Miracle-dz/UniFAR-FTUs huggingface dataset:
Principles of Analytic Monitoring for Continuous Assurance

The advent of new enabling technologies and the surge in corporate scandals has combined to increase the supply, the demand, and the development of enabling technologies for a new system of continuous assurance and measurement. This paper positions continuous assurance (CA) as a methodology for the analytic monitoring of corporate business processes, taking advantage of the automation and integration of business processes brought about by information technologies. Continuous analytic monitoring‐based assurance will change the objectives, timing, processes, tools, and outcomes of the assurance process. The objectives of assurance will expand to encompass a wide set of qualitative and quantitative management reports. The nature of this assurance will be closer to supervisory activities and will involve intensive interchange with more of the firm's stakeholders than just its shareholders. The timing of the audit process will be very close to the event, automated, and will conform to the natural life cycle of.
Comparative trial of the use of antiplatelet and oral anticoagulant in thrombosis prophylaxis in patients undergoing total cavopulmonary operation with extracardiac conduit: echocardiographic, tomographic, scintigraphic, clinical and laboratory analysis

OBJECTIVE To compare the efficacy of aspirin and warfarin for prophylaxis of thrombosis in patients undergoing total cavopulmonary anastomosis. Evaluate whether coagulation factors (VII, VIII and protein C), clinical data, fenestration or hemodynamic factors, interfere with postoperative thrombosis. METHODS A prospective, randomized study of 30 patients, randomized into Group I (Warfarin) and Group II (AAS), underwent total cavopulmonary shunt with extracardiac conduit, between 2008 and 2011, with follow-up by clinical visits to evaluate side effects and adhesion. Performed transesophageal echocardiography in post operatory time, 3, 6,12 and 24 months; angiotomography at 6, 12 and 24 months to evaluate changes in the internal tube wall or thrombi and pulmonary scintigraphy to evaluate possible PTE. RESULTS Two deaths in group I; 33.3% of patients had thrombus (46.7% in Group II). The previous occurrence of thrombus and low levels of coagulation protein C were the only factors that influenced the time free of thrombus (P=0.035 and 0.047). Angiotomographic evaluation: 35.7% in group II presented material accumulation greater than 2 mm (P=0.082). Scintigraphy: two patients had PTE in group II. Five patients had difficulty to comply with the treatment, 4 in group I with INR ranging from 1 to 6.4. CONCLUSION The previous occurrence of thrombus is a risk factor for thrombosis in the postoperative period. Patients using AAS tend to deposit material in the tube wall. The small sample size did not allow to conclude which is the most effective drug in the prevention of thrombosis in this population.
Image Interpolation Techniques Review

image interpolation is very interesting areaof research in image processing which consists of various processing tasks such as compression, restoration, denoising, enhancement. Reconstruction quality of any image interpolation algorithm depends on it's ability to adapt changing pixel structures across image. Interpolation is method of creating new data points from set of available or known data points which helps in analyzing exact details of images which is required in many applications such as medical imaging. By interpolation methods many artifacts in low resolution image such as blurring, ringing can be removed.
Statistically Efficient Smoothing Algorithm for Time-Varying Frequency Estimation

The problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm can be employed to perform many offline signal processing tasks, such as elimination of sinusoidal interference from a prerecorded signal, for example. We show that when the unknown signal frequency drifts according to the random-walk model, the optimally tuned ANS algorithm is, under Gaussian assumptions, statistically efficient, i.e., it attains the Cramer-Rao-type lower smoothing bound, which limits accuracy of any (whether causal or not) frequency estimation scheme.
Changes in Dry State Hemoglobin over Time Do Not Increase the Potential for Oxidative DNA Damage in Dried Blood

Background Hemoglobin (Hb) is the iron-containing oxygen transport protein present in the red blood cells of vertebrates. Ancient DNA and forensic scientists are particularly interested in Hb reactions in the dry state because both regularly encounter aged, dried bloodstains. The DNA in such stains may be oxidatively damaged and, in theory, may be deteriorated by the presence of Hb. To understand the nature of the oxidative systems potentially available to degrade DNA in the presence of dried Hb, we need to determine what molecular species Hb forms over time. These species will determine what type of iron (i.e. Fe2+/Fe3+/Fe4+) is available to participate in further chemical reactions. The availability of “free” iron will affect the ability of the system to undergo Fenton-type reactions which generate the highly reactive hydroxyl radical (OH•). The OH• can directly damage DNA. Methodology/Principal Findings Oxygenated Hb (oxyHb) converts over time to oxidized Hb (metHb), but this happens more quickly in the dry state than in the hydrated state, as shown by monitoring stabilized oxyHb. In addition, dry state oxyHb converts into at least one other unknown species other than metHb. Although “free” iron was detectable as both Fe2+ and Fe3+ in dry and hydrated oxyHb and metHb, the amount of ions detected did not increase over time. There was no evidence that Hb becomes more prone to generating OH• as it ages in either the hydrated or dry states. Conclusions The Hb molecule in the dried state undergoes oxidative changes and releases reactive Fe(II) cations. These changes, however, do not appear to increase the ability of Hb to act as a more aggressive Fenton reagent over time. Nevertheless, the presence of Hb in the vicinity of DNA in dried bloodstains creates the opportunity for OH•-induced oxidative damage to the deoxyribose sugar and the DNA nucleobases.
Assessing the risk of cyclone-induced storm surge and sea level rise in Mozambique

