Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Machine Learning Regression Models for Salary Prediction Featuring Economy Wide Activities and Occupations

A holistic occupational and economy-wide framework for salary prediction is developed and tested using statistical machine learning (ML). Predictive models are developed based on occupational features and organizational characteristics. Five different supervised ML algorithms are trained using survey data from the Saudi Arabian labor market to estimate mean annual salary across economic activities and major occupational groups. In predicting the mean salary over economic activities, the Bayesian Gaussian process regression ML showed a marked improvement in R2 over multiple linear regression (from 0.50 to 0.98). Moreover, lower error levels were obtained: root-mean-square error was reduced by 80% and mean absolute error was reduced by almost 90% compared to multiple linear regression. However, the salary prediction over major occupational groups resulted in artificial neural networks performing the best in terms of both R2, with an improvement from 0.62 in multiple linear regression to 0.94 and errors were reduced by approximately 60%. The proposed framework can help estimate annual salary levels across different types of economic activities and organization sizes, as well as different occupations.
Adela and transformative learning: A Freirean perspective on a community music education project in Melbourne, Australia

In what ways can a community music education project based on historical re-enactment be a vehicle for transformational learning, empowerment and reconnection with community? In 2018, Serenading Adela was performed to celebrate and remember the 100th anniversary of a moment in history when women sang under the prison cell window of Adela Pankhurst, an anti-conscriptionist. The operatic work, which recruited 100 adult participants, was conceived and developed over almost 2 years and rehearsed for 5 months. The researchers were interested in participants’ motivations and their experiences of engagement with a story of historical injustice. Data were collected by holding interviews and focus groups and analysed using thematic analysis informed by Freirean concepts. Five themes emerged, indicating that the pedagogical approach and ideologies of the directors enabled and nurtured collaborative connections, personal growth, new perspectives, meaning-making and empowerment for a diverse group of adults.
Constraint on the growth factor of the cosmic structure from the damping of the baryon acoustic oscillation signature

We determine a constraint on the growth factor by measuring the damping of the baryon acoustic oscillations in the matter power spectrum using the Sloan digital sky survey luminous red galaxy sample. We obtain an effective upper limit on {sigma}{sub 8}D{sub 1}(z=0.3) using the damping of the baryon acoustic oscillation signature, where {sigma}{sub 8} is the root mean square overdensity in a sphere of radius 8h{sup -1} Mpc and D{sub 1}(z) is the growth factor at redshift z. The above result assumes that other parameters are fixed and the cosmology is taken to be a spatially flat cold dark matter universe with the cosmological constant.
S&P 500 Index and Volatility Forecast of Chinese Stock Market

The main purpose of this article is to examine the role of the S&P 500 index in predicting the volatility of China's stock market. Our work is based on the autoregressive model (AR). We further extend this simple benchmark model by adding the volatility of the S&P 500 index. Intrasample regression shows that after adding this indicator, the overall goodness of fit of the model is rising, the explanatory ability is enhanced, and the added variables are also very significant. The out of sample prediction shows that, in terms of statistical test, the extended model has a positive out of sample R-square compared with the benchmark model, and has passed the CW test; In terms of economic test, we find that the extended model has positive CER and Sharp Ratio (SR) compared with the benchmark model. The out of sample predictions of these two aspects show that the newly added S&P 500 index has a good prediction effect. In addition, we also conducted various robustness tests, such as replacing the previous dependent variable (Shanghai Stock Exchange Index) with the CSI 300 index, replacing the previous extended window with a rolling window for prediction, and extending the previous single period prediction to multi period prediction. In the multi period forecast, we found that the S&P 500 index is only effective in a short period, for example, within 3 months, but cannot play a predictive role when it is extended to 6 months.
Integrated Neuroregenerative Techniques for Plasticity of the Injured Spinal Cord

On the slow path to improving the life expectancy and quality of life of patients post spinal cord injury (SCI), recovery remains controversial. The potential role of the regenerative capacity of the nervous system has led to numerous attempts to stimulate the SCI to re-establish the interrupted sensorimotor loop and to understand its potential in the recovery process. Numerous resources are now available, from pharmacological to biomolecular approaches and from neuromodulation to sensorimotor rehabilitation interventions based on the use of various neural interfaces, exoskeletons, and virtual reality applications. The integration of existing resources seems to be a promising field of research, especially from the perspective of improving living conditions in the short to medium term. Goals such as reducing chronic forms of neuropathic pain, regaining control over certain physiological activities, and enhancing residual abilities are often more urgent than complete functional recovery. In this perspective article, we provide an overview of the latest interventions for the treatment of SCI through broad phases of injury rehabilitation. The underlying intention of this work is to introduce a spinal cord neuroplasticity-based multimodal approach to promote functional recovery and improve quality of life after SCI. Nonetheless, when used separately, biomolecular therapeutic approaches have been shown to have modest outcomes.
Chinese University English Teachers’ Professional Learning through Academic Reading on Social Media—A Mixed-Methods Approach

