Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Conversational AI in Ageing and Dementia Care at Home: A Participatory Study

Conversational artificial intelligence (AI) technologies hold significant promise to support the independence, well-being and safety of older adults living with frailty or dementia at home. However, further studies are needed to identify: 1) valuable scenarios of support, 2) desired interactive features, and 3) key challenges preventing long-term adoption and utility in dementia care. In this paper, we explore the role of conversational technology in ageing and dementia care at home. Using a community-based participatory approach, we engaged 20 stakeholders, including people with lived experience of dementia and frailty, to understand preferences, perceived benefits and concerns about integrating conversational AI into daily routines at home. We uncovered key roles of the technology, including support of daily functions, health monitoring, risk mitigation, and cognitive stimulation. We emphasize the need for adapting interactions to different levels of user familiarity and progression of cognitive decline. We address the importance of the communication style and suggest careful use of open-ended questions with target populations. We further discuss feasibility considerations to overcome current barriers to adoption. Overall, this work proposes design guidelines to shape the future conceptualization and development of natural language interactions to support dementia care at home
Implementasi Load Cell Pada Robot Humanoid Terhadap Parameter Jalan Robot

Ilmu pengetahuan dan teknologi yang digunakan untuk mengembangkan ide yaitu dari ilmu elektronika khususnya bidang ilmu robotika. Jenis robot berdasarkan alat geraknya dibagi menjadi dua, yaitu robot berkaki (humanoid) dan beroda. Akan tetapi, ada satu masalah mengenai perancangan robot berkaki (humanoid) pada saat berjalan yaitu bagaimana cara menentukan kesesimbangan pada robot agar robot tetap seimbang pada saat robot berjalan. Dengan adanya sensor Load Cell diharapkan robot dapat mengetahui tekanan pada kaki robot. Jika robot dapat mengetahui tekanan pada kaki robot maka robot dapat berjalan dengan seimbang dengan cara mengatur Pitch pada parameter jalan robot. Nilai pada pembacaan tekanan pada Load Cell akan dijadikan masukan pada proses error kontrol PID. Hasil koreksi dari kontroller PID akan diteruskan menuju keluaran Pitch parameter jalan robot humanoid sehingga diharapkan akan menghasilkan nilai yang semakin akurat
A Vertical Axis Water Turbine for Extracting Energy from Rivers and Tidal Currents

Application of the Darrieus turbine to the extraction of kinetic energy from slow-moving water currents is proposed. A specific design for river application in developing countries is suggested which is amenable to local manufacture. Although full performance and cost data are not yet established, small-scale irrigation using machines of roughly 6m diameter are thought likely to be economically viable.
Peningkatan Motivasi Belajar Bahasa Indonesia dengan Metode Tanya Jawab Berantai

AbstractIndonesian This study aims to explain the increase in students' learning motivation including students' independence in learning and student attitudes as well as increasing student achievement scores in learning Indonesian. The method used in this research is research method used in this research is classroom action research. The subjects of this study were students of class XI Social Sciences 3 SMA Negeri 1 Krencong, Jember Regency, with a total of 32 students, odd semester, 2016/2017 academic year. Meanwhile, when the research was conducted from September to December 2016. The research instruments used were questionnaires, documentation, and field notes. The data analysis technique used is a qualitative descriptive technique on the results of the questionnaire. Instruments to collect data in this study were in the form of questionnaires, documents (values), and field notes. The results of the study indicate that the question and answer method in Indonesian language learning can increase learning motivation and is effective in improving student achievement. This can be seen from the increase in motivation from the aspect of independence in learning and student attitudes towards Indonesian language lessons at the pre-action stage, cycle I, and cycle II as well as student scores that have reached 87.50% in cycle II.AbstrakPenelitian ini bertujuan untuk menjelaskan peningkatan motivasi belajar siswa meliputi kemandirian belajar siswa dan sikap siswa serta peningkatan nilai prestasi siswa dalam belajar bahasa Indonesia. Metode yang digunakan dalam penelitian ini adalah Metode penelitian yang digunakan dalam penelitian ini adalah penelitian tindakan kelas. Subjek penelitian ini adalah siswa kelas XI IPS 3 SMA Negeri 1 Krencong, Kabupaten Jember, dengan jumlah 32 siswa, semester ganjil, tahun pelajaran 2016/2017. Sedangkan waktu penelitian dilakukan pada bulan September sampai dengan Desember 2016. Instrumen penelitian yang digunakan berupa kuesioner, dokumentasi, dan catatan lapangan. Teknik analisis data yang digunakan adalah teknik deskriptif kualitatif terhadap hasil kuesioner. Instrumen untuk menjaring data dalam penelitian ini berupa kuesioner, dokumen (nilai), serta catatan lapangan. Hasil dari penelitian menunjukkan bahwa metode tanya jawab berantai pada pembelajaran bahasa Indonesia dapat meningkatkan motivasi belajar dan efektif dalam meningkatkan prestasi siswa. Hal tersebut dapat dilihat dari peningkatan motivasi dari aspek kemandirian dalam belajar dan sikap siswa terhadap pelajaran bahasa Indonesia pada tahap pratindakan, siklus I, dan siklus II serta nilai siswa yang sudah mencapai 87,50% pada siklus II.
Physicochemical Impacts on Bacterial Communities in Putrajaya Lake, Malaysia

