Miracle-dz/UniFAR-FTUs huggingface dataset:
Acoustic Characterization of Transmitted and Received Acoustic Properties of Air-Coupled Ultrasonic Transducers Based on Matching Layer of Organosilicon Hollow Glass Microsphere

An air-coupled transducer was developed in this study, utilizing hollow glass microsphere-organosilicon composites as an acoustically matching layer, which demonstrated outstanding acoustic performance. Firstly, a comparison and analysis of the properties and advantages of different substrates was carried out to determine the potential application value of organosilicon substrates. Immediately after, the effect of hollow glass microspheres with different particle sizes and mass fractions on the acoustic properties of the matching layer was analyzed. It also evaluated the mechanical properties of the matching layer before and after optimization. The findings indicate that the optimized composite material attained a characteristic acoustic impedance of 1.04 MRayl and an acoustic attenuation of 0.43 dB/mm, displaying exceptional acoustic performance. After encapsulating the ultrasonic transducer using a 3D-printed shell, we analyzed and compared its emission and reception characteristics to the commercial transducer and found that its emission acoustic pressure amplitude and reception voltage amplitude were 34% and 26% higher, respectively. Finally, the transducer was installed onto a homemade ultrasonic flow meter for practical application verification, resulting in an accuracy rate of 97.4%.
Identification of Cellular Measurements: A Neural Network Approach

The efficient utilization of the wireless spectrum is essential to fulfill the rising demand of scarce bandwidth resources. Identifying the cellular signal types occupying the spectrum allows for usage optimization. Neural networks (NNs) are a promising approach for the signals’ identification problems. This article proposes a hybrid convolutional and feedforward NN (HCFNN) that classifies the cellular signals from the power spectral density (PSD) of real measurements into their corresponding types: global system for mobile communications (GSM), universal mobile telecommunications service (UMTS), and long-term evolution (LTE). The measured dataset is collected based on two acquisition modes: multiple-band (MB) and in-band (IB) PSD acquisition modes. In the MB model, the data are collected, trained, and tested from various frequency bands, while in the IB model, the data are collected, trained, and tested from a single frequency band. The accuracy and the precision–recall (PR) metrics are used to evaluate the performance of the proposed HCFNN model. Moreover, the complexity analysis of the model is derived in terms of the number of real additions, real multiplications, and parameters. The extensive assessments of the over-the-air measurements show that the proposed HCFNN model accurately identifies the cellular signal types in all studied scenarios.
Enhancing Convolutional Neural Network Performance through Optimized Sigmoid Activation Function Modeling

: Artificial intelligence (AI) has recently attracted significant attention due to its involvement in phenomena like deep fakes, AI-generated artwork, and other prominent projects and collaborations. It is being used across various domains such as security and deep learning, necessitating high-performance hardware specifications centered around graphics processing units. The research methodology employed in this paper can be outlined as follows: the pursuit of optimal parameter values by manipulating the coefficients and constants within the function employed by the convolutional neural network, and fine-tuning the parameter values themselves. The outcome of this endeavor, involving the optimization of coefficients, constants, and parameter values in the convolutional neural network's functions, yields significant insights. For the original sigmoid formula, optimal parameter values are identified: a coefficient of 9 for the first "x," a coefficient of 7 for the second "x," and a constant term of 0.0001. Shifting attention to the modified Sigmoid function, the pursuit of optimal conditions for high accuracy and fast calculation time leads to the determination of specific values. Notably, the coefficient of the first "x" ("β") within the function is established as 30, while the coeff icient of the second "x" ("δ") is set at 70. Additionally, the square value of 5 is identified as optimal, further underscoring the importance of achieving a balance between accuracy and computational efficiency.
Disturbance Observer-based Pointing Control of Leighton Chajnantor Telescope

