Miracle-dz/UniFAR-FTUs huggingface dataset:
Straightforward Regio- and Diastereoselective Synthesis, Molecular Structure, Intermolecular Interactions and Mechanistic Study of Spirooxindole-Engrafted Rhodanine Analogs

Straightforward regio- and diastereoselective synthesis of bi-spirooxindole-engrafted rhodanine analogs 5a–d were achieved by one-pot multicomponent [3 + 2] cycloaddition (32CA) reaction of stabilized azomethine ylide (AYs 3a–d) generated in situ by condensation of L-thioproline and 6-chloro-isatin with (E)-2-(5-(4-chlorobenzylidene)-2,4-dioxothiazolidin-3-yl)-N-(2-morpholinoethyl)acetamide. The bi-spirooxindole-engrafted rhodanine analogs were constructed with excellent diastereo- and regioselectivity along with high chemical yield. X-ray crystallographic investigations for hybrid 5a revealed the presence of four contiguous stereocenters related to C11, C12, C19 and C22 of the spiro structure. Hirshfeld calculations indicated the presence of many short intermolecular contacts such as Cl.C, S.S, S.H, O.H, N.H, H.C, C.C and H.H interactions. These contacts played a very important role in the crystal stability. The polar nature of the 32CA reaction was studied by analysis of the conceptual DFT reactivity indices. Theoretical study of this 32CA reaction indicated that it takes place through a non-concerted two-stage one-step mechanism associated with the nucleophilic attack of AY 3a to the electrophilic ethylene derivative.
Towards an Improvement of Anticancer Activity of Benzyl Adenosine Analogs

N6-Isopentenyladenosine (i6A) is a naturally occurring modified nucleoside displaying in vitro and in vivo antiproliferative and pro-apoptotic properties. In our previous studies, including an in silico inverse virtual screening, NMR experiments and in vitro enzymatic assays, we demonstrated that i6A targeted farnesyl pyrophosphate synthase (FPPS), a key enzyme involved in the mevalonate (MVA) pathway and prenylation of downstream proteins, which are aberrant in several cancers. Following our interest in the anticancer effects of FPPS inhibition, we developed a panel of i6A derivatives bearing bulky aromatic moieties in the N6 position of adenosine. With the aim of clarifying molecular action of N6-benzyladenosine analogs on the FPPS enzyme inhibition and cellular toxicity and proliferation, herein we report the evaluation of the N6-benzyladenosine derivatives’ (compounds 2a–m) effects on cell viability and proliferation on HCT116, DLD-1 (human) and MC38 (murine) colorectal cancer cells (CRC). We found that compounds 2, 2a and 2c showed a persistent antiproliferative effect on human CRC lines and compound 2f exerted a significant effect in impairing the prenylation of RAS and Rap-1A proteins, confirming that the antitumor activity of 2f was related to the ability to inhibit FPPS activity.
Analysis of Factors Influencing Intensity Use of Mobile Banking Islamic Bank

The development of internet users and technology has influenced the banking industry to transform its services towards digital. XYZ Sharia Bank is one of the banks that implements a digital banking service strategy through mobile banking. The purpose of this study is to describe the characteristics of mobile banking users, then analyze what influences the behavioral intentions of users in increasing the intensity of mobile banking use, and provide recommendations for development strategies for Islamic Bank XYZ to increase the intensity of mobile banking use. The results of this study qualitatively indicate that the characteristics of XYZ Islamic Bank mobile banking users are dominated by millennial generation males. XYZ Syariah Bank is the choice for mobile banking services because of its practical and flexible use. In addition to general banking transactions, XYZ Syariah Bank mobile banking is also an option because it provides services to complement people's lifestyles, namely for digital wallet refills, online shopping payments through the marketplace/e-commerce. The results of the research quantitatively indicate that all of the variables studied, namely perceived usefulness, ease of use, interaction needs, perceived risk, perceived cost of use, trustworthiness, credibility, and compatibility with lifestyle and needs have a significant influence on the intensity of using Islamic Bank mobile banking XYZ, where the biggest factor in influencing the intensity of the use of XYZ Islamic Bank's mobile banking is compatibility with lifestyle and needs. Keywords: Digital Banking, Mobile Banking, Intensity of Using, Sharia Bank.
Dependable Sensor Fault Reconstruction in Air-Path System of Heavy-Duty Diesel Engines

