Predicted Value Research Articles

Validation of Noninvasive Assessment of Pulmonary Gas Exchange in Patients with Chronic Obstructive Pulmonary Disease during Initial Exposure to High Altitude.

Investigation of pulmonary gas exchange efficacy usually requires arterial blood gas analysis (aBGA) to determine arterial partial pressure of oxygen (mPaO2) and compute the Riley alveolar-to-arterial oxygen difference (A-aDO2); that is a demanding and invasive procedure. A noninvasive approach (AGM100), allowing the calculation of PaO2 (cPaO2) derived from pulse oximetry (SpO2), has been developed, but this has not been validated in a large cohort of chronic obstructive pulmonary disease (COPD) patients. Our aim was to conduct a validation study of the AG100 in hypoxemic moderate-to-severe COPD. Concurrent measurements of cPaO2 (AGM100) and mPaO2 (EPOC, portable aBGA device) were performed in 131 moderate-to-severe COPD patients (mean ±SD FEV1: 60 ± 10% of predicted value) and low-altitude residents, becoming hypoxemic (i.e., SpO2 < 94%) during a short stay at 3100 m (Too-Ashu, Kyrgyzstan). Agreements between cPaO2 (AGM100) and mPaO2 (EPOC) and between the O2-deficit (calculated as the difference between end-tidal pressure of O2 and cPaO2 by the AGM100) and Riley A-aDO2 were assessed. Mean bias (±SD) between cPaO2 and mPaO2 was 2.0 ± 4.6 mmHg (95% Confidence Interval (CI): 1.2 to 2.8 mmHg) with 95% limits of agreement (LoA): -7.1 to 11.1 mmHg. In multivariable analysis, larger body mass index (p = 0.046), an increase in SpO2 (p < 0.001), and an increase in PaCO2-PETCO2 difference (p < 0.001) were associated with imprecision (i.e., the discrepancy between cPaO2 and mPaO2). The positive predictive value of cPaO2 to detect severe hypoxemia (i.e., PaO2 ≤ 55 mmHg) was 0.94 (95% CI: 0.87 to 0.98) with a positive likelihood ratio of 3.77 (95% CI: 1.71 to 8.33). The mean bias between O2-deficit and A-aDO2 was 6.2 ± 5.5 mmHg (95% CI: 5.3 to 7.2 mmHg; 95%LoA: -4.5 to 17.0 mmHg). AGM100 provided an accurate estimate of PaO2 in hypoxemic patients with COPD, but the precision for individual values was modest. This device is promising for noninvasive assessment of pulmonary gas exchange efficacy in COPD patients.

Reduced volume of diabetic pancreatic islets in rodents detected by synchrotron X-ray phase-contrast microtomography and deep learning network

The pancreatic islet is a highly structured micro-organ that produces insulin in response to rising blood glucose. Here we develop a label-free and automatic imaging approach to visualize the islets in situ in diabetic rodents by the synchrotron radiation X-ray phase-contrast microtomography (SRμCT) at the ID17 station of the European Synchrotron Radiation Facility. The large-size images (3.2mm×15.97mm) were acquired in the pancreas in STZ-treated mice and diabetic GK rats. Each pancreas was dissected by 3000 reconstructed images. The image datasets were further analysed by a self-developed deep learning method, AA-Net. All islets in the pancreas were segmented and visualized by the three-dimension (3D) reconstruction. After quantifying the volumes of the islets, we found that the number of larger islets (=>1500 μm3) was reduced by 2-fold (wt 1004±94 vs GK 419±122, P<0.001) in chronically developed diabetic GK rat, while in STZ-treated diabetic mouse the large islets were decreased by half (189±33 vs 90±29, P<0.001) compared to the untreated mice. Our study provides a label-free tool for detecting and quantifying pancreatic islets in situ. It implies the possibility of monitoring the state of pancreatic islets in vivo diabetes without labelling.

