Miracle-dz/UniFAR-FTUs huggingface dataset:
Flame Detection on Swirl Burner Using ECT With Dynamic Reconstruction Algorithm Based on the Split Bregman Iteration

To achieve increased combustion efficiency and reduced pollutant generation, methods to describe the spatial distribution of combustion parameters, such as combustion intensity and temperature are desired. Electric capacitance tomography (ECT) is by nature sensitive to the electrical properties of a flame, facilitating combustion intensity imaging. In this paper, a novel image reconstruction algorithm is developed. It is based on an enhanced regularization methodology and adequate fusion of prior knowledge in the optimization of the objective functional through which a higher spatial resolution and lower errors of the reconstructed images are realized. Simulation results show very good agreement of the reconstructed images with typical phantoms. Also, a series of experiments are carried out for a range of flow rates of fuel and air. Data are collected by the ECT sensor and hardware, and the corresponding images are reconstructed by the new algorithm. The experiments demonstrate the advantages of the new method and ECT images correspond well with the variation of the combustion intensity. Further analysis agrees well with the established principle of combustion.
Image Based Localization

In this paper we present an approach for image based localization in urban environments. Given a database of views of city street views tagged by GPS locations, the system computes the GPS location of a novel query view. We first use a wide-baseline matching technique based on SIFT features to select the closest views in the database. Often due to a large change of viewpoint and presence of repetitive structures, a large percentage of matches (> 50%) are not correct correspondences. The subsequent motion estimation between the query view and the reference view, is then handled by a novel and efficient robust estimation technique capable of dealing with large percentage of outliers. We will discuss in detail sensitivity and robustness of the proposed robust estimation method. The motion estimation stage is also accompanied by a model selection step among the fundamental matrix and the homography. Once the motion between the closest reference views is estimated, the location of the query view is then obtained by triangulation of translation directions. The presented system is tested on a moderate size dataset of street views and results are shown to have higher accuracy than previous reported results. Performance and scalability of the presented system will be also discussed.
Real-time human detection using histograms of oriented gradients on a GPU

Human detection has always been an important part of computer vision but many implementations lack the real-time performance that real world applications require. This paper presents a real-time implementation of human detection in video using the state-of-the-art histograms of oriented gradients method. Each image in the video sequence is tested at multiple scales using a sliding window. Histograms of oriented gradients are created for each window and passed to a support vector machine to classify it as human or not. The histograms of oriented gradients method is implemented on a GPU using the NVIDIA CUDA architecture. The implementation significantly speeds up computation, achieving approximately 38 frames a second on VGA video while testing 11,160 windows per frame. Accuracy remains comparable to the CPU implementation. The flexibility and computational power the GPU affords users is discussed. These discussions should benefit those researchers who are interested in using a GPU for high-performance computing tasks.
Proposed disk diffusion susceptibility criteria for ofloxacin

Disk diffusion zone diameter breakpoint criteria for ofloxacin were tentatively established by correlating MICs with 1-, 3-, and 5-micrograms disk inhibitory zone diameters for 638 bacterial isolates representing 36 species. We recommend use of 5-micrograms disks with the following breakpoints: susceptible (MIC, less than or equal to 2.0 micrograms/ml), greater than or equal to 16 mm; intermediate (MIC, 4.0 micrograms/ml), 13 to 15 mm; and resistant (MIC, greater than or equal to 8.0 micrograms/ml), less than or equal to 12 mm.
Efficient Low-Density Parity-Check (LDPC) Code Decoding for Combating Asymmetric Errors in STT-RAM

Spin-transfer torque random access memory (STT-RAM) has emerged as a promising nonvolatile memory technology for its fast speed, small footprint and zero standby power. However, the unique and unusual high asymmetric error rates at different memory bit operations, which are proved to be far beyond the efficiency of common error correction codes (ECCs), greatly hinder its applications. In this work, we investigate the potentials of the powerful low-density parity-check (LDPC) code to address the aggravated reliability issue in STT-RAM. We first develop a holistic STT-RAM channel model to quantitatively measure the asymmetric effects during the write and read process for single-level-cell (SLC) and multi-level-cell (MLC) design. We then propose an asymmetric LDPC (A-LDPC) decoding to particularly enhance the asymmetric error correcting capability. An STT-RAM dedicated hardware-favorable soft information, namely asymmetric Log-Likelihood Ratio (A-LLR), is also derived from the proposed channel model. Experimental results show that our A-LDPC can outperform at least two/four orders of magnitude over existing ECCs for combating the asymmetric bit errors in SLC/MLC STT-RAM.
Earnings Management in Business Groups: Tax Incentives or Expropriation Concealment?

