Enabling Fine Sample Rate Settings in DSOs with Time-Interleaved ADCs

The time-base used by digital storage oscilloscopes allows limited selections of the sample rate, namely constrained to a few integer submultiples of the maximum sample rate. This limitation offers the advantage of simplifying the data transfer from the analog-to-digital converter to the acquisition memory, and of assuring stability performances, expressed in terms of absolute jitter, that are independent of the chosen sample rate. On the counterpart, it prevents an optimal usage of the memory resources of the oscilloscope and compels to post processing operations in several applications. A time-base that allows selecting the sample rate with very fine frequency resolution, in particular as a rational submultiple of the maximum rate, is proposed. The proposal addresses the oscilloscopes with time-interleaved converters, that require a dedicated and multifaceted approach with respect to architectures where a single monolithic converter is in charge of signal digitization. The proposed time-base allows selecting with fine frequency resolution sample rate values up to 200 GHz and beyond, still assuring jitter performances independent of the sample rate selection.

Ship Detection via Dilated Rate Search and Attention-Guided Feature Representation

Due to the complexity of scene interference and the variability of ship scale and position, automatic ship detection in remote sensing images makes for challenging research. The existing deep networks rarely design receptive fields that fit the target scale based on training data. Moreover, most of them ignore the effective retention of position information in the feature extraction process, which reduces the contribution of features to subsequent classification. To overcome these limitations, we propose a novel ship detection framework combining the dilated rate selection and attention-guided feature representation strategies, which can efficiently detect ships of different scales under the interference of complex environments such as clouds, sea clutter and mist. Specifically, we present a dilated convolution parameter search strategy to adaptively select the dilated rate for the multi-branch extraction architecture, adaptively obtaining context information of different receptive fields without sacrificing the image resolution. Moreover, to enhance the spatial position information of the feature maps, we calculate the correlation of spatial points from the vertical and horizontal directions and embed it into the channel compression coding process, thus generating the multi-dimensional feature descriptors which are sensitive to direction and position characteristics of ships. Experimental results on the Airbus dataset demonstrate that the proposed method achieves state-of-the-art performance compared with other detection models.

A Review on Design Basis for Constructed Wetlands for Wastewater Treatment

Since last few years Constructed Wetlands (CWs) are being used to treat secondary or tertiary municipal or domestic wastewater effluents have been recognized as an effective means of “green technology” for wastewater treatment. Constructed wetlands (CWs) provide a natural way for simple, inexpensive, and robust wastewater treatment. The idea of natural management systems is the restoration of disturbed ecosystems and their sustainability for remuneration to nature. The Constructed wetlands (CWs) are designed to copy natural wetland systems, utilizing wetland plants, soil and associated microorganisms using various biological, physicochemical processes to remove unwanted constituents from wastewater effluents. This review paper studies various types of constructed wetlands, i.e., surface or subsurface, vertical or horizontal flow and their type of operation, i.e., continuous, batch or intermittent flow, loading rate, selection of plants and wastewater characteristics that affect the treatment efficiency. The design models with their suitability for various parameters and operational conditions such as Darcy’s equation, Kadlec and Knight Model (K-C* model), Arrhenius equation, and population equivalent calculation have been discussed. Lastly, future research requirements have been considered.

Spectral Classification Based on Deep Learning Algorithms

Convolutional neural networks (CNN) can achieve accurate image classification, indicating the current best performance of deep learning algorithms. However, the complexity of spectral data limits the performance of many CNN models. Due to the potential redundancy and noise of the spectral data, the standard CNN model is usually unable to perform correct spectral classification. Furthermore, deeper CNN architectures also face some difficulties when other network layers are added, which hinders the network convergence and produces low classification accuracy. To alleviate these problems, we proposed a new CNN architecture specially designed for 2D spectral data. Firstly, we collected the reflectance spectra of five samples using a portable optical fiber spectrometer and converted them into 2D matrix data to adapt to the deep learning algorithms’ feature extraction. Secondly, the number of convolutional layers and pooling layers were adjusted according to the characteristics of the spectral data to enhance the feature extraction ability. Finally, the discard rate selection principle of the dropout layer was determined by visual analysis to improve the classification accuracy. Experimental results demonstrate our CNN system, which has advantages over the traditional AlexNet, Unet, and support vector machine (SVM)-based approaches in many aspects, such as easy implementation, short time, higher accuracy, and strong robustness.

Impact of Adjuvant Chemoradiotherapy on Survival of Resected Pancreatic Adenocarcinoma Cancer: A Surveillance, Epidemiology and End Results (SEER) Analysis

BackgroundThe benefits of postoperative adjuvant chemoradiotherapy (CRT) for pancreatic cancer remain controversial. The purpose of this study is to determine if adjuvant CRT can improve the overall survival of postoperative pancreatic cancer patients compared to adjuvant chemotherapy (CT).MethodsPatients with resected pancreas adenocarcinoma were identified in the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016). Multivariate Cox regression was used to determine the factors related to survival rate. Selection bias was reduced to a minimum through propensity matching analysis. Subgroup analyses by clinical characteristics were performed.ResultsThis study identified 10,097 patients who received adjuvant CT (n = 5,454) or adjuvant CRT (n = 4,643). On multivariate analysis, age, sex, tumor size, site, grade, stage, T stage, and lymph node metastasis were independent risk factors for OS. The basic clinical characteristics were well balanced after propensity matching. After propensity matching, CRT can improve the survival rate compared with CT [median OS: 22 months vs 23 months (HR, 0.928; 95% CI, 0.881–0.977; P = 0.004)]. Subgroup analysis indicated that the survival benefit of adjuvant chemoradiotherapy was more significant in patients with female (HR, 0.860; 95% CI, 0.798–0.926; P = 0.005 for interaction) or T3 (HR, 0.905; 95% CI, 0.855–0.957; P = 0.04 for interaction) or lymph nodes positive (HR, 0.883; 95% CI, 0.832–0.938; P = 0.005 for interaction).ConclusionAdjuvant CRT was associated with improved survival compared with adjuvant CT in patients with resection of pancreatic ductal adenocarcinoma. The benefit was more significant in patients with female or T3 or lymph nodes positive.

