Number Research Articles

Computationally efficient handwritten Telugu text recognition

<p>Optical character recognition (OCR) for regional languages is difficult due to their complex orthographic structure, lack of dataset resources, a greater number of characters and similarity in structure between characters. Telugu is popular language in states of Andhra and Telangana. Telugu exhibits distinct separation between characters within a word, making a character-level dataset sufficient. With a smaller dataset, we can effectively recognize more words. However, challenges arise during the training of compound characters, which are combinations of vowels and consonants. These are considered as two or more characters based on associated vattus and dheerghams with the base character. To address this challenge, each compound character is encoded into a numerical value and used as input during training, with subsequent retrieval during recognition. The segmentation issue arises from overlapping characters caused by varying handwritten styles. For handling segmentation issues at the character level arising from handwritten styles, we have proposed an algorithm based on the language's features. To enhance word-level accuracy a dictionary-based model was devised. A neural network utilizing the inception module is employed for feature extraction at various scales, achieving word-level accuracy rates of 78% with fewer trainable parameters.</p>

Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

Solar photovoltaic (SPV) arrays are crucial components of clean and sustainable energy infrastructure. However, SPV panels are susceptible to thermal degradation defects that can impact their performance, thereby necessitating timely and accurate fault detection to maintain optimal energy generation. The considered case study focuses on an intelligent fault detection and diagnosis (IFDD) system for the analysis of radiometric infrared thermography (IRT) of SPV arrays in a predictive maintenance setting, enabling remote inspection and diagnostic monitoring of the SPV power plant sites. The proposed IFDD system employs a custom-developed deep learning approach which relies on convolutional neural networks for effective multiclass classification of defect types. The diagnosis of SPV panels is a challenging task for issues such as IRT data scarcity, defect-patterns’ complexity, and low thermal image acquisition quality due to noise and calibration issues. Hence, this research carefully prepares a customized high-quality but severely imbalanced six-class thermographic radiometric dataset of SPV panels. With respect to previous approaches, numerical temperature values in floating-point are used to train and validate the predictive models. The trained models display high accuracy for efficient thermal anomaly diagnosis. Finally, to create a trust in the IFDD system, the process underlying the classification model is investigated with perceptive explainability, for portraying the most discriminant image features, and mathematical-structure-based interpretability, to achieve multiclass feature clustering.

Numerical simulation of time-dependent viscous fluid flow with upward and downward fluctuation of spinning disk

The parametric approach towards time-dependent viscous fluid flow across a gyrating disk with upward and downward fluctuation. The major goal of this research is to assess fluid flow under the influence of magnetic fields and heat propagation processes. Because they provide a thorough description of electromagnetic interactions. Maxwell's equations are at the heart of all contemporary information and communication technologies. The governing equations comprising Navier Stokes equation, energy, concentration, and Maxwell equations have been represented appropriately for this purpose. The governing equations are turned down to the system of non-linear ODEs through a resemblance framework. The obtained system of differential equations has been resolved via numerical procedure Parametric Continuation Method (PCM). For the scale reliability purpose, the outcomes are compared to another numerical Matlab scheme boundary value solver. In the current analysis, the presence of convective boundary conditions correlated to mass and energy is of physical relevance. The numerical findings are provided in tabular and graphical forms. The consequences of suction and wall injection have been also highlighted. The upward motion of the spinning disc is thought to lead to comparable findings as in an injection scenario, whilst the downhill motion is thought to contribute to wall suction-like effects.

