Miracle-dz/UniFAR-FTUs huggingface dataset:
CNN-based region-of-interest image reconstruction from truncated data in cone-beam CT

We developed a region-of-interest (ROI) image reconstruction method that effectively reduces truncation artifacts in CBCT. By using U-Net-based deep learning (DL) methods, we devised a method to reduce truncation artifacts for ROI imaging. A total of 16294 image slices from 49 patient cases were used to generate projection data. The center of the projected image was cropped to a width of 150 mm. Then, the outer part of the truncation image was filled with each outermost pixel value for the initial correction. After the filtering process, the truncation area was cut off and used as input data in the DL model. Finally, inference images were reconstructed by use of the FDK algorithm. SSIM values for the test set of 14 patients were calculated as 0.541, 0.709 and 0.979 for FBP, Extension and the proposed ROI method, respectively. We have achieved promising results and believe that the proposed ROI image reconstruction method can help reduce radiation dose while preserving image quality
Preparation of β-FeOOH by ultrasound assisted precipitation route for aqueous supercapacitor applications

Abstract Iron oxide (β-FeOOH) nanoparticles were prepared by a simple precipitation method assisted by ultrasound at room temperature. Formation of phase pure β-FeOOH material was confirmed through the Reitveld refined XRD and FTIR analysis. The β-FeOOH nanoparticles prepared was found to have a narrow size distribution range with an average particle size of 138 nm. The optical band gap of the material was found to be 2.6 eV. The electrochemical performance of β-FeOOH was studied in a three electrode system using β-FeOOH coated on graphite sheet as the working electrode. The Ag/AgCl and platinum was used as the reference and counter electrodes, respectively. The KOH in distilled water was used as the aqueous electrolyte. The specific capacitance of the above material at a high current density of 1 A/g for 1 M, 3 M and 5 M aqueous KOH electrolyte was found to be 68.66, 138.67 and 88.17 F/g, respectively.
Analysis and implementation of a novel high step-up DC–DC converter with low switch voltage stress and reduced diode voltage stress

A new high step-up dc–dc converter is proposed in this study. This new high step-up converter utilises the input voltage, clamped-capacitor, and the secondary side of the coupled-inductor to charge the switched-capacitor and the secondary side of the coupled inductor also charges two multiplier capacitors in parallel during the turn-on interval of the switch. The input voltage, coupled-inductor, and multiplier capacitors are in series connection to the output to accomplish the purpose of high voltage gain during the turn-off interval of the switch. By adjusting the turns ratio of the coupled inductors, the proposed circuit does not need to be operated at high duty cycle to achieve the high voltage gain. The voltage stress of the switch and diodes can be decreased to cut down the cost. Moreover, the energy of the leakage inductance can be recovered to reduce the voltage spike of the switch. Therefore, the switch with lower conduction resistance can be applied to reduce the conduction loss and increase the efficiency. Finally, simulation and experiments are conducted. A prototype circuit with input voltage of 24 V, output voltage of 400 V, and output power of 200 W is implemented to validate the property of the proposed converter.
UNDERSTANDING LOCALIZATION OF SERVICE: A CHINESE PERSPECTIVE

Globalization of business and theory act to draw attention from the local. However, service experiences are culturally construed and extant research supports localisation as a basis for business success. The nature of Chinese collectivist-high context culture stands in marked contrast to Western individualistic-low context culture. Its distinct nature and rising economic significance make it ripe for attention by researchers seeking to develop theoretical explanations of service localization. This paper reports research that deepens understanding of service theory to evaluations of service quality, internal service, adoption of self-service technologies and predisposition to service. The results of this work support a culturally construed theoretical perspective towards localisation of service. This is significant for managers wishing to understand and influence design and delivery of service in the Chinese context.
Automatic Traffic Red-Light Violation Detection Using AI

