Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis Of Public Sentiment of Covid-19 Pandemic, Vaccines, And Lockdowns

CoV-2 pandemic prompted lockdown measures to be implemented worldwide; these directives were implemented nationwide to stunt the spread of the infection. Throughout the lockdowns, millions of individuals resorted to social media for entertainment, communicate with friends and family, and express their opinions about the pandemic. Simultaneously, social media aided in the dissemination of misinformation, which has proven to be a threat to global health. Sentiment analysis, a technique used to analyze textual data, can be used to gain an overview of public opinion behind CoV-2 from Twitter and TikTok. The primary focus of the project is to build a deep learning classifier to analyze user sentiment on TikTok. Several deep learning models were developed, including Convolutional Neural Networks (CNN), Long-Short Term Memory (LSTM), Attention Mechanism, and Bidirectional Encoder Representations from Transformer (BERT). CNN excels at local feature extraction, whereas LSTM can store sequential data without loss of information. BERT can overcome the issue of ambiguous sentences and phrases; specifically, it can differentiate between homonyms. Models were trained on Sentiment140, a Twitter dataset. Once these models were trained, the models with the best performance were then used to classify sentiment of the TikTok users from Mar 2020 to August 2021. Proposed models can be used by both government institutions and businesses to understand concerns surrounding the pandemic.
Modification of PVDF membrane for harvesting of Nannochloropsis sp. and its cleaning results

One of the biggest challenges in implementing microalgae-based biofuels is the effective harvesting process. Filtration membrane has become one of the flexible methods in microalgae harvesting. This study investigated the harvesting of Nannochloropsis sp. using a modified PVDF membrane at various LiCl as an additive with N-methyl-2-pyrrolidone (NMP) solvent. Harvesting of Nannochloropsis sp. with PVDF membrane has never been reported before. The addition of LiCl can improve the performance of PVDF membrane due to LiCl has a great affinity for water, resulted in inducing the formation of the pore structure of membrane. The optimum membrane composition was determined at various LiCl additive from 1% to 3% (w/w). The hydrophilicity of the membrane increased as indicated by the increasing of water permeance, which were 516, 546, 660, and 614 l m−2h−1 bar−1 for neat PVDF, PVDF/LiCl-1, PVDF/LiCl-2, and PVDF/LiCl-3 membrane, respectively. PVDF/LiCl-2 membrane showed the highest water permeance and the highest total average permeance (150 l m−2h−1 bar−1) with 100% rejection of Nannochloropsis sp. harvesting. The membranes was cleaned using sodium hypochlorite, citric acid, and nitric acid. The SEM results showed that the membrane after cleaning appears the algae particles in the membrane pore. Furthermore, algae particles were almost not visible on cleaned membrane. The FTIR results showed an absorption at 3401 cm−1, which was a characteristic of the hydrogen N–H bond, also including a typical amide uptake (C=O) at 1648 cm−1 indicating protein appearance. Moreover, the cleaned membrane did not appear any absorption that indicates the foulant.
An integrated approach of TOPSIS and response surface methodology for optimising the micro WEDM parameters

The recent trend in miniaturisation of sensors has given micro wire electrical discharge machining (μ-WEDM) a significant amount of research attention. The underlying challenge in the selection of optimal machining parameter combination to achieve the desired surface finish, kerf width and metal removal rate has urged the disclosure of an integrated method of technique for order of preference by similarity to ideal solution (TOPSIS)-based response surface methodology (TOP-RSM). A L16 orthogonal array was used to design the experiments and multi response optimisation was performed by using the TOP-RSM approach. A confirmation test was conducted to ensure the validity of proposed approach. The response surfaces were also studied to understand the effects of individual parameters on the quality characteristics.
Asymptotic properties of the estimators of the semi-parametric spatial regression model

