A document by Danish Ali Ahmed. Click on the document to view its contents.

Morphological identification of cnidarian species can be difficult throughout all life stages due to the lack of distinct morphological characters. Moreover, in some cnidarian taxa genetic markers are not fully informative, and in these cases combinations of different markers or additional morphological verifications may be required. Proteomic fingerprinting based on MALDI-TOF mass spectra was previously shown to provide reliable species identification in different metazoans including some cnidarian taxa. For the first time, we tested the method across four cnidarian classes (Staurozoa, Scyphozoa, Anthozoa, Hydrozoa) and included different scyphozoan life-history stages (polyp, ephyra, medusa) into our dataset. Our results revealed reliable species identification based on MALDI-TOF mass spectra across all taxa with species-specific clusters for all 23 analyzed species. In addition, proteomic fingerprinting was successful for distinguishing developmental stages, still by retaining a species specific signal. Furthermore, we identified the impact of different salinities in different regions (North Sea and Baltic Sea) on proteomic fingerprints to be negligible. In conclusion, the effects of environmental factors and developmental stages on proteomic fingerprints seem to be low in cnidarians. This would allow using reference libraries built up entirely of adult or cultured cnidarian specimens for the identification of their juvenile stages or specimens from different geographic regions in future biodiversity assessment studies.

RATIONALE: Sample preparation is one of the most crucial steps for MALDI mass spectrometry imaging (MALDI-MSI). The scientists beginning their adventure with this technique may be overwhelmed by the variety of matrices, solvents, concentrations, the ways of their applications, and the lack of widely available knowledge about the influence of these parameters on the results. Here we would like to present our experiences with detailed aspects of matrices deposition, hopefully helpful for the scientific community. METHODS: In our article, we have tested several MALDI matrices applied by the SunCollect® system: wet-interface matrix deposition in the context of lipids analysis. Among them: 2,5-dihydroxybenzoic acid (DHB), norharmane, N-(1-naphthyl) ethylenediamine dihydrochloride (NEDC), 9-aminoacridine (9AA). We have optimized the number of matrix layers and nozzle settings in terms of spectra intensity and the overall quality of obtained ion maps. RESULTS: Our research presents the influence of the number of matrix layers and nozzle settings on the results and allows for choosing the optimal parameters for the analyses. In positive ionization mode, DHB matrix could be chosen as the first selection. In the negative ionization mode, DAN matrix produces higher peak intensity in a lower mass range and seems to provide more information than 9AA. We recommended NEDC for particular tasks such as glucose analysis. Comparably to remaining matrices, norharmane significantly changes received ion maps. CONCLUSIONS: Dealing with such a great amount of data allows us to notice an interesting conclusion: the obtained ion picture for a particular ion could differ dramatically with changing the matrix, the solvent composition, or even the number of matrix layers. This must be considered when interpreting the result and forces us to compare the results obtained with different matrices with extreme caution.

Rational: Organisms that grow a hard carbonate shell or skeleton, such as foraminifera, corals or molluscs, incorporate trace elements into their shell during growth that absorbs the environmental change and biological activity they experienced. These geochemical signals locked within the carbonate are archives used in proxy reconstructions to study past environments and climates, to decipher taxonomy of cryptic species and to resolve evolutionary responses to climatic changes. Methods: Here we use a laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) as a time resolved acquisition to quantify the elemental composition of carbonate shells. We present the LABLASTER (Laser Ablation BLASt Through Endpoint in R) package, which imports a single time resolved LA-ICP-MS analysis, then detects when the laser has ablated through the carbonate as a function of change in signal over time, and outputs key summary statistics. We provide two worked examples within the package: a planktic foraminifera and a tropical coral. Results: We present the first R package that improves signal: noise ratios in data reduction workflows by automating the detection of when the laser has ablated through a sample using a smoothed time-series and subsequent removal of off-target data points. The functions are flexible and adjust dynamically to enhance the signal: noise ratio of the desired geochemical target. Visualisation tools for manual validation are also included. Conclusions: LABLASTER increases transparency and repeatability by algorithmically identifying when the laser has either ablated fully through a sample or across a mineral boundary and is thus no longer documenting a geochemical signal associated with the desired sample. LABLASTER’s focus on better data targeting means more accurate extraction of biological and geochemical signals.