QUALITY OF LIFE IN PATIENTS, WHO UNDERWENT INGUINAL HERNIOPLASTY

Abstract Background 20 million people with inguinal hernias are operated annually throughout the world. Severe chronic pain after hernia repair effects social life, daily activity and overall quality of life (QL). In medicine, QL is assessed by the level of well-being and satisfaction with those aspects of life that are affected by the disease and its treatment. The Short Form-36 is (SF-36) a validated indicator of overall health status. Method this study was to evaluate QL by SF-36 questionnaire in patients, who underwent inguinal hernioplasty (open surgery – Lichtenstein tension-free mesh inguinal hernia repair or laparoscopic surgery – transabdominal preperitoneal (TAPP)). Results: State the main findings, including important numerical values. Results The majority had unilateral hernias 89.0% and the most common surgical technique was Lichtenstein’s repair (82.4%). The postoperative QL was significantly better after surgery. Comparing two groups of patients after surgery, only the pain domain of the questionnaire was worse in patients operated by Lichtenstein repair: 46.5%/39.8% experienced mild pain, 38.6%/42.0% experience moderate pain and only 14.9%/18.2% experienced severe pain. Conclusion Results showed that 213 (86.9%) patients felt that their QL was satisfactory after the hernia repair, with most of them being from the age group of 19–39 years (93.2%).

Magneto-Micropolar Nanofluid Flow Over a Convectively Heated Sheet with Nonlinear Radiation, Chemical Reaction, and Viscous Dissipation

A mathematical model is presented for analyzing the flow of magneto-micropolar nanofluid above a convectively heated permeable stretching sheet with nonlinear radiation, chemical reaction, and viscous dissipation. Similarity transformation is utilized to change the governing partial differential equations to the system of nonlinear ordinary differential equations (ODEs). The resulting system of ODEs is sorted out mathematically by utilizing the shooting method with the Adams-Moulton method of fourth order, and the obtained mathematical outcomes are compared with published results. The obtained numerical results reflect very good agreement with those from open literature. Numerical values of physical quantities like skin friction coefficient, Sherwood number, and Nusselt number for emerging parameters such as Pr , Nb , Nt , Le , etc. are also computed and discussed in this work. The impact of pertinent flow parameters on nondimensional velocity, temperature, and concentration profiles is illustrated via tables and graphs.

A novel dynamic stiffness matrix for the nonlocal vibration characteristics of porous functionally graded nanoplates on elastic foundation with small-scale effects

The present paper deals with the development of a dynamic stiffness matrix to evaluate the free vibration response of functionally graded nanoplate (FG-nP) resting on the Winkler-Pasternak elastic foundation. The complete mathematical modeling of the dynamic stiffness matrix for nanostructures is given for the first time. The equation of motion for rectangular FG-nP plates supported on an elastic foundation is derived using Hamilton’s principle in conjunction with nonlocal elasticity theory. The non-local theory is incorporated to account for the size effect in the small-scale plate. The effective material property of the porous FG-nP has been calculated using three recently developed models of porosity. The developed dynamic stiffness matrix is solved using the Wittrick-Williams algorithm to extract the natural frequencies of the FG-nP. The variation of natural frequencies with the change of numerical values, such as nonlocal parameter, aspect ratio, elastic foundation parameters, and porosity volume fraction is analyzed. The validity and accuracy of the results are confirmed through comparison with the available literature. The use of non-local theory in dynamic stiffness analysis is shown to be effective in predicting the natural frequency of the FG-nP on a Winkler-Pasternak elastic foundation, providing new insights into the dynamic behavior of small-scale structures.

Genetic types and provenance indication of clastic amphibole in the South Yellow Sea

The main focus of studying sediment sources in marine areas is to determine the properties of clastic minerals originating from different rivers. Variations in the characteristics of clastic minerals occur due to differences in the types of source rocks within the watershed. Determining the source rock of clastic minerals in the marine area can improve the accuracy of provenance analysis. Electron probe microanalysis of 258 amphibole grains from six surface stations in the South Yellow Sea (SYS) was conducted to calculate the numerical and characteristic values of cations in the crystal structure. The results showed that amphibole in the SYS is mainly magnesiohornblende (52.2% ~ 81.4%) in the calcic amphibole subgroup, followed by tschermakite. The source rock types of amphibole are mainly different types of magmatic (ultrabasic, basic, and intermediate acidic) and metamorphic rocks. Amphibole derived from intermediate-acid intrusive rocks accounts for a large proportion (>40%). The genetic analysis of clastic amphibole in the SYS showed that most of the medium-acid invading amphibole belong to crust-mantle type, followed by mantle type. Most of the amphibole from metamorphic origins are of medium-low pressure type (± 80%). Combined with electron probe analysis of amphibole from the Huanghe River (the Yellow River, HH) and Changjiang River (the Yangtze River, CJ), the amphibole in the SYS exhibits characteristics inherited from these two rivers. The northern sea area has a strong resemblance to the sediments from the HH, while the southern area is more influenced by sediments supply from the CJ. The central area represents a mixed zone with a higher sediment supply from the HH. The clastic amphibole deduces the type of source rock in different watersheds, serving as a crucial link between the source rock, watershed, and marine area, providing a basis for provenance analysis.