Comparison of ultrasonography and conventional radiography in the diagnosis of extremity fractures in the emergency department

Objective: The purpose of the study is to compare the diagnostic accuracy (sensitivity and specificity) of ultrasonography (USG) with that of conventional radiography (CR), the standard imaging modality used to diagnose acute extremities fractures.&#x0D; Materials and Methods: The prospective investigation examined 245 patients with clinical symptoms of an extremity fracture. Radiography (anteroposterior and lateral radiographs for each patient, oblique if necessary) and USG were performed on all participants and compared with all the results.&#x0D; Results: CR verified 98.5% of 132 patients who were determined to have extremities fractures with USG. CR, on the other hand, confirmed 99.1% of 112 patients who were reported to have no extremities fractures by USG. The sensitivity (detection of fractures based on USG of patients with fractures detected based on the CR imaging) was 99.2% (95%CI=95.8-99.9); selectivity (no fracture was detected based on USG of patients with no fracture detected based on the CR imaging) was 98.2% (95%CI=93.8-99.7); the positive predictability was 98.48% (95%CI=94.2-99.6), whereas the negative predictability value was 99.1%(95%CI=94-99.8).&#x0D; Conclusion: USG and CR showed similar diagnostic performances in the diagnosis of extremity fractures. USG can be considered an alternative to CR in the examination of extremity fractures with comparable diagnostic performance.

Application of the TNO multi-energy and Baker-Strehlow-Tang methods to predict hydrogen explosion effects from small-scale experiments

Analytical models or abacus are of importance to predict explosion effects in open and congested areas for industrial safety reasons. The goal of this work is to compare overpressure and flame speed values of small-scale deflagration experiments to predicted values from the TNO multi-energy (TNO ME) method and the Baker-Strehlow-Tang (BST) method. Experiments were performed in cylindrical congested volumes of hydrogen – air mixtures varying from 1.77 L to 7.07 L. The reactivity was controlled by the equivalence ratio of hydrogen-air mixtures, ranging from 0.5 to 2.5. The congestion was realized with varying numbers of grid layers and configurations. The influence of the obstacle density and the importance of the mixture reactivity to choose the strength index in order to predict the effects of an explosion has been highlighted for the TNO ME method. Predictive flame speed values from the BST method are in accordance with almost half of the experimental results and the method is conservative in most tested configurations. The use of the TNO ME method has been validated on a small-scale experiment to predict maximal overpressures generated by the deflagration of medium and large-scale H2/air clouds.

Predicting physicochemical properties of melon (Cucumis melo L.) using ultrasonic technology and artificial neural network

As one of the favorite fruits widely produced and consumed in Indonesia, quality testing for melon (Cucumis melo L.) fruit is mostly done using destructive testing. To overcome this problem, this study aims to predict physicochemical quality properties of melon fruit non-destructively using ultrasonic and artificial neural network (ANN). Fifty-nine Hami melons were tested to measure the attenuation value of ultrasonic wave emission as a non-destructive variable, along with density and age. Then, destructive testing was conducted to measure physicochemical properties consisting of fruit flesh firmness, total soluble solids (TSS), titratable acidity (TA), pH, and vitamin C. The test data obtained were processed using ANN to acquire prediction models, with non-destructive data as input variables and each destructive data as output variable. The results showed that the prediction values were still not accurate. Reliability analysis conducted on the test data set based on R2 values (R2 ) and Normalized Root Mean Squared Error (NRMSE) values showed that the predicted values were still unreliable with R2 values that were still very low, ranging from -0.776 to 0.485, although the NRMSE value was relatively good.

Utility of Lung Ultrasound in Diagnosis of Respiratory Distress Syndrome in Neonates: A Cross-sectional Study

