Kalman Filters for Parameter Estimation of Nonstationary Signals

An adaptive Taylor-Kalman filter with PSO tuning for tracking nonstationary signal parameters in a noisy environment with primary focus on time-varying power signals has been presented in this piece of work. In order to deal with the dynamic envelope of the power signal, second-order Taylor expansion has been used such that the Taylor coefficients are updated with the PSO-tuned Taylor-Kalman Filter algorithm. In addition to this, for fast convergence, a self-adaptive particle swarm optimization technique has been used for obtaining the optimal values of model and measurement error covariances of the Kalman filter. The proposed algorithm is linear and therefore has less computational burden, which is easier to be implemented on a hardware platform like DSP processor or FPGA. The proposed PSO-tuned Taylor-Kalman filter exhibits robust tracking capabilities even under changing signal dynamics, immune to critical noise conditions, harmonic contaminations, and also reveals excellent convergence properties

Polycystic ovary syndrome risk: efficacy of self-assessment test

Background: Polycystic ovary syndrome (PCOS) is a growing morbidity in young women globally. This disease has an association with several exogenous factors like irregularity of menses, hirsutism and obesity. Very few standardized self-assessment tools based on easily observable factors are available for use in the Indian population, which can help them to assess their PCOS risk accurately.Methods: Undergraduate women of the age group 18-22 years enrolled in a university campus participated in the survey questionnaire. Nineteen questions with binary answers as “yes” or “no” were used for self-assessment test. Each “yes” was scored as one mark, and each “no” scored as zero, leading to the maximum score of 19. Scores of the women with irregular menses (test group) were compared to those of regular menses (control group). Welch’s corrected t-test was used to calculate the significance at 5% between the groups. The clinical assessment confirmed the presence or absence of PCOS condition.Results: One thousand and fifty-four women participated in the study. The study showed that 262 (24.8%) of young women reported irregular menstrual cycle. The average total score of the control group was 3.07±2.35, whereas that of the women with irregular menses was 5.93±2.86. 21 out of 28 participants, who scored high, were diagnosed with PCOS, on clinical assessment by Rotterdam criteria.Conclusions: The self-assessment test can assess the risk of PCOS. This test has 75% sensitivity and accuracy in predicting the presence of PCOS

Pusat rehabilitasi korban narkoba di Aceh Besar, Tema: Arsitektur Perilaku

xvii+176hlm.;29c

Thermo stable α-amylase conjugated antibodies as probes for immunodetection in ELISA

Thermostable α-amylase from B. licheniformis has been conjugated with high efficiency to goat antibodies against human, mouse, and rabbit immunoglobulins to prepare second-step reagents which can be used in Enzyme Linked Immunosorbent Assays (ELISA). Various conjugation methods, such as one- and two-step glutaraldehyde coupling and cross-linking, using heterobifunctional reagents such as sulfosuccinimidyl-4-(N-maleimidomethyl)-cyclohexane-1-carbonate (sulfo-SMCC) and N-succinimidyl-S-acetylthioacetate (SATA), yielded active α-amylase labeled second antibodies. Such conjugates had molecular sizes ranging between 200-300 kDa. Filter sterilized solutions of conjugates, when stored at 37°C for two weeks, retained 32% of their biological activity and were thermostable even after keeping for 1 h at 90°C

CH Selection via Adaptive Threshold Design Aligned on Network Energy

Energy consumption in Wireless Sensor Networks (WSN) involving multiple sensor nodes is a crucial parameter in many applications like smart healthcare systems, home automation, environmental monitoring, and industrial use. Hence, an energy-efficient cluster-head (CH) selection strategy is imperative in a WSN to improve network performance. So to balance the harsh conditions in the network with fast changes in the energy dynamics, a novel energy-efficient adaptive fuzzy-based CH selection approach is projected. Extensive simulations exploited various real-time scenarios, such as varying the optimal position of the location of the base station and network energy. Additionally, the results showed an improved performance in the throughput (46%) and energy consumption (66%), which demonstrated the robustness and efficacy of the proposed model for the future designs of WSN applications

Investigating the gut microbiota composition of individuals with attention-deficit/hyperactivity disorder and association with symptoms

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Given the growing evidence of gut microbiota being involved in psychiatric (including neurodevelopmental) disorders, we aimed to identify differences in gut microbiota composition between participants with ADHD and controls and to investigate the role of the microbiota in inattention and hyperactivity/impulsivity. Fecal samples were collected from 107 participants (NADHD = 42; Ncontrols = 50; NsubthreholdADHD = 15; range age: 13–29 years). The relative quantification of bacterial taxa was done using 16S ribosomal RNA gene amplicon sequencing. Beta-diversity revealed significant differences in bacterial composition between participants with ADHD and healthy controls, which was also significant for inattention, but showing a trend in case of hyperactivity/impulsivity only. Ten genera showed nominal differences (p < 0.05) between both groups, of which seven genera were tested for their association with ADHD symptom scores (adjusting for age, sex, body mass index, time delay between feces collection and symptoms assessment, medication use, and family relatedness). Our results show that variation of a genus from the Ruminococcaceae family (Ruminococcaceae_UCG_004) is associated (after multiple testing correction) with inattention symptoms and support the potential role of gut microbiota in ADHD pathophysiology.</p