Isochromanone is the core structure of many bioactive compounds. Direct oxidation of isochromans is one of leading methods for the construction of isochromanones, while most established processes remain suffering from the use of environmental unfriendly metal oxidants, harsh reaction conditions, and the difficulty in catalyst recycling and production separation. Herein, we report a convenient, cost-effective, and green method for the synthesis of high-value added isochromanones via isochroman oxidations with O2 by a novel heterogeneous vanadium cluster catalyst (Cat.1) under mild conditions. This reaction protocol demonstrates high catalytic activity with good catalyst recyclability and reusability for a wide scope of substrates.

Objective: To assess prevalence of late ANC initiation and its associated factors among pregnant women attending in Hawassa Public Health Facilities, South Ethiopia, 2019. Method and materials: Cross-sectional study was conducted from June 15 to August 15 /2019 among 392 pregnant women’s who visited Hawassa city’s public health facilities, Southern Ethiopia for 1 st ANC service. Pregnant mothers were enrolled using systematic technique and data was collected using semi-structured questionnaires. Epi-data version 3.1 used for data entry and SPSS version 24 for data analysis was used. Variables at p-value <0.25 on binary model was taken into multivariable logistic regression and finally significance was declared at a P-value 0f < 0.05. Results: The prevalence of late ANC visit was 57.7% (95% CI=52.74-62.57%). Maternal age group, 31-35 years (AOR=4.93, 95% CI=1.70-14.27), Husband with no formal education (AOR=2.88,95% CI=1.17-7.314), no previous ANC (AOR=2.03, 95% CI=1.20-3.43), no history of obstetric complications (AOR=4.05, 95% CI=2.06-7.96), Unplanned pregnancy (AOR=2.40,95%CI=1.23-4.68), and no partner support (AOR=2.47,95%CI=1.16-5.26) were significantly associated with increased odds of late ANC initiation. However, Maternal decision making for service (AOR=0.40, 95%CI=0.18-0.87) were significantly associated with decreased odds of late ANC initiation. Conclusion and recommendation: late ANC initiation was high in the study area. Maternal age, husband level of education, previous ANC and obstetric complications, type of pregnancy, maternal decision making, and partner support were significantly associated with late ANC initiation. The City’s health offices need to provide education about danger sign of pregnancy and its complication, create awareness about the importance of early ANC initiation and its recommended time.

Background: Reproductive risk factors are associated with increased risk of cardiovascular disease (CVD) in women. However, the combined effects of the composite reproductive risk factors on CVD are unknown. This study was performed to construct a reproductive risk score (RRS) to measure reproductive status, examine the association between RRS and CVD, and explore the modification effect of healthy lifestyle on the association in women in the UK Biobank cohort. Methods: The RRS was constructed in 74 141 female participants with data about the items derived for the RRS in the UK Biobank. The RRS was derived from 17 baseline variables, all of which indicated women’s reproductive health status. We defined four categories of RRS status: low-risk group (score 0–1); low-intermediate group (score 2–3); high-intermediate group (score 4–5); and high-risk group (score 6–13). We also constructed a healthy lifestyle score (HLS) with five related factors, and categorized into unhealthy lifestyle group (score: 0–1), intermediate lifestyle group (score: 2–3) and healthy lifestyle group (score: 4–5). Findings: Each point increase in the RRS was associated with a 22% higher risk of CVD (adjusted hazard ratio (aHR): 1.22; 95% confidence interval (CI): 1.16 to 1.28), 23% higher risk of IHD (1.23; 1.17 to 1.31) and 19% higher risk of stroke (1.19; 1.07 to 1.32). The percentage population-attribution risks (PAR%) were 16% (95% CI: 8 to 24) for CVD, 15% (95% CI: 6 to 24) for IHD and 18% (95% CI: 1 to 33) for stroke. A healthy lifestyle significantly attenuated RRS associations with the incidence of CVD and IHD. The attributable proportions due to additive interaction ( P < 0.001) between RRS and HLS were 0.14 (95% CI: 0.07 to 0.22) for CVD and 0.15 (95% CI: 0.09 to 0.23) for IHD, respectively. Interpretation: High RRS was associated with increased risks of CVD, IHD and stroke in female participants in the UK Biobank. The early-stage identification of women with reproductive risk using synthesised indicators and appropriate healthy lifestyle interventions could be useful for the prevention of early CVD and the extension of healthy active life expectancy. Funding: This study was supported by grants from the National Key R&D Program of China (2020YFC2003401) and the High-performance Computing Platform of Peking University. The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report or the decision to submit the article for publication.

