Cadinane sesquiterpenes from the stems and branches of Illicium ternstroemioides.

Three new cadinane sesquiterpenes (1-3) and three known sesquiterpenes were isolated from the stems and branches of Illicium ternstroemioides A. C. Smith. The structures of the new compounds were elucidated by extensive analysis of spectroscopic and HRESIMS data. The structures of illiternins A-C (1-3) were confirmed by single crystal X-ray diffraction, allowing for the determination of their absolute configurations. Compounds 3 and 6 exhibited antiviral activity against Coxsackievirus B3 with IC50 values of 33.3 and 57.7 µM, respectively.

An Influence Maximization Algorithm for Dynamic Social Networks Based on Effective Links.

The connection between users in social networks can be maintained for a certain period of time, and the static network structure formed provides the basic conditions for various kinds of research, especially for discovering customer groups that can generate great influence, which is important for product promotion, epidemic prevention and control, and public opinion supervision, etc. However, the computational process of influence maximization ignores the timeliness of interaction behaviors among users, the screened target users cannot diffuse information well, and the time complexity of relying on greedy rules to handle the influence maximization problem is high. Therefore, this paper analyzes the influence of the interaction between nodes in dynamic social networks on information dissemination, extends the classical independent cascade model to a dynamic social network dissemination model based on effective links, and proposes a two-stage influence maximization solution algorithm (Outdegree Effective Link-OEL) based on node degree and effective links to enhance the efficiency of problem solving. In order to verify the effectiveness of the algorithm, five typical influence maximization methods are compared and analyzed on four real data sets. The results show that the OEL algorithm has good performance in propagation range and running time.

Nitrogen-enriched micro-mesoporous carbon derived from polymers organic frameworks for high-performance capacitive deionization.

Nitrogenization is an effective method for improving the capacitive deionization (CDI) performance of porous carbon materials. In particular, polymer organic frameworks with heteroatom doping, containing an ordered pore structure and excellent electrochemical stability, are ideal precursors for carbon materials for high-performance CDI. In this study, a nitrogen-enriched micro-mesoporous carbon (NMC) electrode was fabricated by carbonizing a Schiff base network-1 at 500, 600, and 700 °C. Scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, N2 adsorption-desorption, the contact angle of water, cyclic voltammetry, and electrochemical impedance spectroscopy were used to characterize the morphological structure, wettability, Brunauer-Emmett-Teller surface areas, and electrochemical performance of the NMCs. The results showed that the NMC carbonized at 600°C achieved the best specific capacitance (152.33 F/g), as well as a high electrosorption capacity (25.53 mg/g) because of its chemical composition (15.57% N) and surface area (312 m2/g). These findings prove that NMC is viable as an electrode material for desalination by high-performance CDI applications.

Illihenin A: An Antiviral Sesquiterpenoid with a Cage-like Tricyclo[6.2.2.01,5]dodecane Skeleton from Illicium henryi.

Illihenin A (1), a novel sesquiterpenoid, was isolated from the roots of Illicium henryi. The structure was determined by spectroscopic analyses, ECD calculation, and single-crystal X-ray diffraction. Compound 1 represents a class of novel 5/7/6 tricyclic sesquiterpenoids featuring a rare cage-like tricyclo[6.2.2.01,5]dodecane core. A plausible biosynthetic pathway of 1 by rearrangement of allo-cedrane is proposed. Additionally, 1 showed potent antiviral activity against coxsackievirus B3 with an IC50 value of 2.87 µM.

[A new seco-prezizaane-type sesquiterpene lactone from stems and branches of Illicium ternstroemioides].

Three seco-prezizaane-type sesquiterpene lactones, one phenylpropanoid, and two lignans were isolated from the 95% ethanol extract of stems and branches of Illicium ternstroemioides with silica gel column chromatography, ODS column chromatography, and preparative HPLC. Based on the spectral data, they were identified as burmanicumolide D(1), veranisatin A(2), veranisatin B(3), dihydroconiferylalcohol(4), pinoresinol(5),(-)-matairesinol(6), respectively. Among them, compound 1 was a new seco-prezizaane-type sesquiterpene lactone, and 2-6 were obtained from this plant for the first time. None of these compounds display antiviral or cytotoxic activities.

