Miracle-dz/UniFAR-FTUs huggingface dataset:
Cryptocurrency Price Prediction using Twitter Sentiment Analysis

The cryptocurrency ecosystem has been the centre of discussion on many social media platforms, following its noted volatility and varied opinions. Twitter is rapidly being utilised as a news source and a medium for bitcoin discussion. Our algorithm seeks to use historical prices and sentiment of tweets to forecast the price of Bitcoin. In this study, we develop an end-to-end model that can forecast the sentiment of a set of tweets (using a Bidirectional Encoder Representations from Transformers - based Neural Network Model) and forecast the price of Bitcoin (using Gated Recurrent Unit) using the predicted sentiment and other metrics like historical cryptocurrency price data, tweet volume, a user's following, and whether or not a user is verified. The sentiment prediction gave a Mean Absolute Percentage Error of 9.45%, an average of real-time data, and test data. The mean absolute percent error for the price prediction was 3.6%.
Assessing Stress Levels, Predictors and Management Strategies of Inmates at Ankaful Prison Complex in the Central Region, Ghana

Background: Stress among prison inmates is a neglected psychological health issue, but this phenomenon seems worse in Ghana’s prisons. This study examined the stress levels, predictors and management strategies utilized among inmates at Ankaful Prison Complex. Method: This survey sampled 1160 inmates using the census approach at the Ankaful Prison Complex with a self-developed questionnaire for the data collection. Frequency counts, one-way ANOVA, and multiple regression analysis were applied to the data. Results: The findings indicate that more than half of the inmates were moderately or highly stressed. Specifically, inmates at the Maximum Security Prison were the most stressed, followed by Annex Prison, Communicable Disease Prison, and the least, Main Camp Prison inmates. Inmate engagement in exercises, sporting activities, visit and chat with colleagues, and family connectedness outside the prison were stress-management strategies. Inmates’ self-reported stress levels were influenced by the prison of custody and state of depression. Conclusion: The moderate to high stress levels identified among inmates of Ankaful Prison Complex are influenced by person–environment factors. Management of the Ankaful Prison Complex is encouraged to initiate health screening services for inmates on common mental health challenges such as stress and to promote functional stress reduction interventions to improve prisoners’ mental health and overall well-being.
Evaluation of the Association of VDR rs2228570 Polymorphism with Elite Track and Field Athletes’ Competitive Performance

The present study aimed to examine the vitamin D receptor (VDR), rs2228570 polymorphism, and its effect on elite athletes’ performance. A total of 60 elite athletes (31 sprint/power and 29 endurance) and 20 control/ physically inactive, aged 18–35, voluntarily participated in the study. The International Association of Athletics Federations (IAAF) score scale was used to determine the performance levels of the athletes’ personal best (PB). Whole exome sequencing (WES) was performed by the genomic DNA isolated from the peripheral blood of the participants. Sports type, sex, and competitive performance were chosen as the parameters to compare within and between the groups by linear regression models. The results showed no statistically significant difference between the CC, TC, and TT genotypes within and between the groups (p > 0.05). Additionally, our results underlined that there were no statistically significant differences for the association of rs2228570 polymorphism with PBs within the groups of the (p > 0.05) athletes. The genetic profile in the selected gene was similar in elite endurance, sprint athletes, and in controls, suggesting that rs2228570 polymorphism does not determine competitive performance in the analyzed athlete cohort.
Meta Derivative Identity for the Conditional Expectation

