Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19 Prediction based on Infected Cases and Deaths of Bangladesh using Deep Transfer Learning

The severely infectious virus known as “COVID- 19” has wreaked havoc on the planet, trapping to keep the disease from spreading, while billions of people are staying inside. Every experts and professionals in many disciplines are working tirelessly to create a vaccine and preventative techniques to help the globe overcome this difficult crisis. In Bangladesh, the number of persons infected with Coronavirus is particularly alarming. A accurate prognosis of the epidemic, on the other hand, may aid in the management of this contagious illness until a remedy is discovered. This study aims to forecast impending COVID-19 exposed instances and fatalities using a time series dataset utilizing proposed deep transfer learning model where encoder-decoder CNN-LSTM along with deep CNN pretrained models such as: ResNet-50, DenseNet-201, MobileNet-V2, and Inception-ResNet-V2 performed. We also predict the regular exposed instances and fatalities throughout the following 180 days in data visualization segment using AIC and BIC selection criteria. The suggested paradigms are also used to anticipate Bangladesh's daily confirmed cases and daily which is evaluated by error based on three performance criteria. We discovered that ResNet-50 performs better among others for predicting infected case and deaths owing to COVID-19 in Bangladesh in terms of MAPE, MAE and RMSE evaluations.
First, do no harm: automated detection of abusive comments in student evaluation of teaching surveys

ABSTRACT Student evaluation of teaching (SET) surveys are the most widely used tool for collecting higher education student feedback to inform academic quality improvement, promotion and recruitment processes. Malicious and abusive student comments in SET surveys have the potential to harm the wellbeing and career prospects of academics. Despite much literature highlighting abusive feedback in SET surveys, little research attention has been given to methods for screening student comments to identify and remove those that may cause harm to academics. This project applied innovative machine learning techniques, along with a dictionary of keywords to screen more than 100,000 student comments made via a university SET during 2021. The study concluded that these methods, when used in conjunction with a final stage of human checking, are an effective and practicable means of screening student comments. Higher education institutions have an obligation to balance the rights of students to provide feedback on their learning experience with a duty to protect academics from harm by pre-screening student comments before releasing SET results to academics.
Predictive Algorithms Analysis to Improve Sustainable Mobility

The work is based on carrying out a comparative analysis of 3 prediction algorithms (Linear Regression, Neural Networks, and KNN), which allow the study of information on georeferential coordinates of moving objects, since through an exhaustive study it will be possible to know the predictions of each one. of them and then proceed to comply with the main objective that is to implement the algorithm with greater accuracy and effectiveness, making use of open Source tools that allow working with Machine Learning and thus be able to analyze the forecasts of traffic congestion that is formed in the surroundings of the University of Guayaquil, because this generates a great inconvenience for students and administrative personnel who belong to this institution and diminish an improvement in sustainable mobility. The methodology used is the Waterfall methodology, as it is a linear model of simple implementation, where each phase of the project was emphasized, allowing possible disorientation of the results to be managed and achieving the development of the proposed project without any inconvenience.
Simulation and fabrication of two-dimensional photonic crystal drop filters for biosensing

The main goal of this master thesis was to design and fabricate a biosensor consisting of a 2D photonic crystal. Its periodicity was made by etching a hexagonal hole pattern in a silicon slab, and a few linear defects were added by removing some of the holes. The result was a drop filter consisting of two waveguides with a resonator between them, all of which were positioned on top of a layer of silicon oxide. The idea was that light would couple, or “drop”, from one waveguide to the other if, and only if, it belonged to a resonance frequency, hence the name of the filter. However, the exact resonance frequencies would depend upon the refractive index of the surrounding media, making the filter able to sense its surroundings. To reach that goal, several issues had to be addressed regarding the fabrication method, including silicon growth and etch times, increases in the hole radius relative to the exposure mask and resist cracking. In addition, an estimate of the refractive index nSi ≈ 3.37 for the amorphous silicon slab was found using a combination of simulations and fabrications. Simulation tools were also used both to optimize the silicon slab thickness, which was the only major parameter that had not been optimized during the project thesis, and to measure the biosensing abilities of the device. In addition, they were used to test the possibility of combining two drop filters along one waveguide, called multiplexing. The results from the work mentioned above were used to fabricate a set of functioning drop filters. They resonated nicely, creating a high-intensity peak on the transmission graphs for the dropped light. Finally, the biosensing abilities of the drop filters were tested by changing the surrounding medium from air to purified water both inside the photonic crystal holes and above the crystal. It resulted in a resonance shift of approximately 25 nm, which corresponded to a normalized frequency shift of 4.3× 10−3. The goal of the project can therefore be considered as reached.
Chocolate and Cocoa-Derived Biomolecules for Brain Cognition during Ageing

