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Underwater wireless optical communication (UWOC) systems face challenges due to the significant temporal dispersion caused by the combined effects of scattering, absorption, refractive index variations, optical turbulence, and bio-optical properties. This collective impairment leads to signal distortion and degrades the optical receiver’s bit error rate (BER). Optimising the receiver filter and equaliser design is crucial to enhance receiver performance. However, having an optimal design may not be sufficient to ensure that the receiver decision unit can estimate BER quickly and accurately. This study introduces a novel BER estimation strategy based on a Convolutional Neural Network (CNN) to improve the accuracy and speed of BER estimation performed by the decision unit’s computational processor compared to traditional methods. Our new CNN algorithm utilises the eye diagram (ED) image processing technique. Despite the incomplete definition of the UWOC channel impulse response (CIR), the CNN model is trained to address the nonlinearity of seawater channels under varying noise conditions and increase the reliability of a given UWOC system. The results demonstrate that our CNN-based BER estimation strategy accurately predicts the corresponding signal-to-noise ratio (SNR) and enables reliable BER estimation.

Various published COVID-19 models have been used in epidemiological studies and healthcare planning to model and predict the spread of the disease and appropriately realign health measures and priorities given the resource limitations in the field of healthcare. However, a significant issue arises when these models need help identifying the distribution of the constituent variants of COVID-19 infections. The emergence of such a challenge means that, given limited healthcare resources, health planning would be ineffective and cost lives. This work presents a universal neural network (NN) computational instrument for predicting the mainstream symptomatic infection rate of COVID-19 and models of the distribution of its associated variants. The NN is based on a mixture density network (MDN) with a Gaussian mixture model (GMM) object as a backbone. Twelve use cases were used to demonstrate the validity and reliability of the proposed MDN. The use cases included COVID-19 data for Canada and Saudi Arabia, two date ranges (300 and 500 days), two input data modes, and three activation functions, each with different implementations of the batch size and epoch value. This array of scenarios provided an opportunity to investigate the impacts of epistemic uncertainty (EU) and aleatoric uncertainty (AU) on the prediction model’s fitting. The model accuracy readings were in the high nineties based on a tolerance margin of 0.0125. The primary outcome of this work indicates that this easy-to-use universal MDN helps provide reliable predictions of COVID-19 variant distributions and the corresponding synthesized profile of the mainstream infection rate.

This paper introduces a new simple moment-generating function (MGF) design modelling method to conclude an optimum filter to maximize the Q-factor and increase the link communication span. This approach mitigates the pulse temporal dispersion, particularly the underwater wireless optical communication (UWOC) systems. Hence, some form of equalizing filter design is highly desirable. The model solution environment includes a Double Gamma Function (DGF) water channel impulse response, intersymbol interference (ISI), stochastic Poisson process, and additive Gaussian thermal noise (AGTN). The optimal filters exhibit temporal profiles comparable to those derived by published works based on complex Chernoff Bound (CB) and Modified Chernoff Bound (MCB) methods. The results show the impact of the optimum filter at a signal level and optical receiver level utilizing Eye-Diagrams and BER vs. Q-Factor, respectively. The computation involves four different UWOC propagation channel models for Coastal and Harbor waters. One of the main conclusions indicates that the optimum filter manages the temporal dispersion due to the ISI impairment correctly. Also, the proposed optimum filter reduces eye-opening and the corresponding Q-Factor by less than 15% for a five-times increase in pulse width for the same transmitted optical power level.

Graphene, renowned for its exceptional electrical, optical, and mechanical properties, takes center stage in the realm of next-generation electronics. In this paper, we provide a thorough investigation into the comprehensive fabrication process of graphene field-effect transistors. Recognizing the pivotal role graphene quality plays in determining device performance, we explore many techniques and metrological methods to assess and ensure the superior quality of graphene layers. In addition, we delve into the intricate nuances of doping graphene and examine its effects on electronic properties. We uncover the transformative impact these dopants have on the charge carrier concentration, bandgap, and overall device performance. By amalgamating these critical facets of graphene field-effect transistors fabrication and analysis, this study offers a holistic understanding for researchers and engineers aiming to optimize the performance of graphene-based electronic devices.

BACKGROUND: Expedited discharge following esophagectomy is controversial due to concerns for higher readmissions and financial burden. The present study aimed to evaluate the association of expedited discharge with hospitalization costs and unplanned readmissions following esophagectomy for malignant lesions. METHODS: Adults undergoing elective esophagectomy for cancer were identified in the 2014-2019 Nationwide Readmissions Database. Patients discharged by postoperative day 7 were considered Expedited and others as Routine. Patients who did not survive to discharge or had major perioperative complications were excluded. Multivariable regression models were constructed to assess association of expedited discharge with index hospitalization costs as well as 30- and 90-day non-elective readmissions. RESULTS: Of 9,886 patients who met study criteria, 34.6% comprised the Expedited cohort. After adjustment, female sex (adjusted odds ratio [AOR] 0.71, p = 0.001) and increasing Elixhauser Comorbidity Index (AOR 0.88/point, p

BACKGROUND: While insurance reimbursements allay a portion of costs associated with cardiac operations, uncovered and additional fees are absorbed by patients. An examination of financial toxicity (FT), defined as the burden of patient medical expenses on quality of life, is warranted. Therefore, the present study used a nationally representative database to demonstrate the association between insurance status and risk of financial toxicity (FT) among patients undergoing major cardiac operations. METHODS: Adults admitted for elective coronary artery bypass grafting (CABG) and isolated or concomitant valve operations were assessed using the 2016-2019 National Inpatient Sample. FT risk was defined as out-of-pocket expenditure >40% of post-subsistence income. Regression models were developed to determine factors associated with FT risk in insured and uninsured populations. To demonstrate the association between insurance status and risk of FT among patients undergoing major cardiac operations. RESULTS: Of an estimated 567,865 patients, 15.6% were at risk of FT. A greater proportion of uninsured patients were at risk of FT (81.3 vs. 14.8%, p

