Miracle-dz/UniFAR-FTUs huggingface dataset:
A low-profile wideband circularly polarized MIMO antenna with pattern and polarization diversity

Abstract The present work describes a unique planar low-profile wideband circularly polarized Multiple-Input and Multiple-Output (MIMO) antenna operating in the X-band, with pattern and polarization diversity over the entire axial-ratio bandwidth (ARBW). The design is unique in the sense that a simple grounded stub introduced between two linearly polarized monopole antennas has been used to realize wideband circular polarization, pattern diversity, and high isolation between antennas. The ARBW of the MIMO antenna is 2.45 GHz (8.11–10.56) 3 dB and its impedance matching bandwidth is 3.52 GHz (8.07–11.59). The isolation is better than 20 dB. The antenna can be easily adapted to operate other frequency bands by simple frequency scaling. It has been fabricated on an FR-4 substrate and its performance has been compared against several existing available antennas.
A Prognostic Model Based on DBN and Diffusion Process for Degrading Bearing

Remaining useful life (RUL) prediction is extremely significant to ensure the safe and reliable operation for bearing suffering from the deterioration. The main focus of the RUL prediction is to accurately predict the future failure event, and thus, how to quantify the prediction uncertainty will be a major concern. However, current deep learning based RUL prediction methods are difficult to reflect the uncertainty of the RUL prediction results. Toward this end, we propose a RUL prediction model based on the deep belief network (DBN) and diffusion process (DP) in this article. The proposed method consists of two parts: feature extraction combining DBN and locally linear embedding (LLE), DP-based RUL prediction. In the first part, DBN is used to extract deep hidden features behind the monitoring signals, and then the features with higher tendency are screened as the input of LLE. The health index that can truly reflect the bearing health condition is further determined through LLE. In the second part, a health index evolving model based on DP is presented and the probability density function (PDF) of the predicted RUL is accordingly derived in the sense of the first hitting time (FHT). As such, the proposed method holds promise to improve the prediction accuracy and facilitate the prognostic uncertainty. Finally, experimental studies on the bearing degradation data and the associated comparative analysis verify the effectiveness and superiority of the proposed method.
Dosimetric Significance of the ICRP's Updated Guidance and Models, 1989-2003, and Implications for U.S. Federal Guidance

Over the past two decades the U.S. Environmental Protection Agency (EPA) has issued a series of Federal guidance documents for the purpose of providing the Federal and State agencies with technical information to assist their implementation of radiation protection programs. Currently recommended dose conversion factors, annual limits on intake, and derived air concentrations for intake of radionuclides are tabulated in Federal Guidance Report No. 11 (FGR 11), published in 1988. The tabulations in FGR 11 were based on dosimetric quantities and biokinetic and dosimetric models of the International Commission on Radiological Protection (ICRP) developed for application to occupational exposures. Since the publication of FGR 11 the ICRP has revised some of its dosimetric quantities and its models for workers and has also developed age-specific models and dose conversion factors for intake of radionuclides by members of the public. This report examines the extent of the changes in the inhalation and ingestion dose coefficients of FGR 11 implied by the updated recommendations of the ICRP, both for workers and members of the public.
Effects of challenge feedinhg on the milk yield and its composition in high yielding buffaloes

An experiment was conducted on 18 healthy pregnant high yielding buffaloes (2000–2500 L potential) maintained at PAU dairy farm, Ludhiana. The animals were randomly divided into 3 groups (6 each) on basis of their body weight, previous lactation yield and parity; and provided normal pregnancy allowances of 2 kg (Tc) and challenge-fed (T1 = 3 kg & T2 = 4 kg), in addition to maintenance ration during 3 weeks pre-partum period. Post-partum feeding levels were kept uniform. The buffaloes were hand-milked scientifically in milking parlor. Milk samples were analyzed for milk fat, solid- not-fat (SNF), lactose and total solids. Buffaloes in T1 & T2 groups produced 3–5% more milk during 150 days lactation than control and showed higher peak yield (13.91 & 14.06 v/s 13.58), persistency (1.42 & 1.49 v/s 1.39) and extra net profit of Rs. 3.20 and 3.79 d−1 buffalo−1, respectively. Similarly, yields of different milk components were non-significant. The challenge-fed buffaloes excelled in nutrients body gains. The feeding schedule of T2 group comparatively faired well amongst the 2 challenge-fed groups and thereby stands recommended.
A ZVT Bidirectional Converter With Coupled-Filter-Inductor and Elimination of Input Current Notches

