Miracle-dz/UniFAR-FTUs huggingface dataset:
The Study of Virtual Reality Sensing Technology in the Form Design and Perception of Public Buildings

In order to explore the commercial building design method that meets the needs of contemporary consumer behavior, the author proposes a method of applying virtual reality, behavior simulation, and other technologies to commercial building design. First, through a questionnaire survey of commercial buildings in a city, the influencing factors of consumption behavior are explained with the help of SPSS correlation analysis. Then, applying virtual reality technology on this basis, three-dimensional presentation of the commercial building design scheme, taking the design of commercial space signage system as an example, the preset low-brightness color system, and the color and shape are single, the logo set A and the logo set B using high-brightness color system and changeable form are presented, expand 3D dynamic visual and behavioral simulations. At last, relying on ResNet image recognition technology, it analyzes the user’s visual experience and usage effect. Experimental results show: There is a significant correlation between plane layout, spatial identification, familiarity of indoor space, and frequency of use, and visual perception is the main driving factor for choosing commercial buildings; using the comparative analysis of commercial logos, it is found that the average value of the confidence of set B is less than that of set A; in terms of significance, the average time of identifying all categories of logo set A is 0.68 s, and the average identification time of all categories of identification set B is 0.46 s; in terms of discrimination, it takes 0.28 s to correct the misrecognition of all categories of identification set A and 0.11 s to correct the misrecognition of all categories of identification set B, indicating that the design of the identification system uses bright colors and changeable forms, which are easier to use. The results indicate that the elevation, slope, hydrology, transportation conditions, economic indexes and cultural factors are important factors affecting the spatial distribution of traditional villages in a city. The analysis shows that the distribution of traditional villages is affected by natural conditions, social economic conditions, cultural factors and other factors, and the optimal layout of traditional villages can be strengthened from these aspects.
Post-Occupancy Evaluation and IEQ Measurements from 64 Office Buildings: Critical Factors and Thresholds for User Satisfaction on Thermal Quality

The indoor environmental quality (IEQ) of buildings can have a strong influence on occupants’ comfort, productivity, and health. Post-occupancy evaluation (POE) is necessary in assessing the IEQ of the built environment, and it typically relies on the subjective surveys of thermal quality, air quality, visual quality, and acoustic quality. In this research, we expanded POE to include both objective IEQ measurements and the technical attributes of building systems (TABS) that may affect indoor environment and user satisfaction. The suite of three tools, including user satisfaction survey, workstation IEQ measurements, and TABS in the National Environmental Assessment Toolkit (NEAT) has been deployed in 1601 workstations in 64 office buildings, generating a rich database for statistical evaluation of possible correlations between the physical attributes of workstations, environmental conditions, and user satisfaction. Multivariate regression and multiple correlation coefficient statistical analysis revealed the relationship between measured and perceived IEQ indices, interdependencies between IEQ indices, and other satisfaction variables of significance. The results showed that overall, 55% of occupants responded as “satisfied” or “neutral”, and 45% reported being “dissatisfied” in their thermal quality. Given the dataset, air temperature in work area, size of thermal zone, window quality, level of temperature control, and radiant temperature asymmetry with façade are the critical factors for thermal quality satisfaction in the field. As a result, the outcome of this research contributes to identifying correlations between occupant satisfaction, measured data, and technical attributes of building systems. The presented integrated IEQ assessment method can further afford robust predictions of building performance against metrics and guidelines for IEQ standards to capture revised IEQ thresholds that impact building occupants’ satisfaction.
Clinical Characteristics of Patients with Pustular Psoriasis: A Single-Center Retrospective Observational Study