This paper addresses the problem of robust sensor faults detection and isolation in the air-path system of heavy-duty diesel engines, which has not been completely considered in the literature. Calibration or the total failure of a sensor can cause sensor faults. In the worst-case scenario, the engines can be totally damaged by the sensor faults. For this purpose, a second-order sliding mode observer is proposed to reconstruct the sensor faults in the presence of unknown external disturbances. To this aim, the concept of the equivalent output error injection method and the linear matrix inequality (LMI) tool are utilized to minimize the effects of uncertainties and disturbances on the reconstructed fault signals. The simulation results verify the performance and robustness of the proposed method. By reconstructing the sensor faults, the whole system can be prevented from failing before the corrupted sensor measurements are used by the controller.
Transcriptional adaptation of sensory neurons to GPCR identity and activity

Sensory adaptation is critical to extract information from a changing world. Taking advantage of the extensive parallel coding lines present in the olfactory system, we explored the potential variations of neuronal identities before and after olfactory experience. We found that at rest, the transcriptomic profiles of olfactory sensory neuron populations are already highly divergent, specific to the olfactory receptor they express, and are surprisingly associated with the sequence of these latter. These divergent profiles further evolve in response to the environment, as odorant exposure leads to massive reprogramming via the modulation of transcription. Adenylyl cyclase 3, but not other main elements of the olfactory transduction cascade, plays a critical role in this activity-induced transcriptional adaptation. These findings highlight a broad range of sensory neuron identities that are present at rest and that adapt to the experience of the individual, thus providing a novel layer of complexity to sensory coding.
Thyristor switch model for power electronic circuit simulation in modified SPICE 2

Modifications to the commercially available SPICE 2 program that allow the accurate simulation of thyristor circuits are discussed. A near-ideal switch model of a thyristor is developed using resistive components, thus eliminating the problems associated with transistor models. The simulator SPICE 2G.6 is modified and a new input format for the thyristor is implemented. Examples of simulations with the new model agree closely with theoretical and experimental investigations. >
Behavior, Attitude, and Perception toward Safety Culture from Mandatory Safety Training Course

AbstractThe construction industry is one of the most hazardous trades as far as work safety is concerned. Efforts have been made to improve safety in workplace. These efforts have focused on legislation, engineering failure, safety awareness campaigns, safety training, and unsafe behavior. After years of developing safety technologies and safety management systems in the industry, many organizations recognize that the safety culture within the industry has to be addressed if high standards of health and safety are to be maintained. Therefore, this paper investigated the relationship among people’s behavior, attitude, and perception toward the safety culture and evaluated the effectiveness of a mandatory safety training course in Hong Kong’s construction industry. A questionnaire survey and structured interviews were conducted. It was found that a good personal safety attitude, personal roles and commitment among workers, and low obstacles to safe behavior resulted in good perception of accidents. In addit.
Grafting between species of the genus Handroanthus for the production of multi-colored flower canopies

Urban afforestation is done with trees with adequate size for streets, squares and avenues, as well as those with showy canopies. Trees of the genus Handroanthus and belonging to the family Bignoniaceae are widely used due to their canopies flowering in different colors used for landscape purposes. The use of techniques such as grafting, which assist in early flowering and the possibility of canopies producing flowers of different colors can be of importance. This study aimed to analyze the grafting compatibility in bifurcated seedlings of the genus Handroanthus for the production of multi-colored flowering canopies. The experiment was constituted by 10 treatments, with different scion/rootstock combinations. The studied species were Handroanthus heptaphyllus (Hh), Handroanthus impetiginosus (Hi), Handroanthus chrysotrichus (Hc), and Handronthus roseo-albus (Hr-a), using Hi as the only rootstock species (via seeds), and the remaining species, including Hi from adult plants as scions. Single-stem wedge grafting on a bifurcated seedling was adopted for the following combinations: 1. Hc/Hi; 2. Hr-a/Hi; 3. Hh/Hi; 4. Hi/Hi, whereas double-stem wedge grafting was adopted for: 5. Hi/Hi and Hc/Hi; 6. Hi/Hi and Hr-a/Hi; 7. Hi/Hi and Hh/Hi; 8. Hc/Hi and Hr-a/Hi; 9. Hc/Hi and Hh/Hi; and 10. Hr-a/Hi and Hh/Hi), with three replications of five seedlings. The take percentage and vigor were evaluated 50 days after grafting. The highest establishment rates for the single-stem wedge grafting were obtained by the same species grafts Hi/Hi (80%) and by the Hr-a/Hi (86.6%) combination; whereas for the double-stem grafting the following percentages of combinations were obtained: Hc/Hi (93.3%) and Hr-a/Hi (93.3%); Hc/Hi (73.3%) and Hh/Hi (86.6%); and Hr-a/Hi (86.6%) and Hh/Hi (86.6%).
Detection of Surface Breaking Cracks Using Flying Line Laser Thermography: A Canny-Based Algorithm

