Miracle-dz/UniFAR-FTUs huggingface dataset:
Pretreated Sugarcane Bagasse Result in More Efficient Degradation by Streptomyces sp S2

Streptomyces genera plays important role in lignocellulose degradation. Many research founds Streptomyces has cellulolytic and ligninolytic enzymes that sufficient to degrade lignocellulosic materials. However, minimum lignocellulosic material condition that can efficiently degraded by Streptomyces sp. has not been fully understood. In this research, three pretreament conditions (physical, alkaline-hydrotermal, and hydrogen-peroxide chemical treatments) of sugarcane bagasse used as lignocellulosic material, to further degraded by Streptomyces sp. S2. Lignocellulose component measurement conclude that raw (physical treated only) bagasse wasn’t efficiently degraded by Streptomyces sp S2. Hydrogen-peroxide was effective on reducing both syringil and guaiacyl lignin, meanwhile alkaline-hydrotermal pretreatment was very effective on reducing syringil lignin. This study suggest that hydrogen-peroxide pretreatment can be used in many type of lignocellulosic material, which can be further degraded by Streptomyces sp. S2. Alkaline-hydrotermal preteatment on the other hand is best suited to degrade lignocellulosic material that have high percentage of syringil lignin.
A method of evaluating flicker and flicker-reduction strategies in power systems

The UIE/IEC flicker characteristics of a three-phase power system which includes resistance welders are evaluated in this paper. Welder operation produces cyclic flicker which leads to customer complaints. An adaptive VAr compensator (AVC) has been installed to reduce flicker. In order to investigate the effectiveness of the AVC and to set the stage for the analysis of alternative control strategies, a detailed computer model of the given power system, including the AVC, has been developed. The model also includes a simulation of the UIE/IEC flickermeter to determine the effectiveness of the AVC in an objective manner. The simulated system response is compared with actual system measurements revealing excellent agreement. The modeling methodology set forth provides an efficient and convenient means of evaluating complex flicker resulting in a simple measure of human irritability.
External-cavity actively mode-locked GCSEL (grating coupled surface emitting laser) and amplification characteristics of GCSOA (grating coupled surface emitting semiconductor optical amplifier)

We demonstrate an external cavity, active mode-locked GCSEL. The optical pulse duration from the actively mode-locked oscillator is 22.6ps and a 3 dB optical spectrum bandwidth is 0.07nm at 976nm. The average power from the oscillator is 0.72mW and its peak power is 108mW. The amplification characteristics of a GCSOA, optically injected with a continuously operated external cavity GCSEL, are also demonstrated. Despite the observation of lasing from the device, injection locking can be performed using an external source. At 4A peak current injection, 375mW output is achieved with 12mW injection.
Penerokaan aset manusia dalam kalangan peserta projek kebun komuniti

One of the programs introduced by the government to improve the well-being of the residents in the city is the urban agriculture program through community garden projects. The main goal of this project is to reduce or overcome the economic, social and environmental problems faced by the residents living in the city. However, the success rate of this project remains low and some expect the project to be less successful. Previous studies have identified that human assets are an important element in developing agro-community projects. Therefore, this study was conducted to explore of human assets among community garden project participants. This study was conducted using a qualitative study involving 8 participants of community garden projects. Data were collected through in-depth interviews and follow-up observations. Interviews were recorded and then transcribed verbatim. The data were then analyzed and given codes, categories and sub-themes to develop the main theme to answer each question in this study. The study found that community garden project participants have strength in terms of human assets such as having good health, having nature, agricultural input seekers, information seekers, have high religious practices and do not give up easily. These elements of human assets have been used by project participants to increase crop yield. Human assets should be intensified from time to time in the development of sustainable community garden projects in line with the aspirations of the Ministry of Agriculture and Agro-based Industry to ensure national food security.
Vehicle Transient Air Conditioning Analysis: Model Development & System Optimization Investigations

The National Renewable Energy Laboratory (NREL) has developed a transient air conditioning (A/C) system model using SINDA/FLUINT analysis software. It captures all the relevant physics of transient A/C system performance, including two-phase flow effects in the evaporator and condenser, system mass effects, air side heat transfer on the condenser/evaporator, vehicle speed effects, temperature-dependent properties, and integration with a simplified cabin thermal model. It has demonstrated robust and powerful system design optimization capabilities. Single-variable and multiple variable design optimizations have been performed and are presented. Various system performance parameters can be optimized, including system COP, cabin cool-down time, and system heat load capacity. This work presents this new transient A/C system analysis and optimization tool and shows some high-level system design conclusions reached to date. The work focuses on R-134a A/C systems, but future efforts will modify the model to investigate the transient performance of alternative refrigerant systems such as carbon dioxide systems. NREL is integrating its transient air conditioning model into NRELs ADVISOR vehicle system analysis software, with the objective of simultaneously optimizing A/C system designs within the overall vehicle design optimization.
Engineering a Grimm approach to enhancing student engagement with health and safety lectures: a new perspective on an ancient pedagogy

