Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Geothermal Project Economics with Multi-zone Stimulation: Results from the Newberry Volcano EGS Demonstration

In both conventional geothermal projects and in EGS, the flow rate from each production well is the critical component of project economics and has a direct effect on the Levelized Cost of Electricity (LCOE). In conventional geothermal fields, the cost of the wellfield system makes up 25% - 50% of the total cost of the project. In EGS the wellfield makes up 60%-80% of the cost of the project. While intersecting adequate temperatures during drilling is a significant risk, low temperatures can be compensated by high flow rates. In EGS projects, the temperature is primarily a function of the drilling depth, so the ability to stimulate and achieve a high production rate without risking rapid temperature drop is critical not only to project economics, but also to expansion of the development of geothermal energy into areas where hydrothermal resources are not found. The oil and gas industry has developed stimulation techniques over the years that have allowed the enhancement of very low permeability rock for oil and gas production. Multi-stage stimulation and horizontal well completions can access larger volumes of tight rock to recover poorly connected pore volume. These technology changes in oil and gas stimulation have allowed the development of a resource that was previously thought to be uneconomic. In unconventional oil and gas resources, the permeability of shale is very low, just as heat transfer in rock is very small. The larger the surface area of the contact with the formation, the more production is possible. By focusing our efforts in geothermal energy technology on improving production and injection rates through stimulation, improving power plant efficiency to get more power output from the same flow and temperature and by managing the reservoir to reduce pressure and temperature decline, we can mitigate exploration risk and expand the base of geothermal power production.
Prevalence, molecular characterization and antimicrobial resistance of E. coli isolates from diarrhoeic lambs in Andhra Pradesh

A study was carried out on isolation, molecular characterization and antimicrobial resistance of E. coli isolated from faecal samples of diarrhoeic lambs with the aim to detect antimicrobial resistance in E. coli associated diarrhoeic lambs of this geographic region. A total of 212 faecal samples from diarrhoeic lambs of 1-7, 8-30, 31-60 and 61-90 days age groups were collected from Vizianagaram, West Godavari, Krishna, districts of Andhra Pradesh of which 170 E. coli were isolated with a prevalence rate of 80.18%. After cultural and biochemical confirmation of E. coli the isolates were further confirmed by molecular characterization. The antimicrobial resistance of isolates was tested by disk diffusion method. Among the three districts, higher prevalence of E. coli in diarrhoeic lambs was recorded in West Godavari district (86.41%), while lower (72.83%) prevalence was found in Krishna district. Irrespective of the districts, higher prevalence of E. coli was observed in 1-7 day-old diarrhoeic lambs (84%), while lower prevalence was detected in 61-90 day-old age group (72.72%). This study detected highest antibiotic resistance in E. coli isolates against colistin (98.82%) and sulphamethizole (89.41%), while enrofloxacin (5.88%), gentamicin (5.33%) and chloramphenicol (1.17%) were effective. This study provided baseline data on prevalence of E. coli associated diarrhoea and antimicrobial resistance against commonly used antimicrobials in sheep.
An improved lumped-charge model and parameter extraction approach of PIN diodes

An improved lumped-charge model of PIN diodes is described. This model includes reverse and forward recovery, emitter recombination and boundary-moving effects. Especially for reverse recovery, both sweeping out and recombination effects are taken into account Based on the model, most parameters can be extracted by a new accurate curve-fitting approach, and the other can be obtained by simple experiments. Comparison between simulation and experimental results for transient behavior verifies the model and the parameter extraction approach.
On two new species of deep-sea carrier crabs (Crustacea, Brachyura, Homolodromiidae, Dicranodromia) from Taiwan and the Philippines, with notes on other Indo-West Pacific species

Abstract The systematics of four species of the homolodromiid genus Dicranodromia A. Milne-Edwards, 1880, from East Asia and the Philippines is reappraised: D.danielae Ng & McLay, 2005, D.doederleini Ortmann, 1892, D.karubar Guinot, 1993, and D.martini Guinot, 1995; and key characters such as the epistome, gonopods, and spermatheca are figured in detail. Two new species, D.erinaceussp. nov. and D.robustasp. nov., are described from Taiwan and the Philippines, respectively. Dicranodromiaerinaceussp. nov. resembles D.spinulata Guinot, 1995, and D.delli Ahyong, 2008 (from New Caledonia and New Zealand) but can be separated by its distinctly spinulated carapace surfaces and proportionately shorter fifth ambulatory legs. Dicranodromiarobustasp. nov. is superficially similar to D.baffini (Alcock & Anderson, 1899) and D.karubar Guinot, 1993, but can easily be separated by possessing a broad dorsoventrally flattened infraorbital tooth. A genetic study of the species using the mitochondrial cytochrome c oxidase I gene confirms that the taxa are distinct, with D.erinaceussp. nov. coming out in a well-supported clade from congeners. The megalopa of D.doederleini is also reported for the first time.
Molecular Diagnostic of Ochratoxin A With Specific Aptamers in Corn and Groundnut via Fabrication of a Microfluidic Device

