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The electrical power system (EPS) has been heavily stressed due to high load demand. It operates close to the total capacity limits, resulting in voltage instability that can lead to voltage collapse. In this regard, incorporating flexible alternating current transmission system (FACTS) devices and renewable energy sources (RESs) to obtain the optimum values of the generator voltage, reactive compensation, and transformer tab in optimal reactive power dispatch (ORPD) is essential in increasing the reliability and safety of the system. ORPD involves discrete and continuous variables, which are nonlinear, noncontinuous, non-convex, and complex problems. The objective functions of ORPD are reduction in active power loss (Ploss), voltage deviation, and voltage profile enhancement. This paper presents a recent advancement of the ORPD problem, mathematical formulation of the objectives function, and a summary of various metaheuristic optimization methods (single and hybrid) used to solve the ORPD problems. The hybrid method combines two or more methods to improve the demerits of one method to obtain a quality solution to a problem. This review covered incorporating FACTS devices and RESs used in solving the ORPD problem to reduce the active Ploss and improve the voltage profile in the EPS. The benefits of FACTS devices and RESs are also discussed. Also, various metaheuristic algorithms (single, modified, and hybrid) employed to solve the ORPD problem were discussed. The future direction for researchers in this field was provided to give insight into the applicability and performance. Overall, this research explores different techniques used in solving ORPD problems from the optimization point of view to incorporating RESs and FACTS devices to obtain quality solutions. Some existing methods do not guarantee an optimum solution, but incorporating RESs and FACTS devices will help attain the best solution to the problem for better power system operation to improve system reliability and voltage profile. Based on the review journal, it can be concluded that hybrid techniques offer efficient quality solutions to the ORPD problem. [ABSTRACT FROM AUTHOR]

Credit risk prediction is a crucial task for financial institutions. The technological advancements in machine learning, coupled with the availability of data and computing power, has given rise to more credit risk prediction models in financial institutions. In this paper, we propose a stacked classifier approach coupled with a filter-based feature selection (FS) technique to achieve efficient credit risk prediction using multiple datasets. The proposed stacked model includes the following base estimators: Random Forest (RF), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB). Furthermore, the estimators in the Stacked architecture were linked sequentially to extract the best performance. The filter- based FS method that is used in this research is based on information gain (IG) theory. The proposed algorithm was evaluated using the accuracy, the F1-Score and the Area Under the Curve (AUC). Furthermore, the Stacked algorithm was compared to the following methods: Artificial Neural Network (ANN), Decision Tree (DT), and k-Nearest Neighbour (KNN). The experimental results show that stacked model obtained AUCs of 0.934, 0.944 and 0.870 on the Australian, German and Taiwan datasets, respectively. These results, in conjunction with the accuracy and F1-score metrics, demonstrated that the proposed stacked classifier outperforms the individual estimators and other existing methods. [ABSTRACT FROM AUTHOR]