Cognitive decline is a common problem in older individuals, often exacerbated by neurocognitive conditions, such as vascular dementia and Alzheimer’s disease, which heavily affect people’s lives and exert a substantial toll on healthcare systems. Currently, no cure is available, and commonly used treatments are aimed at limiting the progressive loss of cognitive functions. The absence of effective pharmacological treatments for the cognitive decline has led to the search for lifestyle interventions, such as diet and the use of nutraceuticals that can prevent and limit the loss of cognition. Cocoa and chocolate are foods derived from cocoa beans, commonly used in the population and with good acceptability. The purpose of this review was to collect current experimental evidence regarding the neuroprotective effect of chocolate and cocoa (or derived molecules) in the elderly. From a systematic review of the literature, 9 observational studies and 10 interventional studies were selected, suggesting that the biomolecules contained in cocoa may offer promising tools for managing cognitive decline, if provided in adequate dosages and duration of treatment. However, the molecular mechanisms of cocoa action on the central nervous system are not completely understood.
A Two-Way Update Resource Allocation Strategy in Mobile Edge Computing

Existing studies of mobile edge computing resource allocation strategy problem merely optimize delay and energy cost, seldom considering the benefit of edge servers. So, a two-way update strategy based on game theory (TUSGT) was proposed. TUSGT converts the task competition relationship among edge servers into a noncollaborative game issue and adopts a potential game-based joint optimization strategy, allowing edge servers to determine task selection preference by maximizing their own benefit as the objective. At mobile device side, the EWA algorithm of online learning was used to update parameters, exerting impact on edge server’s task selection preference from a global perspective and improving overall deadline hit rate. The simulation test results show that, compared to BGTA, MILP, greedy strategy, random strategy, and ideal strategy, TUSGT promotes deadline hit rate by up to 30% and increases edge server’s average benefit by up to 65%.
Ferroptosis: A Novel Therapeutic Direction of Spinal Cord Injury

An injury to the spinal cord results in a crucial central nervous system event that further causes irreversible impairment or loss of motor, autonomic, and sensory functions. A progressive pathophysiological cascade following spinal cord injury (SCI) includes ischemia/reperfusion injury, oxidative stress, proapoptotic signaling, peripheral inflammatory cell infiltration, and glutamate-mediated excitotoxicity, and regulated cell death. These complex pathological and physiological changes continue to cause cell injury over the long-term and severely limit the efficacy of clinical treatment strategies in restoring the injured nervous system. Ferroptosis is a nonapoptotic, iron-regulated kind of cell death that has recently been discovered. It is distinguished by iron overload-induced toxic lipid peroxidation associated with mitochondrial morphological changes during the cell death process. For example, after SCI, iron overload activates the reactive oxygen species generation, dysregulation of glutathione/glutathione peroxidase 4 (GSH/GPX4) metabolism, and accumulation of lipid peroxides, which cause lipid membrane deterioration and ferroptosis. Conversely, knockout or differential expression of key genes and application of lipid peroxidation inhibitors and iron chelators (e.g., deferoxamine) (e.g., SRS-16-86) can block ferroptosis and promote neuronal repair for functional recovery after SCI. Although the findings of numerous investigations have been confirmed the importance of ferroptosis in several human neurologic sicknesses and its potential in SCI, the mechanism of ferroptosis and its application in SCI has not been elucidated. This review highlights current ferroptosis research and its impact on SCI, as well as the key molecular mechanism of ferroptosis in promoting the recovery from SCI. Understanding ferroptosis' process and function in SCI could provide useful insight into the treatment and avoidance of such a destructive injury.
Prospective Science Teachers’ Self-Confidence in Computational Thinking Skills

