Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and Strategies of Educational Leadership to Sustain the International Baccalaureate Diploma Programme (IBDP) in a Malaysian Premier Public School

The IBDP is known worldwide as a high-standard diploma programme that aims to cultivate students with the attitudes, knowledge, and skills of the 21st-century education. In the education management aspect, this programme requires extensive planning, organising, sound leadership, and monitoring of the schools’ systems to meet the standards set up by the International Baccalaureate Organisation (IBO). Due to the challenges that persist in each of the management functions, sustainability of the IBDP requires the exploration of both challenges and strategies from the perspective of leadership in relation to the context. Therefore, the purpose of this study is to explore and explain how educational leadership is practised to sustain the IBDP in a Malaysian premier public school. An in-depth qualitative approach was carried out to explore two major areas that consist of strategies and challenges, while semi-structured interviews were conducted with 20 participants comprising of top-level leaders and experienced teachers in the public IB school. These interviewees were chosen due to their instrumental roles as pioneers and leaders since the establishment of the programme in the school. Data analysis through open-coding, axial coding, and selective coding revealed that top-level leaders and experienced teachers of various subjects face various internal and external challenges in maintaining the sustainability of IBDP, such as student-related challenges, teacher-related challenges, teaching and learning processes, external assessments, school facilities, financial problems, and human resource management. Findings also listed various strategies taken by the principal to sustain the IBDP in the Malaysian premier public school. For the purpose of transferability and implication to the context of IB in a Malaysian premier public school, future leaders who are taking over the helm of leadership in the organisation would need to learn from both failures and successes of strategies in relation to their internal and external challenges to continually sustain and thrive in the future.
The spatio-temporal distribution of He (23S1) metastable atoms in a MHz-driven helium plasma jet is influenced by the oxygen/nitrogen ratio of the surrounding atmosphere

The density of helium He (23S1) metastable atoms is measured in a 1.6 mm diameter MHz-driven atmospheric pressure helium plasma jet by laser absorption spectroscopy with spatial and temporal resolution. The surrounding atmosphere of the jet is varied from pure oxygen to pure nitrogen with a gas shielding device. The highest metastable density of 1.3 × 1013 cm−3 is obtained in the center of the jet close to the nozzle exit at normal atmospheric air conditions. Within 0.3 mm in the radial direction and 2 mm in the axial direction, the He metastable density drops below the detection limit. The obtained He metastable lifetime is almost independent of the shielding gas composition. By analyzing the diffusion of shielding gas species into the effluent it is concluded that their density is too low to explain the observed He metastable lifetime. Instead, impurities from the feed gas, especially water molecules, are more likely to be responsible. However, a drastic change in metastable He density is observed when decreasing the amount of oxygen in the shielding gas. The lower the oxygen amount, the lower the metastable He density. For pure nitrogen, no He metastables are detected at all. By exchanging nitrogen with argon, a similar behavior is observed. Thus, it is concluded that it is the absence of ambient oxygen rather than the elevated presence of nitrogen, which is responsible for the observed decrease in the He (23S1) density.
Switchable Reversible Addition–Fragmentation Chain Transfer (RAFT) Polymerization in Aqueous Solution, N,N-Dimethylacrylamide

Reversible addition–fragmentation chain transfer (RAFT) polymerization of a “more activated monomer” (MAM), N,N-dimethylacrylamide (DMAm), has been successfully achieved in aqueous solution using an acid/base switchable pyridyl-substituted dithiocarbamate RAFT agent. The effect of strength (pKa) and stoichiometry of the acid used to switch the RAFT agent on the molecular weight and dispersity of poly(N,N-dimethylacrylamide) (PDMAm) were examined, making use of high-throughput protocol. Best control was achieved with a stoichiometric amount of the strongest acid investigated, p-toluenesulfonic acid monohydrate. Use of weaker acids (higher pKa) or less than stoichiometric amounts of acid with respect to RAFT agent resulted in broader molecular weight distributions. These results can be rationalized in terms of the extent of protonation of the pyridine nitrogen of the RAFT agent (pKa ∼ 3.13). The preparation of unimodal low dispersity block copolymers of PDMAm with the “less-activated” monomers (LAMs) N-viny.
PURCHASE INTENTION TOWARDS ENVIRONMENTALLY FRIENDLY PRODUCTS AMONG CONSUMERS IN SOUTH AFRICA. APPLYING THE THEORY OF PLANNED BEHAVIOUR

