Miracle-dz/UniFAR-FTUs huggingface dataset:
Some evidence of a time-varying thermal perception

Recent research suggests that a time-varying indoor thermal environment can lead to energy savings and contribute to boost buildings' energy flexibility. However, thermal comfort standardization has so far considered thermal comfort criteria as constant throughout the day. In general, very little attention has been given to the ‘time of day' variable in the context of thermal comfort research. In this paper, we show some evidence of a time-varying thermal perception by using: (1) data from about 10,000 connected Canadian thermostats made available as part of the ‘Donate Your Data' dataset and (2) about 22,000 samples of complete (objective + ‘right-here-right-now' subjective) thermal comfort field data from the ASHRAE I and SCATs datasets. We observe that occupants prefer colder thermal conditions at 14:00 and progressively warmer ones in the rest of the day, indistinctively in the morning and evening. Neutral temperature differences between 08:00 and 14:00 and 14:00 and 20:00 are estimated to be of the order of 2°C. We hypothesize that the human circadian rhythm is the cause of this difference. Nevertheless, the results of this study are only based on observational data. Thermal comfort experiments in controlled environmental chambers are required to confirm these findings and to better elucidate the effects of light and circadian timing and their interaction on thermal perception.
Effects of tariff reduction by regional comprehensive economic partnership (RCEP) on global value chains based on simulation

ABSTRACT We estimate the effects of tariff reduction by regional comprehensive economic partnership (RCEP) on global value chains based on simulation. We find that tariff reduction by RCEP has an effect of strengthening signatories’ GVC positions and participation both in the short run and long run. The long-run effects are larger than the short-run effects. Australia, New Zealand, ASEAN countries and Japan have a potential to move towards the top of GVCs in sectors with comparative advantages in the long run. Overall, Korea’s GVC positions improve more than Japan and China, and both Korea and Japan benefit more in GVC participation than China in the long run. In contrast, USA and Europe’s GVC positions and participation tend to slightly drop.
Influence of Wall Material Composition on Microencapsulation Efficiency of Cold Pressed Pumpkin Seed Oil by Freeze-Drying

Encapsulation is a food preservation method where sensitive compounds, known as “core material”, can be entrapped within a matrix that is called “wall material” [1]. Capsules of which sizes range between 3-800μm are called microcapsules, while particle sizes of Nano capsules range between 10-1000nm [2]. The most widely used microencapsulation techniques are spray drying, spray cooling, extrusion, fluidized bed coating, freeze-drying (lyophilization), coacervation, cocrystallization, interfacial or in-situ polymerization [3,4]. Although its high production costs, freeze-drying is a unique technology for heat sensitive core materials. The well-known reasons of encapsulation are protection of core material against environmental factors such as oxygen, light or heat and hence, extending the shelf life of product; improvement of core materials’ handling and storage properties; controlled release of core materials; and/or masking of off-odour and off-taste [1,5]. Main compounds that need to be encapsulated are flavours, antioxidants, antimicrobials, bioactive peptides, minerals, vitamins, bioactive lipids, probiotics and dietary fibres [6]. Various carbohydrates (starch, cellulose, gum Arabic, carrageenan, alginate, xanthan, chitosan etc.), proteins (whey protein, casein, gluten, gelatin etc.) and lipids (phospholipids, fatty acids, waxes etc.) may be used as wall materials in encapsulation processes [7]. The main advantages of maltodextrins are serving as an efficient barrier against oxidation, neutral taste, low cost, high solubility in water and formation of low viscosity solutions even at high concentrations. However, due to lack of emulsifying capacity of maltodextrins, they should be used in combination with surface active wall materials such as gum arabic [8,9]. In encapsulation processes, milk proteins, whey and casein, improve stability of food emulsions by their high film-form ing and emulsifying properties [10]. It should be kept in mind that whey acts as a more effective emulsifier in oil-in-water emulsions than casein and sodium caseinate [11]. Surface active activity of gum arabic is attributed to its low protein content [12]. Nevertheless, its high price and limited availability require its incorporation into other wall materials [13]. Lecithin may be added to wall material combinations to enhance wettability and dispersibility properties of microcapsules containing oil or fat [14].
Evaluation of Transducer and Signature Selections on the Performance of Artificial Intelligence Machine Tool Wear Prognosis

