Miracle-dz/UniFAR-FTUs huggingface dataset:
A Photovoltaic Model With Reduced Computational Time

Modeling partially shaded photovoltaic (PV) systems for online applications such as model-based MPPTs requires a PV circuit model with low computational time to simulate the large number of connected PV units within a reasonable amount of time. Unfortunately, the accurate PV models available in the literature are complex and suffer from high computational time due to their dependence on a transcendental implicit equation. This paper proposes a photovoltaic circuit model featuring lower computational time and comparable accuracy. The model utilizes the accuracy of the practical PV model and reduces the computational time by replacing the model series resistance with a third-degree-polynomial voltage-dependent source. The proposed model mimics the accurate characteristics of the practical model without being dependent on a transcendental implicit equation, thus providing low computational time. The model also introduces a new parameter to enhance the model's accuracy at low irradiance. The effectiveness of the model is shown by comparing the computational time and accuracy of the proposed model with those of the available models. A case study of partially shaded PV systems shows that the percentage of reduction in computational time improves with increases in the number of PV units in a simulated PV system, providing a clear advantage when simulating large PV systems.
Regulation of Varicella-Zoster Virus-Induced Cell-to-Cell Fusion by the Endocytosis-Competent Glycoproteins gH and gE

ABSTRACT The gH glycoprotein of varicella-zoster virus (VZV) is a major fusogen. The realigned short cytoplasmic tail of gH (18 amino acids) harbors a functional endocytosis motif (YNKI) that mediates internalization in both VZV-infected and transfected cells (T. J. Pasieka, L. Maresova, and C. Grose, J. Virol. 77: 4194-4202, 2003). During subsequent confocal microscopy studies of endocytosis-deficient gH mutants, we observed that cells transfected with the gH tail mutants exhibited marked fusion. Therefore, we postulated that VZV gH endocytosis served to regulate cell-to-cell fusion. Subsequent analyses of gH+gL transfection fusion assays by the Kolmogorov-Smirnov statistical test demonstrated that expression of the endocytosis-deficient gH mutants resulted in a statistically significant enhancement of cell-to-cell fusion (P < 0.0001) compared to wild-type gH. On the other hand, coexpression of VZV gE, another endocytosis-competent VZV glycoprotein, was able to temper the fusogenicity of the gH endocytosis mutants by facilitating internalization of the mutant gH protein from the cell surface. When the latter results were similarly analyzed, there was no longer any enhanced fusion by the endocytosis-deficient gH mutant protein. In summary, these studies support a role for gH endocytosis in regulating the cell surface expression of gH and thereby regulating gH-mediated fusion. The data also confirm and extend prior observations of a gE-gH interaction during viral glycoprotein trafficking in a VZV transfection system.
Using Finite Impulse Response Feedback DACs to design Σ∆ modulators based on LC filters.

This paper proposes a general method to design the noise-transfer-function of a continuous-time Σ∆ modulator having high-order passive LC loop filters. The feedback signals can have arbitrary shapes and can be applied either at internal nodes or only at the input node. As a design example, this technique is used to design a 4 th order Σ∆ modulator where the internal nodes of the loop filter are removed for a more efficient circuit implementation. I. INTRODUCTION Nowadays, in Software Defined Radio (SDR) receivers, we try to displace the analog-to-digital conversion closer the antenna. The use of LC filters in a continuous-time (CT) bandpass (BP) Σ∆ modulator allows to consider the digitization of the signal directly at RF frequencies (1). One problem, induced by using LC filters, is the loss of the parity between the order of the loop filter and the number of internal nodes (Fig.1). This implies limited degrees of freedom to design the noise-transfer-function (NTF) of the modulator. The different solutions proposed to solve this problem imply to add one additional feedback at each node of the loop filter of the modulator to compensate the lack in degrees of freedom (2)(3). These papers treated only LC-resonators based Sigma- Delta with rectangular pulse shape feedback digital-to-analog converters (DAC) applied to each node of the modulators. In this paper we present a solution based on finite-impulse response feedback DAC (FIRDAC) to design CT modulators with n th order LC filters (Fig.2). The FIRDACs have already been used to improve the stability of the high order Σ∆ modulators (4) or to decrease the effects of non-idealities like clock-jitter (5)(6). Here we use FIRDACs to provide the sufficient degrees of freedom for designing the NTF of the modulator.
Experimental and Analytical Studies on Pyroelectric Waste Heat Energy Conversion

