Science Progress最新文献

Increasing concerns about climate change and efforts on reducing reliance on fossil fuels have led to research on electric vehicles for sustainable solutions to increasing energy demands. This study comprehensively analyzes the impact of power plant emissions on the adoption of electric vehicles in relation to air pollution. The main pollutants emitted by power plants and the potential change in emissions with the deployment of electric vehicles are assessed. Energy consumption of the vehicles was calculated. A gasoline-powered and an electric vehicle are modelled in MATLAB Simulink software. The theoretical model results of the main pollutants are compared with the power plant emissions to analyze the effect on major pollutants. This investigation aims to identify the potential CO₂ emission and power requirement by transitioning to electric vehicles. Results show that energy consumption and CO₂ emissions can be 111% and 82% higher than GPVs depending on the electricity generation technologies.

Objective: To explore the correlation between cardiac iron deposition and left ventricular function indicators, such as left ventricular end-diastolic volume index, left ventricular end-systolic volume index, and left ventricular ejection fraction, and to evaluate the accuracy of predicting patients with cardiac iron deposition by using left ventricular ejection fraction as an index.

Methods: This quantitative cross-sectional study involved one hundred and fifty transfusion-dependent patients with β-thalassemia major who were evaluated by magnetic resonance imaging to obtain T₂* values, left ventricular end-diastolic volume index, left ventricular end-systolic volume index, and left ventricular ejection fraction. The relationship between cardiac R₂* values and left ventricular end-diastolic volume index, left ventricular end-systolic volume index, and left ventricular ejection fraction was analyzed.

Results: Out of the 150 patients, cardiac iron overload was not observed for 92 patients, 42 patients exhibited mild to moderate cardiac iron overload, and 16 patients were severe cardiac iron overloaded. A linear correlation was not observed between the cardiac R₂* values and left ventricular end-diastolic volume index, left ventricular end-systolic volume index, and left ventricular ejection fraction (P > 0.05). For the left ventricular ejection fraction index, the sensibility, specificity, positive predictive value, negative predictive value, and the agreement rate were 83.3%, 63.2%, 8.6%, 98.9%, and 64.0%, respectively; also, the area under the receiver operating characteristic curve was 0.348.

Conclusions: A linear correlation was not observed between cardiac R₂* values and left ventricular end-diastolic volume index, left ventricular end-systolic volume index, and left ventricular ejection fraction in patients with β-thalassemia major. Therefore, using left ventricular ejection fraction as an indirect index to predict cardiac iron deposition may be not reliable in clinical practice.

This paper presents a deep analysis of a novel method entitled Dhouib-Matrix-SPP-24 (DM-SPP-24) and its application to rapidly generate the shortest trajectory for an autonomous mobile robot. For this problem, the environment is represented by a grid map where several obstacles are exposed with static positions and the main objective is to plan the shortest trajectory for an autonomous mobile robot from the current to the target positions with obstacles free-collisions. This study introduces an in-depth exploration of the twenty-four movement directions of the DM-SPP-24 method, an application on six grid maps and a comparison to several recent metaheuristics taken from the literature (such as the Improved Ant Colony Algorithm, the enhanced Ant Colony Optimization with Gaussian Sampling, the Particle Swarm Optimization, the Genetic Algorithm and other methods). Indeed, a new method namely DM-SPP-24 is introduced and this study notes an improvement in the quality and the rapidity of the generated solution by DM-SPP-24 versus the solution produced by the recent published metaheuristics in the literature. This work serves as a valuable resource for robotics and path planning viewing that it introduces a very fast and accurate method (DM-SPP-24) to plan the trajectory of an autonomous mobile robot.

