Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental Investigation of Decontamination Factor Dependence on Aerosol Concentration in Pool Scrubbing

Because a pool scrubbing is important for reducing radioactive aerosols to the environment for a nuclear reactor in a severe accident situation, many researches have been performed. However, decontamination factor (DF) dependence on aerosol concentration was seldom considered in an aerosol number concentration with limited aerosol coagulation. To investigate an existence of DF dependence on the concentration, DF in a pool scrubbing with 2.4 m water submergence was derived from aerosol measurements by light scattering aerosol spectrometers. It was observed that DF increased monotonically with decreasing particle number concentration in a constant thermohydraulic condition: a gradual increase from 10 to 32 in the range of 1.3×1011 - 8.0×1011/m3 at the inlet and a significant increase from 32 to 77 in the range of 3.6×1010 - 1.3×1011/m3. Two validation experiments were conducted in the range with the gradual DF increase to confirm whether the DF dependence is a real pool scrubbing phenomenon. In addition, characteristics of the DF dependence in different water submergences were investigated experimentally. It was found that the DF dependence became more significant in higher water submergence. Significant DF dependence was observed in the condition of the water submergence higher than 1.6 m and the inlet particle number concentration less than around 1×1011 /m3. It is recommended to perform further analysis for the DF dependence mainly in such condition since it could make a difference to both experiment and model of the pool scrubbing.
Complementary and alternative medicine: A new vista in dental management

Introduction: Since the dawn of civilization, mankind has been plagued by pathogen and its ensuing disease process and to overcome the outcome of the disease, various medical therapies have been formulated over the time. With the evident of medical therapies various side effects of the drugs used have come up and to overcome those side effects complementary and alternative medicine (CAM) has evolved. Aim: The goal of this study is to examine the relationship between the disease condition and the usage of the CAM therapy among the general population. Materials and Method: The CAM encompassed number of therapies so, the survey instrument is a self modified designs questionnaire based on previous studies carried out in the literature. Questionnaire will be filled by the patients visiting a dental school with any dental problem. First part of survey instrument incorporates questions regarding demographic characteristics. While the second part of survey consisted of 17 medical /dental conditions for which the patient visited a dental college and have approached for the management of these diseases. Results: More than half respondents were females(53.8%)with the common age group of 61-80 year old. The most frequent oral health problem was tooth ache (70.3%), followed by other problems and most frequently used CAM therapy was herbals. Conclusion: A large proportion of dental patients reported use of CAM- therapies . Gender and the age group was significant factor. A more refined instrument should be used for the future studies for understanding how CAM usage is associated with dental problems. Keywords: Complementary and alternative medicine (CAM), Dental school clinic, Dental problems, Self-medication, Prevalence
Ensemble of Deep Convolutional Neural Networks for Classification of Early Barrett’s Neoplasia Using Volumetric Laser Endomicroscopy

Barrett’s esopaghagus (BE) is a known precursor of esophageal adenocarcinoma (EAC). Patients with BE undergo regular surveillance to early detect stages of EAC. Volumetric laser endomicroscopy (VLE) is a novel technology incorporating a second-generation form of optical coherence tomography and is capable of imaging the inner tissue layers of the esophagus over a 6 cm length scan. However, interpretation of full VLE scans is still a challenge for human observers. In this work, we train an ensemble of deep convolutional neural networks to detect neoplasia in 45 BE patients, using a dataset of images acquired with VLE in a multi-center study. We achieve an area under the receiver operating characteristic curve (AUC) of 0.96 on the unseen test dataset and we compare our results with previous work done with VLE analysis, where only AUC of 0.90 was achieved via cross-validation on 18 BE patients. Our method for detecting neoplasia in BE patients facilitates future advances on patient treatment and provides clinicians with new assisting solutions to process and better understand VLE data.
Proton Irradiation-Induced Random Telegraph Signal Noise in a $2\text{k}\times2\text{k}$ 4T CMOS Active Pixel Sensor: Testing, Detection, and Modeling

This paper presents our recent study progress on proton-irradiated-induced random telegraph signal (RTS) in a high-resolution CMOS active pixel sensor (APS). First, RTS waveforms of a commercial $2\text{k} \times2\text{k}$ 4T CMOS APS chip in 180-nm CMOS technology are tested under the 10-MeV proton irradiation. Second, a novel adaptive automatic detection method (AADM) based on real-time thresholds is proposed for the sequential processing of a large batch of RTS pixels. Real-time thresholds and two-stage reconstruction algorithms are employed to improve the validity and correctness of RTS reconstruction. The proposed detection method which can realize the batch autoprocessing by using an adaptive filter will improve the detection efficiency. Third, a new approach to model the RTS maximum transition amplitude distribution is presented. It has been proven that the double exponential distribution can fit the RTS maximum transition amplitude distribution better. Two models are proposed to predict the contributions due to the ionizing effects and displacement damage effects. Finally, the error analysis is given. The errors between the simulated data of the proposed models and experimental results are all less than 5.5 %.
Efficiency Bound of Radiative Wireless Power Transmission Using Practical Antennas

