Miracle-dz/UniFAR-FTUs huggingface dataset:
The Lyme Borreliosis Spatial Footprint in the 21st Century: A Key Study of Slovenia

After mosquitoes, ticks are the most important vectors of infectious diseases. They play an important role in public health. In recent decades, we discovered new tick-borne diseases; additionally, those that are already known are spreading to new areas because of climate change. Slovenia is an endemic region for Lyme borreliosis and one of the countries with the highest incidence of this disease on a global scale. Thus, the spatial pattern of Slovenian Lyme borreliosis prevalence was modelled with 246 indicators and transformed into 24 uncorrelated predictor variables that were applied in geographically weighted regression and regression tree algorithms. The projected potential shifts in Lyme borreliosis foci by 2050 and 2070 were calculated according to the RCP8.5 climate scenario. These results were further applied to developing a Slovenian Lyme borreliosis infection risk map, which could be used as a preventive decision support system.
Modelling of Electric Drives using

The (short for “free Field-Oriented Control library”) provides a framework for simulations of electric drives with different application purposes. The library can be used to simply build a field-oriented control system for existing machine models from the Modelica Standard Library, investigate the impact of electric faults (battery faults, inverter faults, machine faults) on a electric drive system, and run simulations to estimate the fuel consumption of hybrid electric vehicles. The library structure and some of its main components are presented. Simulation results of an electric fault are given as an application example of this library. The will be publicly available in Spring 2008.
Governance and Design of Digital Platforms: A Review and Future Research Directions on a Meta-Organization

The burgeoning digital-platforms literature across multiple business disciplines has primarily characterized the platform as a market or network. Although the organizing role of platform owners is well recognized, the literature lacks a coherent approach to understanding organizational governance in the platform context. Drawing on classic organizational governance theories, this paper views digital platforms as a distinct organizational form where the mechanisms of incentive and control routinely take center stage. We systematically review research on digital platforms, categorize specific governance mechanisms related to incentive and control, and map a multitude of idiosyncratic design features studied in prior research onto these mechanisms. We further develop an integrative framework to synthesize the review and to offer novel insights into the interrelations among three building blocks: value, governance, and design. Using this framework as a guide, we discuss specific directions for future research and offer a number of illustrative questions to help advance our knowledge about digital platforms’ governance mechanisms and design features.
Utilisation of solar photovoltaic pumping for aeration systems in aquaculture ponds

This research pertains to solar photovoltaic (PV) pumping for aeration of aquaculture ponds and evaluates it economically. A stand-alone photovoltaic aeration system based on recycling of water at 10 cm under the water surface, at the surface (0 cm) and above the surface (30 cm) on a perforated tray was evaluated. The effect of pump discharges (35, 50, 65 L/min) on standard oxygen transfer rate (SOTR) and standard aeration efficiency (SAE) was investigated. Results revealed that the daily averages of PV energy output, PV efficiency and load energy were 0.844 kWh/d, 9.87% and 0.615 kWh/d, respectively, at 65 L/min and 42.7°C PV temperature. Water flow upward at 30 cm over the perforated tray in the radial direction proved to be better since it gave an opportunity for the exchange of gaseous between the water and the atmosphere. The SOTR and SAE for the third position were 0.025 kgO2/h and 0.1 kgO2/kW h, respectively.
RBFNN speed compensate controller use in high precision servo systems

This paper proposed three control schemes using model reference adaptive control (MRAC) and RBF neural network(RBFNN). Through comparision, it proposed a MRAC scheme with RBFNN compensator for speed control of high precision servo systems. The MRAC scheme is used to give better solutions with online adaptation and guarantee the stablity of the system. In the feedback channel, the parameter Kp makes it easier to design the system poles. By using a PI controller before Kp, the dynamic performance of the system is improved. As a speed compensate controller, the RBFNN is designed parallel with the model reference control. The RBFNN controller is able to online learn the unknown model dynamics, parameter variation and disturbance of the system. Thus, it is feasible to preserve favorable model-following characteristics under various conditions. The effectiveness of the proposed control scheme is demonstrated by simulation. It is found that the proposed scheme can reduce the plant's sensitivity to parameter variation and disturbance. High precision performance is obtained when given constant and sine wave disturbance at the same time.
Integrated position sensing for 2D microscanning mirrors using the SOI device layer as the piezoresistive mechanical-elastic transformer