This study provides evidence that Belgian firms affiliated to a business group (holding) manage their earnings more than stand-alone firms. Earnings management is especially more prevalent in fully owned group firms compared to group firms with minority shareholders. This evidence is consistent with the hypothesis that controlling shareholders face fewer constraints to manage earnings if opportunistic earnings management cannot adversely affect the value of minority shareholders and is inconsistent with the claim that group firms would engage in earnings management to hide controlling shareholders' self-serving transactions. On the incentive part, we find that group firms strategically manage earnings in response to tax incentives. More specifically, we show that signed discretionary accruals of group firms depend significantly more on the marginal tax rate status of the firm as compared to independent firms. Finally, we document that earnings management is particularly facilitated through intra-group transactions.
Multi-Task Learning Organize (MTLN) of Skeleton Sequences Based 3D Action Recognition

Skeleton sequences provide 3D trajectories of human skeleton joints. The spatial temporal in sequence is very significant for action detection. Considering that deep convolution neural network (CNN) is very influential for feature learning in images, in this paper, we intend to transform a skeleton sequence into an image-based demonstration for spatial temporal information learning with CNN. Specifically, for each channel of the 3D coordinates, we distinguish the sequence into a clip with several gray images, which represent multiple spatial structural information of the joints. Those images are fed to a deep CNN to learn high-level features. The CNN features of all the three clips at the same time-step are concatenated in a feature vector. Each feature vector represents the temporal information of the entire skeleton sequence and one particular spatial relationship of the joints. Then we propose a Multi-Task Learning Network (MTLN) to jointly process the feature vectors of all time-steps in related for action detection. Investigational results clearly show the effectiveness of the proposed new representation and feature learning method for 3D action detection.
Analytical and experimental investigation of grinding fluid hydrodynamic pressure at wedge-shaped zone

The conventional method of delivering grinding fluid with a high supply of pressure and hydrodynamic fluid pressure can be generated ahead of the contact zone due to the wedge effect. In the present paper, theoretical hydrodynamic pressure modelling was applied to induce a flow of coolant fluid through the grinding zone during flood delivery grinding. The simulation results show that hydrodynamic pressure was proportional to grinding wheel velocity, and inversely proportional to the minimum gap between the wheel and workpiece surface. The maximum pressure value was generated in the minimum gap region where higher fluid pressure gradient occurred. Moreover, the hydrodynamic pressure at the wedge-shaped zone was also measured through experiments. The results suggest that the proposed model agrees with the theoretical model and it can accurately forecast changes in the hydrodynamic pressure at the contact zone between the grinding wheel and the workpiece.
Regulation of lipid droplets by metabolically controlled Ldo isoforms

Storage and consumption of neutral lipids in lipid droplets (LDs) are essential for energy homeostasis and tightly coupled to cellular metabolism. However, how metabolic cues are integrated in the life cycle of LDs is unclear. In this study, we characterize the function of Ldo16 and Ldo45, two splicing isoforms of the same protein in budding yeast. We show that Ldo proteins interact with the seipin complex, which regulates contacts between LDs and the endoplasmic reticulum (ER). Moreover, we show that the levels of Ldo16 and Ldo45 depend on the growth stage of cells and that deregulation of their relative abundance alters LD morphology, protein localization, and triglyceride content. Finally, we show that absence of Ldo proteins results in defects in LD morphology and consumption by lipophagy. Our findings support a model in which Ldo proteins modulate the activity of the seipin complex, thereby affecting LD properties. Moreover, we identify ER–LD contacts as regulatory targets coupling energy storage to cellular metabolism.
Using motifs in the prediction of eukaryotic protein subcellular localization

Subcellular location of a protein is one of the key functional characters as proteins must be localized correctly at the subcellular level to have normal biological functions. In this paper, all motifs in PROSITE were examined and those that are indicative to eukaryotic protein subcellular localizations were picked out. A corresponding motif module was built and combined to our former work: LOCSVMPSI. Prediction results of this combined method were compared to LOCSVMPSI as well as several other existing methods for subcellular localization. The combined method achieved highest overall prediction accuracy among all listed methods and improved the over-all and each-location accuracies of LOCSVMPSI by 3%-8%. Further analysis indicates the combined motif method is very effective in eukaryotic protein subcellular localization prediction
Asynchronous FIFO Design with Gray code Pointer for High Speed AMBA AHB Compliant Memory controller

