Miracle-dz/UniFAR-FTUs huggingface dataset:
Sustainable Ageing: Supporting Healthy Ageing and Independence Amongst Older Turkish Migrants in the UK

In the UK, as in many other European countries, the population is growing older, and older adults are becoming more diverse. As a result, there is a mounting interest in supporting healthy ageing and independence, acknowledging the needs and agency of older adults from diverse backgrounds, expectations, and life trajectories. Healthy ageing is promoted as a critical component of sustainable ageing to ensure meaningful social and economic contributions through the life course for all individuals. However, the definitions of healthy ageing are debatable. The public and policy discourse treat all older adults through generic and homogeneous models that do not consider the heterogeneity of experiences and perspectives of old age among different groups. In this context, independence has often been defined in terms of functional independence, i.e., cognitive and physical functioning, as a core construct of healthy ageing. However, this focus excludes older adults’ interpretations and day-to-day experiences of this concept. This article investigates the interpretation and lived experience of independence amongst older Turkish adults in the UK as a central explanatory concept of healthy ageing. Semi-structured individual interviews (n = 48) and community mapping workshops (n = 5) were conducted with 65 older Turkish adults in London, supplemented by interviews with professional service providers (n = 13) within the community. The data collection was conducted between March and November 2017. We identified three main themes integral to understanding healthy ageing and independence: 1—interdependency and having reciprocal care relations; 2—individual autonomy at home and choice in housing options; and 3—functional independence, mobility, and control over the physical environment. Independence appears to remain an essential element of healthy ageing. However, it is a fluid and complex construct constantly negotiated around personal and community resources. Therefore, there is a need to develop more comprehensive interventions that capture the diverse experiences in old age to enable healthy ageing and social sustainability. These are timely considering current policy directions such as the UN Decade of Healthy Ageing and the 2030 Sustainable Development Goals.
Decoupled Representation Learning for Attributed Networks

Network representation learning or network embedding, which targets at learning the low-dimension representation of graph-based data, has attracted wide attention due to its effectiveness on various network-oriented applications in recent years. Though large efforts have been made on the joint analysis combining node attributes with the network structure, they usually model the interactions between nodes reflected by network structure and attributes in a coupled way and fail to address the common sparse attribute issues. To this end, in this article, we comprehensively study the problem of learning attributed network embedding, which focuses on characterizing different types of interactions among nodes and alleviating the sparse attribute problem as well. Specifically, we propose a novel DeCoupled Network Embedding (DCNE) model to learn node representations in a unified framework. We first respectively project both nodes and attributes into a low-dimensional vectorial space. Then, we introduce a novel “decoupled-fusion” learning process into each graph layer to iteratively generate node embeddings. In particular, we propose two adapted graph convolution modules to decouple the learning of network structure and attributes respectively, and a fusion module to adaptively aggregate the information. Next, we adopt a modified mini-batch algorithm to iteratively aggregate the higher-order information of both nodes and attributes within a multi-task learning framework. Extensive experiments on five public datasets demonstrate that DCNE could outperform state-of-the-art methods on multiple benchmark tasks. Moreover, several qualitative analyses further indicate DCNE can learn more robust and representative node embeddings than other comparison methods for attributed networks.
Metal–Insulator Transition in Doped Barium Plumbates

Solid solutions in the Ba(Pb1−xSrx)O3−z system were prepared by aliovalent substitution of Pb4+ by Sr2+ ions to investigate the effect of cation stoichiometry on thermal and electrical properties as x was varied between 0 and 0.4, in the temperature range 300–523 K. The starting compound, barium plumbate (BaPbO3), has a perovskite structure and is known to exhibit metallic conductivity due to an overlap of the O2p nonbonding and the Pb–O spσ antibonding band, which is partially filled by the available electrons. The large difference in the ionic radii between the Pb4+ and Sr2+ ions introduces significant strain into the (Pb/Sr)O6 octahedra of the perovskite structure. Additionally, charged defects are created on account of the different oxidation states of the Pb4+ and Sr2+ ions. Evidence of a metal to insulator transition (MIT) of the Mott–Hubbard type has been observed at a critical concentration of Sr2+ ions.
3D-DCDAE: Unsupervised Music Latent Representations Learning Method Based on a Deep 3D Convolutional Denoising Autoencoder for Music Genre Classification