In this work, we introduce a new algorithm for effectual crack detection using flying line laser thermography, based on the well-known Canny approach. The algorithm transforms the input thermographic sequence into an edge map. Experimental measurements are performed on a metallic component that contains surface breaking cracks due to industrial use. The specimen is tested using flying line thermography at different scanning speeds and laser input powers. Results obtained with the proposed algorithm are additionally compared with a previously established algorithm for flying spot thermography. The proposed Canny-based algorithm can be used in automated systems for thermographic non-destructive testing.
Decarbonization of Summer Cooling Energy Demands of Buildings Employing Absorption Systems in the Framework of Climate Change in Italy

Temperatures in the Mediterranean area have gradually risen in the last decades due to climate change, especially in the Italian Peninsula. This phenomenon has increased the cooling needs to ensure thermal comfort in buildings and, consequently, the use of refrigeration machines. Summer air conditioning is carried out mainly using compression machines powered by electricity supplied by the national network. All this contributes to the emission of climate-changing gases. To avoid this disadvantageous chain, compression machines could be replaced by absorption cooling systems powered by solar energy. The energy needs of the buildings in a time are directly proportional to the sum of positive differences between the outdoor air temperature and the indoor set point of the systems (equal to 26°C). The annual sum of hourly temperature differences defined above can be computed for each grid cell thanks to a numerical weather prediction model, namely the Weather Research and Forecasting model, that simulates the hourly temperatures on high-resolution computation grids and over fairly large extents. Maps of cooling consumption for buildings are thus produced. Choosing absorption solar energy-powered systems instead of vapor compression refrigeration systems leads to a drop in electrical energy consumption and therefore in emissions of greenhouse gases. In this work, different hypothetical scenarios of penetration of this technology have been considered. And the subsequent consumption of electricity withdrawn from the national grid has been estimated together with the reduction of greenhouse gas emissions.
Mesenchymal Stromal Cells Adapt to Chronic Tendon Disease Environment with an Initial Reduction in Matrix Remodeling

Tendon lesions are common sporting injuries in humans and horses alike. The healing process of acute tendon lesions frequently results in fibrosis and chronic disease. In horses, local mesenchymal stromal cell (MSC) injection is an accepted therapeutic strategy with positive influence on acute lesions. Concerning the use of MSCs in chronic tendon disease, data are scarce but suggest less therapeutic benefit. However, it has been shown that MSCs can have a positive effect on fibrotic tissue. Therefore, we aimed to elucidate the interplay of MSCs and healthy or chronically diseased tendon matrix. Equine MSCs were cultured either as cell aggregates or on scaffolds from healthy or diseased equine tendons. Higher expression of tendon-related matrix genes and tissue inhibitors of metalloproteinases (TIMPs) was found in aggregate cultures. However, the tenogenic transcription factor scleraxis was upregulated on healthy and diseased tendon scaffolds. Matrix metalloproteinase (MMPs) expression and activity were highest in healthy scaffold cultures but showed a strong transient decrease in diseased scaffold cultures. The release of glycosaminoglycan and collagen was also higher in scaffold cultures, even more so in those with tendon disease. This study points to an early suppression of MSC matrix remodeling activity by diseased tendon matrix, while tenogenic differentiation remained unaffected.
A new optimal model predictive control scheme for a wind energy conversion system