Leighton Chajnantor Telescope (LCT), i.e., the former Caltech Submillimeter Observatory telescope, will be refurbished at the new site in Chajnantor Plateau, Chile in 2023. The environment of LCT will change significantly after its relocation, and the telescope will be exposed to large wind disturbances directly because its enclosure will be completely open during observation. The wind disturbance is expected to be a challenge for LCT’s pointing control since the existing control method cannot reject this disturbance very well. Therefore, it is very necessary to develop a new pointing control method with good capability of disturbance rejection. In this research, a disturbance observer—based composite position controller (DOB-CPC) is designed, in which an H∞ feedback controller is employed to compress the disturbance, and a feedforward linear quadratic regulator is employed to compensate the disturbance precisely based on the estimated disturbance signal. Moreover, a controller switching policy is adopted, which applies the proportional controller to the transient process to achieve a quick response and applies the DOB-CPC to the steady state to achieve a small position error. Numerical experiments are conducted to verify the good performance of the proposed pointing controller (i.e., DOB-CPC) for rejecting the disturbance acting on LCT.
Epidemiologic trends of and factors associated with overall survival in patients with neuroendocrine tumors over the last two decades in the USA

Background Updated epidemiological data of neuroendocrine tumors are currently lacking. Thus, we performed epidemiological and survival analyses on a large cohort of patients with neuroendocrine tumors and developed a new nomogram to predict survival. Methods This population-based study examined 112,256 patients with neuroendocrine tumors between 2000 and 2018 using data from the Surveillance, Epidemiology, and End Results program. Results The age-adjusted incidence per 100,000 persons of neuroendocrine tumors increased from 4.90 in 2000 to 8.19 in 2018 (annual percentage change, 3.40; 95% confidence interval, 3.13–3.67), with the most significant increases in grade 1, localized stage, and appendix neuroendocrine tumors. The age-adjusted mortality rate increased 3.1-fold from 2000 to 2018 (annual percentage change, 4.14; 95% confidence interval, 3.14–5.15). The 1-, 5-, and 10-year relative survival rates for all neuroendocrine tumors were 80.5%, 68.4%, and 63.5%, respectively. Multivariate analyses showed that male sex; older age; Black, American Indian, and Alaska Native populations; earlier year of diagnosis; lung neuroendocrine tumors; higher grades; and later stage were associated with a worse prognosis and that disease stage and grade were the most important risk factors for prognosis. Furthermore, we established a nomogram to predict the 3-, 5-, and 10-year survival rates, and its discrimination ability was better than that of the TNM classification. Conclusions The incidence, prevalence, and mortality rate of neuroendocrine tumors continued to increase over the last two decades. Additionally, the nomogram could accurately quantify the risk of death in patients with neuroendocrine tumors and had good clinical practicability.
Traveling Salesman Problem: The Efficiency of Simulated Annealing Applied to a Real Case Study

This paper deals with a traveling salesman problem that is performed daily by a Portuguese bakery company. The bakery delivers bread to multiple customers using only one vehicle and driver, leading to high costs and time consumption. The objective is to minimize total travel distance and optimize the distribution process to reduce costs. In this case, we have a typical Traveling Salesman Problem and in order to solve this problem, several solutions were first computed and compared, and then, these were used as initial solutions to a Simulated Annealing (SA) approach. The performance of the SA was tested for the real problem, with the actual company data and, an analysis of the SA behavior when started with different solutions was performed. The results obtained allowed the company to reduce its current route by more than 23%.
Vancomycin-Loaded 3D-Printed Polylactic Acid–Hydroxyapatite Scaffolds for Bone Tissue Engineering