Clinical and epidemiologic data on pustular psoriasis are scarce. To investigate the phenotypes of pustular psoriasis and the patients’ characteristics observed in a real-life retrospective observational study. The number of incident cases of pustular psoriasis registered in the period 2005–2021 was retrieved from the electronic medical records of the University Hospital of Verona. One hundred and forty cases of pustular psoriasis were collected. Ninety-one out of 140 patients (65%) were females, with a median (IQR) age of 57 (43–66) years. According to the ERASPEN classification criteria, 116 patients (83%) had palmoplantar pustulosis (PPP), 13 (9%) generalized pustular psoriasis (GPP), and 11 (8%) acrodermatitis continua of Hallopeau (ACH). Gender distribution and median age were consistent among the three groups. The prevalence of psoriatic arthritis in GPP, ACH, and PPP was 8%, 36%, and 28%, respectively. During the same period, a total of 4718 cases of plaque psoriasis were retrieved, with a 1:34 ratio of pustular over plaque psoriasis. Pustular psoriasis is much rarer than plaque psoriasis, with PPP being the more common subtype.
Impact of Multiple Sclerosis Risk Polymorphism rs7665090 on MANBA Activity, Lysosomal Endocytosis, and Lymphocyte Activation

Deficiencies in Mannosidase β (MANBA) are associated with neurological abnormalities and recurrent infections. The single nucleotide polymorphism located in the 3′UTR of MANBA, rs7665090, was found to be associated with multiple sclerosis (MS) susceptibility. We aimed to study the functional impact of this polymorphism in lymphocytes isolated from MS patients and healthy controls. A total of 152 MS patients and 112 controls were genotyped for rs7665090. MANBA mRNA expression was quantified through qPCR and MANBA enzymatic activity was analyzed. Upon phytohemagglutinin stimulation, immune activation was evaluated by flow cytometry detection of CD69, endocytic function, and metabolic rates with Seahorse XFp Analyzer, and results were stratified by variation in rs7665090. A significantly reduced gene expression (p < 0.0001) and enzymatic activity (p = 0.018) of MANBA were found in lymphocytes of MS patients compared to those of controls. The rs7665090*GG genotype led to a significant β-mannosidase enzymatic deficiency correlated with lysosomal dysfunction, as well as decreased metabolic activation in lymphocytes of MS patients compared to those of rs7665090*GG controls. In contrast, lymphocytes of MS patients and controls carrying the homozygous AA genotype behaved similarly. Our work provides new evidence highlighting the impact of the MS-risk variant, rs7665090, and the role of MANBA in the immunopathology of MS.
Multi-agent differential game based cooperative synchronization control using a data-driven method

This paper studies the multi-agent differential game based problem and its application to cooperative synchronization control. A systematized formulation and analysis method for the multi-agent differential game is proposed and a data-driven methodology based on the reinforcement learning (RL) technique is given. First, it is pointed out that typical distributed controllers may not necessarily lead to global Nash equilibrium of the differential game in general cases because of the coupling of networked interactions. Second, to this end, an alternative local Nash solution is derived by defining the best response concept, while the problem is decomposed into local differential games. An off-policy RL algorithm using neighboring interactive data is constructed to update the controller without requiring a system model, while the stability and robustness properties are proved. Third, to further tackle the dilemma, another differential game configuration is investigated based on modified coupling index functions. The distributed solution can achieve global Nash equilibrium in contrast to the previous case while guaranteeing the stability. An equivalent parallel RL method is constructed corresponding to this Nash solution. Finally, the effectiveness of the learning process and the stability of synchronization control are illustrated in simulation results.
Multi-Physics Simulation Platform and Multi-Layer Metal Technology for CMOS-MEMS Accelerometer with Gold Proof Mass