With unlabeled music data widely available, it is necessary to build an unsupervised latent music representation extractor to improve the performance of classification models. This paper proposes an unsupervised latent music representation learning method based on a deep 3D convolutional denoising autoencoder (3D-DCDAE) for music genre classification, which aims to learn common representations from a large amount of unlabeled data to improve the performance of music genre classification. Specifically, unlabeled MIDI files are applied to 3D-DCDAE to extract latent representations by denoising and reconstructing input data. Next, a decoder is utilized to assist the 3D-DCDAE in training. After 3D-DCDAE training, the decoder is replaced by a multilayer perceptron (MLP) classifier for music genre classification. Through the unsupervised latent representations learning method, unlabeled data can be applied to classification tasks so that the problem of limiting classification performance due to insufficient labeled data can be solved. In addition, the unsupervised 3D-DCDAE can consider the musicological structure to expand the understanding of the music field and improve performance in music genre classification. In the experiments, which utilized the Lakh MIDI dataset, a large amount of unlabeled data was utilized to train the 3D-DCDAE, obtaining a denoising and reconstruction accuracy of approximately 98%. A small amount of labeled data was utilized for training a classification model consisting of the trained 3D-DCDAE and the MLP classifier, which achieved a classification accuracy of approximately 88%. The experimental results show that the model achieves state-of-the-art performance and significantly outperforms other methods for music genre classification with only a small amount of labeled data.
Stability constants and thermodynamic behaviour of the complex formation of two crown ethers with zinc (II) and copper (II) ions in water + acetonitrile mixed solvent: a conductivity measurement study

ABSTRACT We have investigated the behaviour of change of molar conductivity of mixtures of two crown ethers (CE) (18-Crown-6; 18C6 and 24-Crown-8; 24C8) and metal ions (Mn+) (Zn2+ and Cu2+) and the complexation between CE and Mn+ in water + acetonitrile binary solvent system (20, 40, 60 and 80%; v/v) at 298.15 K to 328.15 K by conductometric technique. K f values for all complexes were found to be decreased with enhancement of temperature. Complexes associated with Zn2+ exhibit a trend of K f: 24C8 + Zn2+ > 18C6 + Zn2+ in 20% solvent composition (water-acetonitrile) and order of 18C6 + Zn2+ > 24C8 + Zn2+ was found for 80% solvent composition. However, logarithm values of K f for the Cu2+ complexes were found to obey the order of 24C8 > 18C6 almost for all compositions except with a few exceptions. was found to be negative indicating spontaneous complexation between CE and Mn+.
Rough approximation‐based inventory optimization with random prices for B2C companies during the promotion period

Most B2C e‐commerce giants such as Amazon, Bestbuy, Alibaba, periodically or occasionally conduct promotional activities that put significant stress on their inventory systems. The sharp demand and price fluctuations caused by these promotional activities distress stocks over an inventory period if customer satisfaction is maintained. This article develops a chance‐constrained multiobjective programming model to obtain optimal order quantities in an e‐commerce inventory system with stochastic demand and prices. Traditional techniques for coping with the stochastic coefficients using an expected value operator or probability measures are usually inefficient in estimating quantities. With rational assumptions regarding market behavior, stochastic demand and price are characterized with a normal distribution based on historical data. A novel method called rough approximation is designed to flexibly formulate the feasible region, from which a crisp model is obtained that has no uncertain information. A proxy ideal point‐based genetic algorithm (PIP‐GA) is then developed to solve the model, allowing decision makers to fix the optimal order quantities for different promotional activity scales. Finally, the results are illustrated using a practical example from the Chinese B2C e‐commerce giant “JD.COM. ” Some special features are discussed to show the availability of the proposed model and the solution methodology.
SafePath: Exploiting Ubiquitous Smartphones to Avoid Vehicle–Pedestrian Collision

