Miracle-dz/UniFAR-FTUs huggingface dataset:
Initial Intraoperative Experience with Robotic-Assisted Pedicle Screw Placement with Cirq® Robotic Alignment: An Evaluation of the First 70 Screws

Background: Robot-guided spine surgery is based on a preoperatively planned trajectory that is reproduced in the operating room by the robotic device. This study presents our initial experience with thoracolumbar pedicle screw placement using Brainlab’s Cirq® surgeon-controlled robotic arm (BrainLab, Munich, Germany). Methods: All patients who underwent robotic-assisted implantation of pedicle screws in the thoracolumbar spine were included in the study. Our workflow, consisting of preoperative imagining, screw planning, intraoperative imaging with automatic registration, fusion of the preoperative and intraoperative imaging with a review of the preplanned screw trajectories, robotic-assisted insertion of K-wires, followed by a fluoroscopy-assisted insertion of pedicle screws and control iCT scan, is described. Results: A total of 12 patients (5 male and 7 females, mean age 67.4 years) underwent 13 surgeries using the Cirq® Robotic Alignment Module for thoracolumbar pedicle screw implantation. Spondylodiscitis, metastases, osteoporotic fracture, and spinal canal stenosis were detected. A total of 70 screws were implanted. The mean time per screw was 08:27 ± 06:54 min. The mean time per screw for the first 7 surgeries (first 36 screws) was 16:03 ± 09:32 min and for the latter 6 surgeries (34 screws) the mean time per screw was 04:35 ± 02:11 min (p < 0.05). Mean entry point deviation was 1.9 ± 1.23 mm, mean deviation from the tip of the screw was 2.61 ± 1.6 mm and mean angular deviation was 3.5° ± 2°. For screw-placement accuracy we used the CT-based Gertzbein and Robbins System (GRS). Of the total screws, 65 screws were GRS A screws (92.85%), one screw was a GRS B screw, and two further screws were grade C. Two screws were D screws (2.85%) and underwent intraoperative revision. There were no perioperative deficits. Conclusion: Brainlab’s Cirq® Robotic Alignment surgeon-controlled robotic arm is a safe and beneficial method for accurate thoracolumbar pedicle screw placement with high accuracy.
Non-Alcoholic Fatty Liver Disease (NAFLD) and Bariatric/Metabolic Surgery as Its Treatment Option: A Review

The prevalence of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) has considerably increased over the last years. NAFLD is currently the most common cause of chronic liver disease in the developing world. The diagnosis of NAFLD/NASH is often incidental, as the early-stage of disease is frequently free of symptoms. Most patients recognized with NAFLD have severe obesity and other obesity-related disease such as type 2 diabetes mellitus (T2DM), insulin-resistance, dyslipidemia and hypertension. The only proven method for NAFLD improvement and resolution is weight loss. Bariatric surgery leads to significant and long-term weight loss as well as improvement of coexisting diseases. There is a lot of evidence suggesting that metabolic/bariatric surgery is an effective method of NAFLD treatment that leads to reduction in steatosis, hepatic inflammation and fibrosis. However, there is still a need to perform long-term studies in order to determine the role of bariatric surgery as a treatment option for NAFLD and NASH. This review discusses current evidence about epidemiology, pathogenesis and treatment options for NAFLD including bariatric/metabolic surgery and its effect on improvement and resolution of NAFLD.
Prescribed Burning in Spring or Autumn Did Not Affect the Soil Fungal Community in Mediterranean Pinus Nigra Natural Forests