Consider a pair of random vectors <inline-formula> <tex-math notation="LaTeX">$( {\mathbf{X}}, {\mathbf{Y}}) $ </tex-math></inline-formula> and the conditional expectation operator <inline-formula> <tex-math notation="LaTeX">$ \mathbb {E}[ {\mathbf{X}}| {\mathbf{Y}}={\mathbf{y}}]$ </tex-math></inline-formula>. This work studies analytical properties of the conditional expectation by characterizing various derivative identities. The paper consists of two parts. In the first part of the paper, a general derivative identity for the conditional expectation is derived. Specifically, for the Markov chain <inline-formula> <tex-math notation="LaTeX">$ {\mathbf{U}}\leftrightarrow {\mathbf{X}}\leftrightarrow {\mathbf{Y}}$ </tex-math></inline-formula>, a compact expression for the Jacobian matrix of <inline-formula> <tex-math notation="LaTeX">$ \mathbb {E}[ \psi ( {\mathbf{Y}}, {\mathbf{U}})| {\mathbf{Y}}= {\mathbf{y}}]$ </tex-math></inline-formula> for a smooth function <inline-formula> <tex-math notation="LaTeX">$\psi $ </tex-math></inline-formula> is derived. In the second part of the paper, the main identity is specialized to the exponential family and two main applications are shown. First, it is demonstrated that, via various choices of the random vector <inline-formula> <tex-math notation="LaTeX">$ {\mathbf{U}}$ </tex-math></inline-formula> and function <inline-formula> <tex-math notation="LaTeX">$\psi $ </tex-math></inline-formula>, one can recover and generalize several known identities (e.g., Tweedie’s formula) and derive some new ones. For example, a new relationship between conditional expectations and conditional cumulants is established. Second, it is demonstrated how the derivative identities can be used to establish new lower bounds on the estimation error. More specifically, using one of the derivative identities in conjunction with a Poincaré inequality, a new lower bound on the minimum mean squared error, which holds for all prior distributions on the input signal, is derived. The new lower bound is shown to be tight in the high-noise regime for the additive Gaussian noise setting.
DIVORCE IN KANGEAN ISLANDS

Purpose of the study: This article aims to find out how the divorce conditions in the Kangean Islands are and to see how the factors that influence it and the legal reasoning used by the judge in deciding the divorce case. Methods: the method used in this study is a normative juridical method with a decision approach, the data used is secondary data, namely the decisions of the religious courts in 2020-2022, which every year 30% of the decisions are taken, the data are analyzed descriptively Results: From the research conducted, it was found that the majority of divorces in Kangean Island were carried out by a contested divorce mechanism, while the factors behind the majority were due to disputes, then followed by economic factors, legal reasoning judges were divided into empathy, namely the use of legal norms, conformity between facts and norms. , interpretation of problems and norms, as well as the use of the rules of Islamic law in its legal opinion Applications of this study: This article is useful to support research on divorce and legal opinions, especially on Kangean Island and Indonesia in general Novelty: The novelty of this research is that there are still very few people doing research on the Kangean Islands, as well as the discovery of several legal reasoning concepts for judges at the Kangean Religious Court. ABSTRAK Tujuan Penelitian: Artikel ini bertujuan untuk mengetahui bagaimana kondisi perceraian di Kepulauan Kangean dan melihat bagaimana faktor-faktor yang mempengaruhinya serta alasan hukum yang digunakan hakim dalam memutus perkara perceraian. Metode : Metode yang digunakan dalam penelitian ini adalah metode yuridis normatif dengan pendekatan putusan, data yang digunakan adalah data sekunder yaitu putusan pengadilan agama tahun 2020-2022 yang setiap tahun diambil 30% putusannya, data tersebut dianalisis secara deskriptif Hasil: Dari penelitian yang dilakukan diketahui bahwa mayoritas perceraian di Pulau Kangean dilakukan dengan mekanisme cerai gugat, sedangkan faktor penyebab mayoritas adalah karena perselisihan, kemudian disusul faktor ekonomi, pertimbangan hukum hakim terbagi menjadi empati, yaitu penggunaan norma hukum, kesesuaian antara fakta dan norma. , interpretasi masalah dan norma, serta penggunaan aturan hukum Islam dalam opini hukumnya Aplikasi penelitian ini: Artikel ini bermanfaat untuk mendukung penelitian tentang perceraian dan opini hukum khususnya di Pulau Kangean dan Indonesia pada umumnya Kebaruan: Kebaruan dari penelitian ini adalah masih sedikitnya orang yang melakukan penelitian di Kepulauan Kangean, serta ditemukannya beberapa konsep penalaran hukum bagi hakim di Pengadilan Agama Kangean.
Density depletion and Hall effect in magnetic reconnection

