Miracle-dz/UniFAR-FTUs huggingface dataset:
High Efficiency Mechanism Analysis of Resonant Switched-Capacitor Converter

The switched-capacitor (SC) converters are gaining popularity in some practical use. Its resonant counterpart, with a small inductor as current shaper in the architecture, has the advantage of smoother charging current, smaller voltage and current variation ratio and so on. This paper presents a generic and thorough analysis of the efficiency mechanism of the resonant switched-capacitor converter (RSCC). It decomposes any RSCC into three basic sub-circuits of SRLC circuit, CRLC circuit and SRLC2 circuit, which are analyzed and compared with corresponding sub-circuits of SCC, respectively. Then the overall efficiency of a RSCC could be derived. Furthermore, a new calculation method of output impedance is developed in another perspective to reveal the high efficiency mechanism of RSCC. On this basis, the high efficiency operation condition for RSCC could be obtained. Finally, a resonant bridge modular switched-capacitor converter (RBMSCC) is proposed and built for example of extended implementation of RSCC to achieve high efficiency operation. Some useful comments for designing resonant switched-capacitor converters are suggested.
Cyclic Weighted Median Method for L1 Low-Rank with Nonlocal for Single color image denoising

A challenging problem in computer vision is how to restore clean image from the noisy one. Low rank decomposition based on Li norm has become a popular solution. However, Since the matrix factorization is nonconvex and Li norm is non-smooth, most methods cannot be truly realized and only suboptimal results can be obtained. The cyclic weighted median method alleviates this problem to a certain extent by solving a series of scalars minimization convex sub-problems. However, this method currently can only rely on similar image sequences to find low-rank subspaces, which is seriously degraded in single image denoising. In this paper, we introduce non-local self-similar priors, and apply the cyclic weighted median method for single image denoising for the first time. Experiments prove that our method is better than all competition methods.
Publishing Node Strength Distribution With Node Differential Privacy

The challenge of graph data publishing under node-differential privacy mainly comes from the high sensitivity of the query. Compared with edge-differential privacy that can only protect the relationship between people, node-differential privacy can protect both the relationship between people and personal information. Therefore, Node-differential privacy must pay attention to the protection of personal information. This paper studies the release of node strength distribution under node-differential privacy by reducing sensitivity. We propose two algorithms to publish node strength distribution: Alternate-histogram (ALT-histogram) and Density-histogram (DEN-histogram). Experimental results show that compared with the existing node strength histogram publishing algorithm, our proposed algorithm has advantages in L1-error and KS-distance, make the noise node strength distribution closer to that of the original graph. We also propose an introspective analysis to understand the influence of the projection algorithm on the node strength distribution, experiments to prove that the projection algorithm plays an important role in the node strength distribution.
Development and Evaluation of a Computer Game Combining Physical and Cognitive Activities for the Elderly

This study develops a cognitive computer game system for the motor-cognitive dual-task training of the elderly. This system simultaneously combines musical rhythm games with exercises for cognitive training, while the exercises are designed to correlatively combine movements with the concept of acupressure points. Incorporating the concept of acupressure points can motivate participants to complete the exercises. The system has the features of being improvable and expandable based on modular design. The system framework is divided into three parts: first, the motion sensing controller (MSC) can detect a trainee’s slapping motions during cognitive training; a variety of installation methods are designed to flexibly coordinate with a user’s conditions, slapping motions and acupressure points for application. Next, the rhythm game is a set of games combining images and musical rhythms. Games can be developed to correspond with different cognitive skills; in this study, relevant games have been developed for cognitive skills like processing speed, short-term memory, working memory, divided attention, and inhibitory function. Finally, the cognitive skill evaluation (CSE) uses the cognitive computer games to evaluate the user’s relevant cognitive skills. Sixteen healthy elderly people aged 65 or older are recruited for evaluation of the various modes and functions of this system. After four weeks of interventional training twice a week, the subjects’ cognitive skills such as short-term memory, divided attention, and inhibitory function improved significantly, and their overall cognitive function assessed by the Montreal Cognitive Assessment (MoCA) are also found to have improved. On the user’s feedback questionnaire, their self-evaluation of physical conditions, the difficulty levels of the games, and their continued willingness to use the system all receive good appraisals. It can be seen that the rhythmic cognitive computer games in combination with exercises as developed in this study is helpful and feasible for the cognitive training of the elderly.
Distribution Characteristics of Electromagnetic Field and Temperature Field of Different Caliber Electromagnetic Railguns

