bluuebunny/crossref_metadata_2025 huggingface dataset:
Green Synthesis of Copper Nanoparticles Using Withania somnifera and Its Antioxidant and Antibacterial Activity
Authors: Shanmugapriya J. , Reshma C. A. , Srinidhi V. , Harithpriya K. , Ramkumar K. M. , Umpathy Dhamodharan , Gunasekaran Krishnamoorthy , Subashini R.
Published: July 2022

This study employed green chemistry to synthesize copper nanoparticles (CuNPs) using fresh root extract of Withania somnifera. The size, shape, morphology, and stability of resultant CuNPs were investigated by UV‐Vis spectroscopy, FTIR, transmission electron microscopy (TEM), and energy‐dispersive spectrophotometer. Crude extracts were assessed phytochemically to determine the presence of alkaloids, flavonoids, phenols, saponins, steroids, and tannins. The UV‐Vis absorption spectra show maximum absorption at 330 nm, and FTIR showed the presence of biological molecules responsible for reducing Cu+ ions. In TEM and EDS analyses, the average diameter of the synthesized NPs was found to be 6.28 ± 1.13 nm. The crystal structure of synthesized nanoparticle was determined using XRD analysis and showed its peak at 36.34°, 43.33°, 50.47°, and 73.57°, which corresponds to the cubic lattice of copper. The synthesized nanoparticles (NPs) were tested for their in vitro antimicrobial activity against bacterial strains E. coli and S. aureus by the agar well diffusion method which showed higher efficiency against S. aureus. The antioxidant activity of the synthesized NPs was evaluated by DPPH assay, and the percentage of inhibition was found to be 62% at the concentration of 400 μg/ml and the IC50 value was 51.53 μg/ml. The present investigation suggests that the biosynthesized CuNPs showed prominent antibacterial and free radical scavenging potential. The result proved that root extract of W. somnifera could be applied for synthesis of nanoparticle CuNPs with high uniform particle size along with potent biological activity.
Water Inrush Mechanism of Karst Collapse Column in Coal Seam Floor Based on a Variable Mass Seepage Mechanical Model
Authors: Feng Yang , Hai-xiao Lin , Ling-yan Shen , An-zhi Yan , Yong-jiang Wu
Published: July 2022

Water inrush of collapse column in the coal seam floor in the karst area is a frequent hydrogeological disaster, and it is becoming one of the significant hidden dangers threatening the safety of coal mine production in China. Based on the self-developed variable mass seepage test system of broken rock mass, different Talbot gradation seepage tests are carried out in the laboratory. A three-flow field coupled nonlinear seepage model is established based on the variable mass seepage theory and fluid mechanics theory of fractured rock mass. The three flow fields are Darcy laminar flow in the aquifer, variable mass seepage in the collapse column, and Navier-Stokes turbulent flow in the roadway. Combined with a project, a numerical calculation model is established to study the water-conducting channel’s formation process and the fluid flow pattern change. The research achievements indicate that the pore pressure gradient and seepage velocity are both 95% fit with the Forchheimer equation, and the seepage of the broken rock mass conforms to the Forchheimer equation. The seepage and migration of particles caused changes in pressure and flow rate, the pressure at the boundary between the aquifer and the collapse column decreased by 0.26 MPa, and the flow rate increased from 0.01 mm/s to 0.064 mm/s. The formation of the water-conducting channel can be divided into two stages, the seepage channel stage and the water-conducting channel stage. The initial fractures continue to develop with the seepage and migration of particles until the water-conducting channel is formed. At the bottom of the collapse column, the Forchheimer number increases from 0.72 to more than 1, and the flow changes from laminar flow to nonlinear seepage. The Forchheimer number at the center of the collapse column fluctuates between 7.5 and 55 at the top of the collapse column. The research results can be treated as an essential basis and reference for the water inrush control of the collapse column and the reasonable prediction of the water inrush amount.
Dynamic Deduplication Algorithm for Cross-User Duplicate Data in Hybrid Cloud Storage
Authors: Gang Feng , Wei DaHuan
Published: July 2022

The escalating growth of distributed big data in hybrid cloud storage architecture introduces a new set of challenges. Constantly, content enrichment puts pressure on capacity. Nonetheless, the explosion of user data places a significant strain on broadband and storage capacity. Consequently, many cloud storage providers will implement deduplication to compress data, reduce transfer bandwidth, and reduce cloud storage space. In cloud storage systems, it is a data compression and storage optimization method. By locating and removing redundant data, it can save storage space and bandwidth. An MTHDedup deduplication strategy based on the Merkle hash tree is presented in a hybrid cloud environment to address the issue of convergent encryption algorithms being susceptible to brute-force attacks and ciphertext computation time overhead. Merkle hash trees are constructed using additional encryption algorithms to generate encryption keys during file- and block-level deduplication, ensuring that generated ciphertexts are unpredictable. The method is effective against both internal and external brute-force attacks, thereby increasing data security. Our method reduces the computational burden of ciphertext generation and the key storage space, and the performance advantage increases with the number of privilege sets.
Prediction and Analysis of Slope Stability Based on IPSO-SVM Machine Learning Model
Authors: Wang Yu , Du Erxia , Yang Sanqiang , Yu Li
Published: July 2022