Position feedback of resonant scanning micromirrors plays a key role for various applications like portable laser projection displays or scanning grating spectrometers. The SOI device layer without an additional surface implantation is used for the piezoresistive sensor design. It assures the full compatibility to microscanner technology and requires no additional technological efforts. The necessary asymmetry of the current field density is achieved by the geometrical design of the sensor and its contacting. Integrated 2D position sensors with amplitude sensitivities of 0.42mV/V° were fabricated. FEA simulation and measured data correlates well with variations of ≤ 20.4%.
Integration of highly probabilistic sources into optical quantum architectures: perpetual quantum computation

In this paper, we introduce a design for an optical topological cluster state computer constructed exclusively from a single quantum component. Unlike previous efforts we eliminate the need for on demand, high fidelity photon sources and detectors and replace them with the same device utilized to create photon/photon entanglement. This introduces highly probabilistic elements into the optical architecture while maintaining complete specificity of the structure and operation for a large-scale computer. Photons in this system are continually recycled back into the preparation network, allowing for an arbitrarily deep three-dimensional cluster to be prepared using a comparatively small number of photonic qubits and consequently the elimination of high-frequency, deterministic photon sources.
RF sampling gates: a brief review

The paper contains a brief review of the various techniques employed for the sampling of RF and microwave signals, and reference is made to subharmonic sampling as one of the possible applications. Particular attention is given to the two- and four-diode gate arrangements and the associated pulse strategies for fast switching time are discussed, as are the theoretical and practical aspects associated with the use of finite risetime sampling pulse trains. The design and operation of an experimental 10 GHz GaAs FET unit are given in detail, and recommendations are given in the concluding Section as regards development effort in sampling gates.
Online Characterization and Detection of False Data Injection Attacks in Wide-Area Monitoring Systems

False data injection attack (FDIA) is a major threat in wide-area monitoring systems. Being able to differentiate FDIA from normal grid contingencies is a paramount necessity for a grid operator to decide the correct response on a critical prompt basis as well as reduce the overall FDIA's false alarms. Two FDIA's characterization algorithms are developed in this paper. The first is based on the principal component analysis (PCA) while the second is based on the canonical correlation analysis (CCA). Both algorithms are developed in an online platform to reduce the computational complexity. The various designed test cases demonstrate a promising FDIA characterization performance utilizing both algorithms. The testing results of three machine learning-based classifiers indicate that the proposed FDIA's characterization algorithms provide better classification models than conventional PCA-based characterization algorithm with CCA illustrating advanced characterization and detection results.
Dynamic dispatch by constructive dynamic programming

This paper describes a new method of solving the dynamic dispatch problem. Boiler-turbine generators are characterised by variable operating costs and ramp rate constraints and costs. All system costs are piecewise linear. The method employs concepts from dynamic programming and linear programming. Dispatch decisions that minimise system variable cost and marginal costs are determined. Generator outputs are not discretised. Efficiency gains over dynamic programming are achieved by exploiting the underlying convex geometry of the problem and avoiding discretisation of the state space.
Teaching the Basic Concepts of Communications Systems Using Interactive Graphics and Calculations

An open source, open content, and open access (free) electronic textbook, an ebook, introducing the concepts of communication systems is described. The ebook is written in the Wolfram language, Mathematica. The purpose of this interactive presentation of communication systems is to bring the material alive through the use of student driven interactive graphics and dynamic performance metric calculations. In-line interactive questions are included to provide the students with rapid feedback regarding their understanding of the material. The ebook was used as the required text in EECS 562 Introduction to Communication Systems at the University of Kansas in the Spring of 2021.
Mobile Wireless Sensor Networks K-Covering Algorithm