Critical Velocities of Single-layer and Two-layer Composite Tubes of Transversely Isotropic Materials Based on a Potential Function Method in 3-D Elasticity

Abstract Critical velocities of a single-layer tube of a transversely isotropic material and a two-layer composite tube consisting of two perfectly-bonded cylindrical layers of dissimilar transversely isotropic materials are analytically determined using the potential function method of Elliott in three-dimensional (3-D) elasticity. The displacement and stress components in each transversely isotropic layer of the tube subjected to a uniform internal pressure moving at a constant velocity are derived in integral forms by applying the Fourier transform method. The solution includes those for a tube composed of two dissimilar cubic or isotropic materials as special cases. In addition, it is shown that the model for the two-layer composite tube can be reduced to that for the single-layer tube. Closed-form expressions for four critical velocities are derived for the single-layer tube. The lowest critical velocity is obtained from plotting the velocity curve and finding the inflection point for both the single-layer and two-layer composite tubes. To illustrate the newly developed models, two cases are studied as examples – one for a single-layer isotropic steel tube and the other for a two-layer composite tube consisting of an isotropic steel inner layer and a transversely isotropic glass-epoxy outer layer. The numerical values of the lowest critical velocity predicted by the new 3-D elasticity-based models are obtained and compared with those given by existing models based on thin- and thick-shell theories.

Numerical Calculation and Experimental Study of the Axial Force of Aero Fuel Centrifugal Pumps

Axial force is one of the important factors affecting the life and reliability of centrifugal pumps. Based on the SST turbulence model, the unsteady internal flow field of an aero fuel centrifugal pump under various working conditions was analyzed by using the finite volume method and the axial force of the impeller component was predicted. The position servo force measuring system was used to measure the axial force of the fuel centrifugal pump and the theoretical formula of axial force was modified according to the numerical results and experimental values. The study shows that the pressure distribution of the front and rear pump chambers presented uneven circumferential distribution under the influence of dynamic and static interference through numerical simulation. The simulated head number is basically consistent with the test result and the maximum error of the axial force value obtained by the numerical calculation and the experimental value was 9.7% under different speeds, which verified the accuracy of the numerical simulation. Furthermore, the modified formula can accurately calculate the axial force of the fuel centrifugal pump with an error of less than 9.88%. The results of the study provide a theoretical basis for the calculation and balance of axial force in an aero aero fuel centrifugal pump.

Calibrated Empirical Neutrosophic Cumulative Distribution Function Estimation for Both Symmetric and Asymmetric Data

The traditional stratification weight is widely used in survey sampling for estimation under stratified random sampling (StRS). A neutrosophic calibration approach is proposed under neutrosophic statistics for the first time with the aim of improving conventional stratification weight. This addresses the challenge of estimating the empirical cumulative distribution function (CDF) of a finite population using the neutrosophic technique. The neutrosophic technique extends traditional statistics, dealing with indeterminate, vague, and uncertain values. Thus, using additional information, we are able to obtain an effective estimate of the neutrosophic CDF. The suggested estimator yields an interval range in which the population empirical CDF is likely to exist rather than a single numerical value. The proposed family of neutrosophic estimators will be defined under suitable calibration constraints. A simulation study is also computed in order to assess the effectiveness of the suggested and adapted neutrosophic estimators using real-life symmetric and asymmetric datasets.