The regeneration of bone remains one of the main challenges in the biomedical field, with the need to provide more personalized and multifunctional solutions. The other persistent challenge is related to the local prevention of infections after implantation surgery. To fulfill the first one and provide customized scaffolds with complex geometries, 3D printing is being investigated, with polylactic acid (PLA) as the biomaterial mostly used, given its thermoplastic properties. The 3D printing of PLA in combination with hydroxyapatite (HA) is also under research, to mimic the native mechanical and biological properties, providing more functional scaffolds. Finally, to fulfill the second one, antibacterial drugs locally incorporated into biodegradable scaffolds are also under investigation. This work aims to develop vancomycin-loaded 3D-printed PLA–HA scaffolds offering a dual functionality: local prevention of infections and personalized biodegradable scaffolds with osseointegrative properties. For this, the antibacterial drug vancomycin was incorporated into 3D-printed PLA–HA scaffolds using three loading methodologies: (1) dip coating, (2) drop coating, and (3) direct incorporation in the 3D printing with PLA and HA. A systematic characterization was performed, including release kinetics, Staphylococcus aureus antibacterial/antibiofilm activities and cytocompatibility. The results demonstrated the feasibility of the vancomycin-loaded 3D-printed PLA–HA scaffolds as drug-releasing vehicles with significant antibacterial effects for the three methodologies. In relation to the drug release kinetics, the (1) dip- and (2) drop-coating methodologies achieved burst release (first 60 min) of around 80–90% of the loaded vancomycin, followed by a slower release of the remaining drug for up to 48 h, while the (3) 3D printing presented an extended release beyond 7 days as the polymer degraded. The cytocompatibility of the vancomycin-loaded scaffolds was also confirmed.
Cost-effectiveness of the Flapless Insertion of Zygomatic Implants Using Dynamic Navigation - A Retrospective Study

Abstract Introduction: Zygomatic implants are an effective solution for rehabilitation of edentulous atrophic maxillae. However, the conventional technique of zygomatic implant placement is invasive, requires a longer healing period and is economically cumbersome. Therefore, the flapless technique of insertion of zygomatic implants using dynamic navigation system has been introduced. This study aims to compare the cost-effectiveness of flapless insertion of zygomatic implants using dynamic navigation to the conventional flap technique. Materials and Methods: The study participants were divided into two groups: Group A (n = 20) included patients treated by flapless insertion of zygomatic implants using dynamic navigation and Group B (n = 20) included patients treated with zygomatic implants using the flap technique. An analysis of the effectiveness of the implants was done using the concept of quality-adjusted prosthesis years, and an analysis of the costs was done by evaluating the treatment costs at each step. The data were collected, and analysis was done using IBM SPSS software. The Kruskal–Wallis rank-sum test was employed to analyse variations in costs and effects between the two groups. Results: The study showed that the distribution of costs varies across both the categories of the procedure. Group B shows lesser cost-effectiveness as compared to Group A. Conclusion: The technique of flapless insertion of zygomatic implants is cost-effective. However, further studies considering factors such as time and cost of productivity evaluating the cost-effectiveness should be conducted.
Categorization of Website Usability Factors

The usability of a website refers to the ease of the system use and the ability of the users to complete their tasks efficiently and without error. Websites should be user-friendly while designed to be more multi-functional in conjunction with the increasing user necessities. Herein, understanding website usability-related factors becomes important in designing such usable systems. In the current study, we aim to provide a systematic approach to categorizing website usability factors by referencing the usability problems encountered through a cognitive walkthrough approach. In this study, first, the usability problems of a specific website were identified by three experts and the problems were rated according to the severity levels, from cosmetic problems to catastrophic problems. Then, usability problems were mapped with the website usability factors. In the last step, the categorization of website usability factors according to the severity levels was conducted with a cross-tabulation approach, correspondence and cluster analyses. As a result, Individualization and User Adaptation(IND), Privacy and Business Policies(PRV), Link Design(LNK), Search(SRC), and Help(HLP) were grouped with the severity level of catastrophic problems. These factors are the most significant factors that website developers should think about first in the design and evaluation of websites.
Outlier-based Anomaly Detection in Firewall Logs

