Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Strategies for Improving Green Open Spaces in Old Downtown Residential Communities from the Perspective of Public Health to Enhance the Health and Well-Being of the Aged

Based on the trend of global aging, people are paying more and more attention to the health of the elderly and the improvement of green open spaces. However, few studies have focused on strategies to improve green spaces in response to this trend. Especially, with the outbreak of COVID-19, an urgent need to develop a sustainable system strategy to improve the health of the elderly in residential communities in old districts has emerged. Traditional improvement strategies based on current situation evaluation often focus on the most prominent practical problems. Therefore, the objective of this study was to provide theoretical research and practical improvement strategies for green open spaces in old downtown residential communities to improve the health and well-being of the elderly. In response to this problem, this research proposes an alternative method based on causality (FDM-DANP-mV model), by extracting 23 green open space elements that affect the health of the elderly and dividing them into three dimensions, to form a preliminary evaluation framework. On this basis, the more effective and feasible standard elements are screened out, and the influence relationship behind the elements is clarified. Then, the sustainable development strategy is systematically discussed in three practical cases. This allows for the analysis of the present situation to not only identify the current significant problems but also to capture the source of the influence behind the real problems based on the clarification of the dominant influence relationship. The actual value of this study is to provide a key design decision basis for the improvement of the green open spaces in old downtown residential communities, aiming at avoiding waste to the greatest extent under the premise of limited resources and gradually promoting the improvement of the urban built environment to promote the health and well-being of the elderly.
iDim: Practical Implementation of Index Modulation for LiFi Dimming

This paper introduces a novel dimming method for Light Fidelity (LiFi) based on a time-domain sample index modulation (TIM), called indexed dimming (iDim). The aim is to provide a wide brightness range, while maintaining a high signal-to-noise ratio (SNR) performance and a high transmission rate. Direct current optical orthogonal frequency division multiplexing (DCO-OFDM) is used and novel line codes are presented. The system performance is experimentally validated by an implementation on a NI PXIe-1085 and NI-7966R Field Programmable Gate Array (FPGA). Implementation results show that the proposed iDim jointly offers multiple benefits compared to existing dimming methods such as amplitude modulation (AM) dimming. Specially, the lowest optical power of the iDim method is measured at $20~\mu \text{W}$ , which is 10 times lower than the measured limit of AM dimming. The iDim system provides a SNR of 22.5 dB for all brightness levels, while the AM-dimming method dramatically reduces its SNR when light is dimmed. The transmission rate of iDim is also higher than DCO-OFDM. This results in up to 40% reduced optical power per bit when compared to sDim, a pulse-width-modulation (PWM)-inspired dimming method. Therefore, iDim is a promising dimming method for applications targeting extremely low illumination levels.
Categorization in Unsupervised Generative Selflearning Systems

: In this study the authors investigated the connections between the training processes of unsupervised neural network models with self-encoding and regeneration and the information structure in the representations created by such models. We propose theoretical arguments leading to conclusions, confirmed by previously published experimental results that unsupervised representations obtained under certain constraints in training compliant with Bayesian inference principle, favor configurations with better categorization of hidden concepts in the observable data. The results provide an important connection between training of unsupervised machine learning models and the structure of representations created by them and can be used in developing new methods and approaches in self-learning as well as provide insights into common principles underlying the emergence of intelligence in machine and biologic systems.
Analysis of the relationship between the personality traits of university students and their grit levels

This research aims to examine the relationships between personality traits and the grit levels of university students. Participants of the study are 379 students (304 females, 75 males). The age range of the study group is 18-25. Five-Factor Personality Scale, Short Grit Scale, and Personal Information Form were used as data collection tools in the study. Analysis of the data was performed using the Pearson product moments correlation with the SPSS program and t-test techniques for independent groups. According to the findings obtained from the study, a positive significant relationship was found between liability, openness to experience, extraversion and adaptation personality traits, and grit levels. It’s also found that a negative relationship between neuroticism and grit levels. In terms of gender, there was no significant difference between male students and female students in grit levels. However, in terms of gender, it was observed that there was a significant difference between male students and female students in terms of adaptation and openness to experience. The research findings were discussed within the scope of the literature and recommendations were made according to the results.
Expanding the Analysis of Using Augmented Reality for Construction Embedment Inspections

