Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model.

In today's world, stress is a major factor for various diseases in modern societies which affects the day-to-day activities of human beings. The measurement of stress is a contributing factor for governments and societies that impacts the quality of daily lives. The strategy of stress monitoring systems requires an accurate stress classification technique which is identified via the reactions of the body to regulate itself to changes within the environment through mental and emotional responses. Therefore, this research proposed a novel deep learning approach for the stress classification system. In this paper, we presented an Enhanced Long Short-Term Memory(E-LSTM) based on the feature attention mechanism that focuses on determining and categorizing the stress polarity using sequential modeling and word-feature seizing. The proposed approach integrates pre-feature attention in E-LSTM to identify the complicated relationship and extract the keywords through an attention layer for stress classification. This research has been evaluated using a selected dataset accessed from the sixth Korea National Health and Nutrition Examination Survey conducted from 2013 to 2015 (KNHANES VI) to analyze health-related stress data. Statistical performance of the developed approach was analyzed based on the nine features of stress detection, and we compared the effectiveness of the developed approach with other different stress classification approaches. The experimental results shown that the developed approach obtained accuracy, precision, recall and a F1-score of 75.54%, 74.26%, 72.99% and 74.58%, respectively. The feature attention mechanism-based E-LSTM approach demonstrated superior performance in stress detection classification when compared to other classification methods including naïve Bayesian, SVM, deep belief network, and standard LSTM. The results of this study demonstrated the efficiency of the proposed approach in accurately classifying stress detection, particularly in stress monitoring systems where it is expected to be effective for stress prediction.

Physiological effects of some engineered nanomaterials on radish (Raphanus sativus L.) intercropped with pea (Pisum sativum L.).

Intercropping leguminous plant species with non-legume crops could be an effective strategy to maintain soil fertility. Additionally, the application of nano-Zn and Fe in trace amounts can substantially improve the bioavailable fraction of Zn and Fe. We studied the effect of foliar application of some nanomaterials on the agronomic, physio-biochemical attributes under a radish/pea intercropping system. The radish and pea were sprayed with different nanomaterials (Zn-Fe nanocomposite, nZnO, and nanobiochar) at 0 and 50 mg L-1 concentrations. Results indicated that the growth parameters of radish were higher in intercropping than in monocropping, while pea growth was inhibited in intercropping compared with monocropping. The shoot and root length, fresh weight, and dry matter of radish were increased by 28-50%, 60-70%, and 50-56% by intercropping than monocropping. Foliar spray of nano-materials further increased the growth traits of intercropped radish, such as shoot and root length, fresh weight, and dry matter, by 7-8%, 27-41%, and 50-60%, respectively. Similarly, pigments such as chlorophyll a, b, and carotenoids and the concentration of free amino acids, soluble sugars, flavonoids, and phenolics were differentially affected by intercropping and nanomaterials. The yield of the non-legume crop was increased by intercropping, whereas the legume crop exhibited significant growth inhibition due to competitive interactions. In conclusion, both intercropping and foliar spray of nanomaterials could be used as a combined approach to benefit plant growth and enhance the bioavailable Fe and Zn fractions of both crops.

First human case report of Crohn's disease with coexistent acute appendicitis treated by endoscopic retrograde appendicitis therapy.

Background: The coexistence of Crohn's disease (CD) and acute appendicitis (AA) is rare. In this situation, therapeutic experience is lacking and the strategy is paradoxical and intractable. Appendectomy is the gold standard for the treatment of AA whereas a nonsurgical approach is recommended for CD. Case summary: A 17-year-old boy was hospitalized for right lower abdominal pain with fever of 3 days. He had the CD for 8 years. Two years ago, he underwent surgery for anal fistula with the complication of CD. His temperature was elevated at 38.3°C at admission. On physical examination, there was McBurney tenderness with mild rebound tenderness. Abdominal ultrasonography showed that the appendix was notably enlarged and dilated at 6.34 cm long and 2.76 cm wide. These findings were suggestive of uncomplicated AA in this patient with active CD. Endoscopic retrograde appendicitis therapy (ERAT) was performed. The patient had complete pain relief immediately after the procedure without tenderness in the right lower abdomen. During 18 mo follow-up, he had no more attacks in his right lower abdomen. Conclusion: ERAT was effective and safe in a CD patient with coexisting AA. Such cases can avoid surgery and its-related complications.