In this paper, we studies studies the mean-square consensus problem for discrete-time heterogeneous multi-agent systems, where the state information is received with varying dropout uncertainty, which leads to heterogeneous observations. Different from previous consensus studies do not consider the effects of measurement packet dropout, the main challenge addressed in this paper is the design of the state estimator and the controller for each agent with different dynamics subject to multiplicative noise. First, the optimal estimator is designed based on the measurement value to estimate the agent's state, and a distributed dynamic output feedback control protocol is presented based on the given estimator. Second, applying the distributed feedforward control method and constructing the stochastic Lyapunov-Krasovskii functional, the sufficient solvability conditions for achieving mean-square consensus in heterogeneous multi-agent systems is derived for the first time. Moreover, the stability of the error covariance matrices related to the optimal estimator is also studied. Finally, the effectiveness of the proposed scheme is verified via a numerical example.

It is found that there are two piecewise functions satisfy the conditions in the impulsive fractional partial differential system (IFrPDS), which deduce that the three different integral solutions of the IFrPDS given in the cited papers are inappropriate. Next, by applying two limit properties of the IFrPDS and the properties of piecewise function, the new formula of solution of the IFrPDS is discovered that is the integral equation with an arbitrary continuously differentiable function of t on [0 ,c] to reveal the non-uniqueness of the IFrPDE’s solution. Finally, an example is provided to expound the computation of the solution of the IFrPDS.

Human mas-related genes such as MRGPRD are members of the seven transmembrane spanning G protein coupled receptor super family implicated in the sensation and transmission of noxious stimuli such as pain and itch, hence intervening with these may prove useful in the management of unmet patient need. To date there have been few reports of the generation of inhibitors of these receptors. To provide new tools to aid the effort in discovering new agonists and antagonists here we describe the use of a label-free assay to study the pharmacology of MRGPRD and compare it to other more traditional methods such as intracellular calcium release.

Aim: The purpose of this study was to optimize the dosing schedule of recombinant human erythropoietin (rhEPO) for perioperative autologous blood donation in patients undergoing total knee arthroplasty (TKA). Method: TKA patients receiving different dosing schedules of rhEPO were randomly divided into three groups. Group A patients were given 10,000 IU of subcutaneous rhEPO (1 ml) daily from preoperative day 5 to postoperative day 3 (9 doses); Group B patients were given subcutaneous normal saline daily from preoperative day 5 to day 3 and then subcutaneous rhEPO daily until postoperative day 3 (6 doses in total); Group C patients were given subcutaneous normal saline daily from preoperative day 5 to the day before surgery and then subcutaneous rhEPO daily from the surgery day to postoperative day 3 (4 doses). Results: A total of 180 TKA patients were included. On postoperative day 1 and 3, group A showed significantly higher Hb levels than group B and group C. The calculated blood loss was significantly greater in groups B and C than in group A on the day after surgery. Regarding total blood loss, groups B and C lost significantly more blood than group A. No case of allogeneic transfusion occurred during the trial in any of the three groups. Conclusions: A small dose of daily rhEPO from preoperative day 5 to postoperative day 3 could significantly increase perioperative autologous blood donation efficacy and slow the decline in postoperative Hb levels in TKA patients without causing extra complications.

The huge amount of bank operations that occur every day makes it extremely hard for financial institutions to spot malicious money laundering related operations. Although some predefined heuristics are used they aren't restrictive enough, still leaving to much work for human analyzers. This motivates the need for intelligent systems that can help financial institutions fight money laundering in a diversity of ways, such as: intelligent filtering of bank operations, intelligent analysis of suspicious operations, learning of new detection and analysis rules. In this paper, we present a multiagent based approach to deal with the problem of money laundering by defining a multiagent system designed to help financial institutions in this task, helping them to deal with two main problems: volume and rule improvement. We define the agent architecture , and characterize the different types of agents, considering the distinct roles they play in the process.