Transmit Power and Rate Control for Spatial Reuse in Dense Wireless LANs

Spatial reuse is an approach to better utilize the wireless medium in dense networks. In contrast to time multiplexed channel access, the idea is to allow a certain level of interference between parallel transmitting links. Depending on transmit power and rate settings, such parallel transmissions may result in increased overall system performance. This paper presents a systematic approach to model dense networks and optimize transmit power and rate settings for best total system performance. It discusses driving factors and limitations for spatial reuse. The paper introduces two algorithms for concurrent optimal transmit power and rate selection. System simulations using a fading channel model compare the performance of the algorithms against CSMA/CA. The simulation results show that average system performance can be increased by 100% and more.

Estimated Spike Evolution and Impact of Emerging SARS-CoV-2 Variants

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, has been mutating and thus variants emerged. This suggests that SARS-CoV-2 could mutate at an unsteady pace. Supportive evidence comes from the accelerated evolution which was revealed by tracking mutation rates of the genomic location of Spike protein. This process is sponsored by a small portion of the virus population but not the largest viral clades. Moreover, it generally took one to six months for current variants that caused peaks of COVID-19 cases and deaths to survive selection pressure. Based on this statistic result and the above speedy Spike evolution, another upcoming peak would come around July 2021 and disastrously attack Africa, Asia, Europe, and North America. This is the prediction generated by a mathematical model on evolutionary spread. The reliability of this model and future trends out of it comes from the comprehensive consideration of factors mainly including mutation rate, selection course, and spreading speed. Notably, if the prophecy is true, then the new wave will be the first determined by accelerated Spike evolution.

Are Discount Rates In Disarray In The First Year Adoption Of International Financial Reporting Standards?

In calculating recoverable amount of cash generating units (CGUs) under the implementation of value in use approach, discount rate selection represents a central point in deciding the magnitude of impairment charges under Hong Kong Financial Reporting Standards (HKFRSs). The selection of discretion discount rate in the discounted cash flow model (DCF) could be used opportunistically to misstate impairment losses for the benefit of financial statement preparers and causes the transparency of the financial reports. This study is conducted to provide evidence of opportunistic behaviours relating on goodwill impairment by reporting statement preparers. By comparing independently estimated risk adjusted discount rates and those subjectively presented by large listed Hong Kong firms in the first year adoption of HKFRSs, the results showed that discount rates were presented in disarray, in which discount rates were more overstated than understated in comparison with scientifically generated ones.

Predictors of genomic differentiation within a hybrid taxon

ABSTRACTHybridization is increasingly recognized as an important evolutionary force. Novel genetic methods now enable us to address how the genomes of parental species are combined to build hybrid genomes. However, we still do not know the relative importance of contingencies, genome architecture and local selection in shaping hybrid genomes. Here, we take advantage of the genetically divergent island populations of Italian sparrow on Crete, Corsica and Sicily to investigate the predictors of genomic variation within a hybrid taxon. We test if differentiation is affected by recombination rate, selection, or variation in ancestry proportion from each parent species. We find that the relationship between recombination rate and differentiation is less pronounced within hybrid lineages than between the parent species, as expected if purging of minor parent ancestry in low recombination regions reduces the variation available for differentiation. In addition, we find that differentiation between islands is correlated with differences in selection in two out of three comparisons. Patterns of within-island selection are correlated across all islands, suggesting that shared selection may mould genomic differentiation. The best predictor of strong differentiation within islands is the degree of differentiation from house sparrow, and hence loci with Spanish sparrow ancestry may vary more freely. Jointly, this suggests that constraints and selection interact in shaping the genomic landscape of differentiation in this hybrid species.

Estimated Impacts of Emerald Ash Borer on Ash Timber Supply in Texas, USA

We estimated annual timber growth, removals, and mortalities under various scenarios of the spread of emerald ash borer (Agrilus planipennis Fairmaire; EAB) within Texas. Future annual ash EAB-induced mortalities were simulated to follow either a normal or beta distribution over 25, 50, or 75 years, with five percent of the original inventory remaining at the conclusion of each projection. Discounted present values of future ash growth, harvests, mortalities, salvage, and beginning and ending annual inventories were calculated, and economic impacts to timber receipts were determined from average real prices. The present net effects of timber product output, mortalities, and salvage resulted in benefits ranging from lows of (delivered/stumpage) $37.6/$12.8 million over 25 years when assuming a normal distribution to highs of $247.8/$97.2 million over 75 years under a beta distribution. Salvage intensity exceeded mortality accumulation by a factor of at least 2.00. Regardless of length chosen, mortality that skewed toward later years led to lower discounted volumes and less value lost to EAB. Results were sensitive to discount rate selection (constant, increasing, distributional) with the constant and increasing rates having the most similar results. Longer time horizons led to far smaller losses of overall economic returns allowing more typical harvest management despite EAB.