ABSTRACT Spatial data and non parametric methods arise frequently in studies of different areas and it is a common practice to analyze such data with semi-parametric spatial autoregressive (SPSAR) models. We propose the estimations of SPSAR models based on maximum likelihood estimation (MLE) and kernel estimation. The estimation of spatial regression coefficient ρ was done by optimizing the concentrated log-likelihood function with respect to ρ. Furthermore, under appropriate conditions, we derive the limiting distributions of our estimators for both the parametric and non parametric components in the model.
Conceptual Understanding of Newton’s Laws of Motion as a Phenomenological Experience

This paper examined the students’ phenomenological experiences in their conceptual understanding Newton’s laws of motion. The participants in this research were 3 physics college students in a Teacher Education Institution in Iloilo City, Philippines. The data in this research were gathered through individual semi-structured interview to each of the participants. The explicitation of the data through phenomenological analysis (Hycner, 1999). The study revealed that the phenomenological experiences of students in his/her teacher in understanding Newton’s laws of motion were teacher demonstration, reviewing the previous topic, giving questions, giving situations to analyze, getting volunteers for the activities, application of topic to our daily life situation, using analogies to motivate the students, familiarize the basic concepts about Newton’s laws of motion, relate the equations from other situations. The researchers further found that the phenomenological experiences of students help build their conceptual understanding about Newton’s laws of motion by seeing it to understand, give and take knowledge, teaching styles, and students participation. Results also showed that teachers’ teaching style also determines how the students will respond, at times receptive, sometimes withdrawn. The pedagogy of the teacher also affects the students understanding and these are the reasons of students: intimidating teacher, open mindedness, eagerness and interest in teaching, and use of words. Moreover, it was pointed out that students also play an important role in the teaching-learning process. The students should not lie only to the teachers but they should do research or read books in the library. Furthermore, students gave some suggestions to refine the teaching-learning process and these are using visual aids, models or representations, and teaching styles should coincide with the students multiple intelligences to achieve understanding. Finally, the teachers; skill in employing interesting, challenging and relevant teaching methodologies which motivate the students to actively participate and manage their own learning serves as the best guarantee of beneficial and respectful classroom control and making the teaching-learning process fruitful. Both enjoy a winning situation, the students gaining knowledge and useful information on one hand and the teachers feeling satisfied and rewarded in seeing them learn.
Fatal Complications of Extensive Drug-Resistant Typhoid Fever: A Case Report

Typhoid fever is a systemic illness that often presents with fever, abdominal pain, and diarrhea. There are multiple complications associated with typhoid fever which includes intestinal perforation, gastrointestinal hemorrhage, hepatitis, and anemia. In recent years, a new extensively drug resistant (XDR) strain of Salmonella typhi (S. typhi) emerged, associated with higher incidence of complications, responding to azithromycin and carbapenems only. In this article, we report a case of a 28-year-old Pakistani male who initially presented with fever and bloody diarrhea, complicated by massive lower gastrointestinal bleed, leading to his mortality. This case, being the first reported case in Bahrain, illustrates the importance of considering hepatic manifestations and lower gastrointestinal bleeding as fatal complications of typhoid fever, especially in the setting of recent travel to Southeast Asia.
CHALLENGES OF SSF PROCESS FOR PEA AND WHEAT BRAN VALORIZATION USING TRICHODERMA SPP. FOR BIOCONTROL AGENT PRODUCTION

Fungal strain Trichoderma spp. is a known bio control agent (BCA), which are difficult to obtain using more prevalent industrial-scale biofermentation methods such as submerged fermentation (SmF) However, difficult up-scalable solid-state fermentation (SSF) are appropriate for such BCA production. An automated semi-rotating drum bioreactor was developed and built to explore SSF scale-up using pea and wheat bran as substrates to valorise food-industry by-products into viable BCA ‘s. Estimation of biomass using CO2/O2 analysis in exhaust gasses revealed that mix of pea and wheat bran can produce a viable BCA ‘s using gentle mixing technique with possibilities of industrial scale-up
Facilitative Leadership in Controlling Pollution and Damage to The Citarum Watershed as well as improving The Community Economy in Karawang, Indonesia