Our research is the design of a traffic signal violation detection system using machine learning that learns to prevent the increasing number of road accidents. The system is optimized in terms of accuracy by using the region of interest and location of the vehicle with a red-signal state. By modifying some parameters in the YOLOV5s and re-training the COCO dataset, we can create a model which can be predicted with a high accuracy of 82% for vehicle identification, 90% for traffic signal status change and up to 86% for violation detection. This can be used for red light violation detection which will help the traffic police on traffic management.
Classification of global microglia proliferation based on deep learning with local images

Microglial cell proliferation in neural tissue (neuroinflammation) occurs during infections, neurological disease, neurotoxicity, and other conditions. In basic science and clinical studies, quantification of microglial proliferation requires extensive manual counting (cell clicking) by trained experts (∼ 2 hours per case). Previous efforts to automate this process have focused on stereology-based estimation of global cell number using deep learning (DL)- based segmentation of immunostained microglial cells at high magnification. To further improve on throughput efficiency, we propose a novel approach using snapshot ensembles of convolutional neural networks (CNN) with training using local images, i.e., low (20x) magnification, to predict high or low microglial proliferation at the global level. An expert uses stereology to quantify the global microglia cell number at high magnification, applies a label of high or low proliferation at the animal (mouse) level, then assigns this global label to each 20x image as ground truth for training a CNN to predict global proliferation. To test accuracy, cross validation with six mouse brains from each class for training and one each for testing was done. The ensemble predictions were averaged, and the test brain was assigned a label based on the predicted class of the majority of images from that brain. The ensemble accurately classified proliferation in 11 of 14 brains (∼ 80%) in less than a minute per case, without cell-level segmentation or manual stereology at high magnification. This approach shows, for the first time, that training a DL model with local images can efficiently predict microglial cell proliferation at the global level. The dataset used in this work is publicly available at: tinyurl.com/20xData-USF-SRC.
Broadband circularly polarized fabry‐perot antenna integrated with wideband phase shifter for satellite communication

This letter presents a broadband circularly polarized Fabry‐Perot (FP) antenna with high gain. A double‐layer partially reflective surface (PRS) with patch arrays with different sizes is employed. This proposed PRS can provide positive reflective phase gradient in a wideband frequency range, resulting in a significant improvement of 3‐dB gain bandwidth. To obtain the property of wideband circular polarization, a wideband microstrip patch antenna fed by a feeding network integrated with a broadband 90° phase shifter is applied as the primary source. A prototype operating at X‐band is fabricated and tested; whose 3‐dB gain bandwidth achieves 28.3% with the peak gain of 14.7 dBi. Moreover, its 3‐dB bandwidth of axial ratio (AR) can achieve 30% from 8.5 to 11.5 GHz. This antenna is a promising candidate for X‐band satellite communication due to its high gain, wideband AR, and fabrication simplicity. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:1109–1113, 2016
CONTROL OF MOBILE SENSOR NETWORKS: A STATE-OF-THE-ART REVIEW

This paper presents a state-of-the-art survey in the broad area of Mobile Sensor Networks (MSNs). There is currently a great deal of interest in having autonomous vehicles carrying sensors and communication devices that can conduct ISR (intelligence, surveillance and reconnaissance) operations. Although this paper will discuss issues common to mobile sensor networks, the applications will generally be associated with autonomous vehicles, particularly Unmanned Vehicles (UVs). This paper will focus primarily on decentralized architectures, however, in the case of perfect and complete communications, the decentralized solution converges to a centralized one. Areas that are addressed are: 1. mission definition languages that allow the human to compose a mission defined in terms of tasks, 2. communication issues including hardware, software, and network connectivity, 3. task allocation among the assets generally by a market based approach, 4. path planning for individual agents including optimization of performance criteria considering risks and nofly zones, and 5. platform motion control using autopilots with and without GPS signals and including collision avoidance.
Design and aerodynamic simulation of low Reynolds number rotor airfoil

