Miracle-dz/UniFAR-FTUs huggingface dataset:
Technique for sensing inductor and DC output currents of PWM DC-DC converter

The design, analysis and trade-offs of a novel method to sense the inductor and DC output currents of PWM converters are presented. By sensing and adding appropriately the currents in the transistor, rectifier and capacitors of a converter using current transformers, the waveforms of inductor and DC output currents can be reconstructed accurately while maintaining isolation. This method offers high bandwidth, clean waveform, practically zero power dissipation and simple circuit. The technique is applicable to all PWM converters in both continuous and discontinuous modes, and is most suitable for the implementation of current mode control schemes like hysteretic, PWM conductance control, and output current feedforward. This approach has been experimentally verified at a wide range of current levels, duty cycles, and switching frequencies up to 1.4 MHz. >
ICT Research networks and regional competitiveness: an analysis of the 7th Framework Program

ABSTRACT Using Social Network Analysis and the novel concept of bridging centrality this paper investigates the links generated by the research networks created by two of the European Union-funded Programs, the 7th Framework Program (FP7) and the ICT action of the Competitiveness and Innovation Framework Program (CIP) and their impacts on regional competitiveness. Our findings show a positive impact on the competitiveness of both networks. Those regions with higher capacities to establish bridging paths tend to show higher levels of competitiveness. Moreover, our results indicate that these effects differ between research and diffusion networks. Whereas the FP7-related network impacts all the dimensions of competitiveness, the CIP influences competitiveness only through the innovative channel. Our results highlight the importance of facilitating intra- and inter-regional collaboration networks between core and peripheral regions in Europe.
Leak detection survey of a 36 inch diameter 78 mile long submarine pipeline

In the early part of 1982 a leak detection survey on the survey on the 36 inch diameter 78 miles (126 km) long E11 submarine pipeline was carried out with optical and acoustical equipment during a period of 16 days. Two leaks were detected and identified as 0.5 inch (6 mm) cracks in two different circumferential welds.
A Combined Model for Locating Critical Centers (HAPIT)

The most important goals in marring of a country is to destroy it's military and industrial centers. One of the most important and essential measures for preventing the vital damages to these centers or limiting them is to locate accurately these vital and critical industries. Accurate and material location of these centers is one of the most important measures which lead to decrease of future considerable related costs and to increase securely index of them. Therefore by increasing the passive defense capability of these centers the enemy's attacks possibility and destruction effects of possible attacks will be decreased. Through this study a combined model for locating of critical centers is suggested by identifying the effective factors in locating of these critical military centers and emphasizing of passive defense. In developing of the model, Hybrid model, Analytical network process, P-dispersion mathematical model, and an Improved numerical Taxonomy clustering technique (HAPIT) are used. It has been tried that these centers to be considered through three aspects of common, undesirable and military facilities.
Autonomous Incident Detection on Spectrometers Using Deep Convolutional Models

This paper focuses on improving the performance of scientific instrumentation that uses glass spray chambers for sample introduction, such as spectrometers, which are widely used in analytical chemistry, by detecting incidents using deep convolutional models. The performance of these instruments can be affected by the quality of the introduction of the sample into the spray chamber. Among the indicators of poor quality sample introduction are two primary incidents: The formation of liquid beads on the surface of the spray chamber, and flooding at the bottom of the spray chamber. Detecting such events autonomously as they occur can assist with improving the overall operational accuracy and efficacy of the chemical analysis, and avoid severe incidents such as malfunction and instrument damage. In contrast to objects commonly seen in the real world, beading and flooding detection are more challenging since they are of significantly small size and transparent. Furthermore, the non-rigid property increases the difficulty of the detection of these incidents, as such that existing deep-learning-based object detection frameworks are prone to fail for this task. There is no former work that uses computer vision to detect these incidents in the chemistry industry. In this work, we propose two frameworks for the detection task of these two incidents, which not only leverage the modern deep learning architectures but also integrate with expert knowledge of the problems. Specifically, the proposed networks first localize the regions of interest where the incidents are most likely generated and then refine these incident outputs. The use of data augmentation and synthesis, and choice of negative sampling in training, allows for a large increase in accuracy while remaining a real-time system for inference. In the data collected from our laboratory, our method surpasses widely used object detection baselines and can correctly detect 95% of the beads and 98% of the flooding. At the same time, out method can process four frames per second and is able to be implemented in real time.
Data-Centric Performance Improvement Strategies for Few-Shot Classification of Chemical Sensor Data