An improved technique for FIFO design is to perform asynchronous comparisons between the FIFO write and read pointers that are generated in clock domains and asynchronous to each other. The asynchronous FIFO pointer comparison technique uses fewer synchronization flip-flops to build the FIFO. This method requires additional techniques to correctly synthesize and analyze the design, which are detailed in this paper. To increase the speed of the FIFO, this design uses combined binary/Gray counters that take advantage of the built-in binary ripple carry logic. This FIFO design is used to implement the AMBA AHB Compliant Memory Controller. Which means, Advanced Microcontroller Bus Architecture compliant Microcontroller . The MC is designed for system memory control with the main memory consisting of SRAM and ROM.
The Long-run IPO Performance, Frequency of Cash Dividend and Signal Effect: Evidences from China

This article conducts an analysis of the long-run performance of IPOs after cash dividend, with a sample of A shares listed in Chinese stock market before the end of 2008. The significant test of difference, using match-stock method, shows that two times cash dividend within 3 years after IPO listed is an important boundary. The stocks with cash dividend two times or more have better long-run performance than those stocks with cash dividend only one time or less. The regression analysis shows that the long-run performance and the frequency of cash dividend have a positive correlation. The research conclusion, in a whole, suppose the point that the frequency of cash dividend of IPOs within three years after listed can be a positive signal of the IPOs' long-run performance.
Evaluation of simplified repeated resistance training system for severe hemiplegic stroke patient

We have developed a three-dimensional force display robot (3D robot) to discover and embody needs in rehabilitation site. Then we have exchanged opinions with therapists by using the 3D robot together in rehabilitation site. From a therapist' needs we have developed repeated resistance training system by using the 3D robot as one of the application of the 3D robot. On the basis of the results we have developed a simplified repeated resistance training system equipped with a user interface for easy operation for therapists. Moreover, we have developed a brace for fixation as the attachment between the training system and the patient's arm. In this paper, we perform the functional evaluation of the simplified repeated resistance training system and the brace in the clinical site. These results are based on the opinions from the therapist and the patient. Moreover, we verify the therapeutic effects of the repeated resistance training using the simplified system for a hemiplegic stroke patient. The AROMs of pronation and supination of the patient were improved after repeated resistance training using the simplified system.
Neurotensin Enhances Sperm Capacitation and Acrosome Reaction in Mice

ABSTRACT Neurotensin (NT) has multiple functions, ranging from acting as a neurotransmitter to regulating intestinal movement. However, its function in reproductive physiology is unknown. Here, we confirmed the expression and localization of NT receptors (NTR1) in mouse epididymal spermatozoa and investigated the effect of NT on sperm function. Sperm protein tyrosine phosphorylation, one of the indices of sperm capacitation, was facilitated dose-dependently by NT administration. In addition, the acrosome reaction was promoted in capacitated spermatozoa, and addition of a selective antagonist of NTR1 and NTR2 blocked the induction. Furthermore, intracellular calcium mobilization by NT addition was observed. This showed that NT was an accelerator of sperm function via its functional receptors. The presence of NT was confirmed by immunohistochemistry and its localization was observed in epithelia of the uterus and oviduct isthmus and ampulla, which correspond to the fertilization route of spermatozoa. The NT mRNA level in ovulated cumulus cell was remarkably increased by treatment with human chorionic gonadotropin (hCG). Using an in vitro maturation model, we analyzed the effects of FSH, epidermal growth factor (EGF), estradiol, and progesterone in NT production in cumulus cells. We found that FSH and EGF upregulated NT release and mRNA expression. Both FSH- and EGF-induced upregulation were inhibited by U0126, an MAPK kinase inhibitor, indicating that FSH and EGF regulate NT expression via a MAPK-dependent pathway. This evidence suggests that NT can act as a promoter of sperm capacitation and the acrosome reaction in the female reproductive tract.
Comparing three lower bounding methods for DTW in time series classification