This chapter describes technical features and solutions to realize a highly sensitive CMOS-MEMS accelerometer with gold proof mass. The multi-physics simulation platform for designing the CMOS-MEMS device has been developed to understand simultaneously both mechanical and electrical behaviors of MEMS stacked on LSI. MEMS accelerometer fabrication process is established by the multilayer metal technology, which consists of the gold electroplating and the photo-sensitive polyimide film. The proposed MEMS accelerometers are fabricated and evaluated to verify the effectiveness of the proposed techniques regarding sub-1G MEMS and arrayed MEMS devices. The experimental results show that the Brownian noise of the sub-1G MEMS accelerometer can achieve 780 nG/(Hz) 1/2 and the arrayed MEMS accelerometer has a wide detection, ranging from 1.0 to 20 G. Moreover, using the developed simulation platform, we demonstrate the proposed capacitive CMOS-MEMS accelerometer implemented by the multi-layer metal technology. In conclusion, it is confirmed that the multi-physics simulation platform and the multi-layer metal technology for the CMOS-MEMS device have a potential to realize a nano-gravity sensing technology.
Joint bandwidth and power resource allocation technique in multi‐carrier non‐orthogonal multiple access‐based cognitive Internet of Things networks

The recent development of the Internet of Things (IoT) devices offers an intelligent concept for integrating massive number of interconnected wireless devices. However, supporting such massive number of IoT connections (hundreds of billions) requires an efficient and dynamic spectrum access strategy. Accordingly, the integration of non‐orthogonal multiple access (NOMA) in the cognitive radio (CR) systems, referred to as a multi‐carrier NOMA CR‐enabled system, is envisioned as a potential spectrum‐efficient networking paradigm that can support massive energy‐efficient IoT connectivity in B5G networks while maintaining the quality of services (QoS) of the IoT devices. However, the power consumption issue of the multi‐carrier NOMA CR‐based system becomes as one of key challenges, especially when considering the expected massive connectivity. Accordingly, several power‐aware optimization frameworks have been considered to address this issue. While most of the existing CR‐based multi‐carrier NOMA power allocation mechanisms only optimize the allocated per‐user power, this article proposes a novel joint bandwidth and power allocation problem over each available idle channel with the aim of minimizing the overall transmission power under a set of QoS constrains. Specifically, the bandwidth of each channel is adaptively subdivided into two variable‐width sub‐channels, each is capable to serve a group of CR users using power‐domain NOMA. This novel design is formulated as a joint optimization problem that is shown to be a non‐convex. Therefore, an iterative algorithm with a second‐order cone programming is deployed to handle the non‐convexity of the problem, and thus, determine the solution of it. Simulation results reveal that the developed variable bandwidth adaptive power allocation mechanism outperforms the conventional equal sub‐channel allocation in terms of the required transmission power, which significantly improves the energy efficiency in the system.
Novel Phosphonium-Based Ionic Liquid Electrolytes for Battery Applications

In this study, we address the fundamental question of the physicochemical and electrochemical properties of phosphonium-based ionic liquids containing the counter-ions bis(trifluoromethanesulfonyl)imide ([TFSI]−) and bis(fluorosulfonyl)imide ([FSI]−). To clarify these structure–property as well as structure–activity relationships, trimethyl-based alkyl- and ether-containing phosphonium ILs were systematically synthesized, and their properties, namely density, flow characteristics, alkali metal compatibility, oxidative stability, aluminum corrosivity as well as their use in Li-ion cells were examined comprehensively. The variable moiety on the phosphonium cation exhibited a chain length of four and five, respectively. The properties were discussed as a function of the side chain, counter-ion and salt addition ([Li][TFSI] or [Li][FSI]). High stability coupled with good flow characteristics were found for the phosphonium IL [P1114][TFSI] and the mixture [P1114][TFSI] + [Li][TFSI], respectively.
Hierarchical Low-Carbon Economic Dispatch with Source-Load Bilateral Carbon-Trading Based on Aumann–Shapley Method