In the context of global change, wildfires are not only a threat but are also increasing in their severity in forest ecosystems worldwide, affecting and modifying vegetation, wildlife, and fungal dynamics. Mediterranean eco-systems are frequently affected by fire and prescribed burning is being increasingly used as a tool to reduce the risk and severity of wildfires. Although some of the effects of prescribed burning have been studied, the best moment to perform a prescribed burn to reduce the impact of fire on fungal communities has not been fully investigated. In this study, we analysed the effect of prescribed burning in two different seasons (spring and autumn) on soil fungi associated with natural Pinus nigra forests. Four years after prescribed burning was applied, our analyses showed that the total fungal richness and the composition of fungal communities in spring-burned, autumn-burned, and unburned control plots did not differ significantly. However, analyses of specific phyla and functional trophic groups did reveal some significant differences between spring-or autumn-burned plots and unburned control plots. Valuable edible fungi, which were not affected by the prescribed burning, were also found in the study area. Thus, our results suggest that prescribed burning is not only an interesting tool that could be used to reduce the risk of wildfire but also is compatible with the conservation of fungal communities, and could even promote specific valuable edible species, generating complementary incomes for the rural population. Although further studies are needed, our analyses suggest that the season (spring or autumn) in which prescribed burning is performed does not affect fungal conservation and, therefore, does not need to be one of the factors taken into consideration when selecting the most appropriate time to perform a prescribed burning.
Assessing Agile Methods: Investigating Adequacy, Capability, and Effectiveness (An Objectives, Principles, Strategies Approach)

Agile methods provide an organization or a team with the flexibility to adopt a selected subset of principles and practices based on their culture, their values, and the types of systems that they develop. More specifically, every organization or team implements a customized agile method, tailored to better accommodate its needs. However, the extent to which a customized method supports the organizational objectives, i.e. the ‘goodness’ of that method, should be demonstrable. Existing agile assessment approaches focus on comparative analyses, or are limited in scope and application. In this research, we propose a systematic, comprehensive approach to assessing the ‘goodness’ of agile methods. We examine an agile method based on (1) its adequacy, (2) the capability of the organization to support the adopted principles and strategies specified by the method, and (3) the method’s effectiveness. We propose the Objectives, Principles and Strategies (OPS) Framework to guide our assessment process. The Framework identifies (a) objectives of the agile philosophy, (b) principles that support the objectives and (c) strategies that implement the principles. It also defines (d) linkages that relate objectives to principles, and principles to strategies, and finally, (e) indicators for assessing the extent to which an organization supports the implementation and effectiveness of those strategies. The propagation of indicator values along the linkages provides a multi-level assessment view of the agile method. In this dissertation, we present our assessment methodology, guiding Framework, validation approach, results and findings, and future directions.
Micro Electromechanical Filters for Signal Processing

Micro electromechanical filters based on coupled, latei al microresonators aie demonstrated This new class of MEMS has potential signal-pi messing applications for filteis which requii e narrow bandwidth (high Q ), good signal-to-noise ratio. and stable temperature and aging characteristics Both series and paallel filteis have been fabricated and tested using an off-chip modulation technique The frequency range of these filters 15 from approximately 5 kHz to on the order of I MHz. for poljsilicon miciostructuies with suspension beams having a 2 bni square cross section A series-coupled resonator pair designed for operation at atmospheric pressure, has a measured centei frequency of 18 7 kHz and a bandwidth of 1 2 kHz
Process evaluation protocol of a cluster randomised trial for a scalable solution for delivery of Diabetes Self-Management Education in Thailand (DSME-T)