To explore the influence of different caliber on the electromagnetic field and temperature field of railguns, an electromagnetic-thermal coupling analysis is carried out on three kinds of caliber railguns by Maxwell 3-D and ANSYS Workbench. The current density and temperature distribution on the contact surface between armature and rails of three kinds of caliber railguns are obtained, respectively. The calculation results show that the maximum current density and temperature of the small and medium caliber railguns appear on the contact surface, but the large caliber railgun appears to the armature throat. As the caliber increases, the current density and temperature on the contact surface have decreased significantly. The maximum current density of medium and large caliber railguns decrease by 13.7% and 35.5% compared with small caliber railgun, and the maximum temperature decrease by 38.8% and 50.1%, respectively. The temperature of the small caliber railgun rises fastest, which is 1.87 and 1.61 times that of the medium and large caliber railguns, respectively. The results can provide an important basis for the design of large caliber electromagnetic railgun.
Analyzing Multifunctionality of Head Movements in Face-to-Face Conversations Using Deep Convolutional Neural Networks

A functional head-movement corpus and convolutional neural networks (CNNs) for detecting head-movement functions are presented for analyzing the multiple communicative functions of head movements in multiparty face-to-face conversations. First, focusing on the multifunctionality of head movements, i.e., that a single head movement can simultaneously perform multiple functions, this paper defines 32 non-mutually-exclusive function categories, whose genres are speech production, eliciting and giving feedback, turn management, and cognitive and affect display. To represent and capture arbitrary multifunctional structures, our corpus employs multiple binary codes and logical-sum-based aggregations of multiple coders’ judgments. A corpus analysis targeting four-party Japanese conversations revealed multifunctional patterns in which the speaker modulates multiple functions, such as emphasis and eliciting listeners’ responses, through rhythmic head movements, and listeners express various attitudes and responses through continuous back-channel head movements. This paper proposes CNN-based binary classifiers for detecting each of the functions from the angular velocity of the head pose and the presence or absence of utterances. The experimental results showed that the recognition performance varies greatly, from approximately 30% to 90% in terms of the F-score, depending on the function category, and the performance was positively correlated with the amount of data and inter-coder agreement. In addition, we noted a tendency toward overdetection that added more functions to those originally in the corpus. The analyses and experiments confirm that our approach is promising for studying the multifunctionality of head movements.
Process-variation Effects on 3D TLC Flash Reliability: Characterization and Mitigation Scheme

In Solid State Drives, flash management techniques such as wear-leveling and refresh usually assume NAND flash memories have the same endurance value. However, the actual endurance values differ from blocks to blocks. This reliability difference is introduced by process-variation during flash fabrication. In recent years, for improving flash management techniques, various works have been done on the reliability variation of 2D flash memory. As 2D NAND transmitted to 3D NAND flash, the vertical structure and multi-layer stacking changed the effect of previously known reliability problems. In this paper, we are first to characterize the process-variation effects on 3D TLC flash reliability. The characterization includes two parts: endurance variation and error feature variation. Second, we propose an adaptive error prediction scheme to mitigate the process-variation effects. This scheme uses the machine-learning model to realize the error prediction operation. We also discuss the implications of this scheme on main flash management techniques.
On the Classification of ECG Signals Subject to Various Degrees of Dimensionality Reduction

In this paper we investigate the classification performances of ECG signals subject to various degrees of dimensionality reduction. For each case, results obtained with several classification algorithms are presented and discussed. Two of the three methods for dimensionality reduction investigated in this work are Laplacian Eigenmaps (LE), Locality Preserving Projections (LPP). The third one, somehow different, is Compressed Sensing (CS) a method for acquiring and reconstructing signals from a reduced number of random projections under the hypothesis of sparsity. The purpose of the analysis is to investigate the advantages and disadvantages of each method and to determine to what degree it can be considered being optimal for a case of dimensionality reduction. The evaluation of the dimensionality reduction effect for the ECG signals was made based on the classification of the signals in the reduced spaces. Moreover, the classification rates of the original signals were compared with the classification rates of the small-dimensional signals using several classifiers.
RepShard: Reputation-based Sharding Scheme Achieves Linearly Scaling Efficiency and Security Simultaneously