In the evaluation and prediction of slope stability, the traditional numerical analysis method, which is over reliant on experience, takes a large amount of computing time and lacks the ability to reflect the fuzzy and nonlinear characteristics of slope parameters well. Considering the above characteristics, this study proposes an improved particle swarm optimization of support vector machine (IPSO-SVM) algorithm model, which combines optimized particle swarm optimization (IPSO) and support vector machine (SVM) and applies it to slope stability prediction. Based on 28 groups of slope engineering data, the stability prediction results of IPSO-SVM, PSO-SVM, and SVM models were compared with real values for analysis. The results show that the maximum relative error of the IPSO-SVM model is only 1.3%, and the average relative error is 1.1%, which is far lower than the prediction error of the PSO-SVM model and SVM model; therefore, the prediction result of IPSO-SVM is the closest to the real value. This method can accurately predict the slope safety factor under the influence of different indexes, and the research results can provide guidance for practical engineering.
Analysis and Prediction of Public Concern and Academic Concern in Middle School Physics
Authors: Liu Pan , Wang Guanyu , Zhao Yulin , Liu Kai , Li Junke
Published: July 2022

Physics in middle school plays an irreplaceable role in cultivating students’ scientific quality and creativity. It occupies an essential position in middle school teaching, which has always been the focus of academia (academic concern) and the public (public concern). The relationship between academic and public concern for physics in middle school has become an important research issue. To solve this problem, this article proposes the Pearson correlation-linear prediction and ARIMA (autoregressive integrated moving average) (PCLA) framework. It consists of four steps. Firstly, PCLA obtains the public concern and academic concern in middle school physics. Secondly, the Pearson correlation between the public concern and academic concern is analysed, and a linear model between the two concerns is established. Thirdly, for better predicting public concern, the evaluation index is used to choose the best model between the ARIMA model and the SARIMA model. Finally, based on the result of the third step and the linear model, academic concern can also be predicted. The results show that the PCLA framework can reflect the relationship between academic concern and public concern for physics in middle school and can accurately predict public concern and academic concern.
Carbohydrate Supplement Impact on Growth Performance, Bacterial Community, and Bacterial Food Quality of Whiteleg Shrimp (Litopenaeus vannamei) under Biofloc System
Authors: Said Mohamed M. , Ahmed Omaima M.
Published: July 2022

Biofloc technology has a high impact on enhancing shrimp production. Suitable supplemented carbohydrates (CHO) could affect the type of microorganisms developed in the system, which reflects on shrimp production, food safety, and public health. Here, we aimed to compare the effects of sugarcane molasses and wheat flour as carbohydrate sources on biofloc technology. That was achieved through measuring the following parameters: water quality, growth performance, feed utilization, floc composition, shrimp whole body composition, microbial community, and biofloc shrimp food bacterial quality. Postlarvae of whiteleg shrimp (Litopenaeus vannamei) with a mean weight (

38.47
±
5.8
 
mg

) were stocked at a density of 200 individuals/m2 and cultured under a biofloc system for 128 days in six tanks with a total water volume of 30 m2 each. Water quality analysis revealed a better-dissolved oxygen concentration (5.59 mg/L) in the wheat flour treatment, whereas no significant differences were found between the two treatments in ammonia, nitrite, and pH levels. Increased turbidity (64.27 NTU) and floc volume (18.40 mL/L) were recorded with molasses treatment. Growth performance including final weight, weight gain, average daily gain, weight gain per week, and specific growth rate (12.37 g, 12.34 g, 0.096 g/d, 0.68, and 4.70%, respectively) were all significantly higher in the molasses treatment. Wheat flour treatment was associated with a higher survival rate (99%), biomass (71.16 Kg), and biomass increase percentage (395.337) in shrimps. It also improved feed utilization in terms of a lower feed conversion ratio (1.37) and higher protein efficiency ratio (1.92). The chemical composition of biofloc and shrimp whole body were both nutritious higher in wheat flour treatment. In water, total heterotrophic bacterial counts with sugarcane molasses treatment and wheat flour were estimated as

3.4
×

10

5

 
CFU
/
mL

and

1.2
×

10

5

 
CFU
/
mL

, respectively, with no significant difference. In both treatments, beneficial bacteria such as lactic acid bacteria and Enterobacter cloacae were identified in water with the absence of pathogenic Vibrio spp. Wheat flour had a significantly lower total Vibrio-like count (TVC). Shrimps had lower TVC (

1.9
×

10

4

 
CFU
/
g

) with flour than with molasses (

1.32
×

10

5

 
CFU
/
g

). Cronobacter spp. were associated with shrimps in BFT supplemented with molasses, which might pose a potential risk to food safety. In conclusion, the use of wheat flour was the best for shrimp production and shrimp food bacterial quality.
3D Animation Graphic Enhancing Process Effect Simulation Analysis
Authors: Liu Bing , Liu Huiying , Dung Vinh Phuc
Published: July 2022

