Miracle-dz/UniFAR-FTUs huggingface dataset:
A three‐sector array with switchable beams

A design for beam steering antenna arrays is described. The radiating element of the array is mainly composed of dual coplanar slotted‐patch antennas, a metallic reflector, and several PIN diodes embedded in the slots. By controlling the states of the diodes, the operation of the slotted‐patch antennas can be switched among three modes. These operation modes can generate three radiation beams respectively directed to ϕ = 0°, 40°, and −40° in the H‐plane. On the basis of the pattern reconfigurable antenna element, a three‐sector triangular array operated at 2.2 GHz is developed. The measured results demonstrate that the sector array can provide nine radiation beams which are steerable over a full 360° in the azimuthal plane; in addition, each switched beam has a half‐power beamwidth of about 60° and a cross‐polarization level of lower than −20 dB. Detailed designs of the sector array and its feeding network are presented. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1357–1361, 2017
Epithelial immune regulation of inflammatory airway diseases: Chronic rhinosinusitis with nasal polyps (CRSwNP)

Background: The epithelial immune regulation is an essential and protective feature of the barrier function of the mucous membranes of the airways. Damage to the epithelial barrier can result in chronic inflammatory diseases, such as chronic rhinosinusitis (CRS) or bronchial asthma. Thymic stromal lymphopoietin (TSLP) is a central regulator in the epithelial barrier function and is associated with type 2 (T2) and non-T2 inflammation. Materials and methods: The immunology of chronic rhinosinusitis with polyposis nasi (CRSwNP) was analyzed in a literature search, and the existing evidence was determined through searches in Medline, Pubmed as well as the national and international study and guideline registers and the Cochrane Library. Human studies or studies on human cells that were published between 2010 and 2020 and in which the immune mechanisms of TSLP in T2 and non-T2 inflammation were examined were considered. Results: TSLP is an epithelial cytokine (alarmin) and a central regulator of the immune reaction, especially in the case of chronic airway inflammation. Induction of TSLP is implicated in the pathogenesis of many diseases like CRS and triggers a cascade of subsequent inflammatory reactions. Conclusion: Treatment with TSLP-blocking monoclonal antibodies could therefore open up interesting therapeutic options. The long-term safety and effectiveness of TSLP blockade has yet to be investigated.
Improving the Safety of DIEP Flap Transplantation: Detailed Perforator Anatomy Study Using Preoperative CTA

Background: Deep inferior epigastric perforator and muscle sparing transverse rectus abdominis muscle flaps are commonly used flaps for autologous breast reconstruction. CT-angiography allows to analyse the perforator course preoperatively. Our aim was to compare the different aspects of perforator anatomy in the most detailed study. Methods: CT-angiographies of 300 female patients with autologous breast reconstruction of 10 years were analysed regarding the anatomy of the deep inferior epigastric artery and every perforator. Results: Overall, 2260 perforators were included. We identified correlations regarding the DIEA branching point and number of perforators and their intramuscular course. The largest perforator emerged more often from the medial branch of the DIEA than the smaller perforators (70% (416/595) vs. 54% (878/1634), p < 0.001) and more often had a direct connection to the SIEV (large 67% (401/595) vs. small 39% (634/1634), p < 0.01). Medial row perforators were larger than the laterals (lateral 1.44 mm ± 0.43 (n = 941) vs. medial 1.58 mm ± 0.52 (n = 1304) (p < 0.001)). The larger and more medial the perforator, the more likely it was connected to the SIEV: perforators with direct connection to the SIEV had a diameter of 1.65 mm ± 0.53 (n = 1050), perforators with indirect connection had a diameter of 1.43 ± 0.43 (n = 1028), perforators without connection had a diameter of 1.31 mm ± 0.37 (n = 169) (p < 0.001). Medial perforators were more often directly connected to the SIEV than lateral perforators (medial 56% (723/1302) vs. lateral 35% (327/941), p < 0.001). A lateral perforator more often had a short intramuscular course than medial perforators (69% (554/800) vs. 45% (474/1055), p < 0.001), which was also more often observed in the case of a small perforator and a caudal exit of the rectus sheath. Conclusion: The largest perforator emerges more often from the medial branch of the DIEA and frequently has a direct connection to the SIEV, making medial row perforators ideal for DIEP flap transplantation.
Three Level IGBT Inverters for Industrial Drives and Traction Applications