The estimation and monitoring of SpO2 are crucial for assessing lung function and treating chronic pulmonary diseases. The COVID-19 pandemic has highlighted the importance of early detection of changes in SpO2, particularly in asymptomatic patients with clinical deterioration. However, conventional SpO2 measurement methods rely on contact-based sensing, presenting the risk of cross-contamination and complications in patients with impaired limb perfusion. Additionally, pulse oximeters may not be available in marginalized communities and undeveloped countries.

Purpose: Mental health problems affect an estimated 700 million people worldwide, and the prescription of psychotropic drugs is increasing globally. The World Health Organization has called for adequate surveillance of psychotropic drug prescriptions. This study aims to characterize and find trends in the prescription of psychotropics in a Latin American Hospital. Methods: The study analyzed the dispensation of psychotropic prescriptions to outpatients at three pharmacies in the central headquarters of Hospital Clínica Bíblica in San José, Costa Rica, from 2017 to 2021. Psychotropic drugs were classified by ATC groups, and the amount of each medication dispensed was standardized using the defined daily dose per 10000 population per day metric. The prescriptions were categorized according to medical specialty. Results: A total of 5793 psychotropic prescriptions were recorded. The average age of the patients was 58 years. The total consumption of psychotropics decreased by 33.94% from 2017 to 2021, with the most significant decline until 2020. However, there was an increase in consumption in 2021. The most commonly used drugs were clonazepam, bromazepam, and alprazolam. Alprazolam was the only drug that showed an increase in consumption. Anxiolytics were the most commonly prescribed group of drugs. General medicine and psychiatry were the primary specialties that prescribed psychotropics. Conclusion: the consumption of psychotropic drugs decreased from 2017 to 2020 but increased in 2021, with alprazolam being the only drug that showed an increase in consumption throughout the entire period. The elderly population was found to be the group that consumed the most psychotropics.

Listening effort can be defined as a measure of cognitive resources used by listeners to perform a listening task. Several methods have been proposed to assess listening effort, but the reliability of these methods has not yet been thoroughly established, which is necessary before using them in research or clinical settings. This study included 32 participants who performed speech-in-noise tasks in two sessions (separated approx. 1 week apart) by listening to Sentences and Word lists presented at different signal-to-noise ratios (-9, -6, -3, and 0 dB). We assessed the test-retest reliability of the self-reported measure of listening effort and frontal midline theta (Fmθ) power, which has been proposed as a neural correlate of listening effort. The reliability of the percentage of correct words was also examined. Relative and absolute reliability was evaluated using intraclass correlation coefficients (ICC) and Bland-Altman analysis, respectively. The standard error of measurement (SEM) and the smallest detectable change (SDC) were also assessed. Overall, the reliability analysis revealed an acceptable between-session variability for the correct words and effort rating. However, Fmθ power showed high variability, which brings into question its use as a reliable correlate of listening effort.

Auditory processing and the complexity of neural activity can both indicate residual conscious-ness levels and differentiate between states of arousal. However, how measures of neural signal diversity, or complexity, manifest in evoked activity, and, more generally, how the electrophys-iological characteristics of auditory responses change in states of reduced consciousness, re-main under-explored. Here, we tested the hypothesis that measures of neural complexity and the spectral slope would discriminate stages of sleep not only in spontaneous EEG, but also in auditory-evoked responses. High-density EEG was recorded in 21 participants to determine the spatial relationship between these measures, and between spontaneous and auditory-evoked signals. Results showed that the complexity and the spectral slope in the 2-20 Hz range dis-criminated between sleep stages and had a high correlation in sleep. In wakefulness, complexity was strongly correlated to the 20-40 Hz spectral slope. Auditory stimulation resulted in reduced complexity in sleep compared to spontaneous activity and modulated the spectral slope in wake-fulness. These findings demonstrate the persistence of electrophysiological markers of arousal during both spontaneous and evoked EEG activity and have direct applications to studies using auditory stimulation to probe neural functions in states of reduced consciousness.

