Miracle-dz/UniFAR-FTUs huggingface dataset:
Web-Based Student Task Management System

Task management systems are usually used by the project development teams to track their tasks from beginning to end, delegate subtasks to teammates, and set deadlines to make sure projects get done on time. It helps individuals to work more productively and efficiently. The same concept can be applied to students who have to perform group assignments but are located remotely from each other due to the closure of educational institutions because of the Covid19 pandemic. It is difficult for a student to divide group tasks since they only meet each other virtually through online classes with limited time. The objective of this project is to produce a web-based student task management system that can help UCYP students in managing their assignments and (to better manage the tasks assign) so they will not pass the deadline. The system has task tracking and recommendation features that help the student to manage their tasks easier and can decide the most important or critical task to do first. Student Task Management System implementing the Agile methodology in system development using JavaScript frameworks for both frontend and backend. The front-end is developed using Next.js and TypeScript while the back-end uses Node.js and GraphQL. The back-end itself will connect to the MongoDB database stored in the cloud using the MongoDB Atlas. This system implements authentication using the help of Firebase authentication which makes it easy for users to log in using their Google or Facebook accounts. The Web-based Student Task Management System was able to solve the problem of managing students’ tasks and making them become more productive and efficient in their studies.
One-step iterative reconstruction approach based on eigentissue decomposition for spectral photon-counting computed tomography

Abstract. Purpose: We propose a one-step tissue characterization method for spectral photon-counting computed tomography (SPCCT) using eigentissue decomposition (ETD), tailored for highly accurate human tissue characterization in radiotherapy. Methods: The approach combines a Poisson likelihood, a spatial prior, and a quantitative prior constraining eigentissue fractions based on expected values for tabulated tissues. There are two regularization parameters: α for the quantitative prior, and β for the spatial prior. The approach is validated in a realistic simulation environment for SPCCT. The impact of α and β is evaluated on a virtual phantom. The framework is tested on a virtual patient and compared with two sinogram-based two-step methods [using respectively filtered backprojection (FBP) and an iterative method for the second step] and a post-reconstruction approach with the same quantitative prior. All methods use ETD. Results: Optimal performance with respect to bias or RMSE is achieved with different combinations of α and β on the cylindrical phantom. Evaluated in tissues of the virtual patient, the one-step framework outperforms two-step and post-reconstruction approaches to quantify proton-stopping power (SPR). The mean absolute bias on the SPR is 0.6% (two-step FBP), 0.6% (two-step iterative), 0.6% (post-reconstruction), and 0.2% (one-step optimized for low bias). Following the same order, the RMSE on the SPR is 13.3%, 2.5%, 3.2%, and 1.5%. Conclusions: Accurate and precise characterization with ETD can be achieved with noisy SPCCT data without the need to rely on post-reconstruction methods. The one-step framework is more accurate and precise than two-step methods for human tissue characterization.
The Effect of Work Creation Law on the Five Forces of Competition Related to the Formulation of Competitive Strategies According to Michael E. Porter

The Law on Job Creation is an Omnibus Law that has been ratified by the House of Representatives of the Republic of Indonesia. This is closely related to the interests of workers and employers. After the reform era, there was a change in the issues faced by the workers because they had to deal with the market intervention that was getting stronger due to neoliberalism. By using any point of view, the purpose of the entrepreneur (company) in running his business is to make a profit by winning the competition. To understand the forces that exist and become part of the competition in the industry, it can be done by using the five forces that affect industry competition as proposed by Michael E. Porter. This research is descriptive-analytical research describing research data. The research data was qualitative using secondary data. The results of this study were; The Omnibus Law on Job Creation can affect competition in the industry through competition among companies and can be used by companies to select generic competitive strategies, according to Michael E. Porter. This was caused by the Omnibus Law on Job Creation that was created to help provide certainty and convenience to entrepreneurs in running their business.
Theoretical Study of the Soft Optic Mode Scattering in a Relaxor Ferroelectric: the Strong Effect of the Depolarizing Fields