Correction: Investigating the gut microbiota composition of individuals with attention-deficit/hyperactivity disorder and association with symptoms (Microorganisms

The authors wish to make the following correction to this paper [1]: After the publication of the manuscript, the authors recognized a mismatch in the link between the microbiota sequencing data (from ADHD cases and controls) and their descriptive and behavioral data. Thus, the manuscript had to be reanalyzed and rewritten, resulting in different results and conclusion. The main difference is that the case-control comparison resulted in different bacteria differences. Moreover, we did not find an association (only at trend level) between the microbiome relative abundance and inattention score. The corrected results, discussion, and conclusion, can be found below. Due to the changes the abstract, and material and methods section had to be adjusted as well. The changes are provided below. The authors would like to apologize for any inconvenience caused to the readers by these changes. Changes in Abstract The results and conclusion in the abstract changed to: Alpha and Beta-diversity were not different between participants with ADHD and healthy controls. Three genera showed nominal differences (puncorrected < 0.05) between both groups (Prevotella_9, Coprococcus_2 and Intestinibacter) and were further tested for their association with ADHD symptom scores (adjusting for age, sex, body mass index, a time delay between feces collection and symptoms assessment, medication use and family relatedness). Our results show that the variation of a genus from the Lachnospiraceae family (Coprococcus_2) showed a trend of being negatively associated with inattention symptoms. Furthermore, we showed that the relative abundance of four genera was reduced by ADHD medication (puncorrected < 0.05). Overall, our results may support the role of the gut microbiota in the pathophysiology of ADHD. Given the scarcity of studies on the gut microbiota in individuals with ADHD, the current results are an important contribution to this field. More studies are needed into the gut microbiota as part of the pathology of ADHD, especially with a bigger sample size across the lifespan and more detailed information about lifestyle. Changes in Materials and Methods Certain changes had to be applied in the material and methods section. First, for easier maintenance and reproducibility, we used R software instead of SPSS to reanalyze microbiome data. This means that we calculated the alpha-diversity metrics using the R function microbiome::alpha (version 1.6.0) and the composition analysis using “phyloseq” R package version 1.28.0. Second, we used the nonparametric Mann-Whitney U test method in order to identify differences in genera between cases and controls. This was visualized by using a boxplot with a summary table representing the number of zeros using “ggpubr” R package version 0.4.0.999. Third, in the regression analyses, we had to adjust the number of total tests used in FDR to 6 and not 14 tests. Fourth, the new results of the “2.2.9. Correlation Analysis and Multiple Regression with All Selected Genera” are shown in the Supplementary Materials. Changes in Results The data had to be reanalyzed; thus, all the results changed includes all the tables and figures. For easier readability, the whole (corrected) results section is provided below: 3. Results 3.1. Subjects Characteristics The general characteristics of the studied sample are presented in Table 1. Mean age, median BMI, percentage of males, and differences in days between fecal collection and ADHD symptoms assessment (diff_days) were similar among the two groups. As expected, mean inattention and hyperactivity/impulsivity scores were statistically different between the ADHD and control groups. Out of the 41 participants with ADHD, 19 were using medication for ADHD. (Figure and Table Presented)

A New Design of a Terahertz Metamaterial Absorber for Gas Sensing Applications

Metamaterial absorbers are used in the terahertz frequency regime as photo-detectors, as sensing elements, in imaging applications, etc. Narrowband absorbers, on account of their ultra-slender bandwidth within the terahertz frequency spectrum, show a significant shift in the absorption peak when an extrinsic entity relative to the absorber, like refractive index or temperature of the encircling medium, is altered. This property paves the path for the narrowband absorbers to be used as potential sensors to detect any alterations in the encircling medium. In this paper, a novel design of a terahertz metamaterial (MTM) absorber is proposed, which can sense the variations in the refractive index (RI) of the surrounding medium. The effective permeability of the structure is negative, while its permittivity is positive; thus, it is a μ-negative metamaterial. The layout involves a swastika-shaped design made of gold on top of a dielectric gallium arsenide (GaAs) substrate. The proposed absorber achieved a nearly perfect absorption of 99.65% at 2.905 terahertz (THz), resulting in a quality factor (Q-factor) of 145.25. The proposed design has a sensitivity of 2.12 THz/RIU over a range of varied refractive index from n = 1.00 to n = 1.05 with a step size of 0.005, thereby achieving a Figure of Merit (FoM) of 106. Furthermore, the sensor was found to have a polarization-insensitive characteristic. Considering its high sensitivity (S), the proposed sensor was further tested for gas sensing applications of harmful gases. As a case study, the sensor was used to detect chloroform. The proposed work can be the foundation for developing highly sensitive gas sensors