Every year, over 4700 traffic fatalities and 75000 crash injuries involve pedestrians in the United States. Effective solutions are urgently needed to prevent vehicle–pedestrian collision accidents. Many driving assistance systems are proposed to address this problem; however, they require additional infrastructures that may result in higher costs and be difficult to deploy on a large scale. In this article, we propose SafePath, which uses the ubiquitous smartphones to avoid vehicle–pedestrian collision. Specifically, SafePath utilizes the smartphones to broadcast the redesigned service set identifier (SSID) messages containing users’ information (e.g., location, direction, etc.) and scan the surroundings via wireless communications. Considering the limited communication range and the possible interference, and obstruction of obstacles, we propose a collaborative mechanism to enhance the transmission capability, hence predicting the collisions in advance effectively. We also design a risk evaluation scheme to calculate the probability of accidents and inform users to take actions against accidents at different levels. We implement SafePath on the Android platform and conduct extensive real-road experiments to evaluate the system performance. The experimental results demonstrate that SafePath can provide twice the transmission range compared with other collision-avoiding systems. Moreover, it also can significantly reduce the probability of vehicle–pedestrian collisions by up to 81.4%, with respect to other compared collision-avoiding systems in our real-road test.
Effects of the application of biochar on soil fertility status, and nutrition and yield of onion grown in a no-tillage system

ABSTRACT The study was aimed to evaluate the effect of successive applications of increasing biochar rates along with other mineral fertilizers and poultry manure on onion nutrition and yield. The experiment consisted of 2 (agricultural year) × 11 (treatments) factorial combinations over two cropping years (2017 and 2018). Thus, 11 treatments were tested as follows: C = control; MF = mineral fertilizer; PM = poultry manure; B1+ MF = 1 Mg ha−1 of biochar+MF; B1+ PM = 1 Mg ha−1 of biochar+PM; B2+ MF = 2 Mg ha−1 of biochar+MF; B2+ PM = 2 Mg ha−1 of biochar+PM; B4+ MF = 4 Mg ha−1 of biochar+MF; B4+ PM = 4 Mg ha−1 of biochar+PM; B10+ MF = 10 Mg ha−1 of biochar+MF; B10+ PM = 10 Mg ha−1 of biochar+PM. The highest onion yield (39.9 Mg ha−1) was obtained in 2017 with the biochar rate of 5.9 Mg ha−1 while an increase of 308 kg ha−1 in onion yield was found for each Mg ha−1 of biochar added to soil in 2018. The use of biochar combined with mineral fertilizers increased onion yield; and the use of biochar combined with poultry manure improved soil fertility status.
Corridors in heavily fragmented landscapes: reconnecting populations of critically endangered brown spider monkeys (Ateles hybridus) and sympatric terrestrial vertebrates in the lowland rainforests of Central Colombia

In tropical ecosystems, habitat degradation and fragmentation are some of the most important drivers of biodiversity loss. In Colombia, the Magdalena River basin is home to a megadiverse wildlife community, which has been historically exposed to pervasive habitat loss and fragmentation. Within a long‐term project on the conservation of critically endangered brown spider monkeys (Ateles hybridus), we signed conservation agreements with local landowners to protect the remaining forests and reconnect them through restoration corridors. We established 10 corridors within a matrix of pastures used for cattle‐ranching which reconnect approximately 1,000 ha of forests. We planted trees in 2016/2017 and 2020, established 24 vegetation plots (10 × 10 m) to measure their structure and composition, and compared them with six vegetation plots (50 × 2 m) in forest fragments. We installed camera traps to evaluate the effectiveness of corridors as potential pathways for terrestrial vertebrates in a fragmented landscape. Overall, forest structure differed between young corridors (1 year) and both older corridors (5 years) and forests; older corridors had no structural differences with forest fragments. Throughout this preliminary survey, 21 out of 32 species of vertebrates that have been recorded in forests used the corridors, including apex predators and other large birds and mammals. This study provides initial data supporting the use of corridors as a strategy to reconnect wildlife in isolated forest fragments in heavily fragmented landscapes, as well as the establishment of effective corridors that reconnect forest‐dwelling species in relatively short periods of time (<5 years).
The Metallogeny of the Tieling Cu-Mo Porphyry Deposit in Eastern Tianshan, NW China: New Insights from Zircon U-Pb, Fluid Inclusion, and H-O-S Stable Isotope Analyses

