基于像全息技术的资料存储

文中利用像全息技术,对二维文字资料作了全息存储,并对实验结果进行了分析,不仅 提高了存诸质量,而且为今后的全息显示打下了基础。     

Supercritical CO2 Plant Extracts Show Antifungal Activities against Crop-Borne Fungi

Fungal infections of cultivated food crops result in extensive losses of crops at the global level, while resistance to antifungal agents continues to grow. Supercritical fluid extraction using CO₂ (SFE-CO₂) has gained attention as an environmentally well-accepted extraction method, as CO₂ is a non-toxic, inert and available solvent, and the extracts obtained are, chemically, of greater or different complexities compared to those of conventional extracts. The SFE-CO₂ extracts of Achillea millefolium, Calendula officinalis, Chamomilla recutita, Helichrysum arenarium, Humulus lupulus, Taraxacum officinale, Juniperus communis, Hypericum perforatum, Nepeta cataria, Crataegus sp. and Sambucus nigra were studied in terms of their compositions and antifungal activities against the wheat- and buckwheat-borne fungi Alternaria alternata, Epicoccum nigrum, Botrytis cinerea, Fusarium oxysporum and Fusarium poae. The C. recutita and H. arenarium extracts were the most efficacious, and these inhibited the growth of most of the fungi by 80% to 100%. Among the fungal species, B. cinerea was the most susceptible to the treatments with the SFE-CO₂ extracts, while Fusarium spp. were the least. This study shows that some of these SFE-CO₂ extracts have promising potential for use as antifungal agents for selected crop-borne fungi.     

Gaussian states as minimum uncertainty states

In bosonic fields, Gaussian states, which consist of a rather wide family of states including coherent states, squeezed states, thermal states, etc., have many classical-like features, and are usually defined from the mathematical perspective in terms of characteristic functions. It is well known that some special Gaussian states, such as coherent states, are minimum uncertainty states for the conventional Heisenberg uncertainty relation involving canonical pair of position and momentum observables. A natural question arises as whether all Gaussian states can be characterized as minimum uncertainty states. In this work, we show that indeed Gaussian states coincide with minimum uncertainty states for an information-theoretic refinement of the conventional uncertainty relation established in Luo (2005) [40]. This characterization puts Gaussian states on a novel basis of physical significance.     

Channel-Supermodular Entropies: Order Theory and an Application to Query Anonymization

This work introduces channel-supermodular entropies, a subset of quasi-concave entropies. Channel-supermodularity is a property shared by some of the most commonly used entropies in the literature, including Arimoto–Rényi conditional entropies (which include Shannon and min-entropy as special cases), k-tries entropies, and guessing entropy. Based on channel-supermodularity, new preorders for channels that strictly include degradedness and inclusion (or Shannon ordering) are defined, and these preorders are shown to provide a sufficient condition for the more-capable and capacity ordering, not only for Shannon entropy but also regarding analogous concepts for other entropy measures. The theory developed is then applied in the context of query anonymization. We introduce a greedy algorithm based on channel-supermodularity for query anonymization and prove its optimality, in terms of information leakage, for all symmetric channel-supermodular entropies.     

SSIG: Single-Sample Information Gain Mo del for Integrating Multi-Omics Data to Identify Cancer Subtypes

Different living environments of cancer samples lead to different molecular mechanisms of cancer development, which in turn leads to different cancer subtypes. How to identify cancer subtypes is a key issue for the realization of precision medicine. With the development of high-throughput technologies, multi-omics data which can better understand different causes of cancer have emerged. However, the current methods of analyzing cancer subtypes using multi-omics data is mostly derived from population cancer sample data and ignores the differences between different cancer samples. Therefore, the joint analysis of multi-omics based on a single sample may reveal more information about the differences between individual cancers. A strategy for identifying cancer subtypes is proposed based on Single-sample information gain (SSIG) which construct sample feature matrix by considering the heterogeneity of sample. Applying this strategy to current popular subtype identification methods, cancer subtypes can be identified more accurately and the mechanism of cancer can be found from the perspective of a single sample. By comparing different methods in different clustering measure, and using survival analysis, it is shown that SSIG is more suitable for cancer subtype identification than the original multi-omics data, and it is easier to mine the cancer subtype classification mechanism hidden behind the data.     