The correct management of power exchange between the doubly‐Fed induction generator (DFIG) and the grid depends on the effective optimal operation of the DFIG based wind energy conversion system (WECS). A modified optimal model predictive controller (MPC) architecture for WECS is proposed in this paper. The proposed scheme is carried out in two stages, as follows: (a) Using the MPC model and the tracking factor, an optimal control law is created, and (b) the aforementioned optimized issue is addressed using the linear matrix inequality (LMI) approach. Some improvements were made to the conventional LMI‐based MPC technique to lower the high computational complexity. To perform active and reactive power control in DFIG, the proposed approach is applied on the rotor‐side converter (RSC) control. The control law is divided into two sections. The first section deals with rotor current, while the second section deals with the RSC switching states. The LMI is used in the second portion of the control law to find the best switching state solution. The proposed method was created using the MATLAB/SIMULINK environment and tested in a 1hP DFIG‐WECS setup. By comparing the obtained results to conventional LMI‐PI, MPC‐based WECS, the effectiveness of the obtained results is verified. Variable wind speed conditions are used to vary all the results. Integral absolute error, integral time absolute error, and Integral square error measurements are used to compare the tracking performance index of all methods.
A medical image segmentation method based on multi-scale feature extraction

Medical image segment is considered as an important technology in clinical diagnosis. Manual segment is an accurate method but is too time-consuming and laborious. Hence how to realize fast and accurate automatic segmentation with deep learning has been attached more importance in recent years. In view of most segment model loses detailed information due to the convolution and pooling operations, in this paper, we propose a new model to improve the segment result by extracting multi-scale feature at each stage. Our segment model, called mixed-net, combines our multi-scale dilated convolution module (MDCM) with u-net by skip connections across stage. Due to the sufficient feature extraction in shallow layers, the mixed-net can reduce information loss in the processing of training data without increasing network size greatly. Using MDCM before skip connection also can bridge semantic gap between shallow and deeper layers. The experiments on retinal blood vessels images segmentation shows that our mixed-net performs better than u-net after training on DRIVE data sets.
Broadband Square Slot Circularly Polarized Antenna for Wimax and Wlan Applications

A compact coplanar waveguide‐fed circularly polarized antenna with corner truncated ground for broadband wireless applications is presented. The antenna is designed to have a U‐shaped feedline in conjunction with an inverted L‐strip and a 45° bent strip to cover a fractional bandwidth of more than 103% (2.69–8.83 GHz) and fractional 3‐dB axial ratio bandwidth of 58.93% (2.92–5.36 GHz). Triangle shaped pieces are removed from top corners of the antenna to excite circular polarization. The antenna is manufactured and its parameters are measured. It has been shown that there is a good agreement between simulated and experimental results. © 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:2191–2195, 2013
MSST-Net: A Multi-Scale Adaptive Network for Building Extraction from Remote Sensing Images Based on Swin Transformer

The segmentation of remote sensing images by deep learning technology is the main method for remote sensing image interpretation. However, the segmentation model based on a convolutional neural network cannot capture the global features very well. A transformer, whose self-attention mechanism can supply each pixel with a global feature, makes up for the deficiency of the convolutional neural network. Therefore, a multi-scale adaptive segmentation network model (MSST-Net) based on a Swin Transformer is proposed in this paper. Firstly, a Swin Transformer is used as the backbone to encode the input image. Then, the feature maps of different levels are decoded separately. Thirdly, the convolution is used for fusion, so that the network can automatically learn the weight of the decoding results of each level. Finally, we adjust the channels to obtain the final prediction map by using the convolution with a kernel of 1 × 1. By comparing this with other segmentation network models on a WHU building data set, the evaluation metrics, mIoU, F1-score and accuracy are all improved. The network model proposed in this paper is a multi-scale adaptive network model that pays more attention to the global features for remote sensing segmentation.
Prediction of Software Defect Using Ensemble Learning Based Improved Sparrow Search Algorithm To Optimize Extreme Learning Machine