This article considers the impact of sea level rise and storm surge on the port cities of Maputo and Beira in Mozambique. By combining a range of sea level rise scenarios for 2050 with the potential maximum storm surge level for the current 100-year storm, we analyze permanently inundated lands and temporary flood zones. In Beira, our analysis finds that a medium Intergovernmental Panel on Climate Change scenario consistent with Intergovernmental Panel on Climate Change projections through 2050 could increase the frequency of the current 100-year storm, which is associated with a storm surge of roughly 1.9 meters, to once every 40 years. The results in Maputo show similar and even more dramatic changes in the return period of the 100-year storm (associated with more 1.1 meter surges), with a reduction to a 1-in-20-year event under the same scenario. In 2050, approximately 0.4 percent of the Beira study area´s GDP is vulnerable to permanent inundation due to sea level rise, and 0.8 percent is vulnerable to periodic storm surge damage. The figures for Maputo are a bit higher -0.7 percent of the Maputo study area´s GDP is vulnerable to permanent inundation due to sea level rise, and 1.1 percent is vulnerable to periodic storm surge damage.
Transmit Precoding Design for Multi-Antenna Multicast Broadcast Services with Limited Feedback

The provision for spectrally efficient multicast broadcast services (MBS) is one of the key functional requirements for next generation wireless communication systems. The challenge inherent to MBS is to ensure that all MBS receivers can be served, and one effective solution to this problem is to employ MIMO multicast transmit precoding. In previous works on MIMO multicast transmit precoding design, the authors proposed algorithms given 1) perfect transmitter-side channel state information (CSIT) or 2) specific channel conditions that facilitate precoder optimization with imperfect CSIT. In this paper, we focus on transmit precoding design for MBS where the CSIT is obtained via codebook based limited feedback. In addition, we derive the asymptotic closed-form expressions for the average minimum receive signal-noise-ratio (SNR) among the MBS receivers and study the order of growth with respect to the number of MBS receivers, the number of feedback bits and the number of transmit antennas.
Ice thickness effects on
 A
 quarius brightness temperatures over
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 ntarctica

The Dome-C region, in the East Antarctic Plateau, is regarded as an ideal natural laboratory for calibration/validation of space-borne microwave radiometers. At L-band, the thermal stability of this region has been confirmed by several experimental campaigns. However, its use as an independent external calibration target has recently been questioned due to some spatial inhomogeneities and seasonal effects revealed in the brightness temperatures (T-B) acquired in this area. This paper shows the observed relationship, from exploratory research, between the Antarctic ice thickness spatial variations and the measured Aquarius T-B changes. A 3-months no-daylight period during the Austral winter has been analyzed. Four transects have been defined over East Antarctica covering areas with different ice thickness variations and ranges. The theoretical L-band penetration depth has been estimated to understand the possible contributions to the measured signal. A good agreement has been observed between Aquarius T-B and ice thickness variations over the whole Antarctica, with correlations of approximate to 0.6-0.7. The two variables show a linear trend with slopes of approximate to 8.3-9.5 K/km. No correlation has been observed with the subglacial bedrock. The maximum L-band penetration depth has been estimated to be approximate to 1-1.5 km. Results are therefore consistent: the spatial variations found on Aquarius T-B are not related to the emissivity of the bedrock, which lies deeper. This study provides evidence that new L-band satellite observations could contribute to further our understanding of Antarctic geophysical processes.
Prediciting Cone Quantum Catches Under Illumination Change

Given LMS cone quantum catches from a surface under a first illuminant what is the best method of predicting what the corresponding quantum catches will be for the same surface under a second illuminant given only the quantum catches of a white surface under both illuminants? The von Kries rule is one well known method. In this paper, two new prediction methods along with a variation on an existing third method are introduced and then compared experimentally. In contrast to the von Kries rule which is equivalent to a diagonal transformation, all three methods estimate a full 3-by-3 linear transformation mapping LMS values between illuminants. All the new methods perform better than the von Kries rule.
Hypothyroxinemia Induced by Mild Iodine Deficiency Deregulats Thyroid Proteins during Gestation and Lactation in Dams