The Varietal Influence of Flavour Precursors from Grape Marc on Monoterpene and C13-Norisoprenoid Profiles in Wine as Determined by Membrane-Assisted Solvent Extraction (MASE) GC-MS

The winemaking by-product grape marc (syn. pomace) contains significant quantities of latent flavour in the form of flavour precursors which can be extracted and used to modulate the volatile composition of wine via chemical hydrolysis. Varietal differences in grapes are widely known with respect to their monoterpene content, and this work aimed to extend this knowledge into differences due to cultivar in volatiles derived from marc precursors following wine-like storage conditions. Marc extracts were produced from floral and non-floral grape lots on a laboratory-scale and from Muscat Gordo Blanco marc on a winery -scale, added to a base white wine for storage over five to six months, before being assessed using a newly developed membrane-assisted solvent extraction gas chromatography-mass spectrometry (GC-MS) method. The geraniol glucoside content of the marc extracts was higher than that of juices produced from each grape lot. In all wines with added marc extract from a floral variety, geraniol glucoside concentration increased by around 150–200%, with increases also observed for non-floral varieties. The relative volatile profile from extracts of the floral varieties was similar but had varied absolute concentrations. In summary, while varietally pure extracts would provide the greatest control over flavour outcomes when used in winemaking, aggregated marc parcels from floral cultivars may provide a mechanism to simplify the production logistics of latent flavour extracts for use in the wine sector.     

An Efficient Deacidification Process for Safflower Seed Oil with High Nutritional Property through Optimized Ultrasonic-Assisted Technology

Safflower seed oil (SSO) is considered to be an excellent edible oil since it contains abundant essential unsaturated fatty acids and lipid concomitants. However, the traditional alkali-refined deacidification process of SSO results in a serious loss of bioactive components of the oil and also yields massive amounts of wastewater. In this study, SSO was first extracted by ultrasonic-assisted ethanol extraction (UAEE), and the extraction process was optimized using random centroid optimization. By exploring the effects of ethanol concentration, solid–liquid ratio, ultrasonic time, and the number of deacidification times, the optimum conditions for the deacidification of safflower seed oil were obtained as follows: ethanol concentration 100%, solid–liquid ratio 1:4, ultrasonic time 29 min, and number of deacidification cycles (×2). The deacidification rate was 97.13% ± 0.70%, better than alkali-refining (72.16% ± 0.13%). The values of acid, peroxide, anisidine and total oxidation of UAEE-deacidified SSO were significantly lower than those of alkali-deacidified SSO (p < 0.05). The contents of the main lipid concomitants such as tocopherols, polyphenols, and phytosterols in UAEE-decidified SSO were significantly higher than those of the latter (p < 0.05). For instance, the DPPH radical scavenging capacity of UAEE-processed SSO was significantly higher than that of alkali refining (p < 0.05). The Pearson bivariate correlation analysis before and after the deacidification process demonstrated that the three main lipid concomitants in SSO were negatively correlated with the index of peroxide, anisidine, and total oxidation values. The purpose of this study was to provide an alternative method for the deacidification of SSO that can effectively remove free fatty acids while maintaining the nutritional characteristics, physicochemical properties, and antioxidant capacity of SSO.     

Quantum Coherences and Classical Inhomogeneities as Equivalent Thermodynamics Resources

Quantum energy coherences represent a thermodynamic resource, which can be exploited to extract energy from a thermal reservoir and deliver that energy as work. We argue that there exists a closely analogous classical thermodynamic resource, namely, energy-shell inhomogeneities in the phase space distribution of a system’s initial state. We compare the amount of work that can be obtained from quantum coherences with the amount that can be obtained from classical inhomogeneities, and find them to be equal in the semiclassical limit. We thus conclude that coherences do not provide a unique thermodynamic advantage of quantum systems over classical systems, in situations where a well-defined semiclassical correspondence exists.     

军用计算机系统中的电磁信息泄漏和防护

分析了计算机电磁信息泄漏的途径、机理、特点及接收和还原,提出了军用计算机系统中电磁信息防护的几种方法。     

A New Strategy in Boosting Information Spread

Finding a seed set to propagate more information within a specific budget is defined as the influence maximization (IM) problem. The traditional IM model contains two cardinal aspects: (i) the influence propagation model and (ii) effective/efficient seed-seeking algorithms. However, most of models only consider one kind of node (i.e., influential nodes), ignoring the role of other nodes (e.g., boosting nodes) in the spreading process, which are irrational. Specifically, in the real-world propagation scenario, the boosting nodes always improve the spread of influence from the initial activated seeds, which is an efficient and cost-economic measure. In this paper, we consider the realistic budgeted influence maximization (RBIM) problem, which contains two kind of nodes to improve the diffusion of influence. Facing the newly modified objective function, we propose a novel B-degree discount algorithm to solve it. The novel B-degree discount algorithm which adopts the cost-economic boosting nodes to retweet the influence from the predecessor nodes can greatly reduce the cost, and performs better than other state-of-the-art algorithms in both effect and efficiency on RBIM problem solving.