AbstractThe advantages of application of IGBTs in PWM-inverters in industrial motor drives with 3-phase voltage of 400 V and medium power range are well known. To extend the application to industrial motor drives with 3-phase voltage of 690 V and to local traffic with de-line voltage of 600/750 V three level IGBT inverters present a good solution. In this paper some details regarding the realization of the power circuit and the pulse pattern generator with space vector modulation are explained. Three level IGBT inverters are now successfully applied in drives for modern low floor trams. The advantageous performance of these inverters will be illustrated.
PROPERTIES OF GENERATORS OF PSEUDO-RANDOM SEQUENCES CONSTRUCTED USING FUZZY LOGIC AND TWO-DIMENSIONAL CHAOTIC SYSTEMS

Context. The problem of generating pseudo-random sequences of bits using the rules of fuzzy logic and two-dimensional chaotic systems is considered. Objective. Pseudo-random sequences generators built using two-dimensional chaotic systems and fuzzy logic. The purpose of the work is to develop and implement pseudo-random bit sequences generators based on the rules of fuzzy logic and two-dimensional chaotic systems and to evaluate the statistical characteristics of the generated sequences using statistical tests of National Institute of Standards and Technology. Method. A method for generating pseudo-random bit sequences is proposed, which allows form bit sequences with characteristics that meet the requirements of secure communication systems and cryptographic protection of information based on the rules of fuzzy logic and two-dimensional chaotic systems. In the process of studying the operation of generators, histograms of the distribution of output values were constructed, which allows to clearly determine whether the entire range of output values of the twodimensional system could be used to generate pseudo-random bit sequence or only part of it. A study of the statistical characteristics of the generated sequences using a set of statistical tests was also performed. Results. Bit sequences formed using fuzzy logic rules and two-dimensional chaotic systems can be used to transmit information in secure communication systems. Results. The proposed generators were implemented in software, histogram analysis and evaluation of compliance with the criteria for a set of statistical tests of National Institute of Standards and Technology. Conclusions. The experiments confirmed the ability of the proposed generators to generate bit sequences with good statistical characteristics, which allows them to be recommended for use in practice in solving problems of cryptographic protection of information and secure transmission of information over open communication channels. Prospects for further research may be to create cryptographic methods of information protection based on the proposed pseudo-random bit sequences generators, the implementation of secure communication systems.
A computational optimization research on ant colony optimization for the traveling salesman problem

The traveling salesman problem (TSP) is one of typical combinatorial optimization problems. Ant colony optimization (ACO) is an effective method to solve the traveling salesman problem, but there are some non-negligible shortcomings hidden in the original algorithm. The primary objective of this research is to optimize the ACO to produce quality work throughout solving TSP. To this end, the hybrid SOS-MMAS algorithm is proposed. Concretely, apply the advanced Max-Min Ant System (MMAS) as the basic algorithm to raise task scheduling efficiency, meanwhile introduce symbiotic organisms search (SOS) into the MMAS to optimize the key parameters. Experiments were carried out on typical TSP instances of different scales, and the SOS-ACO and ACO algorithms were compared with SOS-MMAS, which proved the excellent performance of SOS-MMAS in solving TSP. Rationality of the algorithm design and high performance has been illuminated by experimentation. In addition, the model also could serve to suggest further research of TSP or other related areas.
Determination of Volatility Parameters of Secondary Organic Aerosol Components via Thermal Analysis