The main object of the present study was to explore the effect on thyroidal proteins following mild iodine deficiency (ID)-induced maternal hypothyroxinemia during pregnancy and lactation. In the present study, we established a maternal hypothyroxinemia model in female Wistar rats by using a mild ID diet. Maternal thyroid iodine content and thyroid weight were measured. Expressions of thyroid-associated proteins were analyzed. The results showed that the mild ID diet increased thyroid weight, decreased thyroid iodine content and increased expressions of thyroid transcription factor 1, paired box gene 8 and Na+/I− symporter on gestational day (GD) 19 and postpartum days (PN) 21 in the maternal thyroid. Moreover, the up-regulated expressions of type 1 iodothyronine deiodinase (DIO1) and type 2 iodothyronine deiodinase (DIO2) were detected in the mild ID group on GD19 and PN21. Taken together, our data indicates that during pregnancy and lactation, a maternal mild ID could induce hypothyroxinemia and increase the thyroidal DIO1 and DIO2 levels.
Break down GPU execution time with an analytical method

Because modern GPGPU can provide significant computing power and has very high memory bandwidth, and also, developer-friendly programming interfaces such as CUDA have been introduced, GPGPU becomes more and more accepted in the HPC research area. Much research has been done to help developers to better optimize GPU applications. But to fully understand GPU performance behavior remains a hot research topic. We developed an analytical tool called TEG (Timing Estimation tool for GPU) to estimate GPU performance. Previous work shows that TEG has good approximation and can help us to quantify bottlenecks' performance effects. We have made some improvement to the tool and in this paper, we use TEG to analyze the GPU performance scaling behavior. TEG takes the dis-assembly output of CUDA kernel binary code and instruction trace as input. It does not execute the codes, but try to model the execution of CUDA codes with timing information. Because TEG takes the native GPU assembly code as input, it can estimate the execution time with a small error and it allows us to get more insight into GPU performance result.
Deep Reinforcement Learning with Averaged Target DQN

The commonly used Q-learning algorithm combined with function approximation induces systematic overestimations of state-action values. These systematic errors might cause instability, poor performance and sometimes divergence of learning. In this work, we present the AVERAGED TARGET DQN (ADQN) algorithm, an adaptation to the DQN class of algorithms which uses a weighted average over past learned networks to reduce generalization noise variance. As a consequence, this leads to reduced overestimations, more stable learning process and improved performance. Additionally, we analyze ADQN variance reduction along trajectories and demonstrate the performance of ADQN on a toy Gridworld problem, as well as on several of the Atari 2600 games from the Arcade Learning Environment.
Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions

As a new method for detecting change-points in high-resolution time series, we apply Maximum Mean Discrepancy to the distributions of ordinal patterns in different parts of a time series. The main advantage of this approach is its computational simplicity and robustness with respect to (non-linear) monotonic transformations, which makes it particularly well-suited for the analysis of long biophysical time series where the exact calibration of measurement devices is unknown or varies with time. We establish consistency of the method and evaluate its performance in simulation studies. Furthermore, we demonstrate the application to the analysis of electroencephalography (EEG) and electrocardiography (ECG) recordings.
Fuzzy PID Motion Control Based on Extended State Observer for AUV

This paper proposed a Fuzzy PID (FPID) control system based on Extended State Observer (ESO). In this paper, fuzzy logic control effectively solves the problem of parameter adjustment of AUV. ESO is used to obtain the state of the system, to realize the estimation of the interference inside and outside the system and to compensate the interference of the control system. Genetic Algorithm (GA) is used to optimize the initial parameters of FPID controller, which solves the problem of determining the searching space of parameters scientifically and overcomes the blindness of subjective setting. Simulation results show the superiority of FPID control method based on ESO.
Objective measures to improve the selection of training speakers in HMM-based child speech synthesis

Building synthetic child voices is considered a difficult task due to the challenges associated with data collection. As a result, speaker adaptation in conjunction with Hidden Markov Model (HMM)-based synthesis has become prevalent in this domain because the approach caters for limited amounts of data. An initial average voice model is trained using data from multiple speakers and adapted to resemble a specific target child speaker. Due to the scarcity of child speech data, initial models used in this approach are mostly trained with adult speech data. However, selection of appropriate training speakers from large corpora is not a trivial task because there is no means, other than conducting exhaustive subjective listening tests, to determine which training speakers will yield the best quality synthetic child voice. Therefore, there is a need to find an objective measure that can be used to easily identify a small set of training speakers that will yield the best quality output. In this paper we investigate whether a relationship exists between objective and subjective voice evaluation measures with regard to the selection of training speakers for an average voice model used in speaker-adaptive HMM child speech synthesis. Results indicate that, if training speakers that are closer to the target speaker are used to train initial models, better quality child voices are generated.
Design of Dual-Band Bandpass Filters Using Stub-Loaded Open-Loop Resonators