In comparison to Euclidean distance, Dynamic Time Warping (DTW) is a much more robust distance measure for time series data. For speeding up DTW computation, a few lower bounding techniques have been proposed in literature to guarantee no false dismissals in time series similarity search. In this work, we apply DTW lower bounding method in time series classification and empirically compare three different typical lower bounding techniques for DTW: LB_Keogh, FTW and LB_Improved in this time series data mining task. Our experimental results show that LB_Keogh and LB_Improved perform well with small warping window widths while FTW is only suitable with large warping window widths or without any constraint on warping windows. Besides, runtime efficiency of LB_Improved is quite poor due to its high complexity in lower bound computation despite of its better pruning power.
Disambiguating temporal-contrastive connectives for machine translation

Temporal-contrastive discourse connectives (although, while, since, etc.) signal various types of relations between clauses such as temporal, contrast, concession and cause. They are often ambiguous and therefore difficult to translate from one language to another. We discuss several new and translation-oriented experiments for the disambiguation of a specific subset of discourse connectives in order to correct some of the translation errors made by current statistical machine translation systems.
Continent caecal bladder.

Summary— A new method of urinary diversion in 27 patients is described. The ileocaecal segment is isolated as a reservoir and an invaginated “inkwell” valve of ileum is sewn into the open end of the caecum. Twenty-four patients are continent and empty their urinary reservoirs by self-catheterisation at regular intervals.
Crowdsourcing Annotation of Non-Local Semantic Roles

This paper reports on a study of crowdsourcing the annotation of non-local (or implicit) frame-semantic roles, i.e., roles that are realized in the previous discourse context. We describe two annotation setups (marking and gap filling) and find that gap filling works considerably better, attaining an acceptable quality relatively cheaply. The produced data is available for research purposes.
Automatic generative design to meet customer's preferences

Design is a creative work that demands inspiration, disciplined crafts, and iterative rollouts. To assist such creative works, the generative design technique has been employed, in which design ideas are coded into computer programs and the programs build designs on behalf of human designers. Human designers work on programs, instead of designs themselves, to modify models and to adopt new design ideas. Although human designers do not directly develop models, they need to be kept involved in model development programs. This paper is concerned with a generative design method which does not require human designers to be deeply involved in the design process. The proposed method uses a genetic algorithm approach as an enabling mechanism. The genetic algorithm creates various shapes of models using the predefined genetic operators which are developed with the help of human designers. The method assumes that the customers express their preferences on designs and thus the preferences evaluation is incorporated into the fitness function of the genetic algorithm. The proposed method has been applied to ring design works.
The Drosophila Mutant tetanic Interacts with a Gene Complex Including the Structural Locus of K+ Channels and Shows Altered Dephosphorylation and Learning

The tetanic (tta; X.‐52.6) mutation has been isolated on the basis of its sensitivity to extradoses of the normal Shaker gene complex (ShC) where the K+ channel la is encoded. The mutant shows up to threefold elevation of the membrane bound protein phosphatase type 1 (PP1) activity in body extracts, probably due to reduced levels of the PP1 specific inhibitor 2 (I‐2). By contrast, PP1 activity in the head is only half of the normal value. In addition, tta fails to perform normally in a negative reinforcement olfactory paradigm. The functional relationships between phosphorylation, K+ currents, phosphatase activity and modulation of synaptic activity during learning and memory are discussed in the light of their possible genetic links.
Deep neural network-based automatic modulation classification technique

Deep neural network (DNN) has recently received much attention due to its superior performance in classifying data with complex structure. In this paper, we investigate application of DNN technique to automatic classification of modulation classes for digitally modulated signals. First, we select twenty one statistical features which exhibit good separation in empirical distributions for all modulation formats considered (i.e., BPSK, QPSK, 8PSK, 16QAM, and 64QAM). These features are extracted from the received signal samples and used as the input to the fully connected DNN with three hidden layer. The training data containing 25,000 feature vectors is generated by the computer simulation under both additive Gaussian white noise (AWGN) and Rician fading channels. Our test results show that the proposed method brings dramatic performance improvement over the existing classifier especially for high Doppler fading channels.
Resonant photon-assisted tunneling through a double quantum dot: An electron pump from spatial Rabi oscillations.

The time average of the fully nonlinear current through a double quantum dot, subject to an arbitrary combination of ac and dc voltages, is calculated exactly using the Keldysh nonequilibrium Green function technique. When driven on resonance, the system functions as an efficient electron pump due to Rabi oscillation between the dots. The pumping current is maximum when the coupling to the leads equals the Rabi frequency.