Processing of graphics is the intermediate stage of an animated film. The adequacy of the preproduction preparation often requires the creators to repeatedly discuss a series of issues such as the story of the script, the structure of the play, the style of the art design and the setting of the scenes, the shape of the characters, and the style of the music. The study of the process of 3D animation graphics enhancing effect optimization can effectively improve the visual effect of images. The optimization of the effect of authenticity of 3D animation graphics requires the optimization of lighting of animation graphics, and the optimization of texture processing of images by extending the shadow map method to complete the optimization of the effect of authenticity of animation graphics. Image enhancement is a very important branch in the field of digital processing of graphics. It is a method of making some transformations to the information or data of an image by some strategy to make the region of interest more prominent in the image while suppressing the secondary information that does not need to be enhanced, with the ultimate goal of making the image conform to the visual response characteristics. It is in this context that this paper proposes to build a process of graphics simulation platform to simulate and analyze the effect of process of 3D animation graphics enhancing. The experimental results show that the enhancement of graphics reduces the running time by 16.5 s and 14.3 s compared to the CDD and FMM algorithms, respectively, and that the MSE and PSNR are both improved, indicating that the enhancement of graphics effectively improves the restoration effect while running quickly. Therefore, it is confirmed that the process of 3D animation graphics enhancing effect has a good balance to obtain a more desirable animation in 3D enhancement effect.
Digital Recognition Methods Based on Deep Learning
Authors: Peng Yuanbo
Published: July 2022

In this paper, the K-nearest neighbor algorithm and the convolutional neural network will be used to train the handwritten digit recognition model, respectively. To establish a reasonable model structure, and through the training data, the model can learn to reflect ten different handwritten number features and finally give the probability of predicting number corresponding to the likelihood of each number. Taking the learning process of the handwritten numeral recognition algorithm based on deep learning as a clue, from deep learning to convolutional neural network, from simple to deep, the relevant basic concepts, model construction, and training process of deep learning are learned and understood. Finally, the deep learning framework uses MNIST as the training dataset to train a model with high recognition rate and then combines it with Open CV technology to realize the identification of handwritten numbers. A reasonable model structure is used to accurately identify the handwritten numbers in the test set. The neural network of deep learning is established with TensorFlow to realize the classification and recognition of handwritten numbers. Various deep learning methods such as CNN and KNN are learned and compared to complete the construction of deep learning architecture. The MNIST dataset was preprocessed, features extracted, and identified. The program is to complete the training of neural network and the recognition of numbers in the image, the recognition results of deep learning methods used are counted and analyzed, and the recognition rates of two different methods are compared to find ways to optimize these methods and improve the recognition rate.
And-1 Coordinates with the FANCM Complex to Regulate Fanconi Anemia Signaling and Cisplatin Resistance
Authors: Zhang Yi , Li Jing , Zhou Yuan , Li Zhuqing , Peng Changmin , Pei Huadong , Zhu Wenge
Published: July 2022

The Fanconi anemia (FA) pathway is essential for repairing DNA interstrand crosslinks (ICL). ICLs induce stalled DNA replication forks and trigger activation of the FA pathway by promoting recruitment of the FANCM/FAAP24/MHF complex to ICL sites. Given that stalled replication forks are proximal to ICL sites, fork-associated proteins may coordinate with FA factors to rapidly sense ICLs for activation of FA signaling. Here we report that And-1, a replisome protein, is critical for activation of the FA pathway by sensing ICL-stalled forks and recruiting the FANCM/FAAP24 complex to ICLs. In response to ICLs, And-1 rapidly accumulated at ICL-stalled forks in a manner dependent on ataxia telangiectasia and Rad3-related protein–induced phosphorylation at T826. And-1 phosphorylation triggered an intramolecular change that promoted the interaction of And-1 with FANCM/FAAP24, resulting in recruitment of the FANCM/FAAP24 complex to ICLs. Furthermore, p-T826 And-1 was elevated in cisplatin-resistant ovarian cancer cells, and activated And-1 contributed to cisplatin resistance. Collectively, these studies elucidate a mechanism by which And-1 regulates FA signaling and identify And-1 as a potential target for developing therapeutic approaches to treat platinum-resistant ovarian cancer.

Significance:

This work shows that phosphorylation of And-1 by ATR activates Fanconi anemia signaling at interstrand crosslink–stalled replication forks by recruiting the FANCM/FAAP24 complex, revealing And-1 as a potential therapeutic target in cancer.
Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia
Authors: Jin Peng , Jin Qiqi , Wang Xiaoling , Zhao Ming , Dong Fangyi , Jiang Ge , Li Zeyi , Shen Jie , Zhang Wei , Wu Shishuang , Li Ran , Zhang Yunxiang , Li Xiaoyang , Li Junmin
Published: July 2022

Purpose:

The molecular complexity of acute myeloid leukemia (AML) presents a considerable challenge to implementation of clinical genetic testing for accurate risk stratification. Identification of better biomarkers therefore remains a high priority to enable improving established stratification and guiding risk-adapted therapy decisions.

Experimental Design:

We systematically integrated and analyzed the genome-wide CRISPR-Cas9 data from more than 1,000 in vitro and in vivo knockout screens to identify the AML-specific fitness genes. A prognostic fitness score was developed using the sparse regression analysis in a training cohort of 618 cases and validated in five publicly available independent cohorts (n = 1,570) and our RJAML cohort (n = 157) with matched RNA sequencing and targeted gene sequencing performed.

Results:

A total of 280 genes were identified as AML fitness genes and a 16-gene AML fitness (AFG16) score was further generated and displayed highly prognostic power in more than 2,300 patients with AML. The AFG16 score was able to distill downstream consequences of several genetic abnormalities and can substantially improve the European LeukemiaNet classification. The multi-omics data from the RJAML cohort further demonstrated its clinical applicability. Patients with high AFG16 scores had significantly poor response to induction chemotherapy. Ex vivo drug screening indicated that patients with high AFG16 scores were more sensitive to the cell-cycle inhibitors flavopiridol and SNS-032, and exhibited strongly activated cell-cycle signaling.