The eastern Tianshan metallogenic belt is an important molybdenum resource base in Xinjiang and is characterized by large-scale porphyry Mo deposits formed during the Triassic. The Tieling Cu-Mo porphyry deposit, which is situated in the western part of the eastern Tianshan metallogenic belt, was recently recognized as being related to Carboniferous granite porphyry. Three stages of hydrothermal mineralization were identified, including quartz+K-feldspar+pyrite±molybdenite±magnetite (stage I), quartz+molybdenite+pyrite+chalcopyrite (stage II), and quartz+pyrite±molybdenite±epidote (stage III). Fluid inclusion petrography and microthermometry analyses indicate the presence of gas-liquid inclusions with a H2O-NaCl composition. The ore-forming fluids have a characteristic temperature ranging from 157 to 262°C under stage II and 135 to 173°C under stage III, which correspond to salinities of 7.2-17.2 wt% NaCl equiv. and 5.9 to 9.6 wt% NaCl equiv. , respectively. The hydrogen and oxygen isotope data indicate that the ore-forming fluids of the Tieling deposit were originally derived from magmatic hydrothermal fluids and then mixed with meteoric water. The sulfur isotope compositions indicate that the ore-forming materials were mainly derived from the Late Carboniferous felsic magma. Furthermore, zircon U-Pb analysis of ore-bearing granite porphyry yields a concordant age of 298.4 ± 0.7 Ma , indicating that the Tieling Cu-Mo deposit formed during the Late Carboniferous and differed from that processed under pre-Early Carboniferous and Triassic mineralization in the eastern Tianshan metallogenic belt. These results also indicate that the Tieling porphyry deposit was formed in the transition condition between subduction-related accretion and postcollisional orogeny, and it should be given more attention in prospect evaluations.
Road geometry estimation using vehicle trails: a linear mixed model approach

Abstract In this paper, we propose an estimation algorithm for the shape of the road using trails of leading vehicles via a linear mixed model (LMM) approach. A vehicle trail is essentially the motion trajectory of a vehicle where samples of the historical path are longitudinally collected from the same vehicle at different points in time. Such measurements can be obtained from the fusion system for single or multiple sensor tracking. The aim is to use trails of leading vehicles to depict the road geometry in highway scenarios. The proposed estimation method uses a polynomial-based road model and is built from a LMM, which is one of the most widely used statistical techniques. To avoid the overload of memory usage from trail samples, trail data are first processed by the newly developed compression and chopping mechanisms before being imported into the LMM framework. Moreover, the profile likelihood function is used to alleviate the computational burden and reduce the number of iterations in the Newton-Raphson algorithm in the LMM. Finally, the proposed method is then evaluated by two publicly available next generation simulation (NGSIM) datasets. The large-scale simulation results show that the road shape estimated by the proposed method has the root mean square error (RMSE) less than 0.5 meters in average for all ranges compared with the ground truth road shape. This suggests that our method provides an accurate road shape estimation and captures the shape of the road successfully.
Medical students and stimulants; they have enough knowledge but they still use non prescribed stimulants