This study is concerned with direct conversion of thermal energy into electrical energy by subjecting pyroelectric materials to the Olsen cycle. The Olsen cycle consists of two isoelectric field and two isothermal process on the electric displacement versus electric field diagram. The energy and power generation capabilities of copolymer poly(vinylidene fluoridetrifluorethylene) [P(VDF-TrFE)] films and lead lanthanum zirconate titanate (PLZT) ceramics were evaluated by executing the Olsen cycle via so-called stamping experiments and dipping experiments . The stamping experiments consisted of alternatively pressing a pyroelectric material in thermal contact with hot and cold aluminum blocks under specified electric fields. It was performed to assess the pyroelectric energy conversion performance using heat conduction. The largest energy density generated in the stamping experiments was 155 J/L/cycle with 60/40 P(VDF-TrFE) thin film at 0.066 Hz between 25 and 110dC and electric fields cycled between 20 and 35 MV/m. This energy density exceeded the 130 J/L/cycle achieved by our previous prototypical device using oscillatory laminar convective heat transfer. However, the performance was limited by poor thermal contact between the aluminum blocks and pyroelectric material and also by excessive leakage current inherent to P(VDF-TrFE) at high temperatures and/or large electric fields. On the other hand, dipping experiments consisted of successively immersing a pyroelectric material into isothermal hot and cold thermal reservoirs at different temperatures while simultaneously cycling the electric fields. It was performed on relaxor ferroelectric x /65/35 PLZT ceramics with x between 5 and 10 mol. %. The operating temperature, applied electric field, sample thickness, cycle frequency, and electrode material were systematically varied to explore their respective effects on the energy and power densities produced. A maximum energy density of 1014 J/L/cycle was obtained with a 190mm thick 7/65/35 PLZT sample at 0.0256 Hz at temperatures between 30 and 200dC and electric field from 0.2 to 7.0 MV/m. To the best of our knowledge, this energy density is the largest achieved among pyroelectric single crystals, ceramics, and polymers using the Olsen cycle. Meanwhile, a maximum power density of 55.3 p 8.0 W/L obtained with a 190mm thick 9.5/65/35 PLZT sample at 0.125 Hz. Additionally, the temperature-dependent dielectric behavior of PLZT ceramics were characterized.The polarization transition temperature of lanthanum-doped x /65/35 PLZT ceramics decreased from 240 to 10dC for increasing lanthanum dopant concentration x from 5 to 10 mol. %. This establishes that the different compositions should be operated at different temperatures for maximum pyroelectric energy conversion. Finally, a physical thermo-electrical model for estimating the energy harvested by ferroelectric relaxors was further validated against experimental data for a wide range of electric fields and temperatures.
Enhancing LVRT of DFIG by Using a Superconducting Current Limiter on Rotor Circuit

This paper have studied the dynamic of a 2.0 MW Doubly Fed Induction Generator (DFIG) during a severe voltage sag. Using the dynamic model of a DFIG, it was possible to determine the current, Electromagnetic Force and flux behavior during three-phase symmetrical voltage dip. Among the technologies of wind turbines the DFIG is widely employed; however, this machine is extremely susceptible to disturbances from the grid. In order to improve DFIG Low Voltage Ride-Through (LVRT), it is proposed a novel solution, using Superconducting Current Limiter (SCL) in two arrangements: one, the SCL is placed between the machine rotor and the rotor side converter (RSC), and another placed in the RSC DC-link. The proposal is validated through simulation using PSCAD™/EMTDC™ and according to requirements of specific regulations. The analysis ensure that both SCL arrangements behave likewise, and are effective in decrement the rotor currents during the disturbance.
Towards Street-Level Client-Independent IP Geolocation