A Watershed (DAS) functions as a storage facility for rain collection and drainage, which often lead to the formation of rivers (Efendi, 2014). Furthermore, it is a unified landscape providing people with physical products and services. In Karawang, the pollution and damage to the Citarum watershed are found to harm the community and endanger the sustainability of the marine ecosystem, as observed to be one of the dirtiest rivers in the world. In this condition, leadership plays an important role in implementing collaboration, because of its central duty in the implementation, development, facilitation, and assessment of ground rules, trust, dialogue, and mutual benefits. According to Ansell & Gash (2007), a comprehensive collaborative leadership need to perform the following, (1) broadly and actively promote participation, (2) ensure broad influence and control, and (3) facilitate group or actor productivity. Therefore, this study aims to evaluate the role of facilitative leadership in controlling pollution within Karawang, Indonesia. It also aims to assess the damage to the Citarum watershed and to improve the economy of this district A qualitative approach was used to understand, explore, and explain facilitative leadership, to control pollution and damage to the Citarum river. In this condition, primary data was directly obtained from the main source, namely the parties or the study object, through observation and interviews. The secondary data was also obtained from the second sources as complements, including related literature books, newspapers, papers, and official documents. The results showed that government needs to be a facilitative leader in controlling pollution and damage to the Citarum watershed, due to being one of the conditions in resolving the cases of environmental pollution.
Lusternik-Schnirelmann theory for fixed points of maps

We use the ideas of Lusternik-Schnirelmann theory to describe the set of fixed points of certain homotopy equivalences of a general space. In fact, we extend Lusternik-Schnirelmann theory to pairs $(\varphi, f)$, where $\varphi$ is a homotopy equivalence of a topological space $X$ and where $f \colon X \rightarrow \mathbb R$ is a continuous function satisfying $f(\varphi(x)) < f(x)$ unless $\varphi (x) = x$; in addition, the pair $(\varphi, f)$ is supposed to satisfy a discrete analogue of the Palais-Smale condition. In order to estimate the number of fixed points of $\varphi$ in a subset of $X$, we consider different relative categories. Moreover, the theory is carried out in an equivariant setting.
Cyclical parthenogenesis algorithm for layout optimization of truss structures with frequency constraints

ABSTRACT Structural optimization with frequency constraints is seen as a challenging problem because it is associated with highly nonlinear, discontinuous and non-convex search spaces consisting of several local optima. Therefore, competent optimization algorithms are essential for addressing these problems. In this article, a newly developed metaheuristic method called the cyclical parthenogenesis algorithm (CPA) is used for layout optimization of truss structures subjected to frequency constraints. CPA is a nature-inspired, population-based metaheuristic algorithm, which imitates the reproductive and social behaviour of some animal species such as aphids, which alternate between sexual and asexual reproduction. The efficiency of the CPA is validated using four numerical examples.
Propagation and Interaction of Electrostatic and Electromagnetic Waves in Two Stream Free Electron Laser in the Presence of Self-Fields

A relativistic theory for twostream free electron laser (FEL) with a onedimensional helical wiggler and ion-channel guiding in the presence of self-fields are presented. A dispersion relation (DR) which includes coupling between the electromagnetic and the electrostatic waves is derived from a fluid model, with all of the relativistic terms related to the transverse wiggler motion. This DR is solved numerically to study many unstable couplings among all possible modes. Numerical calculations are made to illustrate the effects of the self-fields on the unstable couplings. It is shown that the self-fields can produce large effects on the growth rate of the couplings.
Bootstrapping the Seasonal Means and the Overall Mean in Rainfall Time Series

