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The profiled side-channel analysis method can effectively attack the implementation of cryptographic,and the side-channel cryptanalysis method based on convolutional neural network (CNNSCA) can efficiently carry out cryptographic attacks,and even can attack the implementation of protected encryption algorithms.In view of the current research status of side-channel cryptanalysis profiling methods,this paper compares and analyzes the characteristics and performance differences of several CNNSCA models,and focuses on the typical CNN model structure and side-channel signal public data set ASCAD.Through model comparison and experimental results,it compares and analyzes the effects of different CNN network modeling methods,and then analyzes the performance factors that affect the CNNSCA method and the advantages of the side-channel profiling method based on convolutional neural networks.Research and analysis show that CNNSCA based on VGG variants performs best in generalization and robustness when attacking target data sets in various situations,but whether the training level of the used CNN model and the hyperparameter settings are most suitable for SCA scenarios have not been verified.In the future,researchers can improve the classification accuracy and decryption performance of CNNSCA by adjusting various hyperparameters of the CNN model,use data enhancement techniques and combine the excellent CNN network in the Imagenet competition to explore the most suitable CNN model for SCA scenarios,which is a development trend.

Coalescence-induced droplet jumping on superhydrophobic surfaces has been observed at microscale and even nanoscale. The enhancement in jumping velocity of coalescing droplets is crucial for condensation heat transfer enhancement, antiicing, self-cleaning, and so forth. However, the research on how to acquire a higher jumping velocity is really very limited. In this paper, we use molecular dynamics simulations to study the coalescence-induced jumping of two equally sized nanodroplets on chemically heterogeneous surfaces composed of alternating stripes with different hydrophobicity. We show that the jumping velocity is closely related to the stripe width and wettability contrast, and it can even exceed that on an ideal superhydrophobic surface with 180 [degrees] contact angle when the striped surfaces are properly designed. We also demonstrate that there is always an optimal stripe width yielding the maximum jumping velocity, whereas its value is independent of the wettability contrast. We reveal that the dominant factor to determine the jumping velocity is the apparent contact angle of equilibrated droplets over heterogeneous surfaces for small stripe widths; it changes to the time of liquid bridges impacting surfaces for moderate stripe widths and to the contact area between equilibrated droplets and relatively hydrophobic stripes for large stripe widths. We believe the present simulations can provide useful guidance to design self-jumping superhydrophobic surfaces. Key words: mixed-wettability, superhydrophobic surfaces, coalescence, jumping velocity, molecular dynamics simulations. Les sauts de gouttelettes induits par coalescence sur une surface super-hydrophobe s'observent aux echelles micro et nano. L'accroissement de la vitesse de saut des gouttelettes se fusionnant est cruciale pour l'augmentation du transfert de chaleur par condensation, pour l'antigivrage, l'auto-nettoyage, etc. Cependant, il n'y a que tres peu de recherche sur le moyen d'augmenter la vitesse de saut. Nous utilisons ici des simulations de dynamique moleculaire pour etudier le sautillement, induit par leur fusion, de deux nano-gouttelettes de meme grosseur sur des surfaces chimiquement heterogenes composees de bandes alternees de differente hydrophobicite. Nous montrons que la vitesse de saut est etroitement reliee a la largeur de ces bandes et du contraste de mouillabilite et qu'elle peut meme exceder celle sur une surface superhydrophobe continue ideale avec un angle de surface de 180 [degrees], a condition que les surfaces striees soient concues de facon appropriees. Nous annoncons aussi qu'il y a une largeur de bande optimale produisant une vitesse de saut maximale, et que sa valeur est independante du contraste de mouillabilite. Nous revelons que, sur les surfaces heterogenes avec des bandes de petites largeurs, le facteur dominant pour determiner la vitesse de saut est l'angle de contact apparent des gouttelettes en equilibre, mais pour des bandes de largeur moyenne, ce facteur dominant devient le temps du pont liquide impactant la surface, alors que pour des bandes de grande largeur, il devient la surface de contact entre les gouttelettes equilibrees et les bandes relativement hydrophobes. Nous croyons que les resultats de ces simulations fourniront des guides utiles dans la conception des surfaces super-hydrophobes auto-sautillantes. [Traduit par la Redaction] Mots-cles : mouillabilite mixte, super-hydrophobe, coalescence/fusion, vitesse de saut, simulations de dynamique moleculaire., 1. Introduction Coalescence-induced droplet jumping on superhydrophobic surfaces was first discovered by Boreyko and Chen in 2009 [1]. Over the past decade, this phenomenon has received more and more attention [...]