Metal oxide (MOX) sensors offer a low-cost solution to detect volatile organic compound (VOC) mixtures. However, their operation involves time-consuming heating cycles, leading to a slower data collection and data classification process. This work introduces a few-shot learning approach that promotes rapid classification. In this approach, a model trained on several base classes is fine-tuned to recognize a novel class using a small number (n = 5, 25, 50 and 75) of randomly selected novel class measurements/shots. The used dataset comprises MOX sensor measurements of four different juices (apple, orange, currant and multivitamin) and air, collected over 10-minute phases using a pulse heater signal. While high average accuracy of 82.46 is obtained for five-class classification using 75 shots, the model’s performance depends on the juice type. One-shot validation showed that not all measurements within a phase are representative, necessitating careful shot selection to achieve high classification accuracy. Error analysis revealed contamination of some measurements by the previously measured juice, a characteristic of MOX sensor data that is often overlooked and equivalent to mislabeling. Three strategies are adopted to overcome this: (E1) and (E2) fine-tuning after dropping initial/final measurements and the first half of each phase, respectively, (E3) pretraining with data from the second half of each phase. Results show that each of the strategies performs best for a specific number of shots. E3 results in the highest performance for five-shot learning (accuracy 63.69), whereas E2 yields the best results for 25-/50-shot learning (accuracies 79/87.1) and E1 predicts best for 75-shot learning (accuracy 88.6). Error analysis also showed that, for all strategies, more than 50% of air misclassifications resulted from contamination, but E1 was affected the least. This work demonstrates how strongly data quality can affect prediction performance, especially for few-shot classification methods, and that a data-centric approach can improve the results.
Quasi-3D photonic crystals for nanophotonics

Photonic crystals have a great deal of potential in the area of integrated optics. Waveguides with small bends may be formed allowing compact integrated photonic circuits to be formed. Two-dimensional planar photonic crystals are examined for use as integrated photonic circuits. They, however, possess an inherent loss associated with coupling to radiation modes in the surrounding media. Thus, three-dimensional photonic circuits are required in order to realize very low loss integrated photonic crystal circuits. A three-dimensional photonic crystal that is only a few periods thick, quasi-3-D, and can support low loss waveguides embedded in it needs to be identified. We examine several candidate 3-D photonic crystal structures to determine a suitable structure for the fabrication of quasi-3-D photonic crystals.
A Management System for Cut and Fill Earthworks Based on 4D CAD and EVMS

A cut and fill earthworks management system was developed based on 4D CAD and earned value method. The system is composed of a schedule management system, 4D CAD system, cost estimation system, and earned value management system (EVMS). LandXML was employed as the product model to represent terrain data, and IFC was used to represent the process model. We applied the system to a past actual earthworks project and demonstrated that it could facilitate enhancing the control and management of cost and schedule of construction works as well as incorporating the progress payment method effectively.
Numerical Investigation of Periodically Unsteady Pressure Field in a High Power Centrifugal Diffuser Pump