Introduction Type 2 diabetes mellitus is a major global challenge, including for Thai policy-makers, as an estimated 4 million people in Thailand (population 68 million) have this condition. Premature death and disability due to diabetes are primarily due to complications which can be prevented by good risk factor control. Diabetes Self-Management Education (DSME) programmes provide patients with diabetes with the necessary knowledge and skills to effectively manage their disease. Currently, a trial is being conducted in Thailand to evaluate the effectiveness, defined as HbA1c<7 at 12 months after enrolment, of a culturally tailored DSME in Thailand. A process evaluation can provide further interpretation of the results from complex interventions as well as insight into the success of applying the programme into a broader context. Methods and analysis The aim of the process evaluation is to understand how and why the intervention was effective or ineffective and to identify contextually relevant strategies for future successful implementation. For the process evaluation, the design will be a mixed-method study collecting data from nurse providers, and village health volunteers (community health workers) as well as patients. This will be conducted using observations, interviews and focus groups from the three purposively selected groups at the beginning and end of trial. Quantitative data will be collected through surveys conducted at the beginning, during 6-month follow-up, and at the end of trial. The mixed-methods analysis will be triangulated to assess differences and similarities across the various data sources. The overall effectiveness of the intervention will be examined using multilevel analysis of repeated measures. Ethics and dissemination Study approved by the Chiang Mai University Research Ethics Committee (326/2018) and the London School of Hygiene & Tropical Medicine (16113/RR/12850). Results will be published in open access, peer-reviewed scientific journals. Trial registration number NCT03938233.
A Hybrid Modified Sine Cosine Algorithm Using Inverse Filtering and Clipping Methods for Low Autocorrelation Binary Sequences

: The essential purpose of radar is to detect a target of interest and provide information concerning the target’s location, motion, size, and other parameters. The knowledge about the pulse trains’ properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximum possible MF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to propose a new metaheuristic algorithm based on Hybrid Modified Sine Cosine Algorithm with Cuckoo Search Algorithm (HMSCACSA) using Inverse Filtering (IF) and clipping method to achieve better results. The proposed algorithms, LABS-IF and HMSCACSA-IF, achieved better results with two large MFs equal to 12.12 and 12.6678 for lengths 231 and 237, respectively, where the optimal solutions belong to the skew-symmetric sequences. The MF outperformed up to 24.335% and 2.708% against the state-of-the-art LABS heuristic algorithm, xLastovka, and Golay, respectively. These results indicated that the proposed algorithm’s simulation had quality solutions in terms of fast convergence curve with better optimal means, and standard deviation. the subsequent search for odd sequences will be continued with a larger length to get the difference increment with higher MF than the HMSCACSA-IF algorithm. The significant limitations of LABS are solved through IF and clipping methods to find some new, best-known skew-symmetrical solutions with MF and EL values. The results obtained have significantly improved the results compared to the recent state-of-the-art algorithms, where the MF and EL of the proposed algorithms are better than xLastovka, 1bCAN, and Shotgun Hill-Climbing with their largest binary sequences length up to 267, 1000 and 300, respectively. These proposed methods are uniquely postulated to improve the search of local optimal solutions systematically.
There’s a car coming? - Psychometric function for car pass-by in background noise based on simulated data

To detect an approaching car in background noise is an important aspect of traffic safety. Therefore it is essential to understand the determinants that makes people recognize an approaching car especially when the cars become very quiet at low speeds as it is the case for electrical cars for instance. Most studies on the detection of passenger cars in background noise are based on recorded signals. This requires that suitable recordings are available both for the background sound as well as the test sound (i.e. the sound of the approaching vehicle). Due to the limited control of such situations the degrees of freedom to be varied in such experiments is limited as well. In the presented study a different approach has been employed. The utilized sounds are based on an auralization method that allows for simulating vehicle sounds including both tyre/road noise and propulsion noise. Single car events can thus be superposed to background sound with full control of all relevant parameters. The used auralization method has in earlier studies been validated for giving good perceptual ratings compared to recorded sounds. The method allows for evaluating the psychometric functions for single parameters and hopefully give a deeper understanding of the perceptual space for a car in background noise. In the present study the reaction time is measured for the detection of a car (test vehicle) passing by in the presence of background noise from a road with high traffic flow. The distance between the the path of the test vehicle and the highly trafficked road is varied. All other parameters (i.e. car-type, road surface, speed, etc.) are kept constant. The study shows that there is a logarithmic relation between the response times and the distance between the the track of the test car and the road with high traffic volume. At the same time there is a linear relation between reaction time and signal to noise ratio (i.e. the equivalent sound pressure level in relation to the background level).
A computational model of human blood clottings: simulation, analysis, control, and validation