Teachers’ professional learning on social media has received growing attention recently, but research into teachers’ academic engagement on social media remains limited. This study aimed to examine what factors motivated university English teachers to engage with academic reading on social media. The determinants of academic reading on social media were identified by semi-structured interviews, which were further validated by quantitative investigation. The results showed that participants’ perception of values of content knowledge, pedagogical content knowledge, and students’ participation in the classroom affected their intentions toward commitment to academic reading on social media. Additionally, the results revealed that perceived value of pedagogical content knowledge mediated the relationship between perceived value of content knowledge and participants’ intentions toward academic reading on social media while also mediating the relationship between perceived value of students’ participation in the classroom and the participants’ intentions toward academic reading on social media. These findings yield implications for the professional development of university teachers and the development of pedagogical content knowledge.
On a class of Fock-like representations for Lie Superalgebras

Utilizing Lie superalgebra (LS) realizations via the Relative Parabose Set algebra $P_{BF}$, combined with earlier results on the Fock-like representations of $P_{BF}^{(1,1)}$, we proceed to the construction of a family of Fock-like representations of LSs: these are infinite dimensional, decomposable super-representations, which are parameterized by the value of a positive integer $p$. They can be constructed for any LS $L$, either initiating from a given 2-dimensional, $\mathbb{Z}_{2}$-graded representation of $L$ or using its inclusion as a subalgebra of $P_{BF}^{(1,1)}$. As an application we proceed in studying decompositions with respect to various low-dimensional Lie algebras and superalgebras.
Alone and lonely? How physical and perceived isolation can lead to problematic internet use

ABSTRACT Although physical isolation measures can stem the spread of COVID-19, they can also heighten individuals’ perceived isolation and feeling of loneliness, resulting in problematic internet use (PIU). However, studies have rarely investigated both the effects of physical and perceived isolation on PIU. Given the widespread availability and accessibility of digital communication technologies, it is difficult to conclude that the former may necessitate the latter inducing PIU. Using a two-wave longitudinal national survey in Singapore (n = 689), this study found that, at Time 1, both physical and perceived social isolation have direct and independent effects on internet users’ preference for online social interaction (POSI), driving PIU. This, in turn, leads to their experience of negative outcomes at Time 2. The results highlight the importance of considering the independent effects of physical and perceived isolation in affecting POSI leading to PIU.
A comparative study of ecological specialization estimators

1. Ecological specialization is a unifying concept in the biological sciences. While there are reliable ways to characterize specificity at individual and community levels, the evaluation of population and species‐level measures is lacking. There is a need for such assessments given that populations and species are the relevant scales for most ecological and evolutionary processes.
On families of nestohedra

In toric topology it is important to have a way of constructing Delzant polytopes, which have canonical combinatorial data. Furthermore we have examples of quasitoricmanifolds with representatives in all even dimensions. These examples give riseto sequences of polytopes with related combinatorial invariants.In this thesis we intend to formalise the concept of a family of polytopes, whichwill behave in a similar way to the quotient spaces of quasi-toric manifolds. We willthen compute certain combinatorial invariants in this context.Recently, polytope theory has developed to include the ring P with homogeneous polynomialinvariants and an important operator d, which takes a polytope to the disjointunion of its facets. We will examine our families against this background and extendthe polynomial invariants and d to entire families. In particular we will introduce amethod to calculate polynomial invariants of families by the use of partial differentialequations.We will also look at some polytopes called nestohedra, which arise from buildingsets. These nestohedra give us a construction of Delzant polytopes. We will showthat it is possible to calculate d for any given nestohedra directly from its buildingset. We will also show that the canonical characteristic function of a nestohedron, F,which is a facet of a nestohedron, P, agrees with the characteristic function of F asa facet of P.We will see that nestohedra naturally form families. We will end this work bycombining the work on nestohedra with the work on families and calculating thecombinatorial invariants of some families of nestohedra.
Did Elijah Muhammad's Message To the Black Man Uplift Adherents? The Treatment Effects of Membership In The Nation of Islam

