This paper introduces a new design for a H ∞ filter for nonlinear singular systems with bounded disturbance in the time domain, the frequency domain based on both time and frequency domain.In addition, we present results comparison between three filter design methods. The main objective of such a design is the estimation of the state vector. The proposed filter design is verified when using coupled multimodel architecture. In this note, we propose to adopt the Lyapunov–Krasovskii theory to ensure the filter stability by using a Lyapunov functional added to a H ∞ criterion to minimize the disturbance effect.Furthermore, polynomial approach using MFD tools is employed to describe the filter dynamic in the frequency domain. A numerical example is given to demonstrate the effectiveness of the proposed design.

Objective: To understand the extent to which adolescent awareness of and attitudes about anaemia and anaemia prevention can be changed by nutrition messages received at school. Design: Mixed-methods pre–post intervention study Setting: Three Government schools in Bagalkot, Belagavi and Raichur districts of Karnataka, India Population or Sample: Students of grade six and seven and teachers involved in implementing the intervention. Methods: An education intervention was co-developed by school teachers and nutrition experts using locally adapted resource materials that consisted of lectures, role play and practical demonstrations. Seven half-hour educational sessions were delivered by school teachers over seven weeks to 455 students. Pre- and post-intervention tests measured changes in adolescents’ knowledge about anaemia. In-depth interviews with teachers and focus groups with students explored reactions to the intervention. Main outcome measures: Knowledge score related to anaemia Results: The percentage of children with correct scores increased by 7.3 - 49.0 percentage points for the tested questions after implementation of the intervention. The mean knowledge score increased by 3.67±0.17(p<0.01). During interviews, teachers and students highlighted high acceptance of the intervention and materials, an increase in awareness, a positive attitude towards changing behaviour around diet, an increase in the demand for iron folic acid supplements and improved sharing of messages learned with peers and families. Challenges expressed included need for further training, time limitations and hesitancy in teaching about menstruation and pregnancy. Conclusions: Educational interventions carried out for adolescents by teachers in schools are effective in improving awareness and attitude related to anaemia.

Background: Vaccination is a proven method of managing the COVID-19 pandemic and it is essential to prevent negative consequences in pregnant, lactating, and reproductive-age populations. The study aims to identify the rates of COVID-19 vaccine acceptance, the reasons for receiving and not receiving the vaccine, and the associated factors among pregnant, lactating, and non-pregnant women of reproductive age. Methods: This cross-sectional and analytical study was conducted online in Turkey, at the end of the fourth wave of the COVID-19 pandemic, between February-May 2022. A total of 658 participated in the study. The Question Form and the Fear of COVID-19 Scale were used to collect data. Results: Vaccine acceptance rates were 91.7% in non-pregnant women of reproductive age, 77% in lactating women, and 59% in pregnant women (p<0.05). The highest rate of vaccine hesitancy was observed in pregnant women (31.3%), and the vaccine rejection rate was the highest in lactating women (10.2%). For pregnant women (55.5%) and non-pregnant women of reproductive age (56.4%), the primary reason for the acceptance of the vaccine had no other choice but to be protected against the disease, while for lactating women (50.6%), the primary reason for receiving the vaccine was protecting the baby. Conclusion: Lack of knowledge about and confidence in the COVID-19 vaccine is still one of the barriers to vaccine acceptance today. Health care providers (HCPs) should provide effective counseling to pregnant, lactating, and non-pregnant reproductive-aged women based on current information and guidelines.

This investigation proposes a dynamic event-triggered-based anti-disturbance control technique for the uncertain linear parameter varying (LPV) systems subject to multiple disturbances. The disturbances are comprised of two parts including the unavailable modeled disturbances and the available unmodeled disturbances. First, an observer is constructed to capture the unavailable modeled disturbances. Then, a dynamic event-triggered-based feedback controller is proposed. Further, under the developed event-triggered controller, sufficient conditions are presented for the uncertain LPV systems to achieve the multiple disturbances suppression and communication transmission resources saving. In the end, the reasonability of the raised dynamic event-triggered based anti-disturbance control scheme is verified by an example of a turbofan.