This research focuses on the thin circular arc rotor airfoils at a low Reynolds number.A novel thin circular arc airfoil with a convex structure was designed in consideration of its demand for high aerodynamic performance,high structural strength,lightweighting and easy manufacture.A convex curve on the upper surface of the airfoil was adopted to increase the thickness of airfoil at the partial chord and a stiffener in the airfoil was installed to improve the structural strength of blade span wise.The designed thin circular arc airfoil has the maximum thickness of 4.3%,a circular average thickness of 2.5%,the maximum camber of 5.5% and an average camber of 4.5%. Numerical simulations for computing the aerodynamic performance of the airfoil were performed at the representative Reynoldsnumber between 40,000 and 100,000,and the angle of attack(AOA)from-4°to 12°by using the two dimensional steady and incompressible Navier-Stoke equations.The pressure coefficient distribution line of airfoil surfaces and the velocity vector were acquired.A carbon fiber rotor with a diameter of 40 cm,a mass of 15 g and rotor pitch of 15.7cm was manufactured with the present airfoil,and the experiments on the lift force and the structural strength in a hover state were performed and the results show the performance of the airfoil meets the use requirments.At present,the developed rotor airfoil has been successfully used in a rotor aircraft.
Low-Cost Connected Work Zone Devices with Simplified Architecture

Connected work zone devices for safety, traffic monitoring, and performance evaluation are important assets in road construction projects. Challenges for implementation and connectivity present a barrier to their use and full realization of benefits. Typical connected work zone devices require dedicated cellular modems with monthly data charges for each device. The numerous connections or proprietary platforms hinder integration with a central advanced traffic management system. The described architecture presents considerable costs in data ownership and security concerns. This paper presents an alternative architecture wherein many inexpensive monitoring and incident detection devices read and process sensor data and communicate information by radio link to a single internet-connected hub that forwards information to a central server. The server then notifies client applications that support work zone monitoring and incident response. From a field test of the radio units in an active work zone, the effective transmission range was found to be 3 km. All devices in a work zone up to 6 km in length could be serviced by a single internet-connected base receiver station centered within it. Prototype devices were created using readily and inexpensively available sensors and microcontrollers. An example dashboard was created to show real-time work zone device and sensor information on a mapping interface. This project shows how use of connected work zone devices can be expanded at low cost using commonly available hardware and skills with a simplified architecture and encapsulated complexity from the standpoint of work zone management personnel while retaining data ownership.
A review of machine learning applications in soccer with an emphasis on injury risk

This narrative review paper aimed to discuss the literature on machine learning applications in soccer with an emphasis on injury risk assessment. A secondary aim was to provide practical tips for the health and performance staff in soccer clubs on how machine learning can provide a competitive advantage. Performance analysis is the area with the majority of research so far. Other domains of soccer science and medicine with machine learning use are injury risk assessment, players’ workload and wellness monitoring, movement analysis, players’ career trajectory, club performance, and match attendance. Regarding injuries, which is a hot topic, machine learning does not seem to have a high predictive ability at the moment (models specificity ranged from 74.2%-97.7%. sensitivity from 15.2%-55.6% with area under the curve of 0.66–0.83). It seems, though, that machine learning can help to identify the early signs of elevated risk for a musculoskeletal injury. Future research should account for musculoskeletal injuries’ dynamic nature for machine learning to provide more meaningful results for practitioners in soccer.
Study on Exploding Wire Compression for Evaluating Electrical Conductivity in Warm-Dense Diamond-Like-Carbon

