Search Results (10)

The mid-infrared band is the last major observational window for the ground-based large solar telescopes in the 21st century. Achieving ultra-narrowband filter imaging is a fundamental challenge that all solar telescopes encounter as they progress towards the mid-infrared spectrum. The guided-mode resonance filtering (GMRF) technology provides a promising solution to this critical issue. This paper describes in detail the fundamental principles and calculation procedure of guided-mode resonance filtering. Building upon this foundation, a preliminary design and simulation of a mid-infrared guided-mode resonance filter are carried out. The results show that when the thickness of the sub-wavelength grating is an even multiple of the half-wavelength, it is feasible to attain ultra-narrowband filtering with a bandwidth below 0.03 nm by increasing the grating thickness and decreasing the grating fill factor. Nevertheless, the high sensitivity of the resonant wavelength to the angle of incidence still stands as a formidable obstacle that demands further investigation and resolution. Full article

In the 21st century, chemotherapy stands as a primary treatment method for prevalent diseases, yet drug resistance remains a pressing challenge. Utilizing electrospinning to support chemotherapy drugs offers sustained and controlled release methods in contrast to oral and implantable drug delivery modes, which enable localized treatment of distinct tumor types. Moreover, the core–sheath structure in electrospinning bears advantages in dual-drug loading: the core and sheath layers can carry different drugs, facilitating collaborative treatment to counter chemotherapy drug resistance. This approach minimizes patient discomfort associated with multiple-drug administration. Electrospun fibers not only transport drugs but can also integrate metal particles and targeted compounds, enabling combinations of chemotherapy with magnetic and heat therapies for comprehensive cancer treatment. This review delves into electrospinning preparation techniques and drug delivery methods tailored to various cancers, foreseeing their promising roles in cancer treatment. Full article

The leaf area index (LAI) is a crucial parameter for analyzing terrestrial ecosystem carbon cycles and global climate change. Obtaining high spatiotemporal resolution forest stand vegetation LAI products over large areas is essential for an accurate understanding of forest ecosystems. This study takes the northwestern part of the Inner Mongolia Autonomous Region (the northern section of the Greater Khingan Mountains) in northern China as the research area. It also generates the LAI time series product of the 8-day and 30 m forest stand vegetation growth period from 2013 to 2017 (from the 121st to the 305th day of each year). The Simulated Annealing-Back Propagation Neural Network (SA-BPNN) model was used to estimate LAI from Landsat8 OLI, and the multi-period GaoFen-1 WideField-View satellite images (GF-1 WFV) and the spatiotemporal adaptive reflectance fusion mode (STARFM) was used to predict high spatiotemporal resolution LAI by combining inversion LAI and Global LAnd Surface Satellite-derived vegetation LAI (GLASS LAI) products. The results showed the following: (1) The SA-BPNN estimation model has relatively high accuracy, with R² = 0.75 and RMSE = 0.38 for the 2013 LAI estimation model, and R² = 0.74 and RMSE = 0.17 for the 2016 LAI estimation model. (2) The fused 30 m LAI product has a good correlation with the LAI verification of the measured sample site (R² = 0.8775) and a high similarity with the GLASS LAI product. (3) The fused 30 m LAI product has a high similarity with the GLASS LAI product, and compared with the GLASS LAI interannual trend line, it accords with the growth trend of plants in the seasons. This study provides a theoretical and technical reference for forest stand vegetation growth period LAI spatiotemporal fusion research based on high-score data, and has an important role in exploring vegetation primary productivity and carbon cycle changes in the future. Full article

The abrupt transfer from grid-connected (GC) to stand-alone (SA) operation modes is one of the major issues that may threaten the stability of a distributed generation (DG) system. Furthermore, if the islanding mode happens, it is vital to take into consideration the load voltages or load current waveforms as soon as feasible. This paper develops an advanced control technique based on a super-twisting sliding mode controller (ST-SMC) for a three-phase inverter operating in both the GC and SA modes. This control scheme is proposed to ensure a smooth transition from the GC to SA mode and enhance the load voltage waveforms under the islanding mode. In addition, to minimize the operational costs of the system and the complexity of the studied model, a digital Luenberger observer (DLO) with a proper design is adopted for estimating the inverter-side current. The control scheme of the whole system switches between a current control mode during the GC mode and a voltage control mode during the SA mode. The super-twisting control algorithm is applied to the outer voltage control loop involved in the cascaded voltage/current control scheme in the SA mode. Simulation tests of a three-phase inverter are performed for the purpose of assessing the suggested control performance by using the PowerSim (PSIM) software and comparing it with a classical PI controller. Furthermore, a processor-in-the-loop (PIL) implementation in a DSP board TMS32F28335 while debugging is conducted using code composer studio 6.2.0. The obtained results show efficient control properties, such as a smooth transition among the microgrid (MG) operating modes, as well as effectiveness and robustness during both the GC and SA operation modes. Full article

