An efficient and directional optical Tamm state assisted plasmonic nanolaser with broad tuning range

In recent years, nanolasers based on plasmonic crystal nanocavity structures have attracted significant interest. However, the performance of such lasers is affected significantly by the coupling of the lasing emission to both reflection and transmission sides of the device and to multiple spatial modes in the far field due to higher-order diffraction from plasmonic crystals as well. In this work, we propose a nanolaser design that overcomes the performance degradation of plasmonic crystal based nanolasers and increases the emission intensity significantly. In the proposed nanolaser structure, a nanometer-thick gain medium has a one-dimensional photonic crystal on one side and a metal nanohole array on the other side. An incident pump pulse through the one-dimensional photonic crystal excites optical Tamm states at the metal-gain medium interface that are amplified by the stimulated emission of the gain medium. We find that the intensity of the extraordinary optical transmission through the metal nanohole array increases significantly due to the excitation of optical Tamm states with wavevector perpendicular to the nanohole array surface. We also find that the subwavelength periodicity in the nanohole array confines the lasing emission to the zero-th order mode only, and hence, makes the far-field pattern highly directional. Moreover, the laser emission wavelength can be tuned over a broad range by changing the thicknesses of the photonic crystal layers, gain medium, and in real-time, by changing the angle of incidence of the pump pulse

Guillain-Barré Syndrome-related campylobacter jejuni in Bangladesh: ganglioside mimicry and cross-reactive antibodies

BACKGROUND: <br/> Campylobacter jejuni is the predominant antecedent infection in Guillain-Barré syndrome (GBS). Molecular mimicry and cross-reactive immune responses to C. jejuni lipo-oligosaccharides (LOS) precipitate the development of GBS, although this mechanism has not been established in patients from developing countries. We determined the carbohydrate mimicry between C. jejuni LOS and gangliosides, and the cross-reactive antibody response in patients with GBS in Bangladesh.<br/> METHODOLOGY:<br/> Sera from 97 GBS patients, and 120 neurological and family controls were tested for antibody reactivity against LOS from C. jejuni isolates from GBS patients in Bangladesh (BD-07, BD-39, BD-10, BD-67 and BD-94) by enzyme-linked immunosorbent assay (ELISA). Cross-reactivity to LOS was determined by ELISA. The LOS outer core structures of C. jejuni strains associated with GBS/MFS were determined by mass spectrometry.<br/> PRINCIPLE FINDINGS:<br/> IgG antibodies to LOS from C. jejuni BD-07, BD-39, BD-10, and BD-67 IgG antibodies were found in serum from 56%, 58%, 14% and 15% of GBS patients respectively, as compared to very low frequency (<3%) in controls (p<0.001). Monoclonal antibodies specific for GM1 and GD1a reacted strongly with LOS from the C. jejuni strains (BD-07 and BD-39). Mass spectrometry analysis confirmed the presence of GM1 and GD1a carbohydrate mimics in the LOS from C. jejuni BD-07 and BD-39. Both BD-10 and BD-67 express the same LOS outer core, which appears to be a novel structure displaying GA2 and GD3 mimicry. Up to 90-100% of serum reactivity to gangliosides in two patients (DK-07 and DK-39) was inhibited by 50 µg/ml of LOS from the autologous C. jejuni isolates. However, patient DK-07 developed an anti-GD1a immune response while patient DK-39 developed an anti-GM1 immune response.<br/> CONCLUSION:<br/> Carbohydrate mimicry between C. jejuni LOS and gangliosides, and cross-reactive serum antibody precipitate the majority of GBS cases in Bangladesh

Хліб: семантика в контексті народного етикету Середнього Полісся

У статті представлено дослідження міфологічних уявлень, пов’язаних з хлібом. Розглянуто особливості функціонування, семантизації цього культурного явища та його номінацію.Статья представляет исследование мифологических представлений, связанных с хлебом. Рассмотрено особенности функционирования, семантизации этого культурного явления и его номинацию.The article presents the study of the mythological presentations, what a connected with bread. The considered particularity of the operation, semantization this cultural phenomena and its nomination

Trends in Diabetic Retinopathy, Visual Acuity, and Treatment Outcomes for Patients Living With Diabetes in a Fundus Photograph-Based Diabetic Retinopathy Screening Program in Bangladesh