This study determines the associations between the bacterial communities and water physicochemical parameters in Putrajaya Lake and Putrajaya Wetlands Park, Malaysia. Bacterial communities were assessed by metagenomics of the 16S rRNA gene from lake water input, central wetlands, and primary lake area. Water samples (n=18) were collected during two different periods: post-high rainfall events (samples collected in May) and dry periods (July). The data revealed that bacterial communities of the three sites were taxonomically distinct and associated with different environmental parameters. However, no significant differences were found between the wet and dry periods. Alpha diversity analyses revealed the highest index in May 2018 in the constructed wetlands (H’= 5.397) than those from water input or primary lake (p<0.05). Overall, 49 phyla, 147 classes, 284 orders, 471 families, 778 genera and 62 species of bacteria were identified. Verrumicrobia and Firmicutes showed a strong positive correlation with ammonia-nitrogen (r = 0.709). Actinobacteria and Cyanobacteria had a moderate positive correlation with nitrate with r value (r = 0.673) and (r = 0.647), respectively. In this study, the metagenomics of the 16S rRNA gene amplicon by Illumina MiSeq has successfully identified the bacterial community assemblage in Putrajaya Lake and wetlands. Bacterial composition was associated with the availability of physicochemical properties of specific sites. The effectiveness of the engineered wetlands of Putrajaya in bioremediation was demonstrated by the marked decrease in certain nutrient concentrations from lake water input to the primary lake area.
Distribuição de Aglomerados Subnormais na Rede Urbana e nas Grandes Regiões Brasileiras

A precariedade urbana e habitacional e heterogenea no Brasil, o que torna necessario fazer analises territoriais. Este trabalho analisa dados do Censo Demografico 2010 relativos aos aglomerados subnormais (AS), buscando identificar comportamentos diferenciados nos municipios segundo uma rede urbana e sua insercao regional. Escolheu-se como classificacao dos municipios brasileiros em rede urbana o estudo Regioes de Influencia das Cidades 2007 (IBGE, 2008), ou REGIC, tendo sido encontradas quatro grandes tendencias. Primeiramente, o fenomeno dos aglomerados subnormais deixou de ser tao predominantemente metropolitano como antes. Uma segunda tendencia refere-se a intensificacao da presenca de AS nos municipios mais perifericos em areas de abrangencia de metropoles. Uma terceira tendencia e a “interiorizacao” dos AS, mais acentuada no Norte assim como a intensificacao da presenca de AS em municipios litorâneos do Sudeste e do Nordeste. Uma quarta tendencia e a ocorrencia expressiva de AS em diversos niveis de uma mesma rede de influencia de metropole. A identificacao destas tendencias, ao mesmo tempo que adiciona complexidade a analise da precariedade urbana e habitacional, serve como insumo a busca da promocao do desenvolvimento urbano com igualdade regional e espacial. Deficiencies of housing and urban infrastructures are heterogeneous in Brazil, making territorial analyses necessary. In this article we analyze data of the 2010 Census regarding “aglomerados subnormais” (AS), a national classification of census tracts that generally correspond to slums. We try to identify different behaviors taking into account the occurrence of AS in municipalities according to their position in the urban network, as well as their regional insertion. Using the classification of municipalities of Regioes de Influencia das Cidades 2007, a study by the national statistical office (IBGE), we find four trends. Firstly, the phenomenon of AS in 2010 is not as predominantly metropolitan as it was ten years before. A second trend refers to the intensification of the presence of AS in municipalities on the outskirts of metropolises. The third trend is a move of AS towards the country’s hinterland, more accentuated in the North, while the presence of AS increases in municipalities in the coast of the Southeast and the Northeast. The fourth trend is the finding that AS are present in “networks of influence” of metropolises, comprising chains of centers at different levels. The identification of such trends adds complexity to the analysis of slums, and serves as an input to policies aimed at the urban development with regional and spatial equity.
Numerical top‐down effects on red deer (Cervus elaphus) are mainly shaped by humans rather than large carnivores across Europe