This article proposes a ZVT bidirectional buck/boost converter. The proposed converter benefits from the features of the coupled-filter-inductor, while there are no current notches on the current waveform of the input source. As a result, the lifetime of the batteries, which are the primary input source of the bidirectional converters increases, and also, the EMI noises on the equipment which is connected to the batteries would reduce. In the proposed converter, ZVS condition of the main switches and ZCS condition of the auxiliary switches are obtained, regardless of the condition of load, values of the input or output voltages, and the power flow direction. The proposed converter is thoroughly analyzed, and to confirm the theoretical analysis, the experimental results of a 200 W–100 kHz prototype for both the boost and buck modes are presented. Besides, the harmonic content of the input current is analyzed and compared, theoretically and practically.
WHY DO GENERAL PRACTITIONERS (NOT) SIGNAL? Opportunities and Limitations of Collaboration between General Practitioners and Social Service Providers*

Public health and social welfare subsystems are principally linked together by mutual interest in the basic care of elderly people. General practitioner (GP) services are parts of the social signaling system that promotes revealing unprovided needs. On the other hand, taking indigents into social care would make considerably easier the work of GPs. As a consequence, GPs' signaling should be a general practice everywhere. But social specialists experience the contrary. In order to explain the difference between the unity of interest in principle, and weak collaboration in reality, a theoretical model was elaborated and tested empirically. We have found that social service providers' preferences are not evident for GPs; therefore their willingness to signal depends on their opportunity of obtaining information.
Lean Project Management using Unmanned Aerial Vehicles

Development of a lean and automated progress tracking system is one of the most challenging subjects in the construction industry. Since the current methods depend on individual and manual inspections of the site, they may have various problems. For instance, results include a natural bias since field personnel makes interpretations depending on their educational and expertise level. From the practical point of view, manual data collection and their comparison with construction drawings and schedules are inefficient as it takes too much time. With the recent advancement of Unmanned Aerial Vehicles (UAVs) into the market and inclusion of lean project management principles, project management studies are inclined towards the digital and lean approaches. Within this perspective, the objective of this study is to reveal the use of UAVs as a lean project management tool. This paper indicates merely that UAVs have the potential for such a purpose.
Filtering Balanced-to-Single-Ended Power Dividers With Wide Range and High Level of Common-Mode Suppression

A new design approach for developing balanced-to-single-ended (BTSE) power dividers (PDs) to achieve high-level and wide range of common-mode (CM) suppression and minimum mode-conversion level is presented. The suppression of CM signals and mode conversion is realized by a microstrip-to-slotline transition, which is due to the orthogonality between the electric field of the microstrip line and slotline. Filtering responses are included in the differential-mode transmission performance, and multiple transmission zeros are generated by loading shunted coupled-line stubs. A multimode slotline resonator is used to provide multiple resonances in the passband, and these resonances can be easily controlled so that the operating bandwidth can be varied in a large frequency range. Based on this design approach, several BTSE PDs with different bandwidths are simulated in the EM environment. Prototypes are fabricated and tested to verify the design. The experimental results reveal that 200% fractional bandwidth of CM suppression is obtained. The CM suppression and mode-conversion levels are below −35 dB at all frequencies, which is extremely desired in differential circuits and systems.
Research on cloud energy storage service in residential microgrids

In residential microgrids, an energy storage system (ESS) can mitigate the intermittence and uncertainty of renewable energy generation, which plays an important role in balancing power generation and load consumption. Distributed energy storage (DES) is a common form of ESS. However, the high investment cost and fixed energy storage capacity limit their application in residential areas. This study proposes an improved service mechanism based on an alternative form of DES, cloud energy storage (CES). The energy transaction service is added in traditional CES service mechanism to enhance the power interaction between users. In addition, the pricing scheme of CES service fee is formulated, which is calculated based on the battery life loss caused by charging/discharging behaviour during the service period. This study considers that CES can improve energy storage utilisation and meet the energy storage requirements of users at a lower cost than DES. Finally, the CES service decisions are solved by the solver LINGO, including charging/discharging power decisions and energy trading decisions of users. Simulation results show that users' electricity costs are further reduced under the improved CES model. The rationality and economic feasibility of the improved CES model are demonstrated.
Intelligent Hazard-Risk Prediction Model for Train Control Systems

Although there has been substantial research in system analytics for risk assessment in traditional methods, little work has been done for safety risk prediction in communication-based train control (CBTC) system, especially intelligently predicting risk caused by the uncertainty in the system operation. Risk prediction and assessment of hazards in train control systems are vital for the safety and efficiency of urban rail transit. In this paper, we propose an intelligent hazard-risk prediction model based on a deep recurrent neural network for a new communication-mode CBTC system. First, a train-to-train communication-based train control (T2T-CBTC) system is proposed to improve the drawback of CBTC in information-exchanging mode. Then we design a risk prediction feature selection and generation method and estimate a critical function feature in the T2T-CBTC system by statistical model checking. Finally, we construct our intelligent hazard-risk prediction model based on a deep recurrent neural network using a long-short-term memory (LSTM) network. The model had excellent risk prediction classification results and performance in our experiment, even for unbalanced data set. This model consistently outperforms the deep belief network trained in Accuracy, Precision, Recall and F1-score for the hazard-risk prediction problem. Specifically, the mean accuracy is 97.2% and mean F1-score is 93.9% in overall performance of model. The improvements of our model against DBN model are 8.2% for Precision, 7% for Recall and 8% for F1-score.
Association of receptor activator of NF-kb (RANK) expression with bone metastasis in breast carcinomas.

