bluuebunny/crossref_metadata_2025_split huggingface dataset:
Malicious behavior detection in cloud using self‐optimized dynamic kernel convolutional neural network
Authors: Alajlan Abrar Mohammed , Almasri Marwah Mohammad 
Published: February 2022

AbstractCloud computing is one example of a technological revolution that has drastically altered the way traditional commercial operations are conducted. Because cloud platforms are fundamentally revolutionizing the area of computing, they must provide safe transmission and storage of user data by assuring the confidentiality, integrity, and availability of the data. As a result, establishing a secure cloud computing framework is crucial, and security cannot only rely on the user's credentials being verified. To overcome this problem, this article presents a multi‐population genetic algorithm optimized dynamic kernel convolutional neural network to analyze the user's behavior to identify their malicious intent. This article describes a two‐stage malicious detection and prediction scheme. The proposed system's efficiency is measured by its ability to discriminate between nine different types of attacks in the UNSW‐NB15 dataset (abnormal behavior exhibited by users). The average true positive rate, false positive rate, precision, and F‐measure for the nine attack classes were 99.22%, 99.11%, 99.11%, and 99.22%, respectively, when evaluated using the UNSW‐NB15 dataset. The experimental results demonstrate that this technique is effective in detecting malicious behaviors in the cloud environment with higher accuracy.
Effects of ayahuasca on the endocannabinoid system of healthy volunteers and in volunteers with social anxiety disorder: Results from two pilot, proof‐of‐concept, randomized, placebo‐controlled trials
Authors: dos Santos Rafael G. , Rocha Juliana Mendes , Rossi Giordano Novak , Osório Flávia L. , Ona Genís , Bouso José Carlos , Silveira Gabriela de Oliveira , Yonamine Mauricio , Marchioni Camila , Crevelin Eduardo José , Queiroz Maria Eugênia , Crippa José Alexandre , Hallak Jaime E. C. 
Published: February 2022

AbstractObjectiveTo assess endocannabinoid (anandamide, AEA; 2‐arachidonoylglycerol, 2‐AG) plasma levels in healthy volunteers and in volunteers with social anxiety disorder (SAD) after a single oral dose of ayahuasca or placebo.MethodsPost hoc analysis of endocannabinoid plasma levels (baseline, 90 and 240 min after drug intake) from two parallel‐group, randomized, placebo‐controlled trials. In Study 1, 20 healthy volunteers ingested ayahuasca (average 1.58 mg/ml dimethyltryptamine (DMT)) or placebo, and in Study 2, 17 volunteers with SAD received ayahuasca (average 0.680 mg/ml DMT) or placebo.ResultsA significant difference was observed in AEA concentrations in Study 2 after ayahuasca intake (Χ2(2) = 6.5, p = 0.03, Friedman test), and near significant differences (increases) were observed between baseline and 90 (Z = 0, p = 0.06, Wilcoxon test) and 240 (Z = 10, p = 0.06) minutes after ayahuasca intake.ConclusionsAlthough our findings suggest that ayahuasca could modulate AEA levels in SAD patients, the high interindividual variability in both trials and the small samples preclude definitive conclusions. More research with larger samples is needed to better understand the effects of ayahuasca and other hallucinogens in the endocannabinoid system.
Flow and wake characteristics associated with riparian vegetation patches: Results from field‐scale experiments
Authors: Caroppi Gerardo , Västilä Kaisa , Järvelä Juha , Lee Chanjoo , Ji Un , Kim Hyung Suk , Kim Sungjung 
Published: February 2022

