metastasis of solid tumor cells, and glycosylation plays a crucial role in the EMT process. Certain aberrant glycans have been reported as biomarkers during bladder cancer progression, but global variation of N-glycans in this type of cancer has not been previously studied. We examined the profiles of N-glycan and glycogene expression in transforming growth factor-beta (TGFβ)-induced EMT using non-malignant bladder transitional epithelium HCV29 cells. These expression profiles were analyzed by mass spectrometry, lectin microarray analysis, and GlycoV4 oligonucleotide microarray analysis, and confirmed by lectin histochemistry and real-time RT-PCR. The expression of 5 N-glycan-related genes were notably altered in TGFβ-induced EMT. In particular, reduced expression of glycogene man2a1, which encodes α-mannosidase 2, contributed to the decreased proportions of bi-, tri- and tetra-antennary complex N-glycans, and increased expression of hybrid-type N-glycans. Decreased expression of fuca1 gene, which encodes Type 1 α-L-fucosidase, contributed to increased expression of fucosylated N-glycans in TGFβ-induced EMT. Taken together, these findings clearly demonstrate the involvement of aberrant N-glycan synthesis in EMT in these cells. Integrated glycomic techniques as described here will facilitate discovery of glycan markers and development of novel diagnostic and therapeutic approaches to bladder cancer.
A Real-time Traffic Congestion Estimation Approach from Video Imagery

This paper presents a novel approach to detect traffic congestion on roads in a natural open world scene observed from TV cameras placed on poles or buildings. In this system, three algorithms are proposed to estimate the road status. They are based on background subtraction, frame differencing and time-spatial image respectively. The experimental results on real road traffic congestion estimation show that the time-spatial method is the most robust in complex lighting and traffic environment. The detailed algorithms and the comparison results are given in the paper.
PREDICTING STUDENT PERFORMANCE USING DATA MINING TECHNIQUES

The paper represents the data mining techniques used for analysing pupil performance. Educational institutions contain an enormous amount of academic database containing student details. These student databases along with other attributes are taken into consideration like family background, family income, etc. It will help us by identifying promising students and by providing us a chance to pay heed and to refine those students who likely get low marks. For answer, we prepare a structure which will analyse the pupil’s performance from their last performances using concepts of Data Mining under Classification. Classification Algorithms like Decision Tree, Naïve Bayes and Support Vector Machine can help us for predicting student’s performance. This prediction helps parents and teachers to keep track of student’s performance and provide required counselling. These Analysis also help in providing scholarship and other required training to the student. We are actually trying to enhance student’s acquirement and success more effectively in a way using educational data mining techniques. It can bring the benefits & influence of novice, teachers and educational institutions. Experimental answers show that suggested procedure significantly outperforms prevailing procedure due to the misuse of family incomes and students’ personal data component sets. Results of this examination can act as policy improvement technique in higher education. KeywordsData Mining; Student Performance Prediction; Extra-Curricular Activities; Academic Performance; Students Personal Information
The Effect of Lead Time and Demand Uncertainties in (r, q) Inventory Systems

We study a single-item (r, q) inventory system, where r is the reorder point and q is the order quantity. The demand is a compound-Poisson process. We investigate the behavior of the optimal policy parameters and the long-run average cost of the system in response to stochastically shorter or less-variable lead times. We show that although some of the properties of the base-stock system can be extended to this more general model, some cannot. The same findings also apply when the comparison is conducted on the lead-time demand distributions.
Coordinated CTA Combination and Bandwidth Partitioning for GPU Concurrent Kernel Execution

Contemporary GPUs support multiple kernels to run concurrently on the same streaming multiprocessors (SMs). Recent studies have demonstrated that such concurrent kernel execution (CKE) improves both resource utilization and computational throughput. Most of the prior works focus on partitioning the GPU resources at the cooperative thread array (CTA) level or the warp scheduler level to improve CKE. However, significant performance slowdown and unfairness are observed when latency-sensitive kernels co-run with bandwidth-intensive ones. The reason is that bandwidth over-subscription from bandwidth-intensive kernels leads to much aggravated memory access latency, which is highly detrimental to latency-sensitive kernels. Even among bandwidth-intensive kernels, more intensive kernels may unfairly consume much higher bandwidth than less-intensive ones. In this article, we first make a case that such problems cannot be sufficiently solved by managing CTA combinations alone and reveal the fundamental reasons. Then, we propose a coordinated approach for CTA combination and bandwidth partitioning. Our approach dynamically detects co-running kernels as latency sensitive or bandwidth intensive. As both the DRAM bandwidth and L2-to-L1 Network-on-Chip (NoC) bandwidth can be the critical resource, our approach partitions both bandwidth resources coordinately along with selecting proper CTA combinations. The key objective is to allocate more CTA resources for latency-sensitive kernels and more NoC/DRAM bandwidth resources to NoC-/DRAM-intensive kernels. We achieve it using a variation of dominant resource fairness (DRF). Compared with two state-of-the-art CKE optimization schemes, SMK [52] and WS [55], our approach improves the average harmonic speedup by 78% and 39%, respectively. Even compared to the best possible CTA combinations, which are obtained from an exhaustive search among all possible CTA combinations, our approach improves the harmonic speedup by up to 51% and 11% on average.
GPU-based Method for Denoising Time Series of Fluorescent Imaging Data

This paper presents a GPU-based method for denoising of time series images obtained by confocal microscopy, in order to study the oscillations of calcium and membrane voltage potential in beta cells. Since denoising of captured images is one of the first crucial steps, it is desirable that it is highly efficient and fast. This is especially important when dealing with a large number of time series images, where the computational complexity increases tremendously. Results demonstrate that the proposed method is at least 5 times faster, in comparison with a CPU-based implementation, while retaining the same accuracy.