The qualities of machined products are largely depended on the status of machines in various aspects. Thus, appropriate condition monitoring would be essential for both quality control and longevity assessment. Recently, with the advance in artificial intelligence and computational power, status monitoring and prognosis based on data driven approach becomes more practical. However, unlike machine vision and image processing, where data types are fixed and the performance index has already well defined, sensor selection and index for machine tools are versatile and not standardized at this moment. Without supporting of appropriate domain knowledge for selecting appropriate sensors and adequate performance index, pure data driven approach might suffer from unsatisfied prediction accuracy and needing of excessive training data, as well as the possibility of misjudgment. This would be a key obstacle for promoting data driven based prognosis in general intelligent manufacturing field. In this work, the status monitoring and prediction of a cutter wear problem is investigated to address the above concerns and to demonstrate the possible solutions by hiring a 5-axis machine center equipped with milling cutters of different wear levels. Transducers including accelerometers, microphones, current transformer, and acoustic emission sensors are mounted on the spindle, fixture, and nearby structures to monitor the milling process. The collected data are processed to extract various signatures and the key dominated indexes are identified. Finally, three multilayer perception (MLP) artificial neural network models are established. These models trained by different input features are compared to examine the influence of selected sensors and indexes on the prediction accuracy. The results show that with appropriate sensors and signatures, even with less amount of experimental data, the model can indeed achieve a better prediction. Therefore, a proper selection of indexes guided by physical knowledge based experiment or theoretical investigation would be critical.
Pharmacological Potentials, Characterization and Fatty Acids Profile of Persea americana Mill. (Avocardo) Seed Oil Using Gas Chromatography-Mass Spectroscopy

In this study, Avocado seed oil was extracted using sohxlet apparatus, n-hexane: chloroform (30:70) at 70°C for 3 h, characterized and the pharmacological potentials assessed. The percentage oil yield was 36.93%, brown in colour and remained liquid at room temperature. The acid, peroxide and iodine values were 7.86 mg/KOH/g, 42.11 meq/ Kg-1 and 33.21 mg/100 g respectively. The identified fatty acids included Dodecanoic acid (1.05%), tetradecanoic acid (0.86%), n-hexadecanoic acid (13.19%), hexadecanoic acid (4.12%), 9,12-octadecanoic acid (0.28%), 11-octadecanoic acid (0.45%), oleic acid (40.33%), n-hexadecanoic acid (9.69%), 1,E-11-Z-13-octadecatriene (11.45%), 1,E-11-Z-13octadecatriene (6.78%), undecylanic acid (6.31%), palmitaldehyde diisopentylacetal (1.14%), 9-octadecanal (1.18%) and (E)-13-docosenoic acid (3.17%). The presence of fatty acids such as undecylenic acid, oleic acid and other essential fatty acids suggests the seed oil could possess important pharmacological properties.
Usage of bioactivated PCL nanofiber as a fluoxetine capturing matrix in milk

ABSTRACT In this study, for the first time, polycaprolactone (PCL) nanofiber matrix was bioactivated for the removal of fluoxetine from milk. Bioactivated nanofiber was prepared by immobilizing fluoxetine antibody on PCL nanofiber matrix. The fluoxetine removal efficiency of bioactivated nanofiber in milk was found to be approximately 93.6%. This removal did not significantly change the biochemical composition of milk. In conclusion, as a novel product, bioactivated nanofibrous PCL matrix can be used for the removal of drugs or unwanted chemicals from breast milk or from other fluids.
Nutritional evaluation of the peels from Citrullus lanatus and Manihot esculenta, an insight into the conversion of waste to food

