Miracle-dz/UniFAR-FTUs huggingface dataset:
Formation of Dataset for Fuzzy Quantitative Risk Assessment of LNG Bunkering SIMOPs

New international regulations aimed at decarbonizing maritime transportation are positively contributing to attention being paid to the use of liquefied natural gas (LNG) as a ship fuel. Scaling up LNG-fueled ships is highly dependent on safe bunkering operations, particularly during simultaneous operations (SIMOPs); therefore, performing a quantitative risk assessment (QRA) is either mandated or highly recommended, and a dynamic quantitative risk assessment (DQRA) has been developed to make up for the deficiencies of the traditional QRA. The QRA and DQRA are both data-driven processes, and so far, the data of occurrence rates (ORs) of basic events (BEs) in LNG bunkering SIMOPs are unavailable. To fill this gap, this study identified a total of 41 BEs and employed the online questionnaire method, the fuzzy set theory, and the Onisawa function to the investigation of the fuzzy ORs for the identified BEs. Purposive sampling was applied when selecting experts in the process of online data collection. The closed-ended structured questionnaire garnered responses from 137 experts from the industry and academia. The questionnaire, the raw data and obtained ORs, and the process of data analysis are presented in this data descriptor. The obtained data can be used directly in QRAs and DQRAs. This dataset is first of its kind and could be expanded further for research in the field of risk assessment of LNG bunkering.
Music Feature Extraction And Recommendation Using CNN Algorithm

In this age of technological advancements, it has become considerably easier for an individual to access a variety of music from a significant number of sources. Today, there are a multitude of songs of varying diversity available to users. Therefore, it becomes difficult for users to manually discover new music that may suit their liking. Thus arises the need for a system that will help the music streaming applications to recommend new music to their users that will befit their music taste, based on some predetermined criteria. With the ever-expanding user and song database, the system must also be dynamic and its recommendations must be up-to-date and accurate. Therefore, there is a strong demand for a well-qualified music recommendation system. The proposed system focuses of technical features of audio. The main purpose of this systems is to classify songs in different genre using Deep Learning Algorithm. There are two main approaches for implementing these system, viz, Feature Extraction and Content Based Filtering.
Relaxation oscillation model of hemodynamic parameters in the cerebral vessels

Simulation of a blood flow under normality as well as under pathology is extremely complex problem of great current interest both from the point of view of fundamental hydrodynamics, and for medical applications. This paper proposes a model of Van der Pol - Duffing nonlinear oscillator equation describing relaxation oscillations of a blood flow in the cerebral vessels. The model is based on the patient-specific clinical experimental data flow obtained during the neurosurgical operations in Meshalkin Novosibirsk Research Institute of Circulation Pathology. The stability of the model is demonstrated through the variations of initial data and coefficients. It is universal and describes pressure and velocity fluctuations in different cerebral vessels (arteries, veins, sinuses), as well as in a laboratory model of carotid bifurcation. Derived equation describes the rheology of the ”blood stream - elastic vessel wall gelatinous brain environment” composite system and represents the state equation of this complex environment.
Diagnosis of Mechanical Unbalance Fault in Permanent Magnet Synchronous Machine Drives

Abstract In recent years, motor current signature analysis has been used for fault diagnosis of permanent magnet synchronous machines. However, the fault feature is not obvious and is easily hidden in the main component, since the amplitudes of fault harmonic components are quiet small compared with the fundamental component. A new method to diagnose the mechanical unbalance fault effectively in permanent magnet synchronous machine drives is proposed in this article, where Park's vector is used to eliminate the fundamental component from the fast Fourier transform (FFT) results of motor current signature analysis; the fault feature is then analyzed by discrete wavelet transform. The effectiveness of the proposed method is validated by simulation and experimental results. It is shown that the proposed diagnosis method may work well under different control strategies.
Assessment of peak expiratory flow rate and other cardiometabolic parameters of meat roasters (Mai suya) in Kano Nigeria

Occupational exposure to wood smoke and oil fumes is an important cause of respiratory problems. Meat roasting exposes workers to hazard of wood smoke and oil fumes. The aim of this study was to assess peak expiratory flow rate (PEFR) and other cardiometabolic parameters of meat roasters (Mai suya) in Kano, Nigeria. A total of 105 participants consisting of 55 meat roasters and 50 controls were recruited. All participants were assessed for PEFR, pulse rate, oxygen saturation, blood pressure, weight, height, and body mass index (BMI) according to standard protocols. Data were analyzed using SPSS version 23.0 and p value ≤ 0.05 was considered statistically significant. Mean age of the meat roasters and controls was 30.64±10.28 and 23.68±3.15 years. Meat roasters had statistically significant lower PEFR (243±85.35 vs 377.40±64.93 mL/min; p = 0.01), elevated diastolic pressure (81.91±6.64 vs 78.36±4.59 mmHg; p = 0.01), mean arterial pressure (94.12±7.96 vs 90.75±4.88 mmHg; p = 0.01) and BMI (19.53±2.40 vs 18.49±2.08 kg/m2; p = 0.02) compared to the controls. Number of years of working as meat roaster was positively correlated with systolic pressure (r = 0.67, p = 0.01), diastolic pressure (r = 0.41, p = 0.01), mean arterial pressure (r = 0.60, p = 0.01), BMI (r = 0.37, p = 0.01), and pulse rate (r = 0.46, p = 0.01). Meat roasting is associated with impaired lung function and altered blood pressure. Routine assessment of lung function and use of safety equipment should be encouraged among meat roasters.
Hooked By Avatars? Literature Studies in Upper Secondary School—A Simulation Study

Several studies have shown that Swedish students’ reading comprehension and ability to understand fiction are decreasing year by year. Numerous alarming reports point to the unsustainable situation concerning young people’s reading engagement, but the ideas of how it can be remedied are few. This study aims to investigate and evaluate a didactic design that includes avatars as game elements in order to promote students’ reading of fiction. What opportunities and challenges might such a design present? In the study, an action research method and game theory were used, where teachers and researchers collaboratively explored and evaluated the outcome. The results showed that this design offered many opportunities and generated reading engagement. The students co-design their learning by creating an avatar and then entering the fictional world of a short story. Creating an avatar that interacts with the fictional text requires both participation, reading comprehension and meta analytic skills. However, the design also presented challenges, that some students did not link their avatars clearly to the text and instead did their own stories. The design could thus be further developed to provide more room for avatars to interact more with the chosen literary environment.
Future Wireless Communication Technology towards 6G IoT: An Application-Based Analysis of IoT in Real-Time Location Monitoring of Employees Inside Underground Mines by Using BLE

In recent years, the IoT has emerged as the most promising technology in the key evolution of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and many other areas of wireless communication. There is a massively growing number of static and mobile IoT devices with a diversified range of speed and bandwidth, along with a growing demand for high data rates, which makes the network denser and more complicated. In this context, the next-generation communication technology, i.e., sixth generation (6G), is trying to build up the base to meet the imperative need of future network deployment. This article adopts the vision for 6G IoT systems and proposes an IoT-based real-time location monitoring system using Bluetooth Low Energy (BLE) for underground communication applications. An application-based analysis of industrial positioning systems is also presented.
A 6.7μW CMOS Bioamplifier for Active Electrode with DC Rejection

Abstract—Since the fabrication of active electrodes has been reported and their beneficial effects scientifically confirmed, we present a CMOS bioelectric amplifier with DC rejection designed for active electrode in this paper. Analysis, design and post simulation results will be described in detail. The amplifier operating at ±0.9V supply voltage has a mid-band gain of 40dB with ±300mV dc offset rejection and has a power consumption of 6. 7μ W. The bandwidth extends from a low-frequency cutoff of 7.9mHz to a high-frequency cutoff of 2.1kHz which is suitable for ECG signals. This proposed amplifier has an input-referred noise of 5. 9μ Vrms. This amplifier is under fabrication in 0.18 μ m 1P6M CMOS Process.
A Novel Framework Based on the Stacking Ensemble Machine Learning (SEML) Method: Application in Wind Speed Modeling

Wind speed (WS) is an important factor in wind power generation. Because of this, drastic changes in the WS make it challenging to analyze accurately. Therefore, this study proposed a novel framework based on the stacking ensemble machine learning (SEML) method. The application of a novel framework for WS modeling was developed at sixteen stations in Iran. The SEML method consists of two levels. In particular, eleven machine learning (ML) algorithms in six categories neuron based (artificial neural network (ANN), general regression neural network (GRNN), and radial basis function neural network (RBFNN)), kernel based (least squares support vector machine-grid search (LSSVM-GS)), tree based (M5 model tree (M5), gradient boosted regression (GBR), and least squares boost (LSBoost)), curve based (multivariate adaptive regression splines (MARS)), regression based (multiple linear regression (MLR) and multiple nonlinear regression (MNLR)), and hybrid algorithm based (LSSVM-Harris hawks optimization (LSSVM-HHO)) were selected as the base algorithms in level 1 of the SEML method. In addition, LSBoost was used as a meta-algorithm in level 2 of the SEML method. For this purpose, the output of the base algorithms was used as the input for the LSBoost. A comparison of the results showed that using the SEML method in WS modeling greatly affected the performance of the base algorithms. The highest correlation coefficient (R) in the WS modeling at the sixteen stations using the SEML method was 0.89. The SEML method increased the WS modeling accuracy by >43%.
Anisodamine hydrobromide ameliorates cardiac damage after resuscitation

The microcirculation is correlated with the prognosis of patients with cardiac arrest and changes after resuscitation. In the present study, the effects of anisodamine hydrobromide (AH) on microcirculation was investigated and its potential mechanisms were explored. A total of 24 pigs were randomly grouped into three groups (n=8): Sham, Saline and AH group. After pigs were anesthetized, intubated and mechanically ventilated, ventricular fibrillation was induced by electrical stimulation. After 8 min, cardiopulmonary resuscitation was given to the restoration of spontaneous circulation (ROSC). Arteriovenous blood was collected at baseline and 0, 1, 2, 4 and 6 h after ROSC to measure blood gas and cytokines. Perfused vessel density (PVD) and microvascular flow index (MFI) were measured to reflect the microcirculation. Continuous cardiac output and global ejection fraction were measured to indicate hemodynamics. Compared with Sham group, PVD and MFI in the intestines and the sublingual regions decreased significantly after resuscitation. The microcirculation recovered faster in the AH group than the SA group. The decrease of intestinal microcirculatory blood flow was closely related to the decrease of sublingual microcirculatory blood flow. The cardiac function was impaired after resuscitation, and a decrease of IFN-γ as well as IL-2 and an increase of IL-4 as well as IL-10 suggested the immune imbalance. The microcirculation changes in sublingual regions were closely related to the changes in intestines. AH could improve the immune imbalance after resuscitation and was beneficial to the recovery of cardiac function.
Proposal of shoplifting prevention service using image analysis and ERP check

In this paper, we propose a software‐as‐a‐service application that prevents shoplifting using image analysis and enterprise resource planning (ERP). In Japan, the total damage due to shoplifting has reached ¥ 450 billion per year, and each year more than 1000 small book stores give up their business because of shoplifting damage. Based on the recent advancement in cloud technology and data analysis technology, we propose a shoplifting prevention service with the image analysis of security camera movie and ERP data check for small shops. We also confirm the precision ratio of security camera stream movie analysis using the online machine learning framework Jubatus. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
The More Enthusiastic, the Better? Unveiling a Negative Pathway From Entrepreneurs’ Displayed Enthusiasm to Funders’ Funding Intentions

Displaying enthusiasm (an emotional manifestation of passion) is a common practice for entrepreneurs to attract crowdfunding. However, we propose that funders may attribute an entrepreneur’s displayed enthusiasm to impression management motives, which can in turn reduce their funding intentions. Moreover, this negative pathway is more likely to occur when the entrepreneur is perceived to have lower domain expertise. We found consistent support for these hypotheses from a survey and an experiment. Our findings suggest that displaying enthusiasm may not always be effective for entrepreneurs because there are both positive and negative pathways underlying the influence of displayed enthusiasm on funders.
Characterization and In Vitro Cytotoxicity Safety Screening of Fractionated Organosolv Lignin on Diverse Primary Human Cell Types Commonly Used in Tissue Engineering

Simple Summary As global efforts to use eco-friendly and reusable materials increase, the use of lignin from waste biomass will continue to intensify. Lignin is an underutilized biowaste macromolecule that is gaining considerable interest in biomedical research. However, the source of lignin and the extraction process heavily influence its chemistry, which can influence a cell’s reaction to lignin. Organosolv lignin is extracted via an eco-friendly process from leftover waste material. Few studies have tested the biocompatibility of organosolv lignins with human cells. We extensively characterized fractionated organosolv lignin and performed in vitro cytotoxicity safety screening on diverse primary human cell types commonly used in tissue engineering. This is the first study to show that, at a balanced concentration, fractionated low MW beechwood-derived organosolv lignin is non-cytotoxic to highly relevant human cell types used in tissue engineering including human bone marrow-derived mesenchymal stromal cells (MSCs), chondrocytes, osteoblasts, periodontal ligament fibroblasts, gingival fibroblasts and keratinocytes. Additionally, we show that organosolv lignin can be used to fabricate cell scaffolds and that addition of lignin increased the stiffness and viscosity of the scaffolds as well as cell attachment. This suggests that organosolv lignin may be used in the generation of tissue-like biomaterial-based constructs for tissue repair. Abstract There is limited data assessing the cytotoxic effects of organosolv lignin with cells commonly used in tissue engineering. Structural and physico-chemical characterization of fractionated organosolv lignin showed that a decrease of the molecular weight (MW) is accompanied by a less branched conformation of the phenolic biopolymer (higher S/G ratio) and an increased number of aliphatic hydroxyl functionalities. Enabling stronger polymer−solvent interactions, as proven by the Hansen solubility parameter analysis, low MW organosolv lignin (2543 g/mol) is considered to be compatible with common biomaterials. Using low MW lignin, high cell viability (70–100%) was achieved after 2 h, 24 h and 7 days using the following lignin concentrations: MSCs and osteoblasts (0.02 mg/mL), gingival fibroblasts and keratinocytes (0.02 to 0.04 mg/mL), periodontal ligament fibroblasts and chondrocytes (0.02 to 0.08 mg/mL). Cell viability was reduced at higher concentrations, indicating that high concentrations are cytotoxic. Higher cell viability was attained using 30/70 (w/v) NaOH vs. 40/60 (w/v) EtOH as the initial lignin solvent. Hydrogels containing low MW lignin (0.02 to 0.3 mg/mL) in agarose dose-dependently increased chondrocyte attachment (cell viability 84–100%) and hydrogel viscosity and stiffness to 3–11 kPa, similar to the pericellular matrix of chondrocytes. This suggests that low MW organosolv lignin may be used in many tissue engineering fields.
Combined Longitudinal and Surface Acoustic Wave Analysis for Determining Small Filling Levels in Curved Steel Containers

Measurement of the small filling levels in closed steel container systems is still a challenge. Ultrasound, however, is a sensitive and non-invasive technique and is suitable for online monitoring. This study describes a new ultrasonic sensor system for sensing small filling levels using longitudinal and surface acoustic wave analysis. The sensor system consists of one transducer for the longitudinal wave analysis and two transducers for the longitudinal and surface acoustic wave analysis. All transducers were mounted to the outer wall of the steel container, ensuring non-invasiveness, and a filling level ranging from 0 to 5 cm was investigated. Combining both approaches, a consistent determination of small filling levels was achieved for the entire measuring range (R2 = 0.99).
Improvements in learning to control perched landings

Abstract Reinforcement learning has previously been applied to the problem of controlling a perched landing manoeuvre for a custom sweep-wing aircraft. Previous work showed that the use of domain randomisation to train with atmospheric disturbances improved the real-world performance of the controllers, leading to increased reward. This paper builds on the previous project, investigating enhancements and modifications to the learning process to further improve performance, and reduce final state error. These changes include modifying the observation by adding information about the airspeed to the standard aircraft state vector, employing further domain randomisation of the simulator, optimising the underlying RL algorithm and network structure, and changing to a continuous action space. Simulated investigations identified hyperparameter optimisation as achieving the most significant increase in reward performance. Several test cases were explored to identify the best combination of enhancements. Flight testing was performed, comparing a baseline model against some of the best performing test cases from simulation. Generally, test cases that performed better than the baseline in simulation also performed better in the real world. However, flight tests also identified limitations with the current numerical model. For some models, the chosen policy performs well in simulation yet stalls prematurely in reality, a problem known as the reality gap.
Vectorized computing for edge-avoiding wavelet

The discrete wavelet transform (DWT) is an essential tool for image and signal processing. The edge-avoiding wavelet (EAW) is an extension for DWT to have edge-preserving property. EAW constructs a basis based on the edge content of input images; thus, the wavelet contains nonlinear filtering. DWT is computationally efficient processing in the scale-space analysis; however, EAW has a complex loop structure. Therefore, parallel computing for EAW is not an easy task. In this paper, we vectorize EAW computing by using single instruction, multiple data (SIMD) parallelization. Especially, the lifting-based wavelet allows the in-place operation, i.e., the source and destination array for DWT can be shared, and the in-place operation improves cache efficiency. However, the EAW prevents the operation in the update processing. Moreover, data interleaving for wavelet computing is the bottleneck for SIMD computing. Therefore, we show the suitable data structure for effective SIMD vectorization for EAW. Experimental results show that our effective implementation accelerates EAW. For the WCDF method, we accelerate more than two times faster, and for the WRB method, we accelerate about three times faster than the simple implementation.
Evaluation and Characterization of Stabilized Drug, Formulated as Oro Dispersible Tablet Using Advanced Method

In a challenge to prepare a stable Oro-dispersible tablet (ODT) of Desloratadine, using dry resin was incorporated into a fast-disintegrating matrix to prepare an optimized ODT that achieved the desired criteria of stabilization and patient acceptance. In this study, the critical process parameters (CPPs) and critical material attributes (CMAs) were determined via risk assessment methods within the framework of Quality by Design (QbD). The results showed that resin (Amberlite IRP64®) can be used as a dry stabilizer and the selected variables in the optimization phase have a strong influence on the blend flowability, disintegration time, and wetting time of the ODTs. Furthermore, by comparing the optimized formula with the marketed one, the optimized formula showed a significantly lower disintegration, lower wetting time, and an almost similar dissolution profile.
Convergence and Stability Analysis of a New Four-Step Fixed-Point Algorithm

The concept of stability is studied on many different types of mathematical structures. This concept can be thought of as the small changes that will be applied in the structure studied should not disrupt the functioning of this structure. In this context, we performed the convergence and stability analysis of the new four-step iteration algorithm that we defined in this study, under appropriate conditions. In addition, we execute a speed comparison with existing algorithms to prove that the new algorithm is effective and useful, and we gave a numerical example to support our result