In mobile wireless sensor networks, sensor nodes may due to their own moves, energy loss, physical damage, errors and failures or other factors, will result the case of coverage holes, and then lead to inefficient network coverage. This paper designed a new algorithm based on clustering approach for mobile wireless sensor network, can monitor the network in real-time and repairing coverage holes quickly. Simulation results show that, the algorithm used in mobile wireless sensor network not only can achieve the desired uniformity of coverage, but also increase the coverage area, and better performance than the Virtual force algorithm(VFA) [1].
Do Americans Oppose Controversial Evidence-Based Road Safety Policies?

Six safety improvement systems based on legislation have proved to reduce rural roadway fatalities. But their legislative enactment has been limited in part by a perception of journalists and policy makers that the policies are controversial and unpopular with the general public. However, a national public opinion survey found that an overwhelming proportion of Americans support all six policies. Strong support exists across all major demographic, geographic, gender, and ideological groups and calls that perception into question. These findings are instructive for those who attempt to reduce rural roadway fatalities through evidence-based rural roadway safety public policies.
Long-term monitoring of local stress changes in 67km installed OPGW cable using BOTDA

The initial results from continuing long-term monitoring of a 67 km of an aerial fiber optic cable installed on a 500 kV power line cable (total fiber length of 134km) using BOTDA are presented. The effects of thunderstorms and rime ice on the cable were identified by monitoring strain on OPGW fibers. Variations of strain between day and night on the OPGW cable were observed and can potentially be exploited.
A review on microalgae, a versatile source for sustainable energy and materials

Increasing energy demands, predicted fossil fuels shortage in the near future, and environmental concerns due to the production of greenhouse gas carbon dioxide on their combustion have motivated the search for alternative ‘clean’ energy sources. Among many resources for this, microalgae have been found to be most promising due to their high production capacity of vegetable oils. They possess a high growth rate, need abundantly available solar light and CO2, and thus are more photosynthetically efficient than oil crops. Also, they tolerate high concentration of salts allowing the use of any type of water for the agriculture and the possibility of production using innovative compact photobioreactors. In addition, microalgae are a potential source of biomass, which may have great biodiversity and consequent variability in their biochemical composition. This paper presents an overview on microalgae with particular emphasis as a source for energy (biofuel/electricity) and new materials. Critical issues involved in production of microalgae and their use, future R & D to overcome these, including the work initiated by the authors at Federal University of Paraná, UFPR, in Brazil are discussed. Copyright © 2010 John Wiley & Sons, Ltd.
Firm‐Specific Human Capital: A Skill‐Weights Approach

The theory of human capital is agnostic on what constitutes firm‐specific skills. The theory specifies that specific skills contribute to productivity only at the current firm. A broader approach lets all skills be general, but firms use them with different weights attached. For example, computer programming, economics, and accounting are general skills, but there may be only one firm that wants workers trained in all three. One implication is that wage profiles and the split of human capital costs depend on thickness of the market. Another is that firms pay for what appears to be general training.
The Effect of Lifestyle Intervention on Diabetes Prevention by Ethnicity: A Systematic Review of Intervention Characteristics Using the TIDieR Framework