The effects of global warming and the changing climatic conditions have increased the need for environmentally friendly products. South Africa, as a developing nation, has not developed sufficient infrastructure for sustainable behaviour and for this reason its consumers have little exposure to sustainability practices compared to the developed countries. The purpose of this study was to investigate the purchase intention of South African consumers towards environmentally friendly products using the Theory of Planned Behaviour. A self-administered questionnaire was distributed among South African consumers and a total of 200 questionnaires were deemed legible (Comment to author: do you mean valid ? ) for analysis. Factor analysis was used to identify the factors that influence purchase intention of environmentally friendly products. Correlation analysis was used to establish the relationship among variables. Regression analysis was used to investigate the predictive influence of independent variables on the dependent variable. A statistically significant correlation between the factors that influence purchase intention of environmentally friendly products and purchase intention was found. Regression analysis indicated that attitudes and subjective norms had an insignificant influence on the purchase intention of environmentally friendly products. Conversely, perceived behavioural control, environmental concern and environmental knowledge contributed significantly towards the intention to purchase environmentally friendly products. Tangible action is required to encourage everyone to know and understand the significance of purchasing environmentally friendly products.
Nucleation mechanisms of aromatic polyesters, PET, PBT, and PEN, on single-wall carbon nanotubes: early nucleation stages

Nucleation mechanisms of poly (ethylene terephthalate) (PET), poly (butylene terephthalate) (PBT), and poly (ethylene naphthalate) (PEN) on single-wall carbon nanotubes (SWNTs) are proposed, based on experimental evidence, theoretical epitaxy analysis, and semiempirical quantum chemical calculations. In order to elucidate early nucleation stages polyester-coated nanotubes were obtained from highly diluted solutions. High-resolution transmission electron microscopy (HRTEM) revealed helical morphologies for PET/SWNTs and PEN/SWNTs and the formation of lobules with different orientations for PBT/SWNTs. To explain the morphological behavior one model was proposed based on crystallographic interactions, that is, epitaxy. Theoretical epitaxy calculations indicated that epitaxy is not possible from the strict epitaxy point of view. Instead, aromatic self-assembly mechanism was proposed based on p-p interactions and the chirality of the nanotube. It was proposed that themechanism implies two steps to produce helical or lobular morphologies with different orientations. In the first step polymer chains were approached, aligned parallel to the nanotube axis and adsorbed due to electrostatic interactions and the flexibility of the molecule. However, due to p-p interactions between the aromatic rings of the polymer and the nanotube, in the second step chains reoriented on the nanotube surface depending on the chirality of the nanotube. The mechanism was supported by semi-empirical calculations.
Intelligent Dolls and robots for the treatment of elderly people with dementia

Sergio Márquez-Sánchez, Sara Mora-Simon, Jorge Herrera-Santos, Ana Olga Roncero, and Juan M. Corchado Intelligent Dolls and robots for the treatment of elderly people with dementia ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal Regular Issue, Vol. 9 N. 1 (2020), 99-112 eISSN: 2255-2863 https://adcaij.usal. es Ediciones Universidad de Salamanca cc by-nc-nd ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal Regular Issue, Vol. 9 N. 1 (2020), 99-112 eISSN: 2255-2863 DOI: https://dx.doi. org/10.14201/ADCAIJ20209199112
Hydrothermal Upgrading of Korean MSW for Solid Fuel Production: Effect of MSW Composition