To date, there are limited data on the thermal properties of secondary organic aerosol (SOA) components. In this study, we employed an experimental method to evaluate the physical properties of some atmospherically relevant compounds. We estimated the thermodynamic properties of SOA components, in particularly some carboxylic acids. The molar heat capacity, melting point and enthalpy, and vaporization enthalpy of the samples were determined via differential scanning calorimetry and thermogravimetric analysis, and their vaporization enthalpy (ΔHvap) was estimated using Clausius–Clapeyron and Langmuir equations based on their thermogravimetric profiles. The thermodynamic properties of benzoic acid as a reference compound agree well with the reported values. The obtained specific heat capacities of benzoic acid, phthalic acid, pinic acid, ketopinic acid, cis-pinonic acid, terpenylic acid and diaterpenylic acid acetate (DTAA) are 118.1, 169.4, 189.9, 223.9, 246.1, 223.2, and 524.1 J mol−1 K−1, respectively. The ΔHvap of benzoic acid, phthalic acid, ketopinic acid, DTAA, and 3-methylbutane-1,2,3-tricarboxylic acid (3-MBTCA) are 93.2 ± 0.4, 131.6, 113.8, and 124.4 kJ mol−1, respectively. The melting and vaporization enthalpies of the SOA components range from 7.3 to 29.7 kJ mol−1.
Can further subdivision of the Raymond-Roy classification of intracranial aneurysms be useful in predicting recurrence and need for future retreatment following endovascular coiling?

Background: The Raymond-Roy classification has been the standard for neck recurrences following endovascular coiling with three grades. Several modified classification systems with subdivisions have been reported in literature but it is unclear whether this adds value in predicting recurrence or retreatment. Our aim is to assess if these subdivisions aid in predicting recurrence and need for retreatment. Methods: A retrospective review of all patients undergoing endovascular coiling between 2013 and 2014. Patients requiring stent assistance or other embolization devices were excluded from the study. The neck residue was graded at time of coiling on the cerebral angiogram and subsequent 6, 24, and 60 months MRA. Correlation between grade at coiling and follow-up with need for subsequent retreatment was assessed. Results: Overall, 17/200 (8.5%) cases required retreatment within 5 years of initial coiling. 4/130 (3.1%) required retreatment within 5 years with initial Grade 0 at coiling, 6/24 cases (25%) of those Grade 2a, 4/20 cases (20%) Grade 2b, 3/8 (38%) Grade 3, and none of those with Grade 1. Large aneurysms ≥11 mm had an increased risk of aneurysm recurrence and retreatment. About 9.7% of ruptured aneurysms required retreatment versus 4.4% for unruptured. About 55% of carotid ophthalmic aneurysms were retreated. Conclusion: Although the modified classification system was significantly predictive of progressive recurrence and need for retreatment, no significant difference between the subdivisions of Grade 2 was observed. Similar predictive value was seen when using the Raymond-Roy classification compared to the new modified, limiting the usefulness of the new system in clinical practice.
Determination of diazepam in human plasma by developed and validated a high-performance liquid chromatographic ultraviolet method

Background and Aims: Diazepam is accepted as a safer drug to medicate in many serious cases, acting as an anticonvulsant, an anxiolytic and a treatment for many types of poisoning. Monitoring it is important in achieving successful treatment and reducing the risk of toxic effects. In this study, it is aimed to develop and validate a sensitive, repeatable, and reliable method based on high-performance liquid chromatographic analysis for the determination in human plasma. Methods: Separation was carried out using a reverse-phase C18 column (4.0 mm x 150 mm, 3 μm) at 30 °C. The solution was prepared with a 10 mM phosphate buffer and acetonitrile (1:1, v/v) was employed as a mobile phase at the isocratic flow with 0.5 mL/min rate. Quantification was applied at 230 nm. A solid-phase extraction method was established and optimized, which was then used in the preparation of the plasma (0.5 mL) samples to the analysis. Results: The method was found to be linear (r 2 = 0.9805) between 100 and 1200 ng/mL. The analysis run was ≤12 min. Intraday and inter-day accuracy were found between -5.78 and 5.93 and precision was ≤1.82%. The limit of detection and quan- tification were calculated as 20.42 and 61.86 ng/mL, respectively. Recovery was found between the range of 95.12% and 106.83%. The method was determined to be robust according to changes in UV, mobile phase organic solvent content, mobile phase pH, column temperature, and operator. Conclusion: This simple, sensitive and reliable method is suggested for accredited-reference laboratories working on the therapeutic drug monitorization and/or overdose-toxicological quantified analysis of diazepam in human plasma. and inter-day precision, accuracy and recovery values. These results were obtained from individual samples (n=3) prepared as quality control samples in real plasma.
A Robot Pose Estimation Optimized Visual SLAM Algorithm Based on CO-HDC Instance Segmentation Network for Dynamic Scenes