Density depletions were detected by Wind, Cluster, and Polar spacecrafts in the observations of diffusion region encounters at the Earth's magnetotail and magnetopause. In this report we investigate the layers of density depletion in magnetic reconnection using a 2.5-dimensional Hall MHD code developed from a multistep implicit scheme. The numerical results at the quasi-steady state of the Hall MHD reconnection with d(i)/L-c >= 1.0, where d(i) is the ion inertial length and L-c is the half thickness of the initial current sheet, show not only the density depletions along the magnetic separatrices but also a density dip in the x direction near the X neutral line. The comparative tests with various Hall terms demonstrate that the density depletion in the magnetic reconnection is a peculiar feature of the case with a strong Hall effect (d(i)/L-c >= 1.0). The layers of low density following the shape of separatrices are in coincidence with the regions of high magnetic pressure. In the spatial profile of density rho along z, which is in quantitative agreement with Cluster observation, the obvious dips located at the separatrices coincide with the peak and valley in the profile of K-H/rho (J x B)(z) for the case with d(i)/L-c = 2.0. It indicates the major role of the Hall term in the formation of the density depletion layers near the separatrices. On the basis of the comparison between Wind observation and simulation results, we argue that the density dip observed by Wind would be distributed around the reconnection X-line, rather than along the magnetic separatrix. In the case with a strong Hall effect, the in-plane ion flows go around the diffusion region, and enterable ions in this region are significantly reduced due to the action of the in-plane Lorentz force. A density dip in the vicinity of the X-line is attributed to the hard entry of in-plane ion flow and might be related to an increase of the ion drift velocity in the y direction.
Liver Organoids as an In Vitro Model to Study Primary Liver Cancer

Primary liver cancers (PLC), including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are among the leading causes of cancer-related mortality worldwide. Bi-dimensional in vitro models are unable to recapitulate the key features of PLC; consequently, recent advancements in three-dimensional in vitro systems, such as organoids, opened up new avenues for the development of innovative models for studying tumour’s pathological mechanisms. Liver organoids show self-assembly and self-renewal capabilities, retaining essential aspects of their respective in vivo tissue and allowing modelling diseases and personalized treatment development. In this review, we will discuss the current advances in the field of liver organoids focusing on existing development protocols and possible applications in regenerative medicine and drug discovery.
Promising Application of Automated Liquid Culture System and Arbuscular Mycorrhizal Fungi for Large-Scale Micropropagation of Red Dragon Fruit

Red dragon fruit (Hylocereus polyrhizus) is an economic and promising fruit crop in arid and semi-arid regions with water shortage. An automated liquid culture system using bioreactors is a potential tool for micropropagation and large-scale production. In this study, axillary cladode multiplication of H. polyrhizus was assessed using cladode tips and cladode segments in gelled culture versus continuous immersion air-lift bioreactors (with or without a net). Axillary multiplication using cladode segments (6.4 cladodes per explant) was more effective than cladode tip explants (4.5 cladodes per explant) in gelled culture. Compared with gelled culture, continuous immersion bioreactors provided high axillary cladode multiplication (45.9 cladodes per explant) with a higher biomass and length of axillary cladodes. Inoculation of H. polyrhizus micropropagated plantlets with arbuscular mycorrhizal fungi (Gigaspora margarita and Gigaspora albida) significantly increased the vegetative growth during acclimatization. These findings will improve the large-scale propagation of dragon fruit.
A kitchen experiment for replicating lava-ice interaction on stratovolcanoes

Many Quaternary stratovolcanoes host (or hosted) glacial ice with volumes that have fluctuated in response to long-term global climate cycles. The repeated advance and retreat of ice in valleys on the flanks of volcanoes throughout their eruptive histories has impacted how and where lava flows are emplaced and preserved. Understanding the dynamics of lava-ice interaction is a vital part of reconstructing the growth histories of many stratovolcanoes and can provide valuable clues about the evolution of Earth’s climate. We have constructed a basic experiment, using common kitchen ingredients and utensils, to replicate the interaction between lava flows and glaciers on stratovolcanoes. This article outlines the ingredients and recipes for soda bread (stratovolcano analogy), ice cream (glacier analogies), and sauce (lava flow analogies), and describes exercises that provide qualitative lessons about the morphology of volcanoes, natural hazards, and paleoclimate. As such, the experiment can be used in geoscience outreach demonstrations for students and will assist non-specialist scientists with undertaking field identification of ice-bounded lava flows.
How long can Chinese women work after retirement based on health level: Evidence from the CHARLS