This study aims to analyze prospective science teachers’ self-confidence in computational thinking skills on three main points: (i) prospective science teachers’ self-confidence in computational thinking skills, (ii) differences in prospective science teachers’ self-confidence in computational thinking skills as per gender, and (iii) differences in prospective science teachers’ self- confidence in computational thinking skills as per expertise (Biology and Physics). A quantitative cross-sectional survey methodology was used as the research design. A total of 1023 prospective science teachers (biology and physics) were randomly selected as the research sample from the 1959 total population. Data were collected using a self-confidence questionnaire on computational thinking skills. The adaptation results were assessed first by five experts before being tested on 74 prospective science teachers from different universities. The results show that prospective science teachers’ self-confidence in computational thinking skills was generally high (Mean = 78.57). The Mann-Whitney U test found no difference in prospective science teachers’ self-confidence in computational thinking skills as per gender (Mean= 78.05, SD= 9.03 for male, Mean= 78.73, SD= 6.86 for female, with a value of F= 6.028, Z= -0.891, Sig= 0.373 0.05). The Independent Sample t-test also showed no difference in prospective science teachers’ self-confidence in computational thinking skills as per expertise. This study concludes that prospective science teachers have high self-confidence in computational thinking skills as crucial skills in the science teaching profession.
Metabolic Plasticity of Candida albicans in Response to Different Environmental Conditions

The ubiquitous commensal Candida albicans, part of the human microbiota, is an opportunistic pathogen able to cause a wide range of diseases, from cutaneous mycoses to life-threatening infections in immunocompromised patients. Candida albicans adapts to different environments and survives long-time starvation. The ability to switch from yeast to hyphal morphology under specific environmental conditions is associated with its virulence. Using hydrogen nuclear magnetic resonance spectroscopy, we profiled the intracellular and extracellular metabolome of C. albicans kept in water, yeast extract–peptone–dextrose (YPD), and M199 media, at selected temperatures. Experiments were carried out in hypoxia to mimic a condition present in most colonized niches and fungal infection sites. Comparison of the intracellular metabolites measured in YPD and M199 at 37 °C highlighted differences in specific metabolic pathways: (i) alanine, aspartate, glutamate metabolism, (ii) arginine and proline metabolism, (iii) glycerolipid metabolism, attributable to the diverse composition of the media. Moreover, we hypothesized that the subtle differences in the M199 metabolome, observed at 30 °C and 37 °C, are suggestive of modifications propaedeutic to a subsequent transition from yeast to hyphal form. The analysis of the metabolites’ profiles of C. albicans allows envisaging a molecular model to better describe its ability to sense and adapt to environmental conditions.
X-band epi-BAW resonators

Using epitaxial aluminum nitride (AlN) developed for ultraviolet photonics and high-speed electronics, we demonstrate suspended AlN thin-film bulk acoustic resonators (FBARs) at 9.2 GHz in the X-band (8–12 GHz) of the microwave spectrum. The resonators show a [Formula: see text] and a figure of merit [Formula: see text] THz. The material stack of these epi-AlN FBARs allows monolithic integration with AlN/GaN/AlN quantum well high-electron-mobility-transistors to a unique RF front end and also enable integration with epitaxial nitride superconductors for microwave filters for quantum computing.
A Design for Task-Role Based Access Control for Personal Health Record Systems