Nowadays, most corporations or government agencies adopt various cybersecurity detection and protection systems to safeguard their assets. Currently available cybersecurity products include firewalls, intrusion detection systems (IDS), intrusion prevention systems (IPS), web application firewalls (WAF), anti-virus software, distributed denial-of-service (DDoS) protection systems, and advanced persistent threat (APT) protection systems, among many others. This article proposes the use of unsupervised learning methods to detect anomalous behavior in network environments. In order to find critical behavioral features, we attempted to extract and analyze different fields, and ultimately discovering two key behavioral features: (1) the number of daily connections from a source IP address to different external hosts, and (2) the total number of daily connections from a source IP address to a destination IP address. This method simplifies the complexity of various cybersecurity devices and introduces our designed long-cycle analysis method. It also solves the problem of not being able to define baseline behavior due to the high cost involved. Through unsupervised learning and feature compression, our proposed methodology allows monitoring targets to self-compare and self-verify their own behavior. Our proposed methodology can figure out anomalous behavior in over 170 customers, billions of source IP addresses, and trillions of network connections.
Evaluation of Safety and Efficacy of Preoperative Coronal MRI-Guided Minimally Invasive Surgery for Cervical Spondylotic Radiculopathy

Background Key-hole surgery is a minimally invasive technique that has shown promise in various surgical procedures. This study aimed to assess the clinical effectiveness of preoperative coronal MRI-assisted key-hole surgery for the treatment of patients with cervical spondylotic radiculopathy (CSR). Material/Methods A total of 30 patients diagnosed with CSR and undergoing key-hole surgery with CMRI assistance were included in the study. Various parameters, including surgical segments, incision length, disease duration, operative time, intraoperative fluoroscopy times, intraoperative blood loss, complications, and length of hospitalization, were recorded. Precise measurements of Cobb angles and intervertebral space height were taken before and after the surgical procedure. Surgical outcomes were evaluated using modified Macnab criteria, visual analogue scale (VAS), Japanese Orthopaedic Association Scores (JOA), and neck disability index (NDI). Results The average duration of disease was 6.47±3.29 months, with an average incision length of 1.94±0.15 cm and operative time of 57.83±4.34 minutes. The average intraoperative blood loss was 33.70±9.28 ml, with an average of 3.50±0.73 intraoperative fluoroscopies. The average duration of hospitalization was 4.10±1.27 days. Preoperative and postoperative measurements showed no statistically significant difference in C2–C7 Cobb angles and intervertebral space height. However, there were significant improvements in postoperative VAS, NDI, and JOA scores compared to preoperative scores. The surgical effectiveness rate was 100%, with a high rate of good and excellent outcomes. Conclusions The findings of this study suggest that preoperative CMRI-assisted key-hole surgery for single-segment CSR is a safe and effective treatment option with low complication rates. The clinical benefits include high security and good outcomes. Further research and larger studies are warranted to validate these findings.
Atmospheric Moisture Transport to the Arctic: Assessment of Reanalyses and Analysis of Transport Components

AbstractThe atmospheric water cycle of the Arctic is evaluated via seven global reanalyses and in radiosonde observations covering the 1979–2013 period. In the regional moisture budget, evaporation and precipitation are the least consistent terms among different datasets. Despite the assimilation of radiosoundings, the reanalyses present a tendency to overestimate the moisture transport. Aside from this overestimation, the reanalyses exhibit a remarkable agreement with the radiosondes in terms of spatial and temporal patterns. The northern North Atlantic, subpolar North Pacific, and Labrador Sea stand out as the main gateways for moisture to the Arctic in all reanalyses. Because these regions correspond to the end of the storm tracks, the link between moisture transports and extratropical cyclones is further investigated by decomposing the moisture fluxes in the mean flow and transient eddy parts. In all reanalyses, the former term tends to cancel out when averaged over a latitude circle, leaving the latt.
Enhancement Method for Fog-degraded Images based on Multi-scale Retinex and Wavelet Transform

To improve the image defogging effect, a foggy image enhancement method based on multi-scale retinex(MSR) and wavelet transform is proposed. First, the H, I and S component is obtained by converting foggy image to HIS space. Secondly, the logarithmic transformation is used to improve areas with low saturation for better visual effect. Then, a new I component is acquired by combining MSR and wavelet transform to process I component. Finally, the fogless image is obtained by HIS inverse transformation. The experimental results indicate that that the algorithm proposed achieves good defogging effects both subjectively and objectively.
A Two State Adaptive Ant Colony Algorithm Framework for Solving Multi-objective Optimization Problems