A highly accurate client-independent geolocation service stands to be an important goal for the Internet. Despite an extensive research effort and significant advances in this area, this goal has not yet been met. Motivated by the fact that the best results to date are achieved by utilizing additional 'hints' beyond inherently inaccurate delay-based measurements, we propose a novel geolocation method that fundamentally escalates the use of external information. In particular, many entities (e.g., businesses, universities, institutions) host their Web services locally and provide their actual geographical location on their Web-sites. We demonstrate that the information provided in this way, when combined with network measurements, represents a precious geolocation resource. Our methodology automatically extracts, verifies, utilizes, and opportunistically inflates such Web-based information to achieve high accuracy. Moreover, it overcomes many of the fundamental inaccuracies encountered in the use of absolute delay measurements. We demonstrate that our system can geolocate IP addresses 50 times more accurately than the best previous system, i.e., it achieves a median error distance of 690 meters on the corresponding data set.
Sizing Optimization of Retaining Wall by Firefly Algorithm

Retaining wall is used to retain the lateral pressure of soil and surface loading. It has been widely used for application in civil engineering structure such as fill application, roadway cut, etc. This paper considered a firefly algorithm to find out the optimum size and shape of retaining wall with 7m of height and subjected to various loading (5kN/m 2 , 10kN/m 2 , 20kN/m 2 , 40kN/m 2 ). There are four design variables considered for optimization. The objective is to minimize the weight of the retaining wall without violating the requirement of retaining wall. This paper considered stability check of the retaining wall such as overturning stability, sliding stability, and bearing capacity of the soil under the retaining wall. The result shows that the shape of retaining wall with load of 5kN/m 2 and 10kN/m 2 were similar, the body of the retaining wall were rectangular while the shape of retaining wall with load of 20kN/m 2 and 40kN/m 2 were trapezoidal. Sliding stability became design control for all loading cases compared by other stability problem (overturning and bearing capacity of soil under the retaining wall). Therefore, it can be concluded that firefly algorithm has successfully been applied to optimize the retaining wall.
Analyzing polarimetric signatures for different features in polarimetric SAR data

The main idea of this research is to provide a graphical representation of various features in polarimetric SAR data. Returned signal from a target contain all polarizations whereas conventional method shows polarimetric information just in a restricted number of polarization bases. More details of physical information are depicted from polarimetric signature according to various polarization bases of target backscattering. Distinct polarization bases separates classes with near backscattering due to its different responses. A Radarsat-2 image, which was acquired in August 2009, was chosen for this study. The backscattering from different classes (Water, Urban, Forest and Ground vegetation) were analyzed by the proposed method. The results illustrate that polarimetric signatures of various features can be an effective tools for analyzing the different classes.
Regulation of Cellular Immortalization and Steady-State Levels of the Telomerase Reverse Transcriptase through Its Carboxy-Terminal Domain

ABSTRACT Telomerase maintains cell viability and chromosomal stability through the addition of telomere repeats to chromosome ends. The reactivation of telomerase through the upregulation of TERT, the telomerase protein subunit, is an important step during cancer development, yet TERT protein function and regulation remain incompletely understood. Despite its close sequence similarity to human TERT (hTERT), we find that mouse TERT (mTERT) does not immortalize primary human fibroblasts. Here we exploit these differences in activity to understand TERT protein function by creating chimeric mouse-human TERT proteins. Through the analysis of these chimeric TERT proteins, we find that sequences in the human carboxy-terminal domain are critical for telomere maintenance in human fibroblasts. The substitution of the human carboxy-terminal sequences into the mouse TERT protein is sufficient to confer immortalization and maintenance of telomere length and function. Strikingly, we find that hTERT protein accumulates to markedly higher levels than does mTERT protein and that the sequences governing this difference in protein regulation also reside in the carboxy-terminal domain. These elevated protein levels, which are characteristic of hTERT, are necessary but not sufficient for telomere maintenance because stabilized mTERT mutants cannot immortalize human cells. Thus, the TERT carboxy terminus contains sequences that regulate TERT protein levels and determinants that are required for productive action on telomere ends.
Zoonotic Risks from Amphibians and Reptiles