The importance of solar systems as a renewable source has recently captured significant efforts from governments around the world to reduce their dependency on fossil fuels. Improving the efficiency of these systems, in general, is an important topic. Specifically, enhancing the control method used for controlling the DC-DC converter occupies a significant place in the efforts dedicated to increasing the efficiency of the solar system. The nonlinearity of such systems might deteriorate the performance of traditional controllers, such as PIDs. Therefore, this paper suggests a new scheme which consists of a PI controller and a neuro-fuzzy controller in a cascade manner. Particle swarm optimization is used for optimally designing the parameters of the PI controller for improving the system's dynamic and steady-state responses. Also, the proposed PI controller has only two tuning parameters which significantly reduce the design time. The system inputs of the proposed fuzzy controller are the power and the current changes, and its output is the duty cycle which directly affects the desired output voltage. On the other hand, the input of the PI controller is the error signal between the desired voltage and the output voltage of the DC-DC converter which forms the controlled variable. The main contribution of the paper is to enhance the efficiency of the system via connecting the optimal PI and neuro-fuzzy controller, which can store human experiences. Different scenarios are used to test the proposed controller and obtain optimal maximum power point tracking under different weather conditions. Results show that the proposed controller significantly improves the efficiency percentage of the DC-DC converter relative to the neuro-fuzzy controller alone by at least 15%. Also, the integral square error index indicates the proposed method has small tracking errors either for the setpoint tracking or disturbance rejection.

Introduction: In this study, we sought to validate the effectiveness of an automated audiometry system in quiet (AA) and noisy environments (AA-N) by comparing the air pure-tone thresholds obtained by AA to those obtained by traditional manual audiometry (MA).

Methods: In this cross-sectional study, 150 participants with or without hearing loss were tested (age: 11-84 years; female: 57.3%). Air conduction thresholds were assessed by MA, AA, and AA-N in a quiet or noisy sound booth.

Results: In participants without hearing loss, 94.5% and 96% of the threshold comparisons differed between MA versus AA and AA versus AA-N within 10 dB HL or less. In participants with hearing loss, there was no statistically significant difference between the three testing conditions at any frequency (p > 0.05). The hearing threshold difference in the poor hearing ear in participants with a bilateral difference ≥40 dB HL was -15 and +15 dB HL; however, this difference was not statistically significant when excluding participants with tinnitus.

Conclusions: Automatic audiometry can accurately estimate hearing thresholds and screen for hearing loss even in noisy environments. Nevertheless, the algorithm must be corrected when patients experience tinnitus.

Symptomatic chronic subdural hematoma (cSDH) is amongst the most frequent neurological diseases with an upward trend due to an aging society and development in the field of anticoagulation therapies. Lately, subgaleal drainages and middle meningeal artery (MMA) embolization have been introduced to the standard armamentarium as treatment options for cSDH patients. Vascular anomalies, such as internal carotid artery (ICA) occlusion with spontaneous extra-intracranial anastomoses, usually lead to forfeiting embolization treatment from patients. This report presents a case of a 67-year-old male with a repeated recurrence of cSDH in conjunction with a history of middle cerebral artery territory stroke and consecutive platelet inhibition therapy. The patient was initially treated with a burr hole plus subgaleal and subdural drainage upon revision surgery. Due to repeated recurrence, MMA embolization was considered, even though an extra-intracranial anastomosis was present on angiography. The patient was deemed to be fully recovered three months after intervention and no further intervention was needed. We can conclude that MMA embolization is a feasible option also in patients with recurrent cSDH after territorial infarction secondary to ICA occlusion with present extra-intracranial anastomoses.

The recent severe acute respiratory syndrome coronavirus 2 pandemic has clearly exemplified the need for broad-spectrum antiviral (BSA) medications. However, previous outbreaks show that about one year after an outbreak, interest in antiviral research diminishes and the work toward an effective medication is left unfinished. Martin et al. endeavored to support the early stages of focused BSA development by creating the Small Molecule Antiviral Compound Collection (SMACC), which is publicly available online at https://smacc.mml.unc.edu. SMACC is a highly curated database with over 32,500 entries of chemical compounds tested in both phenotypic and target-based assays across 13 viruses from the NIAID's list of emerging infectious diseases/pathogens. The authors advise judicious use of knowledge collections such as SMACC and recommend users critically evaluate retrieved data and resulting hypotheses prior to experimental testing. When used correctly, SMACC-like databases may serve as a reference for medicinal chemists and virologists working to develop novel BSA medications. To summarize, we emphasize the importance of data curation for both novel outbreak prediction and development of BSAs against these outbreaks.