Ion-exchange polymers modified bacterial cellulose electrodes for the selective removal of nitrite ions from tail water of dyeing wastewater.

Ion-exchange polymer and modified carbonization bacterial cellulose (CBC) electrodes were fabricated using varying amounts of cation-exchange polymers (glutaric acid (GA) and sulfosuccinic acid (SSA)) and assembled within an asymmetric capacitive deionization unit (p-CDI). The performance of selective NO2- electro-adsorption was studied. The AC/CBC-SSA group showed a better salt adsorption capacity (14.56 mg/g) and nitrite removal efficiency (71.01%) than the AC/CBC-GA (10.72 mg/g, 47.83%) and AC/AC (4.81 mg/g, 12.74%) groups. It was confirmed that the CBC-SSA/GA electrodes enhanced nitrite selectivity and increased the adsorption capacity, and the total amounts of adsorbed anions increased when the applied voltage was increased from 0.8 to 1.2 V, while the molar fraction of nitrate decreased. The competitive and preferential adsorption of anions was further investigated using different binary solutions of anions and occurred in the following sequence: NO2- >SO42- >NO3- >F-≈ Cl-. Furthermore, the p-CDI units were applied to remove nitrite in real wastewater samples, and the results showed that they had excellent reusability and application for use in dyeing wastewater treatment.

New hexalactone derivatives and a pair of new oxaspiro-carbon epimeric glycosides from the fruits of Illicium lanceolatum.

Five new compounds (1-5), including three hexalactone derivatives (1-3) and a pair of new oxaspiro-carbon epimeric glycosides (4 and 5), and six known compounds (6-11) were obtained from the fruits of Illicium lanceolatum. The structures of the new compounds were elucidated using extensive spectroscopic data. The absolute configurations of compounds 1-3 were determined by an analysis of their CD spectra. It was determined that compounds 4 and 5, which are epimeric at C-5, possess the same 1-oxaspiro[4,5]decane-7α,8α,9ß-triol moiety. Plausible biogenetic pathways for 4 and 5 derived from the key precursor shikimic acid were proposed. Compounds 1-11 were all assayed on monosodium glutamate-induced human neuroblastoma SH-SY5Y cell damage. The results demonstrated that compounds 4, 5, and 8-10 possess potential neuroprotective effects. The anti-inflammatory, antiviral, and cytotoxic activities of 1-11 were also evaluated.

[Investigation on seco-prezizaane sesquiterpenes from fruits of Illicium lanceolatum and their neuroprotection activity].

Ten seco-prezizaane sesquiterpenes were isolated from the water-soluble fraction of the fruit of Illicium lanceolatum using the combined methods of silica gel column chromatography,Sephadex LH-20 column chromatography,and RP-preparative HPLC. They were elucidated as majusanol E( 1),2α-hydroxycycloparviflorolide( 2),2ß-hydroxy-3,6-dedioxypseudoanisatin( 3),majusanol A( 4),merrillianone( 5),cycloparvifloralone( 6),3α-hydroxycycloparvifloralone( 7),1,2-dehydrocycloparvifloralone( 8),henrylactone C( 9),and( 11) 7,14-ortholactone-3α-hydroxyfloridanolide( 10) according to the NMR data. All compounds were obtained from this plant for the first time. Neuroprotection activity,anti-Coxsackie B3 virus,and anti-H3 N2 virus experiments were carried out to test their bioactivities. The bioassay results showed that compounds 1,4,6,7,9 and 10 displayed weak protective effects of the damage of nerve SH-SY5 Y cell induced by monosodium glutamate.

A Strategy toward Collaborative Filter Recommended Location Service for Privacy Protection.