Author(s): Jay-Russell, Michele T. ; Montfort, Jordi; Liu, Yingjia; Huang, Stephanie; Gorski, Lisa; Cooley, Michael; Mandrell, Robert; Wheeler, Jessica; Reis, Dawn; Li, Xunde; Atwill, Edward R. | Abstract: Captive amphibians and reptiles are well-documented sources of human salmonellosis through direct contact with contaminated feces or fomites. However, the relative significance of wild cold-blooded vertebrates as hosts/reservoirs of zoonotic enteric pathogens in their natural habitat is not known. Wild amphibian and reptile populations are present in the leafy green produce production environment in the central California coast, and there are reports from growers that frogs and other species sometimes intrude into produce fields. These intrusions may result in destruction of the crop and economic losses, due to food safety and quality concerns. Environmental groups have also noted potential conflicts between conservation efforts and food safety practices that result in removal or damage to aquatic habitat (e.g., farm ponds, adjacent wetland areas). To address these concerns, we conducted a survey of foodborne pathogen prevalence in common amphibian and reptile populations during the 2011 produce growing season in the central California coast. Preliminary results indicate that Salmonella prevalence was higher among wild-caught reptile (33%) compared with amphibian (4%) taxa. In contrast, all samples were negative for E. coli O157. Wildlife damage management in fresh produce production fields is challenging, due to the diversity of potential hosts/reservoirs of foodborne pathogens and a limited number of mitigation strategies. Professionals working in vertebrate pest control could play an important role in assisting fresh produce growers with implementation of co-management approaches that promote public health and conservation goals in the central coast agricultural landscape.
Modelling groundwater level variations by learning from multiple models using fuzzy logic

ABSTRACT Modelling time series of groundwater levels is investigated by three fuzzy logic (FL) models, Sugeno (SFL), Mamdani (MFL) and Larsen (LFL), using data from observation wells. One novelty in the study is the re-use of these three models as multiple models through the following strategies: (a) simple averaging, (b) weighted averaging and (c) committee machine techniques; these are implemented using artificial neural networks (ANN). These strategies provide some evidence that (i) multiple models improve on the performance of individual models and those using committee machines perform better than the other two options; and (ii) committee machine models produce defensible modelling results to develop management scenarios. The study investigates water table declines through management scenarios and shows that in this aquifer water use has higher impacts on water table variations than climatic variations. This provides evidence of the need for planned management in the study area.
Real-Time Scheduling for Xen-ARM Virtual Machines

This paper investigates the feasibility of real-time scheduling with mobile hypervisor, Xen-ARM. Particularly for mobile virtual machines, real-time support is in high demand. However, it is difficult to guarantee real-time scheduling with virtual machines because inter-VM and intra-VM schedulability have to be determined in multi-OS environments. To address the schedulability, first, this paper presents a definition of a real-time virtual machine. Second, this paper analyzes intra-VM schedulability, taking quantization overhead into account. Quantization overhead comes from tick-based scheduling of Xen-ARM, which requires integer presentation of scheduling period and execution slice. Third, to minimize quantization overhead, this paper provides a new algorithm, called SH-quantization that provides accurate and efficient parameterization of a real-time virtual machine. Fourth, this paper presents an inter-VM schedulability test for incorporating multiple real-time virtual machines. To evaluate the approach, we implement the SH-quantization algorithm in Xen-ARM and paravirtualize a real-time OS, called xeno-μC/OS-II. We ran extensive experiments with various configurations of real-time tasks on a real hardware platform in order to characterize the scheduling behavior of real-time virtual machine with quantization. The results show that quantization overhead consumes additional CPU bandwidth up to 90% and the proposed algorithm guarantees intra/inter-VM schedulability with minimal CPU bandwidth.
Conduction of Heat in Paper