We analyze scattering of the transverse optic modes by spherically symmetric Polarized Nano Regions (PNR) in the paraelectric phase of relaxor ferroelectrics. Calculations have done in the frame of mean-field model early supposed by E.Iolin & J.Toulouse but depolarization field effects, DF, were taken into account. Elementary excitations of the system are found to be of two types - Vortex (V) and Quasi Polar (QP). DF decreases temperature of the local QP phase transition. The local phase transition temperature is found to be lower (higher) for Vortex than for QP excitations for the case of small (large) size PNR. Therefore both QP and Vortex condensations are possible. Depolarization field hasn't effect on the Vortex scattering. For the case of QP scattering DF effect is essential especially in the case when total angular momentum j=1. Vortex and QP (at j \geq 2) cross section of scattering {\Sigma} are nullified at the small value of momentum q of the incident wave. However QP cross section {\Sigma}(j=1) is saturated at q~0.01-0.001, and nullified only at the ultra small value of q corresponding macroscopic value of the soft mode wavelength. This scattering leads to the suppression of the TO spreading wave regime and allows qualitative understand some features of so-called waterfall phenomena observed early by the Brookhaven group in the neutron inelastic scattering in relaxors. PACS: 77.80. -e; 77.84. -s; 78.70. Nx; 77.22. Gm
Productions and Functional Properties of Palm Sugars

Sugar profile, antioxidant properties, DNA damages, and in vitro predicted glycaemic index (pGI) of palm sugars (syrup and powder) were investigated in comparison with refined cane sugar. It was found that palm sugars exhibited better nutritional qualities than refined cane sugars. Palm sugars in both syrup and powder forms showed similar results, except in some properties. They contained a high content of fructose and glucose. They also exhibited better antioxidant properties, as evidenced by the high content of phenolic compounds and flavonoids. This contributed to their great antioxidant activities when assessed by DPPH radical scavenging activity and FRAP assay. The addition of palm sugar extracts to the reaction mixture effectively protected against DNA damage. For pGI, the mixture of corn starch and palm sugars showed slow digestion rate and, consequently, lower pGI values than those of refined cane sugars. Nutritional and functional properties of palm sugars were thought to be influenced by their retained phytonutrients, as they were processed under mild conditions.
Lie group classification and invariant exact solutions of the generalized Kompaneets equations

In this paper, from the group-theoretic point of view it is investigated such class of the generalized Kompaneets equations (GKEs): $$u_t=\frac1{x^2}\cdot\left[x^4(u_x+f(u))\right]_x, \ (t,x) \in \mathbb{R}_{+} \times \mathbb{R}_{+},$$ where $u=u(t,x)$, $u_t=\frac{\partial u}{\partial t}$, $u_x=\frac{\partial u}{\partial x}$, $u_{xx}=\frac{\partial^2 u}{\partial x^2}$; $f(u)$ is an arbitrary smooth function of the variable $u$. Using the Lie--Ovsiannikov algorithm, the group classification of the class under study is carried out. It is shown that the kernel algebra of the full groups of the GKEs is the one-dimensional Lie algebra $\mathfrak{g}^\cap=\langle \partial_t \rangle$. Using the direct method, the equivalence group $G^\sim$ of the class is found. It is obtained six non-equivalent (up to the equivalence transformations from the group $G^\sim$) GKEs that allow wider invariance algebras than $\mathfrak{g}^\cap$. It is shown that, among the non-linear equations from the class, the GKE with the function $f(u)=u^{\frac43}$ has the maximal symmetry properties, namely, it admits a three-dimensional maximal Lie invariance algebra. Using the obtained operators, it is found all possible non-equivalent group-invariant exact solutions of the GKE under consider.
A New Correlation Coefficient for T -Spherical Fuzzy Sets and Its Application in Multicriteria Decision-Making and Pattern Recognition

The goal of this paper is to design a new correlation coefficient for T -spherical fuzzy sets (TSFSs), which can accurately measure the nature of correlation (i.e., positive and negative) as well as the degree of relationship between TSFS. In order to formulate our proposed idea, we had taken inspiration from the statistical concept of the correlation coefficient. While doing so, we firstly introduce the variance and covariance of two TSFS and then constructed our scheme using these two newly defined notions. The numerical value of our proposed correlation coefficient lies within the interval − 1 , + 1 , as it should be from a statistical point of view, whereas the existing methods cannot measure the negative correlation between TSFS, as their numerical value falls within the interval 0 , 1 , which is not reasonable both statistically and intuitively. This aspect has also been thoroughly demonstrated using some numerical examples. The comparison results witnessed the dominance and upper hand of our proposed method over the existing definitions, with reliable and better results. In order to demonstrate the feasibility, usefulness, and practical application, we applied our proposed scheme to solve technical and scientific problems of multicriteria decision-making and pattern recognition. The numerical results show that our proposed scheme is practically suitable, technically applicable, and intuitively reasonable.
mHealth Apps for Low Back Pain Self-management: Scoping Review