The underlying mechanism of chronic hepatitis B virus (HBV) functional cure by interferon (IFN), especially in patients with low HBsAg and/or young ages, is still unresolved due to the lack of surrogate models. Here, we generate a type I interferon receptor humanized mouse (huIFNAR mouse) through a CRISPR/Cas9-based knock-in strategy. Then, we demonstrate that human IFN stimulates gene expression profiles in huIFNAR peripheral blood mononuclear cells (PBMCs) are similar to those in human PBMCs, supporting the representativeness of this mouse model for functionally analyzing human IFN in vivo. Next, we reveal the tissue-specific gene expression atlas across multiple organs in response to human IFN treatment; this pattern has not been reported in healthy humans in vivo. Finally, by using the AAV-HBV model, we test the antiviral effects of human interferon. Fifteen weeks of human PEG-IFNα2 treatment significantly reduces HBsAg and HBeAg and even achieves HBsAg seroconversion. We observe that activation of intrahepatic monocytes and effector memory CD8 T cells by human interferon may be critical for HBsAg suppression. Our huIFNAR mouse can authentically respond to human interferon stimulation, providing a platform to study interferon function in vivo. PEG-IFNα2 treatment successfully suppresses intrahepatic HBV replication and achieves HBsAg seroconversion. There is increasing evidence that treatment of hepatitis B with interferon alpha can be beneficial. Here, Wang et al, present a type 1 interferon receptor humanized mouse model and characterize it as a platform in which to study interferon function in vivo. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the changes in oocytes at the transcriptome level after applying continuous microvibrational mechanical stimulation to human immature oocytes during in vitro maturation. Methods: The discarded germinal-vesicle stage (GV) oocytes with no fertilization value after oocytes retrieval in assisted reproduction cycles were collected. Part of them was stimulated with vibration (n = 6) at 10 Hz for 24 h after obtaining informed consent; the other was cultured in static condition (n = 6). Single-cell transcriptome sequencing was used to detect the differences in oocyte transcriptome compared with the static culture group. Results: The applied 10-Hz continuous microvibrational stimulation altered the expression of 352 genes compared with the static culture. Gene Ontology (GO) analysis suggested that the altered genes were mainly enriched with 31 biological processes. The mechanical stimulation upregulated 155 of these genes and downregulated 197 genes. Among them, the genes related to mechanical signaling, such as protein localization to intercellular adhesion (DSP and DLG-5) and cytoskeleton (DSP, FGD6, DNAJC7, KRT16, KLHL1, HSPB1, MAP2K6), were detected. DLG-5, which was related to protein localization to intercellular adhesion, was selected for immunofluorescence experiments based on the transcriptome sequencing results. The protein expression of DLG-5 in the microvibration-stimulated oocytes was higher than that in the static culture oocytes. Conclusions: Mechanical stimulation affects the transcriptome during oocyte maturation, causing the express changes in intercellular adhesion and cytoskeleton-related genes. We speculate that the mechanical signal may be transmitted to the cell through DLG-5 protein and cytoskeleton-related protein to regulate cellular activities. [ABSTRACT FROM AUTHOR]

The recent advances of e-commerce and e-payment systems have sparked an increase in financial fraud cases such as credit card fraud. It is therefore crucial to implement mechanisms that can detect the credit card fraud. Features of credit card frauds play important role when machine learning is used for credit card fraud detection, and they must be chosen properly. This paper proposes a machine learning (ML) based credit card fraud detection engine using the genetic algorithm (GA) for feature selection. After the optimized features are chosen, the proposed detection engine uses the following ML classifiers: Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Artificial Neural Network (ANN), and Naive Bayes (NB). To validate the performance, the proposed credit card fraud detection engine is evaluated using a dataset generated from European cardholders. The result demonstrated that our proposed approach outperforms existing systems. [ABSTRACT FROM AUTHOR]

Esophageal squamous-cell carcinoma (ESCC), one of the most prevalent and lethal malignant disease, has a complex but unknown tumor ecosystem. Here, we investigate the composition of ESCC tumors based on 208,659 single-cell transcriptomes derived from 60 individuals. We identify 8 common expression programs from malignant epithelial cells and discover 42 cell types, including 26 immune cell and 16 nonimmune stromal cell subtypes in the tumor microenvironment (TME), and analyse the interactions between cancer cells and other cells and the interactions among different cell types in the TME. Moreover, we link the cancer cell transcriptomes to the somatic mutations and identify several markers significantly associated with patients' survival, which may be relevant to precision care of ESCC patients. These results reveal the immunosuppressive status in the ESCC TME and further our understanding of ESCC. Esophageal squamous-cell carcinomas (ESCC) have poor prognosis, and detailed molecular profiles are necessary to identify prognostic markers. Here the authors analyse 60 ESCC patient samples using scRNA-seq, TCR-seq and genomics; they find mucosal immunity markers associated with survival and immunosuppressive microenvironments. [ABSTRACT FROM AUTHOR]