Mapping fluvial hydromorphology is an important part of defining river habitat. Mapping via field sampling or hydraulic modelling is however time consuming, and mapping hydromorphology directly from remote sensing data may offer an efficient solution. Here we present a system for automated classification of fluvial hydromorphology based on a deep learning classification scheme applied to aerial orthophotos. Using selected rivers in Norway, we show how surface flow patterns (smooth or rippled surfaces versus standing waves) can be classified in imagery using a trained convolutional neural network. We show how integration of these classified surface flow patterns with information on channel gradient, obtained from airborne topographic LiDAR data, can be used to compartmentalize the rivers into hydromorphological units that represent the dominant flow features. Automated classifications were consistent with those produced manually. They were found to be discharge-dependent, showing the temporally dynamic aspect of hydromorphology. The proposed system is quick, flexible, generalizable, and free from researcher-subjectivity. The deep learning approach used here can be customized to provide more detailed information on flow features, such as delineating between standing waves and advective diffusion of air bubbles/foam, to provide a more refined classification of surface flow patterns, and the classification approach can be further advanced by inclusion of additional remote sensing methods that provide further information on hydromorphological features.

A Ka-band low noise amplifier (LNA) is presented that improves the traditional source-degeneration LNA by utilizing broadband transformer matching and gate-drain feedback technology. The proposed LNA achieves an ultra-wideband LNA while maintaining the advantages of high integration and low power consumption of the traditional source-degeneration LNA. In addition, cascade technology is adopted to further improve peak gain. The proposed LNA is implemented in 55nm CMOS process. The simulated results show that the LNA achieves stable gain response in the 21.7-36.5 GHz frequency band, with a peak power gain of 20.8 dB. The minimum noise coefficient is 4.4 dB, and the DC power consumption is 15 mW. The LNA achieves a compact chip area of 0.33 mm 2.

Background Cyclin D has been shown to play an essential role in acute lymphoblastic leukemia (ALL) initiation and progression, providing rationale for targeting the CDK4/6-cyclin D complex that regulates cell cycle progression. Procedure The Children’s Oncology Group AINV18P1 phase 1 trial evaluated the CDK4/6 inhibitor, palbociclib, in combination with standard four-drug reinduction chemotherapy in children and young adults with relapsed/refractory B- and T-cell lymphoblastic leukemia (ALL) and lymphoma. Palbociclib (50 mg/m 2/dose) was administered orally once daily for 21 consecutive days, first as a single agent (days 1-3) and subsequently combined with reinduction chemotherapy. This two-part study was designed to determine the maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D) followed by an expansion pharmacokinetic (PK) cohort. Results Twelve heavily pretreated patients enrolled, all of whom were evaluable for toxicity. One dose-limiting hematologic toxicity (DLT) occurred at the starting dose of 50 mg/m 2/dose orally for 21 days. No additional DLTs were observed in the dose determination or PK expansion cohorts and overall rates of grade 3/4 non-hematologic toxicities were comparable to those observed with the chemotherapy platform alone. Five complete responses were observed, two among four patients with T-ALL and three among seven patients with B-ALL. Pharmacokinetic studies showed similar profiles with both liquid and capsule formulations of palbociclib. Conclusions Palbociclib in combination with reinduction chemotherapy was well tolerated with a RP2D of 50 mg/m 2/day for 21 days. Complete responses were observed among heavily pretreated patients.

A coupled inductor based on dual switches buck-boost converter is proposed in the article, which can be used in renewable energy applications. Wide conversion ratio can be realized by regulating turns ratio of the coupled inductor and the duty cycle. The topology has a quadratic- like voltage gain, and the low voltage stress and current stress. Combing the passive clamping circuit to recover leakage energy, the voltage spikes of power switches are suppressed, improving the efficiency. Moreover, it has the merits of continuous input current and common ground. To demonstrate the superior performances of the presented converter, the principle of operation and steady-state analysis are presented in detail. At last, a 100 W experimental prototype was designed to verify the correctness of the theoretical analysis, with a maximum efficiency of 95.7% in step-up mode and 96.8 % in step-down mode.

