Ultra-wideband localization with collocated receivers

Abstract-A three-dimensional (3-D) ultra-wideband time-ofarrival (TOA) localization scheme that employs a single cluster of receivers is studied in this paper. The receivers are placed in proximity (e.g., on a two-dimensional plane within a few decimeters), and thus it does not require wireless synchronization of the receivers. The optimum 3-D receiver placement in the sense of minimum estimation variance defined by the Cramér-Rao lower bound is analyzed. The position error bound as a function of the number of receivers and the distance between the source and the receiver unit is derived. A hardware and software prototype that works in the 3.1−

Research on Heat Transfer Inside the Furnace of Large Scale CFB Boilers

Field tests in one unit of 135MWe and two units of 300MWe commercial Circulating Fluidized bed (CFB) boilers (A&B) with different structures were carried out. The influence of operating conditions on the thermal boundary layer, local heat transfer coefficient and peripheral distribution of heat transfer coefficient were studied. It was found that, in the 135MWe and 300MWe-A CFB furnace, the thickness of the thermal boundary layer was almost constant, about 100mm, and independent of the height above the distributor and the boiler load. The local heat transfer coefficient increased with increasing load as well as the coal feeding rate and air volume in both the 135MWe and 300MWe-A CFB boilers. The boiler structure and heating surface layout had a great influence on the distribution of the heat transfer coefficient in the large-scale CFB boilers. In both the 135MWe furnace and the 300MWe-B CFB boilers, the heat transfer coefficient was lower in the center than near the corner due to higher suspension density in the corner. In the 300MWe-B CFB with heating surfaces in the furnace, because of the uneven layout of the heating surface and the mal-distribution of gas-solid flow caused by the asymmetric arrangement of cyclones, heat transfer coefficients tended to be higher in the middle part than at the walls

Rapamycin Attenuated Zinc-Induced Tau Phosphorylation and Oxidative Stress in Rats: Involvement of Dual mTOR/p70S6K and Nrf2/HO-1 Pathways

Alzheimer's disease is pathologically characterized by abnormal accumulation of amyloid-beta plaques, neurofibrillary tangles, oxidative stress, neuroinflammation, and neurodegeneration. Metal dysregulation, including excessive zinc released by presynaptic neurons, plays an important role in tau pathology and oxidase activation. The activities of mammalian target of rapamycin (mTOR)/ribosomal S6 protein kinase (p70S6K) are elevated in the brains of patients with Alzheimer's disease. Zinc induces tau hyperphosphorylation via mTOR/P70S6K activation in vitro. However, the involvement of the mTOR/P70S6K pathway in zinc-induced oxidative stress, tau degeneration, and synaptic and cognitive impairment has not been fully elucidated in vivo. Here, we assessed the effect of pathological zinc concentrations in SH-SY5Y cells by using biochemical assays and immunofluorescence staining. Rats (n = 18, male) were laterally ventricularly injected with zinc, treated with rapamycin (intraperitoneal injection) for 1 week, and assessed using the Morris water maze. Evaluation of oxidative stress, tau phosphorylation, and synaptic impairment was performed using the hippocampal tissue of the rats by biochemical assays and immunofluorescence staining. The results from the Morris water maze showed that the capacity of spatial memory was impaired in zinc-treated rats. Zinc sulfate significantly increased the levels of P-mTOR Ser2448, P-p70S6K Thr389, and P-tau Ser356 and decreased the levels of nuclear factor erythroid 2-related factor-2 (Nrf2) and heme oxygenase-1 (HO-1) in SH-SY5Y cells and in zinc-treated rats compared with the control groups. Increased expression of reactive oxygen species was observed in zinc sulfate-induced SH-SY5Y cells and in the hippocampus of zinc-injected rats. Rapamycin, an inhibitor of mTOR, rescued zinc-induced increases in mTOR/p70S6K activation, tau phosphorylation, and oxidative stress, and Nrf2/HO-1 inactivation, cognitive impairment, and synaptic impairment reduced the expression of synapse-related proteins in zinc-injected rats. In conclusion, our findings imply that rapamycin prevents zinc-induced cognitive impairment and protects neurons from tau pathology, oxidative stress, and synaptic impairment by decreasing mTOR/p70S6K hyperactivity and increasing Nrf2/HO-1 activity

Cabin air quality on non-smoking commercial flights: a review of published data on airborne pollutants