Complex biological systems pose many challenges to researchers, including, inter alia, choice of computational model, with its consequences for simulation and analysis; methods of manipulating the system exogenously (control); and model validation. I attempt to address these issues for human blood clotting. By treating the system as comprising interacting discrete and continuous aspects, i.e. as hybrid, the entire coagulation cascade may be simulated: Blood proteins, elemental ions, and other state elements are modeled either as real-valued concentrations or as binary variables (present/absent); interactions are rendered either as ODEs (per their chemical equations) or as discrete events. Techniques from nonlinear control theory are then used to devise drug therapies for diseased patients. Finally, the model is used to warp variations in the input parameters—rate constants and initial conditions—into an output space where pathologies and healthy clotting are cleanly separated by a semi-supervised clustering analysis. This serves to validate the model as well as to summarize efficiently the predicted clinical consequences of individual variations.
Oxidized low-density lipoprotein receptor 1: a novel potential therapeutic target for intracerebral hemorrhage

Oxidized low-density lipoprotein receptor 1 (OLR1) is upregulated in neurons and participates in hypertension-induced neuronal apoptosis. OLR1 deletion exerts protective effects on cerebral damage induced by hypertensive-induced stroke. Therefore, OLR1 is likely involved in the progress of intracerebral hemorrhage. In this study, we examined the potential role of OLR1 in intracerebral hemorrhage using a rat model. OLR1 small interfering RNA (10 μL; 50 pmol/μL) was injected into the right basal ganglia to knock down OLR1. Twenty-four hours later, 0.5 U collagenase type VII was injected to induce intracerebral hemorrhage. We found that knockdown of OLR1 attenuated neurological behavior impairment in rats with intracerebral hemorrhage and reduced hematoma, neuron loss, inflammatory reaction, and oxidative stress in rat brain tissue. We also found that silencing of OLR1 suppressed ferroptosis induced by intracerebral hemorrhage and the p38 signaling pathway. Therefore, silencing OLR1 exhibits protective effects against secondary injury of intracerebral hemorrhage. These findings suggest that OLR1 may be a novel potential therapeutic target for intracerebral hemorrhage.
AdaRW training optimization algorithm for deep learning model of marine target detection based on SAR

ABSTRACT Deep learning adjusts parameters to optimize the model through model training. Training algorithm is the key to model optimization and implementation. Therefore, the improvement of model training algorithm is of great significance to deep learning. Based on the original gradient algorithm, the paper proposes a new gradient descent algorithm AdaGrad Restricted by Windows (AdaRW) for Deep learning model training optimization. Aiming at the defects of AdaGrad algorithm, the new algorithm uses the subset of window to limit historical accumulation, so as to slow down the attenuation of learning rate, and improve the speed of model training. The paper constructs OceanTDA9, a Deep learning model of marine target detection for Synthetic Aperture Radar (SAR) data, and adopts the proposed AdaRW algorithm to train the model based on SAR data with a resolution of 10 m in the Bohai Sea. Experiment shows that the accuracy and loss of the algorithm are better than those of AdaGrad and Stochastic Gradient Descent (SGD) algorithms, and the standard deviation is better than that of Adam algorithm.
Transformation of Selected Fusarium Toxins and Their Masked Forms during Malting of Various Cultivars of Wheat

This study investigated the impact of malting of six wheat cultivars inoculated with Fusarium culmorum on the dynamics of content changes of selected Fusarium toxins. The grains of all the tested cultivars showed a high content of deoxynivalenol (DON), zearalenone (ZEN), and their derivatives, whereas nivalenol (NIV) and its glucoside were found only in the Legenda cultivar. Our experiments confirmed that the malting process of wheat grain enables the secondary growth of Fusarium, and mycotoxin biosynthesis. The levels of toxins in malt were few-fold higher than those in grain; an especially high increase was noted in the case of ZEN and its sulfate as the optimal temperature and pH conditions for the biosynthesis of these toxins by the pathogen are similar to those used in the grain malting process. This is the first paper reporting that during the malting process, biosynthesis of ZEN sulfate occurs, instead of glycosylation, which is a typical modification of mycotoxins by plant detoxication enzymes.
The Influence of Magnetron Sputtering Process Temperature on ZnO Thin-Film Properties