In order to improve the accuracy of visual SLAM algorithms in a dynamic scene, instance segmentation is widely used to eliminate dynamic feature points. However, the existing segmentation technology has low accuracy, especially for the contour of the object, and the amount of calculation of instance segmentation is large, limiting the speed of visual SLAM based on instance segmentation. Therefore, this paper proposes a contour optimization hybrid dilated convolutional neural network (CO-HDC) algorithm, which can perform a lightweight calculation on the basis of improving the accuracy of contour segmentation. Firstly, a hybrid dilated convolutional neural network (HDC) is used to increase the receptive field, which is defined as the size of the region in the input that produces the feature. Secondly, the contour quality evaluation (CQE) algorithm is proposed to enhance the contour, retaining the highest quality contour and solving the problem of distinguishing dynamic feature points from static feature points at the contour. Finally, in order to match the mapping speed of visual SLAM, the Beetle Antennae Search Douglas–Peucker (BAS-DP) algorithm is proposed to lighten the contour extraction. The experimental results have demonstrated that the proposed visual SLAM based on the CO-HDC algorithm performs well in the field of pose estimation and map construction on the TUM dataset. Compared with ORB-SLAM2, the Root Mean Squared Error (Rmse) of the proposed method in absolute trajectory error is about 30 times smaller and is only 0.02 m.
A car wheel energy harvesting system regarded as a robotic kinematic chain system

The aim of this article is the mathematical modeling of the car wheel with an energy harvester. The car wheel will be represented as a 3-DoF robotic kinematic chain. The Matlab program has been used to simulate the movement of the car wheel and the movement of the electromagnetic energy harvester located on the tire of the wheel. Simulation of the movement of the energy harvesting element allows us to compute the energy harvested in such a system.
Enabling Graduate School Decision-Making Through User-Centered Redesign of Program Website

When faced with difficult budget restrictions, many university departments attempt to increase enrollment to offset costs. To appeal to high quality students who may be interested in a program, it is critical for a university department to provide information online in an easily accessible, aesthetically pleasing format that matches potential students’ goals and information needs. Our research team was tasked with helping [redacted] university’s Computer Graphics Technology (CGT) Master of Science (MS) program to improve their existing website. Through user-centered design and goal-directed design methodologies, we were able to evaluate the existing website for design flaws, gather user research to inform our conceptual redesign, and evaluate our redesign for usability and compatibility with users’ mental models. This paper outlines our process and concludes with design implications that other university departments can use to improve their own websites.
Multi-view Attention Mechanism Learning for POI Recommendation