Efficacy and Safety of Radiofrequency Ablation Plus Stent Versus Stent-alone Treatments for Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND/AIMS: Malignant biliary strictures (MBS) are very aggressive and cannot be diagnosed in the early stages due to their asymptomatic nature. Stenting the stricture area of the biliary tree is palliative treatment but has poor survival time. Radiofrequency ablation plus stent (RFA+S) have been recently used to improve the survival and stent patency time in patients with MBS. In this systematic review and meta-analysis, we tried to evaluate the efficacy and safety of radiofrequency ablation. MATERIALS AND METHODS: Study search up to December 2021 was performed in different medical databases such as PubMed, Web of Science, and Cochrane library, etc. We selected eligible studies reporting survival time, stent patency time, and adverse events in patients with MBS. We compare the outcomes of RFA+S and stent-alone treatment groups. RESULTS: A total of 15 studies (6 randomized controlled trials and 9 observational studies) with 1815 patients were included for meta-analysis of which 701 patients were in RFA+S group and 1114 patients in the stent-alone group. Pooled mean difference of survival time was 2.88 months (95% CI: 1.78-3.97) and pooled mean difference of stent patency time was 2.11 months (95% CI: 0.91-3.30) and clinical success risk ratio was 1.05 (95% CI: 1.01-1.09). Risk ratios for adverse events are given; Bleeding 0.84 (95% CI: 0.34-2.11), abdominal pain 1.06 (95% CI: 0.79-1.40), pancreatitis 0.93 (95% CI: 0.43-2.01), cholangitis 1.07 (95% CI: 0.72-1.59), and stent dysfunction 0.87 (95% CI: 0.70-1.07). CONCLUSIONS: Radiofrequency ablation is involved in increased survival and stent patency time for MBS patients. With the help of better techniques, adverse events can be limited.

Study on the Pakistan stock market using a new stock crisis prediction method.

A Stock market collapse occurs when stock prices drop by more than 10% across all main indexes. Predicting a stock market crisis is difficult because of the increased volatility in the stock market. Stock price drops can be triggered by a variety of factors, including corporate results, geopolitical tensions, financial crises, and pandemic events. For scholars and investors, predicting a crisis is a difficult endeavor. We developed a model for the prediction of stock crisis using Hybridized Feature Selection (HFS) approach. Firstly, we went for the suggestion of the HFS method for the removal of stock's unnecessary financial attributes. The Naïve Bayes approach, on the other hand, is used for the classification of strong fundamental stocks. In the third step, Stochastic Relative Strength Index (StochRSI) is employed to identify a stock price bubble. In the fourth step, we identified the stock market crisis point in stock prices through moving average statistics. The fifth is the prediction of stock crises by using deep learning algorithms such as Gated Recurrent Unit (GRU) and Long-Short Term Memory (LSTM). Root Mean Square Error (RMSE), Mean Squared Error (MSE) and Mean Absolute Error (MAE) are implemented for assessing the performance of the models. The HFS-based GRU technique outperformed the HFS-based LSTM method to anticipate the stock crisis. To complete the task, the experiments used Pakistan datasets. The researchers can look at additional technical factors to forecast when a crisis would occur in the future. With a new optimizer, the GRU approach may be improved and fine-tuned even more.

Incidence and predictors of pacemaker-induced cardiomyopathy with right ventricular pacing: a systematic review.