The mains signal is a complex fusion of various electrical equipment load signals in a building. In the non-intrusive load monitoring recognition, our main aim is to be able to extract as much load features as possible from the complex aggregate mains signal in a simpler way through a computer vision-based approach as opposed to the powers series signal approach. Power series methods, which are one dimensional in nature, suffer from poor aggregate and load signal feature localization necessitating a larger training dataset spanning very long time periods and normally require signal formatting and pre-processing. We use Gramian angular summation fields to transform the power series into a reduced image dataset that contains a rich set of localized signal features. A computer vision approach allows us to capture as much information as possible, and then propose an image-based mains load recognition system with high performance. In this paper for the entire recognition system, we use convolutional neural networks that very well adapted to vision recognition. The load signal image disaggregation is achieved through the powerful stacked denoising autoencoder noise extraction network. To test the proposed system, some simulations and comparisons are carried out and the results show that our easier to handle method can achieve acceptable performance. [ABSTRACT FROM AUTHOR]

Background: Ischemic stroke is a serious cardiovascular disease with high morbidity and mortality rates that affects millions of people worldwide.Currently, the only therapy with proven efficacy for acute ischemic stroke is alteplase, however, it still has many shortcomings and limitations. Therefore,we screen new compounds from traditional Chinese medicine to explore their efficacy against ischemic reperfusion injury. Procyanidins, a natural productextracted from grapes seed, which have been shown can ameliorate cerebral ischemic injury. However, the underlying mechanism is still not very clear. Theaim of this study was to investigate the effect of procyanidins on middle cerebral artery occlusion/reperfusion (MCAO/R)-mediated cerebral ischemic injuryand its underlying possible mechanisms. Methods: SD rats were used to evaluate the effect of procyanidins on MCAO/R induced cerebral ischemic injury in vivo. Histological analysis was used toassess neuronal apoptosis. Cell signaling was assayed by Western blot. Results: In this study, we found that procyanidins can significantly ameliorate the middle cerebral artery occlusion/reperfusion (MCAO/R)-mediatedneurological deficits, and relieved brain edema, cerebral infarction volume, histopathological damage and apoptosis in rats. In addition, procyanidins canalso markedly inhibit MCAO/R and oxygen-glucose deprivation/reoxygenation (OGD/R)-mediated activation of TLR4-p38-NF-κB-NLRP3 signalingpathway in vitro and in vivo. Moreover, procyanidins can inhibit MCAO/R and OGD/R-induced the production of inflammatory cytokines such asinterleukin-1β (IL-1β) in vitro and in vivo. Besides, treatment with TLR4 inhibitor (Cli-095) in BV2 cell also shows the same effect. Conclusion: Altogether, these data suggested that procyanidins exerted a potential neuroprotective effect may by inhibit the TLR4-p38-NF-κB-NLRP3signaling pathway in the brain in MCAO/R rats. [ABSTRACT FROM AUTHOR]

The relationship between ζ-potential and surface defects of micro-nano sized hexagram-like α-Al2O3 particles was investigated in this paper. The 2D α-Al2O3 particles was prepared by the phase transformation of gibbsite precursor by the following steps during calcination in air: Al(OH)3 → AlOOH→a-Al2O3 → θ-Al2O3 → α-Al2O3. Resulting from the varied intensities of surface defects, as-prepared α-Al2O3 samples have different Eg values around 4.5 eV, which is much narrower than that of bulk α-Al2O3. While benefiting from the interface reaction between surface > AlOH0 and water (>AlOH0 + OH−⇋ > AlO− + H2O), as-prepared α-Al2O3 suspensions can reach their specific pHE values after stirring for 8 h at room temperature. And the measured IEP values of Al2O3-1250°C-2 h, Al2O3-1250°C-3 h, and Al2O3–1300 °C-3 h, which remain 2D morphology, are 7.96, 8.67, and 8.86, respectively. This study is significant and useful for making the industrial applications of α-Al2O3 valid. [ABSTRACT FROM AUTHOR]