In this paper, open-loop resonators loaded by shunt open stubs are proposed to design compact dual-band bandpass filters with improved out-of-band rejection characteristics. The second passband of the dual-band filter is obtained by tuning higher resonant modes of the open-loop resonator by the stub length and position. A tapped-line input/output feed structure is used for external coupling. Required external coupling is obtained by adjusting the tapping position and dimension of the stub-loaded resonator. A lossless transmission line model is used to determine the resonance properties of the resonator and the external quality factor. Theoretical predictions are verified by the experimental results of three dual-band filters.
Hardware Trojan Prevention Through Limiting Access to the Active Region

Hardware Trojan (HT) has become a serious threat to the semiconductor industry. Many solutions have been developed to detect Trojans and address hardware security concerns. However, due to the wide range of possible Trojans, specific solutions for certain Trojans have been presented and a comprehensive solution is yet to be developed. Trojan prevention methods have also been explored to ensure hardware security. This paper presents a new technique for HT prevention in which attackers are deprived of the resources to route their Trojans and connect them to the active region of the chip. In the proposed solution, the empty space of the die is filled with polysilicon to block unauthorized die connection by attackers. This will deprive attackers of the routing resources to layout their Trojan circuitry. A readout circuit is used to determine that the polysilicon layer is intact, and it has not been tampered with. Simulation results indicate that with proper design, even a reduction of around 14.85 $\mu m^{2}$ polysilicon can be detected. This technique can ensure 100% utilization of the empty spaces in the polysilicon layer.
Cervical Column Morphology and Craniofacial Profiles in Monozygotic Twins

Abstract Previous studies have described the relationships between cervical column morphology and craniofacial morphology. The aims of the present study were to describe cervical column morphology in 38 pairs of adult monozygotic (MZ) twins, and compare craniofacial morphology in twins with fusions with craniofacial morphology in twins without fusion. Visual assessment of cervical column morphology and cephalometric measurements of craniofacial morphology were performed on profile radiographs. In the cervical column, fusion between corpora of the second and third vertebrae was registered as fusion. In the twin group, 8 twin pairs had fusion of the cervical column in both individuals within the pair (sub-group A), 25 pairs had no fusions (subgroup B), and in 5 pairs, cervical column morphology was different within the pair (subgroup C), as one twin had fusion and the other did not. Comparison of craniofacial profiles showed a tendency to increased jaw retrognathia, larger cranial base angle, and larger mandibular inclination in subgroup A than in subgroup B. The same tendency was observed within subgroup C between the individual twins with fusion compared with those without fusion. These results confirm that cervical fusions and craniofacial morphology may be interrelated in twins when analysed on profile radiographs. The study also documents that differences in cervical column morphology can occur in individuals within a pair of MZ twins. It illustrates that differences in craniofacial morphology between individuals within a pair of MZ twins can be associated with cervical fusion.
Vision System for Quality Assessment of Robotic Cleaning of Fish Processing Plants Using CNN

A vision system has been developed for automatic quality assessment of robotic cleaning of fish processing lines. The quality assessment is done by detecting residual fish blood on cleaned surfaces. The system is based on classification using convolutional neural networks (CNNs). The performance of different convolutional neural network architectures and parameters is evaluated. The datasets that simulate various conditions in fish processing plants are generated using data augmentation techniques. Tests using further augmented training data to increase the performance of the neural network are performed, which results in a substantial increase in performance both compared to the color thresholding technique and the same neural network architecture without augmented training data. The performance of the system is validated in experiments in an industrial setting.
Margin-based Ranking and an Equivalence between AdaBoost and RankBoost

We study boosting algorithms for learning to rank. We give a general margin-based bound for ranking based on covering numbers for the hypothesis space. Our bound suggests that algorithms that maximize the ranking margin will generalize well. We then describe a new algorithm, smooth margin ranking, that precisely converges to a maximum ranking-margin solution. The algorithm is a modification of RankBoost, analogous to "approximate coordinate ascent boosting. " Finally, we prove that AdaBoost and RankBoost are equally good for the problems of bipartite ranking and classification in terms of their asymptotic behavior on the training set. Under natural conditions, AdaBoost achieves an area under the ROC curve that is equally as good as RankBoost's; furthermore, RankBoost, when given a specific intercept, achieves a misclassification error that is as good as AdaBoost's. This may help to explain the empirical observations made by Cortes and Mohri, and Caruana and Niculescu-Mizil, about the excellent performance of AdaBoost as a bipartite ranking algorithm, as measured by the area under the ROC curve.