Terrestrial ecosystems are shaped by interacting top‐down and bottom‐up processes, with the magnitude of top‐down control by large carnivores largely depending on environmental productivity. While carnivore‐induced numerical effects on ungulate prey populations have been demonstrated in large, relatively undisturbed ecosystems, whether large carnivores can play a similar role in more human‐dominated systems is a clear knowledge gap. As humans influence both predator and prey in a variety of ways, the ecological impacts of large carnivores can be largely modified. We quantified the interactive effects of human activities and large carnivore presence on red deer (Cervus elaphus) population density and how their impacts interacted and varied with environmental productivity. Data on red deer density were collected based on a literature survey encompassing 492 study sites across 28 European countries. Variation in density across study sites was analysed using a generalized additive model in which productivity, carnivore presence (grey wolf, European lynx, Brown bear), human activities (hunting, intensity of human land‐use activity), site protection status and climatic variables served as predictors. The results showed that a reduction in deer density only occurred when wolf, lynx and bear co‐occurred within the same site. In the absence of large carnivores, red deer density varied along a productivity gradient without a clear pattern. Although a linear relationship with productivity in the presence of all three large carnivore species was found, this was not statistically significant. Moreover, hunting by humans had a stronger effect than the presence of all large carnivores in reducing red deer density and red deer density increased with increasing intensity of human land use, with stronger large carnivore effects (all three carnivore species present) at sites with low human land‐use activities. Synthesis and applications. This study provides evidence for the dominant role played by humans (i.e. hunting, land‐use activities) relative to large carnivores in reducing red deer density across European human‐dominated landscapes. These findings suggest that when we would like large carnivores to exert numeric effects, we should focus on minimizing human impacts to allow the ecological impacts of large carnivores on ecosystem functioning.
Associations between circulating cardiovascular disease risk factors and cognitive performance in cognitively healthy older adults from the NuAge study

Introduction Cardiovascular disease risk factors (CVRFs) contribute to the development of cognitive impairment and dementia. Methods This study examined the associations between circulating CVRF biomarkers and cognition in 386 cognitively healthy older adults (mean age = 78 ± 4 years, 53% females) selected from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge). Memory, executive function, and processing speed were assessed at baseline and 2-year follow-up. CVRF biomarkers included total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides, glucose, insulin, high sensitivity C-reactive protein (hs-CRP), homocysteine, protein carbonyls, and cortisol. Linear mixed models were used to determine associations between individual CVRF biomarkers and cognition at both time points. Results HDL-C was most consistently associated with cognition with higher values related to better performance across several domains. Overall, stronger and more consistent relationships between CVRF biomarkers and cognition were observed in females relative to males. Discussion Findings suggest that increases in the majority of circulating CVRFs are not associated with worse cognition in cognitively healthy older adults.
Effects of mesenchymal stem cell on dopaminergic neurons, motor and memory functions in animal models of Parkinson's disease: a systematic review and meta-analysis

