A Four-Stage Data Augmentation Approach to ResNet-Conformer Based Acoustic Modeling for Sound Event Localization and Detection

In this paper, we propose a novel four-stage data augmentation approach to ResNet-Conformer based acoustic modeling for sound event localization and detection (SELD). First, we explore two spatial augmentation techniques, namely audio channel swapping (ACS) and multi-channel simulation (MCS), to deal with data sparsity in SELD. ACS and MDS focus on augmenting the limited training data with expanding direction of arrival (DOA) representations such that the acoustic models trained with the augmented data are robust to localization variations of acoustic sources. Next, time-domain mixing (TDM) and time-frequency masking (TFM) are also investigated to deal with overlapping sound events and data diversity. Finally, ACS, MCS, TDM and TFM are combined in a step-by-step manner to form an effective four-stage data augmentation scheme. Tested on the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 data sets, our proposed augmentation approach greatly improves the system performance, ranking our submitted system in the first place in the SELD task of DCASE 2020 Challenge. Furthermore, we employ a ResNet-Conformer architecture to model both global and local context dependencies of an audio sequence to yield further gains over those architectures used in the DCASE 2020 SELD evaluations.Comment: 12 pages, 8 figure

Minimum Energy Expenditure of Arm and Leg Motions

The purpose of the study is to find the optimized arm and leg motions by computer simulation. The research method of this study was based on Lagrange-Euler equations (LEE) of motion and the seven types of homogeneous transformation matrices (CH-7T) defin

Overcome Cancer Cell Drug Resistance Using Natural Products

Chemotherapy is one of the major treatment methods for cancer. However, failure in chemotherapy is not uncommon, mainly due to dose-limiting toxicity associated with drug resistance. Management of drug resistance is important towards successful chemotherapy. There are many reports in the Chinese literature that natural products can overcome cancer cell drug resistance, which deserve sharing with scientific and industrial communities. We summarized the reports into four categories: (1) in vitro studies using cell line models; (2) serum pharmacology; (3) in vivo studies using animal models; and (4) clinical studies. Fourteen single compounds were reported to have antidrug resistance activity for the first time. In vitro, compounds were able to overcome drug resistance at nontoxic or subtoxic concentrations, in a dose-dependent manner, by inhibiting drug transporters, cell detoxification capacity, or cell apoptosis sensitivity. Studies in vivo showed that single compounds, herbal extract, and formulas had potent antidrug resistance activities. Importantly, many single compounds, herbal extracts, and formulas have been used clinically to treat various diseases including cancer. The review provides comprehensive data on use of natural compounds to overcome cancer cell drug resistance in China, which may facilitate the therapeutic development of natural products for clinical management of cancer drug resistance

Overcome Cancer Cell Drug Resistance Using Natural Products

Chemotherapy is one of the major treatment methods for cancer. However, failure in chemotherapy is not uncommon, mainly due to dose-limiting toxicity associated with drug resistance. Management of drug resistance is important towards successful chemotherapy. There are many reports in the Chinese literature that natural products can overcome cancer cell drug resistance, which deserve sharing with scientific and industrial communities. We summarized the reports into four categories: (1) in vitro studies using cell line models; (2) serum pharmacology; (3) in vivo studies using animal models; and (4) clinical studies. Fourteen single compounds were reported to have antidrug resistance activity for the first time. In vitro, compounds were able to overcome drug resistance at nontoxic or subtoxic concentrations, in a dose-dependent manner, by inhibiting drug transporters, cell detoxification capacity, or cell apoptosis sensitivity. Studies in vivo showed that single compounds, herbal extract, and formulas had potent antidrug resistance activities. Importantly, many single compounds, herbal extracts, and formulas have been used clinically to treat various diseases including cancer. The review provides comprehensive data on use of natural compounds to overcome cancer cell drug resistance in China, which may facilitate the therapeutic development of natural products for clinical management of cancer drug resistance

Soft Margin Estimation with Various Separation Levels for LVCSR

ABSTRACT We continue our previous work on soft margin estimation (SME) to large vocabulary continuous speech recognition (LVCSR) in two new aspects. The first is to formulate SME with different unit separation. SME methods focusing on string-, word-, and phonelevel separation are defined. The second is to compare SME with all the popular conventional discriminative training (DT) methods, including maximum mutual information estimation (MMIE), minimum classification error (MCE), and minimum word/phone error (MWE/MPE). Tested on the 5k-word Wall Street Journal task, all the SME methods achieves a relative word error rate (WER) reduction from 17% to 25% over our baseline. Among them, phone-level SME obtains the best performance. Its performance is slightly better than that of MPE, and much better than those of other conventional DT methods. With the comprehensive comparison with conventional DT methods, SME demonstrates its success on LVCSR tasks