Pressure fluctuations are the main factors that can give rise to reliability problems in centrifugal pumps. The periodically unsteady pressure characteristics caused by rotor-stator interaction have been investigated by CFD calculation in a residual heat removal pump. Side chamber flow effect is also considered for the simulation to accurately predict the flow in whole flow passage. The pressure fluctuation results in time and frequency domains were considered for several typical monitoring points in impeller and diffuser channels. In addition, the pressure fluctuation intensity coefficient (PFIC) based on standard deviation was defined on each grid node for entire space and impeller revolution period. The results show that strong pressure fluctuation intensity can be found in the gap between impeller and diffuser. As a source, the fluctuation can spread to the upstream and downstream flow channels as well as the side chamber channels. Meanwhile, strong pressure fluctuation intensity can be found in the discharge tube of the circular casing. In addition, the obvious influence of operational flow rate on the PFIC distribution can be found. The analysis indicates that the pressure fluctuations in the aspects of both frequency and intensity can be used to comprehensively evaluate the unsteady pressure characteristics in centrifugal pumps.
Azospirillum Actinidiae sp. nov., a Nitrogen-Fixing Bacterium Isolated From The Roots of Kiwifruit Plants

A novel diazotrophic bacterium, designated CCTCC AB 2021101T, was isolated from fresh roots of kiwifruit. Cells of strain CCTCC AB 2021101T were Gram-negative, aerobic and rod-shaped, with motility provided by peritrichous flagella. The 16S rRNA analysis showed that strain CCTCC AB 2021101T belongs to the genus Azospirillum and is closely related to Azospirillum melinis (98.32%), Azospirillum oryzae (97.73%), Azospirillum lipoferum (96.98%), Azospirillum humicireducens (96.49%) and Azospirillum largimobile (96.01%) and lower sequence similarity (<96.0 %) to all other species of the genus Azospirillum. Strain CCTCC AB 2021101T was able to grow well at 35–40℃ and pH 6.0–7.0, and tolerated up to 3.0 % (w/v) NaCl. The major saturated fatty acids are C14:0, C16:0 and C18:0. C18:1 ω7c and C16:0 3-OH were the major unsaturated and hydroxylated fatty acid. The G+C content was 67.8 mol%. Strain CCTCC AB 2021101T gave positive amplification for dinitrogen reductase (nifH gene). Highest nifH gene sequence similarities were obtained with Azospirillum brasilense AWB14T(95.9%), Azospirillum zeae Gr24T(95.56%), Azospirillum picis DSM 19922T(96.79%), Azospirillum lipoferum B22T(94.88%) and Azospirillum oryzae COC8T(94.88%). The activity of the nitrogenase of the strain was further confirmed by acetylene-reduction assay, which was recorded as 81 nmol ethylene h-1. Based on these data, strain CCTCC AB 2021101T is considered to represent a novel endophytic diazotrophs species in the genus Azospirillum, for which the name Azospirillum actinidiae sp. nov. is proposed. The type strain is CCTCC AB 2021101T.
A Title 40 Code of Federal Regulations Part 191 Evaluation of Buried Transuranic Waste at the Nevada Test Site

In 1986, 21 m{sup 3} of transuranic (TRU) waste was inadvertently buried in a shallow land burial trench at the Area 5 Radioactive Waste Management Site on the Nevada Test Site (NTS). The U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office is considered five options for management of the buried TRU waste. One option is to leave the waste in-place if the disposal can meet the requirements of Title 40 Code of Federal Regulations (CFR) Part 191, 'Environmental Radiation Protection Standard for Management and Disposal of Spent Nuclear Fuel, High-Level, and Transuranic Radioactive Wastes'. This paper describes analyses that assess the likelihood that TRU waste in shallow land burial can meet the 40 CFR 191 standards for a geologic repository. The simulated probability of the cumulative release exceeding 1 and 10 times the 40 CFR 191.13 containment requirements is estimated to be 0.009 and less than 0.0001, respectively. The cumulative release is most sensitive to the number of groundwater withdrawal wells drilled through the disposal trench. The mean total effective dose equivalent for a member of the public is estimated to reach a maximum of 0.014 milliSievert (mSv) at 10,000 years, or approximately 10 percent of themore » 0.15 mSv 40 CFR 191.15 individual protection requirement. The dose is predominantly from inhalation of short-lived Rn-222 progeny in air produced by low-level waste disposed in the same trench. The transuranic radionuclide released in greatest amounts, Pu-239, contributes only 0.4 percent of the dose. The member of public dose is most sensitive to the U-234 inventory and the radon emanation coefficient. Reasonable assurance of compliance with the Subpart C groundwater protection standard is provided by site characterization data and hydrologic processes modeling which support a conclusion of no groundwater pathway within 10,000 years. Limited quantities of transuranic waste in a shallow land burial trench at the NTS can meet the requirements of 40 CFR 191. « less
Retrotransposons Down- and Up-Regulation in Aging Somatic Tissues