INTRODUCTION: This systematic review aims to evaluate the incidence and predictors of pacemaker-induced cardiomyopathy (PICM) in patients undergoing right ventricular pacing. AREAS COVERED: A literature review was conducted using MeSH terms (Right ventricular pacing, Pacemaker-related cardiomyopathy, Pacemaker-induced cardiomyopathy) in PubMed, EMBASE, Web of science CINAHL, and the Cochrane Library until October 2021. All data reporting the incidence of PICM after implantation of right-sided pacemakers or implantable cardioverter-defibrillator (ICD) were retrieved from the eligible studies. EXPERT OPINION: Out of 3,625 articles, 20 studies met the inclusion criteria that included 5,381 patients. . The mean age of the patients ranged between 55.8 ± 13.5 and 77.4 ± 10.8 years. The mean incidence of PICM was 25.7%. Mean ejection fraction (EF) at baseline ranged from 48 ± 1% and 62.1 ± 11.2%, while mean EF at follow-up ranged between 33.7 ± 7.4% and 53.2 ± 8.2%. Three studies reported a decline of >20% EF at follow-up. RV pacing was associated with a considerable risk of PICM, with biological factors, such as male gender, old age, increased QRS duration, and chronic RV pacing burden playing an important role in the development of disease.

Endoscopic retrograde appendicitis therapy in the management of chronic fecalith appendicitis in a patient with ulcerative colitis: The first human case report.

To assess the effectiveness of endoscopic retrograde appendicitis therapy (ERAT) as a new technique and method for chronic fecalith appendicitis complicated by active ulcerative colitis. A 46-year-old male patient was admitted with right iliac fossa pain, tenderness, and raised inflammatory markers. A computed tomography (CT) scan of his abdomen confirmed a dilated appendix, which is considered chronic fecalith appendicitis combined with active ulcerative colitis. He was treated with an endoscopic retrograde appendicitis therapy procedure. The patient recovered well after the ERAT procedure and was discharged from the hospital in two days. On follow-up one year later, there was no recurrence of pain in his abdomen. In conclusion, ERAT could be seen as a different approach and be favored as a safer and more effective option in treating UC patients with appendicitis, especially those who are later in the course of the disease. Because of the ERAT procedure, such cases can avoid surgery and surgery-related complications. More research and issues must be addressed to demonstrate the efficacy and effectiveness of ERAT in appendicitis combined with UC.

A comparative analysis on question classification task based on deep learning approaches.

Question classification is one of the essential tasks for automatic question answering implementation in natural language processing (NLP). Recently, there have been several text-mining issues such as text classification, document categorization, web mining, sentiment analysis, and spam filtering that have been successfully achieved by deep learning approaches. In this study, we illustrated and investigated our work on certain deep learning approaches for question classification tasks in an extremely inflected Turkish language. In this study, we trained and tested the deep learning architectures on the questions dataset in Turkish. In addition to this, we used three main deep learning approaches (Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN)) and we also applied two different deep learning combinations of CNN-GRU and CNN-LSTM architectures. Furthermore, we applied the Word2vec technique with both skip-gram and CBOW methods for word embedding with various vector sizes on a large corpus composed of user questions. By comparing analysis, we conducted an experiment on deep learning architectures based on test and 10-cross fold validation accuracy. Experiment results were obtained to illustrate the effectiveness of various Word2vec techniques that have a considerable impact on the accuracy rate using different deep learning approaches. We attained an accuracy of 93.7% by using these techniques on the question dataset.

Bimetallic cobalt-iron diselenide nanorod modified glassy carbon electrode: an electrochemical sensing platform for the selective detection of isoniazid.

The increasing demand of a sensitive and portable electrochemical sensing platform in pharmaceutical analysis has developed widespread interest in preparing electrode materials possessing remarkable properties for the electrochemical determination of target drug analytes. Herein, we report the synthesis, characterization and application of bimetallic cobalt-iron diselenide (FeCoSe2) nanorods as electrode modifiers for the selective detection of a commonly used anti-tuberculosis drug Isoniazid (INZ). We prepared FeCoSe2 nanorods by a simple hydrothermal route and characterized these by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDX) and temperature-programmed reduction (TPR) techniques. The electrochemical characterization of FeCoSe2 modified GCE was performed by cyclic voltammetry (CV) and square wave anodic stripping voltammetry (SWASV). Under optimized experimental conditions, a linear current-concentration response was obtained for INZ in the range of 0.03-1.0 µM, with very low limit of detection 1.24 × 10-10 M. The real applicability of the designed FeCoSe2/GCE sensing platform was adjudicated by the detection of INZ in biological samples.

FeCoSe2 Nanoparticles Embedded in g-C3N4: A Highly Active and Stable bifunctional electrocatalyst for overall water splitting.