УТОЧНЕННЯ РОЗРАХУНКОВОГО ЗНАЧЕННЯ МОДУЛЯ ПРУЖНОСТІ АСФАЛЬТОБЕТОНІВ

Introduction. One of the most important characteristics of asphalt concrete that characterizes its properties is the elasticity modulus. The elasticity modulus of asphalt concrete is used in the design of pavement structures to calculate its permissible elastic deflection, under the condition of shear resistance of the working subgrade layer and the layers of non-cohesive materials, as well as bending tensile strength. Problem statement. Today, the calculated value of the elasticity modulus of asphalt concrete is taken in accordance with Handbook No. 2 «Design Characteristics of Asphalt Concrete» [2]. In this Handbook, the calculated value of the elasticity modulus of asphalt concrete is given depending on the bitumen grade, temperature, type of asphalt mixture, and time of load action. Numerical design values of the elasticity modulus of asphalt concrete are provided only for asphalt concrete type B; for other types of asphalt concrete, it is proposed to reduce or increase the design value of the elasticity modulus by the value that depends on the type of asphalt concrete and temperature. Since 2020, a new standard on technical requirements for bitumen has been in force in Ukraine, which brings bitumen grades in line with the European classification [4]. At the same time, in the Handbook No. 2 [2], the calculated value of the elasticity modulus of asphalt concrete is given in accordance with the previous bitumen grades, which necessitates their adjustment.

Barriers to neurosurgery for medical students: a national study focused on the intersectionality of gender and race.

Despite 51.2% of medical school graduates being female, only 29.8% of neurosurgery residency applicants are female. Furthermore, only 12.6% of neurosurgery applicants identify as underrepresented in medicine (URM). Evaluating the entry barriers for female and URM students is crucial in promoting the equity and diversity of the neurosurgical workforce. The objective of this study was to evaluate barriers to neurosurgery for medical students while considering the interaction between gender and race. A Qualtrics survey was distributed widely to US medical students, assessing 14 factors of hesitancy toward neurosurgery. Likert scale responses, representing statement agreeability, converted to numeric values on a 7-point scale were analyzed by Mann-Whitney U-test and ANOVA comparisons with Bonferroni correction. Of 540 respondents, 68.7% were female and 22.6% were URM. There were 22.6% male non-URM, 7.4% male URM, 53.5% female non-URM, and 15.2% female URM respondents. The predominant reasons for hesitancy toward neurosurgery included work/life integration, length of training, competitiveness of residency position, and perceived malignancy of the field. Females were more hesitant toward neurosurgery due to maternity/paternity needs (p = 0.005), the absence of seeing people like them in the field (p < 0.001), and opportunities to pursue health equity work (p < 0.001). Females were more likely to have difficulties finding a mentor in neurosurgery who represented their identities (p = 0.017). URM students were more hesitant toward neurosurgery due to not seeing people like them in the field (p < 0.001). Subanalysis revealed that when students were stratified by both gender and URM status, there were more reasons for hesitancy toward neurosurgery that had significant differences between groups (male URM, male non-URM, female URM, and female non-URM students), suggesting the importance of intersectionality in this analysis. The authors highlight the implications of gender and racial diversity in the neurosurgical workforce on medical student interest and recruitment. Their findings suggest the importance of actively working to address these barriers, including 1) maternity/paternity policy reevaluation, standardization, and dissemination; and 2) actively providing resources for the creation of mentorship relationships for both women and URM students in an effort to create a workforce that aligns with the changing demographics of medical graduates to continue to improve diversity in neurosurgery.

Body mass weighted PSA levels, new markers to predict locally advanced prostate cancer after prostatectomy.