Ochratoxin A (OTA) is one of the predominant mycotoxins that contaminate a wide range of food commodities. In the present study, a 36-mer aptamer was used as a molecular recognition element coupled with gold nanoparticles (AuNPs) for colorimetric detection of OTA in a microfluidic paper-based analytical device (μPADs). The μPADs consisted of three zones: control, detection, and sample, interconnected by channels. UV-vis spectroscopy (UV-vis), Dynamic Light Scattering (DLS), and Transmission Electron Microscopy (TEM) were used for characterization of AuNPs and AuNPs/Aptamer. According to the colorimetric assay, limit of detection (LOD) was found to be 242, 545.45, and 95.69 ng/mL in water, corn, and groundnut, respectively. The HPLC detection method achieved acceptable coefficient in standard curves (r2 = 0.9995), improved detection range, and recovery rates in spiked corn and groundnut samples as 43.61 ± 2.18% to 87.10 ± 1.82% and 42.01 ± 1.31% to 86.03 ± 2.64% after multiple sample extractions and cleanup steps. However, the developed μPADs analytical device had the potent ability to rapidly detect OTA without any extraction pre-requirement, derivatization, and cleanup steps, thus illustrating its feasibility in the animal health sector, agricultural, and food industries.
DESIGN OPTIMIZA TION OF DEEPDRA WING PROCESS

The design optimization of deepdrawing process in manufacturing is proposed to control the final shape of the workpiece after elastic springback. The manufacturing process design problem is formulated to minimize the difference between the shape of the desired •workpiece geometry and the final analysis result after elastic springback. Nonlinear structural problem that includes elastoplasticity withfrictional contact is solved using a meshfree method where the structural domain is discretized by a set of particle points. Continuumbased design sensitivity analysis (DSA) is carried out to efficiently obtain the gradient information for the optimization. The shape of the workpiece and the geometry of the rigid die are treated as design variables. The accuracy of the sensitivity result is compared with the finite difference result with excellent agreement. The optimum stamping process improves the quality of the final product significantly.
Periodic and quasi-periodic nonlinear photonic crystals

Nonlinear photonic crystals are materials in which the second order susceptibility is modulated, while the linear susceptibility remains constant. In this paper, quasi-phase matching possibilities in several different nonlinear photonic crystals are analyzed and compared. A periodic one-dimensional structure is usually employed for phase matching a single process, but we show that two processes can also be simultaneously phase matched by non-collinear interaction. Two-dimensional periodic modulation provides additional extension of the phase matching possibilities. The dependence of the process conversion efficiency on the specific choice of lattice, nonlinear motif and quasi-phase-matched order is analyzed. Further extensions are provided by quasi-periodic schemes. A very powerful method for designing quasi-periodic nonlinear structures, with either one-dimensional or two-dimensional modulation, is the socalled dual-grid method. This method practically enables to phase matched any set of nonlinear interactions, in any chosen direction of propagation. Finally, frequency conversion using a converter with pure rotation symmetry is analyzed and demonstrated.
Wind turbine condition monitoring: technical and commercial challenges

Deployment of larger scale wind turbine systems, particularly offshore, requires more organized operation and maintenance strategies to ensure systems are safe, profitable and cost-effective. Among existing maintenance strategies, reliability centred maintenance is regarded as best for offshore wind turbines, delivering corrective and proactive (i.e. preventive and predictive) maintenance techniques enabling wind turbines to achieve high availability and low cost of energy. Reliability centred maintenance analysis may demonstrate that an accurate and reliable condition monitoring system is one method to increase availability and decrease the cost of energy from wind. In recent years, efforts have been made to develop efficient and cost-effective condition monitoring techniques for wind turbines. A number of commercial wind turbine monitoring systems are available in the market, most based on existing techniques from other rotating machine industries. Other wind turbine condition monitoring reviews have been published but have not addressed the technical and commercial challenges, in particular, reliability and value for money. The purpose of this paper is to fill this gap and present the wind industry with a detailed analysis of the current practical challenges with existing wind turbine condition monitoring technology. Copyright © 2012 John Wiley & Sons, Ltd.
Using agent-based simulation to explore sugarcane supply chain transport complexities at a mill scale

