Considered heavy metals, such as As(III), Bi(II), Cd(II), Cr(VI), Mn(II), Mo(II), Ni(II), Pb(II), Sb(III), Se(-II), Zn(II), and contaminating chemical compounds (monocyclic aromatic hydrocarbons such ...as phenolic or polycyclic derivatives) in wastewater (petrochemical industries: oil and gas production plants) are currently a major concern in environmental toxicology due to their toxic effects on aquatic and terrestrial life. In order to maintain biodiversity, hydrosphere ecosystems, and people, it is crucial to remove these heavy metals and polluting chemical compounds from the watery environment. In this study, different Nanoparticles (α-Fe
O
, CuO, and ZnO) were synthesized by green synthesis method using Portulaca oleracea leaf extract and characterized by UV-Vis spectrophotometers, FTIR spectroscopy, X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS) techniques in order to investigate morphology, composition, and crystalline structure of NPs, these were then used as adsorbent for the removal of As(III), Bi(II), Cd(II), Cr(VI), Mn(II), Mo(II), Ni(II), Pb(II), Sb(III), Se(-II), and Zn(II) from wastewater, and removal efficiencies of were obtained 100% under optimal conditions.
The main problem in this research is how the quality management developed at the madrasa diniyah is boarded in the muhammdiyah lamongan pesantren. In accordance with these problems, the objectives of ...this study are (1) how is the quality planning (2) how is the quality program implemented (3) How is quality monitoring and evaluation (4) how is the quality improvement action carried out by boarding muhammadyah lamongan boarding school. The research method uses qualitative methods, with the reason that the questions are open so that researchers can be flexible and can develop questions, because researchers want to describe and analyze the implementation of quality management in Islamic boarding schools in Muhammadiyah dilamongan, Madrasah diniyah Islamic boarding schools in Muhammadiyah Lamongan, the results of the study show that there are several diniyah muhammdiyah Islamic boarding school program in lamongan has developed quality management starting from planning, implementation of monitoring and evaluation as well as follow-up of quality improvement which is very synergic between madrasa and Islamic boarding school so that the existence of madrasa diniyah and pondok pesantren continues to develop. Recommendations, this study recommends that madrash diniyah and lamuh muhammadyah Islamic boarding schools should continue to be quality teamwork in improving quality with structured roles and responsibilities, and become models that can be used as alternative concepts for quality management of madrasa diniyah. Key words: Quality Management , Madrasah diniyah, and Islamic Boarding School Muhammadiyah dilamongan
The novel synthesis of MgO from
Laurus
nobilis
L. leaves was prepared using the green synthesis method. It is using direct blending process to decorate MgO/PEG nanocomposite to enhance the ...photodegradation properties and examine its physical properties using diverse characterization techniques, including XRD, FTIR, SEM, EDX, and UV–Vis. X-ray diffraction reveals a cubic phase of MgO with a 37-nm grain size. SEM images confirm spherical nanoparticles with a diameter size of 22.9 nm. The optical energy gap of MgO NPs was 4.4 eV, and the MgO/PEG nanocomposite was 4.1 eV, which made it an efficient catalyst under sunlight. The photocatalytic activity of Rose Bengal (RB) and Toluidine Blue (TB) dyes at 5 × 10
−5
mol/l dye concentration indicates excellent degradation efficiencies of 98% and 95% in 120 min, respectively, under sunlight irradiation. MgO/PEG is an excellent candidate nanocomposite for applications of photodegradation and could be used for its potential capability to develop conventionally used techniques.
The great attention to gender classification is increasing recently as genders carry rich information related to male and female social activities. Extracting discriminating visual representations ...for gender classification is challenging especially with covered or camouflaged faces. In this work, the authors propose a network that uses a combination of inceptions with variational feature learning (VFL) loss function. The proposed network recognises the gender of normal or covered/camouflaged faces through the middle face part. This network trained on the middle part of the faces that contain both eyes with a small margin from the top-left corner to the bottom-right corner of the area of the eyes. Experimental results showed that the proposed network achieved state-of-art performance on five public data sets: FEI, SCIEN, AR FACES, LFW, and ADIENCE. They also evaluated the authors’ network on another new collected data set for covered and camouflaged faces and obtained encouraging outcomes.
The GALAD score is a serum biomarker-based model that predicts the probability of having hepatocellular carcinoma (HCC) in patients with chronic liver disease. We aimed to assess the performance of ...the GALAD score in comparison with liver ultrasound for detection of HCC.
A single-center cohort of 111 HCC patients and 180 controls with cirrhosis or chronic hepatitis B and a multicenter cohort of 233 early HCC and 412 cirrhosis patients from the Early Detection Research Network (EDRN) phase II HCC Study were analyzed.
The area under the ROC curve (AUC) of the GALAD score for HCC detection was 0.95 95% confidence interval (CI), 0.93-97, which was higher than the AUC of ultrasound (0.82,
<0.01). At a cutoff of -0.76, the GALAD score had a sensitivity of 91% and a specificity of 85% for HCC detection. The AUC of the GALAD score for early-stage HCC detection remained high at 0.92 (95% CI, 0.88-0.96; cutoff -1.18, sensitivity 92%, specificity 79%). The AUC of the GALAD score for HCC detection was 0.88 (95% CI, 0.85-0.91) in the EDRN cohort. The combination of GALAD and ultrasound (GALADUS score) further improved the performance of the GALAD score in the single-center cohort, achieving an AUC of 0.98 (95% CI, 0.96-0.99; cutoff -0.18, sensitivity 95%, specificity 91%).
The performance of the GALAD score was superior to ultrasound for HCC detection. The GALADUS score further enhanced the performance of the GALAD score.
The GALAD score was validated in the United States.
