Miracle-dz/UniFAR-FTUs huggingface dataset:
The predictive value of KRAS, NRAS, BRAF, PIK3CA and PTEN for anti-EGFR treatment in metastatic colorectal cancer: A systematic review and meta-analysis

Abstract Background. In metastatic colorectal cancer, mutation testing for KRAS exon 2 is widely implemented to select patients with wild-type tumors for treatment with the monocloncal anti-EGFR antibodies cetuximab and panitumumab. The added predictive value of additional biomarkers in the RAS-RAF-MAPK and PI3K-AKT-mTOR pathways in colorectal cancer is uncertain, which led us to systematically review the impact of alterations in KRAS (outside of exon 2), NRAS, BRAF, PIK3CA and PTEN in relation to the clinical benefit from anti-EGFR treatment. Methods. In total, 22 studies that include 2395 patients formed the basis for a meta-analysis on alterations in KRAS exons 3 and 4, NRAS, BRAF, and PIK3CA and PTEN and outcome of anti-EGFR treatment. Odds ratios for objective response rate (ORR) and hazard ratios (HR) for progression-free survival (PFS) and overall survival (OS) were calculated. Results. Mutations in KRAS exons 3 and 4, BRAF, PIK3CA and non-functional PTEN (mutations or loss of protein expression) significantly predicted poor ORR (OR = 0.26, OR = 0.29, OR = 0.39, and OR = 0.41, respectively). Significantly shorter PFS applied to mutations in KRAS exons 3 and 4 (HR = 2.19), NRAS (HR = 2.30) and BRAF (HR = 2.95) and non-functional PTEN (HR = 1.88). Significantly shorter OS applied to mutations in KRAS exons 3 and 4 (HR = 1.78), NRAS (HR = 1.85), BRAF (HR = 2.52), PIK3CA (HR = 1.43) and alterations in PTEN (HR = 2.09). Conclusions. Meta-analysis suggests that mutations in KRAS exons 3 and 4, NRAS, BRAF and PIK3CA and non-functional PTEN predict resistance to anti-EGFR therapies and demonstrates that biomarker analysis beyond KRAS exon 2 should be implemented for prediction of clinical benefit from anti-EGFR antibodies in metastatic colorectal cancer.
CIMDS: Adapting Postprocessing Techniques of Associative Classification for Malware Detection

Malware is software designed to infiltrate or damage a computer system without the owner's informed consent (e.g., viruses, backdoors, spyware, trojans, and worms). Nowadays, numerous attacks made by the malware pose a major security threat to computer users. Unfortunately, along with the development of the malware writing techniques, the number of file samples that need to be analyzed, named "gray list," on a daily basis is constantly increasing. In order to help our virus analysts, quickly and efficiently pick out the malicious executables from the "gray list," an automatic and robust tool to analyze and classify the file samples is needed. In our previous work, we have developed an intelligent malware detection system (IMDS) by adopting associative classification method based on the analysis of application programming interface (API) execution calls. Despite its good performance in malware detection, IMDS still faces the following two challenges: (1) handling the large set of the generated rules to build the classifier; and (2) finding effective rules for classifying new file samples. In this paper, we first systematically evaluate the effects of the postprocessing techniques (e.g., rule pruning, rule ranking, and rule selection) of associative classification in malware detection, and then, propose an effective way, i.e., CIDCPF, to detect the malware from the "gray list. " To the best of our knowledge, this is the first effort on using postprocessing techniques of associative classification in malware detection. CIDCPF adapts the postprocessing techniques as follows: first applying Chi-square testing and Insignificant rule pruning followed by using Database coverage based on the Chi-square measure rule ranking mechanism and Pessimistic error estimation, and finally performing prediction by selecting the best First rule. We have incorporated the CIDCPF method into our existing IMDS system, and we call the new system as CIMDS system. Case studies are performed on the large collection of file samples obtained from the Antivirus Laboratory at Kingsoft Corporation and promising experimental results demonstrate that the efficiency and ability of detecting malware from the "gray list" of our CIMDS system outperform popular antivirus software tools, such as McAfee VirusScan and Norton Antivirus, as well as previous data-mining-based detection systems, which employed Naive Bayes, support vector machine, and decision tree techniques. In particular, our CIMDS system can greatly reduce the number of generated rules, which makes it easy for our virus analysts to identify the useful ones.
HIV-1 Nef Selectively Activates Src Family Kinases Hck, Lyn, and c-Src through Direct SH3 Domain Interaction*