Abstract – We present our design for a Task-Role Based Access control system for Personal Health Records (PHR). Current access control models deployed for PHR systems are, at best, based on role-based models. This neither allow for flexibility nor fine-grained restrictions on access to records. The ideal situation is to have a dynamic, task-based access control model on top of the role-based restrictions. Multiple constrains were also added to provide a more fine-grained access. Furthermore, specific policies for PHR systems were also defined. From our survey of existing PHR systems none provide these combination of dynamic access control coupled with constraints and roles. We implemented a prototype, a hybrid PHR-EMR (Electronic Medical Record) system, of our design where we applied the security model we are proposing. We also conducted a usability testing and our evaluation shows that our design can be used and implemented in an actual PHR. Keywords : Access Control, TRBAC, Task – Role Based Access Control, PHR, Personal Health Record System.
Identification of Material Viscoelastic Properties using the Motion of a Rigid Sphere Located at Tissue-Mimicking Material Interface in Response to a Dynamic Force

The motion of a rigid sphere located at tissue-mimicking material interface in response to a dynamic force of short duration for the purpose of the determination of material viscoelastic properties was investigated in this study. The experiments were performed using a rigid sphere located at tissue-like material (gelatin phantom) interfaces. An electromagnet was used to apply the desired dynamic force to the sphere and a high-speed camera was used to track the movement of the sphere. Using the experimentally measured response of the sphere and the dynamic response of the sphere predicted by a sophisticated analytical model of the sphere located at a medium interface, the shear modulus, density and damping of the tissue-mimicking material were determined. The procedure followed in this study successfully produced the shear modulus, density and viscous damping ratio of the 20% (and 30%) gelation phantom as 1320 Pa, 1040 kg/m3 and 0.12 (and 2580 Pa, 1180 kg/m3 and 0.2), respectively. As the sophisticated theoretical model that is valid for small and large sphere displacements includes many parameters for the system such as the mass and size of the sphere, the inertia force of the medium involved in motion and the radiation damping due to shear waves and the experimental setup is very straightforward, it is believed that the procedure proposed in this study can be widely exploited to identify accurate material viscoelastic properties in practice.
Biocrust‐forming lichens increase soil available phosphorus under simulated climate change

Drylands are important reservoirs of soil phosphorus (P) at the global scale, although large uncertainties remain regarding how climate change will affect P cycling in these ecosystems. Biocrust‐forming lichens are important regulators of abiotic and biotic processes occurring in the soil surface, including nutrient availability and redistribution, across global drylands. However, their role as modulators of climate change impacts on soil P cycling is poorly known. We conducted a manipulative microcosm experiment to evaluate how six biocrust‐forming lichens (Buellia zoharyi, Diploschistes diacapsis, Fulgensia subbracteata, Psora decipiens, Squamarina lentigera and Toninia sedifolia) with diverse morphology and chemistry affect soil available P concentration and the activity of acid phosphatase after 50 months of simulated ~2°C warming and 35% rainfall reduction. Lichens increased soil available inorganic and total available P, and the activity of acid phosphatase, although the magnitude of these effects was highly species‐specific. Climate change treatments increased available organic P regardless of lichen species. Our findings provide novel experimental evidence of the importance of biocrusts as modulators of P cycling in drylands and highlight the necessity to take into account the identity of biocrust constituents when evaluating their effects on soil fertility.
Analysis of Acute Nitrite Exposure on Physiological Stress Response, Oxidative Stress, Gill Tissue Morphology and Immune Response of Large Yellow Croaker (Larimichthys crocea)