POI(point of interest) recommendation is a very necessary research field in both academic and commerce, however, predicting users’ potential points of interest is always faced with the problems of data sparsity and context semantics. Some studies have shown that graph embedding technology alleviates the problem of data sparsity to a certain extent. However, neither graph embedding techniques nor unsupervised learning models can adaptively learn the different effects of multiple relations between users and POIs, respectively. In view of this, we leverage the contextual information of users and POIs to build the multi-view affinity graphs(e.g. User-User, POI-POI and User-POI), and learn the latent representations of users and POIs based on the Graph Embedding technology and Attention mechanism, namely the GEA model. In particular, we first construct multi-view affinity graphs by using user’s social relationship, geographical distance and check-in behaviour, and embed them into a low dimensional shared space to learn the latent representation of users and POIs. Afterwards, in order to take advantage of the different effects of multiple relationships in the final recommendation task, we exploit the attention mechanism to obtain the fused latent representation and make recommendation according users’ potential preferences. Finally, we design a multi-task objective function for joint optimization to obtain more accurate recommendation results. Extensive experiments on Gowalla have verified the effectiveness of our model.
Correction of Hypercortisolemia with an Improved Cognitive Function and Muscle Mass after Transsphenoidal Surgery in an Older Patient with Cushing's Disease

Cushing's disease causes numerous metabolic disorders, cognitive decline, and sarcopenia, leading to deterioration of the general health in older individuals. Cushing's disease can be treated with transsphenoidal surgery, but thus far, surgery has often been avoided in older patients. We herein report an older woman with Cushing's disease whose cognitive impairment and sarcopenia improved after transsphenoidal surgery. Although cognitive impairment and sarcopenia in most older patients show resistance to treatment, our case indicates that normalization of the cortisol level by transsphenoidal surgery can be effective in improving the cognitive impairment and muscle mass loss caused by Cushing's disease.
Surgical Strikes on Host Defenses: Role of the Viral Protease Activity in Innate Immune Antagonism

As a frontline defense mechanism against viral infections, the innate immune system is the primary target of viral antagonism. A number of virulence factors encoded by viruses play roles in circumventing host defenses and augmenting viral replication. Among these factors are viral proteases, which are primarily responsible for maturation of viral proteins, but in addition cause proteolytic cleavage of cellular proteins involved in innate immune signaling. The study of these viral protease-mediated host cleavages has illuminated the intricacies of innate immune networks and yielded valuable insights into viral pathogenesis. In this review, we will provide a brief summary of how proteases of positive-strand RNA viruses, mainly from the Picornaviridae, Flaviviridae and Coronaviridae families, proteolytically process innate immune components and blunt their functions.
IMPROVING POWER LINE UTILIZATION AND PERFORMANCE WITH FACTS DEVICES IN DISTURBED POWER SYSTEMS

This Paper describes the theory and simulation by mat lab of flexible Alternative Current Transmission Systems (FACTS) devices used in the disturbed power systems. One of these devices, Unified Power Flow Controller (UPFC) will be chosen for a specific application, detailed in this Project. Simulation investigate the effect of UPFC on the voltage of the related bus, it also considers the effect on the amount of active and reactive power flowing through the transmission system. Finally simulation results have been presented to indicate the improvement in the performance of the UPFC to control voltage in disturbed power systems.
Timing and Duration of Student Homelessness and Educational Outcomes in Los Angeles

As student homelessness grows, little is known about how the timing and duration of homeless experiences shape K–12 outcomes. Using Los Angeles Unified School District administrative data, the authors examine whether these temporal dimensions of homelessness predict students’ achievement and attendance. The authors find that homeless students scored lower on math tests and missed more school days than students who were never homeless. These associations are largest when students experience homelessness in the year the outcomes are measured. Experiencing homelessness in only 1 year and in 2 or more years both negatively predict outcomes, but associations are larger for students experiencing homelessness in only 1 year.
Traffic classification algorithm using CNN and multi-head attention mechanism for representation learning

With the development of the times, the demand for privacy and security by people, enterprises and government units has become stronger and stronger, driven by this, encrypted traffic has shown a blowout growth, and the security of traffic has become an issue that cannot be ignored. To solve the traffic classification problem, this paper proposes a new traffic classification algorithm based on convolutional neural network and multi-head attention mechanism. In addition, this paper uses a feature engineering method based on representation learning and proposes a discard threshold to improve the quality of data sets obtained by feature engineering. The experimental results show that the algorithm model and the optimized feature engineering method proposed in this paper have good performance on the traffic classification task.