PSA remains the most useful marker for screening, risk categorization, and follow-up in patients with prostate cancer. In the obese population, several studies have revealed that obesity may not only inversely interfere with the concentration of PSA, but also increase the risk of prostate cancer. Thus, we considered using the Body mass weighted PSA levels, presented as serum PSA concentration multiplied by body weight or BMI, instead of traditional PSA concentration, as potential markers to predict locally advanced prostate cancer after prostatectomy. We retrospectively collected and analyzed data acquired from a single institute at which robot-assisted laparoscopic radical prostatectomy was performed. A total of 174 patients underwent radical prostatectomy, and the collected data included age, PSA level, body weight, BMI, and pathology results. A total of 174 patients diagnosed with adenocarcinoma of the prostate by needle biopsy, and most (N=165) were considered to have localized disease on preoperative multi-parameter magnetic resoanace imaging. After prostatectomy, 73% (N=127) of the patients remained in the localized disease group (group A) and 27%(N=47) of the patients were reclassified to the locally advanced prostate cancer (group B). The value of PSA was higher in Group B (16.9 vs 11.2 ng/dL; p= 0.062), but there was no statistically significant difference between the two groups. After using the numerical values of PSA x body weight and PSA x BMI, a statistically significant difference emerged between the two groups (p= 0.0198 in PSA × BW; p=0.0110 in PSA × BMI). The Body mass weighted PSA levels, instead of the traditional PSA concentration, may be better markers for predicting non-organ-confined disease after surgery. It may also be useful in screening and risk categorization.

Predictive Analysis of Campus Placement of Student Using Machine Learning Algorithms

In today's competitive job market, student campus placement process becomes very important role in the academic journey of students and the reputation of educational institutions alike. As the demand for skilled professionals continues to rise, the ability to accurately predict and optimize student placement outcomes becomes increasingly essential. This research paper proposes a machine learning algorithms analysis to forecast the campus placement of students with the help of various academic factors. The dataset contains historical placement records of students received from open-source repository named as kaggle. It includes information such as student academic achievements, internship, project, workshop, soft skill, extracurricular activities, and placement outcomes. Through data preprocessing and feature engineering, we transform raw data into a structured format suitable for predictive modeling. One hot encoding (Dummy encoding) applied on dataset to represent categorical variables as numerical values to provide more information to the model about the categorical variables. Predictive analysis work on various machine learning algorithms, including logistic regression, decision trees, random forests, support vector machines (SVM), XGBoost, AdaBoost, KNN and Naive Byes. The results of analysis demonstrate in predicting student placement outcomes with high accuracy and reliability. Accuracy is calculated in the form of precision, recall, f1-score, and support. Furthermore, we conduct feature importance analysis to identify the importance of different predictors in determining placement success. This research paper study can help to academic institutions that can identify at-risk students early in their academic journey and to improve their employability. In conclusion, research underscores the potential of predictive analysis and machine learning in optimizing student placement outcomes. By harnessing the power of data-driven insights, institutes can make use of placement prediction model to check the likelihood of campus placement of students.

Evaluation of subjective policy reflection using the Choquet integral and its applications

This paper proposes a methodology for assessing the subjective policy reflection in national trade policies through the use of Choquet integral. Specifically, we introduce three fuzzy measures that reflect different policies based on the trade items included in data on the annual trade amounts of selected national animal products from 2010 to 2020. The Choquet expected utility serves as a tool for evaluating subjective policy reflection, allowing for the comparison of national economic policies across selected countries. To demonstrate the practical application of the proposed methodology, we provide specific numerical values that represent the evaluation of subjective policy reflection. Furthermore, we present a decision-making strategy that pertains to the allocation of subsidies on imports and exports of trade transaction amounts, assuming that government subsidies are budgeted using the Choquet expected utility. The proposed methodology offers a valuable framework for policymakers and stakeholders, facilitating in-depth analysis and improvement of the effectiveness of national trade policies.