Although significant advances have been made recently in the field of face recognition, these have some limitations, especially when faces are in different poses or have different levels of ...illumination, or when the face is blurred. In this study, we present a system that can directly identify an individual under all conditions by extracting the most important features and using them to identify a person. Our method uses a deep convolutional network that is trained to extract the most important features. A filter is then used to select the most significant of these features by finding features greater than zero, storing their indices, and comparing the features of other identities with the same indices as the original image. Finally, the selected features of each identity in the dataset are subtracted from features of the original image to find the minimum number that refers to that identity. This method gives good results, as we only extract the most important features using the filter to recognize the face in different poses. We achieve state-of-the-art face recognition performance using only half of the 128 bytes per face. The system has an accuracy of 99.7% on the Labeled Faces in the Wild dataset and 94.02% on YouTube Faces DB.
Background and Aims
Statins have been proven to be cytotoxic to human cholangiocarcinoma cells by inhibiting cell division and inducing apoptosis. We aimed to determine the effect of statin use on ...the risk of cancer development and survival in patients with extrahepatic cholangiocarcinoma (ECC), including perihilar cholangiocarcinoma (pCCA) and distal cholangiocarcinoma (dCCA).
Approach and Results
A total of 394 patients with ECC and hyperlipidemia who received care at Mayo Clinic Rochester between 2005 and 2015 were matched by age, sex, race, ethnicity, and residency to 788 controls with hyperlipidemia. Clinical and outcome data were ed. The odds ratios (ORs) for risk and hazard ratios for outcomes were calculated. The mean age and standard deviation (SD) for cases and controls was 65.6 years (13.8). The number of statin users in cases and controls was 73 (19%) and 403 (51%), respectively. Hepatitis C virus infection (OR, 15.84; 95% confidence interval CI, 4.06‐61.87; P < 0.001) was the most significant risk factor for pCCA followed by inflammatory bowel disease and cirrhosis, whereas other liver disease, including biliary stone disease (OR, 4.06; CI, 2.24‐7.36; P < 0.001), was the only significant risk factor for dCCA. Statin use was associated with significantly reduced risk for all ECC (OR, 0.22; CI, 0.16‐0.29) as well as for the subtypes pCCA (OR, 0.3; CI, 0.21‐0.41) and dCCA (OR, 0.06; CI, 0.03‐0.14), all P < 0.0001. Moderate‐intensity dosage was found to decrease the risk of ECC (OR, 0.48; CI, 0.34‐0.67; P < 0.001). Comparing statin ever users to nonusers, patients with dCCA who used statins had significantly overall better survival (hazard ratio = 0.53; CI, 0.29‐0.97; P = 0.04).
Conclusions
This case‐control study suggests that statins decrease the risk of ECC and may improve survival in patients with dCCA. Additional validation studies are warranted.
High-quality, patient-centered care is essential to achieving equity and dignity for individuals with infertility, yet few studies have explored quality of infertility care in sub-Saharan Africa. We ...interviewed 13 non-specialist physicians and 2 medical school faculty to explore experiences in and perceptions of providing infertility care in Greater Accra, Ghana. We used a patient-centered infertility care model to inform our analysis and results. Individualized care and taking time to counsel and emotionally support patients were perceived as the most important things a physician can do to provide quality infertility care. Financial costs and lack of infertility services within a single facility were the most common barriers reported to providing quality infertility care. To the best of our knowledge, our study is the first to explore quality of infertility care provided by physicians in public sector facilities in Ghana, shedding light on existing barriers and identifying strategies for improvement.
In this paper, we present StEduCov, an annotated dataset for the analysis of stances toward online education during the COVID-19 pandemic. StEduCov consists of 16,572 tweets gathered over 15 months, ...from March 2020 to May 2021, using the Twitter API. The tweets were manually annotated into the classes agree, disagreeor neutral. We performed benchmarking on the dataset using state-of-the-art and traditional machine learning models. Specifically, we trained deep learning models—bidirectional encoder representations from transformers, long short-term memory, convolutional neural networks, attention-based biLSTM and Naive Bayes SVM—in addition to naive Bayes, logistic regression, support vector machines, decision trees, K-nearest neighbor and random forest. The average accuracy in the 10-fold cross-validation of these models ranged from 75% to 84.8% and from 52.6% to 68% for binary and multi-class stance classifications, respectively. Performances were affected by high vocabulary overlaps between classes and unreliable transfer learning using deep models pre-trained on general texts in relation to specific domains such as COVID-19 and distance education.
The accurate models of photovoltaic systems are the core of solar energy studies that are describing the system performance and behavior under different operating conditions. The improving of ...photovoltaic models based on optimizing method is recently the main simulation tool to construct I-V and P–V characteristic curves with the aid of system parameters. These parameters are extracted by using powerful optimal techniques that are building-up from datasheet of manufacturers or experimental data. This paper presents a novel proposed photovoltaic model based on Marine Predators Algorithm to estimate the optimal model parameters of solar cells or modules. Also, it can extract parameters of single diode, double diode and three diode models. Moreover, the Route Mean Square Error value between each model computed parameters and measured results of photovoltaic components are considered as the objective function. R.T.C. France Solar Cell, Photowatt-PWP201 and thin-film photovoltaic modules have been implemented to extract parameters for all three previously mentioned models at different irradiance intensities or temperature degrees. The proposed algorithm results of such cells and modules for each diode model are compared with other research works and manufacturer's results. Moreover, the evaluation of proposed algorithm has been presented considering the complexity analysis and statistical tests. The compared results show that, the accuracy of algorithm results is the best and their I-V and P–V characteristic curves are highly coinciding with manufacturer's curves. Therefore, the results of the proposed algorithm are satisfied with high superiority and better reliability to optimize parameters under different operating conditions.
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