Background: Huge quantity of cassava and watermelon wastes are daily discharged to the environment with unwholesome consequences. Therefore, research into the effective utilization of these agricultural by-products is of global interest. Methods: The present study evaluated the proximate, minerals, and amino acid compositions of cassava and watermelon peels using standard procedures. Results: The results revealed that carbohydrate is the most abundant proximate contents of both the cassava (82.14±0.42%) and watermelon (62.58±0.78%) peel, followed by crude fiber (5.51±0.06% and 18.90±0.04%), moisture (8.31±0.04% and 5.20±0.07%), crude ash (1.25±0.03% and 7.25±0.04%) for cassava and watermelon peels respectively, while crude fat (0.98±0.03% and 3.92±0.06%) is the least abundant proximate in both samples. Magnesium is the most abundant mineral contents of both the cassava (79.50±4.45Mg/100g) and watermelon (75.53±3.70Mg/100g) peel, followed by sodium (62.35±0.79 Mg/100g and 52.24±3.24 Mg/100g), potassium (22.12±1.34 and 32.65±2.01 mg/100g) for cassava and watermelon peels respectively while copper (0.73±0.05 Mg/100g and 0.67±0.64 Mg/100g) was the least abundant minerals in both samples. The total amino acid compositions of 66.31±4.56 g/100g and 41.80±2.68 g/100g were recorded for cassava and watermelon peel. Glutamic acid (9.96±0.06g/100g) and leucine (4.03±0.05 mg/100g) the most abundant amino acid in cassava and watermelon seed respectively. Conclusion: In conclusion, the peels of cassava and water melon examined, have appreciable levels of nutrients compositions that can be incorporated into human and animal feed formulation.
Ciliates as Symbionts

Although many ciliates are free-living, more than 140 families of ciliates (Alveolata, Ciliophora) include symbiotic species of animals. Symbiosis, defined as an interaction between two species, is analyzed in this chapter to show a wide diversity of symbiotic systems in ciliates (epibiosis, commensalism, mutualism, and parasitism), providing some data about ciliate strategies showing their success as symbionts. Some species are free-living as well symbionts, facultative symbionts, and obligate symbionts. Analysis of reconstructions of ancestral state evidence that the parasitism arose numerous times and independently among the lineages of ciliates. At least three evolutionary routes can be traced: (1) transition from free-living to mutualism and parasitism, (2) transition from free-living to parasitism, and (3) regression from parasitism to free-living. The evolution of the symbiosis in ciliates demonstrates a higher diversification rate concerning free-living ciliates. The analysis of the evolution of the life cycles complexity, exploring molecular data of the phases of the ciliate cycle in their hosts is also essential. We propose new approaches for an integrative study of symbiotic ciliates.
Assessing the Role of Leadership Mechanisms for Inter-agency Collaboration and Information Sharing Success in Indonesia

Previous studies have identified leadership as an essential factor influencing inter-agency collaboration and information sharing in government settings. This study argues that some unique characteristics of inter-agency information sharing (IIS) initiatives across different jurisdictions and levels of government call for particular types of leadership. Specifically, this study uses data from in-depth interviews with fifteen public officials in Indonesia to better understand the role of leadership in inter-agency collaboration and information sharing initiatives. Findings from the interviews support two leadership mechanisms influencing IIS in Indonesia: executive involvement and exercise of formal authority, whereas the role of informal leaders seems to be less important in this case. It seems that in some developing countries such as Indonesia, informal leaders are not as influential to the success of IIS initiatives as formal ones, due to the influence of organizational culture.
Emulsions and Emulsifiers

