Miracle-dz/UniFAR-FTUs huggingface dataset:
Delivery of Nucleic Acids and Nanomaterials by Cell-Penetrating Peptides: Opportunities and Challenges

Many viral and nonviral systems have been developed to aid delivery of biologically active molecules into cells. Among these, cell-penetrating peptides (CPPs) have received increasing attention in the past two decades for biomedical applications. In this review, we focus on opportunities and challenges associated with CPP delivery of nucleic acids and nanomaterials. We first describe the nature of versatile CPPs and their interactions with various types of cargoes. We then discuss in vivo and in vitro delivery of nucleic acids and nanomaterials by CPPs. Studies on the mechanisms of cellular entry and limitations in the methods used are detailed.
Two-dimensional Hydrodynamic Models of Super Star Clusters with a Positive Star Formation Feedback

Using the hydrodynamic code ZEUS, we perform 2D simulations to determine the fate of the gas ejected by massive stars within super star clusters. It turns out that the outcome depends mainly on the mass and radius of the cluster. In the case of less massive clusters, a hot high-velocity (~1000 km s−1) stationary wind develops and the metals injected by supernovae are dispersed to large distances from the cluster. On the other hand, the density of the thermalized ejecta within massive and compact clusters is sufficiently large as to immediately provoke the onset of thermal instabilities. These deplete, particularly in the central densest regions, the pressure and the pressure gradient required to establish a stationary wind, and instead the thermally unstable parcels of gas are rapidly compressed, by a plethora of repressurizing shocks, into compact high-density condensations. Most of these are unable to leave the cluster volume and thus accumulate to eventually feed further generations of star formation. The simulations cover an important fraction of the parameter space, which allows us to estimate the fraction of the reinserted gas that accumulates within the cluster and the fraction that leaves the cluster as a function of the cluster mechanical luminosity, the cluster size, and heating efficiency.
A prospective evaluation of urine microscopy in septic and non-septic acute kidney injury.

BACKGROUND Sepsis is the most common trigger for acute kidney injury (AKI) in critically ill patients. We sought to determine whether there are unique patterns to urine sediment in septic compared with non-septic AKI. METHODS Prospective two center cohort study of adult critically ill patients with septic and non-septic AKI, defined by the RIFLE criteria. Eligible patients had clinical, physiologic and laboratory data extracted. Blood and urine were sampled for urine biochemistry, microscopy and neutrophil gelatinase-associated lipocalin (NGAL). A urine microscopy score (UMS) was derived based on the observed quantification of renal tubular cells and casts in the sediment. The UMS was compared between septic and non-septic AKI and correlated with NGAL, worsening AKI, renal replacement therapy (RRT) and hospital mortality. RESULTS Eighty-three patients were enrolled. Mean (SD) age was 64.3 (16.6) years, 60.2% were male, Charlson comorbidity score was 3.3 (2.8) and Acute Physiology and Chronic Health Evaluation II score was 21.4 (7.6). Septic AKI was present in 43 patients (51.8%). RIFLE class at enrollment was not different between groups (P = 0.43). Septic AKI was associated with higher UMS compared with non-septic AKI (P = 0.001). There was no correlation between UMS and fractional excretion of sodium (FeNa) or fractional excretion of urea (FeU). Elevated urine NGAL (uNGAL) correlated with higher UMS (P = 0.0003), while correlation with plasma NGAL was modest (P = 0.05). Worsening AKI occurred in 22.9% with no difference between septic and non-septic groups. A UMS score ≥ 3 was associated with increased odds of worsening AKI [adjusted odds ratio 8.0; 95% confidence intervals (CI), 1.03-62.5, P = 0.046]. For a UMS ≥3, sensitivity and specificity were 0.67 (95% CI, 0.39-0.86) and 0.95 (0.84-0.99) and positive and negative predictive values we re 0.80 (0.49-0.94) and 0.91 (0.78-0.96) for detecting worsening AKI, respectively. While there were no differences between septic and non-septic AKI, higher UMS correlated with need for RRT (15.7%, P = 0.02) and in-hospital death (30.1%, P = 0.01); however, this did not persist in multivariable analysis. CONCLUSIONS Septic AKI is associated with greater urine microscopy evidence of kidney injury compared with non-septic AKI, despite similar severity of AKI. A UMS ≥ 3 correlated with higher uNGAL and was predictive of worsening AKI. Urine microscopy may have a complementary role for discerning septic from non-septic AKI, discriminating severity and predicting worsening AKI in critically ill patients.
Solution analysis for SIP security threats