Objective To further enhance the understanding of factors impacting female participation in the workforce based on health levels and to measure the excess work capacity of middle-aged and older female groups by residence and educational level. Methods Data of women aged 45–74 were accessed from the China Health and Retirement Longitudinal Study (CHARLS) from 2011, 2013, 2015, to 2018. The health status of women was comprehensively evaluated by single health variables and frailty index. A Probit model was used to measure the excess working capacity of women by region (rural/urban) and educational level, taking all women aged 45–49, rural women aged 45–49, and rural (illiterate) women in all age groups as the benchmark, respectively. Results The excess capacity of all Chinese women aged 50–64 is 1.9 years, and that of women aged 50–74 is 5.1 years. The excess work capacity of women in urban and rural areas and with different educational levels is heterogeneous. The excess working capacity of urban women aged 50–64 is 6.1–7.8 years, and that of urban women aged 50–74 is 9.8–14.9 years. The excess working capacity of urban women aged 50–64 is about 6 times that of rural women. The excess work capacity of highly educated women was 3 times higher than that of illiterate women. Conclusion The potential work capacity of Chinese women remains to be exploited, especially for urban and highly educated middle-aged and older women with better conditions of health, whose potential is more significant. A rational retirement policy for women and the progressive implementation of an equal retirement age for men and women will contribute to further advancement of gender equality and healthy aging in the workplace in China.
A biosemiotics perspective on dogs’ interaction with interfaces

Understanding how animals might make sense of the interfaces they interact with is important to inform the design of animal-centered interactions. In this regard, biosemiotics provides a useful lens through which to examine animals’ interactions with interfaces and the sensemaking mechanisms that might underpin such interactions. This paper leverages Uexküll’s Umwelt theory, Peirce’s logic of sign relations and Gibson’s theory of affordances to analyze examples of dogs’ interactions with interfaces, particularly the role of the semiotic mechanisms of indexicality and isomorphism. Based on these analyses, the paper derives design implications, and proposes a semiotic framework to support the analysis and design of canine-centered interactions. The framework could be subsequently extended to support the analysis and design of interactive systems for other species.
Comparative study of several distortion measures for speech recognition

In this study we compared several different spectral distortion measures including the Itakura-Saito (IS), the log likelihood ratio (LLR), the likelihood ratio (LR), the cepstral (CEP), and two perceptually based distortion measures, the weighted likelihood ratio (WLR) and the weighted slope metric (WSM) distortion measures, in terms of their effects on the performance of a standard dynamic time warping (DTW) based, isolated word, speech recognizer. Two modifications of the basic forms of each measure were also investigated, namely a Bark-scale frequency warping and the incorporation of suprasegmental energy information. All distortion measures and their modifications were tested on an alpha-digit vocabulary, 4-talker, telephone recording data base. The results can be summarized as: (1) All LPC-based distortion measures performed reasonably well. The LLR and WSM distortion measures gave the highest recognition accuracy, while the IS distortion measure gave the lowest score; (2) Whereas the addition of suprasegmental energy information helped the recognition performance, the use of gain and absolute loudness degraded the performance; (3) Bark-scale frequency warping did not perform as well as its unwarped counterpart; (4) The WLR distortion measure did not perform as well as its unweighted counterpart.
Non-Intrusive Privacy-Preserving Approach for Presence Monitoring Based on WiFi Probe Requests