Embedments (embeds) are commonly used when dissimilar construction materials such as steel and concrete or wood and masonry need to be anchored together. The embed serves as a structural connecting point for different materials. Construction managers are aware of the significance in terms of lost time and cost overruns when these embeds are not properly installed. Missing embeds require extensive structural re-work that is costly and involves a significant amount of time to remedy. The inspection process directly impacts the success of a project when missing embeds can be identified early. This research analysis expands on a past research study involving the use of an augmented reality headset to assist inspectors in the process of examining a simulated embed installation. This paper will identify shortcomings from the original study that were used to further develop and refine the augmented reality inspection process. While the use of improved equipment helped to stabilize the virtual image when viewed through a head-mounted augmented reality headset, newly discovered visibility issues turned out to be problematic for its use. The researchers found that virtual image opacity and image drift were problematic in the follow-up study, resulting in inaccurate inspections. As a result of these findings, the researchers recommend adjustments to the virtual overlay presented by the head-mounted augmented reality headset in a future iteration of this study.
EVALUATION OF PLUG-IN PARALLEL HEV TOPOLOGIES USING OPTIMAL CONTROL METHODS AND VEHICLE DYNAMICS SIMULATION

Hybrid electric vehicle (HEV) powertrains with parallel topologies are among the frequently used layouts, because of their easy applicability on an existing conventional powertrain, by the addition of hybrid modules with mild, full, or a plug-in capability. This paper investigates three of such parallel HEV topologies: P2, P3, and P4; all in a plug-in variant, to find-out which one performs best. Apart from the topology consideration, one of the other common questions or challenges in HEV development is the ICE concept selection. To address it, the paper combines the three HEV topologies with three technologically different internal combustion engines, all with the same power outputs. Then, all the powertrain and ICE combinations are tested in homologation driving cycles and vehicle dynamics simulation test – different acceleration tests – giving a holistic methodology suitable for thorough HEV topology evaluation, identifying all possible hybridization benefits. To find the maximum CO2 potential, it is convenient to exclude the effect of the energy management control strategy on the CO2 result in a charge sustaining driving cycle; therefore, to use some optimal control method. For this task, the paper compares the Equivalent Consumption Minimization Strategy, that realizes a Pontryagin’s minimum principle against the Dynamic Programming optimal control method, which is based on Bellman’s principle of optimality. Both control methods are available as a part of GT-Suite 0D/1D/3D multi-physics CAE simulation software, that is used in our whole study.
Talent retention strategies: An exploratory study within the consulting industry in Gauteng province, South Africa

According to Consultancy (2018), the consulting industry is worth approximately R125 billion with 60 000 professionals. The consulting industry accounts for over half of the African continent’s overall industry and it has grown in recent years. The consultancy industry globally has however witnessed a paradigm shift over the past few years in terms of its nature, level of technology and overall scope of work (Srinivasan 2014). Over the last few decades, business consulting has recorded continuous and significant dynamic growth. The great economic relevance of the consulting industry has attracted many young professionals (Nissen 2019). However, the industry has also experienced some major changes over the past few years. These changes inform the introduction of new business processes and the approaches in designing their compensation system to retain talent. The objective of many organisations is to remain in, or gain, a competitive advantage within the market and to deliver more value to their stakeholders (Liberty 2017). This is often a challenge in the consulting industry as organisations struggle to attain commitment from their employees. The current study aims to bridge the gap by suggesting initiatives for retaining talent. In the consulting industry, which is a knowledge-intensive industry, human resources (HR) are considered to be the most important asset (Badiyala 2015), and maintaining their performance and retaining them is of particular importance. Orientation: The consultancy industry globally has witnessed a paradigm shift over the past few years in terms of its nature, employee turnover and attraction and retention of talent. These changes have posed a challenge because the industry struggles to attain commitment from their employees.
Food Sector as an Interactive Business World: A Framework for Research on Innovations

The objective of this paper is to enhance the dominant research perspective of innovations in the food market (power or supply chain centric) with an interactive/network approach. Many scholars identify the development challenges facing the food sector, including economic factors, changes in lifestyle, climate change, changes to the food consumption mix, shrinkage of Earth’s resources and interactions between food production and the environment, in the context of sustainable development. A new approach to innovations in the food market may shift it towards a more sustainable path of development. Based on a literature review, we present the specific conditions for innovation in the food market and discuss previous research as being focused on the power of operators and flows in supply chains. Methodologically, this paper puts these considerations in the context of interaction and business networks. We note that the concept of power and dependence can be embedded with the concept of interdependence, and flows in supply chains can be replaced by the concept of cooperation in business networks. We conceptualize a research framework based on innovative activities in business relationships and networks and we propose the following themes as research avenues for further research: (1) What drives innovation in food ecosystems? (2) When is the power-centric approach to innovations more effective than taking the perspective of interdependence? (3) How do network-born innovations develop in the food sector? (4) How do actors handle innovation in their business models? (5) What is the impact of innovations on the food sector?
Modular and Self-Scalable Origami Robot: A First Approach