In this communication, we provide the efficiency bound of radiative wireless power transmission (WPT) for several types of practical receiving antennas. The optimal current distribution of the transmitting surface is analytically derived. In addition, the maximum bound of the power transfer efficiency (PTE) and the optimal shape of the base station current are found in terms of the transmitting area and the transfer distance. Examples applying the proposed theory to three types of practical mobile antennas are shown and the results are compared with those of previous reports, demonstrating significant differences. The results indicate that the optimum current distribution on the transmitting surface and the maximum efficiency of radiative WPT depend on the radiating field pattern of the mobile antenna. The results further show that microwave power transmission using a compact patch antenna can achieve high power transmission efficiency, especially in the Fresnel region.
Long Term Impact in Reinforced Recycled Concrete Beams Under 9-Month Loading

Green concrete is an active area of research. Structural demolishing waste is a global serious problem, particularly in urban areas. This research paper presents the experimental evaluation of the effect of long term loading on reinforced green concrete beams. Three beams were cast with partial replacement of natural coarse aggregates with demolished old concrete. Three beams were cast with all-natural coarse aggregates to compare the results. The beams were mounted on purpose made frames for 9 months. Deflection, strain and cracking in beams were monitored on a daily basis. After 9 months, the beams were tested until failure in a universal load testing machine under central point load. It was observed that the proposed beams exhibited 3.55% reduction in maximum load caring capacity compared to control specimens. The obtained results show good performance of the proposed green concrete beams under 9-month long term loading.
The Potential and Status of Renewable Energy Development in Malaysia

The Malaysian Government has set an ambitious target to achieve a higher penetration of Renewable Energy (RE) in the Malaysian energy mix. To date, Malaysia has approximately 2% of its energy coming from RE generation sources compared to the total generation mix and targets achieving 20% penetration by 2025. The current energy mix for Malaysia power generation is mainly provided by natural gas and coal. The discussion will cover the traditional sources of generation including natural gas, coal and big hydro stations. In addition, the paper will cover in depth the potential of RE in the country, challenges, and opportunities in this sector. This study can give an initial evaluation of the Malaysian energy industry, especially for RE and can initiate further research and development in this area in order to support the Government target to achieve RE target of 20% by 2025.
Building Student Skills and Capabilities in Information Technology and e-Business: A Moving Target

In discipline areas such as information technology and eBusiness, technology advances so rapidly that the issue of developing student skills and capabilities adequate to the demands of the industry becomes a moving target. Industryrelated learning models such as cooperative education can help academic programmes meet the challenge of keeping the IT and eBusiness curricula up-to-date. This paper presents the results of an investigation into student and employer perceptions of the relevance of the professional academic content and outcomes of an undergraduate programme with specializations in IT and in eBusiness. The research models used in the study are derived from a general framework, based on a nomological net of constructs representing three major stakeholder groups: academia, students, and industry. The study found that while both employers and students placed an increased emphasis on technical skills, the need for better understanding of the processes of convergence and integration within the business was also evidenced. Areas in need of specialized curriculum development are identified, as well as a possible misconstruction of the eBusiness discipline as perceived by employers and students.
IE5 Energy-Efficiency Class Synchronous Reluctance Motor With Fractional Slot Winding

This paper considers an optimization of the IE5 four-pole synchronous reluctance motor of a new design. The motor has an original rotor design and a stator with a fractional-slot winding (2.5 slots per pole and phase). The target parameters of optimization are the resulting efficiency of the motor at the fan load profile, the torque ripple, the required power of the frequency converter, and the total harmonic distortion of the supply voltage. The motor efficiency is much higher than the IE5 class requirement and remains high in wide range of powers at the fan load profile. Also, the motor has low torque ripple despite that its rotor and stator have no skewing.
Graphene-Based Cylindrical Pillar Gratings for Polarization-Insensitive Optical Absorbers

In this study, we present a two-dimensional dielectric grating which allows achieving high absorption in a monolayer graphene at visible and near-infrared frequencies. Dielectric gratings create guided-mode resonances that are exploited to effectively couple light with the graphene layer. The proposed structure was numerically analyzed through a rigorous coupled-wave analysis method. Effects of geometrical parameters and response to the oblique incidence of the plane wave were studied. Numerical results reveal that light absorption in the proposed structure is almost insensitive to the angle of the impinging source over a considerable wide angular range of 20°. This may lead to the development of easy to fabricate and experimentally viable graphene-based absorbers in the future.
Performance of LEMMO with artificial neural networks for water systems optimisation