1053 Background: Recently, it has been demonstrated that RANK is overexpressed in about 65% of primary breast tumors. Here we explored the clinical significance of RANK expression in early breast cancer. For this purpose we included in the study a series of early breast cancer primary tissues and correlated IHC RANK expression with skeletal clinical outcome. Methods: This study included 93 patients with breast cancer with complete clinicopathological information and up to 2 years of follow-up. Samples contained 15 lobular carcinomas and 77 ductal carcinomas; N0-1 versus N2-3: 63/29; HER2/neu ±/unknown: 25/55/13; sites of metastases: 16 patients only skeletal, 16 only visceral, 29 skeletal plus visceral, 32 without metastases. No patient was treated with neoadjuvant therapy. RANK protein expression was determined using immunohistochemistry. We considered RANK-positive patients when more than 50% of tumoral tissues was scored as grade 2 (intensity higher than internal control -macrophages-) or 3 (intensity .
Discrete sliding mode control based on exponential reaching law and time delay estimation for an asymmetrical six‐phase induction machine drive

This study deals with the problem of controlling rotor speed and stator currents of an asymmetrical six-phase induction machine with uncertain dynamics, disturbances, and unmeasurable rotor currents and proposes a robust non-linear variable structure controller. First of all, an outer control loop based on a proportional–integral regulator is performed to control the rotor speed and to construct the desired stator current references. Then, the inner loop is performed based on the proposed method that combines the time delay estimation method and discrete sliding mode control based on exponential reaching law. This structure allows an accurate and simple estimation of uncertainties and rotor currents, a high-tracking precision, a convergence of the stator currents to their known desired references in finite-time and chattering reduction. The design procedure is detailed step by step and the stability analysis and the convergence time are established for the current closed-loop system. Experimental work was carried out on an asymmetrical six-phase induction motor drive to show the effectiveness and performance of the proposed robust non-linear discrete method. The results obtained highlighted the good tracking performance of the stator currents.
Response Time and Time Headway of an Adaptive Cruise Control. An Empirical Characterization and Potential Impacts on Road Capacity

Road vehicles are characterized by increasing levels of automation and it is vital to understand the future impact on transport efficiency. Adaptive Cruise Control (ACC) is one of the first and most common automated functionalities available in privately owned vehicles. The effect of ACC on traffic flow has been widely studied by making assumptions on its operating strategy and on some of its important parameters such as the response time and the desired time headway. In the literature, these parameters are usually set to low values, based on the vehicle controller’s theoretical ability to respond within a very short time frame. Response time is known to be an important parameter in defining the capacity of the road and therefore, assuming a very short response time, studies usually conclude that systems like the ACC will contribute increasing the road capacity significantly. The present study aims at measuring the actual response time of an ACC-enabled vehicle in car-following conditions. A new methodology for the estimation of the controller’s response time and the desired time-gap was developed to this objective. Results show that the response time of the particular ACC controller was in the range 0.8s-1.2s, which is similar to what is commonly assumed for human drivers. In this light, the results of the present study question the common assumption that ACC or other automation technologies necessarily improve traffic flow and increase road capacity.
Comparing AutoDock and Vina in Ligand/Decoy Discrimination for Virtual Screening

AutoDock and Vina are two of the most widely used protein–ligand docking programs. The fact that these programs are free and available under an open source license, also makes them a very popular first choice for many users and a common starting point for many virtual screening campaigns, particularly in academia. Here, we evaluated the performance of AutoDock and Vina against an unbiased dataset containing 102 protein targets, 22,432 active compounds and 1,380,513 decoy molecules. In general, the results showed that the overall performance of Vina and AutoDock was comparable in discriminating between actives and decoys. However, the results varied significantly with the type of target. AutoDock was better in discriminating ligands and decoys in more hydrophobic, poorly polar and poorly charged pockets, while Vina tended to give better results for polar and charged binding pockets. For the type of ligand, the tendency was the same for both Vina and AutoDock. Bigger and more flexible ligands still presented a bigger challenge for these docking programs. A set of guidelines was formulated, based on the strengths and weaknesses of both docking program and their limits of validation.
Optimal Position of the Intermediate Coils in a Magnetic Coupled Resonant Wireless Power Transfer System