Background The role of self-management in health promotion, as well as prevention and rehabilitation, is increasing through the use of mobile health (mHealth) apps. Such mHealth apps are also increasingly being used for self-management of low back pain (LBP), but their effectiveness has not been sufficiently explored. Objective The aim of this scoping review was to provide an overview of the literature on self-management mHealth apps and their effects on the levels of pain and disability in people with LBP. Methods We applied the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) methodology, including a priori research questions. A literature search was conducted in 2 databases (PubMed and PEDro) for studies published between January 1, 2015, and June 17, 2021. Interventional, cohort, or case series studies with an interventional period were included if the mHealth app included built-in self-management content, the app was used for self-management for people with LBP, and the study reported outcomes regarding pain and disability in people with LBP. Results In total, 7 studies were selected for the review with overall 2307 persons with LBP, of whom 1328 (57.56%) were women. Among the studies (5/7, 71%) that reported the type of pain, 85% (390/459) of the participants were experiencing chronic LBP. A total of 5 different mHealth apps were identified, of which 4 contributed to a statistically significant reduction in LBP and clinically meaningful changes. Of the 7 studies, 4 (57%) used 4 different assessments for disability, of which 3 (75%) showed statistically significant improvements in the level of functional ability of participants in the experimental groups using an mHealth app with built-in self-management content for LBP. Conclusions This scoping review supports the conclusion that people with LBP may benefit from mHealth apps that provide self-management content. However, the generalizability of the findings is limited because of heterogeneity in the pain characterization of the included participants and the intervention durations. More high-quality studies with longer follow-up periods to investigate personalized mHealth approaches are recommended for LBP self-management.
Tecovirimat for the Treatment of Human Monkeypox: An Initial Series From Massachusetts, United States

Abstract A large, ongoing multicountry outbreak of human monkeypox has the potential to cause considerable morbidity and mortality. Therapeutics for the treatment of smallpox, a related Orthopoxvirus, may be used and affect the natural history of monkeypox. We present 3 patients from our hospitals treated with tecovirimat, a pan-Orthopoxvirus inhibitor currently available under an expanded access investigational new drug protocol for monkeypox.
Vehicle Motion Planning With Joint Cartesian-Frenét MPC

The Frenét frame is commonly used in motion planning for its superiority of reshaping nonconvex curving boundaries and decoupling lateral and longitudinal behaviors. Nevertheless, such frame is not friendly for describing vehicle-related characteristics such as body shape and classical dynamic models. By contrast, the Cartesian frame facilitates straightforward modeling of vehicle dynamics, but confronts nonconvex constraints on curving lanes. For purpose of combining the complementary superiority of both frames, this letter proposes a joint Cartesian-Frenét MPC planning method based on a locally linear intermediary connection which is updated along with solving iterations. The augmented Cartesian-Frenét state space is constrained by a Cartesian vehicle control model that stands for tracking feasibility, a set of Frenét road constraints that account for driving safety, and a Cartesian-Frenét transformation that connects both frames. The final optimization is solved iteratively, where each iteration formulates into a quadratic programming problem with help of the apriori trajectory solved by the previous iteration. A comparative simulation and a 5-month-long real-vehicle test prove that the proposed method can produce a feasible and smooth trajectory within a safe area efficiently in complex real-world scenarios.
Adversarial machine learning: the rise in AI-enabled crime

The rise in frequency and consequence of cybercrimes enabled by artificial intelligence (AI) has been a cause of concern for decades. At the same time, we've seen the development of defensive capabilities. This article examines the mechanics of AI-enabled attacks. These include voice mimicking used for crime, and natural processing algorithms absorbing harmful and offensive human text patterns to create problematic virtual situations. It also looks at shadow models – evasion, infiltration and manipulation of machine-learning models through shadow modelling techniques are on the rise due to their straightforward development methods, allowing the identification of shortcomings in input features, which can cause misclassification by the model. With a special focus on spam filters, their structure and evasion techniques, we look at the ways in which artificial intelligence is being utilised to cause harm, concluding with a final analysis of the Proofpoint evasion case.
Rutin and Quercetin Counter Doxorubicin-Induced Liver Toxicity in Wistar Rats via Their Modulatory Effects on Inflammation, Oxidative Stress, Apoptosis, and Nrf2

The presented study was performed to verify whether rutin and/or quercetin can inhibit liver injury induced by doxorubicin (DXR) in male Wistar rats. In this study, male Wistar rats were treated via the oral route with rutin and quercetin (50 mg/kg) either alone or in combination every other day for five weeks concomitant with receiving intraperitoneal DXR (2 mg/kg) two times a week for five successive weeks. Quercetin, rutin, and their combination significantly improved the deteriorated serum AST, ALT, and ALP activities and total bilirubin level, as well as albumin, AFP, and CA 19.9 levels in DXR-injected rats. Treatments of the DXR-injected group with quercetin and rutin prevented the elevation in liver lipid peroxidation and the reduction in superoxide dismutase, glutathione-S-transferase and glutathione peroxidase activities, and glutathione content. Treatments with quercetin and rutin significantly repressed the elevated expression of liver p53 and TNF-α and enhanced Nrf2 expression. Furthermore, the treatments significantly reduced DXR-induced liver histological changes. In conclusion, rutin and quercetin either alone or in combination may have potential preventive effects against DXR-induced hepatotoxicity through inhibiting oxidative stress, inflammation, and apoptosis as well as modulating the Nrf2 expression.
Microcredit and the household food security of the fish farmers: evidence from rural Bangladesh