The sugarcane supply chain (from sugarcane grower to mill) have particular challenges. One of these is that the growers have to deliver their cane to the mill before its quality degrades. The sugarcane supply chain typically consists of many growers and a mill. Growers deliver their cane daily during the milling season; the amount of cane they deliver depends on their farm size. Growers make decisions about when to harvest the cane, and the number and type of trucks needed to deliver their cane. The mill wants a consistent cane supply over the milling season. Growers are sometimes affected long queue lengths at the mill when they offload their cane. A preliminary agent-based simulation model was developed to understand this complex system. The model inputs a number of growers, and the amount of cane they are to deliver over the milling season. The number of trucks needed by each grower is determined by the trip, loading and unloading times and the anticipated waiting time at the mill. The anticipated waiting time was varied to determine how many trucks would be needed in the system to deliver the week’s cane allocation. As the anticipated waiting time increased, the number of trucks needed also increased, which in turn delayed the trucks when queuing at the mill. The growers’ anticipated waiting times never matched the actual waiting times. The research shows the promise of agent-based models as a sense-making approach to understanding systems where there are many individuals who have autonomous behaviour, and whose actions and interactions can result in unexpected system-level behaviour.
Demonstration of Adaptive Analogue Beam Forming in the E-Band

In this paper, we report the test results of a small-scale prototype that implements an analogue-beam-formed phased antenna array in the E-band. A four-channel dual-conversion receive RF module for 71~76 ㎓ frequency band has been developed and integrated with a linear end-fire antenna array. Measured performance is very close to the simulated results. An ad-hoc wireless communication system has also been demonstrated. Low BER was measured for an 8PSK data stream at 1.5 Gbps with the receive array beam formed in the direction of arrival of the transmitted signal. To our knowledge this is the first steerable antenna array reported to date in the E-band.
Parameter Selection and Convergence Analysis of the PSO Algorithm Applied to the Design of Risers

The design of risers is a very important issue for the offshore exploration of oil and gas as they are essential components of floating production systems (FPS). Many aspects involve the design of those structures mainly security and cost savings. Those demands include the optimum design of the riser configuration. The current tendency in the design of risers for FPSs considers the use of nonlinear, time-domain dynamic analysis tools, comprising either a coupled analysis strategy (where a hydrodynamic model of the floating system is coupled to a finite element structural and hydrodynamic model of the mooring lines and risers), or else an uncoupled strategy where the finite-element model of an individual line is analyzed, submitted to the motions of the platform. In either case, it is employed a time-domain dynamic simulation that requires a large amount of computational time. Thus, it is necessary the development of computational tools able to improve the efficiency in the design of risers through optimization methods. This work presents a study of the Particle Swarm Optimization method (PSO) applied to the design of risers in lazy wave configuration. The PSO method has shown good efficiency but its performance greatly depends on its parameters settings. In order to improve the PSO performance, we analyze the behavior of its parameters through several experiments. The results show that some default values initially used were not the best ones to obtain a good performance of the PSO algorithm when applied to the design of risers. The best parameter selection will be included in the OtimRiser program – a computational tool that uses several optimization methods based on evolutionary concepts.
Adaptive Strategies Based on Differential Evolutionary Algorithm for Many-Objective Optimization

The decomposition-based algorithm, for example, multiobjective evolutionary algorithm based on decomposition (MOEA/D), has been proved effective and useful in a variety of multiobjective optimization problems (MOPs). On the basis of MOEA/D, the MOEA/D-DE replaces the simulated binary crossover (SBX) operator with differential evolution (DE) operator, which is used to enhance the diversity of the solutions more effectively. However, the amplification factor and the crossover probability are fixed in MOEA/D-DE, which would lead to a low convergence rate and be more likely to fall into local optimum. To overcome such a prematurity problem, this paper proposes three different adaptive operators in DE with crossover probability and amplification factors to adjust the parameter settings adaptively. We incorporate these three adaptive operators in MOEA/D-DE and MOEA/D-PaS to solve MOPs and many-objective optimization problems (MaOPs), respectively. This paper also designs a sensitive experiment for the changeable parameter η in the proposed adaptive operators to explore how η would affect the convergence of the proposed algorithms. These adaptive algorithms are tested on many benchmark problems, including ZDT, DTLZ, WFG, and MaF test suites. The experimental results illustrate that the three proposed adaptive algorithms have better performance on most benchmark problems.
A SINGLE-VENDOR MULTI-BUYERS INTEGRATED INVENTORY POLICY FOR A DETERIORATING ITEM

ABSTRACT Since optimal inventory policy decision by individual player may not result in global optimum, modern enterprise seeks to decrease the total system cost by strategic alliances between the vendor and buyer. This study develops a single-vendor, multi-buyers inventory policy of a deteriorating item with a constant demand rate. A mathematical model considering the view of both the vendor and the buyer is developed. It can be shown that the integrated policy results in an impressive cost-reduction compared with an independent decision by the buyer.
Assessing the Progress of ASEAN MRAs on Professional Services