For the traditional ensemble learning algorithm of software defect prediction, the base predictor exists the problem that too many parameters are difficult to optimize, resulting in the optimized performance of the model unable to be obtained. An ensemble learning algorithm for software defect prediction that is proposed by using the improved sparrow search algorithm to optimize the extreme learning machine, which divided into three parts. Firstly, the improved sparrow search algorithm (ISSA) is proposed to improve the optimization ability and convergence speed, and the performance of the improved sparrow search algorithm is tested by using eight benchmark test functions. Secondly, ISSA is used to optimize extreme learning machine (ISSA-ELM) to improve the prediction ability. Finally, the optimized ensemble learning algorithm (ISSA-ELM-Bagging) is presented in the Bagging algorithm which improve the prediction performance of ELM in software defect datasets. Experiments are carried out in six groups of software defect datasets. The experimental results show that ISSA-ELM-Bagging ensemble learning algorithm is significantly better than the other four comparison algorithms under the six evaluation indexes of Precision, Recall, F-measure, MCC, Accuracy and G-mean, which has better stability and generalization ability.
Combined Pharmacophore and Grid-Independent Molecular Descriptors (GRIND) Analysis to Probe 3D Features of Inositol 1,4,5-Trisphosphate Receptor (IP3R) Inhibitors in Cancer

Inositol 1, 4, 5-trisphosphate receptor (IP3R)-mediated Ca2+ signaling plays a pivotal role in different cellular processes, including cell proliferation and cell death. Remodeling Ca2+ signals by targeting the downstream effectors is considered an important hallmark in cancer progression. Despite recent structural analyses, no binding hypothesis for antagonists within the IP3-binding core (IBC) has been proposed yet. Therefore, to elucidate the 3D structural features of IP3R modulators, we used combined pharmacoinformatic approaches, including ligand-based pharmacophore models and grid-independent molecular descriptor (GRIND)-based models. Our pharmacophore model illuminates the existence of two hydrogen-bond acceptors (2.62 Å and 4.79 Å) and two hydrogen-bond donors (5.56 Å and 7.68 Å), respectively, from a hydrophobic group within the chemical scaffold, which may enhance the liability (IC50) of a compound for IP3R inhibition. Moreover, our GRIND model (PLS: Q2 = 0.70 and R2 = 0.72) further strengthens the identified pharmacophore features of IP3R modulators by probing the presence of complementary hydrogen-bond donor and hydrogen-bond acceptor hotspots at a distance of 7.6–8.0 Å and 6.8–7.2 Å, respectively, from a hydrophobic hotspot at the virtual receptor site (VRS). The identified 3D structural features of IP3R modulators were used to screen (virtual screening) 735,735 compounds from the ChemBridge database, 265,242 compounds from the National Cancer Institute (NCI) database, and 885 natural compounds from the ZINC database. After the application of filters, four compounds from ChemBridge, one compound from ZINC, and three compounds from NCI were shortlisted as potential hits (antagonists) against IP3R. The identified hits could further assist in the design and optimization of lead structures for the targeting and remodeling of Ca2+ signals in cancer.
Multi-agent-based approach to solve part selection and task allocation problem in flexible manufacturing systems

Agent technology is currently being considered as an important approach for developing intelligent manufacturing systems. It offers a new way of thinking about many of the classical problems in manufacturing engineering. A multi-agent-based approach for solving the part allocation problems in flexible manufacturing systems (FMS) is presented that can easily cope with the dynamic environment. Four agents were involved in carrying out the tasks of allocating parts on different machines: communicator, machine, part and material handling device (MHD). Upon arrival in the manufacturing facility, the part informs the communicator agent about the task requirements. The communicator agent divides the task into subtasks and sends a call-for-bids message to the machine and MHD agents. Each machine responds in accordance with its process capabilities and buffer limit. This response may be for the whole task or for one or more subtasks and it contains the price and cost details for these subtasks along with the performance index and acceptance ratio of the machine. The final allocation is made based on the objective function that includes processing and transportation costs and time. An algorithm is presented that is used by the communicator agent for allocating parts to different machines. An illustrative example is given to solve the task allocation on five machines, with each machine having different performance index and acceptance ratio.