In Korea, municipal solid waste (MSW) treatment is conducted by converting wastes into energy resources using the mechanical-biological treatment (MBT). The small size MSW to be separated from raw MSW by mechanical treatment (MT) is generally treated by biological treatment that consists of high composition of food residue and paper and so forth. In this research, the hydrothermal treatment was applied to treat the surrogate MT residue composed of paper and/or kimchi. It was shown that the hydrothermal treatment increased the calorific value of the surrogate MT residue due to increasing fixed carbon content and decreasing oxygen content and enhanced the dehydration and drying performances of kimchi. Comparing the results of paper and kimchi samples, the calorific value of the treated product from paper was increased more effectively due to its high content of cellulose. Furthermore, the change of the calorific value before and after the hydrothermal treatment of the mixture of paper and kimchi can be well predicted by this change of paper and kimchi only. The hydrothermal treatment can be expected to effectively convert high moisture MT residue into a uniform solid fuel.
Residual Neural Network Architectures to Improve Prediction Accuracy of Properties of Materials

Properties in material composition and crystal structures have been explored by density functional theory (DFT) calculations, using databases such as the Open Quantum Materials Database (OQMD). Databases like these have been used currently for the training of advanced machine learning and deep neural network models, the latter providing higher performance when predicting properties of materials. However, current alternatives have shown a deterioration in accuracy when increasing the number of layers in their architecture (over-fitting problem). As an alternative method to address this problem, we have implemented residual neural network architectures based on Merge and Run Networks, IRNet and UNet to improve performance while relaxing the observed network depth limitation. The evaluation of the proposed architectures include a 9:1 ratio to train and test as well as 10 fold cross validation. In the experiments we found that our proposed architectures based on IRNet and UNet are able to obtain a lower Mean Absolute Error (MAE) than current strategies. The full implementation (Python, Tensorflow and Keras) and the trained networks will be available online for community validation and advancing the state of the art from our findings.
Contributions of Toluene and α-Pinene to SOA Formed in an Irradiated Toluene/α-Pinene/NOx/ Air Mixture: Comparison of Results Using 14C Content and SOA Organic Tracer Methods

An organic tracer method, recently proposed for estimating individual contributions of toluene and α-pinene to secondary organic aerosol (SOA) formation, was evaluated by conducting a laboratory study where a binary hydrocarbon mixture, containing the anthropogenic aromatic hydrocarbon, toluene, and the biogenic monoterpene, α-pinene, was irradiated in air in the presence of NOx to form SOA. The contributions of toluene and α-pinene to the total SOA concentration, calculated using the organic tracer method, were compared with those obtained with a more direct 14C content method. In the study, SOA to SOC ratios of 2.07 ± 0.08 and 1.41 ± 0.04 were measured for toluene and α-pinene SOA, respectively. The individual tracer-based SOA contributions of 156 μg m-3 for toluene and 198 μg m-3 for α-pinene, which together accounted for 82% of the gravimetrically determined total SOA concentration, compared well with the 14C values of 182 and 230 μg m-3 measured for the respective SOA precursors. While there are unce.
Fluorescence detection of aromatic amines and photocatalytic degradation of rhodamine B under UV light irradiation by luminescent metal–organic frameworks

The detection of trace amounts of aromatic amines is significantly important for security concerns and pollution control. Two multifunctional metal–organic frameworks (MOFs), [ZnL·H2O]n (1) and [CdL·H2O]n·2nH2O (2) (L = 5-aminoisophthalic acid), were strategically chosen for the detection of aromatic amines pollutants. The fluorescent experiments show that the two MOFs can selectively detect aromatic amines with high sensitivity. Among the given analytes, p-nitroaniline, an electron-deficient analyte, significantly quenched the fluorescence intensities of 1 and 2. In contrast, other aromatic amines enhanced the fluorescence intensities of 1 and 2 to some extent. In particular, diphenylamine gives the most apparent enhancement effect than those of others under the same experimental conditions. Moreover, the photocatalytic activities of the two MOFs were also determined by UV light induced photodegradation of Rhodamine B (RhB) experiments. All the results indicate that the complexes studied are stable and good candidates for both as heterogeneous photocatalysts and detectable materials for aromatic amines.
Local binary pattern defect recognition approach for the friction stir welded AA 1200 and AA 6061-T6 aluminum alloy