The important research direction in surface engineering and photovoltaics is the development of new materials that can replace the previously used expensive films. A prospective compound is zinc oxide (ZnO), characterized by optical and electrical properties similar to ITO and a lower production cost. One of the key factors influencing the properties of the ZnO thin films is the technique and parameters of their production. The comprehensive investigation results of the influence of ZnO thin-films deposition process temperature on their structure, optical properties, and adhesion are presented in the paper. ZnO films were deposited by the magnetron sputtering method. The structural characteristics of the tested films were investigated by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffractometry (XRD) and Raman spectroscopy, while the optical properties of the films were studied by the UV/VIS spectroscopy. Thickness and adhesion measurements of the obtained films were performed using the spectroscopic ellipsometry technique and the scratch test, respectively. The obtained research results showed the influence of the deposition process temperature on the morphology, crystallite size and adhesion of the thin films to the substrate. The effect of process temperature on optical properties, the value of the optical bandgap and crystal structures were analyzed and described. The results of this work have a meaning for the development of surface engineering and may serve as a clue in future studies in the field of modern photovoltaic structures.
A new method for electrical frequency locking of optical FDM transmitters

A novel method for locking the frequency spacing between semiconductor lasers electrically is presented. The method is a modification of the offset frequency master-slave principle. The method allows the frequency spacing between optical channels to be chosen independently, with an accuracy determined by the selectivity of the electronics, and it improves the frequency stability of the locked lasers. A rigorous analytical model of the locking configuration is presented. This model is used to investigate how laser frequency noise and electrical noise from the locking circuit affect the frequency stability of the locked lasers. It is found that the improvements in frequency stability can be achieved for up to 350 lasers, each having a linewidth of 1 MHz. Consequently, the method is suited to lock the transmitters in a coherent optical FDM system. >
Damage Signal Decomposition of Lamb Wave Based on Similarity in SHM

Rapid detecting structural damage by lamb wave is an emerging technology in the field of structural health monitoring, and damage signal decomposition of Lamb wave, with the intent of obtaining reflection signal from damage, is the key point of detecting damage by Lamb wave. Therefore, this paper proposes a new algorithm for damage signal decomposition--similarity-based algorithm. In order to obtain reflection signal form damage, it simulates the reflection signals from damage and boundary with the waveform after the input signal has propagated a distance, and then optimizes the various parameters of the synthetic signal, which consists of reflection signals from damage and boundary, by genetic algorithm based on similarity so that the similarity between the synthetic signal and the damage signal reaches the maximum. Finally, simulation results showed the feasibility and accuracy of the algorithm proposed in this paper.
Passivation schemes for copper/polymer thin film interconnections used in multichip modules

The use of thin inorganic dielectric films as barrier layers between copper and polyimide was examined. Emphasis was placed on discovering the effectiveness of the barrier layers in preventing copper/polyimide interaction and determining its impact on the high-frequency electrical performance of transmission line structures. The integrity of the inorganic dielectric layers as diffusion barriers for the copper was analyzed using transmission electron microscopy. These effects were studied by depositing thin layers of Si/sub 3/N/sub 4/, SiO/sub 2/, and SiO/sub x/N/sub y/ between chromium/copper/chromium lines and either Dow benzocyclobutene or Dupont 2525 polyimide. Both sputtered Si/sub 3/N/sub 4/ and PECVD SiO/sub x/N/sub y/ behaved as diffusion barriers, which resulted in improved performance at very high frequencies over unprotected transmission lines. <<ETX>>