Abstract In this article, we cast a critical eye over the current approach to the presentation of health and safety information and question the efficacy of conveying its relevance through isolated inductions and pictograms on lab scripts. An argument is made for the adoption of a more integrated approach to the delivery of the material to facilitate greater student engagement and provide a more coherent and repetitive reinforcement of the central messages. A strategy for revitalising student engagement is presented and relates to an exploration of storytelling as a medium through which to recognise the significance of safe practice. An innovative approach to the proactive involvement of the student body is presented that adopts the emerging literary techniques of flash fiction and harnesses eSerialisation to aid dissemination. The approach is eminently transferable across the engineering, life and physical sciences disciplines and can be implemented with few administrative or technological overheads.
A Social Anxiety Mobile Intervention for College Students Attending Therapy: A Usability and Acceptability Study

ABSTRACT Social anxiety is significantly prevalent among college students and frequently leads to school dropout and academic underachievement. Since university counseling services are often overburdened, a mobile-based cognitive behavioral intervention was designed to support students attending therapy for social anxiety and therapists. Our main goals are to evaluate usability and acceptability of this technological system developed by a multidisciplinary team. Twenty students and three therapists participated in the usability studies. To evaluate usability we utilized a thinking aloud and question asking protocol, and the system usability scale (SUS) to assess usability and satisfaction. SPICA app demonstrated usability scores above average and the large majority of students agreed that the app was easy to use and that they would use it frequently. As for the therapist platform (database) preliminary results indicated that the database is useful but some alterations are still necessary. SPICA app demonstrated usability and acceptability among college students. A more rigorous study is needed to assess the therapist platform but preliminary results demonstrate acceptability.
Neural networks to analyze surface tracking on solid insulators

Surface tracking on solid insulators is one of the most severe breakdown mechanisms associated with polymeric materials under long term service conditions. A wide range of relays can detect failure in a transmission line and prevent a total breakdown in the systems, but due to the non-healing characteristics of solid insulators, in most cases it might be too late to save the insulator after tracking initiation and growth. The method described here is employed mainly in detecting several conditions, such as discharges, leakage current, dry conditions, severe damage and tracking initiation. Initially a BPN (back propagation network) type NN (neural network) is trained with different signal types. Due to the nature of NN, which always require similar values of input nodes, the system uses the FFT (fast Fourier transform) of the input signal, which might have high amplitude frequency components other than the fundamental frequency depending an the condition of the surface. The system works on a real time basis and warns the user with the first indication of severe damage on the surface and can protect the insulator from excessive damage.
Information acquisition during decisionmaking processes: an exploratory study of decision roles in media selection

This paper reports on a field study that explores; (1) how sources and media used by managers change over time and across decisional role as decision making processes unfold; and (2) how the rate of information acquisition affects media selection. The results indicate that: face-to-face meetings are favored for the entrepreneur and negotiator roles; other face-to-face media and telephone calls are employed to discharge resource allocator activities; the telephone is widely used in all roles, and the velocity of information acquisition influences media selection during the decision making process. >
Steady State Performance and Simulation of Matrix Converter for Various Load

The matrix converter is superior to the PWM inverter drive, because of regeneration ability, sinusoidal input, sinusoidal output and highest limit of the voltage transfer ratio. This paper describes the basic operating principle with various load conditions. The matrix converter has received considerable attention due to th e following advantages. A large capacity and compact converter system can be designed because the system does not have any dc-link circuit and, as a result, does not need any energy storage component, such as a smoothing inductor or a smoothing capacitor. The system has high efficiency, because the number of devices connected in series is less in this system than in the conventional rectifier- inverter system. Four-quadrant operation is very easy. The theory of the three-phase to three phase matrix converter is dealt with and its switching angle equations are presented. Matrix converter operation is based on the calculated switching angles. Modeling and numerical simulations of converter loaded with passive (R. L) and active (induction motor) loads are performed. Simulation results are presented.
Encrypted XML Data Query Processing with Range Query

Without decrypting the encrypted blocks, it is difficult to query encrypted XML data. Inspired by Query-Aware decryption scheme, the paper extends the scheme to support range query with value index. Value index is based on order preserving encryption. The testing results indicate that the proposed scheme can complete a correct query processing, and support range query.
A Surrogate-Assisted Many-Objective Evolutionary Algorithm using Multi-Classification and Coevolution for Expensive Optimization Problems