Introduction: Respiratory Distress Syndrome (RDS) is one of the most common conditions leading to significant morbidity and mortality. Early diagnosis with a non-invasive imaging tool such as ultrasound, with no radiation hazard will be beneficial for timely intervention in neonates. Aim: To evaluate the utility of Lung Ultrasound (LUS) in diagnosing RDS in neonates and to compare it with chest X-ray (CXR). Materials and Methods: A cross-sectional study was conducted at a tertiary care hospital in Department of Pediatrics, AJ Institute of Medical Sciences, Mangalore, Karnataka, India, from June 2017 to December 2018. Forty neonates (preterm and term) admitted to Neonatal Intensive Care Unit (NICU) with symptoms of respiratory distress within six hours of life and fulfilling clinical criteria of RDS were included in the study. CXR and LUS were performed and interpreted by the same radiologist. The disease was graded as mild and severe by LUS based on the indices like B (Beam like comet-tail pattern) lines, alveolar consolidation, air bronchogram and white lung and it was compared with CXR in terms of sensitivity and specificity to diagnose RDS. Data were statistically analysed using Kendall’s tau-b test. Results: Eighteen (45%) neonates were &lt;32 weeks, 19 (47%), between 32-34 weeks and 3 (7.5%) were &gt;34 weeks of gestation. Twenty-six (65%) were males and 14 (35%) were females. Mean gestational age of the study cohort was 32±2 weeks. Mean birth weight in the study group was 1.7±0.5 kg. 14 out of the 40 neonates (65%) received steroids prior to delivery. LUS detected signs of RDS in all the 40 cases (100% sensitivity). Sixteen out of 40 (40%) neonates were graded as mild RDS and 24 out of 40 neonates (60%) as severe RDS. The sensitivity to detect severe cases was 100% when compared to CXR but specificity to detect mild cases was found to be 59%. The Positive Predictability Value (PPV) was found to be 54% and the Negative Predictable Value (NPV) was found to be 100%. Conclusion: LUS can be used as a reliable, bed side screening tool for the early diagnosis of RDS in NICU without side-effects of radiation.

Sustainability of Pod Yields of Groundnut through Crop Seasonal Rainfall, Length of Growing Period and Cultivated Area under Arid Alfisols of Anantapur in South India

A study was conducted with the objective of assessing the effect of crop seasonal rainfall and length of growing period on the sustainability of pod yields of groundnut attained in 31 mandals under arid Alfisols of Anantapur in Andhra Pradesh. We have considered the variability of mandals with regard to (i) crop seasonal rainfall (mm) and (ii) pod yield of groundnut (kg/ha) during 2001 to 2020; (iii) extent of crop area (ha) during 2009 to 2020; and (iv) length of growing period (days). Based on the mean and standard deviation (SD) of each parameter, the mandals were classified into 5 groups viz., (i) G1: Less than (Mean–2SD); (ii) G2: (Mean–2SD) to (Mean–SD); (iii) G3: (Mean–SD) to (Mean+SD); (iv) G4: (Mean+SD) to (Mean+2SD); and (v) G5: More than (Mean+2SD). Out of 31 mandals, 22 mandals for area and crop seasonal rainfall, 20 mandals for LGP and 18 mandals for yield have fallen in G3. Estimates of correlation were derived between groundnut area, crop seasonal rainfall and yield for each mandal over years and tested for significance to assess the superiority of mandals. Significant correlation of yield and crop seasonal rainfall was observed which ranged from 0.433 at Kalyandurg to 0.765 at Putlur. Similarly, significant correlation between yield and area of groundnut was observed in Kalyandurg (-0.764), Brahmasamudram (-0.674) and Rapthadu (-0.584) mandals. The predictability of yield and prediction error were derived based on a regression model of yield calibrated through the crop seasonal rainfall, LGP and crop area in different mandals. The model gave significant predictability (R2 ) value of 0.46 with prediction error of 90.9 kg/ha and indicated negative effect of area, positive effect of crop seasonal rainfall and LGP on yield. The sustainability yield index ranged from 26.6% (Kambadur) to 87.5% (Peddavadagur) with mean of 53.9% (CV of 30.1%) over years. Ranks were assigned to the mean and variation of area, crop seasonal rainfall, yield, LGP and SYI of each mandal and rank sums were derived. Guntakal, Gooty and Vidapanakal were superior with rank sums of 30, 38 and 70 respectively. Guntakal was superior with an area of 16570 ha (CV of 17.3%), crop seasonal rainfall of 436.1 mm (CV of 33.4%), LGP of 140 days, yield of 644 kg/ha (CV of 70.9%) and SYI of 76.5%, while Gooty was superior with area of 14146 ha (CV of 14.6%), crop seasonal rainfall of 429.6 mm (CV of 42.4%), LGP of 140 days, yield of 663 kg/ha (CV of 69.1%) and SYI of 79.1%. Similarly, Vidapanakal was superior with area of 5077 ha (CV of 31.1%), crop seasonal rainfall of 403.2 mm (CV of 47.4%), LGP of 140 days, yield of 654 kg/ha (CV of 49.5%) and SYI of 77.9%. Due to maximum LGP and crop seasonal rainfall, we recommend that the farmers of these mandals could enhance the area of groundnut and attain maximum sustainable yields under arid Alfisols.