Conclusions:

Our findings demonstrated the utility of the AFG16 score as a powerful tool for better risk stratification and selecting patients most likely to benefit from chemotherapy and alternative experimental therapies.
The Serum Levels of IL-36 in Patients with Coronary Artery Disease and Their Correlation with the Serum Levels of IL-32, IL-6, TNF-α, and Oxidative Stress
Authors: Kazemian Shakiba , Ahmadi Reza , Rafiei Ali , Azadegan-Dehkordi Fatemeh , Khaledifar Arsalan , Abdollahpour-Alitappeh Meghdad , Bagheri Nader
Published: July 2022

Introduction: Atherosclerosis is a chronic inflammatory process maintained during all stages of the disease by several proinflammatory mediators, such as cytokines and chemokines. Interleukin (IL)-36 cytokines are proinflammatory and have an essential role in innate and adaptive immunity, but the role of IL-36 has not been determined in coronary artery disease (CAD). This study aimed to measure the serum levels of IL-36 in patients with CAD and their association with the serum levels of tumor necrosis factor (TNF)-α, IL-6, and IL-32 and also investigate their correlation with the serum levels of malondialdehyde (MDA) and ferric reducing antioxidant power (FRAP). Methods: A total of 168 subjects (84 CAD and 84 control subjects) were examined in this research. The total serum levels of IL-36 were measured using the enzyme-linked immunosorbent assay (ELISA). Also, some oxidative stress parameters were evaluated by FRAP and MDA assays in the serum. Results: The serum levels of IL-36 and MDA were significantly higher, and FRAP was significantly lower in the CAD group compared to the controls. Furthermore, the serum levels of IL-36, MDA, and FRAP significantly correlated with the CAD group’s cardiac arterial stenosis. Also, the serum levels of IL-36 had a positive and significant correlation with the serum levels of TNF-α, IL-6, IL-32, and biochemical parameters in the CAD group. Conclusion: Higher serum levels of IL-36 and its association with the serum levels of TNF-α, IL-32, and IL-6 may play a key role in the pathogenesis of CAD, leading to an increased risk of clogged arteries and oxidative stress.
A survey of exact motif finding algorithms
Authors: Yousif Ali Basim , Keitan Al-Khafaji Hussein , Abbas Thekra
Published: July 2022

Deoxyribonucleic acid (DNA) motif finding (discovery/mining) in biological chains is the most recent challenging and interesting trend in bioinformatics. It represents a crucial phase in most bioinformatics systems related to unravelling the secrets of gene functions. Despite the efforts made to date to produce robust algorithms, DNA motif finding remains a difficult task for researchers in this field. In general, biological pattern locating algorithms are categorized into two categories: probabilistic and numerical methods. In this paper, we provide a survey of exact DNA motif finding algorithms and their working principles with a suitable comparison among these algorithms to provide an essential step for researchers in this field.
Study of harmonic distortion from variable speed drive and energy saving lamps
Authors: Siregar Yulianta , Khalid Al-Azzawi Waleed , Pane Zulkarnaen , E Parhusip Unedo , Suherman Suherman
Published: July 2022

The power electronic component has been widely used in the current industrial era. It has been considered more efficient than the previous devices as it saves more space and uses less power. One example of power electronic components is the variable speed drive for speed regulation of electric motors in the industrial world. Another application of power electronic components is to be used in energy-saving lamps. The use of power electronic components in these two loads generates harmonic distortion and reduces network power quality. In this paper, the authors analyzed the harmonics in both loads. As a result, the total harmonic distortion (THD) current for four energy-saving lamps is 88.3%. Meanwhile, the THD current at the 50 Hz, 5 A, and variable speed drive is 46.2%. After mixing the two loads, the THD current decreases by around 35%.
Y2O3:Eu3+ concentration and particle size: their impacts on color rendering index and lumen of multi-chip white diodes
Authors: Dang Huu Phuc , Xuan Le Phan
Published: July 2022

Aiming at achieving higher colour standard for multi-chip white light-emitting diode (MCW-LEDs) through the enhancement of their color rendering index (CRI), this article worked on and proposed a novel MCW-LED package using a compound of red phosphor Y2O3:Eu3+. The red phosphors were synthesized and applied to build both protective coating and in-cup phosphor configurations. The CRI of MCW-LED which has high correlated colour heat of 8,500 K was observed to be heightened to 86. Moreover, the scattering of the light when added the red phosphor Y2O3:Eu3+ is demonstrated using Mie-scattering theory, while the influences of the red-light enhancement is analyzed using the law of Lambert-Beer.
Wide area monitoring system control management of the IEEE-14 bus system using least square support vector regression
Authors: Awalin Lilik Jamilatul , Halim Syahirah Abd , Ramli Nor Azuana , Jamaludin Jafferi Bin , Ali Mohd Syukri
Published: July 2022

The wide area monitoring system (WAMS) records and monitors every fault or disturbance that occurs in a power system network using phasor measuring units (PMUs). Extensive monitoring of the condition of the electrical power system can ensure the sustainability of reliable energy. The accuracy of the PMUs placement can be determined using the least square support vector regression (LS-SVR) technique. The primary goal of this study is to assess the level of accuracy of the PMUs placement using mean square error (MSE). First, the IEEE-14 bus system equipped with PMUs was built in Matlab software using Simulink. The MSE of the PMUs was then calculated using the LS-SVR. The results revealed that the lower the MSE, the better the PMUs placement. It was also observed that placing the PMUs on bus 2, bus 6, and bus 9 produced the lowest value of MSE.
Classification of focal liver disease in egyptian patients using ultrasound images and convolutional neural networks
Authors: Abd-ElGhaffar Rania Mohamed , El-Zalabany Mahmoud , El-Din Moustafa Hossam , El-Seddek Mervat
Published: July 2022