Severe fetal anaemia resulting from a widely metastatic antenatal choriocarcinoma

This paper proposes a new precharging scheme to reduce the power consumption in dynamic comparator. It basically allows the comparator to perform evaluation after precharging the output nodes to a weaker potential rather than full V DD , which eventually helps in reducing the power consumption of the comparator significantly. Corresponding proposed design also improves the input offset voltage of the comparator. The proposed comparator has been realized in cadence virtuoso environment using the GPDK 45nm CMOS process and results have been extracted using SPECTRE simulator. Proposed comparator achieves an input offset voltage of 0.5 mV, and it consumes an average power of 367 nW while operating at a maximum frequency of 2.5 GHz. Comparison of these results with referred work indicates the that proposed comparator design archives 4.1× better energy efficiency in terms of energy per conversion and 20× better input offset voltage.

Objectives In a COVID-19 sero-surveillance cohort study with predominantly healthy and vaccinated individuals, the objectives were (i) to investigate longitudinally the factors associated with the quantitative dynamics of anti-spike IgG antibody levels, (ii) to evaluate whether the antibody levels were associated with protection from SARS-CoV-2 infection and (iii) to assess whether the association was different in the pre-Omicron compared with the Omicron period. Methods The QuantiVac Euroimmun ELISA test was used to quantify anti-S1 IgG levels. The entire study period (16 months), the 11-month pre-Omicron period and the cross-sectional analysis prior to the Omicron surge included 3219, 2310 and 895 reactive serum samples from 949, 919 and 895 study participants, respectively. Mixed-effect linear, mixed-effect time-to-event and logistic regression models were used to achieve the objectives. Results Age and time since infection or vaccination were the only factors associated with a decline of anti-S1 IgG levels. Antibody levels were significantly associated with protection from SARS-CoV-2 infection, and the association was higher for the Omicron than for the Alpha and Delta variants. In a prediction model, it was estimated that >8000 BAU/mL anti-S1 IgG was required to reduce the risk of infection with Omicron variants by 20% to 30% for 90 days. Conclusions Anti-S1 IgG antibody levels are associated with protection from infection. The levels in the pre-Omicron periods were less significant than during the Omicron surge, which in turn required very high levels for protection in a statistical model.

This work proposes a new method for estimating the excess Gibbs energy and activity of liquid alloy based on partial pair distribution function (PPDF). This work utilized the PPDF to calculate the parameters of the MIVM, RSM, Wilson, and NRTL model. This new method offers simplicity, numerical calculation stability, and excellent reproducibility. The work examined the impact of expressing the model parameters as first-order linear functions of the components or as constants on the accuracy of the estimation. When the model parameters were treated as constants, MIVM and RSM provided an average relative deviation (ARD) of activity of less than ±20% for 15 and 10 alloys. When model parameters were expressed as a function of components, QCM showed the best estimation performance, having 9 alloys with an ARD of less than ±20%.

This paper proposes a novel deep learning architecture named as Inverted Funnelized Multilayer Network (IFMN) for detecting intrusions in Internet of Things (IoT) networks. The proposed approach for intrusion detection employs a feature selection model that uses a Hybrid Yellow saddle goatfish algorithm and Particle Swarm Optimization algorithm for Feature Selection (HYFSPSO) to identify the optimal features. The effectiveness of the selected features is evaluated using a decision tree (DT) classification method, ensuring only the most informative features are used in the deep learning architecture for intrusion detection. For analyzing and proving the effectiveness of proposed scheme the current research has used three benchmark datasets i.e. KDD-CUP99, NSL-KDD and UNSW-NB15 datasets. The simulations of the proposed architecture are conducted in MATLAB and evaluated using performance matrices. While comparing the outcomes on 3 datasets results revealed that proposed HYSGPSO-DL based IDS approach is more effective on NSL-KDD and UNSW-NB15 datasets with an accuracy of 99.96% and 99.80%, while as it achieved an accuracy of 99.53% on KDD-CUP99 dataset. Additionally, comparative analysis with existing intrusion detection systems shows that proposed scheme outperforms the state-of-the-art methods.