Established in 1930, the Nation of Islam (NOI) offered uplift to the wellbeing of Black Americans. Its charismatic leader, the Honorable Elijah Muhammad, articulated how membership in the NOI would improve the well-being of Black Americans. We consider the impact of NOI membership on several measures of individual well-being. Using data from the first wave of the National Survey of Black Americans, we appeal to the Rubin Causal Framework to estimate the treatment effect of being a member of the NOI on certain outcomes: e.g., overall socioeconomic status, self-employment, self-esteem, and health status. To enable causal interpretation, we estimate the treatment parameters by matching on observable covariates that are not affected by the treatment. Treatment parameter estimates suggest that, at least in the late 1970s, had the NOI been able to expand its membership, new adherents would have benefited from enhanced Black identity, a higher likelihood of not having common health problems, and a lower likelihood of hypertension, diabetes, cardiovascular disease, and incarceration. Our findings suggest that the NOI could have had a substantial impact on the individual well-being of Black Americans if it were larger, and that NOI-like organizations can help mitigate race-based inequalities in well-being.
Efficient Spectral Graph Convolutional Network Deployment on Memristive Crossbars

Graph Neural Networks (GNNs) have attracted increasing research interest for their remarkable capability to model graph-structured knowledge. However, GNNs suffer from intensive data exchange and poor data locality, which will cause critical performance and energy bottlenecks under conventional complementary metal oxide semiconductor (CMOS)-based von-Neumann computing architectures (graphics processing unit (GPU), central processing unit (CPU)) for the “Memory Wall” issue. Fortunately, memristive crossbar-based computation has emerged as one of the most promising neuromorphic computing architectures, which has been widely studied as the computing platform for convolutional neural network (CNNs), recurrent neural network (RNNs), spiking neural network (SNNs), etc. This paper proposes the deployment of spectral graph convolutional networks (GCNs) on memristive crossbars. Further, based on the structure of GCNs (extremely high sparsity and unbalanced non-zero data distribution) and the neuromorphic characteristics of memristive crossbar circuit, we propose the acceleration method that consists of Sparse Laplace Matrix Reordering and Diagonal Block Matrix Multiplication. The simulated experiment on memristor crossbars achieves 90.3% overall accuracy on the supervised learning graph dataset (QM7), and compared with the original computation, the proposed acceleration computing framework (with half-size diagonal blocks) achieves a 27.3% reduction of memristor number. Additionally, on the unsupervised learning dataset (Karate club), our method shows no loss of accuracy with half-size diagonal block mapping and reaches a 32.2% reduction of memristor number.
Rubus Capped Zinc Oxide Nanoparticles Induce Apoptosis in MCF-7 Breast Cancer Cells

Rubus fairholmianus (RF) has widely been used to treat various ailments, including pain, diabetes, and cancer. Zinc oxide nanoparticles (ZnO NPs) have drawn attention in modern healthcare applications. Hence, we designed this study to synthesize zinc oxide (ZnO) nanoparticles using R. fairholmianus root extract to investigate its synergistic cytotoxic effect on MCF-7 cells and explore the possible cell death mechanism. ZnO NPs were synthesized via green synthesis using R. fairholmianus root extract, and the effect on MCF-7 cells was determined by looking at cellular morphology, proliferation, cytotoxicity, apoptosis, and reactive oxygen species (ROS). The results showed that cellular proliferation was reduced following treatment with R. fairholmianus capped zinc oxide nanoparticles (RFZnO NPs), while cytotoxicity and ROS were increased. There was also an increase in apoptosis as indicated by the significant increase in cytoplasmic cytochrome c and caspase 3/7 (markers of apoptosis), as well as increased levels of pro-apoptotic proteins (p53, Bax) and decreased levels of anti-apoptotic protein (Bcl-2). In conclusion, these results showed that RFZnO NPs induce apoptosis in breast cancer cells via a mitochondria-mediated caspase-dependent apoptotic pathway and suggest the use of acetone root extract of R. fairholmianus for the treatment of cancer-related ailments.
Patterned Colouring via Variable-Speed Single Stretching

We demonstrate a cost-effective, highly reliable/stable and environmentally friendly approach for the patterned colouring of a commercial transparent polyethylene terephthalate (PET). We show that different colour patterns (transparent, white/translucent, complete white/silver and different combinations of these three colours) can be realised in PET strips upon varying the speed during continuous stretching. The conditions for good quality colour patterns are investigated, and the length of transient region during speed change is investigated.
Seeking serpents: Ball python trade in Benin, West Africa