This paper presents a proposal of a modular robot with origami structure. The proposal is based on a self-scalable and modular link made of soft parts. The kinematics of a single link and several links interconnected is studied and validated. Besides, the link has been prototyped, identified, and controlled in position. The experimental data show that the system meets the scalability requirements and that its response is totally reliable and robust.
Structural and activity changes of xanthine oxidase induced by cetyltrimethylammonium bromide and its Gemini homologue bis(cetyldimethylammonium)hexane dibromide: a comparative study

Abstract Interaction of xanthine oxidase (XOD), a key enzyme in purine metabolism, with cetyltrimethylammonium bromide (CTAB) and bis(cetyldimethylammonium)hexane dibromide (C16C6C16Br2) has been studied by employing different techniques at pH 7.4 and 25 °C. The existence of interaction between the surfactants and the enzyme was established by the deviation of tensiometric profiles of surfactants with and without the enzyme. The results obtained by Circular Dichroism, Fluorescence and activity suggest that the Gemini surfactant interacts strongly with the XOD than its conventional homologue. The peculiar structural design of C16C6C16Br2, enhanced ability for electrostatic and hydrophobic interactions, and unique aggregation behavior is accountable for the effectiveness of the Gemini in interacting/unfolding the XOD. The results are contemplated to offer valuable understandings in designing the surfactant-based formulations to moderate the activity of XOD. Graphical Abstract
Innovating Methods: Observing In Situ Technology Experiences Using Novel Visual Research Methods

ABSTRACT This paper describes the development of novel visual research methods derived through the application of consumer-grade tools of immersive virtual reality. The research methods highlighted are ideally suited for research in the wild, providing field researchers the means to observe and capture any situated activity within its natural context, including the capability to reexamine or “reexperience” activities observed. The utility of these methods was validated empirically through formal and informal field studies. The methods herein are either completely novel approaches or innovative variations of existing visual research methods, thus expanding the existing arsenal of HCI and UX visual research methodologies for in situ observation of ubiquitous and pervasive technology experiences.
Synthesis and Advanced Characterization of Polymer–Protein Core–Shell Nanoparticles

Enzyme immobilization techniques are widely researched due to their wide range of applications. Polymer–protein core–shell nanoparticles (CSNPs) have emerged as a promising technique for enzyme/protein immobilization via a self-assembly process. Based on the desired application, different sizes and distribution of the polymer–protein CSNPs may be required. This work systematically studies the assembly process of poly(4-vinyl pyridine) and bovine serum albumin CSNPs. Average particle size was controlled by varying the concentrations of each reagent. Particle size and size distributions were monitored by dynamic light scattering, ultra-small-angle X-ray scattering, small-angle X-ray scattering and transmission electron microscopy. Results showed a wide range of CSNPs could be assembled ranging from an average radius as small as 52.3 nm, to particles above 1 µm by adjusting reagent concentrations. In situ X-ray scattering techniques monitored particle assembly as a function of time showing the initial particle growth followed by a decrease in particle size as they reach equilibrium. The results outline a general strategy that can be applied to other CSNP systems to better control particle size and distribution for various applications.
Urban Organic Waste for Urban Farming: Growing Lettuce Using Vermicompost and Thermophilic Compost

A transformation towards sustainable food production requires improved circular nutrient management. Urban organic waste contains relevant nutrients and organic matter, yet only 4% of global urban nitrogen (N) and phosphorus (P) sources are presently recycled. One recycling approach is the composting of urban wastes for urban horticulture. We characterized compost from various urban waste fractions and assessed their fertilizer value in a pot trial with lettuce plants. Seven treatments were investigated: food waste vermicompost with coir and paperboard bedding material, thermophilic compost from green waste and human feces, two references with mineral fertilization and a sand control. The lettuce yield and total uptake of P, potassium (K), calcium (Ca), and magnesium (Mg) were highest in plants grown in coir-based vermicompost. The fecal compost led to the highest shoot P and K content, but the shoot uptake of Ca and Mg were lower than in the other treatments. All composts required additional N for lettuce growth. In conclusion, urban waste-derived vermicompost and fecal compost demonstrate a high delivery rate of plant-available Ca, Mg, P, and K. Research is needed on macronutrient availability and alternative N sources for the substitution of synthetic fertilization. These findings support the production of urban waste composts, furthering efforts in nutrient recycling.
Evaluation of Quantile Delta Mapping as a bias‐correction method in maximum rainfall dataset from downscaled models in São Paulo state (Brazil)