Lifestyle intervention is effective in preventing type 2 diabetes mellitus (T2DM), but the efficacy of intervention components across different ethnic groups is less clear. This systematic review examined the effects of intervention characteristics of lifestyle interventions on diabetes incidence and weight loss by ethnicity using the Template for Intervention Description and Replication (TIDieR) framework. MEDLINE, EMBASE and other databases were searched for randomized and non-randomized controlled trials on lifestyle interventions (diet and/or physical activity) in adults at risk of T2DM. Ethnicity was categorized into European, South Asian, East and Southeast Asian, Middle Eastern, Latin American and African groups. Forty-five studies (18,789 participants) were included in the systematic review and 41 studies in meta-analysis. Meta-analysis showed a high number of intervention sessions was significantly associated with a greater reduction in diabetes incidence (P = 0.043) and weight (P = 0.015), while other intervention characteristics including intervention provider and delivery format did not alter the outcomes (all P > 0.05). Additionally, narrative synthesis showed long-term interventions (≥12 months) were associated with significant diabetes risk reduction for all ethnic groups, while short-term interventions (<12 months) were more effective in weight loss in most ethnic groups. There may be ethnic preferences for the optimal number of intervention sessions.
Elementary school student’s acceptance of Lego NXT: The technology acceptance model, a preliminary investigation

1 Department and Graduate School of Computer Science, National Pingtung University of Education, No. 4 to 18, Ming Shen Road. , Pingtung 90003, Taiwan. 2 Department of Business Administration, Shu-Te University, Yen Chau, Kaohsiung 82445, Taiwan, R.O. C. 3 Department of Finance, Yuanpei University, No.306, Yuanpei Street, Hsinchu 30015, Taiwan. 4 Department and Graduate School of Computer Science, National Pingtung University of Education, No. 4-18, Ming Shen Rd., Pingtung 90003, Taiwan, R.O. C. 5 Global Earth Observation and Data Analysis Center (GEODAC), National Cheng Kung University, No 1, Ta-Hsueh Road, Tainan 701, Taiwan, R.O. C. 6 Doctoral Program in Management, National Kaohsiung First University of Science and Technology, Taiwan, R.O. C.
A reconfigurable Yagi antenna for wireless communications

The design of a reconfigurable Yagi antenna that can operate at two frequencies, 2.4 GHz and 5.78 GHz, for use in wireless communications is presented. The Yagi can be reconfigured through the use of appropriate switches placed on the elements of the antenna. This paper shows the feasibility of this antenna and presents simulated and measured results at the two frequencies. © 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 38: 140–141, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10997
Fundamental continuous-pulp-digester model for simulation and control

A model of a continuous digester was developed as an extension of the well-known Purdue model. A lumped-parameter approximation is used to describe the flow transport mechanism of the digester, and a model based on the fundamental principles of mass and energy is derived. Mass bases and volume fractions are defined to allow fewer simplifying assumptions in the model derivation than in previous model versions. The steady-state profiles and dynamic responses of the digester model are compared with a previous version of the Purdue model, and the significant differences between the two models are highlighted. The digester model is also compared to the Weyerhaeuser benchmark digester model, and a parametric sensitivity analysis to several model parameters is performed. Physical explanations are given for the demonstrated model behaviors. Model implementation is straightforward, making it useful for process control, optimization and design studies.
Association between blood pressure and the risk of chronic kidney disease in treatment-naïve hypertensive patients

Background Although hypertension is a well-known risk factor for chronic kidney disease (CKD), the blood pressure (BP) at which antihypertensive interventions should be initiated remains to be determined. Therefore, we investigated the association between BP and CKD in treatment-naïve individuals. Methods This prospective cohort study considered 7,343 individuals in the Korean Genome and Epidemiology Study who were not taking antihypertensive medications. Subjects were categorized into six groups according to their systolic BP (SBP) and five groups according to their diastolic BP (DBP). The primary outcome was incident CKD, which was defined as an estimated glomerular filtration rate of <60 mL/min/1.73 m2 or the development of proteinuria. The secondary outcome was incident cardiovascular disease (CVD). Results In the time-varying Cox models, the hazard ratios (95% confidence interval [CI]) for CKD were 1.39 (1.10–1.77) with SBP 130–139 mmHg, 1.79 (1.40–2.28) with SBP 140–159 mmHg, and 3.22 (2.35–4.40) with SBP ≥ 160 mmHg, compared with SBP 100–119 mmHg. In addition, the hazard ratios (95% CI) for CKD were 1.88 (1.48–2.37) with DBP 90–99 mmHg and 4.30 (3.20–5.76) with DBP ≥ 100 mmHg, compared with DBP 70–79 mmHg. A significantly increased CVD risk was also observed in subjects with SBP ≥ 130 mmHg or DBP ≥ 90 mmHg. Conclusion Our findings indicate that SBP ≥ 130 mmHg and DBP ≥ 90 mmHg are associated with an increased risk of CKD. Therefore, BP-lowering strategies should be considered starting at those thresholds to prevent CKD development.
Spatial Variability of Suspended Sediments in San Francisco Bay, California