This paper proposes for the first time the preparation of a series of amino acid ionic liquids (AAILs) via one-step hydrolysis of cheap lactams for the capture of CO2. The structures of the prepared AAILs are confirmed using NMR, FTIR, and ESIMS, and their physical properties are also determined. It is found that these AAILs are reversible CO2 absorbents with very high absorption capacities (0.15 to 0.18 g·g1 at 313.2 K and 1.0 bar), better than almost all task-specific ionic liquids reported in literatures. The absorption mechanism is also elucidated to be a combination of 1:1 and 2:1 stoichiometric reaction of AAILs with CO2 from NMR, FTIR, reaction equilibrium thermodynamical modelling (RETM) and quantum calculations. The AAILs have the advantages of simple synthesis, high yield, and using available cheap raw materials. It is believed that this kind of AAILs have great potentials to be used as efficient CO2 absorbents.

The present study though preliminary in nature but the generated baseline information will be helpful to design conservation planning for the endangered plant species Strychnos potatorum and its associated species as these diversified vegetation patches are connective corridors of flora and fuana. In addition, soil samples were collected from 0-20 cm depth and analyzed physically and chemically. Keywords: Strychnos potatorum , Soil analysis, Associated species, Conservation

This study presents a novel autonomous reconfiguration strategy to achieve full cycle optimal control of the heat exchanger networks. The proposed method aims to select the optimal control structure online to solve the problem of slow time-varying process transition caused by the inevitable fouling accumulation. Specifically, an auxiliary variable is introduced to increase the degree of control freedom, and a flexible control structure is studied to provide appropriate pairings dynamically between variables. Subsequently, the nonparametric Relative Energy Gain Array is considered as the switching mechanism to determine switching instants of control loops. Furthermore, the online optimization of switching regions ensures the optimal control performance. Finally, one typical experiment for the heat exchanger network in crude distillation unit was conducted and the results illustrated the effectiveness of the proposed control method. Compared with the conventional control system, the available service time was extended by nearly 18 months.

The application of heterogeneous catalysts in dimethyl carbonate (DMC) synthesis from methanol is hindered by low activation efficiency of methanol to methoxy intermediates (CH3O*), which is the key intermediate for DMC generation. Herein, a catalyst of alkali metal K anchored on the CuO/ZnO oxide is rationally designed for offering Lewis acid-base pairs as dual active centers to improve the activation efficiency of methanol. Characterizations of CO2-TPD, NH3-TPD, XPS, and DRIFTS revealed that the addition of Lewis base K observably boosted the dissociation of methanol and combined with Lewis acid CuO/ZnO oxide to adsorb the formed CH3O* stably, thus synergistically promoted the transesterification. Finally, the CuO/ZnO-9%K2O catalyst exhibited the optimal catalytic activity, achieving a high yield of 74.4% with an excellent selectivity of 98.9% for DMC at a low temperature of 90 °C. The strategy of constructing Lewis acid-base pairs provides a reference for the design of heterogeneous catalysts.

Bladed mixers are widely used for processing granular materials where significant mechanical energy is required to produce the desired blend. Some mechanical energy is dissipated within the granular medium, generating heat during this process. However, our knowledge of the heat generation mechanisms without external thermal loads is still lacking. This study uses an overhead stirrer to mix granular materials and investigate heat generation by monitoring the temperature changes in the granular bed. Additionally, first-order kinetic equations are used to extrapolate the experimental data to a thermal equilibrium where the heat generation and heat loss rates are equal. Lead, steel, and glass particles are used under various operating conditions. It is observed that metallic particles heat up faster owing to their lower heat capacity. Also, increasing the rotation speed, fill ratio and particle size result in a greater temperature increase. Moreover, flat blades induce more heat generation compared to tilted blades.