Intelligent lower-limb prosthesis appears in the public view due to its attractive and potential functions, which can help amputees restore mobility and return to normal life. To realize the natural transition of locomotion modes, locomotion mode classification is the top priority. There are mainly five steady-state and periodic motions, including LW (level walking), SA (stair ascent), SD (stair descent), RA (ramp ascent), and RD (ramp descent), while ST (standing) can also be regarded as one locomotion mode (at the start or end of walking). This paper mainly proposes four novel features, including TPDS (thigh phase diagram shape), KAT (knee angle trajectory), CPO (center position offset) and GRFPV (ground reaction force peak value) and designs ST classifier and artificial neural network (ANN) classifier by using a user-dependent dataset to classify six locomotion modes. Gaussian distributions are applied in those features to simulate the uncertainty and change of human gaits. An angular velocity threshold and GRFPV feature are used in the ST classifier, and the artificial neural network (ANN) classifier explores the mapping relation between our features and the locomotion modes. The results show that the proposed method can reach a high accuracy of 99.16% ± 0.38%. The proposed method can provide accurate motion intent of amputees to the controller and greatly improve the safety performance of intelligent lower-limb prostheses. The simple structure of ANN applied in this paper makes adaptive online learning algorithms possible in the future. Full article

A quasi-Z-source inverter (qZSI) is a single-stage inverter that enables a boost of the input dc voltage through the utilization of a so-called shoot-through state (STS). Generally, the efficiency of the qZSI depends on the utilized STS injection method to a significant extent. This paper presents a novel method of STS injection, called the zero-sync method, in which the STS occurrence is synchronized with the beginning of the zero switching states (ZSSs) of the three-phase sinusoidal pulse width modulation (SPWM). In this way, compared to the conventional STS injection method, the total number of switchings per transistor is reduced. The ZSSs are detected by utilizing the SPWM pulses and the logic OR gates. The desired duration of the STS is implemented by utilizing the LM555CN timer. The laboratory setup of the three-phase qZSI in the stand-alone operation mode was built to compare the proposed zero-sync method with the conventional STS injection method. The comparison was carried out for different values of the switching frequency, input voltage, duty ratio, and load power. As a result of the implementation of the zero-sync method, the qZSI efficiency was increased by up to 4%. In addition, the unintended STSs, caused by the non-ideal switching dynamics of the involved transistors, were successfully eliminated by introducing the optimal dead-time as part of the modified zero-sync method. As a result, the efficiency was increased by up to 12% with regard to the conventional method. Full article

My paper analyses the 15th-century seven-sacraments font at the medieval church of St Peter and St Paul at Salle in Norfolk (England). The church guides and gazetteers that describe the font, and the church in which it is situated, owe both their style and content to Art History, focusing as they do on their material and aesthetic dimensions. The guides also tend towards isolating the various elements of the font, and these in turn from the rest of the architectural elements, fittings and furniture of the church, as if they could be meaningfully experienced or interpreted as discrete entities, in isolation from one another. While none of the font descriptions can be faulted for being inaccurate, they can, as a result of these tendencies, be held insufficient, and not quite to the purpose. My analysis of the font, by means of Heidegger’s concept of Dwelling, does not separate the font either from the rest of the church, nor from other fonts, but acknowledges that it comes to be, and be seen as, what it is only when considered as standing in ‘myriad referential relations’ to other things, as well as to ourselves. This perspective has enabled me to draw out what it is about the font at Salle that can be experienced as not merely beautiful or interesting, but also as meaningful to those—believers and non-believers alike—who encounter it. By reconsidering the proper mode of perceiving and engaging with the font, we may spare it from being commodified, from becoming a unit in the standing reserve of cultural heritage, and in so doing, we, too, may be momentarily freed from our false identities as units of production and agents of consumption. The medieval fonts and churches of Norfolk are, I argue, not valuable as a result of their putative antiquarian qualities, but invaluable in their extending to us a possibility of dwelling—as mortals—on the earth—under the sky—before the divinities. Full article