Understanding spatial variability of water quality in estuary systems is important for making monitoring decisions and designing sampling strategies. In San Francisco Bay, the largest estuary system on the west coast of North America, tracking the concentration of suspended materials in water is largely limited to point measurements with the assumption that each point is representative of its surrounding area. Strategies using remote sensing can expand monitoring efforts and provide a more complete view of spatial patterns and variability. In this study, we (1) quantify spatial variability in suspended particulate matter (SPM) concentrations at different spatial scales to contextualize current in-water point sampling and (2) demonstrate the potential of satellite and shipboard remote sensing to supplement current monitoring methods in San Francisco Bay. We collected radiometric data from the bow of a research vessel on three dates in 2019 corresponding to satellite overpasses by Sentinel-2, and used established algorithms to retrieve SPM concentrations. These more spatially comprehensive data identified features that are not picked up by current point sampling. This prompted us to examine how much variability exists at spatial scales between 20 m and 10 km in San Francisco Bay using 10 m resolution Sentinel-2 imagery. We found 23–80% variability in SPM at the 5 km scale (the scale at which point sampling occurs), demonstrating the risk in assuming limited point sampling is representative of a 5 km area. In addition, current monitoring takes place along a transect within the Bay’s main shipping channel, which we show underestimates the spatial variance of the full bay. Our results suggest that spatial structure and spatial variability in the Bay change seasonally based on freshwater inflow to the Bay, tidal state, and wind speed. We recommend monitoring programs take this into account when designing sampling strategies, and that end-users account for the inherent spatial uncertainty associated with the resolution at which data are collected. This analysis also highlights the applicability of remotely sensed data to augment traditional sampling strategies. In sum, this study presents ways to supplement water quality monitoring using remote sensing, and uses satellite imagery to make recommendations for future sampling strategies.
Potential energy saving for a side-lit room using daylight-linked fluorescent lamp installations

The high frequency (HF) electronic ballast has been replacing the conventional magnetic ballast for operating fluorescent lamps. It has the advantage of low energy consumption, running the lamps free from stroboscopic effects, low noise production, being light weight and allowing the lamps to be dimmed. This study shows that for a cellular office at the perimeter of a building lit by a dimmable HF electronic ballast lighting, about 40% of the lighting energy could be saved under Hong Kong’s daylight conditions. A saving of 40% at the perimeter amounts to an overall lighting energy saving of about 10% if the perimeter area is about one quarter of the total floor area. Lighting energy normally accounts for about 30% of the total energy consumption for office buildings. For a shallow plan office building, the amount of saving using a daylight linked system could be significant.
Automatic Unhulled Rice Grain Crack Detection by X-Ray Imaging

Crack detection of incoming paddy (unhulled rice grain) is an important step in the rice milling industry, as paddy grains with cracks severely affect the milling yield. The present method of crack detection by manually dehusking and examining kernels under light is laborious, time consuming, and highly subjective. The potential of x-ray imaging for paddy grain crack detection was investigated. Algorithms were developed for automatic detection of paddy cracks from the x-ray image. Hough transform was used to determine the cracks in the final segmented image. A graphical user interface (GUI) was developed for displaying the number of cracks in the given x-ray image.