The transposon theory of aging hypothesizes the activation of transposable elements (TEs) in somatic tissues with age, leading to a shortening of the lifespan. It is thought that TE activation in aging produces an increase in DNA double-strand breaks, contributing to genome instability and promoting the activation of inflammatory responses. To investigate how TE regulation changes in somatic tissues during aging, we analyzed the expression of some TEs, as well as a source of small RNAs that specifically silence the analyzed TEs; the Drosophila cluster named flamenco. We found significant variations in the expression levels of all the analyzed TEs during aging, with a trend toward reduction in middle-aged adults and reactivation in older individuals that suggests dynamic regulation during the lifespan.
Theoretical Categories of Successful Collaboration and BIM Implementation within the AEC Industry

Researchers have found successful collaboration that spans organizational boundaries enhances the productivity of the design and construction process. Researchers and practitioners alike argue using Building Information Modeling (BIM) should lead to tighter collaboration and closer communication among project participants working in cross-organizational environments. Using data from observations over fifteen months of the integrated design process of a laboratory building project, the authors build a typology of the strategies of successful collaboration within the AEC industry. Then, using interview data from 70 architects, engineers and general contractors from across the U.S., we test our proposed typology to suggest how the collaboration process is implicated in inter-organizational BIM integration. The authors find that inter-organizational BIM-enabled projects and successful inter-organizational collaboration have shared theoretical categories: fostering integrated teams; implementing tools and strategies to encourage clear communication across the team; and developing transparent technology use. The authors argue that attempts at either will not be successful without first establishing the right social and organizational foundation that supports both collaboration and successful technology implementation.
An Iterative Learning-Based Modulation Scheme for Torque Control in Switched Reluctance Motors

This paper deals with an iterative learning approach for modulating the desired torque profile so as to obtain ripple-free torque in switched reluctance motors. Because of the highly nonlinear relation between torque, current, and rotor position for this motor, it is not possible to obtain a closed-form mathematical expression for current as a function of torque and rotor position. Thus, the current waveforms are conventionally computed by using the linear torque model of the motor, and it is well known that such a scheme results in high torque ripple. In this paper, a novel method is proposed to minimize the ripple. In this new scheme, the current is still computed using the linear torque model, but the value of the torque used for this is not the desired (specified) torque, but rather a modulated-desired torque that is obtained by repeated corrections to the desired torque from iteration to iteration. The conventional rectangular pulse profile is taken as the initial current waveform. The method require.
WBG and Si Hybrid Half-Bridge Power Processing Toward Optimal Efficiency, Power Quality, and Cost Tradeoff

Wide-bandgap (WBG) power semiconductors offer a higher switching frequency and lower switching loss than their silicon counterparts but suffer from a significantly higher component cost. In this article, we propose a new WBG and Si hybrid half-bridge (HHB) power processing approach, which combines the high-frequency performance of WBG and low cost of Si toward optimal tradeoff among efficiency, power quality, and cost. The HHB approach uses a low-frequency base-power Si half bridge in a typical power converter to achieve a full-power conversion at a low cost and a high-frequency fractional-power WBG half bridge in parallel to improve the efficiency and power quality at a reasonable cost penalty. A current ripple and a cost analysis model are developed in great detail to indicates that the HHB approach can achieve a 20%–50% device cost reduction in comparison to an all-WBG converter design while offering almost the same efficiency and power quality. A simple control strategy is developed to enable the unique operation of the proposed HHB approach in this article. The HHB approach combining with the proposed control strategy can be easily implemented in a wide range of power converters. A 3-kW bidirectional dc–dc converter is built using Si IGBTs and SiC mosfets as a case study to validate the HHB concept. In comparison with the all-SiC design, the HHB-based converter achieves a comparable efficiency and two times higher current spectrum with at least 17% total cost reduction and 33% capacitor rms current reduction.
Delay in the Effect of Restricting Community Mobility on the Spread of COVID-19 During the First Wave in the United States