ABSTRACT Introduction Medical university students are more likely to use non-prescribed stimulants, due to the claim that some of these drugs may improve learning abilities and concentration. Side effects of non-prescribed stimulants in healthy young adults are not so far widely studied. The present cross-sectional survey demonstrates the prevalence of stimulants misuse and the characteristics of non-prescribed users among Iranian medical students. Materials and Methods Healthy medical students were asked to fill a validated researcher-administered questionnaire about their previous stimulant use. Both online and printed versions of the questionnaire were available for the students. Results Among 301 medical students, 157 students (52.2%) reported misusing stimulant agents. The most common stimulant was methylphenidate, with a prevalence of 46.5%. Compared to non-users, stimulant users were more likely to smoke (p < .05). Among the non-prescribed users, 31.8% reported being tempted to reuse stimulants, 89.8% were aware of the complications of stimulants before use, and 54.1% reported recommending the stimulants to others. Conclusion The findings of the present emphasize the necessity of focusing on psychoeducational programs for medical students, alongside increasing awareness about possible side effects of stimulants.
IDENTIFICATION OF POSSIBLE MOLECULAR TARGETS OF POTENTIAL ANTI-PARKINSON DRUGS BY PREDICTING THEIR BINDING AFFINITIES USING MOLECULAR DOCKING TECHNIQUE

Objective: Mechanistic study of newly reported anti-Parkinson agents by molecular docking to predict possible target.Methods: Structures of newer drugs known anti-Parkinson agents were drawn using ChemBioDraw 2D software. Thereafter, they were converted to 3D structures using ChemBioDraw 3D software in which they were subjected to energy minimization using the MM2 method and then saved as PDB extension files, which can be accessed using the AutoDock Vina (ADT) interface. ADT 1.5. 6 software version was used for molecular docking study.Results: Various molecular targets were selected (D2/D3, D2, A2A, and MAO-B) and studied for Pardoprunox, Istradefylline, Rasagiline, and Bromocriptine. Pardoprunox, Istradefylline, and Bromocriptine had more affinity with their corresponding receptor with −6.9, −8.5, and −9.4 kcal/mol binding affinity, respectively, except Rasagiline, who has less affinity with its corresponding receptor (−6.4kcal/mol) and shown better affinity with 3pbl receptor (−6.7 kcal/mol). Conclusion: Pardoprunox, Istradefylline, and Bromocriptine were found to act on D2/D3 (3pbl), A2A (3pwh), and D2 (4yyw), respectively, whereas Rasagiline found to be act on D2/D3 (3pbl) receptor. The results help in prediction of mechanism and interaction to various Parkinson’s disease targets.
Parents' trust in food safety and healthiness of children's diets: A TPB model explaining the role of retailers and government

This study started from the assumption that children's healthy diets are primarily determined by their parents and their intentions towards serving fruit and vegetables. Although it is widely known that a significant share in fruits and vegetables in children's diets has several advantages, there are some safety issues that can act as barriers in promoting fruit and vegetable consumption.Therefore, we investigated parents' determinants in giving fruits and vegetables to their children taking into account that the trust in actors who minimize the presence of risks could be instrumental to understand the whole story. Due to the incidence of childhood obesity, Southern Italy is a suitable case study. An extended Theory of Planned Behavior (tpb) model including trust towards government and retailers has been set up.Results suggested that parental intention to give to their children fruits and vegetables in primarily determined by their perceived behavioral control, then by their attitude and by subjective norm.Trust has been proved to influence parents' intentions, but only related to retailers and not to government. Furthermore, the model positively explained childrens' behavior reported by parents.
The Effect of a Men’s Initiation Weekend on Authenticity, Assertiveness, and Forgiveness: A Pilot Study

American men experience worse outcomes on a wide range of health and well-being variables compared to women, including disease, educational problems, violence, addiction, suicide, unemployment, and life expectancy. Because of this, organizations have created programs that focus on helping men both psychologically and spiritually; however, it is important to assess the effectiveness of these programs. The Crucible Project, founded in 2002, attempts to facilitate the development of integrity, courage, and grace in men using a weekend retreat format. The purpose of this pilot study was to explore the effect of the weekend retreat on participants’ authenticity, assertiveness, and willingness to forgive (i.e. empirical constructs analogous to integrity, courage, and grace, respectively). Participants (N = 22) completed measures before the weekend retreat (Time 1), immediately after the weekend retreat (Time 2), and at a 1-month follow-up (Time 3). Results indicate that weekend retreat participants demonstrated a significant increase in scores on measures of authenticity and willingness to forgive and a trend toward increased scores on the measure of assertiveness over time. We conclude by discussing limitations of the study, areas for future research, and implications for spiritual and character development.