Surrogate-assisted evolutionary algorithms have received a surge of attentions for their promising ability of solving expensive optimization problems. Existing surrogate-assisted evolutionary algorithms usually adopt the regression models and the binary classification models to guide the evolution of the population for solving the multiobjective optimization problems. However, the regression models will make the algorithm to be increasingly computation-expensive as the number of objectives increases, while the use of the binary classification models might suffer from the poor diversity since the diversified information of solutions cannot be reflected in these classification models. For this issue, this paper proposes a surrogate-assisted many-objective evolutionary algorithm using the cooperation of the multi-classification and regression models to improve the search quality while reducing the computational cost. Our approach includes two parts: At the model training stage, a multi-classification model is constructed to divide the whole population into several classes for ensuring diversity, a distance regression model and an angle regression model are used to select solutions with better convergence and diversity in each class; At the evolution stage, a coevolutionary framework is used to guide the evolution according to a new selection criterion. Experimental results verify the effectiveness of the proposed algorithm on a set of expensive test problems with up to 10 objectives.
An empirical and analytical study of forecasting practices and perceptions in the United Kingdom

Since way back in the 1970's, academic research has attempted to improve forecasting practice. Unfortunately, this process is still incomplete and ongoing. There has been little research in the forecasting area in incorporating forecasting techniques, systems and administration (Mentzer and Kahn, 1997). Several other problems have been identified upon reviewing the literature, such as the limited use of modern forecasting practices (Flores and Duran, 1998). In particular, quantitative methods were slow to gain acceptance in practice, whilst forecasting techniques are little known and little used. The purpose of our investigation is to find out if the findings from various related studies persist or have changed over time and whether there are any other factors involved in forecasting that should be highlighted in the current practice. The motivation for this research is to bridge the gap between theory and practice in order to improve forecasting practices and enhance the quality of forecasts. We carry out four types of study, namely pilot study, postal survey, case study and follow-up survey, and we base our work on several related publications (Wheelwright and Clarke, 1976; Sparkes and McHugh, 1984; Dalrymple, 1987; Winklhofer et al, 1996; Mahmoud et #/., 1992). We explain our findings using statistical analysis and we offer different ways of explaining the behaviour patterns of the factors involved in forecasting. We demonstrate links between particular variables by offering basic mathematical functions to describe the effects of changes and by presenting an application of methods for improving point predictions and cost functions (Goodwin, 1996 and Percy, 1993). This research contributes to the present literature on forecasting in which behavioural issues have not been as thoroughly explored as have quantitative methods. It is intended that our findings will strengthen principles and enhance strategies within organisations towards achieving the ultimate goal of accurate forecasting.
The role of adaptive thermal comfort in the prediction of the thermal performance of a modern mixed-mode office building in the UK under climate change

Climate change is becoming a serious issue for the construction industry, since the time scales at which climate change takes place can be expected to show a true impact on the thermal performance of buildings and HVAC systems. In predicting this future building performance by means of building simulation, the underlying assumptions regarding thermal comfort conditions and the related heating, ventilating and air conditioning (HVAC) control set points become important. This article studies the thermal performance of a reference office building with mixed-mode ventilation in the UK, using static and adaptive thermal approaches, for a series of time horizons (2020, 2050 and 2080). Results demonstrate the importance of the implementation of adaptive thermal comfort models, and underpin the case for its use in climate change impact studies. Adaptive thermal comfort can also be used by building designers to make buildings more resilient towards change.
Facing Disinformation: Narratives and Manipulative Techniques Deployed in the Czech Republic

Abstract Disinformation represents a pressing issue in the context of security and politics in the region (not only) of Central and Eastern Europe. With the conflict in Ukraine, European virtual space was flooded with online media offering alternative explanations concerning the situation in that country. So-called alternative media developed into trusted sources of information for part of society. Therefore, this paper analyzes in-depth the techniques of manipulation they use; in other words, the aim of the paper is to deconstruct their power over peoples’ hearts and minds. Through the case of the Czech Republic, we demonstrate modernized manipulation of public opinion based on a selective choice of topics and stories combined with properly chosen manipulative techniques controlling emotions and relativity.
Energy Efﬁcient Resource Allocation for 5G Heterogeneous Networks using Genetic Algorithm