Nef is an HIV-1 virulence factor that promotes viral pathogenicity by altering host cell signaling pathways. Nef binds several members of the Src kinase family, and these interactions have been implicated in the pathogenesis of HIV/AIDS. However, the direct effect of Nef interaction on Src family kinase (SFK) regulation and activity has not been systematically addressed. We explored this issue using Saccharomyces cerevisiae, a well defined model system for the study of SFK regulation. Previous studies have shown that ectopic expression of c-Src arrests yeast cell growth in a kinase-dependent manner. We expressed Fgr, Fyn, Hck, Lck, Lyn, and Yes as well as c-Src in yeast and found that each kinase was active and induced growth suppression. Co-expression of the negative regulatory kinase Csk suppressed SFK activity and reversed the growth-inhibitory effect. We then co-expressed each SFK with HIV-1 Nef in the presence of Csk. Nef strongly activated Hck, Lyn, and c-Src but did not detectably affect Fgr, Fyn, Lck, or Yes. Mutagenesis of the Nef PXXP motif essential for SH3 domain binding greatly reduced the effect of Nef on Hck, Lyn, and c-Src, suggesting that Nef activates these Src family members through allosteric displacement of intramolecular SH3-linker interactions. These data show that Nef selectively activates Hck, Lyn, and c-Src among SFKs, identifying these kinases as proximal effectors of Nef signaling and potential targets for anti-HIV drug discovery.
Study of Optical Emission Spectroscopy in a GaN ECR-PECVD

The paper presents excited gallium (Ga*) emission at 403.2nm and 417.2nm by optical emission spectroscopy (OES) during GaN growth in electron-cyclotron-resonance plasma enhance chemical vapor deposition (ECR-PECVD). At the same time, we investigated the spectroscopy of simple nitrogen plasma without TMG source as a function of microwave power. In this paper, we tentatively conclude that N* plays an important role in the GaN deposition by ECR-PECVD. Fourier Transform Infrared Transmission (FTIR) was employed to analyze the composition of GaN layer. The results show that the FTIR reflectivity spectra exhibit the GaN A1 (LO) and E1 (TO) phonon modes at 559 cm-1 and 737cm-1, respectively.
Lymphocyte function during hepatic ischemia/reperfusion injury

The liver is the primary organ affected by ischemia/reperfusion (I/R) injury after shock, surgical resection, or transplantation. The actions of myeloid leukocytes have been well studied and are thought to be the primary cells responsible for propagating the injury response. However, there is an emerging view that T lymphocytes can also regulate liver I/R‐induced inflammation. Resident lymphocytes found within the liver include conventional αβ TCR cells as well as unconventional NK and γδ T cells. These lymphocytes can alter inflammation through the secretion of soluble mediators such as cytokines and chemokines or through cognate interactions in an antigen‐dependent manner. Expression of these mediators will then result in the recruitment of more lymphocytes and neutrophils. There is evidence to suggest that T cell activation in the liver during I/R can be driven by antigenic or nonantigenic mechanisms. Finally, immune cells are exposed to different oxygen tensions, including hypoxia, as they migrate and function within tisues. The hypoxic environment during liver ischemia likely modulates T cell function, at least in part through the actions of hypoxia‐inducible factor‐1α. Further, this hypoxic environment leads to the increased concentration of extracellular adenosine, which is generally known to suppress T cell proinflammatory function. Altogether, the elucidation of T lymphocyte actions during liver I/R will likely allow for novel targets for therapeutic intervention.
Unexplained spectral peaks in Earth tremor