Several bootstrap methods have been studied nowadays for estimating the parameters in periodic data and it is important to consider the periodicity present in choosing the right bootstrap method. In this study we conducted a comparison of the performance of several block bootstrap methods designed for dependent data in the case of a real data time series with periodic structure such as the rainfall time series that is a time series with meteorological data collected monthly in a region in Albania. R programming language is used to perform the bootstrap and to obtain the results. We proposed a block bootstrap procedure in the case of estimating the seasonal means and the overall mean in the time series studied and based on the results obtained we notice a good performance of our proposed bootstrap procedure compared with other procedures considered. Received: 12 January 2023 / Accepted: 16 March 2023 / Published: 20 March 2023
The Change of Global Temperature Affected by Global Economy

Global warming is the most serious environmental problem due to rising temperatures. Previous studies showed CO2 is the primary greenhouse gas. CO2 emission is caused by the burning of fossil fuels. Humans pursue industrial growth at the expense of releasing CO2 into the atmosphere. Economic development is represented by Gross Domestic Product (GDP). The growth of CO2 emission increases more and more and does not reach the peak. The global temperature is facing a 2˚C crisis. The global emissions and global economy have a strong indication of relative sensitivity. We found out that countries with higher GDP emit more CO2. Individuals who have higher GDP per capita emit more CO2 to the atmosphere. GDP has a positive correlation with global temperature. Climate change is one of the biggest inequalities around the world. Richer countries caused more damage to global warming, but poor countries suffer more from global warming’s damage. GDP per capita has a positive correlation with temperature and CO2 emissions. The development of a country has a trend of increasing CO2 emissions at an early stage and decreasing CO2 emissions at a later stage. Total GDP although cannot positively correlated to CO2 emissions, but multicollinearity tests proved the two variables are related.
High precision timing using self-timed circuits

Constraining the events that demarcate periods on a VLSI chip to precise instances of time is the task undertaken in this thesis. High speed sampling and clock distribution are two example applications. Foundational to my approach is the use of self-timed data control circuits. Specially designed self-timed control circuits deliver high frequency timing signals with precise phase relationships. The frequency and the phase relationships are controlled by varying the number of self-timed control stages and the number of tokens they control. The self-timed control circuits are constructed with simple digital logic gates. The digital logic gates respond to a range of analog values with a continuum of precise and controlled delays. The control circuits implement their functionality efficiently. This allows the gates to drive long wires and distribute the timing signals over a large area. Also gate delays are short and few, allowing for high frequencies. The self-timed control circuits implement the functionality of a FIFO that is then closed into a ring. Timing tokens ripple through the rings. The FIFO stages use digital handshaking protocols to pass the timing tokens between the stages. The FIFO control stage detects the phase between the handshake signals on its inputs and produces a signal that is sent back to the producers with a delay that is a function of the phase relationship of the input signals. The methods described are not bound to the same process and systematic skew limitations of existing methods. For a certain power budget, timing signals are generated and distributed with significantly less power with the approaches to be presented than with conventional methods.
Illumination normalisation using convolutional neural network with application to face recognition

A novel illumination normalisation (IN) method using a convolutional neural network (CNN) is proposed. The proposed network is composed of the local pattern extraction (LPE) and illumination elimination (IE) layers. The LPE layers model the relationships between the pixels in each local region in order to handle various types of local shadow and shading in the face image. Based on the commonly used assumption about the illumination field, the IE layers generate illumination-insensitive ratio images by calculating the ratio between the output pairs produced from the LPE layers. The final feature map obtained by combining the ratio images can possess an improved discriminative ability for face recognition (FR). For training the proposed network, the results produced by the Weber fraction-based IN methods as ground truths are utilised. The experimental results demonstrate that the proposed network performs better in terms of FR accuracy compared with the conventional non-CNN-based method and it can be combined with any CNN-based face classifier.
Self-Calibration Using a Planar Scene and Parallelogram

In this article, we are interested in the utilization of an unknown planar scene for the CCD camera selfcalibration having a constant focal distance. The originality of our method resides in the matching utilization in three images to estimate all matrixes of a parallelogram projection that are exploited with homographies between images to estimate the camera intrinsic parameters. The experimental results show the robustness of our algorithms, in term of stability and convergence.
Health Needs and Self-Efficacy for Patients Undergoing Hemodialysis