The research reported in this paper focuses on the application of local binary patterns (LBPs) for surface defects detection. The surface defection detection algorithm for friction stir welded aluminum plates is the key part of the entire surface defect recognition system. Two different grades i.e AA 1200 and AA 6061 plates were similarly joined with the help of Friction Stir Welding process. Python codes for the proposed algorithm were executed on Google Colaboratory platform. The results obtained prove that the local binary patterns method can be used for real-time surface defects detection in friction stir welded joints.
Learning of Evaluation Functions on Mini-Shogi Using Self-playing Game Records

In this study, we applied the machine learning method of evaluation functions, which has been used in Shogi recently, to Mini-Shogi and verify whether the method is also effective in Mini-Shogi. Specifically, we developed Mini-Shogi program based on YaneuraOu and the program learned evaluation functions using self-playing game records. Our program won the UEC-cup Mini-Shogi Tournament in March 2020 and recorded over 70% win rate against the leading programs. The result analyzing self-playing game records suggests there is a possibility that the second player has an advantage in Mini-Shogi.
Clicking throughout the year: sperm whale clicks in relation to environmental conditions off the west coast of South Africa

Knowledge of cetacean occurrence and behaviour in southern African waters is limited, and passive acoustic monitoring has the potential to address this gap efficiently. Seasonal acoustic occurrence and diel-vocalizing patterns of sperm whales in relation to environmental conditions are described here using passive acoustic monitoring data collected off the west coast of South Africa. Four autonomous acoustic recorders (AARs) were deployed on 3 oceanographic moorings from July 2014 to January 2017. Sperm whale clicks were detected year round in most recording sites, with peaks in acoustic occurrence in summer and late winter through spring. Dielvocalizing patterns were detected in winter, spring and summer. Higher percentages of sperm whale clicks were recorded by AARs deployed at 1100 m water depth compared to those concurrently deployed at 850 and 4500 m, likely inferring that the whales exhibited some preference to water depths around 1100 m. Acoustic propagation modelling suggested a maximum detection range of 83 km in winter for sperm whale clicks produced at 1100 m. Random forest models classified daylight regime, sea surface height anomaly and month of the year as the most important predictors of sperm whale acoustic occurrence. The continuous acoustic occurrence of sperm whales suggests that the study area supports large biomasses of prey to sustain this species’ food requirements year round. This is the first study to describe the seasonal acoustic occurrence and diel-vocalizing patterns of sperm whales off the west coast of South Africa, extending knowledge of the species previously available only through whaling records.
A 42–62 GHz Transformer-Based Broadband mm-Wave InP PA With Second-Harmonic Waveform Engineering and Enhanced Linearity

Indium phosphide (InP) heterojunction bipolar transistors (HBTs) with <inline-formula> <tex-math notation="LaTeX">$f_{t}/f_{\max}$ </tex-math></inline-formula> of 350/675 GHz are studied and explored for a linear, high efficiency and broadband power amplifiers (PAs) at mm-wave frequencies. Unlike the conventional transmission-like-based design, this article presents a compact, broadband transformer-based power combining and impedance matching using the waveform engineering approach. We present, for the first time, mm-wave (40–60 GHz) InP topologies incorporating the following: 1) on-chip transformer for broadband, efficient and compact impedance matching and power combining; 2) synthesis of optimal second-harmonic impedance through transformer center tap to achieve high-efficiency differential PA operation; and 3) biasing techniques to reduce AM–PM distortion for linearity enhancement. This work reports a transformer-based push–pull InP PA in <inline-formula> <tex-math notation="LaTeX">$0.25~\mu \text{m}$ </tex-math></inline-formula> technology across 42–62 GHz demonstrating a peak power added efficiency (PAE) of 39.5% and peak <inline-formula> <tex-math notation="LaTeX">$P_{\text{sat}}$ </tex-math></inline-formula> of 20.6 dBm. The PA supports 4 GHz bandwidth at 52 GHz with an EVM of −22.9 dB and an adjacent channel leakage ratio (ACLR) of −32 dBc for an 8 Gb/s QPSK signal at 13.3 dBm average output power. This work presents one of the highest efficiency with wide bandwidth and highest linearity mm-wave PAs in integrated technology.
Intrinsic Plasticity for Online Unsupervised Learning Based on Soft-Reset Spiking Neuron Model