S U M M A R Y Independent multi-year analyses of Earth tremor have suggested a continuous excitation of Earth normal modes by ocean storms, but also a number of unexplained spectral peaks extraneous to them, mostly in the 0.2–2 mHz frequency band. We reassess the worldwide existence of such peaks by stacking the multitaper high-resolution spectra of all stations of the International Geodynamics and Earth Tide Service superconducting gravimeter network with at least 30 months of uninterrupted record, analysing a global epoch of 656 months. The analysis, beyond showing the predominance of 0Sn, n = 0, . , 12 Earth spheroidal modes, confirms the existence of unexplained spectral peaks which (1) cannot be ascribed to instrumental noise, (2) occur at frequencies extraneous to Earth normal modes, (3) have a statistical significance comparable to them and (4) appear incompatible with any natural or anthropic terrestrial source. While at odds with the hypothetical Earth ‘tune in’ on a continuum detectable gravitational wavefield, the peaks appear to be compatible in terms of amplitude, frequency and—according to cosmological constraints—expected number, with the independently calculated gravitational wave monochromatic emission of a few binary systems consisting of a star with mass ∼1/10 of the sun captured in close orbit by the supermassive black hole at the centre of our galaxy.
Farmers' perceptions and adaptation behaviours concerning land degradation: A theoretical framework and a case‐study in the Qinghai–Tibetan Plateau of China

Land degradation through environmental pollution represents a serious threat to vulnerable populations in rural China. To better understand farmers' perceptions of land degradation and their corresponding adaptation behaviour, this paper presents a theoretical framework to explain the interactions among awareness, perception, mitigation, and adaptation, and tests the framework using a case‐study. A case‐study was conducted in Qinghai, where historical environmental pollution from a chemical plant had caused the contamination of soil, groundwater, and river water, which had negatively impacted the livelihood of local farmers. A questionnaire survey was conducted (n = 277), and the results were used to test the theoretical framework using structural equation modelling. Results indicated strong structural relationships between awareness and perceptions (r = .75, p < .01), a relatively strong relationship between mitigation and adaptation (r = .63, p = .02), and a weak relationship between perception and mitigation (r = .20, p = .54). The study results suggested that farmers were well aware of land degradation issues, but they lacked in‐depth knowledge about the situation and about sophisticated adaptation methods; therefore, they had chosen the easiest adaptation strategy‐ to avoid the degraded land. The farmers were less willing to bear significant financial costs in adaptation; however, the proportion of respondents adopting ‘moving’ as an adaptation strategy was relatively high, suggesting that farmland degradation in combination with employment opportunities in urban areas may be causing environmental displacement and accelerating urbanization. The authors of this paper recommend that policymakers should consider more than just technical factors in addressing China's environmental pollution and land degradation problems. The socio‐economic status of farmers should be a critical component in the equation, and bottom‐up empowerment adaptation behaviour should be used in combination with top‐down mitigation.
BNP but Not s-cTnln Is Associated with Cardioembolic Aetiology and Predicts Short and Long Term Prognosis after Cerebrovascular Events

Background We analyzed the prognostic value of b-type natriuretic peptide (BNP) and sensitive cardiac Troponin (s-cTnI) in patients with ischemic stroke or transient ischemic attack (TIA) and their significance in predicting stroke aetiology. Methods In a prospectively enrolled cohort we measured BNP and s-cTnI levels upon admission. Primary endpoints were mortality, unfavorable functional outcome and stroke recurrence after 90 days and after 12 months. Secondary endpoint was cardioembolic aetiology. Results In 441 patients BNP but not s-cTnI remained an independent predictor for death with an adjusted HR of 1.2 (95% CI 1.1–1.4) after 90 days and 1.2 (95% CI 1.0–1.3) after one year. The comparison of the Area under Receiver Operating Characteristic (AUROC) of model A (age, NIHSS) and model B (age, NIHSS, BNP) showed an improvement in the prediction of mortality (0.85 (95% CI 0.79–0.90) vs. 0.86 (95% CI 0.81–0.92), Log Rank p = 0.004). Furthermore the category free net reclassification improvement (cfNRI) when adding BNP to the multivariate model was 57.5%, p<0.0001. For the prediction of functional outcome or stroke recurrence both markers provided no incremental value. Adding BNP to a model including age, atrial fibrillation and heart failure lead to a higher discriminatory accuracy for identification of cardioembolic stroke than the model without BNP (AUC 0.75 (95% CI 0.70–0.80) vs. AUC 0.79, (95% CI 0.75–0.84), p = 0.008). Conclusion BNP is an independent prognostic maker for overall mortality in patients with ischemic stroke or TIA and may improve the diagnostic accuracy to identify cardioembolic aetiology. Trial Registration ClinicalTrials.gov NCT00390962
OBJECT-ORIENTED IMAGE ANALYSIS AND SEMANTIC NETWORK FOR EXTRACTING THE ROADS AND BUILDINGS FROM IKONOS PAN-SHARPENED IMAGES