Ball pythons are traded as bushmeat, leather and belief-based medicine in West Africa, and specimens are exported in large numbers for the exotic pet trade. Here, we focused on understanding the purpose and socio-economic context of this trade in Benin through interviews with 44 actors involved in the trade of this species. We provided a snapshot of trade dynamics during a period when hunters are not predominantly actively involved in supplying eggs, neonates and gravid females for ranching and export as exotic pets. Our findings revealed that hunters and traders were largely focused on supplying the bushmeat and medicine markets in West Africa during this time. We estimated that the 21 collectors engaged in hunting in our study collectively hunt between 576 and 5,083 ball pythons from the wild each year. Collection rates reported by some suggests that they could earn more than 15,000 USD from ball python sales in bushmeat markets annually. Ball pythons hunted in Benin were mainly sold to local customers as “bushmeat” (53%) or for belief-based uses (39%) (including “fetish”, “medicinal products” and “voodoo”). However, cross-border trade with neighboring countries of Togo, Nigeria, and Ghana (or even further) also occurred. Although profitable for some, the scale of this practice, together with the widely reported decline in ball python populations in Benin, raises concern about the sustainability and long-term economic viability of this type of large-scale commercial wildlife trade in West Africa, especially as it occurs alongside extensive ranching practices to support the exotic pet trade.
A NOVEL USE OF LATENT CLASS MODELLING TO UNDERSTAND THE HETEROGENEITY OF URBAN LAND USE EFFICIENCY IN CHINA

Abstract. Urban and regional development disparity is a salient issue for both developed and developing countries, and increasing development control brings the efficiency of urban land use to the forefront. Understanding the heterogeneity of urban land-use efficiency is therefore important for balancing growth-oriented land supply and sustainable development. However, two research gaps can be identified from existing studies. Firstly, the disparities of urban land-use efficiency are usually multi-faceted, the measurement of which is thus a major challenge. Secondly, a systematic investigation of land-use efficiency and the associated geographical heterogeneity using multidimensional, longitudinal measurements seems limited. Therefore, this paper presents a novel latent class modelling method for understanding the pattern of such heterogeneity using purposely constructed, repeated cross-sectional measurements, including local government revenue density and employment density. Using data of 272 prefecture-level Chinese cities, our model first identifies the level of urban land-use efficiency can be split into three distinct cities groups based on the performance in 2017. To further investigate the change of the efficiency over the years (2012–2017), two separate models have been applied and a total of five latent groups among Chinese cities are identified with distinct development patterns. This modelling approach represents a viable method for assessing the land-use efficacity, both statically and over time, across a large number of cities of varying development stages. Policy implications are drawn.
Applications of Hemp Polymers and Extracts in Food, Textile and Packaging: A Review

Hemp (Cannabis sativa Linn.) is a high-yielding annual crop farmed for its stalk fiber and oil-producing seeds. This specialized crop is currently experiencing a revival in production. Hemp fiber contains pectin, hemicellulose and lignin with superior strength, while hemp seed oil contains unsaturated triglycerides with well-established nutritional and physiological properties. Therefore, focus on the utilization of hemp in various industries is increasing globally. This study reviewed recent applications of hemp components, including fiber and extract, in food, textile and packaging applications. Hemp fibers mainly consisting of cellulose derivatives have superior strength to be used as reinforcements in thermoplastic packaging and paper. Combined physical and chemical modifications of hemp fibers improved mechanical and barrier properties of composite materials. Physically and chemically processed hemp extracts have been used in food and non-food applications. Functional foods containing hemp oils deliver nutrients by their unsaturated lipids. High-quality hemp fiber with several fiber modifications has been applied in garments. Innovative applications of hemp components and by-products are increasing, thereby facilitating utilization of green sustainable biomaterials.
Measure of Departure from Conditional Partial Symmetry for Square Contingency Tables

: For square contingency tables, a symmetry of conditional probability in part of the off-diagonal cells is considered with respect to the main diagonal. A measure is proposed to represent the degree of departure from the symmetric structure and gives the approximate confidence interval. Some numerical experiments are performed to illustrate the validity and usefulness of the proposed measure. Japanese occupational data are analyzed using the measure.
Application of Microfluidics in Drug Development from Traditional Medicine

While there are many clinical drugs for prophylaxis and treatment, the search for those with low or no risk of side effects for the control of infectious and non-infectious diseases is a dilemma that cannot be solved by today’s traditional drug development strategies. The need for new drug development strategies is becoming increasingly important, and the development of new drugs from traditional medicines is the most promising strategy. Many valuable clinical drugs have been developed based on traditional medicine, including drugs with single active ingredients similar to modern drugs and those developed from improved formulations of traditional drugs. However, the problems of traditional isolation and purification and drug screening methods should be addressed for successful drug development from traditional medicine. Advances in microfluidics have not only contributed significantly to classical drug development but have also solved many of the thorny problems of new strategies for developing new drugs from traditional drugs. In this review, we provide an overview of advanced microfluidics and its applications in drug development (drug compound synthesis, drug screening, drug delivery, and drug carrier fabrication) with a focus on its applications in conventional medicine, including the separation and purification of target components in complex samples and screening of active ingredients of conventional drugs. We hope that our review gives better insight into the potential of traditional medicine and the critical role of microfluidics in the drug development process. In addition, the emergence of new ideas and applications will bring about further advances in the field of drug development.