Simple Summary Fish are vulnerable to nitrite stress and display variations in physiologic parameter and stress response. In this study, the effects of nitrite on the stress response of large yellow croaker were evaluated. Large yellow croaker were exposed to four (i.e., 0, 29.36, 58.73, and 88.09 mg/L) nitrite concentrations for 48 h. The results of this study indicated that nitrite exposure could induce oxidative stress in the gills and serum of large yellow croaker. The result of immunoglobulin and lysozyme levels indicated that nitrite exposure could cause an immune response in large yellow croaker. In addition, nitrite stress changed the morphology of the gill of large yellow croaker. Abstract Nitrite is a common pollutant in aquaculture water, and nitrite toxicity that negatively affects aquatic species is common in aquaculture systems when the water quality is low. Therefore, the present research aimed to evaluate the effect of acute nitrite exposure on the hematological parameters, antioxidant enzymes, immune response, and gill morphology of large yellow croaker (Larimichthys crocea). The fish were randomly separated and exposed to four (i.e., 0, 29.36, 58.73, and 88.09 mg/L) nitrite concentrations for 48 h. The fish blood and gills were collected at 0, 12, 24, 36, and 48 h of nitrite exposure for further analysis. In hematological parameters, the results showed that the levels of hemoglobin, triglyceride, and total cholesterol in blood significantly decreased (p < 0.05) in all nitrite-treated samples after 12 h, while the contents of methemoglobin in blood significantly increased (p < 0.05) in these treatments. After 48 h of nitrite exposure, the levels of cortisol in serum showed a 94.5%, 132.1%, and 165.6% increase in fish exposed to 29.36, 58.73, and 88.09 mg/L nitrite, respectively. The nitrite (i.e., 29.36, 58.73, and 88.09 mg/L) exposure significantly increased (p < 0.05) the levels of antioxidant enzymes (i.e., catalase and glutathione) in the gill and serum after 12 h of exposure compared with the control. The lysozyme levels in serum decreased in the nitrite (i.e., 29.36, 58.73, and 88.09 mg/L) exposure samples. It was found that immunoglobulin levels in the 29.36, 58.73, and 88.09 mg/L nitrite-treated samples (i.e., 1.86, 1.58, and 0.74 μg/mL, respectively) were lower than that of the control (2.56 μg/mL). In addition, the surface of the gill lamellae displayed deformation and contraction after 48 h of nitrite, especially in the fish exposed to 88.09 mg/L nitrite. These results indicate that the nitrite exposure induced the oxidative stress, affected the immune response, and changed the gill morphology, leading to nitrite poisoning in large yellow croaker.
Enhanced seedling growth by 3‐n‐pentadecylphenolethanolamide is mediated by fatty acid amide hydrolases in upland cotton ( Gossypium hirsutum L.)

Abstract Fatty acid amide hydrolase (FAAH) is a conserved amidase that is known to modulate the levels of endogenous N‐acylethanolamines (NAEs) in both plants and animals. The activity of FAAH is enhanced in vitro by synthetic phenoxyacylethanolamides resulting in greater hydrolysis of NAEs. Previously, 3‐n‐pentadecylphenolethanolamide (PDP‐EA) was shown to exert positive effects on the development of Arabidopsis seedlings by enhancing Arabidopsis FAAH (AtFAAH) activity. However, there is little information regarding FAAH activity and the impact of PDP‐EA in the development of seedlings of other plant species. Here, we examined the effects of PDP‐EA on growth of upland cotton ( Gossypium hirsutum L. cv Coker 312) seedlings including two lines of transgenic seedlings overexpressing AtFAAH. Independent transgenic events showed accelerated true‐leaf emergence compared with non‐transgenic controls. Exogenous applications of PDP‐EA led to increases in overall seedling growth in AtFAAH transgenic lines. These enhanced‐growth phenotypes coincided with elevated FAAH activities toward NAEs and NAE oxylipins. Conversely, the endogenous contents of NAEs and NAE‐oxylipin species, especially linoleoylethanolamide and 9‐hydroxy linoleoylethanolamide, were lower in PDP‐EA treated seedlings than in controls. Further, transcripts for endogenous cotton FAAH genes were increased following PDP‐EA exposure. Collectively, our data corroborate that the enhancement of FAAH enzyme activity by PDP‐EA stimulates NAE‐hydrolysis and that this results in enhanced growth in seedlings of a perennial crop species, extending the role of NAE metabolism in seedling development beyond the model annual plant species, Arabidopsis thaliana .