The energy efﬁcient resource allocation scheme based on genetic algorithm (GA) for the downlink orthogonal frequency division multiple access (OFDMA) heterogeneous networks (HetNets) is developed in this paper. To maximize the spectrum efﬁciency for the ﬁfth generation (5G) mobile networks, frequency reuse-1 is employed. Thus, advanced inter-cell interference coordination techniques are required to mitigate the inter-cell interference for 5G HetNets. In this paper, the energy efﬁcient optimization problem based on coordinated scheduling is formulated, which is a mixed-integer nonlinear fractional programming problem and is intractable to solve directly. To tackle this, a two-step GA based scheme is proposed to solve the optimization problem. In the ﬁrst step, the resource blocks matrix is solved by normal GA in the spectral efﬁciency aspect with ﬁxed power distribution matrix, and then the power distribution matrix is obtained in the second step by non-dominated sorting genetic algorithm II (NSGA-II) with obtained resource blocks allocation matrix. Finally, the system level numerical evaluation process is provided to illustrate the effectiveness of the developed scheme.
A comparison of the integrated fuzzy object-based deep learning approach and three machine learning techniques for land use/cover change monitoring and environmental impacts assessment

ABSTRACT Recent improvements in the spatial, temporal, and spectral resolution of satellite images necessitate (semi-)automated classification and information extraction approaches. Therefore, we developed an integrated fuzzy object-based image analysis and deep learning (FOBIA-DL) approach for monitoring the land use/cover (LULC) and respective changes and compared it to three machine learning (ML) algorithms, namely the support vector machine (SVM), random forest (RF), and classification and regression tree (CART). We investigated LULC impacts on drought by analyzing Landsat satellite images from 1990 to 2020 for the Urmia Lake area in northern Iran. In the FOBIA-DL approach, following the initial segmentation steps, object features were identified for each LULC class. We then derived their respective attributes using fuzzy membership functions and deep convolutional neural networks (DCNNs), a deep learning method. The Fuzzy Synthetic Evaluation and Dempster-Shafer Theory (FSE-DST) also applied to validate and carryout the spatial uncertainties. Our results indicate that the FOBIA-DL, with an accuracy of 90.1% to 96.4% and a spatial certainty of 0.93 to 0.97, outperformed the other approaches, closely followed by the SVM. Our results also showed that the integration of Fuzzy-OBIA and DCNNs could improve the strength and robustness of the OBIA’s decision rules, while the FSE-DST approach notably improved the spatial accuracy of the object-based classification maps. While object-based image analysis (OBIA) is already considered a paradigm shift in GIScience, the integration of OBIA with fuzzy and deep learning creates more flexibility and robust OBIA decision rules for image analysis and classification. This research integrated popular data-driven approaches and developed a novel methodology for image classification and spatial accuracy assessment. From the environmental perspective, the results of this research support lake restoration initiatives by decision-makers and authorities in applications such as drought mitigation, land use management and precision agriculture programs.
China's Gold Statistical Arbitrage

This article tries to find an arbitrage strategy in the gold prices market of China. And the method is the linear regression based on the time serious date, the gold price, the gold companies' stock prices and other metals prices from 2002 to 2014, and the data of different period, so we tried to test every possible relationship which based on the financial theory between these dates. At last we find there really is a relationship which is statistic tested significantly between the gold price and gold company stock price and based on a special time period date, so we can base the relationship to build an arbitrage strategy, then we test it by the real world dates, and we found it is good, what is more, this method we can use it in the other similar market, for example, silver or oil. And this is not just a method, we can really use it. Keywords-Stock Price; Gold Price; Arbitrage strategy; Time series; Gold price volatility
First-Principles Investigation of Structural, Electronic, and Room Temperature Ferromagnetism in Si-Doped Monolayer BN

We performed spin-polarized density functional theory (DFT) to investigate the structural, electronic, and magnetic properties of silicon- (Si-) doped monolayer boron nitride (BN). The present study revealed that structural parameters like bond length, bond angle, and lattice parameters increase as Si-doped in the B site of monolayer BN. However, the bandgap of monolayer BN is reduced in the presence of the Si dopant. Moreover, the obtained magnetic moment and analysis of the total density of states (TDOS) show that Si-doped monolayer BN displays ferromagnetism. The calculated ferromagnetic transition temperature (Tc) value for Si concentration of 12.5% is 476 K which exceeds room temperature. The findings are avenues to enhance the application of monolayer BN for spintronics.
40 Gbit/s modulation of 1550 nm VCSEL

The modulation characteristics of vertical-cavity surface-emitting lasers with a buried tunnel junction emitting in the important wavelength regime around 1.55 m are presented. For the first time it was possible to demonstrate bit rates up to 40 Gbit/s also in this waveband. The 3 dB bandwidth measured under continuous-wave driving conditions was higher than 19 GHz. The present devices were found to be somehow sensitive to the bit-pattern length, especially at high temperatures or data rates resulting in some error-flooring. Error-free performance could be demonstrated up to 35 Gbit/s at room temperature and up to 25 Gbit/s at 55°C.