Recently, computer-aided diagnostic systems for various diseases have received great attention. One of the latest technologies used is deep learning architectures for analyzing and classifying medical images. In this paper, a new system that uses deep learning to classify three focal diseases in the liver besides the normal liver is proposed. A pre-trained convolutional neural network is utilized. Two types of networks are used, ResNet50 and AlexNet with fully connected networks (FCNs). After extracting the deep features using deep learning, FCNs can input images in different states of the disease, such as Normal, Hem, HCC, and Cyst. Dataset is obtained from the Egyptian Liver Research Institute. Two classifiers are utilized, the first includes two classes (Normal/Cyst, Normal/Hem, Normal/HCC, HCC/Cyst, HCC/Hem, Cyst/Hem) and the second contains four classes (Normal/Cyst/ HCC/Hem) to distinguish liver images. Using performance criteria, it has been shown that the two-category classifiers have given better results than the four-class classifier, and accordingly a hybrid classifier was suggested to merge the weighted probabilities of the classes obtained by each singular classifier. Experimental results have achieved an accuracy of 96.1% using ResNet50 which means that it can be used as an assistive diagnostic method for classification of focal liver disease.
Blockchain adoption barriers in Moroccan sustainable supply chain: a proposed approach
Authors: Bendarag Abdesadik , Boutkhoum Omar , Abada Driss , Hanine Mohamed
Published: July 2022

Currently, the emerging countries like Morocco seeks to benefit from the potential of blockchain technology to meet its various growing demands, especially in sustainable supply chain management (SSCM). This explains the need for more effort to understand blockchain implementation and identify the barriers influencing the blockchain adoption decision in SSCM, especially, from Moroccan industry and service sectors perspective. In this context, this research paper proposes a group decision-making approach to identify the barriers from a comprehensive literature search, then evaluate them based on intuitionistic fuzzy analytic hierarchy process (IFAHP). Due to the varied importance of the selected barriers, IFAHP is utilized to allocate priority weights for each barrier according to its importance level. The evaluation results reveal that “Government policy and support” and “Challenges in integrating sustainable practices and blockchain technology through sustainable supply chain management (SCM)” are the best ranked barriers that impact the implementation of blockchain technology in Moroccan context. The main objective is to inquire the barriers preventing the blockchain implementation, and assist industry decision-makers in developing supple short- and long-term decision-making strategies for better sustainable supply chain management.
Breast cancer recognition based on performance evaluation of machine learning algorithms
Authors: Haydar Salih Chiman , M. Ali Abbas
Published: July 2022

Breast cancer is the one common cause of death in both developed worlds and the most death-causing disease diagnosed among women. Early recognition of this condition can help to minimize death rates. The breast problem statement, in brief, is not reliable for accuracy recognition. They have a high degree of classification accuracy as well as diagnostic capabilities. The most common classifications are normal, benign cancer, and malignant cancer. Machine learning (ML) techniques are now widely used in the classification of breast cancer. In this paper, some machine learning technics have been investigated to diagnose breast cancer (BC) on magnetic resonance imaging (MRI) images using multi-step processes. The first step has been to take the MRI image as an input image and have been pre-processing an image, then use feature extraction by using (scale-invariant feature transform (SIFT), histogram of oriented gradient (HOG), local binary patterns (LBP), bag of words (BoW), and edge-oriented histogram (EOH)). Next step we implement the classifying algorithms (KNN, decision tree (DT), naïve Bayes, ANN, SVM, RF, AdaBoost), have been used to detect and classify the normal or breast cancer region for this purpose datasets like ACRIN-Contralateral-Breast-MRI, In and breast cancer MRI dataset) has been collected our breast cancer MRI images from Erbil and Sulaymaniyah hospital the results was 91.9%, the result of ACRIN was 97% and the results Breast Cancer was 92.3%.
Quando a memória é o pomo da discórdia: o 13 de maio de 2020 e a Fundação Palmares
Authors: Lopes Juliana Serzedello Crespim , Sergio da Costa Neves Paulo
Published: July 2022

Neste artigo, refletimos sobre as disputas políticas pela memória da escravidão e a abolição desta no Brasil por meio da análise de publicações realizadas no site e nas redes sociais oficiais da Fundação Cultural Palmares (FCP) em maio de 2020. Nesses textos, a FCP, sob a presidência de Sérgio Camargo, busca valorizar o legado da Princesa Isabel como artífice da abolição e denunciar o caráter mitológico de Zumbi dos Palmares. A consolidação dos “lugares de memória” (NORA, 1993) não é consequência natural ou inexorável dos processos históricos, mas sim o resultado de embates e disputas sociais e simbólicas (LE GOFF, 1990). Assim, este artigo tem como objetivo investigar os elementos simbólicos e históricos mobilizados pela atual gestão da Fundação Cultural Palmares, no sentido de desqualificar e desmontar as políticas públicas de igualdade racial calcadas na reconstrução de símbolos, heróis e efemérides da negritude que surgiram a partir da redemocratização do país na década de 1980.
Proposição e aplicação de um índice de salubridade ambiental em aglomerados rurais
Authors: Braga Débora de Lima , Bezerra Nolan Ribeiro , Scalize Paulo Sérgio
Published: July 2022