Friction stir-welding of AZ31B Mg and 6061-T6 Al alloys optimization using Box-Behnken design (BBD) and Artificial Neural network (ANN)

The primary goal of the study is to optimize the welding parameters using Friction Stir Welding (FSW) to join AZ31B Mg and AA 6061 alloys considering input parameters such as rotational speed, welding speed, shoulder-to-pin diameter ratio and plunge force and output parameters as peak temperature. The simulation experiment is carried out using COMSOL Multiphysics® 6.0 Software. The simulation experiment is designed using the Box-Behnken design (BBD) of Response Surface Methodology (RSM) and mathematical models were developed. The Analysis of Variance (ANOVA) is used to assess the features of the performance effectiveness of the parameters. Both direct and indirect interaction effects are investigated; the results indicate that the rotational speed is the most influential parameter when compared to other factors; as rotational speed increases consequently; there is an increase in temperature. Finally, the Artificial Neural Network was trained and tested in MATLAB software to optimize the parameters. The validation was performed to predict the minimal predicted temperature value. The confirmatory tests reveal that the predicted results are extremely close to the experimental values from the simulation.

Prevalence of hypertension links with body mass index by academic population in Babylon city.

Many risk factors have been listed that predispose to the occurrence of high blood pressure (BP). Although high body mass index (BMI) is a recognized risk factor for hypertension, the cutoff value for the high BMI was not taken into consideration as a predictor risk. There is no clear data on the occurrence of hypertension in Iraq in the highly educated population. Moreover, studies on hypertension in Iraq have been limited to a few studies. To assess and study the prevalence of BP in the academic population of Babylon city, a prospective study of 100 people was conducted. In the course of 3 months, during their work at the university in the morning, the questionnaire was filled out along with the body weight measurement. The receiver operating characteristic curve was used to measure the maximum area under the curve for the BMI score. Outcomes demonstrated that despite the high level of education, the prevalence of hypertension remains unacceptable. Awareness raising about the risk factors should be addressed through ongoing health education in health sectors and media. BMI of more than 25 could be considered a predictable risk value.

Application of a self-propelled autonomous aquatic robot for environmental education

Environmental protection in education poses challenges for both teachers and students due to its multidisciplinary nature, involving data acquisition, transfer, data structuring, virtual environment deployment, database access, and data protection. These complexities hinder the preparation of course assignments, and using simulations and modeling as a substitute for technical performance is not recommended for pedagogical reasons. Employing a mobile robot as a data source offers several advantages. Firstly, the data acquisition process becomes transparent, as sensor readings align with intuitively predictable values based on the robot’s trajectory. Secondly, a coherent data structure is formed, connecting diverse data types such as time stamps, coordinates, and sensor readings (e.g., temperature, air and water quality, lighting, distance). Thirdly, the solution’s applicability for environmental monitoring purposes can be easily demonstrated. This study proposes the development of an environmental monitoring solution that employs a self-propelled robot (driving, floating, flying) to obtain readings of environmental parameters. The proposed project solution in education provides many opportunities in data acquisition, processing, transfer, visualization and opens the field for interpretations.

Predicting proximate composition of mutton by fourier transform-near infrared spectroscopy

A study was conducted to predict the proximate composition viz., moisture, crude protein, crude fat and total ash contents of mutton by Fourier transform-near infrared (FT-NIR) spectroscopy.Atotal of 200 longissimus dorsi muscle samples of mutton were collected from the retail meat outlets in and around Chennai in of September, 2020. The correlation coefficient ((R2)between true (conventional) and prediction (FT-NIR) values for moisture, crude protein, crude fat and total ash in mutton were 0.98, 0.98, 0.89, and 0.84, respectively. The root mean square errors of cross-validation (RMSECV) were 0.106, 0.095, 0.188 and 0.034, respectively. Ratios of prediction to deviation (RPD) were 7.80, 8.08, 3.15 and 2.53, respectively. Nonsignificant (P>0.05) difference was observed between the true and predicted values for all the proximate composition. It was concluded that FT-NIR spectroscopy canbeusedas a promisingtoolforassessing theproximate composition of mutton.