We reviewed 47 documents published 1967-2019 that reported measurements of volatile organic compounds (VOCs) on commercial aircraft. We compared the measurements with the air quality standards and guidelines for aircraft cabins and in some cases buildings. Average levels of VOCs for which limits exist were lower than the permissible levels except for benzene with average concentration at 5.9±5.5 μg/m3. Toluene, benzene, ethylbenzene, formaldehyde, acetaldehyde, limonene, nonanal, hexanal, decanal, octanal, acetic acid, acetone, ethanol, butanal, acrolein, isoprene and menthol were the most frequently appearing compounds. The concentrations of SVOCs (Semi-Volatile Organic Compounds) and other contaminants did not exceed standards and guidelines in buildings except for the average NO2 concentration at 12 ppb. Although the focus was on VOCs, we also retrieved the data on other parameters characterizing cabin environment. Ozone concentration averaged 38±30 ppb below the upper limit recommended for aircraft. The outdoor air supply rate ranged from 1.7 to 39.5 L/s per person and averaged 6.0±0.8 L/s/p (median 5.8 L/s/p), higher than the minimum level recommended for commercial aircraft. Carbon dioxide concentration averaged 1,315±232 ppm, lower than what is permitted in aircraft and close to what is permitted in buildings. Measured temperatures averaged 23.5±0.8°C and were generally within the ranges recommended for avoiding thermal discomfort. Relative humidity averaged 16%±5%, lower than what is recommended in buildings

Unleashing the power of supply chain learning: an empirical investigation

Purpose Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This study investigates the extent to which supply chain learning (SCL) affects operational resilience under such circumstances. Design/methodology/approach This study developed a research framework and underlying hypotheses based on SCL and information processing theory (IPT). An empirical test was carried out using secondary data derived from the “Supply Chain Policy” launched by the Chinese government and two large related conferences. Findings SCL positively relates to operational resilience, and several moderators influence the relationship between them. The authors argue that digital-technological diversity could weaken the role of SCL in operational resilience, whereas customer concentration, and participating in a pilot programme could enhance the effect of SCL. Practical implications Firms should embrace the power of SCL in building resilience in the VUCA era. Meanwhile, they should be cautious of a digital-technological diversification strategy, appraise the customer base profile and proactively engage in pilot programmes. Originality/value This research develops the SCL construct further in the context of China and empirically measures its power on operational resilience using a unique dataset. This contributes to the theorisation of SCL

A multi-stage algorithm for solving multi-objective optimization problems with multi-constraints

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.There are usually multiple constraints in constrained multi-objective optimization. Those constraints reduce the feasible area of the constrained multi-objective optimization problems (CMOPs) and make it difficult for current multi-objective optimization algorithms (CMOEAs) to obtain satisfactory feasible solutions. In order to solve this problem, this paper studies the relationship between constraints, then obtains the priority between constraints according to the relationship between the Pareto Front (PF) of the single constraint and their common PF. Meanwhile, this paper proposes a multi-stage CMOEA and applies this priority, which can save computing resources while helping the algorithm converge. The proposed algorithm completely abandons the feasibility in the early stage to better explore the objective space, and obtains the priority of constraints according to the relationship; Then the algorithm evaluates a single constraint in the medium stage to further explore the objective space according to this priority, and abandons the evaluation of some less-important constraints according to the relationship to save the evaluation times; At the end stage of the algorithm, the feasibility will be fully considered to improve the quality of the solutions obtained in the first two stages, and finally get the solutions with good convergence, feasibility, and diversity. The results on five CMOP suites and three real-world CMOPs show that the algorithm proposed in this paper can have strong competitiveness in existing constrained multi-objective optimization

Epidemiological changes and molecular characteristics of Brucella strains in Ningxia, China

ObjectiveHuman brucellosis causes serious public health concerns in Ningxia, China.MethodsThis study employed epidemiological, bacteriological, and multiple-locus variable-number tandem repeat analysis (MLVA) methods to conduct an epidemiological investigation, which is necessary for devising tailored control strategies.ResultsBetween 1958 and 2022, 29,892 cases were reported, with an average annual number of cases and incidence of 467 and 7.1/100,000, respectively. The epidemic situation gradually worsened, with cases escalating from 26 cases in 2005 to 6,292 in 2022, with the incidence rate rising from 0.441 in 2005 to 86.83 in 2022. Geographically, the disease spread from a single affected county in 2004 to encompass all 22 counties in 2022. Yanchi County had the highest incidence, followed by the Hongsibao and Tongxin counties. These data suggest that Brucella infection has become a rampant regional concern in human brucellosis. Between 1958 and 2019, a total of 230 Brucella strains were identified across four studied hosts. These strains comprised four species with 12 biovars, including B. melitensis bv. 1, bv. 2, bv. 3, B. abortus bv. 1, bv. 3, bv. 4, bv. 5, bv. 6, bv. 7, B. suis bv. 1 and bv. 3, and B. canis. These data highlight the high species/biovars and host diversity of the Brucella population, posing a substantial challenge to brucellosis surveillance. There was an apparent transition from multiple species/biovars historically to the current dominance of a single species, B. melitensis, emphasizing the requirement for strengthening surveillance of B. melitensis. Genotypes 42 and 116, constituting 96.2% of the total number of genotypes, predominated in panel 1 and MLVA-11, indicating that all strains belong to the East Mediterranean lineage. MLVA cluster analysis revealed persistent transmission of dominant circulating genotypes, presenting an epidemic pattern characterized primarily by epidemiologically related cases with a few sporadic cases. Strains in this study exhibited high genetic homogeneity with strains from the Northwest, and those from Kazakhstan and Mongolia.ConclusionThe epidemic situation of human brucellosis has gradually worsened; the rampant epidemic of the disease has become a regional concern. The present study highlights that implementing the of targeted surveillance and intervention strategies is urge