Sample Size and Repeated Measures Required in Studies of Foods in the Homes of African-American Families

Measurement of the home food environment is of interest to researchers because it affects food intake and is a feasible target for nutrition interventions. The objective of this study was to provide estimates to aid the calculation of sample size and number of repeated measures needed in studies of nutrients and foods in the home. We inventoried all foods in the homes of 80 African-American first-time mothers and determined 6 nutrient-related attributes. Sixty-three households were measured 3 times, 11 were measured twice, and 6 were measured once, producing 217 inventories collected at ~2-mo intervals. Following log transformations, number of foods, total energy, dietary fiber, and fat required only one measurement per household to achieve a correlation of 0.8 between the observed and true values. For percent energy from fat and energy density, 3 and 2 repeated measurements, respectively, were needed to achieve a correlation of 0.8. A sample size of 252 was needed to detect a difference of 25% of an SD in total energy with one measurement compared with 213 with 3 repeated measurements. Macronutrient characteristics of household foods appeared relatively stable over a 6-mo period and only 1 or 2 repeated measures of households may be sufficient for an efficient study design

Body Mass Index at Age 25 and All-Cause Mortality in Whites and African Americans: The Atherosclerosis Risk in Communities Study

Approximately 20% of young adults in the United States are obese, and most gain weight between young and middle adulthood. Few studies have examined the association between elevated BMI in early adulthood and mortality or examined such effects independent of changes in weight. We know of no studies in African American samples

Long- and Short-term Weight Change and Incident Coronary Heart Disease and Ischemic Stroke: The Atherosclerosis Risk in Communities Study

Weight gain increases the prevalence of obesity, a risk factor for cardiovascular disease. Nevertheless, unintentional weight loss can be a harbinger of health problems. The Atherosclerosis Risk in Communities Study (1987–2009) included 15,792 US adults aged 45–64 years at baseline and was used to compare associations of long-term (30 years) and short-term (3 years) weight change with the risks of coronary heart disease (CHD) and ischemic stroke. Age-, gender-, and race-standardized incidence rates were 4.9 (95% confidence interval (CI): 4.6, 5.2) per 1,000 person-years for CHD and 2.5 (95% CI: 2.3, 2.8) per 1,000 person-years for stroke. After controlling for baseline body mass index and other covariates, long-term weight gain (since age 25 years) of more than 2.7% was associated with elevated CHD risk, and any long-term weight gain was associated with increased stroke risk. Among middle-aged adults, short-term (3-year) weight loss of more than 3% was associated with elevated immediate CHD risk (hazard ratio = 1.46, 95% CI: 1.18, 1.81) and stroke risk (hazard ratio = 1.45, 95% CI: 1.10, 1.92). Risk tended to be larger in adults whose weight loss did not occur through dieting. Avoidance of weight gain between early and middle adulthood can reduce risks of CHD and stroke, but short-term, unintentional weight loss in middle adulthood may be an indicator of immediate elevated risk that has not previously been well recognized

Development, test and comparison of two Multiple Criteria Decision Analysis(MCDA) models: A case of healthcare infrastructure location

When planning a new development, location decisions have always been a major issue. This paper examines and compares two modelling methods used to inform a healthcare infrastructure location decision. Two Multiple Criteria Decision Analysis (MCDA) models were developed to support the optimisation of this decision-making process, within a National Health Service (NHS) organisation, in the UK. The proposed model structure is based on seven criteria (environment and safety, size, total cost, accessibility, design, risks and population profile) and 28 sub-criteria. First, Evidential Reasoning (ER) was used to solve the model, then, the processes and results were compared with the Analytical Hierarchy Process (AHP). It was established that using ER or AHP led to the same solutions. However, the scores between the alternatives were significantly different; which impacted the stakeholders‟ decision-making. As the processes differ according to the model selected, ER or AHP, it is relevant to establish the practical and managerial implications for selecting one model or the other and providing evidence of which models best fit this specific environment. To achieve an optimum operational decision it is argued, in this study, that the most transparent and robust framework is achieved by merging ER process with the pair-wise comparison, an element of AHP. This paper makes a defined contribution by developing and examining the use of MCDA models, to rationalise new healthcare infrastructure location, with the proposed model to be used for future decision. Moreover, very few studies comparing different MCDA techniques were found, this study results enable practitioners to consider even further the modelling characteristics to ensure the development of a reliable framework, even if this means applying a hybrid approach