AbstractRiparian vegetation patches growing on river banks and floodplains influence in‐channel and overbank hydromorphological processes. The current knowledge on patch‐scale hydrodynamics is largely based on laboratory flume experiments with simplified vegetation. The aim of this study is to provide new understanding of the flow and wake characteristics for real riparian vegetation patches based on field‐scale experiments with natural willows, in order to inform hydromorphological and ecological modelling. The focus was placed on the effects of foliage as the main driver of the seasonal changes in vegetation and on the influence of the flexibility‐induced reconfiguration on the flow in the wake and around the patches. The patch drag, defined by its flow blockage factor, was increased by 3.0–4.4 times by the presence of foliage and decreased by up to 60% because of the streamlining and reconfiguration of foliage with increasing flow velocity. Such large changes in the patch drag altered the flow and wake characteristics, affecting the onset of a patch‐scale vortex street. Seasonality and flexibility modified the patch sheltering effect, that is, the magnitude of velocity, turbulent kinetic energy, and bed shear stress reduction in the wake, relative to the background level. In the presence of foliage, mean flow velocity and bed shear stress in the wake were reduced on average by ~50% and ~70%, respectively. The sheltering effect was lower for the leafless conditions than for the foliated conditions. For the foliated cases, the spatial extents of the over‐depth and the near‐bed sheltered region were on average 1.5 and 1.8 times larger than in the corresponding leafless cases, respectively. Overall, seasonal changes in vegetation and flexibility‐induced mechanisms were identified as key controls for the flow associated with patches of riparian vegetation, with major implications on developing models for predicting hydromorphological processes and the potential to preserve and create habitats.
Optimal operational instructions for on‐request delivery using hybrid genetic algorithm and artificial neural network, considering unsteady flow
Authors: Savari Hajar , Monem Mohammad Javad 
Published: February 2022

AbstractFlexible on‐request (arranged) water delivery is applicable in existing canals that operate manually. A challenge facing this method is the diversity and multiplicity of requests across the network, making planning for water distribution very difficult and time‐consuming. Therefore, we need a suitable tool to derive the proper operation of structures quickly to improve network performance compared to rotational delivery. This study uses intelligent optimization methods to prepare on‐request operational instructions of irrigation canals under unsteady flow conditions. A meta‐model was developed using artificial neural networks (ANNs) for the first reach of the Aghili canal for simulating unsteady flow in canals to speed up the process. The meta‐model was combined with a genetic algorithm (GA) to determine optimal operational instructions. The error rate of the ANN model was smaller than 2.5%, indicating excellent performance of the developed model. Two scenarios of 3‐ and 6‐h delivery were defined to compare the optimal operation of the ANN‐GA model with conventional operation. For both scenarios, the percentage of improvement was remarkable, and on average, it was above 50%. The utility of the developed model for shorter deliveries is significant. Moreover, the model can be generalized to other reaches.
Dysregulated transient receptor potential channel 1 expression and its correlation with clinical features and survival profile in surgical non‐small‐cell lung cancer patients
Authors: Ke Changjiang , Long Shenghua 
Published: February 2022

AbstractBackgroundTransient receptor potential channel 1 (TRPC1) facilitates the tumor growth, metastasis, and chemoresistance in a series of neoplasms, while its correlation with clinical features and survival profile in NSCLC patients remains elusive. Hence, this study aimed to explore this topic.MethodsTotally, 192 NSCLC patients were enrolled. Protein and mRNA expression of TRPC1 in carcinoma tissue and para‐carcinoma tissue were evaluated by immunohistochemistry (IHC) assay and reverse transcription quantitative polymerase chain reaction (RT‐qPCR) assay, respectively.ResultsImmunohistochemistry score and mRNA expression of TRPC1 were higher in carcinoma tissue compared with para‐carcinoma tissue (both p < 0.001). Besides, increased TRPC1 IHC score (p = 0.004) and elevated TRPC1 mRNA overexpression (p = 0.016) were linked with occurrence of LYN metastasis; meanwhile, increased TRPC1 IHC score (p = 0.015) and raised TRPC1 mRNA expression (p = 0.009) were also linked with advanced TNM stage, whereas TRPC1 IHC score and TRPC1 mRNA expression were not correlated with other clinical features (all p > 0.05). Additionally, TRPC1 protein high (p = 0.007) and TRPC1 mRNA high (p = 0.015) were correlated with poor disease‐free survival (DFS) but not correlated with overall survival (OS). Moreover, multivariate Cox's proportional hazards regression analysis showed that high TRPC1 protein expression (p = 0.046) and advanced TNM stage (p < 0.001) were independently correlated with poor DFS. However, TRPC1 protein and mRNA expression were not linked with OS (both p > 0.05), while poor differentiation (p = 0.003) and advanced TNM stage (p < 0.001) were independently associated with worse OS.ConclusionsTRPC1 is unregulated in NSCLC tissue with its overexpression relating to the occurrence of LYN metastasis and worse DFS in NSCLC patients.
Perception of genetic testing among patients with inherited retinal disease: Benefits and challenges in a Japanese population
Authors: Inaba Akira , Yoshida Akiko , Maeda Akiko , Kawai Kanako , Kosugi Shinji , Takahashi Masayo 
Published: February 2022