Monitoring the presence and movements of individuals or crowds in a given area can provide valuable insight into actual behavior patterns and hidden trends. Therefore, it is crucial in areas such as public safety, transportation, urban planning, disaster and crisis management, and mass events organization, both for the adoption of appropriate policies and measures and for the development of advanced services and applications. In this paper, we propose a non-intrusive privacy-preserving detection of people’s presence and movement patterns by tracking their carried WiFi-enabled personal devices, using the network management messages transmitted by these devices for their association with the available networks. However, due to privacy regulations, various randomization schemes have been implemented in network management messages to prevent easy discrimination between devices based on their addresses, sequence numbers of messages, data fields, and the amount of data contained in the messages. To this end, we proposed a novel de-randomization method that detects individual devices by grouping similar network management messages and corresponding radio channel characteristics using a novel clustering and matching procedure. The proposed method was first calibrated using a labeled publicly available dataset, which was validated by measurements in a controlled rural and a semi-controlled indoor environment, and finally tested in terms of scalability and accuracy in an uncontrolled crowded urban environment. The results show that the proposed de-randomization method is able to correctly detect more than 96% of the devices from the rural and indoor datasets when validated separately for each device. When the devices are grouped, the accuracy of the method decreases but is still above 70% for rural environments and 80% for indoor environments. The final verification of the non-intrusive, low-cost solution for analyzing the presence and movement patterns of people, which also provides information on clustered data that can be used to analyze the movements of individuals, in an urban environment confirmed the accuracy, scalability and robustness of the method. However, it also revealed some drawbacks in terms of exponential computational complexity and determination and fine-tuning of method parameters, which require further optimization and automation.
Evaluation of physical hardening and oxidative aging effects on Delta Tc of asphalt binders

The Delta $ {T_c} $ Tc ( $ \mathrm{\Delta }{T_c} $ ΔTc) is a rheological parameter for asphalt binders, which has been adopted in the past years by many highway agencies in North America for asphalt binder selection. In this study, the effects of the low-temperature physical hardening and oxidative aging on $ \mathrm{\Delta }{T_c} $ ΔTc are experimentally investigated and analysed. The experimental study is performed on both plain and polymer-modified binders. The results show that both physical hardening and oxidative aging have strong effects on decreasing $ \mathrm{\Delta }{T_c} $ ΔTc. An approximate linear relationship is identified between $ \mathrm{\Delta }{T_c} $ ΔTc and rheological parameters, such as the creep stiffness (S) and the m-value. The linear relationship is theoretically explained by analytical derivation. Based on the linear relationship, a graphical method is proposed for interpreting $ \mathrm{\Delta }{T_c} $ ΔTc using the log(S)-m diagram. By this method, it is found that polymer modification increases the susceptibility of $ \mathrm{\Delta }{T_c} $ ΔTc to oxidative aging, while it does not significantly affect the susceptibility of $ \mathrm{\Delta }{T_c} $ ΔTc to physical hardening.
Smart digital platforms for carbon neutral management and services: Business models based on ITU standards for green digital transformation

This brief research report focuses on the effects of artificial intelligence (AI) on the environment, by analyzing the latest documents issued by major standard organizations such as the International Telecommunication Union (ITU) and the Internet Society of China (ISC). By outlining the latest developments into a platform canvas for carbon neutrality management and services, this report identifies the potential of “AI of the environment” (i.e., the material composition and environmental impact of AI itself) and “AI for the environment” (i.e., the purposeful use of smart applications to benefit the environment). The role of AI is contextualized in the digital platform design for the provision of services on carbon emission data, which serves as the material foundation for smart services facing both the producers and the consumers of such information. Contributing to the design of business models that enable open innovations, this report discusses the emission impact reduction mechanisms that can optimize, substitute, induce, manage, and facilitate processes and services, indicating the potential of AI-enabled smart services such as forecasting, planning, and recommendation systems. Despite the limited disciplinary considerations and detailed discussions on specific AI technologies, this report provides a simple, practical, and flexible technology roadmap that can be used as a guide for researchers and practitioners to refine their operations and designs and to follow best practices. This report succinctly visualizes key elements of digital platforms of/for GHG emission reduction and their enabling mechanisms, serving as an AI technology roadmap for future research and innovation in the field.