INDIPENDENT PROGNOSTIC VALUE OF SOLUBLE–SUPRESSION OF TUMORIGENICITY (S–ST2) IN PATIENTS AFFECTED BY PULMONARY HYPERTENSION

Abstract Introduction According to ESC 2022 guidelines, pulmonary hypertension (PH) is a hemodynamic condition characterized by mean pulmonary arterial pressure&amp;gt;20 mmHg. Pulmonary arterial hypertension (PAH) represents 5% of the PH, with an unfavorable prognosis primarily because of late diagnosis and treatment. In PAH, it is important to evaluate the individual patient mortality risk through a multiparametric approach: a three–layer model at diagnosis and a four–layer model based on WHO–FC, 6MWD and NT–proBNP at follow up, which allows better discrimination within the intermediate risk group helping therapeutic decision making. The only biomarker included in risk stratification is NT–proBNP; however, in previous studies soluble–Supression of Tumorigenicity 2(s–ST2), a marker of myocardial stress, resulted a strong predictor of death in heart failure and acute coronary syndromes. Aim The aim of this study is to analyze the prognostic value of s–ST2 in patients with pulmonary hypertension. Methods This is a prospective study conducted on 45 PH patients (75% PAH), which were followed for survival. They underwent echocardiography, venous sampling to measure s–ST2 levels, right heart catheterization. All the patients were followed for survival. Results During an average 18–month follow–up, 17 patients died, 76% of whom had pulmonary arterial hypertension (PAH). They showed significantly higher values of s–ST2. sST2&amp;gt;78 ng/ml represents a numerical value with the highest association with mortality in our study population: at 6–12 months the patients with sST2&amp;gt;78 ng/ml showed statistically significant early higher mortality in comparison with sST2 &amp;lt;78 ng/ml patients (Fig. 1). At multivariate analysis s–ST2&amp;gt;78 ng/ml is confirmed to be a statistically significant predictor of mortality, regardless of WHO functional class III–IV, PAPs and NT–proBNP. Furthermore, s–ST2 appears a better early mortality predictor than NT–proBNP, at the limit of statistical significance (Fig. 2). Conclusions In a population of patients with pulmonary hypertension (predominantly PAH) we define a numerical value of sST2&amp;gt;78 ng/ml, which is a prognostic discriminator, independent and incremental to NT–proBNP at short–term follow–up. It allows the clinician the appropriate planning of therapeutic strategies in a condition in which the earliness of therapy affects prognosis.

The final part of the CRESS trilogy- how to evaluate the quality of stability studies.

High quality laboratory results are critical for patient management. However, poor sample quality can impact these results and patient safety. To ensure reliable and accurate results laboratories must be aware of each analyte's stability under various storage conditions and matrices to guarantee correct and dependable outcomes. This knowledge allows laboratories to define the allowable delay between sample collection and centrifugation/analysis for all analytes to guarantee appropriate results quality and interpretation. The EFLM WG-PRE therefore established a 4-step plan to tackle this issue, aiming to standardize and harmonize stability studies for improved comparison andmeta-analysis. The plan included the development of checklists and how-to guides for performing and reporting stability studies as well as a central resource of stability data. This manuscript deals with the issue of evaluating publications and incorporating them into a central resource. To evaluate stability studies, the CRESS checklist was used to structure 20 sections used to judge the quality of studies. Each section has 4 levels of quality, with scores converted to numerical values and weighted based on expert opinion. Based on this, a final score ranging from A to D was determined. The procedure was then tested on six manuscripts and checked for agreement between expert judgements. The results demonstrated that the proposed evaluation process is a useful tool to distinguish between best in class manuscripts and those of lower quality. The EFLM WG-PRE strongly believes that the provided recommendations and checklists will help improving stability studies both in quality and standardisation.

Regression Approach in the Evaluation of White’s Effect Magnitude in Comparison to Lightness

In the achromatic White's grid, the grey patches between the grey lines are perceived as darker while the same elements inserted between white lines are perceived lighter than their true measured values. A number of authors attempted to calculate the magnitude and direction of this effect using mathematical models based on multiple spatial filters. This paper uses different mathematical model, based on regression analysis, which has shown itself as an excellent tool for prediction of direction and magnitude of White's effect. The psychophysical visual experiment was conducted on 38 subjects of both genders. The differences in lightness perception ∆L00 were calculated in CIE ∆E_2000 system. This paper determined the functional dependence of White's effect magnitude ∆L00 to the lightness L of rectangular elements in White's achromatic grid. The results gave the square polynomial of very high quality (R2 = 0,974). Regression polynomials were also found. The gave numerical values ∆L00 of difference in perception of left and right elements in comparison to their physical values (left R2 = 0,943, right R2 = 0,938) in dependence to variation of lightness parameter L. Results of the research clearly show the mathematical pattern of White's effect based on the lightness of rectangular elements.