Background : Hemodialysis is critical process for chronic renal failure patient that make them have several health needs that must be met to improve the patient self-efficacy. Aim of the Study : This study aimed to assess health needs and identify self-efficacy for patients undergoing hemodialysis. Subjects and method: Design: A descriptive design was used in carrying on this study. Setting : The present study was conducted at the hemodialysis units of El-Salam and Al-Hayah Hospitals that affiliated to the universal health insurance in Port Said Governorate. Subjects : Subjects were recruited using a purposive sampling technique. The total number of patients was (100) patients. Tools : Three tools were used. First tool is demographic characteristics and Patient’s health history sheet. Second tool was health needs assessment scale. Third tool was Self – Efficacy for Managing Chronic Disease Results : The results revealed that all studied patients have met level of arteriovenous access care, 98% of studied sample have met level of psychological need, while 96% , 95% & 88% of them have unmet level of diet , sleep &hygiene and mobility needs respectively. There was significant negative correlation between total health needs scores and total self- efficacy scores among studied sample. Conclusion There was significant negative relation between total health needs and total self-efficacy. Recommendations : Provide Patients undergoing hemodialysis with needed pamphlets, posters and booklets including instructions that contain information about hemodialysis therapy, diet schedule, medication, life style changes.
A mixed‐type Galerkin variational formulation and fast algorithms for variable‐coefficient fractional diffusion equations

We consider the variable‐coefficient fractional diffusion equations with two‐sided fractional derivative. By introducing an intermediate variable, we propose a mixed‐type Galerkin variational formulation and prove the existence and uniqueness of the variational solution over H01(Ω)×H1−β2(Ω) . On the basis of the formulation, we develop a mixed‐type finite element procedure on commonly used finite element spaces and derive the solvability of the finite element solution and the error bounds for the unknown and the intermediate variable. For the Toeplitz‐like linear system generated by discretization, we design a fast conjugate gradient normal residual method to reduce the storage from O(N2) to O(N) and the computing cost from O(N3) to O(NlogN). Numerical experiments are included to verify our theoretical findings. Copyright © 2017 John Wiley & Sons, Ltd.
Model Selection in Finite Mixture Models: A k-Fold Cross-Validation Approach

Finite mixture models, whether latent class models, growth mixture models, latent profile models, or factor mixture models, have become an important statistical tool in social science research. One of the biggest and most debated challenges in mixture modeling is the evaluation of model fit and model comparison. In the application of mixture models, researchers often fit a collection of models and then decide on a single optimal model based on a variety of model fit information. We propose a k-fold cross-validation procedure to model selection whereby the model is repeatedly fit to different partitions of the data set, the resulting model is then applied to kth partition of the sample, and the distribution of fit indexes is examined. This method is illustrated with growth mixture models fit to longitudinal data on reading ability collected as part of the Early Childhood Longitudinal Study–Kindergarten Cohort.
A 2.4-GHz Ring-VCO-Based Sub-Sampling PLL With a −70-dBc Reference Spur by Adopting a Capacitor-Multiplier-Based Sub-Sampling DLL

This paper investigates the mechanisms of spurious contents in a ring-VCO-based sub-sampling phase-locked-loop (SSPLL). An area-efficient solution to suppress reference spurs in a ring-VCO-based SSPLL is proposed using an auxiliary capacitor-multiplier-based delay-locked loop (DLL). Besides, the implementation of a finite state machine circuit with a narrow dead zone improves the relocking time and reduces the power consumption of the PLL. Implemented in a 0.18- $\mu \text{m}$ CMOS technology, the SSPLL has an active area of 0.051 mm2, while consuming a dc power of 4.89 mW at an output frequency of 2.4 GHz. Based on measurement results, the proposed circuit achieves an in-band phase noise of -107 dBc/Hz at 1-MHz offset and a reference spur of -70 dBc. The integrated RMS jitter from 1-kHz to 10-MHz interval is 877.5 fs.