The thermal conductivity of paper was measured using a thermoacoustic method based on the propagation of a periodic temperature wave in the medium. Thermal diffusivity and thermal conductivity can be calculated from the resulting phase shift. The thermal conductivities of sheets prepared from different pulps were measured under standard conditions and at 70°C and 10% RH. In paper, heat is conducted through both the solid phase and the gaseous phase. In the case of dense paper and at high moisture contents, heat transfer due to diffusion of water vapour makes a major contribution. The results were used to construct a qualitative physical model for the conduction of heat in paper. In the normal paper density range of 400 – 900 kg/m³ heat conduction can be explained in terms of layers of air and solid phase connected together in different ways. At higher densities and higher moisture contents the mechanisms of hear conduction change. The heat conduction characteristics of paper are better explained using thermal diffusivity calculated in terms of basis weight than by using thermal diffusivity and thermal conductivity.
Cognitive Dimensions of Design Rationale

A design rationale (DR) is a representation of the reasoning behind the design of a system. One of the primary goals in developing a usable DR environment is minimising the cognitive overhead of representing design deliberation in a structured form. This paper examines some of the cognitive attributes of various DR notations, focussing on how generic cognitive dimensions of notations can be operationalised to clarify the relationship between DR notations and the DR authoring process. It is shown how cognitive dimensions analysis makes explicit some of the requirements for DR authoring environments, highlighting the importance of supporting intermediate DR representations; these ‘rough DRs’ evolve as design reasoning unfolds, to reflect new perspectives on the design space.
Towards Ontological Approach on Trust-Aware Ambient Services

With various information sources (e.g., from IoT sensors to social media), it is difficult to provide users with trustworthy services in ambient environment. The aim of this paper is <inline-formula> <tex-math notation="LaTeX">$i$ </tex-math></inline-formula>) to design trust ontology for representing semantics of the ambient services and <inline-formula> <tex-math notation="LaTeX">$ii$ </tex-math></inline-formula>) to compute trust measures among users by using a personalized trust ontology. In particular, given a large amount of data collected from ambient sensors, efficient trust computation and reasoning are required for the stability and reliability. Thereby, we propose trust ontology-based framework for deriving personalized ontologies for individual users according to their preference, perspective, and purpose. To evaluate the proposed model, we have figured out a method how the degree of trust is estimated based on the trust ontology. Furthermore, we have proved that the proposed method is reliable with a case study on a social media (Twitter) for a particular domain (restaurant).
Significant Feature Elimination and Sample Assessment for Remote Sensing Small Objects’ Detection

In recent years, small object detection has remained challenging in remote sensing tasks. First, small objects inherently have fewer pixels, making them susceptible to interference from prominently featured larger objects during feature extraction. Second, existing detection methods solely based on the intersection over union (IOU) loss are disadvantageous for small object detection and fail to leverage the rich prior information in remote sensing images. Based on these observations, we propose a significant feature elimination and sample assessment network for small object detection called SESA-Net, based on the Facet derivative model. SESA-Net introduces prior information to the network through the directional derivatives characteristic of remote sensing images. The overall network comprises the adaptive derivative mask (ADM) module and sample importance assessment (SIA) strategy. The ADM module eliminates significant responses from shallow large objects, directing the network’s focus toward the features of shallow small objects. The SIA strategy addresses the limitations of the IOU loss function using high-quality positive samples generated by ADM to provide an evaluation strategy for different positive samples of small objects. This enables the network to focus more on high-quality positive samples, thereby improving the accuracy of small object detection. The effectiveness of the proposed algorithm has been validated on multiple datasets. Our code is available at https://github.com/Xidian-AIGroup190726/RS-objectdetection-SESANet.