Sharding technology is becoming a promising candidate to address the scalability issues in blockchain. The key concept behind sharding technology is to partition the network status into multiple distinct smaller committees, each of which handles a disjoint set of transactions to leverage its capability of parallel processing. However, when introducing sharding technology to blockchain, several key challenges need to be resolved, such as security and heterogeneity among the participating nodes. This paper introduces RepShard, a reputation-based blockchain sharding scheme that aims to achieve both linearly scaling efficiency and system security simultaneously. RepShard adopts a two-layer hierarchical chain structure, consisting of a reputation chain and independent transaction chains. Each transaction chain is maintained within its shard to record transactions, while the reputation chain is maintained by all shards to update the reputation score of each participating node. We leverage a novel reputation scheme to record each participating node’s integrated and valid contribution to the system, in which we consider the heterogeneity of participating nodes (e.g., computational resources). The reputation score used in sharding and leader election processes maintains the balance and security of each shard. RepShard relies on verifiable relay transactions for cross-shard transactions to ensure consistency between distinct shards. By integrating reputation into the sharding protocol, our scheme can offer both scalability and security at the same time.
Comparison of Pre-Trained Deep Learning Algorithms for Quality Assessment of Electrocardiographic Recordings

Convolutional neural networks (CNNs) have recently become popular for electrocardiogram (ECG) analysis. However, their ability for ECG quality assessment has still not been thoroughly assessed. This challenging topic, aimed at identifying poor-quality ECG intervals, could facilitate more accurate decisions on cardiac disorders, especially from wearable long-term ECG monitoring systems. Hence, this work introduces a comparative study about how several CNN algorithms discern between high and low-quality ECGs. Because no many datases with large amount of annotated ECG signals are freely available, three pretrained CNNs, such as AlexNet, VGG16 and GoogLeNet, have been compared. For that purpose, 2,000 5 second-length ECG excerpts were extracted from a public database and classified into two groups. Thus, 1,000 ECG intervals were annotated as noisy and other 1,000 segments presented sufficient quality for further analysis. For robust validation of the algorithms, five learningtesting cycles with random 80/20 splits of the dataset were conducted. Whereas all CNN models achieved mean accuracies about 90%, remarkable differences were seen in terms of computational time and memory usage. Thus, AlexNet was the fastest method classifying ECG excerpts, but GoogLeNet required the lowest memory content for its performance. Consequently, both algorithms reported an interesting trade-off between poor-quality ECG identification accuracy and computational load.
Burnout of resident doctors in a teaching hospital in Jordan

Background: Burnout syndrome in the medical field recently gained much attention, becoming an essential factor in specialty selection and job satisfaction. In this study, we focus on evaluating the emotional distress among residents of various specialties at a tertiary hospital and associated factors. Methods: This is a cross-sectional study which was done using a sociodemographic questionnaire among residents of various specialties. The collected answers were assessed using Student's t-test and Chi-square test for continuous variables and categorical ones respectively. Results: A total of 250 out of 382 registered residents took the survey with a response rate of 65%, 48% were female, 67.1% single, mean age 27.5 ± 2.2, and mean weekly duty work was 71.8 ± 22.6. 53.6% of residents reported a high grade of emotional exhaustion. Furthermore, 82.4% of the residents exceeded the 24-shift length, reaching a maximum of 56 h straight in-house duty. Male residents reported a higher rate of feeling pressured to work, while female residents reported that they would learn more effectively and commit fewer errors if they slept more. Conclusion: This is the first Jordanian study to measure elements leading to resident emotional distress and its effect on personal achievement. The prompt recognition of risk factors is essential for the achievement of prophylactic actions against resident emotional distress, which can be minimized by a well-defined regulation for residency working hours.
Effect of temperature and activation techniques of irrigating solutions on push-out bond strength of fiber post

AIM: This study evaluated the effect of preheated irrigants (EDTA, QMix), then use of various activation techniques such as ultrasonic system and laser on push-out bond strength (POBS) of fiber posts to root dentin. Methodology: One hundred and twenty extracted human teeth were decoronated below the cementoenamel junction. All the root canals were instrumented, irrigated using sodium hypochlorite and normal saline, dried with paper points, and filled with gutta-percha and AH Plus sealer. Post spaces were prepared. The irrigating solutions QMix and EDTA were heated to 60°C. Normal QMix and EDTA served as control. The irrigants were activated with Laser and Ultrasonic system. Then, the fiber posts were cemented, roots were sliced to thickness of 2 mm and mounted for measurement of POBS. Results: Preheated irrigants group showed maximum POBS as compared to Normal irrigants. QMix group showed better results as compared to EDTA. Irrigants when activated with laser and ultrasonics showed comparable results. Conclusion: Within the limitations of the study, it can be concluded that preheated irrigants(QMix, EDTA) increase the POBS of fiber post to root dentin. Both laser and ultrasonic are equally effective for increasing the POBS.
Evaluation of tissue inflammatory response of four intracanal medicament – An animal study