AbstractInherited retinal disease (IRD) is clinically and genetically heterogeneous. Awareness of the importance of genetic testing for IRD in the clinical setting is increasing with the recent development of new therapeutic strategies, such as gene therapy. Here, the perception of genetic testing, including its benefits and potential challenges, among patients with IRD was investigated to establish strategies for IRD genetic testing and counseling practices that can meet the requirements of the patients in Japan. An anonymous self‐administered questionnaire was distributed to 275 patients with IRD who underwent genetic testing after clinical consultation and genetic counseling to investigate the motivations for genetic testing, benefits, challenges, status of communication of results to family, and attitude to timing of genetic testing. In total, 228 (82.9%) responses were analyzed. Several major motivations for genetic testing were identified, including gaining information on future treatment options and clarification of the inheritance pattern, among others. No association was found between the sharing of results with family members and the results of genetic testing. Moreover, according to patients who received positive results, the benefits of genetic testing included information on the inheritance pattern, additional information on the diagnosis, and mental preparation for the future. Even patients who received negative or inconclusive (variant of uncertain significance) results reported certain informative and psychological benefits. Altogether, these findings suggest that provisions for genetic testing and genetic counseling are necessary within a certain period after clinical diagnosis and it is necessary to facilitate appropriate family communication about genetic testing results while paying attention to the background of family relationships. Moreover, the benefits of genetic testing can be influenced by the careful interpretation and information provided on the test results during genetic counseling and consultation.
Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Using CNN Based on Multiparametric MRI
Authors: Wang Zijian , Sun Hang , Li Jing , Chen Jing , Meng Fancong , Li Hong , Han Lu , Zhou Shi , Yu Tao 
Published: February 2022

BackgroundMultiparametric magnetic resonance imaging (MRI) is widely used in breast cancer screening. Accurate prediction of the axillary lymph nodes metastasis (ALNM) is essential for breast cancer surgery and treatment. However, there is no mature and effective discerning method for ALNM based on multiparametric MRI.PurposeTo evaluate the ALNM using T1‐weighted imaging (T1WI), T2‐weighted imaging (T2WI), and diffusion‐weighted imaging (DWI) sequences, respectively, and construct a quantitative ALNM discerning model of integrated multiparametric MRI.Study TypeRetrospective.PopulationThree‐hundred forty‐eight breast cancer patients, 163 with ALNM (99.39% females), and 185 without ALNM (100% females). The dataset was randomly divided into the training set (315 cases) and the testing set (33 cases).Field Strength/Sequence1.5 T; T1WI (VIBRANT), T2WI (FSE), and DWI (echo planar imaging [EPI]).AssessmentThe lesion region of interest images were cropped and sent to a pretrained ResNet50 network. Then, the results of different sequences were sent to a classifier for ensemble learning to construct the ALNM model of multiparametric MRI.Statistical TestsPerformance indicators such as accuracy, the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) were calculated. Student's t‐test, chi‐square test, Fisher's exact test, and Delong test were performed, and P < 0.05 was considered statistically significant.ResultsT2WI performed the best among the three sequences, and achieved the accuracy and AUC of 0.933/0.989 in the testing set. Compared to T1WI with the accuracy and AUC of 0.691/0.806, the increase is significant. While compared to DWI with the accuracy and AUC of 0.800/0.910, the improvement is not significant (P = 0.126). After integrating three sequences, the accuracy and AUC improved to 0.970 and 0.996.Data ConclusionT2WI performed better than DWI and T1WI in discerning ALNM in this breast cancer dataset. The proposed quantitative model of integrated multiparametric MRI could effectively help the ALNM diagnosis.Level of Evidence1Technical Efficacy Stage2
Diffusion‐Weighted Imaging Distinguishes Between Osteomyelitis, Bone Marrow Edema, and Healthy Bone on Forefoot Magnetic Resonance Imaging
Authors: Kruk Konrad A. , Dietrich Tobias J. , Wildermuth Simon , Leschka Sebastian , Toepfer Andreas , Waelti Stephan , Kim Chan‐Hi Olaf , Güsewell Sabine , Fischer Tim 
Published: February 2022