Session Initial Protocol (SIP) is widely used for handling multimedia signaling. Because SIP is widely used in many multimedia applications, it becomes an attractive target to attackers. Actually, in contrast to traditional telephone networks, SIP works at the application layer in IP networks. It is thus faced to not only the IP-networks security issues, but also to new issues which are related to the SIP protocol directly. In this paper, we present the most relevant SIP-related security vulnerabilities and threats; then, we discuss the different security mechanisms that can be deployed to overcome the SIP security issues while putting emphasis the most important ones. Afterwards, taking into account the targeted security property, we propose adaptable solutions to the SIP threats already identified and we present our implementation and simulation test bed to experiment two versions of the SIP Asterisk software. Finally, we draw out conclusions and we introduce some perspectives to improve the security of multimedia applications.
An Approach to Overcome Inference Channels on k-anonymous Data

The concept of k-anonymity protection model has been proposed as an effective way to protect the identities of subjects in a disclosed database. However, from a k-anonymous dataset it may be possible to directly infer private data. This direct disclosure is called attribute linkage. k-anonymity also suffer to another form of attack based on data mining results. In fact, data mining models and patterns pose a privacy threat even if the k-anonymity is satisfied. In this paper, we discuss how the privacy requirements characterized by kanonymity can be violated by data mining results and introduce an approach to limit privacy breaches. We experiment it by using the adult dataset from the UCI KDD archive. We report the experimental results which show its effectiveness.
Customer Value of LINE Mobile Services: The Study of Adolescents inThree East Asian Cities

Although previous studies on customer satisfaction and loyalty are quite extensive, few have focused on customer value in LINE mobile services (LMSs) and its effect on customers, and the belief transmission mechanism of customer value has been ignored or underestimated. This study used grounded theory to summarize the evidentiary bases and concepts for establishing a conceptual model for an underlying LMSs belief transmission mechanism on the basis of customer value. The results obtained offer three potential contributions: value-driven, situational dynamics, and beliefs transmission. The analysis demonstrated two plausible pathways in beliefs transmission: beliefs adaptation and augmentation, and beliefs adaptation manifested in satisfaction and social exchange. Beliefs augmentation manifested in word-of-mouth, interpersonal network, and demonstrative effects. The pathways associated with customer value modes were uncovered in this study. The findings concerning beliefs transmission mechanism expands literature on the origins of customer value.
Frequency agile filter structure improved by MOS-only technique

In this paper, a new frequency agile filter structure for analog signal processing is proposed by using of MOS only technique. In contrast to the conventional analog building blocks, the filter is designed with only MOS transistors. The parasitic capacitances of the MOS transistor are used instead of the classical capacitors. The operating frequency range is improved and the power consumption is decreased. The simulations have been performed in Cadence environment using 0. 18μm TSMC parameters.
Analysis of a Global Contiguity Constraint

We address a global constraint for enforcing contiguity. Contiguity is the property that all of one kind of object in an array or list are grouped together; it is a one-dimensional discrete form of convexity. We present an implementation of this property in a concurrent constraint programming language. We adapt and apply the constraint propagation framework of [19] to analyse the contiguity property. In particular, the soundness of the implementation is proved and the forms of local consistency that are maintained by the implementation are identified. A complexity analysis shows that the implementation is optimal for achieving arc-consistency. However, an optimal implementation is not given for a stronger consistency condition, and we raise the possibility that an optimal implementation requires meta-level programming.
Soft mask estimation for single channel speaker separation

1. Abstract The problem of single channel speaker separation, attempts to extract a speech signal uttered by the speaker of interest from a signal containing a mixture of auditory signals. Most algorithms that deal with this problem, are based on masking, where reliable components from the mixed signal spectrogram are inversed to obtain the speech signal from speaker of interest. As of now, most techniques, estimate this mask in a binary fashion, resulting in a hard mask. We present a technique to estimate a soft mask that weights the frequency sub-bands of the mixed signal. The speech signal can then be reconstructed from the estimated power spectrum of the speaker of interest. Experimental results shown in this paper, prove that the results are better than those obtained by estimating the hard mask.
Intelligent Intrusion Detection System Using a Committee of Experts

Intrusion detection plays an important role in today's computer and communication technology. It is of a paramount importance to design a time efficient and accurate Intrusion Detection System (IDS). In this paper, an Intelligent Intrusion Detection System (IIDS) is developed using the combination of several neural experts forming a Committee of Experts, used to detect and prevent various anomalies. The input to the system is given by the feature extraction of various historic data present in the central database and making a suitable training data classifier. Furthermore, each expert within the committee is assigned a different granularity of data, because the training set is based on its fundamental properties. The experts are designed in such a way that they make accurate predictions using the data. The system takes the necessary steps in identification of the anomaly and was found to have a high attack success detection rate.
Imitation of Facial Expressions for a Virtual Robotic Head