There is presently a paucity of mass transfer studies to single nanocatalyst particles with diameters ranging from 1 nm to 100 nm. We have experimentally investigated the flux associated with the electrocatalytic reduction of hexacyanoferrate (III) to hexacyanoferrate (II) on gold nanospheres. We have found that the flux of hexacyanoferrate (III) to the surface is insensitive to particle sizes in the range of 30 nm ≤ dp ≤ 100 nm. For particle sizes of 5 nm ≤ dp ≤ 30 nm, we see the flux increase sharply as the particle size decreases. While qualitatively the same, the measured fluxes are one to three orders of magnitude smaller than that predicted by a diffusion-limited model. Factors in addition to diffusion are evaluated and discussed, including enhanced surface reactivity of nanoparticles, flux concentration due to sphericity, interactions among particles, presence of stabilizing layers on the particle, and advection due to Brownian motion.

Background- Premature births are on a rise. Mechanical ventilation (MV) is required by very low birth weight (VLBW) neonates with respiratory failure. Optimal extubation remains challenging, as approximately 30% of ventilated preterm infants fail extubation. The incidence and risk factors for extubation failure (EF) may vary from country to country. Methods- This prospective observational study was conducted among VLBW neonates to find the EF rate and risk factors. Results- Of the 60 enrolled neonates with a mean gestational age of 30.94±1.55 weeks and mean birth weight of 1198±201 grams, 25 (41.7%) failed extubation. The risk factors associated with EF were shock (0.002), use of vasopressor (0.005), presence of complications (pneumothorax, ventilator-associated pneumonia) (0.032), anemia (0.017), culture-positive sepsis (0.042), duration of MV (0.006), post-extubation FiO2 requirement (<0.001) and post-extubation blood gas parameters- pH (<0.001), PaCO2 (0.001), HCO3 (0.001), SPO2/FiO2 ratio (p<0.001). On multivariate regression, Silverman Anderson (SAS) Score ≥ 5 (OR 5.23; 95% CI 2.3-12; <0.001) and anemia (hemoglobin less than 12 gram/dl) (OR1.71;95%CI 0.96-3.06; 0.028) were significant risk factors. Significantly more babies in the EF group expired (0.002). Also, neonates who failed extubation had an increased length of NICU stay as compared to those who succeeded 27±14 vs 20±12 days (p=0.048). Conclusion- Forty-one percent of VLBW neonates failed extubation. Post extubation SAS of ≥ 5, anemia (hemoglobin less than 12 grams) were independent risk factors for EF. Neonates with EF had poor outcomes with more deaths and prolong NICU stay.

Background: Multiple Breath washout (MBW) represents an important tool to detect early a possible pulmonary exacerbation especially in Cystic Fibrosis (CF) disease. Lung clearance index (LCI) is the most commonly reported multiple breath washout (MBW) index and in the last years was used as management measure for evaluation. Our aim was to analyze clinical utility of LCI index variability in pulmonary exacerbation in CF. Methods: A single-center study was conducted at CF Unit of Bambino Gesù Children’s Hospital among hospitalized > 3 years patients for pulmonary exacerbations and treated with antibiotic intravenous treatment for 14 days. MBW and spirometry were evaluated within 72 hours of admission to hospital and at the end of hospitalization. Descriptive analysis was conducted and correlations between quantitative variables were investigated. Results: Fifty-seven patients (M22/F35) with an average age 18.56 (± 8.54) years were enrolled. LCI 2.5 was significantly reduced at the end of antibiotic treatment in both pediatric and adult populations with an average improvement of -6% in 37/57 patients. 26/57 are stable in LCI values. A significant elevation of +7.30% was found for FEV1%. 4/57 (7.02 %) had a significant deterioration in LCI values at the end of IV antibiotic treatment. A positive good correlation among LCI 2.5 and Scond (rho= +0.615, p=0.000) and LCI 2.5 and Sacin (rho=+0.649, p=0.000) and a negative strong correlation between FEV1% and LCI 2.5 were found in post treatment period. A better increase of LCI 2.5 in < 18 years (-10.27% vs -4.57%) than adult was noticed. Conclusions: LCI may have a role in the routine clinical care of CF patients as a good tool to assess response to intravenous antibiotic therapy.