BackgroundDiagnosis of osteomyelitis by imaging can be challenging. The feasibility of diffusion‐weighted imaging (DWI) as ancillary sequence was evaluated in this study.PurposeTo evaluate DWI for differentiation between osteomyelitis, bone marrow edema, and healthy bone on forefoot magnetic resonance imaging (MRI).Study typeProspective.SubjectsA total of 60 consecutive patients undergoing forefoot MRI divided into three study groups (20 subjects each): osteomyelitis, bone marrow edema, and healthy bone.Field strength/SequenceA 1.5T and 3T MRI scanners; readout‐segmented multishot echo planar DWI.AssessmentTwo independent radiologists measured apparent diffusion coefficient (ADC) values within abnormal or healthy bone.Statistical TestsADC values were compared between groups (pairwise t‐test with Bonferroni‐Holm correction for multiple testing). Intraclass correlation coefficient (ICC) was calculated to assess inter‐reader agreement. Threshold ADC values were determined as the cutoffs that maximized the sum of sensitivity and specificity. Receiver operating characteristic (ROC) analysis was performed with statistical threshold of P < 0.05.ResultsInter‐reader agreement was 0.92 in the healthy bone group and 0.78 in both the edema and osteomyelitis groups. Average ADC values were significantly different between groups: 1432 ± 222 × 10−6 mm2/sec (osteomyelitis), 1071 ± 196 × 10−6 mm2/sec (bone marrow edema), and 277 ± 89 × 10−6 mm2/sec (healthy bone). A threshold ADC value of 534 × 10−6 mm2/sec distinguishes between healthy and abnormal bone with specificity and sensitivity of 100% each. For distinction between osteomyelitis and bone marrow edema, two cutoff values were determined: a 95%‐specificity cutoff indicating osteomyelitis (>1320 × 10−6 mm2/sec) and a 95%‐sensitivity cutoff indicating bone marrow edema (<1155 × 10−6 mm2/sec). Diagnostic accuracy of 95% was achieved for 73% (29/40) of the subjects.Data ConclusionDWI with ADC maps distinguishes between healthy and abnormal bone on forefoot MRI. Calculated cutoff values allow confirmation or exclusion of osteomyelitis in a high proportion of subjects.Evidence Level2Technical EfficacyStage 2
Characteristics of summer cloud precipitation along latitude 30°N in East Asia derived from Tropical Rainfall Measuring Mission Precipitation Radar and Visible and Infrared Scanner measurements
Authors: Wang Mengxiao , Fu Yunfei , Zhao Chun , Zhong Lei , Li Rui , Wang Dongyong , Qiu Xuexing , Zhou Shengnan 
Published: February 2022