A new collaborative filtered recommendation strategy was proposed for existing privacy and security issues in location services. In this strategy, every user establishes his/her own position profiles according to their daily position data, which is preprocessed using a density clustering method. Then, density prioritization was used to choose similar user groups as service request responders and the neighboring users in the chosen groups recommended appropriate location services using a collaborative filter recommendation algorithm. The two filter algorithms based on position profile similarity and position point similarity measures were designed in the recommendation, respectively. At the same time, the homomorphic encryption method was used to transfer location data for effective protection of privacy and security. A real location dataset was applied to test the proposed strategy and the results showed that the strategy provides better location service and protects users' privacy.

CS²-Collector: A New Approach for Data Collection in Wireless Sensor Networks Based on Two-Dimensional Compressive Sensing.

In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular choices to reduce the energy consumption of the data collection in WSNs. The existing solutions only consider sparsity of sensors' data from either temporal or spatial dimensions. In this paper, we propose a novel data collection strategy, CS²-collector, for WSNs based on the theory of Two Dimensional Compressive Sensing (2DCS). It exploits both temporal and spatial sparsity, i.e., 2D-sparsity of WSNs and achieves significant gain on the tradeoff between the compression ratio and reconstruction accuracy as the numerical simulations and evaluations on different types of sensors' data. More intuitively, with the same given energy budget, CS²-collector provides significantly more accurate reconstruction of the profile of the physical phenomena that are temporal-spatially sparse.

Mobile recommendation based on link community detection.

Since traditional mobile recommendation systems have difficulty in acquiring complete and accurate user information in mobile networks, the accuracy of recommendation is not high. In order to solve this problem, this paper proposes a novel mobile recommendation algorithm based on link community detection (MRLD). MRLD executes link label diffusion algorithm and maximal extended modularity (EQ) of greedy search to obtain the link community structure, and overlapping nodes belonging analysis (ONBA) is adopted to adjust the overlapping nodes in order to get the more accurate community structure. MRLD is tested on both synthetic and real-world networks, and the experimental results show that our approach is valid and feasible.

Diverse prenylated C6-C3 derivatives from the stems and branches of Illicium ternstroemioides A. C. Smith with anti-inflammatory and antiviral activities.

Fifteen unreported prenylated C6-C3 derivatives (1-15) were isolated from the stems and branches of Illicium ternstroemioides A. C. Smith, including one bis-prenylated C6-C3 derivative (1), three prenylated C6-C3 derivative-shikimic acid ester hybrids (2-4) and 11 prenylated C6-C3 monomers (5-15). The structures of compounds 1-15 were elucidated by spectroscopic analysis (UV, IR, 1D and 2D NMR, and HRESIMS). The absolute configurations of the compounds were determined using electronic circular dichroism (ECD), induced circular dichroism (ICD), and the modified Mosher's method. Among the isolates, compounds 11, 12, and 15 exhibited significant anti-inflammatory activities by inhibiting the nitric oxide with IC50 values ranging from 1.89 to 24.83 µM in lipopolysaccharide-stimulated murine RAW 264.7 macrophages and murine BV2 microglial cells; compounds 2, 3, and 7 exhibited antiviral activitives against Coxsackievirus B3 with an IC50 value of 33.3, 25.9, and 27.8 µM, respectively.

Intelligent Classification of Japonica Rice Growth Duration (GD) Based on CapsNets.

Rice cultivation in cold regions of China is mainly distributed in Heilongjiang Province, where the growing season of rice is susceptible to low temperature and cold damage. Choosing and planting rice varieties with suitable GD according to the accumulated temperate zone is an important measure to prevent low temperature and cold damage. However, the traditional identification method of rice GD requires lots of field investigations, which are time consuming and susceptible to environmental interference. Therefore, an efficient, accurate, and intelligent identification method is urgently needed. In response to this problem, we took seven rice varieties suitable for three accumulated temperature zones in Heilongjiang Province as the research objects, and we carried out research on the identification of japonica rice GD based on Raman spectroscopy and capsule neural networks (CapsNets). The data preprocessing stage used a variety of methods (signal.filtfilt, difference, segmentation, and superposition) to process Raman spectral data to complete the fusion of local features and global features and data dimension transformation. A CapsNets containing three neuron layers (one convolutional layer and two capsule layers) and a dynamic routing protocol was constructed and implemented in Python. After training 160 epochs on the CapsNets, the model achieved 89% and 93% accuracy on the training and test datasets, respectively. The results showed that Raman spectroscopy combined with CapsNets can provide an efficient and accurate intelligent identification method for the classification and identification of rice GD in Heilongjiang Province.