IMPORTANCE: Diabetic retinopathy (DR) is the leading cause of low vision among working-age adults. An estimated 6.9 million people in Bangladesh were living with diabetes in 2017, which is projected to increase to more than 10 million people in 2025. Currently, no standardized and/or large-scale DR screening program exists in Bangladesh. OBJECTIVE: To develop a novel fundus photograph–based eye screening model for early detection of DR to prevent vision loss in Bangladeshi individuals with diabetes. DESIGN, SETTING, AND PARTICIPANTS: In this cross-sectional study, 49 264 patients with diabetes underwent opportunistic eye screening at 2 eye hospitals and 1 diabetic hospital in Bangladesh between June 1, 2010, and September 30, 2017. The data set was analyzed from April 8 to December 30, 2018. Technicians were trained to obtain 2-field digital fundus photographs and to grade each according to a standardized DR severity scale. Each patient was counseled and triaged for treatment using defined DR referral criteria. MAIN OUTCOMES AND MEASURES: Primary DR grading outcomes, visual acuity, and treatment outcomes. RESULTS: A total of 49 264 patients (54.3% male; mean [SD] age, 50.8 [12.3] years) underwent DR screening during a 7-year period. The DR prevalence rate across all 3 sites was 33% (95% CI, 33%-33%). Prevalence rates varied by center (Chittagong, 64.6% [95% CI, 64.0%-65.0%]; Dhaka, 39.8% [95% CI, 39.0%-41.0%]; and Feni, 13.0% [95% CI, 13.0%-14.0%]). Across all age groups, male patients were at higher risk of prevalent DR than female patients (odds ratio, 1.99; 95% CI, 1.90-2.07). The prevalence was 3.9% for preproliferative DR, 7.8% for proliferative DR, and 19.2% for maculopathy. Individuals with DR had significantly worse visual acuity than those with no DR (bestcorrected visual acuity, 0.35 vs 0.21 logMAR; P < .001). The rate of moderate visual impairment was 12.2%, and the rate of blindness was 2.5%. Primary treatments included laser photocoagulation (n = 1637), intravitreal injection (n = 1440), and vitrectomy (n = 309). CONCLUSIONS AND RELEVANCE: Screening Bangladeshi individuals known to have diabetes using fundus photography identified large numbers of patients with sight-threatening proliferative DR, maculopathy, and visual impairment or blindness. Expansion of eye screening services in Bangladesh is warranted as part of a national government eye care and diabetes health polic

An intelligent wind turbine with yaw mechanism using machine learning to reduce high-cost sensors quantity

In this paper, with the assistance of some tools and a machine learning model, a smart wind turbine was formed that eliminates some expensive sensors and reduces sensor complexity. Squirrel cage induction generator (SCIG) and six rotor blades make up the proposed design, and depending on the wind's direction, the turbine itself can rotate the rotor hub to produce energy more effectively. Additionally, two stepper motors are coupled to the yaw mechanism with the aid of the rotor hub, and the entire controlling procedure will depend on the direction of the wind. The rotor hub must continuously revolve in the same direction as the wind to maximize wind energy utilization. Additionally, to correctly predict wind degrees, a machine learning model was deployed. Random forest regression was used to train and predict the wind direction. The model is deployed in Raspberry Pi, where the incoming sensor values are being stored. Using the generated data, machine learning model was trained and it can be concluded that the model can potentially replace some of the expensive sensors to reduce cost. The model can be used for similar weather conditions only based on machine learning model and fewer sensors

High genetic merit dairy heifers grazing low quality forage had similar weight gain and urinary nitrogen excretion to those of low genetic merit heifers

Climate variability and increasing drought events have become significant concerns in recent years. However, there is limited published research on body weight (BW) change of dairy heifers with different genetic merit when grazing on drought impacted pastures in southern Australia. Achieving target body weight (BW) is vital for dairy heifers, especially during critical stages like mating and calving. This study aimed to assess dry matter (DM) intake, BW change, urinary nitrogen excretion, and grazing behaviours of high vs. low genetic dairy heifers grazing pasture during a 43-day experimental period in a drought season. Forty-eight Holstein Friesian heifers grazed on ryegrass-dominant pasture and were divided into two groups based on their high and low Balanced Performance Index (HBPI and LBPI, respectively). Each group was further stratified into six plots, with similar BW, resulting in four heifers per replication group. Data from the five measurement days were averaged for individual cows to analyse the dry matter intake, nitrogen intake and nitrogen excretion. The statistical model included the treatment effect of BPI (H and L) and means were analysed using ANOVA. The pasture quality was poor, with metabolizable energy 9.3 MJ/Kg DM and crude protein 5.9% on a DM basis. Nitrogen intake and urinary nitrogen excretion were significantly higher (p  &lt;  0.05) in HBPI compared to the LBPI. However, despite these differences, the study did not find any advantages of having HBPI heifer grazing on low quality forage in terms of BW performance

Učinak formulacijskih parametara na oslobađanje lijeka i svojstva dvoslojnih tableta koje plutaju u želucu