ABSTRACT Optimisation algorithms could potentially provide extremely valuable guidance towards improved intervention strategies and/or designs for water systems. The application of these algorithms in this domain has historically been hindered by the extreme computational cost of performing hydraulic modelling of water systems. This is because running an optimisation algorithm generally involves running a very large number of simulations of the system being optimised. In this paper, a novel optimisation approach is described, based upon the ‘learning evolution model for multi-objective optimisation’ algorithm. This approach uses deep learning artificial neural network meta-models to reduce the number of simulations of the water system required, without reducing the accuracy of the optimisation results. This is then compared to an industry standard optimisation approach, showing results with increased speed of convergence and equivalent or improved accuracy. Therefore, demonstrating that this approach is suitable for use in highly computationally demanding areas such as water systems optimisation.
Molecular Specific and Sensitive Detection of Pyrazinamide and Its Metabolite Pyrazinoic Acid by Means of Surface Enhanced Raman Spectroscopy Employing In Situ Prepared Colloids

The prodrug pyrazinamide (PZA) is metabolized by the mycobacteria to pyrazinoic acid (POA), which is expelled into the extracellular environment. PZA resistance is highly associated to a lack of POA efflux. Thus, by detecting a reduction of the concentration of POA in the extracellular environment, by means of lab-on-a-chip (LoC)-SERS (surface-enhanced Raman spectroscopy), an alternative approach for the discrimination of PZA resistant mycobacteria is introduced. A droplet-based microfluidic SERS device has been employed to illustrate the potential of the LoC-SERS method for the discrimination of PZA resistant mycobacteria. The two analytes were detected discretely in aqueous solution with a limit of detection of 27 µm for PZA and 21 µm for POA. The simultaneous detection of PZA and POA in aqueous mixtures could be realized within a concentration range from 20 μm to 50 μm for PZA and from 50 μm to 80 μm for POA.
Locating Software, Video Game, and Editing Electronics Firms: Using Microgeographic Data to Study Barcelona

ABSTRACT This paper analyzes location patterns of software, video game, and editing electronics firms (hereafter SVE) in the Metropolitan Area of Barcelona using microgeographic data. These industries are mainly attracted by agglomeration economies look to benefit from skilled labor and spillover effects, and tend to cluster in large metropolitan areas. However, less is known about their detailed location patterns inside these areas. We contribute to the empirical literature by identifying how SVE firms are concentrated in some core areas of the metropolitan area. Our empirical application includes using the Nearest Neighbor Index (NNI) and M-functions, as well as local spatial autocorrelation indicators.
A Filter Model Based on Hidden Generalized Mixture Transition Distribution Model for Intrusion Detection System in Vehicle Ad Hoc Networks

Vehicle ad hoc networks (VANETs) are considered to be the next big thing that will remarkably change our lives, since this kind of technology is able to make our lives and roads safer. Due to the very fast move and high dynamic in VANETs, it is important to quickly ascertain the reliability of information. Although intrusion detection system (IDS) has been proposed as a reliable approach to protect VANETs against attacks, its overhead is serious, which spends too much time on detection, especially when the number of vehicles increases. Thus, in this paper, we propose a novel filter model based on a hidden generalized mixture transition distribution model (HgMTD) in VANETs, called FM-HgMTD, which can quickly filter the messages from neighboring vehicles so as to reduce the overhead and detection time. It adopts a well-known multi-objective optimization (NSGA-II) algorithm combined with an expectation-maximization (EM) algorithm to forecast the future states of neighboring vehicles and then to filter out malicious messages, by monitoring the change of the state pattern of each neighboring vehicle. In addition, a timeliness method is used to maintain the accuracy of the forecast. The experiments show that IDS with the proposed FM-HgMTD has better performance than other available IDSs in terms of detection rate, detection time, and overhead.
In Situ Measurements of Energy Consumption and Indoor Environmental Quality of a Pre-Retrofitted Student Dormitory in Athens