DPWSS: differentially private working set selection for training support vector machines.

Support vector machine (SVM) is a robust machine learning method and is widely used in classification. However, the traditional SVM training methods may reveal personal privacy when the training data contains sensitive information. In the training process of SVMs, working set selection is a vital step for the sequential minimal optimization-type decomposition methods. To avoid complex sensitivity analysis and the influence of high-dimensional data on the noise of the existing SVM classifiers with privacy protection, we propose a new differentially private working set selection algorithm (DPWSS) in this paper, which utilizes the exponential mechanism to privately select working sets. We theoretically prove that the proposed algorithm satisfies differential privacy. The extended experiments show that the DPWSS algorithm achieves classification capability almost the same as the original non-privacy SVM under different parameters. The errors of optimized objective value between the two algorithms are nearly less than two, meanwhile, the DPWSS algorithm has a higher execution efficiency than the original non-privacy SVM by comparing iterations on different datasets. To the best of our knowledge, DPWSS is the first private working set selection algorithm based on differential privacy.

Prenylated C6-C3 derivatives from the stems and branches of Illicium ternstroemioides A. C. Smith with antiviral activity.

Thirteen compounds were isolated from the lipid-soluble extracts of Illicium ternstroemioides A. C. Smith, including eleven previously undescribed prenylated C6-C3 compounds, a previously undescribed prenylated C6-C3 derivative-abscisic acid ester hybrid, and a known compound (4S)-illicinone I. Their structures and configurations were mainly elucidated by spectroscopic analyses, CD experiments and X-ray crystallography. (2S,4R,11S)-4-O-methyl-12-chloroillifunone C, (2S,4R,11R)-2,3-dihydro-4-O-methyl illioliganfunone D, and illiternfunol A were found to exhibit weak activity against Coxsackievirus B3, with IC50 values ranging from 27.8 to 33.3 µM. Illiternone B exhibited more potent activities against Coxsackievirus B3 and influenza virus A than did its geometric isomer illiternone A, with IC50 values of 7.7 µM and 2.5 µM, respectively. None of these compounds displayed cytotoxic activities.

Highly oxidized sesquiterpenes from the fruits of Illicium lanceolatum A. C. Smith.

Ten undescribed highly oxidized sesquiterpenes and six known sesquiterpenes were isolated from H2O-soluble part of the fruits of Illicium lanceolatum A. C. Smith. The structures of undescribed compounds were elucidated by interpretation of spectroscopic data, and the absolute configurations of 2α-hydroxyneoanisatinic acid, (1R,5R,6S,7R,9R,10R)-3,4-dehydro-12-hydroxy-floridanolide, and (1R,4S,5R,6S,7S,9S)-1-deoxy-13-hydroxymerrilactone B were determined by the single-crystal X-ray diffraction analysis. Illilanceolatin A was the first example of a seco-prezizaane type sesquiterpene with a hemiacetal moiety located at C-10. 2α-Hydroxyneoanisatinic acid and anisatinic acid were two naturally occurring undescribed seco-prezizaane type sesquiterpenes with a 5/5/6 tricyclic carbon skeleton. Plausible biosynthetic pathways of the isolated polycyclic and highly oxidized sesquiterpenes derived from the intermediate allo-cedrane were proposed. (1R,5R,6S,7R,9R,10R)-3,4-dehydro-12-hydroxy-floridanolide, 1,3-dihydroxyneoanisatin, and 2α-hydroxyneoanisatin displayed neuroprotective effects with protection rates of 19.9, 22.7 and 24.3% at 10 µM, respectively. Additionally, the preliminary acute toxicity of anisatinic acid was also evaluated.