The porosity ration of weathered crust elution-deposited rare earth ores is the main factor that affects the leaching results and the stability of the ore body. To determine the strength characteristics of weathered crust elution-deposited rare earth ores under different porosity ratios, six groups of rare earth minerals were reconstituted, and direct shear tests were performed for different samples. The effect of pore evolution on the shear strength of the orebody was studied, and the mechanism of the influence of porosity ratio on cohesion and internal friction angle was revealed. The results show that the unsaturated rare earth ores with different porosity ratios correspond to different shear strengths. The relation between shear stress and shear displacement was summarized as parabolic type based on the experimental data, and the relation between the porosity ratio and the shear strength index was established. The mechanism analysis shows that with an increase in the porosity ratio, the effect of the bonded water film effect gradually weakens, the number of the contact points reduces, and the shear strength of the minerals reduces.

Bioleaching is one of the most effective methods of extracting valuable elements from low-grade, refractory secondary copper sulfide. In this research, Acidithiobacillus ferrooxidans was used to leach refractory secondary copper sulfide from Fujian Province. The bioleaching microorganisms were added to the culture, domesticated, and column leaching experiments. These were based on different particle size ratios and carried out sequentially. Based on this experiments, the evolution disciplinarians of bacterial concentration, pH values and copper extraction rates were obtained at different stages. Using computed tomography (CT) technology, ore heap slumping inside the columns, cross section porosity evolution and leaching mechanisms were studied. The results indicate that bacterial concentration and pH values present trends that increase first and then stabilize. The proliferation of bacteria in the leaching columns is slower and the bacterial concentration is only 5×107 per mL after 480 h. During the leaching process, fine particles tend to move to the bottom of columns and the ore heap slump phenomenon appears. On the top surface of the column the porosity tends to be greater with increase rate of 6.65%, conversely, this tends to be smaller at the column bottom, and its decreases rate is 8.29%. The slump degree is proportional to the fines content; the minimum slump is 1.7 mm and the maximum 6.15 mm. Ore particle size is the key factor in the leaching process; column B (with particle size r < 1 mm accounted for 28.41% of whole ores quality) shows the best copper extraction rate of 47.23% after 480 h.

To investigate the leaching characteristic of alkaline copper dioxide ore by ammonia producing bacteria, the influence of the ammonia producing bacteria on the ore during the process was analyzed. To expose the possible influence factor, the shaking flask leaching test was carried out by putting alkaline cupric oxide ore from Yunnan separately into five kinds of leaching solutions, such as bacteria-containing, bacteria-removing inoculums and ammonia solution. Experimental results indicate that the bacteria have a strong ability at producing ammonia and the highest ammonia mass concentration reaches 8. 93 g·L-1. Ammonia production is positively correlated with the content of bacteria. The bacteria leach mineral mainly through producing ammonia, besides, the bacteria and their metabolites can also effect. The leaching capacity is in the order of bacteria ammonia > bacteria > bacterial metabolites, and the ratio of the three is 12:5:4.