Multimodal optimization is still one of the most challenging tasks in the evolutionary computation field, when multiple global and local optima need to be effectively and efficiently located. In this paper, a niching particle swarm optimization (PSO)-based Euclidean distance and hierarchical clustering (EDHC) for multimodal optimization is proposed. This technique first uses the Euclidean distance-based PSO algorithm to perform preliminarily search. In this phase, the particles are rapidly clustered around peaks. Secondly, hierarchical clustering is applied to identify and concentrate the particles distributed around each peak to finely search as a whole. Finally, a small-world network topology is adopted in each niche to improve the exploitation ability of the algorithm. At the end of this paper, the proposed EDHC-PSO algorithm is applied to the traveling salesman problems (TSP) after being discretized. The experiments demonstrate that the proposed method outperforms existing niching techniques on benchmark problems and is effective for TSP. [ABSTRACT FROM AUTHOR]

In this study, a Ni-Co-Mn-Cd-based precursor was synthesized using a solvothermal method and the Li(Ni0.6Co0.2Mn0.2O2)xCd1-xO2 cathode materials were prepared using a high-temperature solid-phase method. Scanning electron microscopy (SEM), X-ray powder diffraction (XRD), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) were used to determine the morphology, structure, elemental composition, and electronic state of the pristine and Cd-doped cathode materials. The electrochemical tests indicated that the Cd-doped samples exhibited better electrochemical performance than the pristine material; specifically, at a doping amount of 0.01 mol, the initial discharge capacity was 186.3 mAh g−1 with a capacity retention of 87.49% after 200 cycles at a current rate of 0.5 C and a capacity retention of 72.43% after 300 cycles at a current rate of 2 C, whereas the pristine material only had an initial capacity of 173.2 mAh g−1 and a capacity retention of 61.25% and 41.09% for the same current rate and cycle number, respectively. In addition, at 8 C, the discharge capacity was 129.8 mAh g−1 for the Cd-doped samples but only 119.6 mAh g−1 for the pristine material. The enhanced electrochemical performance was attributed to the in situ doping modification during the synthesis process of the precursor. This approach effectively stabilized the crystal structure, improved the electronic conductivity of the material, and reduced the impact of the hydrofluoric acid (HF) on the electrode surface due to the generation of CdF2 during the cycle process. [ABSTRACT FROM AUTHOR]

Herein, we present the use of lithium tetrafluoroborate (LiBF4) as an electrolyte salt for wide-temperature electrolytes in lithium-ion batteries. The research focused on the application of blend salts to exhibit their synergistic effect especially in a wide temperature range. In the study, LiCoO2 was employed as the cathode material; LiBF4 and lithium difluoro(oxalate)borate (LiODFB) were added to an electrolyte consisting of ethylene carbonate (EC), propylene carbonate (PC), and ethyl methyl carbonate (EMC). The electrochemical performance of the resulting electrolyte was evaluated through various analytical techniques. Analysis of the electrical conductivity showed the relationship among solution conductivity, the electrolyte composition, and temperature. Cyclic voltammetry (CV), charge-discharge cycling, and AC impedance measurements were used to investigate the capacity and cycling stability of the LiCoO2 cathode in different electrolyte systems and at different temperatures. Scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) were applied to analyze the surface properties of the LiCoO2 cathode after cycling. The results indicated that the addition of a small amount of LiODFB into the LiBF4-based electrolyte system (LiBF4/LiODFB of 8:2) may enhance the electrochemical performance of the LiCoO2 cell over a relatively wide temperature range and improve the cyclability of the LiCoO2 cell at 60 °C. [ABSTRACT FROM AUTHOR]

Magnetic sepiolite was synthesized by chemical precipitation of Fe and Fe at sepiolite suspension. Removal kinetics of U(VI) on sepiolite and magnetic sepiolite can be well fitted by pseudo-second-order and pseudo-first-order kinetic models, respectively. At pH < 5.0, U(VI) removal on sepiolite significantly decreased with increasing ionic strength, whereas U(VI) removal on magnetic sepiolite was independent of ionic strength. The maximum removal capacity of sepiolite and magnetic sepiolite at pH 5.0 and 298 K calculated from Langmuir model were 28.17 and 74.63 mg/g, respectively. XANES spectra suggested that U(VI) was partly reduced to U(IV) at long-term conditions. [ABSTRACT FROM AUTHOR]