Analysis of University Professors’ Digital Teaching Competence

Digital competence for teaching is the set of values, abilities, skills, and attitudes that allow the proper implementation of the teaching-learning process during online education. This study analyzed digital teaching competence in professors from two different university contexts concerning sociodemographic and academic variables in June 2021. This research had a quantitative approach, classified as non-experimental, analytical, and cross-sectional. The population comprised 79 professors from the Faculty of Health Sciences, National University of Chimborazo, Ecuador, as well as 35 from the Faculty of Educational Sciences, University of Granada, Spain. The data were collected using the Online Tutor Functions and Competencies Scale. There were statistically significant differences in the specific competence related to socialization activities regarding the university where the participants were teaching (p = 0.018) and experience as a professor (p = 0.028). Results of the global competence indicated significant differences according to the time of experience in teaching and preferred teaching modality. A significant association was established between the variables related to academic components and the global competence for digital teaching. The R 2 values indicated a low level of goodness of fit, with a higher percentage favoring the forecast level. The preferred teaching modality had a significant predictability value, but its odds ratio showed that it did not condition the state of global competence for digital teaching. The study innovated using binary logistic regression to analyze the predictive capacity of specific dimensions regarding digital competence in higher education settings. Keywords: digital competence, higher education, digital teaching. DOI: https://doi.org/10.55463/hkjss.issn.1021-3619.60.81

PS-C35-8: ESTIMATING A MODEL FOR 24-HOUR URINARY SODIUM EXCRETION FROM SPOT URINE SODIUM AND CREATININE OF BANGLADESHI POPULATION

Background: The best estimate of population distribution and the average level of dietary salt intake is provided by measuring 24hour urinary sodium (Na) excretion in a representative sample. Collection of 24hour urine is difficult for community living people, and therefore, use of the spot urine Na concentration for estimation of daily salt intake was proposed as an alternative to 24hour urine collection. Purpose: To develop and validate equations to estimate the population mean levels of 24hour urinary Na excretion from spot urine Na for a Bangladeshi population. Methods: We utilized a dataset in which estimates of urinary Na levels were available from urine samples from 24hour urine collection and from spot urine of 217 participants, aged 40 to 59 years. We developed formulas to estimate 24hour urinary Na (24HUNa) by using 24hour urinary Creatinine (24HUCr), spot urine Na (SUNa), and spot urine creatinine (SUCr). For the reliability and validity tests of developed formulas, we use another dataset of 517 participants, aged 30 to 59 years, that also contains Na levels from urine samples from 24hour urine collection and from spot urine collection. Results: The obtained formulas were as follows: (i) PRCr (mg/day) = − 6.68 × age (year) + 14.68 × weight (kg) + 23.89 × height (cm) − 3198.18; (ii) estimated 24HUNa (mmol/day) = 42.40 × XNa0.270; where PRCr = predicted value of 24HUCr, XNa = SUNa (mmol/L)/SUCr (mg/L) × PRCr (mg/day). The correlation coefficients of Na (mmol/day) between estimated and measured from 24hour urine sample were 0.477, which was statistically highly significant (p &lt; 0.001). The mean difference (bias) between estimated and measured Na (mmol/day) was 2.9, which was not statistically significant (p &gt; 0.05). Intraclass correlation coefficient (ICC) between estimated and measured 24HUNa was 0.502. Conclusions: These formulas are useful for estimating population mean levels of 24hour urinary Na excretion, though this method is not suitable for estimating individual Na excretion.

EFFICACY OF NAVIGATOR-TRIGGERED PACE TECHNIQUE MRCP IN CHOLEDOCHOLITHIASIS

Aim: The navigator-triggered Prospective Acquisition Correction Enhancement technique is a method used to eliminate respiratory motion artifacts caused in magnetic resonance cholangiopancreatography examinations. The purpose of this study was to compare the diagnostic accuracy of navigator-triggered Prospective Acquisition Correction Enhancement tecnique magnetic resonance cholangiopancreatography examination with endoscopic retrograde cholangiopancreatography as a gold standard reference in presence of choledocholithiasis. &#x0D; Materıal and Method: The diagnostic rates of magnetic resonance cholangiopancreatography examination performed with Prospective Acquisition Correction Enhancement technique in the diagnosis of choledocholithiasis were compared according to the results of the endoscopic retrograde cholangiopancreatography examination, which was accepted as a gold standard reference. &#x0D; Results: Among 107 patients included in the study, 40 patients with magnetic resonance cholangiopancreatography and 36 patients with endoscopic retrograde cholangiopancreatography were diagnosed with choledocholithiasis. endoscopic retrograde cholangiopancreatography showed the presence of choledocholithiasis in 36 patients among 40 patients diagnosed as choledocholithiasis with magnetic resonance cholangiopancreatography. The positive predictivity value of the magnetic resonance cholangiopancreatography examination performed with the Prospective Acquisition Correction Enhancement technique was 90%, the negative predictivity value was 98.5%, the sensitivity was 97.3%, the specificity was 94.3%, and the diagnostic accuracy was 95.3%. &#x0D; Conclusıon: We think that navigator-triggered magnetic resonance cholangiopancreatography examination obtained with Prospective Acquisition Correction Enhancement technique is a reliable method with high accuracy in the diagnosis of choledocholithiasis.

Predictive value of SYNTAX-Ⅱ score on prognosis of patients with chronic total occlusion undergoing percutaneous coronary intervention

Objective: To investigate the predictive value of SYNTAX-Ⅱ score on long term prognosis of patients diagnosed with chronic total occlusion (CTO) and received percutaneous coronary intervention (PCI). Methods: Patients undergoing CTO-PCI in Fuwai hospital from January 2010 to December 2013 were enrolled in this retrospective analysis. The SYNTAX-Ⅱ score of the patients was calculated. According to SYNTAX-Ⅱ score tertiles, patients were stratified as follows: SYNTAX-Ⅱ≤20, 20<SYNTAX-Ⅱ≤27, SYNTAX-Ⅱ>27. Primary endpoint was major adverse cardiac events (MACCE), including all-cause death, myocardial infarction, stroke and any revascularization. Secondary endpoints included stent thrombosis, heart failure and target lesion failure (TLF). Patients were followed up by outpatient visit or telephone call at 1 month, 6 months and 1 year after PCI, and annually up to 5 years. Multivariate Cox regression model was used to analyze the independent risk factors of all-cause death in patients undergoing CTO-PCI. The predictive value of SYNTAX score with SYNTAX-Ⅱ score for all-cause death was evaluated by the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Results: A total of 2 391 patients with CTO and received PCI were enrolled in this study. The mean age was (57.0±10.5) years, 1 994 (83.40%) patients were male. There were 802 patients in lower tertile group (SYNTAX-Ⅱ≤20), 798 patients in intermediate group (20<SYNTAX-Ⅱ≤27) and 791 patients in upper tertile group (SYNTAX-Ⅱ>27). At the end of 5-year follow-up, the loss to follow-up rate of the three groups was 9.10%(73/802), 10.78%(86/798)and 8.85%(70/791), respectively. The rate of all-cause mortality (1.78% (13/729) vs. 3.65% (26/712) vs. 9.02% (65/721), P<0.001), cardiac death (1.37% (10/729) vs. 2.11% (15/712) vs. 4.85% (35/721), P<0.001), target vessel myocardial infarctions (4.25% (31/729) vs. 4.49% (32/712) vs. 7.07% (51/721), P=0.03), probable stent thrombosis (1.51% (11/729) vs. 2.81% (20/712) vs. 3.61% (26/721), P=0.04) and heart failure (1.78% (13/729) vs. 1.97% (14/712) vs. 5.41% (39/721), P<0.001) increased in proportion to increasing SYNTAX-Ⅱ score (all P<0.05). Multivariable Cox regression analysis indicated that female (HR=2.05, 95%CI 1.12-3.73, P=0.01), left ventricular ejection fraction (HR=0.97, 95%CI 0.95-1.00, P=0.05) and SYNTAX-Ⅱ score (HR=1.07, 95%CI 1.02-1.11,P=0.01) were independent predictors for all-cause mortality in patients undergoing CTO-PCI. The predicted value of the SYNTAX-Ⅱ score for all-cause death was significantly higher than the SYNTAX score (AUC 0.71 vs. 0.60, P=0.003). Conclusion: For CTO patients who underwent percutaneous coronary intervention, SYNTAX-Ⅱ score is an independent predictor for 5-year all-cause death, and SYNTAX-Ⅱ serves as an important predictor for all-cause death in these patients.