ASEAN has established mutual recognition arrangements (MRAs) on eight professional services. This paper assesses the progress of these arrangements’ paying special attention to the (i) regional and national implementation, (ii) national regulatory changes, and (iii) utilization of these frameworks and actual movement of these professionals in the region. MRAs on Architectural and Engineering Services have made steady progress, including the setting up of regional registration systems. This, however, has not resulted in a large-scale movement of these professionals for many reasons, such as existence of alternative legal schemes and small additional benefits of ASEAN MRAs. The ASEAN MRA on Nursing Services, without a regional registration system, has facilitated movement of nurses in only a few countries. Meanwhile, further efforts in advancing initiatives closely related to the movement of people are being made: ASEAN Agreement on the Movement of Natural Persons, ASEAN MRA on Accountancy Services, ASEAN MRA on Tourism Professionals, and the ASEAN Qualifications Reference Framework
A flexible way to generate PWM-SHE switching patterns using genetic algorithm

A genetic algorithm is developed as the preferred solution algorithm of specific harmonic elimination (PWM-SHE) switching pattern. The usual problem of the selection of starting values in numerical solution of a PWM-SHE switching pattern can now easily be avoided. Hence, easy convergence and less computing-time are achieved. Simulation and supporting experimental results are reported in this work.
Selection of TQM pilot projects using an MCDM approach

Total quality management (TQM) has been perceived as a competitive strategy to improve continually the quality of products and processes. However, the initial stages of TQM implementation may encounter major problems owing to misplaced efforts. The extent to which TQM is successful in an organization is determined by the initial impact of TQM efforts. Experts like Juran have suggested an incremental approach to TQM introduction, stressing pilot projects in some business units/areas of an organization. Presents a multiple‐criteria decision‐making (MCDM) model using the analytical hierarchy process (AHP) technique to identify and select key pilot TQM projects, and discusses model development and implementation issues. Illustrates the general applicability of this model by applying it to a hospital environment. Such an approach should help an organization to prioritize and enhance the returns from TQM efforts. Carefully selected projects will help to improve organizational acceptance of TQM efforts and overc.
Vision-based augmented reality computer assisted surgery navigation system

A vision-based Augmented Reality computer assisted surgery navigation system is presented in this paper. It applies the Augmented Reality technique to surgery navigation system, so the surgeon's vision of the real world is enhanced. In the system, the camera calibration is adopted to calculate the cameras projection matrix, and then make the virtual-real registration by using the transformation relation. The merging of synthetic 3D information into user's vision is realized by texture technique. The experiment results demonstrate the feasibility of the system we have designed.
Drivers’ Risk Perception and Risky Driving Behavior under Low Illumination Conditions: Modified Driver Behavior Questionnaire (DBQ) and Driver Skill Inventory (DSI)

Most road crashes are caused by human factors. Risky behaviors and lack of driving skills are two human factors that contribute to crashes. Considering the existing evidence, risky driving behaviors and driving skills have been regarded as potential decisive factors explaining and preventing crashes. Nighttime accidents are relatively frequent and serious compared with daytime accidents. Therefore, it is important to focus on driving behaviors and skills to reduce traffic accidents and enhance safe driving in low illumination conditions. In this paper, we examined the relation between drivers’ risk perception and propensity for risky driving behavior and conducted a comparative analysis of the associations between risk perception, propensity for risky driving behavior, and other factors in the presence and absence of streetlights. Participants in Hefei city, China, were asked to complete a demographic questionnaire, the Driver Behavior Questionnaire (DBQ), and the Driver Skill Inventory (DSI). Multiple linear regression analyses identified some predictors of driver behavior. The results indicated that both the DBQ and DSI are valuable instruments in traffic safety analysis in low illumination conditions and indicated that errors, lapses, and risk perception were significantly different between with and without streetlight conditions. Pearson’s correlation test found that elderly and experienced drivers had a lower likelihood of risky driving behaviors when driving in low illumination conditions, and crash involvement was positively related to risky driving behaviors. Regarding the relationship between study variables and driving skills, the research suggested that age, driving experience, and annual distance were positively associated with driving skills, while myopia, penalty points, and driving self-assessment were negatively related to driving skills. Furthermore, the differences across age groups in errors, lapses, violations, and risk perception in the presence of streetlights were remarkable, and the driving performance of drivers aged 45–55 years was superior to that of drivers in other age groups. Finally, multiple linear regression analyses showed that education background and crash involvement had a positive influence on error, whereas risk perception had a negative effect on errors; crash involvement had a positive influence, while risk perception had a negative effect on lapse; driving experience and crash involvement had a positive influence on violation; and age had a negative influence on it.