This paper presents the direct synthesis of highly nanoporous carbon materials via the carbonization of sodium oxalate in inert atmosphere without any activation. The carbonization temperature and time are very important for the carbon structures and their electrochemical performance in supercapacitors. The SOC-800-2.5 material derived from sodium oxalate has a high specific surface area of 1456 m g, and a total of 74 % of the pore volume is composed of mesoporosity with average pore size 3.7 nm, which is ideal for adoption as an electrode for supercapacitors. The SOC-800-2.5 material can also deliver a high specific capacitance of 245 F g at a constant charge/discharge current of 0.7 A g. This capacitance is maintained at a value of 173 F g at 10 A g. This material also has good cycle stability with over 89.1 % capacitance retention after 5000 cycles when measured in a three-electrode system using 6 M KOH as electrolyte. [ABSTRACT FROM AUTHOR]

A series of porous carbon/CoO (NZMC-18(6)-700-3/CoO) composite materials with different cobalt contents were synthesized at low reaction temperature using a facile chemical precipitation method. The morphology and crystal structure of the materials were evaluated on field emission scanning electron microscope and X-ray diffraction, respectively. The results show that composite materials possess incompact lamellar structure with some irregular agglomerated CoO particles adhering. The calcination temperature has a distinct influence on the morphology and electrochemical properties of porous carbon/CoO composites. The electrochemical performances were measured by constant current charge/discharge tests, cyclic voltammetry, and electrochemical impedance spectroscopy tests. It is illustrated that the composite materials have outstanding charge storage ability and the specific capacitance can reach up to 462 F g when the calcination temperature and cobalt content are 250 °C and 95 wt.%. With the increase of scan rate, the response current increases, and the anodic peaks and cathodic peaks shifted to higher potential and lower potential, respectively, which both illustrate that the material has excellent reversibility. The combination impedance of the electrode is only 0.674 Ω cm at a calcination temperature of 250 °C and is much less than those at other calcination temperatures which means that the electrode material has good conductivity. [ABSTRACT FROM AUTHOR]

Argentina songzhuensis, a new species of tribe Potentilleae (Rosaceae) from Southeast Tibet, is described and illustrated. Placement of this species within Argentina was assessed based on morphological comparisons with related species and on phylogenetic analyses of nuclear ITS and plastid trnL- F sequences. The new species is similar to A. glabriuscula, but can be easily distinguished by its densely hairy leaflets, number of stamens (ca.10-12) and decurrent bases of the uppermost pair of leaflets. Our results support the generic status of Argentina and suggest that ventral stipular auricles may be a good synapomorphy for the genus. The recent transfer to Argentina of several Sibbaldia species as well as the genera Piletophyllum and Tylosperma is also confirmed by our molecular phylogenetic analyses. A taxonomic key to A. songzhuensis and other Argentina species in Tibet is provided. [ABSTRACT FROM AUTHOR]

Lung cancer including non-small cell lung cancer (NSCLC) and small cell lung cancer is one of the most aggressive tumors with high incidence and low survival rate. The typical NSCLC patients account for 80-85 % of the total lung cancer patients. To systemically explore the molecular mechanisms of NSCLC, we performed a molecular network analysis between human and mouse to identify key genes (pathways) involved in the occurrence of NSCLC. We automatically extracted the human-to-mouse orthologous interactions using the GeneWays system by natural language processing and further constructed molecular (gene and its products) networks by mapping the human-to-mouse interactions to NSCLC-related mammalian phenotypes, followed by module analysis using ClusterONE of Cytoscape and pathway enrichment analysis using the database for annotation, visualization and integrated discovery (DAVID) successively. A total of 70 genes were proven to be related to the mammalian phenotypes of NSCLC, and seven genes ( ATAD5, BECN1, CDKN2A, FNTB, E2F1, KRAS and PTEN) were found to have a bearing on more than one mammalian phenotype (MP) each. Four network clusters centered by four genes thyroglobulin ( TG), neurofibromatosis type-1 ( NF1 ), neurofibromatosis type 2 ( NF2 ) and E2F transcription factor 1 ( E2F1) were generated. Genes in the four network modules were enriched in eight KEGG pathways ( p value < 0.05), including pathways in cancer, small cell lung cancer, cell cycle and p53 signaling pathway. Genes p53 and E2F1 may play important roles in NSCLC occurrence, and thus can be considered as therapeutic targets for NSCLC. [ABSTRACT FROM AUTHOR]