Aim: The aim of the study was to evaluate the tissue inflammatory response of origanum vulgarae, omeprazole, triple antibiotic paste (TAP), and calcium hydroxide in an animal model. Materials and Methods: Seventy Five male Wistar rats were randomly divided into four experimental groups and one control group: Group 1: control (n = 15), Group 2: 0.25 mg origanum vulgarae/1 ml of cellulose (n = 15), Group 3: 2 mg omeprazole/1 ml of distilled water (n = 15), and Group 4: 1 mg TAP/1 ml of distilled water (n = 15), Group 5: 16 mg calcium hydroxide/1 ml of distilled water (n = 15). A trough was made in the periapical bone and the medicament of the respective groups was placed. After the 7th, 14th, 28th and days, the animals were euthanized and tissue specimen was prepared for histological examination. Results: The results were analyzed statistically. On the 7th and 14th days, all the experimental groups showed severe inflammatory response with no statistical significance, whereas on the 28th day, the inflammatory response was graded based on the mean value, in which omeprazole showed moderate inflammatory cells followed by TAP. Mild inflammatory response was seen in calcium hydroxide and origanum vulgarae, showing no statistical significance. Conclusion: Within the limitation of the study, severe inflammatory response was reported on the 7th and 14th days in all experimental groups, whereas on 28th day, there was a moderate inflammatory response seen in omeprazole, followed by TAP. Calcium hydroxide and origanum vulgarae showed a mild inflammatory response.
The susceptibility of various UK aggregates to alkali silica reaction

A group of lithologically varied UK aggregates have been incorporated into concrete prisms of variable alkali content to ascertain the alkali levels at which significant ASR first occurs at 38oC and 100% RH. Petrographical analysis was used to establish the source of reactivity. The results of these expansion tests showed that significant ASR can develop with certain aggregates at initial alkali levels as low as 3.5 kg/m3 Na2Oe. Similar prisms were made at initial alkali levels, well above, on and just below the alkali thresholds for each aggregate. These prisms were placed in salt solution to establish the effects of ASR. The results showed that an external source of NaCl does accentuate ASR in high alkali mixes. However, in low alkali mixes the ASR initiated was even greater than that developed by the high alkali mixes. It was proposed that an `initial alkali pessimum' existed for each aggregate type for specimens placed in salt solution. Electron microprobe analysis of the ASR gels from concretes immersed in salt solution, showed that two compositionally varied gel suites develop. The first suite was derived from ASR caused by the initial alkalis in a concrete mix and was identical to ASR gels derived from the various concretes when immersed in distilled water. The second suite was developed by alkalis derived from a reaction between NaCl and the C3A component of the cement paste. It was demonstrated that the `initial alkali pessimum' was probably due to a combination of these two ASR types at the alkali threshold point where both suites of ASR gel can develop. Equivalent mixes were made with a 25% replacement of the cement by pulverised fuel ash (pfa) to establish whether alkalis released from the pfa could initiate ASR in otherwise non-reactive low alkali mixes. The addition of air entrainment to reactive concrete mixes was also examined as a method of suppressing ASR.
Beware of effects on isotopes of dissolved oxygen during storage of natural iron-rich water samples: A technical note.

RATIONALE Investigations of the isotope ratios of dissolved oxygen (δ18 ODO values) provide valuable information about the oxygen cycle in aquatic systems. However, oxidation of Fe (II) may change the pristine δ18 ODO values during storage and can lead to a misinterpretation. We sampled an Fe (II)-rich spring system and measured δ18 ODO values afterwards to determine influences of Fe-oxidation. METHODS Water samples were collected from a spring and related stream and the δ18 ODO values were measured in fresh, 4- and 13-day old samples with an isotope ratio mass spectrometer. 3 replicates were measured for each sample with a 1σ of ± 0.2 ‰. On-site parameters and Fe (II) contents were also measured over the course of the spring by multi parameter probes and spectrophotometry. RESULTS The δ18 ODO values over the course of the spring system in fresh, 4- and 13-day old samples revealed differences of up to 8 ‰. We explain this increase by the consumption of DO by Fe (II) oxidation. After 85 meters' flow length the differences in δ18 ODO values between fresh and older samples decreased due to consumption of Fe (II). CONCLUSION False interpretations of δ18 ODO values are possible if the values of Fe-rich water samples are measured after too long storage, and we recommend measurement immediately after sampling.
A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication

In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles’ path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle’s front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning.