Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Stacked Long Short-Term Memory Approach of Deep Learning for Streamflow Simulation

Rainfall-Runoff simulation is the backbone of all hydrological and climate change studies. This study proposes a novel stochastic model for daily rainfall-runoff simulation called Stacked Long Short-Term Memory (SLSTM) relying on machine learning technology. The SLSTM model utilizes only the rainfall-runoff data in its modelling approach and the hydrology system is deemed a blackbox. Conversely, the distributed and physically-based hydrological models, e.g., SWAT (Soil and Water Assessment Tool) preserve the physical aspect of hydrological variables and their inter-relations while taking a wide range of data. The two model types provide specific applications that interest modelers, who can apply them according to their project specification and objectives. However, sparse distribution of point-data may hinder physical models’ performance, which may not be the case in data-driven models. This study proposes a specific SLSTM model and investigates the SLSTM and SWAT models’ data dependency in terms of their spatial distribution. The study was conducted in the two distinct river basins of Samarahan and Trusan, Malaysia, with over 20 years of hydro-climate data. The Trusan basin’s rain gauges are scattered downstream of the basin outlet and Samarahan’s are located around the basin, with one station within each basin’s limits. The SWAT was developed and calibrated following its general modelling approach, however, the SLSTM performance was also tested using data preprocessing with principal component analysis (PCA). Results showed that the SWAT performance for daily streamflow simulation at Samarahan has been superior to that of Trusan. Both the SLSTM and PCA-SLSTM models, however, showed better performance at Trusan with PCA-SLSTM outperforming the SLSTM. This demonstrates that the SWAT model is greatly affected by the spatial distribution of its input data, while data-driven models, irrespective of the spatial distribution of their entry data, can perform well if the data adequacy condition is met. However, considering the structural difference between the two models, each has its specific application in a water resources context. The study of catchments’ response to changes in the hydrology cycle requires a physically-based model like SWAT with proper spatial and temporal distribution of its entry data. However, the study of a specific phenomenon without considering the underlying processes can be done using data-driven models like SLSTM, where improper spatial distribution of data cannot be a restricting factor.
Evaluating essential features of proppant transport at engineering scales combining field measurements with machine learning algorithms

The characterization of the proppant transport at a field-engineering scale is still challenging due to the lack of direct subsurface measurements. Features that control the proppant transport may link the experimental and numerical observations to the practical operations at a field scale. To improve the numerical and laboratory simulations, we propose a machine-learning-based workflow to evaluate the essential features of proppant transport and their corresponding calculations. The proppant flow in fractures is estimated by applying the Gated recurrent unit (GRU) and Support-vector machine (SVM) algorithms to the measurements obtained from shale gas fracturing operations. Over 430,000 groups of fracturing data are collected and pre-processed by the proppant transport models to calculate key features, including settlement, stratified flow and inception of settled particles. The features are then fed into machine learning algorithms for pressure prediction. The root mean squared error (RMSE) is used as the criterion for ranking selected features via the control variate method. Our result shows that the stratified-flow feature (fracture-level) possesses better interpretations for the proppant transport, in which the Bi-power model helps to produce the best predictions. The settlement and inception features (particle-level) perform better in cases that the pressure fluctuates significantly, indicating that more complex fractures may have been generated. Moreover, our analyses on the remaining errors in the pressure-ascending cases suggest that (1) an introduction of the alternate-injection process, and (2) the improved calculation of proppant transport in complex fracture networks and highly-filled fractures will be beneficial to both experimental observations and field applications.
DESIGN AND OPTIMIZATION OF ELECTROSTATIC PRECIPITATOR USING FINITE ELEMENT ANALYSIS TOOL

An electrostatic precipitator is designed to trap and remove dust particles from the exhaust gas. The computer aided design and finite element analysis of electrostatic precipitator cone structure has been carried out. For static structure analysis two models (Model A and Model B) is being considered having horizontal and vertical stiffener arrangement. As per ISO (IS 808: 1989, Edition 4.1 ) standard for stiffeners, the various sizes of stiffeners are analyzed for electrostatic precipitator cone structure. The deformation of Model A cone structure and Model B cone structure is analyzed with various stiffener arrangements with allowable deformation 39mm. From analysis it is observed that deformation goes on decrease as weight of electrostatic precipitator cone structure increase. Also it is interestingly noted that maximum deflection region in each case of model is at centre of face having maximum surface area.
Resilient Trajectory Propagation in Multirobot Networks

This article presents a novel method for a class of multirobot networks to resiliently propagate vector messages from a set of leaders to all followers within the network in the presence of faulty or adversarially behaving robots. It is shown that the proposed method can operate under heterogeneous communication rates between robots and perturbations of the leaders’ propagated information. As a case study, the proposed method is applied to the problem of time-varying trajectory tracking; more specifically, time-varying reference trajectories in the form of Bezier curves are encoded into vectors of static parameters, which, in turn, are resiliently propagated from the leaders to the followers.
Public Education Funding and Economic Growth IN Nigeria; ARDL-VECM and Causal Inference Approach

Considering the enormous impact of poor standard of educational system in Nigeria over the years, the study investigated the effects of public education funding on economic growth in Nigeria from 1985 to 2019. The paper used secondary data sourced from both Central Bank of Nigeria Statistical Bulletin and World Bank’s Development Indicators 2019. The paper employed Auto-Regressive Distributed Lag co-integration, Error correction mechanism and granger-causality tests as technique for data analysis. The ARDL bound test co-integration results revealed that RRETE, RCETE and Inflation have positive relationship with Economic growth. However, RETE, SEDU and PRI have indirect influence on Economic growth in Nigeria. Statistically, only RRETE has a long run causal effect on economic growth. ARDL Error Correction Regression output showed that RETE and RCETE are significant at 10% level while PRI is significant at 5% level this indicates the existence of short run causal relationship with the establishment of ECM long run equilibrium adjustment speed. The causal results revealed unidirectional inference between SEDU and RETE, PRI and RETE, PRI and RRETE with no feedback effect. Therefore, the study recommended educational funding targeted at secondary and primary education system in order to acquire productive skills and knowledge to stimulate economic growth and development in Nigeria. There is need to meet the UNESCO funding ratio for both recurrent and capital expenditure on education sector.
Magnetic Cleaning Device for Lunar Dust Adhering to Spacesuits

The removal of lunar dust adhering to spacesuits is essential for the long-term exploration of the Moon. Because lunar dust is magnetic, a convenient cleaning device that utilizes magnetic force has been developed. The device can capture and separate lunar dust continuously with a multipole magnetic roller. The observed separation rate was 90%, but the capture rate was low, resulting in an overall cleaning rate of 40%. The rate increased when large amounts of dust adhered to the fabric. Although it was difficult to capture small particles trapped between fabric fibers, this device will be able to preliminarily clean spacesuits and save the precious activity time of astronauts on the Moon.
Improving Power-Conversion Efficiency via a Hybrid MPPT Approach for Photovoltaic Systems

This paper presents a hybrid Maximum Power Point Tracking (MPPT) method for improving the power -conversion efficiency of Photovoltaic (PV) generators. By detecting the output power changes caused by environmental reasons, the proposed method performs variable-step online search process with an accurate estimation of the Maximum Power Point (MPP) locus. A PV generator with a Single Ended Primary Inductance Converter (SEPIC) is developed in PSIM to verify the feasibility and suitability of the proposed method. Simulation results show that it can not only deliver a stable reference operating voltage for MPPs at steady state, but also can speed up the searching process under rapidly changing environment conditions.
Verification of Collision Avoidance for CommonRoad Traffic Scenarios

We propose a benchmark for the verification of autonomous vehicles. By considering different traffic scenarios from the CommonRoad database, we obtain several thousands of different verification tasks, where the verification problem is to prove that the con- sidered tracking controller safely follows a given reference trajectory despite disturbances and measurement errors. The dynamic of the car is described by a nonlinear kinematic single-track model. Since the feedback matrix for the tracking controller is time-varying, the dynamic of the controlled system changes constantly. Because of this, the proposed benchmark is well-suited to evaluate how robustly reachability tools can handle changing system dynamics.
Culturally Adapted Psychoeducation among Family Caregivers of Schizophrenic Clients: A Scoping Review

Background: As psychoeducation was originally developed from Western, this intervention should be integrated with a culture to obtain effective outcomes. However, how culturally adapted psychoeducation on family caregivers of schizophrenic client developed in previous studies has not been systematically documented. The purpose of this review was to map culturally adapted psychoeducation in previous studies. Methods: This scoping review followed Arksey & O'Malley approach. Inclusion criteria including family caregiver, culture, psychoeducation, schizophrenia. Non-primary and non-experiment studies, non-English language and non-free articles were excluded. Advanced search technique used keywords family caregiver, culture, psychoeducation, schizophrenia on CINAHL, PubMed, and PsycInfo databases. Screening was done by checking duplication, title, and abstract. Full text of relevant articles was read in detail to select eligible articles. Selection results were described in the PRISMA flow chart. Data were analyzed after these were extracted and resumed on the table. Result: A total of 8 studies were included in this review. More than half of articles used randomized control trial (RCT) but these studies did not conduct follow up. Most of studies were in Asia (6) and it conducted in the outpatient department (6). Almost all studies modified multifamily group psychoeducation with culture theories. The longest duration of intervention was 12 months. Multidiscipline health professional delivered the intervention and most of the were psychiatrist. Coping was the most family caregiver outcomes in reviewed studies. Conclusion: In conclusion, limited studies were obtained in various ethnics and ways. Further studies need to measure effectiveness of the intervention in long term effect.
A dual-stage control algorithm for magnetic disk drives based on coarse motion prediction

A control algorithm is presented for both reliable and efficient realization of hard disk drives with a dual-stage actuator. It enables the full capability of the dual-stage actuator, while preserving the well-established structure of conventional single-arm actuator control algorithms. Basically, the present methodology is a combination of the existing single-arm servo design and an add-on tracking controller design for the microactuator subsystem, with the desired trajectory being the residual position error due to the coarse actuator. A key feature of the tracking controller is that it utilizes the preview information of its desired trajectory, which can be predicted fairly accurately based on the relatively slow coarse actuator dynamics. The best practical advantage is that the present method can achieve not only the high-performance track-following but also the overshoot-free track-seeking without significantly altering the existing single-arm servo system. The performance of the proposed method is demonstrated through some simulation and experiment.
Statistical optimisation of esterase from Salinicoccus roseus strain RF1H and its potential application in synthetic dye decolorisation

Abstract Halophilic bacteria isolated from Indian Sundarban Wetland, identified as Salinicoccus roseus strain RF1H, were screened for extracellular esterase production. Media components for esterase production under submerged fermentation were optimised using Plackett–Burman Design followed by Box-Behnken Design of Response Surface Methodology (RSM) at pH 4.0, 3.5 g/L of MgSO4, and tributyrin concentration of 1(%v/v). The regression model was significant with a determination coefficient (R 2) value of 0.826. Using RSM, the experimental value of maximum enzyme activity (2.442 UmL−1) was 1.35 fold increased. The kinetic parameters K m and V max for hydrolysis of p-nitrophenyl acetate were 9.98 mM and 2.26 µmol/min/mg respectively, establishing a high affinity for the substrate. Further, the enzyme conferred promising results in decolorisation of synthetic dyes -Malachite Green, Congo Red, Brilliant Yellow, and Orange G. Molecular docking was used to investigate the binding pockets of the esterase, enzyme-ligand interactions, and amino acids which played a key role in dye decolorisation. Docking score results and decolorisation percentage were found in good agreement. This is the first report on the biotransformation of synthetic dyes to non-toxic products using esterase from Salinicoccus roseus. Graphical Abstract
Exploring Providers’ Perception Towards Provision of Sexual and Reproductive Health Services for Unmarried Adolescents in Gamo Zone, Southern Ethiopia: A Phenomenological Study

Background Healthcare providers play a critical role in the provision of sexual and reproductive health services for adolescents. In Ethiopia, due to different reasons, including healthcare providers associated reasons, most unmarried adolescents are not accessing the services. However, little is known about healthcare providers’ perception towards the provision of SRH services for unmarried adolescents. This study aimed to explore healthcare provider perception towards the provision of SRH services to unmarried adolescents in Gamo zone, Southern Ethiopia. Methods A qualitative phenomenological research design was used in May 2021. Fifteen healthcare providers (HCPs) working in adolescent and youth sexual and reproductive health centers were involved in this study. A purposive sampling technique was used to select healthcare providers assuming they are “information-rich” regarding the phenomenon of interest. Inclusion of the study participants was continued until data saturation is reached. To analyze the data, we used inductive thematic analysis, method, and main themes, which captured the diverse views and feelings of the participants. To maintain the trustworthiness of the data, we used dependability, transferability, conformability, and credibility. Results In this study, individual-level attributes such as healthcare provider’s personal belief, attitude, and motivation; community-level influences like socio-cultural norms, religious reasons, and lack of parental support; and health system setbacks like shortage of essential medical supplies and lack of training are identified as major obstacles in the provision of sexual and reproductive health services for unmarried adolescents. Conclusion Provision of sexual and reproductive health services for unmarried adolescents is constrained by the interplay of factors acting at an individual level, community level, and health system level. The Ministry of Health (MOH), program planners and policymakers are recommended to give due attention to fulfill the necessary inputs, improving healthcare provider’s attitude and skill and engagement of religious and community leaders to create a safe and supportive environment for providing sexual and reproductive health services to unmarried adolescents.
The Marple Project: A tool for Design Patterns Detection and Software Architecture Reconstructiion