Emulsions are heterogeneous systems of one liquid dispersed throughout another in the form of droplets usually exceeding 0.1 ? m in diameter. Emulsions are generally categorised into single emulsions which include water-in-oil and oil-in-water and multiple emulsions including water-in-oil-in-water and oilin-water-in-oil. Emulsions are prepared by phase inversion method, membrane emulsification method, dry gummethod, andwet gummethod. Continental/drygummethod or bottle/general method are most commonly employed techniques for emulsification. Membrane emulsification method which is based on principle of dispersing one immiscible phase (dispersing phase) into another phase (continuous phase) by applying pressure is used for the preparation of multiple emulsions. Emulsifier / emulgentis a substance which stabilises the emulsion by increasing the kinetic energy. Emulsifiers are generally classified based on their chemical structure into four types including synthetic, natural, finely divided solids, and auxillary agents; by mechanism of action into three categories including monomolecular films, multimolecular films, and solid particle films.There are different theories which help in understanding emulsification process which include surface tension theory, surface orientation theory, and plastic/interfacial film theory.Stability of emulsion is one of the critical parameter which is difficult to attain. The instability of emulsions is categorised into flocculation, creaming, coalescence, and breaking which were further detailed in the text.
Low-resistance stretchable electrodes using a thick silver layer and a PDMS-PDMS bonding technique

In this paper, a stretchable silver electrode having high stretching capability and good stability is demonstrated using a poly (dimethyl siloxane) (PDMS) substrate bonding technique. By bonding two silver electrodes (bonding electrode), low initial sheet resistance and good stretching capability under a 38% strain condition were achieved. It was also shown that the bonding electrode has good stability under a 1000-cycle prolonged stress condition (15% strain). The origin of the good stretching capability of the bonding sample is explained as percolation of the current path between the top and bottom electrodes. Using a resistor network model, the percolation of the current path was quantitatively characterized.
Co-working, co-learning and culture – co-creation of future tech lab in Namibia

Purpose Future places for learning and working are digitally and physically integrated hybrid environments. The purpose of this paper is to analyse the co-creation process of the remote presence-based digital and physical co-working and co-learning place. The context is cross-cultural when Finnish space approach is applied and further developed in Namibia. Design/methodology/approach A qualitative case study is conducted of the Future Tech Lab (FT Lab) in the University of Namibia’s main campus. The case study of the FT Lab is about 200m2 space with three different zones in the University of Namibia’s main campus. The physical solution encourages collaboration and technical solutions interlink the place overseas by using the remote presence. The data are gathered by using document analysis, observations, participatory workshops and interviews including structured questionnaire. Findings The action design research approach is a functional framework to co-create hybrid environments in two ways. It helps to design digital and physical solutions as integrated entity. Additionally, it provides a tool to analyse decision-making processes as well as design initiatives, also from the cultural perspective. Both Finnish and Namibian cultures are normative and feminine, which helped the realisation of the project based on mutual trust. However, the differences in power distance were affecting the process fluency and decision-making processes. Research limitations/implications The findings indicate that the co-design of the hybrid-learning environment sets requirements for the physical solution such as surface materials for premises and retrofitting of technology, which need to be considered by co-creation from the shared vision to realisation of the space. The co-creation involves many stakeholders, and cultural differences have a different impact on various stages of the co-creation process. Originality/value The cultural context in the case study provides an interesting comparison between the Finnish and Namibian approach. The remote presence and its requirements provide new knowledge and guidelines for co-creation of hybrid environments.
Admittance‐inverter‐based two‐section filtering power divider with OVER 40‐dB output isolation

An admittance‐inverter‐based two‐section topology is proposed for filtering power dividers in this article aiming at high and wideband output isolation. Different from the classic two‐section Wilkinson power dividers, the bulky quarter‐wave transmission lines are removed and replaced by using two pairs of admittance inverters, which are realized by the input external quality factor (Qe‐in) and coupling coefficient (k12), respectively. Since the electric size of these coupling effects (Qe‐in and k12) are negligible, a significant size reduction is easily realized. In addition, two isolation elements are added between the input resonators and the output ones, respectively. Two‐prefect absorption points are accordingly realized in |S23|, indicating wider and higher output isolation compared with the reported designs using one isolation element. For demonstration, one two‐section filtering power divider is designed and fabricated. The circuit size is only 0. 009λg2, while the output isolation exceeds 41.5 dB over the passband.
CDEC: a constrained deep embedded clustering