OBJETIVO Propor um índice de salubridade ambiental que expresse as condições vividas em aglomerados rurais (ISARural), englobando indicadores e subindicadores para sua posterior aplicação em comunidades rurais do estado de Goiás. MÉTODOS A pesquisa foi desenvolvida em três fases: 1) análise prévia para proposição de um ISARural, contando com a participação de sete especialistas; 2) proposição do ISARural por meio do método Delphi, iniciando com 168 especialistas das 26 unidades federativas do Brasil e do Distrito Federal; e 3) aplicação do ISARural em 43 comunidades rurais do estado de Goiás. RESULTADOS O ISARural proposto resultou na composição de oito indicadores, sendo quatro relacionados ao saneamento básico, e os demais à saúde, às condições socioeconômicas, aos serviços públicos ofertados e às condições de moradia. O peso atribuído para cada indicador variou de 22,82%, para indicador de abastecimento de água, a 6,35%, para o indicador de serviços, podendo o ISARural ser aplicado na sua totalidade ou para avaliação de cada indicador individualmente. A aplicação do ISARural em comunidades de Goiás evidenciou que 86% se classificam com baixa salubridade, destacando as piores condições para as comunidades quilombolas. Dentre os indicadores do ISARural, o de esgotamento sanitário foi caracterizado com a menor pontuação, o que demanda uma maior atenção do poder público. CONCLUSÕES Esse estudo cumpriu o papel de contribuir com a proposição de um índice em consonância com o conceito de salubridade ambiental, podendo ser empregado no âmbito das políticas públicas como um condicionante para a priorização das ações necessárias à melhoria das condições de salubridade identificadas. O ISARural proposto pode ser aplicado na sua totalidade ou ainda na avaliação individual de cada indicador de sua composição. Os resultados da sua aplicação possibilitaram identificar as comunidades com piores condições de salubridade ambiental e os indicadores que requerem maior atenção prioritária nas comunidades estudadas.
Barriers faced by patients in the diagnosis of multidrug-resistant tuberculosis in Brazil
Authors: Bhering Marcela , Dalcolmo Margareth , Sarubbi Júnior Vicente , Kritski Afrânio
Published: July 2022

OBJECTIVE To understand patients’ narratives about the barriers they faced in the diagnosis and treatment of multidrug-resistant tuberculosis, and their consequences in Rio de Janeiro State, Brazil. METHODS This is a qualitative cross-sectional study with non-probabilistic sampling. A theoretical saturation criterion was considered for composing the number of interviewees. Semi-structured interviews were conducted from August to December 2019 with 31 patients undergoing treatment for multidrug-resistant tuberculosis at an outpatient referral center in Rio de Janeiro. Data were transcribed and processed with the aid of the NVIVO software. Interviews were evaluated by content analysis, and their themes, cross-referenced with participants’ characterization data. RESULTS Our main findings were: a) participants show a high proportion of primary drug resistance, b) patients experience delays in the diagnosis and effective treatment of multidrug-resistant tuberculosis ; c) healthcare providers fail to value or seek the diagnosis of drug-resistant tuberculosis, thus beginning the inadequate treatment for drug-susceptible tuberculosis, d) primary health units show low report rates of active case-finding and contact monitoring, and e) patients show poor knowledge about the disease. CONCLUSIONS We need to improve referral systems, and access to the diagnosis and effective treatment of multidrug-resistant tuberculosis; conduct an active investigation of contacts; intensify the training of healthcare providers, in collaboration with medical and nursing schools, in both public and private systems; and promote campaigns to educate the population on tuberculosis signs and symptoms.
Trends in Uptake and Adherence to Oral Anticoagulation for Patients With Incident Atrial Fibrillation at High Stroke Risk Across Health Care Settings
Authors: Yogasundaram Haran , Dover Douglas C. , Hawkins Nathaniel M. , McAlister Finlay A. , Goodman Shaun G. , Ezekowitz Justin , Kaul Padma , Sandhu Roopinder K.
Published: July 2022

Background

Oral anticoagulation (OAC) therapy prevents morbidity and mortality in nonvalvular atrial fibrillation; whether location of diagnosis influences OAC uptake or adherence is unknown.

Methods and Results

Retrospective cohort study (2008–2019), identifying adults with incident nonvalvular atrial fibrillation across health care settings (emergency department, hospital, outpatient) at high risk of stroke. OAC uptake and adherence via proportion of days covered for direct OACs and time in therapeutic range for warfarin were measured. Proportion of days covered was categorized as low (0–39%), intermediate (40–79%), and high (80–100%). Warfarin control was defined as time in therapeutic range ≥65%. All‐cause mortality was examined at a 3‐year landmark. Among 75 389 patients with nonvalvular atrial fibrillation (47.0% women, mean 77.4 years), 19.7% were diagnosed in the emergency department, 59.1% in the hospital, and 21.2% in the outpatient setting. Ninety‐day OAC uptake was 51.6% in the emergency department, 50.9% in the hospital, and 67.9% in the outpatient setting (
P
<0.0001). High direct OAC adherence increased from 64.9% to 80.3% in the emergency department, 64.3% to 81.7% in the hospital, and 70.9% to 88.6% in the outpatient setting over time (
P
values for trend <0.0001). Warfarin control was 40.3% overall and remained unchanged. In multivariable analysis, outpatient diagnosis compared with the hospital was associated with greater OAC uptake (odds ratio [OR], 1.79; [95% CI, 1.72–1.87]) and direct OAC (OR, 1.42; [95% CI, 1.27–1.59]) and warfarin (OR, 1.49; [95% CI, 1.36–1.63]) adherence. Varying or persistently low adherence was associated with a poor prognosis, especially for warfarin.