AbstractThere has been little systematic analysis of the influence of the three‐step staircase topography on the characteristics of precipitation along latitude 30°N in East Asia. After the distribution of atmospheric climate states over East Asia was analysed, in this study, the climatological characteristics of summer convective and stratiform precipitation on horizontal distribution, vertical structure, and diurnal variation in East Asia were investigated by using a merged dataset derived from the measurements of the Tropical Rainfall Measuring Mission Precipitation Radar and Visible and Infrared Scanner from 1998 to 2012 reanalysis datasets. Results indicate that the rain frequency, the mean rain rate, and the maximum echo reflectivity factor show clear differences among the three‐step staircase topography, especially between the first staircase and its eastern region. There are small changes in the echo‐top height, the cloud‐top height, the maximum echo reflectivity factor and its corresponding height from the East China Sea westwards to the eastern part of the first staircase, passing the third staircase and the second staircase along 30°N. However, the rain rate decreased obviously twice westwards along this latitude, which responds to aerosol indirect effect and humidity effect, respectively. The diurnal variation of the convective precipitation reflectivity factor indicated that the development of convection in the eastern part of the first staircase gets at the maximum from the early afternoon to sunset, whereas the strongest echo reflectivity factor of precipitation in the second and third staircases including the East China Sea appears in the early morning, which is consistent with the diurnal variations of the atmospheric circulation.
Extension and application of an observation‐based local climate index aimed to anticipate the impact of El Niño–Southern Oscillation events on Colombia
Authors: Sayol Juan‐Manuel , Vásquez Laura M. , Valencia Jorge L. , Linero‐Cueto Jean R. , García‐García David , Vigo Isabel , Orfila Alejandro 
Published: February 2022

AbstractThe Tumaco multivariate index (TMI) is a multidecadal monthly index constructed with unique time series of sea surface temperature, surface air temperature and rain measured at Tumaco bay, in the southern Pacific coast of Colombia, and available since 1961. In this work, this index is re‐evaluated after the addition of in situ sea level data, and its properties for different standardization periods are compared against oceanic El Niño–Southern Oscillation (ENSO) and other derived indices. In particular, we propose a modified TMI, hereinafter referred as TMI4, whose potential to identify the expected sign and the amount of future variations of rain induced by ENSO events in Colombia is analysed for selected extreme episodes. Results indicate that after the inclusion of sea level data, TMI4 can anticipate the development of El Niño events before the ENSO 3 and some other sea surface temperature‐based regional indices, although its predictability depends on the ENSO type (canonical or Modoki). The explanation is that sea level includes new information into TMI4 on the onset of El Niño events. In particular, the signal of intraseasonal sea level anomalies carried by downwelling Kelvin waves is detected at Tumaco tide‐gauge. Moreover, the analysis of the differences, both in magnitude and spatial distribution, of rainfall anomalies induced by positive (El Niño) and negative (La Niña) ENSO events characterized by TMI4 are regionally presented. As a result, we find that TMI4 is especially suited for extensive northern and western areas of mainland Colombia. For completeness, in the appendix we briefly introduce the semi‐automated implementation of TMI4, including a visual interface, which is currently being tested by personnel within the operational oceanography area at Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico (Dimar‐CCCP).
Unravelling the backbone of climate networks from the analysis of collective dynamics and time reversal
Authors: Naghipour Leyla , Aalami Mohammad Taghi , Nourani Vahid 
Published: February 2022

AbstractMany complex systems are characterized by interconnected units often difficult, or even impossible, to map through direct observations, while the dynamics of units is mostly easier to measure. The reconstruction of an unknown structure from the observed dynamics is a typical inverse problem in network‐based approaches to overcome such obstacles. However, this procedure is affected by the interplay between the structure and dynamics, as well as by the choice of the statistical method. In this study, collective behaviour of the Earth's climate system was investigated by focusing on three distinct climatological variables in monthly time step using a causality measure to separately construct climate networks through a robust statistical analysis. Multiplex network (MUX) was used to integrate the information obtained from collective dynamics and time reversal for better filtering spurious connectivity. In fact, the proposed approach mitigates undesired effects of pairwise statistical inference by adjusting for unphysical relationships in two layers of the constructed networks. The results indicate that the mere existence of statistical errors allowed by the hypothesis testing lead, inevitably, to reconstruct spurious connections in the null models even when the collective dynamics consists of white‐noise datasets from uncoupled units. The impact of spurious connections with the MUX dynamics is not remarkable to reconstruct the underlying plausible interactions; therefore, the concepts of MUX might be employed with the statistical analysis to unravel the backbone of climate networks. In this way that the inferred connections could distinguish highly connected regions for better understanding interconnected dynamical patterns, yielding deep insights into underlying physical interactions between the oceans and atmosphere. More specifically, edge directionality features provide a complementary tool for analysing topology of the networks with respect to the climatological variables, identifying relevant patterns in the climate system.