A large eddy simulation (LES) and combustion instability analysis are performed using OpenFOAM for the multiple shear-coaxial injector combustor DLR-BKD (in German Deutsches Zentrum für Luft–Brennkammer D, German Aerospace Center–Combustion Chamber D), which is a laboratory-scale combustor operating in a real-gas environment. The Redlich–Kwong–Peng–Robinson equation of state and steady-laminar flamelet model are adopted in the simulation to accurately capture the real-gas combustion effects. Moreover, the stable combustion under the LP4 condition is numerically analyzed, and the characteristics of the combustion flow field are investigated. In the numerical simulation of the combustion instability, the instability is generated by artificially superimposing the 1st transverse standing wave solution on the stable combustion solution. To decompose the combustion instability mode, the dynamic mode decomposition method is applied. Several combustion instability modes are qualitatively and quantitatively identified through contour plots and graphs, and the sustenance process of the limit cycle is investigated. Full article

Parkinson’s disease (PD) is one of the leading neurological disorders in the world with an increasing incidence rate for the elderly. Freezing of Gait (FOG) is one of the most incapacitating symptoms for PD especially in the later stages of the disease. FOG is a short absence or reduction of ability to walk for PD patients which can cause fall, reduction in patients’ quality of life, and even death. Existing FOG assessments by doctors are based on a patient’s diaries and experts’ manual video analysis which give subjective, inaccurate, and unreliable results. In the present research, an automatic FOG assessment system is designed for PD patients to provide objective information to neurologists about the FOG condition and the symptom’s characteristics. The proposed FOG assessment system uses an RGB-D sensor based on Microsoft Kinect V2 for capturing data for 5 healthy subjects who are trained to imitate the FOG phenomenon. The proposed FOG assessment system is called “Kin-FOG”. The analysis of foot joint trajectory of the motion captured by Kinect is used to find the FOG episodes. The evaluation of Kin-FOG is performed by two types of experiments, including: (1) simple walking (SW); and (2) walking with turning (WWT). Since the standing mode has features similar to a FOG episode, our Kin-FOG system proposes a method to distinguish between the FOG and standing episodes. Therefore, two general groups of experiments are conducted with standing state (WST) and without standing state (WOST). The gradient displacement of the angle between the foot and the ground is used as the feature for discriminating between FOG and standing modes. These experiments are conducted with different numbers of FOGs for getting reliable and general results. The Kin-FOG system reports the number of FOGs, their lengths, and the time slots when they occur. Experimental results demonstrate Kin-FOG has around 90% accuracy rate for FOG prediction in both experiments for different tasks (SW, WWT). The proposed Kin-FOG system can be used as a remote application at a patient’s home or a rehabilitation clinic for sending a neurologist the required FOG information. The reliability and generality of the proposed system will be evaluated for bigger data sets of actual PD subjects. Full article

Compared with optical sensors, Synthetic Aperture Radar (SAR) can provide important damage information due to its ability to map areas affected by earthquakes independently from weather conditions and solar illumination. In 2013, a new TerraSAR-X mode named staring spotlight (ST), whose azimuth resolution was improved to 0.24 m, was introduced for various applications. This data source made it possible to extract detailed information from individual buildings. In this paper, we present a new concept for individual building damage assessment using a post-event sub-meter very high resolution (VHR) SAR image and a building footprint map. With the building footprint map, the original footprints of buildings can be located in the SAR image. Based on the building imaging analysis of a building in the SAR image, the features in the building footprint can be extracted to identify standing and collapsed buildings. Three machine learning classifiers, including random forest (RF), support vector machine (SVM) and K-nearest neighbor (K-NN), are used in the experiments. The results show that the proposed method can obtain good overall accuracy, which is above 80% with the three classifiers. The efficiency of the proposed method is demonstrated based on samples of buildings using descending and ascending sub-meter VHR ST images, which were all acquired from the same area in old Beichuan County, China. Full article