Intrinsic plasticity (IP) is an unsupervised, self-adaptive, local learning rule that was first found in biological nerve cells, and has been shown to be able to maximize neuronal information transmission entropy. In this article, we propose a soft-reset leaky integrate-and-fire (LIF) model, a spiking neuron model based on widely used LIF neurons, with a new IP learning rule that optimizes the neuronal membrane potential state to be exponentially distributed. Previous studies have generally used such as spiking neuron expected firing rate as the target variable to maximize output spike distribution. In contrast, the proposed soft-reset model can avoid the problem that conventional LIF neuronal membrane potential is not fully differentiable, hence the proposed IP rule can directly regulate the membrane potential as an auxiliary “output signal” to desired distribution to maximize its information entropy. We experimentally evaluated the proposed IP rule for pattern recognition on the spiking feed-forward and spiking convolutional neural network models. Experimental results verified that the proposed IP rule can effectively improve spiking neural network computational performance in terms of classification accuracy, spiking inference speed, and noise robustness.
Multi-Objective Sizing of Battery Energy Storage Systems for Stackable Grid Applications

The deployment of battery energy storage systems (BESS) is rapidly increasing as a prominent option to support future renewable-based energy systems. However, despite its benefits from a technical perspective, there are still challenges related to its economic viability. On the other hand, sizing BESS considering only their economic viability can be impractical because financial objectives could be in conflict with other aspects, such as battery degradation and grid impact. This article proposes a multi-objective approach to determine the optimal size of BESS providing stackable services, such as frequency regulation and peak shaving. The proposed optimization method comprises financial and technical aspects represented by the payback period, battery life span, and grid impact. Given a set of market rules, a cost-benefit function, a regulation signal, consumption profiles and grid data, an enumerative approach is adopted to provide a set of Pareto optimal solutions. The performance of the proposed method is validated using the regulation market structure from PJM interconnection. Furthermore, a real 240-node distribution grid is used to assess the grid impact via OpenDSS. Simulations demonstrate that the proposed approach is a flexible and practical decision-making tool that investors can exploit when designing new BESS.
Stabilization to prevent soil erosion using vetiver (Chrysopogon zizanioides L.) in slopes: a field case study of selected grounds at Guatemala

The effects of Chrysopogon zizanioides (vetiver) on the hydrophysical properties of soils and infiltration rate have been determined. Thus, it has been examined the stabilization to prevent soil erosion using vetiver in slopes, studying a field case of selected grounds at Guatemala. The particle size analysis of the soil samples showed a predominant sand fraction and a plasticity index of 7.9 %. The results indicated that these soils were fairly acid with worthless salinity and non-swelling. The specific surface area, determined by nitrogen adsorption-desorption analysis, ranged from 11.7 - 15.5 m2 /g and the pore sizes between 17-160 µm, which changed to 20-100 µm, with predominant pore size around 40 µm after cultivation. The characteristics of the soils showed the presence of cohesion (2.05 t/m2) and an internal friction angle Ф = 31. 69º. After the plantation, it has been found a decrease in the cohesion and an increase of the internal friction angle. The sowing of vetiver affected the infiltration characteristics of the soil. An analysis using the Kostiakov-Lewis classical model, with a mathematical fitting, has been performed. From these results, it has been deduced that the slope protected using this plant diminished its infiltration rate, being associated to the compaction caused by the plant roots. The present results demonstrated that the plantation of vetiver is effective to stabilize and prevent slopes from the soil erosion caused by severe rainfall events.