To improve a coupling efficiency for the fast ignition scheme of the inertial confinement fusion, fast electron behaviors as a function of an electrical conductivity are required. To evaluate the electrical conductivity for low-Z materials as a diamond-like-carbon (DLC), we have proposed a concept to investigate the properties of warm dense matter (WDM) by using pulsed-power discharges. The concept of the evaluation of DLC for WDM is a shock compression driven by an exploding wire discharge with confined by a rigid capillary. The qualitatively evaluation of the electrical conductivity for the WDM DLC requires a small electrical conductivity of the exploding wire. To analyze the electrical conductivity of exploding wire, we have demonstrated an exploding wire discharge in water for gold. The results indicated that the electrical conductivity of WDM gold for 5000 K of temperature has an insulator regime. It means that the shock compression driven by the exploding wire discharge with confined by the rigid capillary is applied for the evaluation of electrical conductivity for WDM DLC.
Bionic Antenna with Low RCS for Microstrip Application

In order to solve the conflict between RCS(Radar Cross Section) reduction and performance of microstrip antenna,bionics principle is applied to antenna,and a bionic butterfly microstrip antenna is presented in this paper.The structure is cutting the fuscous area of butterfly in the sunshine away based on bow-tie patch.Simulation and measured results and analysis demonstrate that this bionic antenna can not only guarantee the antenna radiation performance,but also reduce the RCS of the antenna significantly at frequency range from 4 GHz to 8 GHz,the largest reduction is up to 23 dBsm.
EFFECTS OF INTERNATIONAL TRADE ON ECONOMIC GROWTH OF ECONOMIC COMMUNITY OF WEST AFRICAN STATES (ECOWAS)

Economic literature identifies international trade as one of the channels through which sustainable economic growth can be achieved. For years, the relevance of trade in economic growth process has been one of the most commonly debated topics among economists and policy makers in Africa. This study investigates the effects of international trade on the economic growth of Economic Community of West African States (ECOWAS) from 2000 to 2018 across the 15 countries of the sub-region. Fixed effect model in a panel data environment was used for the analysis. The variables of interest are real gross domestic product, exports, imports, exchange rate, balance of payments and gross capital formation. The results show that exports, imports, exchange rate and balance of payments exert significant positive effects on economic growth of the ECOWAS, while gross capital formation exerts significant negative effect on growth of the economy of the countries. However, the independent variables jointly showed significant growth effect. Consequently, this study recommends that the ECOWAS should explore modern technology to transform their raw materials into intermediate export goods in order to increase the limited production and export base so as to become more competitive in international trade relations. Also, the imports of the sub-region should be skewed towards intermediate production inputs such as technology, machineries and chemicals which, when combined with the abundantly available human capital, would increase the production of value-added exports volumes, improve trading position and ultimately improve economic growth of the sub-region
A holistic approach to lead pipe scale analysis: Importance, methodology, and limitations

With lead service lines (LSLs) remaining for decades to come, scale analyses are critical to helping limit lead exposure from drinking water. This laboratory has used an integrated suite of analytical techniques to characterize the elemental composition, mineral identification, and physical features of scales, helping the water industry to evaluate, predict, and reduce lead corrosion. The methods used in this laboratory to prepare and analyze the LSL scale, and guidance to achieving reliable and meaningful results, are described. Primary methods include the following: optical microscopy, powder X‐ray diffraction, inductively coupled plasma spectroscopy, X‐ray fluorescence, scanning electron microscopy with energy dispersive spectroscopy, combustion and coulometric analyses of C and S, and X‐ray absorption spectroscopy. Examples of associated pitfalls and ways to avoid them are provided, including pipe excavation/transport, sample preparation, analysis, and data interpretation. Illustrative examples are presented of practical scale analysis questions that could be answered by combinations of pipe scale analyses.
Substation Locating and Sizing Based on Hybrid Genetic Algorithm

A novel hybrid genetic algorithm (GA-LA) based on alternative location-allocation and genetic algorithm is proposed to optimize the locations and sizes of distribution substations without candidate locations. The algorithm adopts a three-dimensional coding strategy including numbers, locations and sizes of new substations. It also designs the crossover and mutation operator adaptive to the strategy. For location sub-problem, the GA-LA algorithm combines alternative location-allocation and genetic algorithm together and after GA operator's global searching in the population, the LA operator for local optimization in the chromosomes is developed. The results demonstrate that GA-LA algorithm has better global searching performance and convergence property than traditional algorithm. The method proposed has a promising application in large-scale practical problem.
AN UPDATED REVIEW ON: FLOATING DRUG DELIVERY SYSTEM (FDDS)