Parkinson’s disease is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta, and although restoring striatal dopamine levels may improve symptoms, no treatment can cure or reverse the disease itself. Stem cell therapy has a regenerative effect and is being actively studied as a candidate for the treatment of Parkinson’s disease. Mesenchymal stem cells are considered a promising option due to fewer ethical concerns, a lower risk of immune rejection, and a lower risk of teratogenicity. We performed a meta-analysis to evaluate the therapeutic effects of mesenchymal stem cells and their derivatives on motor function, memory, and preservation of dopaminergic neurons in a Parkinson’s disease animal model. We searched bibliographic databases (PubMed/MEDLINE, Embase, CENTRAL, Scopus, and Web of Science) to identify articles and included only peer-reviewed in vivo interventional animal studies published in any language through June 28, 2023. The study utilized the random-effect model to estimate the 95% confidence intervals (CI) of the standard mean differences (SMD) between the treatment and control groups. We use the systematic review center for laboratory animal experimentation’s risk of bias tool and the collaborative approach to meta-analysis and review of animal studies checklist for study quality assessment. A total of 33 studies with data from 840 Parkinson’s disease model animals were included in the meta-analysis. Treatment with mesenchymal stem cells significantly improved motor function as assessed by the amphetamine-induced rotational test. Among the stem cell types, the bone marrow MSCs with neurotrophic factor group showed largest effect size (SMD [95% CI] = –6.21 [–9.50 to –2.93], P = 0.0001, I2 = 0.0 %). The stem cell treatment group had significantly more tyrosine hydroxylase positive dopaminergic neurons in the striatum ([95% CI] = 1.04 [0.59 to 1.49], P = 0.0001, I2 = 65.1 %) and substantia nigra (SMD [95% CI] = 1.38 [0.89 to 1.87], P = 0.0001, I2 = 75.3 %), indicating a protective effect on dopaminergic neurons. Subgroup analysis of the amphetamine-induced rotation test showed a significant reduction only in the intracranial-striatum route (SMD [95% CI] = –2.59 [–3.25 to –1.94], P = 0.0001, I2 = 74.4 %). The memory test showed significant improvement only in the intravenous route (SMD [95% CI] = 4.80 [1.84 to 7.76], P = 0.027, I2 = 79.6 %). Mesenchymal stem cells have been shown to positively impact motor function and memory function and protect dopaminergic neurons in preclinical models of Parkinson’s disease. Further research is required to determine the optimal stem cell types, modifications, transplanted cell numbers, and delivery methods for these protocols.
Improving Autonomous Vehicle Performance through Integration of an Image Deraining and a Deep Learning-Based Network for Lane Following

—Lane-keeping is a vital component of autonomous driving that requires multiple artificial intelligence technologies and vision systems. However, maintaining a vehicle’s position within the lane is challenging when there is low visibility due to rain. In this research, a combination of image deraining and a deep learning-based network is proposed to improve the performance of the autonomous vehicle. First, a robust progressive Residual Network (ResNet) is used for rain removal. Second, a deep learning-based network architecture of the Convolutional Neural Networks (CNNs) is applied for lane-following on roads. To assess its accuracy and rain-removal capabilities, the network was evaluated on both synthetic and natural Rainy Datasets (RainSP), and its performance was compared to that of earlier research networks. Furthermore, the effectiveness of using both deraining and non-deraining networks in CNNs is evaluated by analyzing the predicted steering angle output. The experimental results show that the proposed model generates safe and accurate motion planning for lane-keeping in autonomous vehicles.
Optimized faster R-CNN for oil wells detection from high-resolution remote sensing images