Coaxial coil topology is used as the transfer medium in traditional MCR-WPT (Magnetic Coupled Resonant Wireless Power Transfer) systems to improve the transfer characteristics. The intermediate coils are added to extend the transmission distance, whose positions are critical. This paper focuses on the optimal intermediate coil positions for an MCR-WPT system with four coaxial planar circular spiral coils. By modeling the MCR-WPT system, the mathematical expression of the self-inductance and the mutual inductance are used to calculate the load power of the MCR-WPT system, which is composed of four planar circular spiral coaxial coils, and using MATLAB. The optimal distance ratio between the adjacent coils for maximizing the power of load is proposed. Furthermore, the experiments are implemented from the network analyzer and the experimental platform. In the platform, the load power is measured at the different intermediate coil positions, and the optimal position at which the load power is maximized is found. Both experimental results obtained by the network analyzer and the experimental platform have validated the theoretical and simulation results and provided the correctness of the suggested ratios.
EFFECT OF CHRONIC ADMINISTRATION OF OPIOIDS (MORPHINE) ON GROWTH AND INTESTINAL MUCOSA IN MOUSE STRAIN BALB/C

Apart from the nervous system, the digestive system has the maximum opioids receptors which it indicates importance of the opioids in this system. It seems that morphine and other opiods compound have major harmful effects on intestinal tissue. Purpose of this study is to examine of the long-termed use of the morphine on growth and histomorphological structure of digestive system in mice strain Balb/c. Some mice were selected from three age groups (premature, mature and from premature to full mature). One hundred fifty mice (at the age of 21 days) were divided to 12 groups randomly. Groups consisted of six test groups (20 mice in each group), three control groups (5 mice in each group) and three sham groups (5 mice in each group). Control groups were maintained on stock dieted of tap water while sham groups dieted with tap water and sugar (5mg/ml). Test groups also used tap water, sugar and two different dosages of morphine (0.01mg/ml or 0.1mg/ml). Our study showed that in all tests groups, the chronic administration of escalating doses of the morphine caused decrease of the weight of mice. In addition, the long -termed use of morphine caused histological changes in small intestine and colon in all the groups of age. Invasion of mononuclear cell (especially lymphocyte) to mucosa was the most important histological change. In addition, villous height and intensity also decreased. This study suggested that the chronic consumption of opioids causes pathological change in gasterointestinal system. Vet. Res. Bull. 6,2:176-181, 2011.
An Online Hybrid Model for Temperature Prediction of Wind Turbine Gearbox Components

Condition monitoring can improve the reliability of wind turbines, which can effectively reduce operation and maintenance costs. The temperature prediction model of wind turbine gearbox components is of great significance for monitoring the operation status of the gearbox. However, the complex operating conditions of wind turbines pose grand challenges to predict the temperature of gearbox components. In this study, an online hybrid model based on a long short term memory (LSTM) neural network and adaptive error correction (LSTM-AEC) using simple-variable data is proposed. In the proposed model, a more suitable deep learning approach for time series, LSTM algorithm, is applied to realize the preliminary prediction of temperature, which has a stronger ability to capture the non-stationary and non-linear characteristics of gearbox components temperature series. In order to enhance the performance of the LSTM prediction model, the adaptive error correction model based on the variational mode decomposition (VMD) algorithm is developed, where the VMD algorithm can effectively solve the prediction difficulty issue caused by the non-stationary, high-frequency and chaotic characteristics of error series. To apply the hybrid model to the online prediction process, a real-time rolling data decomposition process based on VMD algorithm is proposed. With aims to validate the effectiveness of the hybrid model proposed in this paper, several traditional models are introduced for comparative analysis. The experimental results show that the hybrid model has better prediction performance than other comparative models.
Voltage and frequency regulation in an islanded microgrid with PEM fuel cell based on a fuzzy logic voltage control and adaptive droop control

Nowadays, the demand for electrical energy is increasing, and conventional power systems will face major problems in the future if they cannot generate extra demand for electrical energy. One of the best solutions for solving extra demand for electrical energy is the use of renewable resources to produce energy. The main aim of this study is designing and controlling the microgrid voltage and frequency. This study proposed the voltage and frequency control of an islanded microgrid based on fuzzy logic controller. The system considered for this study consists of Proton-Exchange Membrane Fuel Cell (PEMFC) that connected to parallel inverters to convert DC voltage to AC voltage. The control structure is based on adaptive droop control and fuzzy voltage control loop. Also, the proposed structure controls active and reactive powers and decreases power losses of the microgrid. Simulation results are presented to show the effectiveness and robustness of the proposed control structure over the conventional proportional-integral controller. It is shown that the proposed controller has good transient response under the output voltage PEMFC variation and load changes as disturbance.