Recent technological and scientific research has been devoted to the development of rate controlled drug delivery systems to overcome physiological adversities such as short gastric residence times and unpredictable gastric emptying times. Differences in gastric physiology such as gastric pH and motility exhibit both intra and inter subject variability demonstrating significant impact on gastric residence time and drug delivery behavior. This triggered an increased interest towards formulation of novel delivery systems which retained in the stomach for prolonged and predictable period of time. Several approaches such as floating drug delivery systems (FDDS), swelling and expanding systems, bioadhesive systems, modified shape systems, high density systems or other delayed gastric emptying devices have been discovered till now. FDDS are of particular interest for drugs that are locally active and have narrow absorption window in stomach or upper small intestine, unstable in the intestinal or colonic environment, and exhibit low solubility at high pH values. This review article is in pursuit of giving detailed information on the pharmaceutical basis of their design, classification, advantages, in vitro and in vivo evaluation parameters, and the future potential of FDDS.
Establish of an Initial Platinum-Resistance Predictor in High-Grade Serous Ovarian Cancer Patients Regardless of Homologous Recombination Deficiency Status

Backgrounds Ovarian cancer (OC) is still the leading aggressive and lethal disease of gynecological cancers, and platinum-based regimes are the standard treatments. However, nearly 20%–30% of patients with OC are initial platinum resistant (IPR), and there is a lack of valid tools to predict whether they will be primary platinum resistant or not prior to chemotherapy. Methods Transcriptome data from The Cancer Genome Atlas (TCGA) was downloaded as the training data, and transcriptome data of GSE15622, GSE102073, GSE19829, and GSE26712 were retrieved from Gene Expression Omnibus (GEO) as the validation cohorts. Differentially expressed genes (DEGs) were selected between platinum-sensitive and platinum-resistant patients from the training cohort, and multiple machine-learning algorithms [including random forest, XGboost, and least absolute shrinkage and selection operator (LASSO) regression] were utilized to determine the candidate genes from DEGs. Then, we applied logistic regression to establish the IPR signature based on the expression. Finally, comprehensive clinical, genomic, and survival feature were analyzed to understand the application value of the established IPR signature. Results A total of 532 DEGs were identified between platinum-resistant and platinum-sensitive samples, and 11 of them were shared by these three-machine learning algorithms and utilized to construct an IPR prediction signature. The area under receiver operating characteristic curve (AUC) was 0.841 and 0.796 in the training and validation cohorts, respectively. Notably, the prediction capacity of this signature was stable and robust regardless of the patients’ homologous recombination deficiency (HRD) and mutation burden status. Meanwhile, the genomic feature was concordant between samples with high- or low-IPR signature, except a significantly higher prevalence of gain at Chr19q.12 (regions including CCNE1) in the high-IPR signature samples. The efficacy of prediction of platinum resistance of IPR signature successfully transferred to the precise survival prediction, with the AUC of 0.71, 0.72, and 0.66 to predict 1-, 3-, and 5-year survival, respectively. At last, we found a significantly different tumor-infiltrated lymphocytes feature, including lower abundance of CD4+ naive T cells in the samples with high-IPR signature. A relatively lower tumor immune dysfunction and exclusion (TIDE) value and more sensitivity to multiple therapies including Gefitinib may suggest the potency to transfer from platinum-based therapy to immunotherapy or target therapies in patients with high-IPR signature. Conclusion Our study established an IPR signature based on the expression of 11 genes that could stably and robustly distinguish OC patients with IPR and/or poor outcomes, which may guide therapeutic regimes tailoring.