Fiber-Integrated Reversibly Wavelength-Tunable Nanowire Laser Based on Nanocavity Mode Coupling.

As an ideal miniaturized light source, wavelength-tunable nanolasers capable of emitting a wide spectrum stimulate intense interests for on-chip optoelectronics, optical communications, and spectroscopy. However, realization of such devices remains a major challenge because of extreme difficulties in achieving continuously reversibly tunable gain media and high quality (Q)-factor resonators on the nanoscale simultaneously. Here, exploiting single bandgap-graded CdSSe NWs and a Fabry-Pérot/whispering gallery mode (FP/WGM) coupling cavity, a free-standing fiber-integrated reversibly wavelength-tunable nanolaser covering a 42 nm wide spectrum at room temperature with high stability and reproducibility is demonstrated. In addition, a 1.13 nm tuning spectral resolution is realized. The substrate-free device design enables integration in optical fiber communications and information. With reversible and wide, continuous tunability of emission color and precise control per step, our work demonstrates a general approach to nanocavity coupling affording high Q-factors, enabling an ideal miniaturized module for a broad range of applications in optics and optoelectronics, with optical fiber integration.

Microblog sentiment analysis using social and topic context.

Analyzing massive user-generated microblogs is very crucial in many fields, attracting many researchers to study. However, it is very challenging to process such noisy and short microblogs. Most prior works only use texts to identify sentiment polarity and assume that microblogs are independent and identically distributed, which ignore microblogs are networked data. Therefore, their performance is not usually satisfactory. Inspired by two sociological theories (sentimental consistency and emotional contagion), in this paper, we propose a new method combining social context and topic context to analyze microblog sentiment. In particular, different from previous work using direct user relations, we introduce structure similarity context into social contexts and propose a method to measure structure similarity. In addition, we also introduce topic context to model the semantic relations between microblogs. Social context and topic context are combined by the Laplacian matrix of the graph built by these contexts and Laplacian regularization are added into the microblog sentiment analysis model. Experimental results on two real Twitter datasets demonstrate that our proposed model can outperform baseline methods consistently and significantly.

Improving the performance of lexicon-based review sentiment analysis method by reducing additional introduced sentiment bias.

Sentiment analysis is widely studied to extract opinions from user generated content (UGC), and various methods have been proposed in recent literature. However, these methods are likely to introduce sentiment bias, and the classification results tend to be positive or negative, especially for the lexicon-based sentiment classification methods. The existence of sentiment bias leads to poor performance of sentiment analysis. To deal with this problem, we propose a novel sentiment bias processing strategy which can be applied to the lexicon-based sentiment analysis method. Weight and threshold parameters learned from a small training set are introduced into the lexicon-based sentiment scoring formula, and then the formula is used to classify the reviews. In this paper, a completed sentiment classification framework is proposed. SentiWordNet (SWN) is used as the experimental sentiment lexicon, and review data of four products collected from Amazon are used as the experimental datasets. Experimental results show that the bias processing strategy reduces polarity bias rate (PBR) and improves performance of the lexicon-based sentiment analysis method.

Protection of Location Privacy Based on Distributed Collaborative Recommendations.

In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users' location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system. In this strategy, each node establishes profiles of their own location information. When requests for location services appear, the user can obtain the corresponding location services according to the recommendation of the neighboring users' location information profiles. If no suitable recommended location service results are obtained, then the user can send a service request to the server according to the construction of a k-anonymous data set with a centroid position of the neighbors. In this strategy, we designed a new model of distributed collaborative recommendation location service based on the users' location information profiles and used generalization and encryption to ensure the safety of the user's location information privacy. Finally, we used the real location data set to make theoretical and experimental analysis. And the results show that the strategy proposed in this paper is capable of reducing the frequency of access to the location server, providing better location services and protecting better the user's location privacy.