The one-pot four-component condensation of benzoic acid (R1), aniline (R2), benzaldehyde (R3), and 2-isocyano-2-methylpropane was investigated at the B3LYP/6-311G** level to explore the reaction mechanism as a theoretical study. All routes were studied and structure of intermediates (IM) was optimized and all of the respective transition states (TS) were found. The calculation results proved that the proposed mechanism consists of eight steps that rate determining the state is nucleophilic attack of isocyanide to benzaldehyde. [ABSTRACT FROM AUTHOR]

Current teleultrasound methods include audiovisual guidance and robotic teleoperation, which constitute tradeoffs between precision and latency versus flexibility and cost. We present a novel concept of "human teleoperation" which bridges the gap between these two methods. In the concept, an expert remotely teloperates a person (the follower) wearing a mixed-reality headset by controlling a virtual ultrasound probe projected into the person's scene. The follower matches the pose and force of the virtual device with a real probe. The pose, force, video, ultrasound images, and 3-dimensional mesh of the scene are fed back to the expert. This control framework, where the actuation is carried out by people, allows more precision and speed than verbal guidance, yet is more flexible and inexpensive than robotic teleoperation. The purpose of this paper is to introduce this concept as well as a prototype teleultrasound system with limited haptics and local communication. The system was tested to show its potential, including mean teleoperation latencies of 0.32 ± 0.05 seconds and steady-state errors of 4.4 ± 2.8 mm and 5.4 ± 2.8 $^ \circ $ ∘ in position and orientation tracking respectively. A preliminary test with an ultrasonographer and four patients was completed, showing lower measurement error and a completion time of 1:36 ± 0:23 minutes using human teleoperation compared to 4:13 ± 3:58 using audiovisual teleguidance. [ABSTRACT FROM AUTHOR]

Despite rigorous theoretical and clinical training, nursing students face emotional and academic challenges that can harm their well‐being. Nonetheless, there is a dearth of research investigating the impact of laughter yoga (LY) on nursing students' well‐being, perceived stress, and self‐efficacy. The aim of this single‐blinded, two‐armed randomized controlled trial is to evaluate the effect of LY on nursing students' well‐being, perceived stress, and academic self‐efficacy (ASE). A total of five sessions of LY were applied to the intervention group. The analysis included a total of 83 nursing students (intervention group n = 41 and control group n = 42). Repeated‐measures multivariate analysis of variance (MANOVA) and paired‐samples t‐test were used for data analysis. Results revealed that the intervention group showed a significant increase in well‐being (p < .001) and a decrease in perceived stress after LY (p < .01). However, statistically significant differences between the intervention and control groups were not found in well‐being, perceived stress, and ASE (p > .05). These results indicate the potential effects of LY on the students' well‐being and perceived stress. Community mental health nurses and educators can use LY to improve well‐being in universities. [ABSTRACT FROM AUTHOR]

Background: The most common first-line treatment for canine lymphoma is a chemotherapy protocol that includes cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP). Canine high-grade T-cell lymphoma has been found to have a significantly poorer prognosis than high grade B-cell lymphoma. Several studies have investigated alternative protocols for non-indolent T-cell lymphoma. This retrospective study investigated using a cyclophosphamide, lomustine, vincristine, and prednisone protocol (CLOP) for naïve non-indolent T-cell lymphoma patients. Methods: In this retrospective study, medical records of dogs treated for non-indolent T-cell lymphoma at a veterinary teaching hospital from 2017 to 2022 were reviewed. Response rate, toxicity, progression-free survival and survival time were calculated. Factors potentially related to prognosis were statistically analyzed. Results: Twenty-six dogs were included in the study. The median progression-free survival (PFS) time was 166 days (95% CI 119–213). The median overall survival time (OST) for the whole study group was 318 days (95% CI 239–374). Twenty-four dogs experienced gastrointestinal adverse events during the protocol, with 79% of them being grade 1 or 2 as per VCOG-CTCAE v2. Conclusions: This protocol has shown similar median PFS time and OST compared with previous studies for canine non-indolent T-cell lymphoma treated with CHOP, along with minimal toxicity, and suggests the inclusion of lomustine in first-line chemotherapy protocol against canine non-indolent T-cell lymphoma may be beneficial. [ABSTRACT FROM AUTHOR]

Underwater wireless optical communication (UWOC) systems face challenges due to the significant temporal dispersion caused by the combined effects of scattering, absorption, refractive index variations, optical turbulence, and bio-optical properties. This collective impairment leads to signal distortion and degrades the optical receiver's bit error rate (BER). Optimising the receiver filter and equaliser design is crucial to enhance receiver performance. However, having an optimal design may not be sufficient to ensure that the receiver decision unit can estimate BER quickly and accurately. This study introduces a novel BER estimation strategy based on a Convolutional Neural Network (CNN) to improve the accuracy and speed of BER estimation performed by the decision unit's computational processor compared to traditional methods. Our new CNN algorithm utilises the eye diagram (ED) image processing technique. Despite the incomplete definition of the UWOC channel impulse response (CIR), the CNN model is trained to address the nonlinearity of seawater channels under varying noise conditions and increase the reliability of a given UWOC system. The results demonstrate that our CNN-based BER estimation strategy accurately predicts the corresponding signal-to-noise ratio (SNR) and enables reliable BER estimation. [ABSTRACT FROM AUTHOR]