This paper proposes a recurrent neural network (RNN) based model to segment and classify multiple combined multiple power quality disturbances (PQDs) from the PQD voltage signal. A modified bi-directional long short-term memory (BI-LSTM) model with two different types of attention mechanism is developed. Firstly, an attention gate is added to the basic LSTM cell to reduce the training time and focus the memory on important PQD signal part. Secondly, attention layer is added to the BI-LSTM to obtain the more important part of the voltage signal by assigning weightage to the output of the BI-LSTM model. Finally a SoftMax classifier is applied to classify the combined PQD signal in 96 different combinations. The performance of proposed BI-LSTM model with attention gate and attention layer mechanism is compared with the performance of baseline models based on recurrent neural network (RNN) and convolution neural network (CNN). With this model, the PQD signal is easily segmented from the voltage signal which makes the process of PQD classification more accurate with less computation complexity and in less time.

Large penetration of renewable energy sources into the power grid has increased the complexity of power system operation and greatly reduced the ability of the system to withstand large disturbances. The frequent occurrence of voltage instability problems in the power grid has brought new challenges to the assessment of transient stability analysis of the power system. To achieve fast and accurate assessment of transient voltages, a transfer learning-based transient voltage stability assessment with small samples is proposed, introducing a domain transfer learning approach, embedding a cooperative attention mechanism in the residual network during the feature extraction stage to capture long-range correlations between features, and using adversarial approaches to reduce the differences between samples from different data sets, using the source domain to guide the target domain for network training to improve model's evaluation capability when the number of samples is insufficient, enhance the generalisation performance of the network, and effectively improve the performance of real-time power system transient voltage stability evaluation in the absence of sufficient historical data. Testing on an improved New England 39-node system validates the superiority of this method in transient voltage stability assessment and provides a new approach to practical field transient voltage stability assessment.

Small-scale horizontal axis wind-turbines (SHAWTs) are acquiring relevance within the regulatory policies of the wind sector aiming at net-zero-emissions, while reducing visual and environmental impact by means of distributed grids. SHAWTs operate transitionally, at Reynolds numbers that fall between 10^5 < Re < 5·10^5. Furthermore, environmental turbulence and roughness affect the energetic outcome of the turbines. In this study, the combined effect of turbulence and roughness is analysed via wind tunnel experiments upon a transitionally-operating NACA0021 airfoil. The combined effects cause a negative synergy, inducing higher drops in lift and efficiency values than when considering the perturbing agents individually. Besides, such losses are Reynolds-dependent, with higher numbers increasing the difference between clean and real configurations, reaching efficiency decrements above 60% in the worst-case scenario. Thus, these experimental measurements are employed for obtaining the power curves and estimating the annual energy production (AEP) of a 7.8 kW-rated SHAWT design by means of a BEM code. The simulations show a worst-case scenario in which the AEP reduces above 70% when compared to the baseline configuration, with such a loss getting attenuated when a pitch-regulated control is assumed. These results highlight the relevance of performing tests that consider the joint effect of turbulence and roughness.