In order to improve the performance of ant colony algorithm in solving multi-objective optimization problems and enhance the universality of the algorithm, this paper introduces cloud model theory and proposes an adaptive ant colony algorithm framework between "development" and "exploration". In the algorithm, the concept of cloud model dominant solution is introduced, and pheromone update mechanism, pheromone status evaluation mechanism and the determination mechanism of cloud model dominant solution are constructed. At the same time, a multi-objective adaptive mechanism based on cloud model has been constructed, enabling the algorithm to maintain a balance between exploring unknown feasible solutions and developing known Pareto optimal solutions, thereby improving the search efficiency of the algorithm. In the simulation comparative experiment of solving multi-objective traveling salesman problem, the experimental results show that the framework proposed in this paper is feasible and effective.
Investigating Correlations and the Validation of SMAP-Sentinel L2 and In Situ Soil Moisture in Thailand

Soil moisture plays a crucial role in various hydrological processes and energy partitioning of the global surface. The Soil Moisture Active Passive-Sentinel (SMAP-Sentinel) remote-sensing technology has demonstrated great potential for monitoring soil moisture with a maximum spatial resolution of 1 km. This capability can be applied to improve the weather forecast accuracy, enhance water management for agriculture, and managing climate-related disasters. Despite the techniques being increasingly used worldwide, their accuracy still requires field validation in specific regions like Thailand. In this paper, we report on the extensive in situ monitoring of soil moisture (from surface up to 1 m depth) at 10 stations across Thailand, spanning the years 2021 to 2023. The aim was to validate the SMAP surface-soil moisture (SSM) Level 2 product over a period of two years. Using a one-month averaging approach, the study revealed linear relationships between the two measurement types, with the coefficient of determination (R-squared) varying from 0.13 to 0.58. Notably, areas with more uniform land use and topography such as croplands tended to have a better coefficient of determination. We also conducted detailed soil core characterization, including soil–water retention curves, permeability, porosity, and other physical properties. The basic soil properties were used for estimating the correlation constants between SMAP and in situ soil moistures using multiple linear regression. The results produced R-squared values between 0.933 and 0.847. An upscaling approach to SMAP was proposed that showed promising results when a 3-month average of all measurements in cropland was used together. The finding also suggests that the SMAP-Sentinel remote-sensing technology exhibits significant potential for soil-moisture monitoring in certain applications. Further validation efforts and research, particularly in terms of root-zone depths and area-based assessments, especially in the agricultural sector, can greatly improve the technology’s effectiveness and usefulness in the region.
A Low Loss, 6 GHz Large-Signal Bandwidth Analog Pre-Distortion Linearizer for K-Band High Power Amplifiers

This work presents the design, characterization, and validation of an Analog Pre-Distortion (APD) circuit. This circuit is based on a dual-branch configuration with a Schottky diode as a non-linear element and delay line. The Schottky diode is first experimentally characterized and a large signal model is extracted. The manufactured APD circuit provides a 6 GHz bandwidth around a central frequency of 18 GHz. At large-signal, this APD circuit shows to be able to correct up to 3 dB of HPA compression and up to 9° of HPA phase rotation within a 6 GHz large-signal bandwidth, with a low insertion loss of only 7 dB. The complete APD + HPA chain is verified with modulated signals at 19 GHz and results in an improvement of the P1dB point by 2.6 dB and by 6° in the phase distortion. Finally, the APD is demonstrated with a 750 MHz modulated signal and results in the improvement of the left Adjacent Channel Leakage Ratio (ACLR) by 4.5 dB, of the central Noise-Power Ratio (NPR) by 8.2 dB, and then of the right ACLR by 9.8 dB while maintaining the same maximum output power.