ABSTRACT As the oil and gas industry is crucial to the global energy market, policymakers need accurate information about local oil reserves and the harmful environmental effects of drilling, such as damage to public land and wildlife. Therefore, accurate automatic detection of the location, distribution and quantity of oil wells is essential. Recent advancements in remote sensing and deep learning technologies provide potential solutions for automatic oil wells detection using high-resolution remote sensing images. This study proposes an optimized Faster R-CNN-based model that incorporates three key modifications to improve the accuracy of oil wells detection. The modifications include replacing the VGG16 network with the ResNet50 network to improve the model’s feature extraction capabilities, substituting the ordinary convolution of ResNet with a dilated convolution to improve the model’s receptive field, and constructing a feature pyramid to improve the model’s ability to detect small targets and objects at different scales. Also, an edge detection module is added to further improve the detection accuracy. Furthermore, a new framework based on Faster R-CNN and leveraging Soft-NMS (Non-Maximum Suppression) and the proposed ClusterRPN sub-network is combined to address the problem of clustered oil wells detection. Experimental results demonstrate that the proposed optimized model outperforms existing models.
Tiger Nut Oil-Based Oil Gel: Preparation, Characterization, and Storage Stability

In this study, Tiger nut (Cyperus esculentus L.) oil-based oleogels were prepared using the emulsion template method with whey protein (WPI; 0.5–2.5% (w/v) and Xanthan gum (XG; 0.1–0.5% (w/v). The microstructure of the oleogels obtained from the high internal phase emulsion (HIPE) and an emulsion after further shearing were observed using an optical microscope and laser confocal microscopy. A series of rheological tests were conducted to evaluate the effect of WPI and XG concentrations on the strength of the emulsion and oleogel. The texture, oil holding capacity, and oxidative stability of oleogels were characterized. The results showed that XG alone could not form oleogel, while the concentration of WPI had more effect than XG. When WPI was at a fixed concentration, the viscoelasticity of HIPE increased with the addition of XG. This was due to the complexation of WPI and XG, forming a stable gel network between the tight emulsion droplets and thus giving it a higher viscoelasticity. With an increase in WPI concentration, the stability and viscoelasticity of the emulsion were increased, and the oil-holding capacity and gel strength of the oleogels were enhanced. Moreover, the addition of XG could significantly enhance the stability and viscoelasticity of the emulsion (p < 0.05), and an increase in the concentration had a positive effect on it. The oleogels showed high gel strength (G′ > 15,000 Pa) and good thixotropic recovery when the XG concentration was higher than 0.3% (w/v). WPI (2.0%) and XG (>0.3%) could be used to obtain HIPE with good physicochemical and viscoelastic properties, which in turn lead to oleogels with minimal oil loss, viscoelastic and thixotropic recovery, and temperature stability. Compared with tiger nut oil-based oleogel, tiger nut oil contained more polyunsaturated fatty acids, which were more easily decomposed through oxidation during storage and had lower oxidation stability. This study provides a reference for the preparation of oleogels from food-approved polymers and provides additional theoretical support for their potential application as solid fat substitutes.
ISS/JEM crew-task analysis to support astronauts with intra-vehicular robotics

This paper proposes employing robotics and automation technology to manned spaceflight to manage repetitive activities for the crew. Current operations on the International Space Station (ISS) were analyzed to better determine target tasks for automation. Crew tasks on the ISS are precisely planned by the ground control and planning teams and then monitored and documented. In this study, astronauts’ tasks related to JAXA’s Japanese Experimental Module were analyzed based on their task names and categorized to determine consistently occulting, repetitive types of work. Based on the categorized tasks’ durations, three categories were anticipated for future automation: sample and equipment retrieval (swapping), logistics (cargo handling), and monitoring. This paper discusses automation methods for each category based on JAXA’s ground and in-orbit robotic research and development.
An analysis of BSS coloring mechanism in IEEE 802.11ax dense networks

—The paper presents an analysis of BSS coloring scheme defined in IEEE 802.11ax standard. The efficiency of dense networks for different scenarios was analyzed and compared. This analysis covers various topologies and work configurations through the use of multiple parameters of the PHY and MAC layers. A positive impact of the coloring mechanism on the QoS was observed. The study also analyzed the impact of the RTS/CTS mechanism on the obtained network performance and adequate prioritization of various traffic classes. It was shown that the proper selection of the coloring mechanism parameters in the IEEE 802.11ax standard has a strong impact on QoS and the performance of dense networks.