It is well known that software maintenance and evolution are expensive activities, both in terms of invested time and money. Reverse engineering activities support the obtainment of abstractions and views from a target system that should help the engineers to maintain, evolve and eventually re-engineer it. Two important tasks pursued by reverse engineering are design pattern detection and software architecture reconstruction, whose main objectives are the identication of the design patterns that have been used in the implementation of a system as well as the generation of views placed at dierent levels of abstractions, that let the practitioners focus on the overall architecture of the system without minding at the programming details it has been implemented with. In this context we propose an Eclipse plug-in called MARPLE (Metrics and Architecture Reconstruction Plug-in for Eclipse), which supports both the detection of design patterns and software architecture reconstruction activities through the use of basic elements and metrics that are mechanically extracted from source code. The development of this platform is mainly based on the exploitation of the Eclipse framework and plug-ins as well as of dierent Java
Design and Performance Simulation of Computer Control System for Automatic Monitoring of Upper Computer Communication Operation State

The upper computer communication operation state automatic monitoring system is mainly used to remotely monitor the equipment, obtain various parameter indexes in the operation process of remote equipment, realize remote monitoring and fault diagnosis, and improve the management efficiency of decentralized equipment. This paper completes the design of communication, data storage, query, and other subsystems of upper and lower computers. The lower computer establishes a data channel with the OPC server through the MPI protocol and uploads the collected data to the OPC server in real time. The upper computer reads the data through the OPC server and displays the changes of monitored parameters in real time through the monitoring interface, so as to give an alarm under abnormal conditions. In addition, since the default database of Kingview is access, considering that the Microsoft Access database can store up to 2G of content, in order to upgrade and expand the subsequent system, SQL Server database is selected for data query, backup, and saving. The parameter setting method of communication control system is analyzed, the simulation model of industrial boiler control system is established by using Matlab/Simulink, and the interface between host computer software (IBCCS-e) and the model is provided. This paper analyzes the results of communication parameter adjustment. The simulation results show that the industrial boiler computer control system (IBCCS) has stable performance, low cost, convenient operation, and good maintainability. After further improvement, it has certain application value in the operation transformation of new small- and medium-sized boilers and original boilers.
‘SRS’ R Package and ‘q2-srs’ QIIME 2 Plugin: Normalization of Microbiome Data Using Scaling with Ranked Subsampling (SRS)

Several ecological data types, especially microbiome count data, are commonly sample-wise normalized before analysis to correct for sampling bias and other technical artifacts. Recently, we developed an algorithm for the normalization of ecological count data called ‘scaling with ranked subsampling (SRS)’, which surpasses the widely adopted ‘rarefying’ (random subsampling without replacement) in reproducibility and in safeguarding the original community structure. Here, we describe an implementation of the SRS algorithm in the ‘SRS’ R package and the ‘q2-srs’ QIIME 2 plugin. We also provide accessory functions for dataset exploration to guide the choice of parameters for SRS.
Research Study of Energy Harvesting in Wireless Sensor Networks

A wireless sensor network (WSNs) exploits the sustainability technological requirement and research solution to alternate energy source of power. To power WSNs is by harvesting ambient energy from the environment is a promising challenge as there is no such efficient protocol that can continuously support the requirements. We provide a survey study of applying WSN to real application of habitat monitoring. A system architecture design of sensor nodes to address the requirement of habitat monitoring is analyzed. Consequently, substantial research efforts have been carried in designing sensor nodes that exploit sporadic energy needs to transmit data to maximize the lifetime of WSNs. This paper surveys related recent research development and challenges in protocol design in the harvesting energy in WSN architecture and provide scope for open research issues.
A parallel implementation of 3-D CT image reconstruction on hypercube multiprocessor

A parallel is given of how image reconstruction in computerized tomography (CT) can be parallelized on a message-passing multiprocessor. In particular, the results obtained from parallel implementation of 3-D CT image reconstruction for parallel beam geometries on the Intel hypercube, iPSC/2, are presented. A two-stage pipelining approach is used for filtering (convolution) and backprojection. The conventional sequential convolution algorithm is modified such that the symmetry of the filter kernel is fully utilized for parallelization. In the backprojection stage, the 3-D incremental algorithm, a recently developed backprojection scheme which is shown to be faster than the conventional algorithm, is parallelized. The speed-up, defined as sequential processing time/parallel processing time, ranging from 5 to 27, and the efficiency, defined as speed-up/the number of processing elements, ranging from 60% to 92%, have been achieved, depending on the size of the image and the number of processing elements used. >