Our previous study has shown that ferromagnetic gadolinium silicide (Gd5Si4) nanoparticles (NP) could be potentially efficient T2 CA for MRI with significantly reduced echo time (TE) compared to Superparamagnetic Iron Oxide Nanoparticles (SPION) [1]. T2 CA are defined by their relaxivity, r2, which is dependent on both the saturation magnetization (Ms) and size of the NPs [1,2,4]. In this study, effect of Gd5Si4 NPs of varying sizes and concentrations are investigated on T1, T2 and T2* (effective/observed T2) relaxations times. Gd5Si4 NPs categorized into three fractions (named S1, S2 and S3) based on average sizes of 586 nm, 287 nm and 135 nm respectively as analyzed from SEM images (Fig. 1). XRD analysis on the combined samples shows that Gd5Si4 is the major phase while GdSi and Gd5Si3 are present as the minor phases in all fractions (Fig. 1). Magnetic properties measured in VSM reveal that the Curie temperature (Tc) decreases for Gd5Si4 phase from 312 K for S1 to 304 K for S2 and is undetectable in S3. The M-H curves at 300 K exhibits ferromagnetic behavior descending to paramagnetic as we move from S1 to S3 fraction (Fig. 1). MR data were acquired on the 21.1 T (900 MHz) magnet. The results shown in Table 1 indicate that higher concentrations of NPs shorten the T2 and T2* relaxation times and the contrast disappears rapidly at higher dilutions. The S2 fraction at 1/20 dilution shows notably shortened T1 and T2 relaxation times compared to the other two fractions. Although S1 has higher Gd5Si4 phase volume fraction and larger average particle size compared to S2, further investigation is needed inorder to establish the reason for shortened relaxation times compared to the S1 fraction. Acknowledgements Work at the Ames Lab was supported by DOE (contract No. DE-AC02-07CH11358). Work at VCU was partially funded by NSF, Award No.: 1610967. Work performed at the NHMFL is supported by the State of Florida and the NSF (agreement No. DMR-1157490).This paper was presented at the ICM 2018, San Francisco.

A document by Jeff Lee. Click on the document to view its contents.

Electro explosive devices (EEDs) are used in both military and civilian applications to initiate explosives. Currently, the wireless solutions used for initiating EEDs commonly use star network topology. As the control distance in the star topology increases, so does the power requirement and hence the weight of the batteries. In Additionally, safety issues may arise when initiating EEDs over short distances when low-power transceivers are used. In this study, a microcontroller-based mobile system that uses mesh network topology to initiate EEDs was proposed. Within the scope of this study, a system consists of an initiation control unit, remote ignition units, a mobile device layer, and a charge unit have been developed. EED initiation delays in the proposed system can be programmed using a mobile device. Thus, the expensive and extensive programming devices used in conventional initiating systems are no longer required for wireless EED initiating systems. In the developed system, the average communication distances of the remote initiating units were 251, 154, and 104 m in outdoor, urban, and indoor environments, respectively. Unlike conventional commercial wireless initiating systems that use star network topology, a system that prefers the mesh network topology can successfully initiate detonators from 1882 meters outdoors, 1170 meters in urban areas, and 811 meters indoors. Technical capabilities of an EED have been added to an electric detonator by means of using the developed mobile initiation device, and the initiation delay could be configured over mobile network.

A document by Zhiwen Niu. Click on the document to view its contents.

Background: m6A modification plays an important role in various biological processes and can regulate the function of non-coding RNA. Our research group found the m6A level of lncRNA TUG1 was reduced in HK-2 cells cultured with high glucose. Here we study the impact of the important component of m6A-METTL3 on TUG1 in diabetic nephropathy. Objective: Explore the m6A modification mechanism of lncRNA TUG1 and whether METTL3 can promote PGC-1α transcription, alleviate mitochrondrial dysfunction and diabetic renal injury. Methods: Test the m6A modification level of the total RNA and lncRNA TUG1 in HK-2 cells and db/db mice.Detect whether lncRNA TUG1 can combine METTL3 and IGF2BP2 by RIP-PCR. Test the mitochondrial function HK-2 cells and db/db mice. Use transmission electron microscope to observe the morphology of mitochondria in HK-2 cells and db/db mice. Results: RIP-PCR showed that lncRNA TUG1 could bind to METTL3, and IGF2BP2 could recognize the m6A-modified lncRNA TUG1. IGF2BP2 improved the stability of lncRNA TUG1. High glucose and transfection of siTUG1 in HK-2 cells inhibited PGC-1α pathway, and aggravated mitochondrial dysfunction and morphological damages, while overexpression of METTL3 in HK-2 cells and injection of AAV-METTL3 in db/db mice partially rescued the negative effect. Conclusion: RNA m6A methylation/demethylation imbalance may be mainly regulated by METTL3 in HK-2 cells, and involved in the occurrence and development of diabetic nephropathy. METTL3 can promote the expression of TUG1 through m6A modification in a IGF2BP2-dependent manner in HK-2 cells, and regulate the PGC-1α pathway to alleviate mitochrondrial dysfunction of diabetic nephropat