Introduction: Hospital admission due to fragility hip fracture has increased significantly in recent years. In patients with hip fracture, perioperative pain management is usually with opioids, whose dosage is difficult to adjust and have many side effects, especially in older adults. The purpose of this study was to determine the impact and the advantages of the implementation of the fascia iliaca blockade in older adults with hip fracture due to fragility included in the Orthogeriatric Clinical Care Center of the Fundación Santa Fe de Bogotá and the San José Infantil University Hospital in Bogotá, Colombia. The primary outcome of our study is the incidence of delirium during hospitalization. Methods: A retrospective observational cohort study was conducted. The data was collected from patients older than 65 years treated for a fragility fracture of the hip in two fourth-level hospitals in Bogotá, Colombia from the beginning of 2019 until the end of 2020. Results: A sample of 218 patients was obtained, of which 119 received conventional analgesic management. 99 patients underwent fascia iliaca blockade. No significant difference was found between the use of the block and the development of delirium (p = 0.442). There was a higher consumption of opioids in the conventional analgesia group compared to the block group (27.61 mg vs 16.34 mg, respectively, p = 0.003), longer duration of the surgical procedure (90.84 vs 81.08 min, respectively, p = 0.030) and longer hospital stay (6.06 vs 5.41 days, respectively, p = 0.641). Conclusions: While this study found no significant difference in the incidence of delirium, fascia iliaca blockade was associated with significant reductions in opioid consumption and shorter procedural times. These findings suggest that fascia iliaca blockade may improve pain management efficiency in older adults with hip fractures.

Because of their proficiency in capturing the category characteristics of graphs, graph neural networks have shown remarkable advantages for graph-level classification tasks, that is, rumor detection and anomaly detection. Due to the manipulation of special means (e.g. bots) on online media, rumors may spread across the whole network at an overwhelming speed. Compared with normal information, popular rumors usually have a special propagation structure, especially in the early stage of information dissemination. More specifically, the special propagation structure determines whether rumors can be spread successfully. Namely, online users and their interaction that constitute the special propagation structure play a key role in the spread of rumors. Therefore, the problem of rumor detection can be transformed into detecting the existence of a special propagation structure. Inspired by backdoor attacks, we propose an interpretable rumor detection algorithm based on backdoor. Firstly, based on causal analysis, the causal sub-graph that determines the category of the graph (rumor vs. normal information) is obtained, that is, the critical online users in the rumor spreading effect are found, and then the specific propagation structure is explored. Finally, the special propagation structure is planted into the rumor detection model as a trigger. Experimental results and performance analysis on three real-world datasets demonstrate the effectiveness of our proposed algorithm in the special propagation structure detection of rumors. Compared with two baselines, Lurker achieves up to 33.1% and 61.8% performance improvement in terms of attack success rate and clean accuracy drop.

Photocatalysts are the most essential in photocatalytic degradation of dyes in wastewater. Here, ZnO/TiO₂ composite photocatalysts with variable proportions were prepared by chemical deposition method in order to meet the realistic requirements of low-cost synthesis, high stability, and environmental friendliness. The as-prepared photocatalyst was characterized by the technologies of scanning electron microscope, transmission electron microscope, X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, UV-vis diffuse reflection, photoluminescence spectroscopy, electrochemistry, nitrogen adsorption and X-ray diffraction. The degradation of methyl orange (MO) was applied to evaluate the photocatalytic activity of ZnO/TiO₂ under low-power irradiation. At the same time, the effects of the chemical composition of photocatalyst, pH and MO concentration of solution on the photocatalytic degradation performance were mainly investigated. The results demonstrated an excellent synergistic effect between ZnO and TiO₂ for improving the photocatalytic efficiency of the composite catalyst. The highest degradation rate of MO reaches to 98.6% for the photocatalyst with a mass proportion of ZnO:TiO₂ being 0.131:1 under the condition of 10 mg/L for MO concentration and 6.7 for pH via the light of ultraviolet radiation A band. This study brings a new way for the production of low-cost and efficient catalysts with low-power light sources to mitigate azo dyes, e.g. MO.