Childhood interstitial lung disease (chILD) is a heterogeneous group of diffuse lung diseases (DLD) that can be challenging to diagnose. With relative rarity of individual entities, data are limited on disease prevalence, care patterns, and healthcare utilization. The objective of this study was to evaluate chILD prevalence and review diagnostic and clinical care patterns at our center. A single-center, retrospective cohort study was conducted of patients receiving care at the Children’s Hospital of Philadelphia (CHOP) between January 1, 2019, and December 31, 2021. Through query of selected ICD-10 billing codes relevant for chILD/DLD, a total of 306 patients were identified receiving care during this period. Respiratory symptom onset was documented to have developed before two years of age for 40% of cases. The most common diagnostic categories included those with oncologic disease (21.2%), bronchiolitis obliterans (10.1%), and connective tissue disease (9.5%). Genetic testing was performed in 49% of cases, while 36% underwent lung biopsy. Hospitalization at CHOP had occurred for 80.4% of patients, with 45.1% ever hospitalized in an intensive care unit. One-third of children had required chronic supplemental oxygen. Seven (2.3%) patients died during this three-year period. Collectively, these data demonstrate the scope of chILD and extent of health care utilization at a large volume tertiary care center. This approach to cohort identification and EMR-driven data collection in chILD provides new opportunities for cohort analysis and will inform the feasibility of future studies.

Childhood interstitial and diffuse lung disease (chILD) encompasses a broad spectrum of rare disorders. The Children’s Interstitial and Diffuse Lung Disease Research Network (chILDRN) established a prospective registry to advance knowledge regarding etiology, phenotype, natural history, and management of these disorders. This longitudinal, observational, multicenter registry utilizes single-IRB reliance agreements, with participation from 25 chILDRN centers across the U.S. Clinical data are collected and managed using the Research Electronic Data Capture (REDCap) electronic data platform. We report the study design and some elements of the initial Registry enrollment cohort, which includes 683 subjects with a broad range of chILD diagnoses. The most common diagnosis reported was neuroendocrine cell hyperplasia of infancy (NEHI), with 155 (23%) subjects. Components of underlying disease biology were identified by enrolling sites, with cohorts of interstitial fibrosis, immune dysregulation, and airway disease being most commonly reported. Prominent morbidities affecting enrolled children included home supplemental oxygen use (63%) and failure to thrive (46%). This Registry is the largest longitudinal chILD cohort in the U.S. to date, providing a powerful framework for collaborating centers committed to improving the understanding and treatment of these rare disorders.

AIMS The aim of this umbrella review was to identify tools and guidelines available to aid the deprescribing process of potentially inappropriate medications (PIM), evaluate their methods of development and validation, and describe at what level of evidence medications are included in the tools and guidelines. METHODS Searches were conducted on MEDLINE(Ovid), Embase.com, Cochrane CDSR, CINAHL (EBSCO), Web of Science Core Collection, and guideline databases from the date of inception to July 7, 2022. We described and compared the different characteristics and contents of tools and guidelines. RESULTS From 10,606 records screened, 23 systematic reviews and guidelines met the inclusion criteria. We then identified 90 tools (67 explicit, 12 mixed, 11 implicit), and 9 guidelines. The majority were developed for use in older adults (n = 74). Nineteen tools targeted older adults with limited life expectancy (LLE), and 7 targeted children <18 years. The majority (97%) of explicit/mixed tools were validated through Delphi techniques (n = 61). Two tools and eight guidelines provided information on the level of evidence for the included medications, of which less than a quarter were included based on high-quality evidence. CONCLUSION Existing tools are available for a diversity of populations. Discrepancies identified in categorizing medications as appropriate or not can be a result of low quality evidence. Particularly, tools for patients with LLE were developed based on very limited evidence, and research to generate this evidence is highly needed. Our medication lists, along with the level of evidence, could facilitate efforts to strengthen the evidence.