Stacking ensemble learning models for daily runoff prediction using 1D and 2D CNNs

In recent years, applications of convolutional neural networks (CNNs) to runoff prediction have received some attention due to their excellent feature extraction capabilities. However, existing studies are still limited since merely either 1D or 2D CNNs are developed to predict runoff. In this study, a stacking ensemble learning model for daily runoff prediction based on different types of 1D and 2D CNNs is proposed and applied to the Quinebaug River Basin, Connecticut, USA. The structure of the CNN models is developed with reference to the classic LeNet5 network. Especially, the predictors are reconstructed into 1D vectors and 2D matrices with 10-, 20- and 30-day time steps. Totally 18 member models are constructed through selecting 3 representative 1D and 2D CNN models with 3 time steps. The simple average method (SAM) is used to integrate different CNN member models. The results show that the performance of the same-type SAM based on either 1D or 2D CNNs improves because it can counteract the effects of both positive and negative predicted values by the member models to some extent. Furthermore, the mixed-type SAM models based on both 1D and 2D CNN member models can further improve the prediction accuracy. The optimal model SAM15 consists of two 1D CNNs and four 2D CNNs. Compared with the optimal CNN member models, SAM15 reduces the validation RMSE by about 13% and improves the validation R and NSE by about 3% and 7%, respectively. This study highlights that the proposed stacking ensemble learning model can improve the daily runoff prediction accuracy through integration of the nonlinear fitting ability of 1D and 2D CNN member models.

The relationship between dimensions of empathy and symptoms of depression among university students during the COVID-19 pandemic: A network analysis.

The relationship between different dimensions of empathy and individual symptoms of depression during the COVID-19 pandemic remains unclear, despite the established link between empathy and depression. The network analysis offers a novel framework for visualizing the association between empathy and depression as a complex system consisting of interacting nodes. In this study, we investigated the nuanced associations between different dimensions of empathy and individual symptoms of depression using a network model during the pandemic. 1,177 students completed the Chinese version of the Interpersonal Reactivity Index (IRI), measuring dimensions of empathy, and the Chinese version of the Patient Health Questionnaire-9 (PHQ-9), measuring symptoms of depression. First, we investigated the nuanced associations between different dimensions of empathy and individual depressive symptoms. Then, we calculated the bridge expected influence to examine how different dimensions of empathy may activate or deactivate the symptoms of depression cluster. Finally, we conducted a network comparison test to explore whether network characteristics such as empathy-depression edges and bridge nodes differed between genders. First, our findings showed that personal distress was positively linked to symptoms of depression. These symptoms involved psychomotor agitation or retardation (edge weight = 0.18), sad mood (edge weight = 0.12), trouble with concentrating (edge weight = 0.11), and guilt (edge weight = 0.10). Perspective-taking was found to be negatively correlated with trouble with concentrating (edge weight = -0.11). Empathic concern was negatively associated with suicidal thoughts (edge weight = -0.10) and psychomotor agitation or retardation (edge weight = -0.08). Fantasy was not connected with any symptoms of depression. Second, personal distress and empathic concern were the most positive and negative influential nodes that bridged empathy and depression (values of bridge expected influence were 0.51 and -0.19 and values of predictability were 0.24 and 0.24, respectively). The estimates of the bridge expected influence on the nodes were adequately stable (correlation stability coefficient = 0.75). Finally, no sex differences in the studied network characteristics were observed. This study applied network analysis to reveal potential pathways between different dimensions of empathy and individual symptoms of depression. The findings supported the existing theoretical system and contribute to the theoretical mechanism. We have also made efforts to suggest interventions and preventions based on personal distress and empathic concern, the two most important dimensions of empathy for depressive symptoms. These efforts may help Chinese university students to adopt better practical methods to overcome symptoms of depression during the COVID-19 pandemic.

Association analysis of apoptosis-related gene caspase3, Integrin a subunit 1 and glutathione sulfur transferase M1 gene polymorphisms and susceptibility to gastric cardia carcinoma.