Conclusions

Locale of nonvalvular atrial fibrillation diagnosis is associated with varying OAC uptake and adherence. Interventions specific to health care settings are needed to improve stroke prevention.
Fibroblast Growth Factor 23 and Risk of New Onset Heart Failure With Preserved or Reduced Ejection Fraction: The PREVEND Study
Authors: Binnenmars S. Heleen , Hoogslag Georgette E. , Yeung Stanley M. H. , Brouwers Frank P. , Bakker Stephan J. L. , van Gilst Wiek H. , Gansevoort Ron T. , Navis Gerjan , Voors Adriaan A. , de Borst Martin H.
Published: July 2022

Background

The role of fibroblast growth factor 23 (FGF23) in the development of new‐onset heart failure (HF) with reduced (HFrEF) or preserved ejection fraction (HFpEF) in the general population is unknown. Therefore, we set out to investigate associations of C‐terminal FGF23 with development of new‐onset HF and, more specifically, with HFrEF or HFpEF in a large, prospective, population‐based cohort.

Methods and Results

We studied 6830 participants (aged 53.8±12.1 years; 49.7% men; estimated glomerular filtration rate, 93.1±15.7 mL/min per 1.73 m
2
) in the community‐based PREVEND (Prevention of Renal and Vascular End‐Stage Disease) study who were free of HF at baseline. Cross‐sectional multivariable linear regression analysis showed that ferritin (standardized β, −0.24;
P
<0.001) and estimated glomerular filtration rate (standardized β, −0.13;
P
<0.001) were the strongest independent correlates of FGF23. Multivariable Cox proportional hazard regression was used to study the association between baseline FGF23 and incident HF, HFrEF (ejection fraction ≤40%) or HFpEF (ejection fraction ≥50%). After median follow‐up of 7.4 [IQR 6.9–7.9] years, 227 individuals (3.3%) developed new‐onset HF, of whom 132 had HFrEF and 88 had HFpEF. A higher FGF23 level was associated with an increased risk of incident HF (fully adjusted hazard ratio, 1.29 [95% CI, 1.06–1.57]) and with an increased risk of incident HFrEF (fully adjusted hazard ratio, 1.31 [95% CI, 1.01–1.69]). The association between FGF23 and incident HFpEF lost statistical significance after multivariable adjustment (hazard ratio, 1.22 [95% CI, 0.87–1.71]).

Conclusions

Higher FGF23 is independently associated with new‐onset HFrEF in analyses fully adjusted for cardiovascular risk factors and other potential confounders. The association between FGF23 and incident HFpEF lost statistical significance upon multivariable adjustment.
RNF213
R4810K Variant in Suspected Unilateral Moyamoya Disease Predicts Contralateral Progression
Authors: Ok Taedong , Jung Yo Han , Kim Jinkwon , Park Sang Kyu , Park Goeun , Lee Sujee , Lee Kyung‐Yul
Published: July 2022

Background

Early‐stage unilateral moyamoya disease (MMD) is difficult to discriminate from isolated intracranial atherosclerotic stenosis, and identification of contralateral progression may aid in the diagnosis of MMD. The RNF213 (ring finger protein 213) R4810K variant is a strong genetic susceptibility factor for MMD; however, the role of contralateral progression in unilateral MMD is unknown.

Methods and Results

Patients who had undergone
RNF213
R4810K genotyping with suspected unilateral MMD between January 2017 and August 2021 from 2 tertiary university hospitals were retrospectively reviewed. We compared the clinical features and radiographic outcomes of patients with and without this variant. The risk factors of contralateral progression in patients with suspected unilateral MMD were evaluated. The
RNF213
R4810K variant was observed in 72 of 123 patients with suspected unilateral MMD, all of which were heterozygous. The allele frequency of the R4810K variant was significantly higher in the suspected unilateral MMD group compared with the historical control group (29.3% versus 1.2%;
P
<0.0001). Family history of MMD was significantly more common in patients with the variant than in those without (17% versus 4%;
P
=0.003). Eleven of 72 patients with the variant developed contralateral progression, whereas only 1 of 51 patients without the variant developed contralateral progression during a median follow‐up period of 28 months (log‐rank test;
P
=0.03). The presence of the
RNF213
R4810K variant significantly correlated with contralateral progression (adjusted odds ratio, 6.39 [95% CI, 1.11–36.63];
P
=0.04).

Conclusions

Contralateral progression is more likely to occur in patients with suspected unilateral MMD with the
RNF213
R4810K variant than in those without the variant. However, because our study used a small sample size, this finding should be carefully interpreted and requires further studies with more patients and longer follow‐up periods.
Estimating Perfusion Deficits in Acute Stroke Patients Without Perfusion Imaging
Authors: Reyes Dennys , Simpkins Alexis N. , Hitomi Emi , Lynch John K. , Hsia Amie W. , Nadareishvili Zurab , Luby Marie , Latour Lawrence L. , Leigh Richard
Published: July 2022

Background:

Perfusion weighted imaging (PWI) is critical for determining whether stroke patients presenting in an extended time window are candidates for mechanical thrombectomy. However, PWI is not always available. Fluid-attenuated inversion recovery hyperintense vessels (FHVs) are seen in patients with a PWI lesion. We investigated whether a scale measuring the extent FHV could serve as a surrogate for PWI to determine eligibility for thrombectomy.