PurposeThe aim of this study is to propose a deep neural network (DNN) method that uses side information to improve clustering results for big datasets; also, the authors show that applying this information improves the performance of clustering and also increase the speed of the network training convergence.Design/methodology/approachIn data mining, semisupervised learning is an interesting approach because good performance can be achieved with a small subset of labeled data; one reason is that the data labeling is expensive, and semisupervised learning does not need all labels. One type of semisupervised learning is constrained clustering; this type of learning does not use class labels for clustering. Instead, it uses information of some pairs of instances (side information), and these instances maybe are in the same cluster (must-link [ML]) or in different clusters (cannot-link [CL]). Constrained clustering was studied extensively; however, little works have focused on constrained clustering for big datasets. In this paper, the authors have presented a constrained clustering for big datasets, and the method uses a DNN. The authors inject the constraints (ML and CL) to this DNN to promote the clustering performance and call it constrained deep embedded clustering (CDEC). In this manner, an autoencoder was implemented to elicit informative low dimensional features in the latent space and then retrain the encoder network using a proposed Kullback–Leibler divergence objective function, which captures the constraints in order to cluster the projected samples. The proposed CDEC has been compared with the adversarial autoencoder, constrained 1-spectral clustering and autoencoder + k-means was applied to the known MNIST, Reuters-10k and USPS datasets, and their performance were assessed in terms of clustering accuracy. Empirical results confirmed the statistical superiority of CDEC in terms of clustering accuracy to the counterparts.FindingsFirst of all, this is the first DNN-constrained clustering that uses side information to improve the performance of clustering without using labels in big datasets with high dimension. Second, the author defined a formula to inject side information to the DNN. Third, the proposed method improves clustering performance and network convergence speed.Originality/valueLittle works have focused on constrained clustering for big datasets; also, the studies in DNNs for clustering, with specific loss function that simultaneously extract features and clustering the data, are rare. The method improves the performance of big data clustering without using labels, and it is important because the data labeling is expensive and time-consuming, especially for big datasets.
Transnational Representation in Global Labour Governance and the Politics of Input Legitimacy

Private governance raises important questions about democratic representation. Rule making is rarely based on electoral authorisation by those in whose name rules are made—typically a requirement for democratic legitimacy. This requires revisiting the role of representation in input legitimacy in transnational governance, which remains underdeveloped. Focussing on private labour governance, we contrast two approaches to the transnational representation of worker interests in global supply chains: non-governmental organisations providing representative claims versus trade unions providing representative structures. Studying the Bangladesh Accord for Fire and Building Safety, we examine their interaction along three dimensions of democratic representation: 1) creating presence, 2) authorisation, and 3) accountability to affected constituents. We develop a framework that explains when representative claims and structures become complementary but also how the politics of input legitimacy shape whose interests get represented. We conclude by deriving theoretical and normative implications for transnational representation and input legitimacy in global governance.
German and Swedish students going digital: do gender and interaction matter in quality evaluation of digital learning systems?

ABSTRACT This study aims to examine the difference in students’ satisfaction with the Quality Characteristics (QualChar) of the Digital Learning Systems (DLs) with regards to gender and frequency of interaction between students-students and students-teachers. A cross-sectional online quantitative survey was used to collect data from English language business administration and social sciences online master’ students at eight German and Swedish Universities. The t-test shows that in both German and Swedish settings male students are more satisfied with the QualChar of DLs. Further analysis of multidimensional QualChar shows that German male students are more satisfied with the intrinsic and contextual QualChar of DLs – contextual, accessible, and actionable QualChar of DLs are important for Swedish male students. Concerning students’ interaction frequency with teachers and students, the ANOVA test revealed a statistical difference in the German students’ satisfaction with QualChar of DLs – while no difference was found for Swedish students. German student respondents are active in their interaction with teachers and other students which is associated with their satisfaction with QualChar of DLs. This study contributes to the literature in shedding light on the German and Swedish students’ satisfaction with the QualChar of the DLs highlighting the differences by gender and interaction frequency.