Traditional pixel-based approaches are based exclusively on the grey value of pixel itself. Thereby only the spectral information is used for the classification. The situation becomes worse when extracting the certain features only. An object-oriented image analysis is implemented in order to overcome the limitation mentioned above. The existing software, eCognition v3.0 allows the polygon based classification process. It is based on fuzzy logic, allows the integration of a broad spectrum of different object features, such as spectral values, shape and texture. This study demonstrated the extraction of buildings and roads from the high-resolution Ikonos pan-sharpened image data by first dividing it into the segments and then classifying it using the spectral, spatial and contextual information. The test site was agro-industrial area in the city of Zonguldak which has rolling topography along the Black Sea coast. Land use classification results as well as the spatial information can be exported to GIS environment for evaluation purposes with existing larger scale cadastral maps and other available ground truth materials. * Corresponding author.
Document Ranking and the Vector-Space Model

Efficient and effective text retrieval techniques are critical in managing the increasing amount of textual information available in electronic form. Yet text retrieval is a daunting task because it is difficult to extract the semantics of natural language texts. Many problems must be resolved before natural language processing techniques can be effectively applied to a large collection of texts. Most existing text retrieval techniques rely on indexing keywords. Unfortunately, keywords or index terms alone cannot adequately capture the document contents, resulting in poor retrieval performance. Yet keyword indexing is widely used in commercial systems because it is still the most viable way by far to process large amounts of text. Using several simplifications of the vector-space model for text retrieval queries, the authors seek the optimal balance between processing efficiency and retrieval effectiveness as expressed in relevant document rankings.
On the Secure Spectral-Energy Efficiency Tradeoff in Random Cognitive Radio Networks

Spectrum efficiency (SE) and energy efficiency (EE) in secure communications have attracted much attention recently due to the fact that future wireless networks need to address the issues of high throughput, low power consumption, and high level of security. However, maximizing EE and SE are conflicting objectives, which can hardly be achieved simultaneously. In this paper, we develop a framework to study the SE and EE for secure transmission in underlay random cognitive radio (CR) networks where the primary, secondary, and eavesdropper nodes are randomly distributed according to Poisson point processes. We first analyze the connection outage probability and the secrecy outage probability of the typical links in the random CR network. Then, we evaluate the secure SE and EE in the secondary network based on the outage probability analysis. It is demonstrated that the scheduling scheme of the secondary network (i.e., the transmission power and the intensity of secondary transmitters arouses a tradeoff between the secure SE and EE. Furthermore, applying a unified secure SE-EE tradeoff metric, which condenses the secure SE and EE into a single utility function with a tradeoff factor, we formulate the joint secure SE and EE optimization problem with respect to the scheduling scheme of the secondary network. An iterative algorithm is proposed based on the separation optimization of the transmission power and the intensity. The analytical and simulation results show the effects of system parameters on the optimal solutions and secure SE-EE tradeoff. We also verify that the optimal scheduling scheme can improve the secure SE-EE tradeoff. Using these results, one can easily understand and make the secure SE-EE tradeoff in random CR networks.
New MAP estimators for speaker recognition

We report the results of some experiments which demonstrate that eigenvoice MAP and eigenphone MAP are at least as effective as classical MAP for discriminative speaker modeling on SWITCHBOARD data. We show how eigenvoice MAP can be modified to yield a new model-based channel compensation technique which we call eigenchannel MAP. When compared with multi-channel training, eigenchannel MAP was found to reduce speaker identification errors by 50%.
Influences of external store on aerodynamic performance of UTM-LST generic light aircraft model

