ALBERT

Description: Crowdsourcing is a new mode of value creation in which organizations leverage numerous Internet users to accomplish tasks. However, because these workers have different backgrounds and intentions, crowdsourcing suffers from quality concerns. In the literature, tracing the behavior of workers is preferred over other methodologies such as consensus methods and gold standard approaches. This paper proposes two novel models based on workers’ behavior for task classification. These models newly benefit from time-series features and characteristics. The first model uses multiple time-series features with a machine learning classifier. The second model converts time series into images using the recurrent characteristic and applies a convolutional neural network classifier. The proposed models surpass the current state of-the-art baselines in terms of performance. In terms of accuracy, our feature-based model achieved 83.8%, whereas our convolutional neural network model achieved 76.6%.

Description: In this work, a kind of Gd/Cr codoped Bi3TiNbO9 Aurivillius phase ceramic with the formula of Bi2.8Gd0.2TiNbO9 + 0.2 wt% Cr2O3 (abbreviated as BGTN−0.2Cr) was prepared by a conventional solid-state reaction route. Microstructures and electrical conduction behaviors of the ceramic were investigated. XRD and SEM detection found that the BGTN−0.2Cr ceramic was crystallized in a pure Bi3TiNbO9 phase and composed of plate-like grains. A uniform element distribution involving Bi, Gd, Ti, Nb, Cr, and O was identified in the ceramic by EDS. Because of the frequency dependence of the conductivity between 300 and 650 °C, the electrical conduction mechanisms of the BGTN−0.2Cr ceramic were attributed to the jump of the charge carriers. Based on the correlated barrier hopping (CBH) model, the maximum barrier height WM, dc conduction activation energy Ec, and hopping conduction activation energy Ep were calculated with values of 0.63 eV, 1.09 eV, and 0.73 eV, respectively. Impedance spectrum analysis revealed that the contribution of grains to the conductance increased with rise in temperature; at high temperatures, the conductance behavior of grains deviated from the Debye relaxation model more than that of grain boundaries. Calculation of electrical modulus further suggested that the degree of interaction between charge carriers β tended to grow larger with rising temperature. In view of the approximate relaxation activation energy (~1 eV) calculated from Z″ and M″ peaks, the dielectric relaxation process of the BGTN−0.2Cr ceramic was suggested to be dominated by the thermally activated motion of oxygen vacancies as defect charge carriers. Finally, a high piezoelectricity of d33 = 18 pC/N as well as a high resistivity of ρdc = 1.52 × 105 Ω cm at 600 °C provided the BGTN−0.2Cr ceramic with promising applications in the piezoelectric sensors with operating temperature above 600 °C.

Description: During the past year, health care environments have struggled to cope with the various impacts of COVID-19 around the world. Health care facilities need to help strengthen resistance to pathogen threats and provide care for patients and health workers in the safest possible way. Architectural design strategies can play a significant role in infection prevention and control. The current study aims to examine the experiences of health workers with hospital spaces during the COVID-19 pandemic. Identifying the difficulties they face, the present study attempts to shed light on the role of the health care layout configuration in combating pandemics. The authors conducted observations at four hospitals and a series of online semi-structured interviews with 162 health care staff from March to May 2020. The study indicated that space configuration and the hospitalization of patients, layout and circulation of the environment, operation services such as indoor environment conditions, maintenance of health care system, and organizational support for health care staff were the most critical factors affecting infection control in health care environments. The initial zoning and separation of patients were the most effective methods of controlling infection. Hospitals with clustered plan layouts were found to be the most effective buildings for the zoning of COVID-19 patients during the pandemic and for infection control.

Description: Aimed at the problem of the small wet etching depth in sapphire microstructure processing technology, a multilayer composite mask layer is proposed. The thickness of the mask layer is studied, combined with the corrosion rate of different materials on sapphire in the sapphire etching solution, different mask layers are selected for the corrosion test on the sapphire sheet, and then the corrosion experiment is carried out. The results show that at 250 °C, the choice is relatively high when PECVD (Plasma Enhanced Chemical Vapor Deposition) is used to make a double-layer composite film of silicon dioxide and silicon nitride. When the temperature rises to 300 °C, the selection ratio of the silicon dioxide layer grown by PECVD is much greater than that of the silicon nitride layer. Therefore, under high temperature conditions, a certain thickness of silicon dioxide can be used as a mask layer for deep cavity corrosion.