To explore the association of polymorphisms of apoptosis-linked genes caspase3 (CASP3), integrin a subunit 1 (ITGA1), glutathione sulfur transferase M1 (GSTM1) with susceptibility to gastric cardia carcinoma (GCC). From February 2016 to March 2018, selection of 113 GCC patients was as the gastric cancer (GC), and selection of 75 patients without gastric disease was as the control. Detection of CASP3, ITGA1 and GSTM1 gene polymorphisms in patients' peripheral blood was to analyze their association with GC. Division of the GC was into the good prognosis and the unpleasing prognosis in the light of the survival of patients after surgery of 3 years, and the predictable value of gene polymorphisms of CASP3, ITGA1 and GSTM1 in GCC patients was analyzed. CASP3 gene rs12108497 locus, ITGA1 gene rs1862610 locus and GSTM1 genotype of the GC and the control were in accord with Hardy-Weinberg equilibrium (P > 0.05); The detection rate of CASP3 gene rs12108497 locus TC/CC type, ITGA1's gene rs1862610 locus AC/AA type and GSTM1 blank type in the GC was elevated vs. the control (P < 0.05); Logistic regression analysis manifested smoking, anxiety, helicobacter pylori infection, family history of gastrointestinal tumor, combination with chronic gastric disease, CASP3 gene and GSTM1 gene polymorphism were risk factors for GC (P < 0.05); Stratification was in the light of individual smoking status, discovering that the detection rates of CASP3 gene rs12108497 locus TC/CC type, ITGA1 gene RS1862610 locus AC/AA type and GSTM1 blank type in the smoking were crucially augmented vs. the smoking (P < 0.05); The detection rates of CASP3 gene rs12108497 locus TC/CC type, ITGA1 gene rs1862610 locus AC/AA type and GSTM1 blank type in the death were augmented vs. the survival (P < 0.05); Combined detection of CASP3, ITGA1 and GSTM1 gene polymorphisms was provided with predictive value for GCC's prognosis (P < 0.05). CASP3 and GSTM1 genes are susceptibility genes for GCC, which might be associated with the occurrence of GCC in smoking patients, and the joint detection of multiple genes is provided with predictive value for patients' prognosis.

Soil Geochemical Properties Influencing the Diversity of Bacteria and Archaea in Soils of the Kitezh Lake Area, Antarctica.

It is believed that polar regions are influenced by global warming more significantly, and because polar regions are less affected by human activities, they have certain reference values for future predictions. This study aimed to investigate the effects of climate warming on soil microbial communities in lake areas, taking Kitezh Lake, Antarctica as the research area. Below-peak soil, intertidal soil, and sediment were taken at the sampling sites, and we hypothesized that the diversity and composition of the bacterial and archaeal communities were different among the three sampling sites. Through 16S rDNA sequencing and analysis, bacteria and archaea with high abundance were obtained. Based on canonical correspondence analysis and redundancy analysis, pH and phosphate had a great influence on the bacterial community whereas pH and nitrite had a great influence on the archaeal community. Weighted gene coexpression network analysis was used to find the hub bacteria and archaea related to geochemical factors. The results showed that in addition to pH, phosphate, and nitrite, moisture content, ammonium, nitrate, and total carbon content also play important roles in microbial diversity and structure at different sites by changing the abundance of some key microbiota.

Terrestrial Diet Dependence in an Unprotected Nile Crocodile (Crocodylus niloticus) Population

Nile Crocodile (Crocodylus niloticus) populations that exist outside of protected areas are under threat in South Africa. They are believed to predominantly feed on fish, but they also take prey from the terrestrial system, which brings them into conflict with humans and hampers their management. Here, we use stable light isotope analysis to explore the diet of an unprotected Nile Crocodile population in the Olifants River, Mpumalanga and Limpopo Provinces. Nitrogen stable isotope ratios were obtained from fish and crocodile populations along the length (±430 km) of the river. The catchment is severely polluted with elevated d15N values at nutrient hotspots, which provides a basis for tracking the trophic response of crocodiles to the longitudinal profile of fish d15N values. Crocodiles did not respond to changes in the d15N values of fish populations and dietary predictions based on size-specific diet to tissue discrimination factors suggests a nonaquatic food base. These results suggest terrestrial diet dependence in one of the few viable Nile Crocodile populations from outside protected areas, posing unique challenges to their conservation.