This paper discusses the impact of the external store on the aerodynamic performance of the light aircraft model in the subsonic region. Light aircrafts are normally used to train pilots, survey, leisure and transportation. To date, there have been a lot of small aircrafts were used for a strategic purposes where an external store either external fuel storage or armament has been installed on its wing. Examples of such aircraft are KAI-KA1, A29 Super Tucano and Beechcraft AT-6. Therefore it is important to study the effect of this external store installation on the aerodynamic characteristics of a small aircraft. An available light aircraft model of UTM Low speed wind tunnel (UTM-LST) has been modified so that a generic external store can be mounted on the lower surface of the wing. Two set of experiments were carried out on the model which were; the experimental with the external store and followed by the experimental without external store as a benchmark of tested configuration. The experiments were conducted at 2 different speeds of 26 and 39 m / s that corresponding to 0.4 × 106 and 0.6 × 106 Reynolds numbers respectively. Three measurement techniques were employed on each configuration. The first measurement was the 6 component forces and moments measurement technique. The second technique was the pressure measurement on the wing while the final test was the tufts flow visualization. The result of steady balance indicates that external store has no effect on coefficient of lift at low attack angle but it shows that there was a reduction of lift coefficient by 2% at higher angle of attack. The data showed that the coefficient of drag increases by 4% when the external is installed. Suprisingly, the installation of store does not give significance effects on the pitching moment coefficient. An interesting feature is observed from surface pressure studies, the results obtained show that there is an increase in the pressure coefficient if the external is mounted on the wing at a low angle of attack, while this change does not occur at high attack angle.
Inhibitory effect of essential oils against Lactobacillus rhamnosus and starter culture in fermented milk during its shelf-life period

The use of essential oils in foods has attracted great interest, due to their antagonistic action against pathogenic microorganisms. However, this action is undesirable for probiotic foods, as products containing Lactobacillus rhamnosus. The aim of the present study was to measure the sensitivity profile of L. rhamnosus and a yogurt starter culture in fermented milk, upon addition of increasing concentrations of cinnamon, clove and mint essential oils. Essential oils were prepared by steam distillation, and chemically characterised by gas chromatography-mass spectrometry (GC-MS) and determination of density. Survival curves were obtained from counts of L. rhamnosus and the starter culture (alone and in combination), upon addition of 0.04% essential oils. In parallel, titratable acidity was monitored over 28 experimental days. Minimum inhibitory concentration values, obtained using the microdilution method in Brain Heart Infusion medium, were 0.025, 0.2 and 0.4% for cinnamon, clove and mint essential oils, respectively. Cinnamon essential oil had the highest antimicrobial activity, especially against the starter culture, interfering with lactic acid production. Although viable cell counts of L. rhamnosus were lower following treatment with all 3 essential oils, relative to controls, these results were not statistically significant; in addition, cell counts remained greater than the minimum count of 108CFU/mL required for a product to be considered a probiotic. Thus, although use of cinnamon essential oil in yogurt makes starter culture fermentation unfeasible, it does not prevent the application of L. rhamnosus to probiotic fermented milk. Furthermore, clove and mint essential oil caused sublethal stress to L. rhamnosus.
On HR calculus, quaternion valued stochastic gradient, and adaptive three dimensional wind forecasting

Short term forecasting of wind field in the quaternion domain is addressed. This is achieved by casting the three components of wind speed (two horizontal and a vertical) into a pure quaternion and adding air temperature as a scalar component, to form the full quaternion. First, HR calculus is introduced in order to provide a unifying framework for the calculation of the derivatives of both analytic quaternion valued functions and real functions of quaternion variables, such as the standard cost function (error power). The analysis shows that the maximum change in the gradient is in the direction of the conjugate of the weight vector, conforming with the gradient calculation in the complex domain. For rigour, we also illustrate that the widely linear model is required in order to capture full second order information within three- and four-dimensional quaternion valued signals. The so established framework is used to illustrate a convenient way to derive the recently introduced quaternion least mean square (QLMS) and the widely linear QLMS (WL-QLMS). Simulations on short term prediction of real world wind signals support the approach.