An essential step for improving climate change models' performance is to evaluate their ability to represent the current climate conditions, especially extreme events. On such background, this study aims at evaluating the performance of the Quantile Delta Mapping (QDM) as a bias correction method for annual maximum daily precipitation series (bmax) generated from downscaled climate change models under tropical–subtropical conditions of Brazil. We selected the QDM due to its ability to correct bias in extreme quantile of wet days. Climate projections obtained from 20 NASA Earth Exchange Daily Downscaled Projections models (NEX‐GDDP) from 1950 to 2005 were subjected to validation processes based on the QDM method. Two climate change scenarios (RCP 4.5 and RCP 8.5 W m−2) have also been considered. Several goodness‐of‐fit measures, such as root‐mean‐square‐error (RMSE), SD, percentual bias (pbias), mean absolute error (MAE), Pearson correlation test, modified Willmott test (dm), have been calculated from the outcomes of the models and their corresponding observed data (obtained from rain gauges). These goodness‐of‐fit measures were calculated before and after applying the QDM method. The QDM was able to correct virtually all biases. More specifically, the QDM successfully adjusted the empirical cumulative distribution of climate change projections, removing the systematic error of raw data. The QDM also presented a suitable performance when applied to future projections (2020–2095). This statement holds for all NEX‐GDDP models, except for the ACCESS1‐0 model in RCP 8.5. In such a scenario, this latter model presented unrealistic rainfall values. Finally, with the improvement resulting from applying the bias correction method QDM, there was an increase in the number of climate projections suitable for end‐users in the study region.
Chemical characterization of oxygenated organic compounds in the gas phase and particle phase using iodide CIMS with FIGAERO in urban air

Abstract. The atmospheric processes under polluted environments involving interactions of anthropogenic pollutants and natural emissions lead to the formation of various and complex secondary products. Therefore, the characterization of oxygenated organic compounds in urban areas remains a pivotal issue in our understanding of the evolution of organic carbon. Here, we describe measurements of an iodide chemical ionization time-of-flight mass spectrometer installed with a Filter Inlet for Gases and AEROsols (FIGAERO-I-CIMS) in both the gas phase and the particle phase at an urban site in Guangzhou, a typical megacity in southern China, during the autumn of 2018. Abundant oxygenated organic compounds containing two to five oxygen atoms were observed, including organic acids, multi-functional organic compounds typically emitted from biomass burning, oxidation products of biogenic hydrocarbons and aromatics. Photochemistry played dominant roles in the formation of gaseous organic acids and isoprene-derived organic nitrates, while nighttime chemistry contributed significantly to the formation of monoterpene-derived organic nitrates and inorganics. Nitrogen-containing organic compounds occupied a significant fraction of the total signal in both the gas and particle phases, with elevated fractions at higher molecular weights. Measurements of organic compounds in the particle phase by FIGAERO-I-CIMS explained 24 ± 0.8 % of the total organic aerosol mass measured by aerosol mass spectrometer (AMS), and the fraction increased for more aged organic aerosol. The systematical interpretation of mass spectra of the FIGAERO-I-CIMS in the urban area of Guangzhou provides a holistic view of numerous oxygenated organic compounds in the urban atmosphere, which can serve as a reference for the future field measurements by FIGAERO-I-CIMS in polluted urban regions.
Major Approaches to the Dosage of Vitamin D in the Elderly: A Systematic Review

Introduction: In the scenario of vitamin D deficiency, this incident is prevalent and with risks to public health in the world, reaching approximately 90% of individuals. Hypovitaminosis D can cause, mainly in the elderly, lower bone mineral density, fractures, muscle weakness, falls, and acute respiratory infection. Objective: To evaluate the main clinical results on vitamin D levels in the elderly, as well as to analyze which daily or weekly dose of vitamin D is most effective in the elderly in reducing the number of falls and fractures. Methods: The present study developed a systematic review, addressing randomized clinical studies, diverse clinical studies, systematic reviews, meta-analysis, and the latest international consensus, following the rules of PRISMA. Results and Conclusion: A total of 152 articles were found involving the dosage and the impact of vitamin D in the elderly. In total, 72 articles were evaluated in full and 30 were included. According to the main literary findings, vitamin D deficiency implies problems with mineralization and bone mineral density, causing fractures and an increase in the number of elderly falls. In this sense, SBEM recommends maintaining vitamin D concentrations above 30 ng/mL. Also, vitamin D deficiency points to the occurrence of neurological diseases such as cognitive decline, risk of Alzheimer's disease, and depression. In the current scenario of the pandemic, vitamin D points as an important modulator of the immune system, and its deficiency promotes the unregulated release of cytokines, leading to complications in patients with COVID-19.