A multi-population evolutionary algorithm using new cooperative mechanism for solving multi-objective problems with multi-constraint

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In science and engineering, multi-objective optimization problems usually contain multiple complex constraints, which poses a significant challenge in obtaining the optimal solution. This paper aims to solve the challenges brought by multiple complex constraints. First, this paper analyzes the relationship between single constrained Pareto Front (SCPF) and their common Pareto Front sub-constrained Pareto Front (SubCPF). Next, we discussed the SCPF, SubCPF, and Unconstrainti Pareto Front (UPF)’s help to solve constraining Pareto Front (CPF). Then further discusses what kind of cooperation should be used between multiple populations constrained multi-objective optimization algorithm (CMOEA) to better deal with multi-constrained multi-objective optimization problems (mCMOPs). At the same time, based on the discussion in this paper, we propose a new multi-population CMOEA called MCCMO, which uses a new cooperation mechanism. MCCMO uses C+2 (C is the number of constraints) populations to find the UPF, SCPF, and SubCPF at an appropriate time. Furthermore, MCCMO uses the newly proposed Activation Dormancy Detection (ADD) to accelerate the optimization process and uses the proposed Combine Occasion Detection (COD) to find the appropriate time to find the SubCPF. The performance on 32 mCMOPs and real-world mCMOPs shows that our algorithm can obtain competitive solutions on MOPs with multiple constraints

A finite element numerical simulation analysis of mine direct current method’s advanced detection under varied field sources

Ensuring the safety of coal mine production requires accurate forecasting of coal road heading faces in advance. Because of its high resistance to electromagnetic interference, the mine direct current (DC) method has been widely utilized in the advanced detection and prediction of coal mines. The layout of the field source significantly influences the detection outcomes obtained through this method. In this study, a variety of full-space three-dimensional geoelectric models were established based on the fundamental principle of DC resistivity, and the response features of geological anomalies located in various positions in front of a roadway were studied under different field source conditions using finite element numerical simulation. The electrical response characteristics were analyzed with the electrodes positioned in different directions and two-point to seven-point current sources located on the floor and side of the roadway, respectively. The electrical response of the geological anomalies was characterized with varying positions of the multi-point current source in the roadway and the pole distance of the power supply electrode. Furthermore, the electrical response characteristics of the mine DC method in advanced detection were compared for geological anomalies placed differently across the entire space. The results indicate that the response effect of the geological anomaly in front of the roadway is greater when the field source is placed on the shorter side of the roadway cross-section, with the number of field sources showing a positive correlation with the product of the pole distance and low-resistance amplitude. In advanced detection by DC method, the existence of geological anomalies on the side will affect the recognition of anomalies in front of the roadway

Automatic Recognition of Laryngoscopic Images Using a Deep-Learning Technique

Objectives/Hypothesis: To develop a deep-learning–based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngoscopy findings. Study Design: Retrospective study. Methods: A total of 24,667 laryngoscopy images (normal, vocal nodule, polyps, leukoplakia and malignancy) were collected to develop and test a convolutional neural network (CNN)-based classifier. A comparison between the proposed CNN-based classifier and the clinical visual assessments (CVAs) by 12 otolaryngologists was conducted. Results: In the independent testing dataset, an overall accuracy of 96.24% was achieved; for leukoplakia, benign, malignancy, normal, and vocal nodule, the sensitivity and specificity were 92.8% vs. 98.9%, 97% vs. 99.7%, 89% vs. 99.3%, 99.0% vs. 99.4%, and 97.2% vs. 99.1%, respectively. Furthermore, when compared with CVAs on the randomly selected test dataset, the CNN-based classifier outperformed physicians for most laryngeal conditions, with striking improvements in the ability to distinguish nodules (98% vs. 45%, P <.001), polyps (91% vs. 86%, P <.001), leukoplakia (91% vs. 65%, P <.001), and malignancy (90% vs. 54%, P <.001). Conclusions: The CNN-based classifier can provide a valuable reference for the diagnosis of laryngeal neoplasms during laryngoscopy, especially for distinguishing benign, precancerous, and cancer lesions. Level of Evidence: NA Laryngoscope, 130:E686–E693, 2020