The phenomenon of droplet coalescence and jumping has received increasing attention due to its potential applications in the fields of condensation heat transfer and surface self-cleaning. Basic research on the process and mechanism of coalescence-induced droplet jumping has been carried out, and some universal laws have been established. However, it is found that the focus of these studies is based on two identical droplets, and the coalescence-induced jumping with different radii is rarely investigated, which is commonly encountered in nature. Therefore, it is essential to proceed with the research of coalescence and jumping of droplets with unequal radii. In this paper, molecular dynamics (MD) simulations are performed to reveal the effects of radius ratio and radius of small droplets on jumping velocity. The results show that as the increasing of radius ratio with an unchanged small droplet radius of 8.1 nm, the jumping velocity increases then decreases, which indicates there is an optimal radius ratio to maximize the jumping velocity. Additionally, it is found that if the small droplet radius is changed, the critical radius ratio for characterizing whether the coalesced droplet jumping increases with increasing the small droplet radius. Furthermore, according to energy conservation, the conversion efficiency of energy is discussed. The results show that when the radius ratio is greater than 1.3 with three different small droplet radii, the energy conversion efficiency rapidly decreases to below 1.0%; and the critical radius ratios are consistent with the result obtained from the velocity analysis. This work broadens the understanding of the more general phenomenon of coalescence-induced droplet jumping and can better guide industrial applications. [ABSTRACT FROM AUTHOR]

Background: Differential diagnosis of brain metastases subtype and primary central nervous system lymphoma (PCNSL) is necessary for treatment decisions. The application of machine learning facilitates the classification of brain tumors, but prior investigations into primary lymphoma and brain metastases subtype classification have been limited. Purpose: To develop a machine‐learning model to classify PCNSL, brain metastases with primary lung and non‐lung origin. Study Type: Retrospective. Population: A total of 211 subjects with pathologically confirmed PCNSL or brain metastases (training cohort 168 and testing cohort 43). Field Strength/Sequence: A 3.0 T axial contrast‐enhanced T1‐weighted spin‐echo inversion recovery sequence (T1WI‐CE), axial T2‐weighted fluid‐attenuation inversion recovery sequence (T2FLAIR) Assessment: Several machine‐learning models (support vector machine, random forest, and K‐nearest neighbors) were built with least absolute shrinkage and selection operator (LASSO) using features from T1WI‐CE, T2FLAIR, and clinical. The model with the highest performance in the training cohort was selected to differentiate lesions in the testing cohort. Then, three radiologists conducted a two‐round classification (with and without model reference) using images and clinical information from testing cohorts. Statistical Tests: Five‐fold cross‐validation was used for model evaluation and calibration. Model performance was assessed based on sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC). Results: Twenty‐five image features were selected by LASSO analysis. Random forest classifier was selected for its highest performance on the training set with an AUC of 0.73. After calibration, this model achieved an accuracy of 0.70 on the testing set. Accuracies of all three radiologists improved under model reference (0.49 vs. 0.70, 0.60 vs. 0.77, 0.58 vs. 0.72, respectively). Data Conclusion: The random forest model based on conventional MRI and clinical data can diagnose PCNSL and brain metastases subtypes (lung and non‐lung origin). Model classification can help foster the diagnostic accuracy of specialists and streamline prognostication workflow. Evidence Level: 4 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

A double–heptagon–containing C70H6 (dihept-C70H6) was isolated and unambiguously characterized in the soot of low-pressure combustion, which shares the identical heptagonal cage as dihept-C70Cl6 previously identified in the products of carbon arc, and thus represents the first nonclassical fullerene isolable in both carbon arc and combustion. [ABSTRACT FROM AUTHOR]

Due to the partially reduced π-conjugation of the fullerene cage, multi-functionalized fullerene derivatives exhibit remarkable fluorescent properties compared to pristine fullerenes, which have high potential for application in organic light-emitting diodes (OLEDs). In this study two multi-functionalized C70 derivatives, C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2, with excellent fluorescence properties, were designed and synthesized. Compared with C70(OCH3)10 containing a single kind of functional group, both the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 exhibited enhanced fluorescence properties with blue fluorescence emission. The fluorescence quantum yields of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were 1.94% and 2.30%, respectively, which were about ten times higher than that of C70(OCH3)10. The theoretical calculations revealed that the multi-functionalization of the C70 increased the S1–T1 energy gap, reducing the intersystem crossing efficiency, resulting in the higher fluorescence quantum yield of the C70 derivatives. The results indicate that multi-functionalization is a viable strategy to improve the fluorescence of fullerene derivatives. [ABSTRACT FROM AUTHOR]