Abstract Background It remains unclear how changes in human mobility shaped the transmission dynamic of coronavirus disease 2019 (COVID-19) during its first wave in the United States. Methods By coupling a Bayesian hierarchical spatiotemporal model with reported case data and Google mobility data at the county level, we found that changes in movement were associated with notable changes in reported COVID-19 incidence rates about 5 to 7 weeks later. Results Among all movement types, residential stay was the most influential driver of COVID-19 incidence rate, with a 10% increase 7 weeks ago reducing the disease incidence rate by 13% (95% credible interval, 6%–20%). A 10% increase in movement from home to workplaces, retail and recreation stores, public transit, grocery stores, and pharmacies 7 weeks ago was associated with an increase of 5%–8% in the COVID-10 incidence rate. In contrast, parks-related movement showed minimal impact. Conclusions Policy-makers should anticipate such a delay when planning intervention strategies restricting human movement.
Pediatric data from the All of Us research program: demonstration of pediatric obesity over time.

Objective To describe and demonstrate use of pediatric data collected by the All of Us Research Program. Materials and Methods All of Us participant physical measurements and electronic health record (EHR) data were analyzed including investigation of trends in childhood obesity and correlation with adult body mass index (BMI). Results We identified 19 729 participants with legacy pediatric EHR data including diagnoses, prescriptions, visits, procedures, and measurements gathered since 1980. We found an increase in pediatric obesity diagnosis over time that correlates with BMI measurements recorded in participants' adult EHRs and those physical measurements taken at enrollment in the research program. Discussion We highlight the availability of retrospective pediatric EHR data for nearly 20 000 All of Us participants. These data are relevant to current issues such as the rise in pediatric obesity. Conclusion All of Us contains a rich resource of retrospective pediatric EHR data to accelerate pediatric research studies.
Security Threats at Each Layer of Wireless Sensor Networks

Wireless sensor network is a combination of tiny devices called as sensor nodes which have computing, sensing and processing capabilities. Efficient design and implementation of wireless sensor networks have become a hot area of research in recent years due to the vast potential of the sensor networks to enable application that connect the physical world to the virtual world As WSN are deployed in hostile environment usually and can be physically accessible by an adversary; he/she can affect the confidentiality and integrity of the data as well as some other security measures. So security is a main concern for wireless sensor network protocol designers because of the wide security-critical applications of WSNs. This paper deals with the security aspects in the wireless sensor networks giving the probable counter measure for the same.
Simulation of Crack Propagation in Glass Panels Using Finite Element Analysis

Abstract The applicability of the discrete crack approach of finite element (FE) modelling for simulating the propagation of cracks in glass panels was investigated. Two methods of discrete analysis for crack propagation, namely the re-meshing method and node-splitting method, were considered in this investigation. The re-meshing method employs fracture mechanics theory to determine the initiation and direction of crack propagation, whereas the node-splitting method uses plastic strain as the fracture criterion. It was revealed that the re-meshing method can be used to simulate the path of crack propagation in a glass panel which is subject to out-of-plane static loading. Results from FE simulations using the re-meshing method were found to correspond well with observations from physical experimentation conducted in this research. The node-splitting method has also been studied in an attempt to simulate both the initiation and the propagation of cracks. Results were found to be sensitive to the size of the meshing.