Sentinel Lymph Node Mapping in Lung Cancer: A Pilot Study for the Detection of Micrometastases in Stage I Non-Small Cell Lung Cancer.

Lymphadenectomy represents a fundamental step in the staging and treatment of non-small cell lung cancer (NSCLC). To date, the extension of lymphadenectomy in early-stage NSCLC is a debated topic due to its possible complications. The detection of sentinel lymph nodes (SLNs) is a strategy that can improve the selection of patients in which a more extended lymphadenectomy is necessary. This pilot study aimed to refine lymph nodal staging in early-stage NSCLC patients who underwent robotic lung resection through the application of innovative intraoperative sentinel lymph node (SLN) identification and the pathological evaluation using one-step nucleic acid amplification (OSNA). Clinical N0 NSCLC patients planning to undergo robotic lung resection were selected. The day before surgery, all patients underwent radionuclide computed tomography (CT)-guided marking of the primary lung lesion and subsequently Single Photon Emission Computed Tomography (SPECT) to identify tracer migration and, consequently, the area with higher radioactivity. On the day of surgery, the lymph nodal radioactivity was detected intraoperatively using a gamma camera. SLN was defined as the lymph node with the highest numerical value of radioactivity. The OSNA amplification, detecting the mRNA of CK19, was used for the detection of nodal metastases in the lymph nodes, including SLN. From March to July 2021, a total of 8 patients (3 female; 5 male), with a mean age of 66 years (range 48-77), were enrolled in the study. No complications relating to the CT-guided marking or preoperative SPECT were found. An average of 5.3 lymph nodal stations were examined (range 2-8). N2 positivity was found in 3 out of 8 patients (37.5%). Consequently, pathological examination of lymph nodes with OSNA resulted in three upstages from the clinical IB stage to pathological IIIA stage. Moreover, in 1 patient (18%) with nodal upstaging, a positive node was intraoperatively identified as SLN. Comparing this protocol to the usual practice, no difference was found in terms of the operating time, conversion rate, and complication rate. Our preliminary experience suggests that sentinel lymph node detection, in association with the accurate pathological staging of cN0 patients achieved using OSNA, is safe and effective in the identification of metastasis, which is usually undetected by standard diagnostic methods.

Ask-Tell-Ask with Bidirectional Feedback Improves Feedback Culture.

The authors sought to assess whether an Ask-Tell-Ask feedback model augmented with bidirectional feedback improves perception of feedback. Implementation occurred on an inpatient psychiatry unit at University of North Carolina (UNC) Hospitals from July 2022 to June 2023 among attending and resident physicians and medical students. Attending physicians were educated on the Ask-Tell-Ask model and encouraged to hold weekly bidirectional feedback sessions with trainees. Surveys containing scales and free-text response were distributed by email before and after rotations to assess perception of feedback: if feedback was clearly stated, occurred on a predictable basis, included actionable goals, and fostered bidirectional feedback with attendings. For statistical analysis, survey responses were assigned numerical values of 1 (strongly disagree) to 5 (strongly agree). Differences between mean numerical correlates of responses from pre-rotation and post-rotation surveys were analyzed with unpaired t-tests; p < 0.05 indicated statistical significance. Authors independently developed themes from free-text responses, which were consolidated with themes developed by all authors. Mean ratings to survey items universally improved following the intervention; all p < 0.0001 and statistically significant. Pre-rotation, feedback culture was described as constrained, fraught, non-actionable, inconsistent, improving, and hierarchical. Post-rotation, the feedback culture within the UNC Department of Psychiatry was described as constructive, consistent, improving, strength-based, approachable, and nonhierarchical. An Ask-Tell-Ask feedback model with an added emphasis on giving and receiving feedback significantly improves perception of feedback and feedback culture.