Xylanase gene xynB, cellulase genes egxA and bgl4 were subjected to codon optimisation using two opposing strategies. One was designated the 'one amino acid-one codon' approach, which employs only the codon most used by humans for each amino acid. The other one is referred to as the 'humanised' codon usage method, which selects synonymous codons for each amino acid according to the human codon usage table to mimic patterns used in humans. Protein expression levels in mammalian cell lines from each sequence were measured using fluorescence-activated cell sorting, western blotting and enzymatic activity assay. The results indicate that compared with the humanised codon usage method, the relatively simple 'one amino acid-one codon' approach could enhance heterologous protein expression in mammalian cells without apparent drawbacks. [ABSTRACT FROM AUTHOR]

Mesoporous carbons (NZMC) were synthesized by using single-step nanocasting in which maltose was used as carbon precursors and natural zeolite as template. Physical property characterization methods such as field emission scanning electron microscopy, transmission electron microscopy, N absorption/desorption, and X-ray diffraction were employed to determine the structure and crystallinity of NZMC. The results show that the materials possess a disordered lamellar structure and numerous nanopores. The specific surface area and pore volume reach up to 1076.9 m/g and 1.46 cm/g, respectively. Typical electrochemical measurements such as constant current charge/discharge test, cyclic voltammetry (CV), and electrochemical impedance spectra revealed that NZMC has excellent charge storage capability. Specific capacitance is 176 F/g in the alkaline media when the current density is 600 mA/g. The CV curve maintains a typical CV quasi-rectangular feature at a scan rate of 5-100 mV/s, which indicates that the materials perform well rate capability. The combination resistance of the carbon materials is 0.78 Ω. After 750 cycles, the specific capacitance retention value is 94.5 %, which proves that NZMC is a promising electrode material for electrochemical capacitors because of its long-term cycle stability. [ABSTRACT FROM AUTHOR]

This article introduces a new chaotic system of 4-D autonomous ordinary differential equations, which has no equilibrium. This system shows a hyper-chaotic attractor. There is no sink in this system as there is no equilibrium. The proposed system is investigated through numerical simulations and analyses including time phase portraits, Lyapunov exponents, and Poincaré maps. There is little difference between this chaotic system and other chaotic systems with one or several equilibria shown by phase portraits, Lyapunov exponents and time series methods, but the Poincaré maps show this system is a chaotic system with more complicated dynamics. Moreover, the circuit realization is also presented. [ABSTRACT FROM AUTHOR]

Many control researches for complicated and uncertain system are model-dependent and therefore require some prior knowledge for the complex systems. To avoid this problem, a number of model-free controllers are proposed. However, it is difficult to determine the control performance as the controller is not designed according certain system model especially when there are uncertainties and/or nonlinear dynamics in the system. To get over this problem, the model free controller (MFC) based on generalized internal model control (GIMC) structure is proposed in this paper. The MFC is used to attenuate the disturbance or uncertainty, and the system performance is determined by the nominal model and the nominal model controller. The parameters of nominal-model controller can be easily changed for meeting the change of the desired requirements. Moreover, the robust controller in the original GIMC is disassembled and rearranged to make the proposed methods easier to use, and the proposed method makes the controller be more flexible and greatly improves the system performance. Finally, the experiment results show that the MFC can be used to control the nonlinear systems and get the expected performance. The statistical analysis of performance for servo and regulatory behaviors also shows that the proposed method can achieve a better control performance than just using model free controller. [ABSTRACT FROM AUTHOR]

It is well known that no single histological feature is diagnostic for malignant pheochromocytomas (PCCs). So we developed a logistic model based on a series of clinical and pathological features to predict malignance in PCCs, and evaluated its diagnostic performance. In all 130 cases with malignant or benign PCCs, 15 predictive variables were observed and entered in the logistic regression analysis in a backward stepwise way. The diagnostic performance of this logistic model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve. In logistic analysis, of the 15 variables entered in the logistic regression analysis, 9 were retained in the model. High cellularity had the highest odds ratio (OR), followed by spindle cell (>10% of tumor volume), atypical mitotic figure, periadrenal adipose tissue invasion, mitotic figures [>3/10 high-power field (HPF)], cellular monotony, capsular invasion, vascular invasion, and central or confluent tumor necrosis. High cellularity, spindle cell (>10% of tumor volume) and atypical mitotic figure were selected to built a logistic model. This model had the area under the ROC curve of 0.927 (95% confidence interval 0.883–0.971). The application of the model can benefit the clinical management decision for patients with PCCs. We still emphasize, however, that a clinical prospective evaluation is needed to confirm its actual value. [ABSTRACT FROM AUTHOR]

Adenocarcinoma at the gastroesophageal junction (ACGEJ) has dismal clinical outcomes, and there are currently few specific effective therapies because of limited knowledge on its genomic and transcriptomic alterations. The present study investigates genomic and transcriptomic changes in ACGEJ from Chinese patients and analyzes their drug vulnerabilities and associations with the survival time. Here we show that the major genomic changes of Chinese ACGEJ patients are chromosome instability promoted tumorigenic focal copy-number variations and COSMIC Signature 17-featured single nucleotide variations. We provide a comprehensive profile of genetic changes that are potentially vulnerable to existing therapeutic agents and identify Signature 17-correlated IFN-α response pathway as a prognostic marker that might have practical value for clinical prognosis of ACGEJ. These findings further our understanding on the molecular biology of ACGEJ and may help develop more effective therapeutic strategies. Adenocarcinoma at the gastroesophageal junction has a dismal prognosis and few drug options. Here, the authors present genomic and transcriptomic features and potential therapeutic targets and prognostic biomarkers of Chinese and Caucasian tumours, and reveal the molecular similarities. [ABSTRACT FROM AUTHOR]

Computer networks intrusion detection systems (IDSs) and intrusion prevention systems (IPSs) are critical aspects that contribute to the success of an organization. Over the past years, IDSs and IPSs using different approaches have been developed and implemented to ensure that computer networks within enterprises are secure, reliable and available. In this paper, we focus on IDSs that are built using machine learning (ML) techniques. IDSs based on ML methods are effective and accurate in detecting networks attacks. However, the performance of these systems decreases for high dimensional data spaces. Therefore, it is crucial to implement an appropriate feature extraction method that can prune some of the features that do not possess a great impact in the classification process. Moreover, many of the ML based IDSs suffer from an increase in false positive rate and a low detection accuracy when the models are trained on highly imbalanced datasets. In this paper, we present an analysis the UNSW-NB15 intrusion detection dataset that will be used for training and testing our models. Moreover, we apply a filter-based feature reduction technique using the XGBoost algorithm. We then implement the following ML approaches using the reduced feature space: Support Vector Machine (SVM), k-Nearest-Neighbour (kNN), Logistic Regression (LR), Artificial Neural Network (ANN) and Decision Tree (DT). In our experiments, we considered both the binary and multiclass classification configurations. The results demonstrated that the XGBoost-based feature selection method allows for methods such as the DT to increase its test accuracy from 88.13 to 90.85% for the binary classification scheme. [ABSTRACT FROM AUTHOR]

A retraction of the article "Text mining and network analysis of molecular interaction in non-small cell lung cancer by using natural language processing" that was published in the 2014 issue is presented.