Methods:

The National Institutes of Health (NIH) FHV score was developed to quantify the burden of FHV and applied to magnetic resonance imaging scans of stroke patients with fluid-attenuated inversion recovery and perfusion imaging. The NIH-FHV was combined with the diffusion weighted image volume to estimate the diffusion-perfusion mismatch ratio. Linear regression was used to compare PWI volumes and mismatch ratios with estimates from the NIH-FHV score. Receiver operating characteristic analysis was used to test the ability of the NIH-FHV score to identify a significant mismatch.

Results:

There were 101 patients included in the analysis, of whom 78% had a perfusion deficit detected on PWI with a mean lesion volume of 47 (±59) mL. The NIH-FHV score was strongly associated with the PWI lesion volume (
P
<0.001; R
2
=0.32; β-coefficient, 0.57). When combined with diffusion weighted image lesion volume, receiver operating characteristic analysis testing the ability to detect a mismatch ratio ≥1.8 using the NIH-FHV score resulted in an area under the curve of 0.94.

Conclusions:

The NIH-FHV score provides an estimate of the PWI lesion volume and, when combined with diffusion weighted imaging, may be helpful when trying to determine whether there is a clinically relevant diffusion-perfusion mismatch in situations where perfusion imaging is not available. Further studies are needed to validate this approach.
Theoretical foundations of studying criticality in the brain
Authors: Tian Yang , Tan Zeren , Hou Hedong , Li Guoqi , Cheng Aohua , Qiu Yike , Weng Kangyu , Chen Chun , Sun Pei
Published: July 2022

Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information-processing capacities in the brain. While considerable evidence generally supports this hypothesis, nonnegligible controversies persist regarding the ubiquity of criticality in neural dynamics and its role in information processing. Validity issues frequently arise during identifying potential brain criticality from empirical data. Moreover, the functional benefits implied by brain criticality are frequently misconceived or unduly generalized. These problems stem from the nontriviality and immaturity of the physical theories that analytically derive brain criticality and the statistic techniques that estimate brain criticality from empirical data. To help solve these problems, we present a systematic review and reformulate the foundations of studying brain criticality, that is, ordinary criticality (OC), quasi-criticality (qC), self-organized criticality (SOC), and self-organized quasi-criticality (SOqC), using the terminology of neuroscience. We offer accessible explanations of the physical theories and statistical techniques of brain criticality, providing step-by-step derivations to characterize neural dynamics as a physical system with avalanches. We summarize error-prone details and existing limitations in brain criticality analysis and suggest possible solutions. Moreover, we present a forward-looking perspective on how optimizing the foundations of studying brain criticality can deepen our understanding of various neuroscience questions.
Dynamical interactions reconfigure the gradient of cortical timescales
Authors: Sorrentino P. , Rabuffo G. , Baselice F. , Troisi Lopez E. , Liparoti M. , Quarantelli M. , Sorrentino G. , Bernard C. , Jirsa V.
Published: July 2022

The functional organization of the brain is usually presented with a back-to-front gradient of timescales, reflecting regional specialization with sensory areas (back) processing information faster than associative areas (front), which perform information integration. However, cognitive processes require not only local information processing but also coordinated activity across regions. Using magnetoencephalography recordings, we find that the functional connectivity at the edge level (between two regions) is also characterized by a back-to-front gradient of timescales following that of the regional gradient. Unexpectedly, we demonstrate a reverse front-to-back gradient when nonlocal interactions are prominent. Thus, the timescales are dynamic and can switch between back-to-front and front-to-back patterns.
Feud, Law, and Society in Mid-Nineteenth-Century Northern Albania
Authors: Bayraktar Uğur
Published: July 2022

The present article investigates the kanun or Albanian “customary law”, with a particular focus on feuds in the town of Dibra. It explores a case of Ottoman legal pluralism in which the kanun and Ottoman law interacted, a major watershed in the development of Ottoman law. By shifting the perspective to the Albanian highlanders’ understanding of “law”, this paper sheds light on how a set of customary laws contributed to the making of the Tanzimat, which called for a standardised legal framework in the provinces. It examines the means the Ottoman government developed to eliminate feuds and demonstrates that the Tanzimat converged with the principles of Albanian customary law. Analysis of this interaction between the kanun and state law demonstrates how this process constituted one of the foundations of the modern Ottoman legal order in northern Albania.
Jianghuaimon dabiense gen. nov. et sp. nov (Crustacea: Decapoda: Potamidae), a new genus and new species of freshwater crab from eastern-central China
Authors: ZHAO JUN-DA , XU YI-YANG , HUANG CHAO
Published: July 2022

A new genus and new species of freshwater crab, Jianghuaimon dabiense gen. et sp. nov., is described from Anhui and Hubei Provinces of China based on morphology and mitochondrial 16S rDNA sequences. Externally, the new genus resembles several other potamid genera from China. However, its combination of carapace, male pleon, third maxilliped, and uniquely structured male first gonopod distinguish it from the others. Phylogenetic analysis using the 16S gene supports the new genus new species and shows that it, together with morphologically similar Neilupotamon and Bottapotamon, form a distinct clade.