Description: Publicly available optical remote sensing images from platforms such as Sentinel-2 satellites contribute much to the Earth observation and research tasks. However, information loss caused by clouds largely decreases the availability of usable optical images so reconstructing the missing information is important. Existing reconstruction methods can hardly reflect the real-time information because they mainly make use of multitemporal optical images as reference. To capture the real-time information in the cloud removal process, Synthetic Aperture Radar (SAR) images can serve as the reference images due to the cloud penetrability of SAR imaging. Nevertheless, large datasets are necessary because existing SAR-based cloud removal methods depend on network training. In this paper, we integrate the merits of multitemporal optical images and SAR images to the cloud removal process, the results of which can reflect the ground information change, in a simple convolution neural network. Although the proposed method is based on deep neural network, it can directly operate on the target image without training datasets. We conduct several simulation and real data experiments of cloud removal in Sentinel-2 images with multitemporal Sentinel-1 SAR images and Sentinel-2 optical images. Experiment results show that the proposed method outperforms those state-of-the-art multitemporal-based methods and overcomes the constraint of datasets of those SAR-based methods.

Description: Spiro compounds provide attractive targets in drug discovery due to their inherent three-dimensional structures, which enhance protein interactions, aid solubility and facilitate molecular modelling. However, synthetic methodology for the spiro-functionalisation of important classes of penicillin and cephalosporin β-lactam antibiotics is comparatively limited. We report a novel method for the generation of spiro-cephalosporin compounds through a Michael-type addition to the dihydrothiazine ring. Coupling of a range of catechols is achieved under mildly basic conditions (K2CO3, DMF), giving the stereoselective formation of spiro-cephalosporins (d.r. 14:1 to 8:1) in moderate to good yields (28−65%).

Description: (1) Background: Physical restraint in psychiatric settings must be determined by health care professionals for ensuring their patients’ safety. However, when a patient cannot participate in the process of deciding what occurs in their own body, can they even be considered as a personal self who lives in and experiences the lifeworld? The purpose of this study is to review the existential capability of the body from Merleau-Ponty’s phenomenology to explore ways of promoting human rights in physical restraint. (2) Methods: A philosophical reflection was contemplated regarding notions of the body’s phenomenology. (3) Results: Merleau-Ponty’s body phenomenology can explain bodily phenomena as a source of the personal subject, who perceives and acts in the world, and not as a body alienated from the subject in health and illness. Patients, when they are physically restrained, cannot be the self as a subject because their body loses its subjecthood. They are entirely objectified, becoming objects of diagnosis, protection, and control, according to the treatment principles of health care professionals. (4) Conclusions: The foundation of human rights, human being’s dignity lies in the health professionals’ genuine understanding and response to the existential crisis of the patient’s body in relation to its surrounding environment.

Description: The review presents the development of an approach of constructing approximate solutions to complicated physics problems, starting from asymptotic series, through optimized perturbation theory, to self-similar approximation theory. The close interrelation of underlying ideas of these theories is emphasized. Applications of the developed approach are illustrated by typical examples demonstrating that it combines simplicity with good accuracy.

Description: With the aim of increasing the efficiency of maintenance and fuel usage in airplanes, structural health monitoring (SHM) of critical composite structures is increasingly expected and required. The optimized usage of this concept is subject of intensive work in the framework of the EU COST Action CA18203 “Optimising Design for Inspection” (ODIN). In this context, a thorough review of a broad range of energy harvesting (EH) technologies to be potentially used as power sources for the acoustic emission and guided wave propagation sensors of the considered SHM systems, as well as for the respective data elaboration and wireless communication modules, is provided in this work. EH devices based on the usage of kinetic energy, thermal gradients, solar radiation, airflow, and other viable energy sources, proposed so far in the literature, are thus described with a critical review of the respective specific power levels, of their potential placement on airplanes, as well as the consequently necessary power management architectures. The guidelines provided for the selection of the most appropriate EH and power management technologies create the preconditions to develop a new class of autonomous sensor nodes for the in-process, non-destructive SHM of airplane components.

Description: At present, inspection systems process visual data captured by cameras, with deep learning approaches applied to detect defects. Defect detection results usually have an accuracy higher than 94%. Real-life applications, however, are not very common. In this paper, we describe the development of a tire inspection system for the tire industry. We provide methods for processing tire sidewall data obtained from a camera and a laser sensor. The captured data comprise visual and geometric data characterizing the tire surface, providing a real representation of the captured tire sidewall. We use an unfolding process, that is, a polar transform, to further process the camera-obtained data. The principles and automation of the designed polar transform, based on polynomial regression (i.e., supervised learning), are presented. Based on the data from the laser sensor, the detection of abnormalities is performed using an unsupervised clustering method, followed by the classification of defects using the VGG-16 neural network. The inspection system aims to detect trained and untrained abnormalities, namely defects, as opposed to using only supervised learning methods.