To investigate cost affordable and robust HER and OER catalysts with significant low overpotentials, we have successfully embedded FeCoSe2 spheres on smooth surfaces of graphitic carbon nitride that demonstrated high stability and electrocatalytic activity for H2 production. We systematically analyzed the composition and morphology of FexCo1-xSe2/g-C3N4 and attributed the remarkable electrochemical performance of the catalyst to its unique structure. Fe0.2Co0.8Se2/g-C3N4 showed a superior HER activity, with quite low overpotential value (83 mV at -20 mA cm-2 in 0.5 M H2SO4) and a current density of -3.24, -7.84, -14.80, -30.12 mA cm-2 at 0 V (vs RHE) in Dulbecco's Phosphate-Buffered Saline (DPBS), artificial sea water (ASW), 0.5 M H2SO4 and 1 M KOH, respectively. To the best of our knowledge, these are the highest reported current densities at this low potential value, showing intrinsic catalytic activity of the synthesized material. Also, the catalyst was found to deliver a high and stable current density of -1000 mA cm-2 at an overpotential of just 317 mV. Moreover, the synthesized catalyst delivered a constant current density of -30 mA cm-2 for 24 h without any noticeable change in potential at -0.2 V. These attributes confer our synthesized catalyst to be used for renewable fuel production and applications.

Needle stick injuries among nurses of two tertiary care hospitals of Lahore: A KAP study.

OBJECTIVE: To estimate the prevalence of needle-stick injuries in female nurses of a public and private hospital and compare the findings. METHODS: This cross-sectional study was conducted at one public and one private tertiary care hospital in Lahore, Pakistan, from March to June 2015, and comprised female nurses who were selected using non-probability purposive sampling. A structured questionnaire was used to interview the subjects. Data analysis was done using SPSS 17. RESULTS: Of the 386 participants, there were 193(50%) from each of the two hospitals. The prevalence of needle-stick injuries was found to be 85(44%) in public and 51(26.4%) in the private hospital. The highest proportion of injuries in both hospitals occurred while disposing or recapping needles, 36(42.4%) and 32(62.7 %) in public and private hospitals, respectively, especially in the morning shift, i.e. 42(49.4%) in public and 32(62.7%) in private hospital. Syringe needles were mostly involved, 51(60%) in public and 45(88.2%) in private hospital. CONCLUSIONS: The prevalence of needle-stick injuries was higher in public hospital.

Risk of Mortality Associated With QT and JT Intervals at Different Levels of QRS Duration (from the Third National Health and Nutrition Examination Survey).

QT prolongation in the setting of QRS >120 ms is believed to be triggered by prolonged depolarization rather than repolarization. Hence, JT interval is suggested as an alternative to QT interval when QRS duration is prolonged. It is unclear, however, if JT and QT intervals portend similar risk of mortality for different durations of QRS. We examined the association between QT and JT, separately, with all-cause mortality across different levels of QRS duration in 8,025 participants (60 ± 13 years, 41% white and 54% women) from the Third National Health and Nutrition Examination Survey. At baseline (1986 to 1994), 486 participants (6%) had QRS duration ≥120 ms. During a follow-up of up to 18 years, 3,045 deaths (38%) occurred. There were significant nonlinear relations of QT and JT intervals with mortality (p <0.001). Hence, QT and JT were categorized as prolonged (>95th percentile), shortened (<5th percentile), and normal (reference group). In multivariate-adjusted Cox regression models, prolonged JT (hazard ratio [HR] 4.75, 95% confidence interval [CI] 1.86 to 12.11) was associated with increased risk of mortality more than prolonged QT (HR 1.50, 95% CI 1.03 to 2.17) in participants with QRS ≥120 ms (interaction p = 0.02). In participants with QRS duration <120 ms, prolonged QT and JT were equally predictive of all-cause mortality (HR 1.27, 95% CI 1.06 to 1.54, and HR 1.31, 95% CI 1.10 to 1.55, respectively). Similar patterns were observed with shortened QT and JT intervals. In conclusion, although both QT and JT intervals are predictive of mortality, JT is more predictive in the setting of QRS duration >120 ms supporting the use of JT interval in patients with prolonged QRS.