ABSTRACT The credit-constrained poor fish farmers in Bangladesh usually have limited access to formal credit institutions. As a result, NGOs took the effort to provide collateral-free microcredit support for the fish farmers to tide over their credit-related problems. This study empirically assesses the impact of microcredit on the household food expenditure of fish farmers. The empirical results challenge the existing literature that access to credit increases the food expenditure of poor fish farmers. However, household assets played a pivotal role in increasing the food expenditure capacity of the fish farmers.
Lattices of intermediate and cylindric modal logics

Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva. nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
AutoSpec: detection of narrowband frequency changes in time series

Most established techniques that search for structural breaks in time series have a diﬃcult time identifying small changes in the process, especially when looking for narrowband frequency changes. The problem is that many of the techniques assume very smooth local spectra and tend to produce overly smooth estimates. The problem of over-smoothing tends to produce spectral estimates that miss slight frequency changes because frequencies that are close together will be lumped into one frequency. The goal of this work is to develop techniques that concentrate on detecting slight frequency changes by requiring a high degree of resolution in the frequency domain.
What drives university students to practice social distancing? Evidence from South Korea and Vietnam

As COVID-19 has caused unprecedented social change, governments are implementing several social measures to control transmission. Among them, social distancing is being enforced in almost all countries and is effective in preventing infection. Based on the importance of social distancing, this study identifies factors influencing the intention towards social distancing. The research model was developed by introducing risk perception in the theory of planned behaviour. To examine the proposed model, a survey was conducted with 339 university students from two countries, South Korea and Vietnam. The data were analysed using the partial least squares method. The results show that social distancing attitude and perceived behavioural control significantly influence social distancing intention. The findings indicate that both affective risk perception and cognitive risk perception serve as imperative factors in the formation of social distancing attitudes, subjective norms and perceived behavioural control. However, subjective norms and nationality do not affect social distancing intention. Based on the results, suggestions are made for policymakers to establish effective social measures. © 2022 Victoria University of Wellington and John Wiley & Sons Australia, Ltd.
Accuracy of MRI in Diagnosis of Invasive Placenta by Taking Per Operative Findings as Gold Standard

Objective: To assess the diagnostic accuracy of magnetic resonance imaging (MRI) in detecting invasive placentas using per-operative findings as the gold standard.Methodology: A prospective cross-sectional study was conducted in the diagnostic radiology department of KRL General Hospital Islamabad during Oct 2019 to Sep 2021. Sixty prenatal individuals were identified as having a high risk of invasive placenta and underwent MRI (Phillips 1.5 T) to confirm the diagnosis. A trainee radiologist and a consultant radiologist reviewed the images. The MRI's sensitivity, specificity, positive predictive value, negative predictive value, and accuracy was calculated using a 2×2 contingency tables. Results: Ten cases of invasive placenta were detected postoperatively (gold standard). The MRI had a sensitivity of 90%, a specificity of 93%, a positive predictive value of 90%, a negative predictive value of 90%, and an accuracy of 92.3 percent, respectively. Conclusion: The study concluded that magnetic resonance imaging (MRI) offers a good diagnostic accuracy and is a reproducible technology for prenatal identification of invasive placentas.
Effect of AI chatbot empathy and identity disclosure on willingness to donate: the mediation of humanness and social presence

Abstract This paper explores the effect of chatbot empathy and identity disclosure on willingness to donate (WTD) to a fundraising project and the psychological mechanism in the relationship. In a 3 (information-only vs. cognitive empathy vs. affective empathy) × 2 (chatbot vs. human identity) experiment, 496 US adults had a conversation about a fundraising event with one of six artificial intelligence-powered chatbots. The results revealed that neither chatbot empathy nor identity disclosure has a significant effect on WTD, rejecting the hypotheses. However, the data supported a significant interaction effect between chatbot empathy and identity disclosure on WTD. Moreover, the results suggested that the interaction effect between chatbot empathy and identity disclosure on WTD would be mediated through human likeness and social presence. This study suggests how empathy and human identity of chatbots should be applied with care to avoid the uncanny valley effect.