Floating dosage forms of acetylsalicylic acid, used for its antithrombotic effect, were developed to prolong gastric residence time and increase bioavailability. In the two-layer tablet formulation, hydroxypropyl methylcellulose (HPMC) of high viscosity and an effervescent mixture of citric acid and sodium bicarbonate formed the floating layer. The release layer contained the drug, direct tableting agent and different types of matrix-forming polymers such as HPMC of low viscosity, sodium carboxymethylcellulose and chitosan. Tablets were prepared using a direct compression technique. The effect of formulation variables on physicochemical and floating properties and the drug release from tablets were investigated. Floating ability was dependent on the amount of effervescent agent and gel-forming polymer of the floating layer. Drug release was prolonged to 8 hours by changing the type and viscosity of the matrix-forming polymer in the drug-loading layer and all formulations showed a diffusion release mechanism.U radu su opisane plutajuće tablete acetilsalicilne kiseline za antikoagulacijsku upotrebu s produljenim zadržavanjem u želucu i većom bioraspoloživošću. Plutajući dio tih dvoslojnih tableta sadržavao je hidroksipropil metilcelulozu (HPMC) visoke viskoznosti i efervescentnu smjesu limunske kiseline i natrijevog hidrogenkarbonata. Drugi sloj sadržavao je ljekovitu tvar, sredstvo za izravno tabletiranje i različite vrste matriksnog polimera poput HPMC niske viskoznosti, natrij-karboksimetilceluloze i kitozana. Tablete su pripravljene metodom izravne kompresije. Ispitivan je utjecaj formulacijskih varijabli na fizikokemijska i plutajuća svojstva, te oslobađanje ljekovite tvari. Plutajuća svojstva ovise o količini efervescentnih tvari i gelirajućeg polimera u plutajućem sloju. Promjenom vrste i viskoznosti polimera u matriksnom sloju s lijekom produljeno je oslobađanje ljekovite tvari na 8 sati. Iz svih formulacija ljekovita tvar oslobađala se difuzijom

Soybean Canopy Stress Classification Using 3D Point Cloud Data

Automated canopy stress classification for field crops has traditionally relied on single-perspective, two-dimensional (2D) photographs, usually obtained through top-view imaging using unmanned aerial vehicles (UAVs). However, this approach may fail to capture the full extent of plant stress symptoms, which can manifest throughout the canopy. Recent advancements in LiDAR technologies have enabled the acquisition of high-resolution 3D point cloud data for the entire canopy, offering new possibilities for more accurate plant stress identification and rating. This study explores the potential of leveraging 3D point cloud data for improved plant stress assessment. We utilized a dataset of RGB 3D point clouds of 700 soybean plants from a diversity panel exposed to iron deficiency chlorosis (IDC) stress. From this unique set of 700 canopies exhibiting varying levels of IDC, we extracted several representations, including (a) handcrafted IDC symptom-specific features, (b) canopy fingerprints, and (c) latent feature-based features. Subsequently, we trained several classification models to predict plant stress severity using these representations. We exhaustively investigated several stress representations and model combinations for the 3-D data. We also compared the performance of these classification models against similar models that are only trained using the associated top-view 2D RGB image for each plant. Among the feature-model combinations tested, the 3D canopy fingerprint features trained with a support vector machine yielded the best performance, achieving higher classification accuracy than the best-performing model based on 2D data built using convolutional neural networks. Our findings demonstrate the utility of color canopy fingerprinting and underscore the importance of considering 3D data to assess plant stress in agricultural applications.This article is published as Young, Therin J., Shivani Chiranjeevi, Dinakaran Elango, Soumik Sarkar, Asheesh K. Singh, Arti Singh, Baskar Ganapathysubramanian, and Talukder Z. Jubery. "Soybean Canopy Stress Classification Using 3D Point Cloud Data." Agronomy 14, no. 6 (2024): 1181. doi: https://doi.org/10.3390/agronomy14061181. © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)

Multi-Sensor and Multi-temporal High-Throughput Phenotyping for Monitoring and Early Detection of Water-Limiting Stress in Soybean

Soybean production is susceptible to biotic and abiotic stresses, exacerbated by extreme weather events. Water limiting stress, i.e. drought, emerges as a significant risk for soybean production, underscoring the need for advancements in stress monitoring for crop breeding and production. This project combines multi-modal information to identify the most effective and efficient automated methods to investigate drought response. We investigated a set of diverse soybean accessions using multiple sensors in a time series high-throughput phenotyping manner to: (1) develop a pipeline for rapid classification of soybean drought stress symptoms, and (2) investigate methods for early detection of drought stress. We utilized high-throughput time-series phenotyping using UAVs and sensors in conjunction with machine learning (ML) analytics, which offered a swift and efficient means of phenotyping. The red-edge and green bands were most effective to classify canopy wilting stress. The Red-Edge Chlorophyll Vegetation Index (RECI) successfully differentiated susceptible and tolerant soybean accessions prior to visual symptom development. We report pre-visual detection of soybean wilting using a combination of different vegetation indices. These results can contribute to early stress detection methodologies and rapid classification of drought responses in screening nurseries for breeding and production applications.This is a preprint from Jones, Sarah E., Timilehin Ayanlade, Benjamin Fallen, Talukder Z. Jubery, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, and Asheesh K. Singh. "Multi-Sensor and Multi-temporal High-Throughput Phenotyping for Monitoring and Early Detection of Water-Limiting Stress in Soybean." arXiv preprint arXiv:2402.18751 (2024). doi: https://doi.org/10.48550/arXiv.2402.18751. Copyright 2024 The Authors