In the following years all European Union member states should bring into force national laws on the energy performance of buildings. Moreover, university campus dormitories are buildings of great importance, due to their architectural characteristics and their social impact. In this study, the energy performance along with the indoor environmental conditions of a dormitory of a university has been analysed. The in situ measurements included temperature, relative humidity, concentrations of carbon dioxide, total volatile organic compounds, and electrical consumption; lastly, the energy signature of the whole building was investigated. The study focused on the summer months, during which significantly increased thermal needs of the building were identified. The ground floor was found to be the floor with the highest percentage of thermal conditions within the comfort range, and the third floor the lowest. Lastly, a significant correlation between electrical consumption and the outdoor temperature was presented, highlighting the lack of thermal insulation. Overall, it was clear that a redesign of the cooling and heating system, the installation of a ventilation system, and thermal insulation are essential for improving the energy efficiency of this building.
Modelling, analysis and improvement of an integrated chance-constrained model for level of repair analysis and spare parts supply control

In traditional practices, maintenance system and spare parts inventory control are usually considered in isolation, resulting in suboptimality. In a military system, the level of repair analysis (LORA) is often employed to help operate its repair networks. In this paper, we consider an integrated LORA and inventory control problem and formulate this problem as a mixed-integer nonlinear programming problem with chance constraints. Two second-order cone constraints are proposed to approximate the chance constraints. Furthermore, we propose an outer approximation (OA) algorithm based on the OA cuts. Extensive numerical results show that the OA algorithm significantly improves the computational efficiency under various types of components and network complexity. Next, we investigate the influence of service level and resource capacity, and propose the findings. Our results indicate that a higher service level leads to steeper costs, more resources, larger storage and heavier repair burdens at operating sites. Moreover, enhancements in resource capacity from the status quo lead to improvements in repairs and shrinkage in discards, bringing direct economic benefits. The insights extend to uncertain settings. It may be initially counterintuitive for many practitioners that demand uncertainty poses relatively subtle impacts.
Contrasting Crash- and Non-Crash-Involved Riders: Analysis of Data from the Motorcycle Crash Causation Study

Motorcycle crashes and fatalities remain a significant public health problem as fatality rates have increased substantially as compared to other vehicle types in the United States. Analysis of causal factors for motorcycle crashes is often challenging given a lack of reliable traffic volume data and the fact that such crashes comprise a relatively small portion of all traffic crashes. Given these limitations, on-scene crash investigations represent an ideal setting through which to investigate the precipitating factors for motorcycle-involved crashes. This study examines motorcycle crash risk factors by employing data recently made available from the Federal Highway Administration Motorcycle Crash Causation Study (MCCS). The MCCS represents a comprehensive investigative effort to determine the causes of motorcycle crashes and involved the collection of in-depth data from 351 crashes, as well as the collection of comparison data from 702 paired control observations in Orange County, California. This dataset provides a unique opportunity to understand how the risk of crash involvement varies across different segments of the riding population. Logistic regression models are estimated to identify the rider and vehicle attributes associated with motorcycle crashes. The results of the study suggest that motorcycle crash risks are related to rider age, physical status, and educational attainment. In addition to such factors outside of the rider’s control, several modifiable risk factors, which arguably affect the riders’ proclivity to take risks, were also found to be significantly associated with motorcycle crash risk, including motorcycle type, helmet coverage, motorcycle ownership, speed, trip destination, and traffic violation history.
How loud is too loud? noise from domestic mechanical ventilation systems

Abstract Noise from domestic ventilation systems is currently a little understood problem in the UK. Other European countries that have a longer history of using mechanical domestic ventilation systems have introduced noise limits for these systems. Without mandatory limits for noise in UK, noise is not a factor that is often considered during the design. However, noise can be a significant constraint to the use of ventilation systems. Research is reviewed from across Europe and North America which indicates residents turn off ventilation equipment that has objectionable noise. Without adequate ventilation in modern airtight dwellings, poor air quality can have a significantly adverse effect on the health of the occupants. There is a lack of evidence in the literature and performance standards for appropriate noise metrics and values that occupants find acceptable: this research is urgently required, and the steps to realise this are outlined; interim noise limits are proposed. Causes of excessive noise are found to originate due to problems during the design, procurement, installation, commissioning and operation of ventilation systems. A suitable metric is required along with regulatory control to ensure that residents are not forced to choose between intolerable noise or inadequate air quality.
MODELING OF BASIL ESSENTIAL OIL EXTRACTION WITH VARIABLE DIFFUSION COEFFICIENT

Essential oils are complex mixtures of volatile compounds found at low levels in aromatic plant specific parts. Soluble in organic solvents, these oils are characterized by their fragrance and antimicrobial activity, being widely used in industries. The mathematical modeling of essential oil extraction is a relevant step in the project of industrial plants because it is about achieving optimized operational conditions. A model is available in the literature describing the extraction process of basil essential oil, based on diffusion within the leaf. Parametric equations were tested for the variable diffusion coefficient with the concentration, resulting in a significant improvement in the description process, when compared to papers presented in the literature.