Introducing carbon trading is an essential way to decarbonize the power system. Many existing studies mainly consider source-side unilateral carbon trading (UCT). However, there are still rare studies considering source-load bilateral carbon trading (BCT). The effect of source-load BCT on system-wide carbon mitigation is worth studying. To fill this research gap, a hierarchical low-carbon economic-dispatch model with source-load BCT based on the Aumann–Shapley method was proposed. In the first layer, economic-dispatch was conducted to minimize the power-generation costs and source-side carbon-trading costs. Then, based on the carbon-emission flow (CEF) theory, the actual load carbon emissions can be obtained and passed to the second layer. At the second layer, the demand-response optimization was performed to minimize the load-side carbon-trading costs. Finally, the proposed model was tested on the modified New England 39-bus and IEEE 118-bus systems using the MATLAB/YALMIP platform with the Gurobi solver. The results indicate that the proposed model can effectively facilitate peak-load shifting, wind-power consumption, and carbon mitigation. Furthermore, compared with the models only considering source-side or load-side UCT, the proposed source-load BCT model has obvious advantages in carbon mitigation.
The relationship of the elderly toward their home and living environment

Housing is a basic human good and right. It plays a versa-tile role, allowing people to fulfil a number of needs, and it is not limited only to one’s immediate living space, but also includes an individual’s wider living environment. People’s relationship toward housing and their living environment changes over the course of their lives. Especially in old age, housing becomes more important. Research shows that the elderly want to remain in their home environments as long as possible because they are closely attached to them. In order to determine whether these findings also apply to Slovenia, this article analyses how attached the elderly in Slovenia are to their homes and wider living environment and how satisfied they are with living there. The elderly’s views were obtained with a survey, and a statistical analysis was carried out using SPSS software, based on the calculation of various statistical correlation tests. The analysis confirmed the assumption that the Slovenian elderly are also very attached to their homes or home environments and are satisfied with living there. In addition, the analysis showed some differences among the elderly in this regard depending on their age, where they live and how long they have been living in their current homes.
Deterministic annealing, clustering, and optimization

This work introduces the concept of deterministic annealing (DA) as a useful approach to clustering and other related optimization problems. It is strongly motivated by analogies to statistical physics, but is formally derived within information theory and probability theory. This approach enables escaping local optima that plague traditional techniques, without the extremely slow schedules typically required by stochastic methods. The clustering solutions obtained by DA are totally independent of the choice of initial configuration. A probabilistic framework is constructed, which is based on the principle of maximum entropy. The association probabilities at a given average distortion are Gibbs distributions parametrized by the corresponding Lagrange multiplier $\beta$, which is inversely proportional to the temperature in the physical analogy. By computing marginal probabilities, an effective cost is obtained, which is minimized to find the most probable set of cluster representatives at a given temperature. This effective cost is the free energy in statistical mechanics, which is indeed optimized at isothermal, stochastic equilibrium. Within the probabilistic framework, annealing is introduced by controlling the Lagrange multiplier $\beta$. This annealing is interpreted as gradually reducing the "fuzziness" of the associations. Phase transitions are identified in the process, which are, in fact, cluster splits. A sequence of phase transitions produces a hierarchy of fuzzy-clustering solutions. Critical $\beta$ are computed exactly for the first phase transition and approximately for the following ones. Specific algorithms are derivable from the general approach, to address different aspects of clustering. From the experimental results it appears that DA is substantially superior to traditional techniques. The approach is extended to deal with a larger family of optimization problems that can be reformulated as constrained clustering. A probabilistic framework for constrained clustering is derived. Three examples are discussed. Mass-constrained clustering yields an improvement of the clustering procedure. The process is now independent of the number and multiplicities of representatives. The travelling salesman problem is reformulated as constrained clustering, yielding the elastic net approach. A second Lagrange multiplier is identified and is controlled in the process. Finally, this approach is suggested for self-organization of neural networks.
Adaptive Tone Reproduction Based on the Pseudo-Hilbert Scan

The Pseudo-Hilbert curve is an extension of Hilbert curve which one of space-filling curves published by G. Peano. Because of its property of preserving spacial relationship of the multidimensional patterns, there are several applications using this curve such as image processing, computer graphics, etc. In this paper, we concentrate on a tone mapping technique, which is to display high contrast images on devices with limited dynamic range of luminance values. Based on the Pseudo-Hilbert scan, an adaptive tone reproduction algorithm is proposed. The proposed method takes advantage of both properties of global and local processing while preserving low computational complexity, because the Pseudo-Hilbert scan transforms a complex two-dimensional luminance local processing into a simple one-dimensional one. Therefore, the algorithm can preserve visibility and contrast impression of high dynamic range scenes in the common display devices. From the experimental results, we have confirmed that the proposed method produces good results on a variety of high dynamic range images. Kyewords: Tone reproduction high dynamic, Pseudo-Hilbert scan, luminance mapping, Euclidean distance. Vol. 3, No. 1, (2007) 41-46 International Journal of Information Systems for Logistics and Management http://www.knu. edu.tw/ijislm
Factors affecting the design and development of responsive facades: a historical evolution

ABSTRACT A responsive facade system is considered a major component of high-performance building envelope that is capable of responding to environmental stimuli and aims to improve occupants’ comforts and energy consumption. While building design-related research have addressed the technical and design aspects of responsive facades, very limited historical studies have been conducted on the evolution of such systems. This paper investigates and classifies in a chronological manner the historical factors involved in the evolution of design and development of responsive facade systems. The influential factors are classified into a set of sociocultural, technological, political, environmental and economic factors originating from revolutionary changes in art, technology and building construction since late nineteenth century. The historical timeline presented is intended to serve as a helpful resource for researchers and educators in research and teaching activities. The formulated timeline can be utilized to track the pattern of current developments and predict what might be expected in the future. While the focus of the paper is on individual architecture, the trend of the recent facade developments as presented in the timeline suggests that responsive facades will be possibly implemented for urban-scaled development of smart neighborhoods and/or cities in the future.
Singing Voice Detection in Electronic Music with a Long-Term Recurrent Convolutional Network

Singing Voice Detection (SVD) is a classification task that determines whether there is a singing voice in a given audio segment. While current systems produce high-quality results on this task, the reported experiments are usually limited to popular music. A Long-Term Recurrent Convolutional Network (LRCN) was adapted to detect vocals in a new dataset of electronic music to evaluate its performance in a different music genre and compare its results against those in other state-of-the-art experiments in pop music to prove its effectiveness across a different genre. Experiments on two datasets studied the impacts of different audio features and block size on LRCN temporal relationship learning, and the benefits of preprocessing on performance, and the results generate a benchmark to evaluate electronic music and its intricacies.
A Simple Palladium Hydride Embedded Atom Method Potential for Hydrogen Energy Applications

When hydrogen is produced from a biomass or coal gasifier, it is necessary to purify it from syngas streams containing components such as CO, CO2, N2, CH4, and other products. Therefore, a challenge related to hydrogen purification is the development of hydrogen-selective membranes that can operate at elevated temperatures and pressures, provide high fluxes, long operational lifetime, and resistance to poisoning while still maintaining reasonable cost. Palladium-based membranes have been shown to be well suited for these types of high-temperature applications and have been widely utilized for hydrogen separation. Palladium's unique ability to absorb a large quantity of hydrogen can also be applied in various clean energy technologies, like hydrogen fuel cells. In this paper, a fully analytical interatomic embedded atom method (EAM) potential for the Pd-H system has been developed, that is easily extendable to ternary Palladium-based hydride systems, such as Pd-Cu-H and Pd-Ag-H. The new potential has fewer fitting parameters than previously developed EAM Pd-H potentials and is able to accurately predict the cohesive energy, lattice constant, bulk modulus, elastic constants, melting temperature, and the stable Pd-H structures in molecular dynamics (MD) simulations with various hydrogen concentrations. The EAM potential also well predicts the miscibility gap, the segregation of the palladium hydride system into dilute (α), and concentrated (β) phases.