Facial expression has an important role for natural interaction among social robots and humans. In this paper, an architecture conceived for imitation of facial expressions is proposed. We describe the computer vision algorithm that was implemented for real-time geometric facial features extraction. It covers face detection, extraction of eyes, eyebrows, nostrils and mouth characteristic points, as well as an estimation of the face tilt angle. Fast processing has been prioritized over precision. Although we cannot make a definitive statement before all of the modules are built, the experiments show promising results on different subjects and illumination circumstances.
Towards a Conceptual Model of Consumer Confusion

As consumers are provided with ever-increasing amounts of information from more products sold through more channels and promoted in more ways, the notion of marketplace confusion is becoming Increasingly important. From the extant literature, we propose and define three types of confusion resulting from brand similarity, information load, and misleading or ambiguous information. This latter type can be regarded as an 'altered knowledge state' in which a revision of understanding occurs. We argue that confusion should be conceptualized as a state variable and that existing confusion measures have focused solely on the behavioral and cognitive outcomes of confusion, ignoring the role of affect which is also a part of confusion. The paper is the first to discuss the consequences of confusion and elaborate on consumer confusion-reducing strategies. It concludes with some research implications of the new conceptualization. [ABSTRACT FROM AUTHOR]
Age at Mycobacterium bovis BCG Priming Has Limited Impact on Anti-Tuberculosis Immunity Boosted by Respiratory Mucosal AdHu5Ag85A Immunization in a Murine Model

Tuberculosis (TB) remains a global pandemic despite the use of Bacillus Calmette-Guérin (BCG) vaccine, partly because BCG fails to effectively control adult pulmonary TB. The introduction of novel boost vaccines such as the human Adenovirus 5-vectored AdHu5Ag85A could improve and prolong the protective immunity of BCG immunization. Age at which BCG immunization is implemented varies greatly worldwide, and research is ongoing to discover the optimal stage during childhood to administer the vaccine, as well as when to boost the immune response with potential novel vaccines. Using a murine model of subcutaneous BCG immunization followed by intranasal AdHu5Ag85A boosting, we investigated the impact of age at BCG immunization on protective efficacy of BCG prime and AdHu5Ag85A boost immunization-mediated protection. Our results showed that age at parenteral BCG priming has limited impact on the efficacy of BCG prime-AdHu5Ag85A respiratory mucosal boost immunization-enhanced protection. However, when BCG immunization was delayed until the maturity of the immune system, longer sustained memory T cells were generated and resulted in enhanced boosting effect on T cells of AdHu5Ag85A respiratory mucosal immunization. Our findings hold implications for the design of new TB immunization protocols for humans.
Genome disorder and breast cancer susceptibility

Many common diseases have a complex genetic basis in which large numbers of genetic variations combine with environmental and lifestyle factors to determine risk. However, quantifying such polygenic effects and their relationship to disease risk has been challenging. In order to address these difficulties we developed a global measure of the information content of an individual's genome relative to a reference population, which may be used to assess differences in global genome structure between cases and appropriate controls. Informally this measure, which we call relative genome information (RGI), quantifies the relative "disorder" of an individual's genome. In order to test its ability to predict disease risk we used RGI to compare single nucleotide polymorphism genotypes from two independent samples of women with early-onset breast cancer with three independent sets of controls. We found that RGI was significantly elevated in both sets of breast cancer cases in comparison with all three sets of controls, with disease risk rising sharply with RGI (odds ratio greater than 12 for the highest percentile RGI). Furthermore, we found that these differences are not due to associations with common variants at a small number of disease-associated loci, but rather are due to the combined associations of thousands of markers distributed throughout the genome. Our results indicate that the information content of an individual's genome may be used to measure the risk of a complex disease, and suggest that early-onset breast cancer has a strongly polygenic basis.
Learnability of Specific Structural Patterns of Planning Problems

In Automated planning, learning and exploiting additional knowledge within a domain model, in order to improve the performance of domain-independent planners, has attracted much research. Reformulation techniques such as those based on macro-operators or entanglements are very promising because they are, to some extent, domain model and planning engine independent. Despite the significant amount of work that has been done for designing techniques aimed at extracting this additional knowledge in this form, no methodological analysis has been performed for a better comprehension of their learning process. In this paper, we focus on studying learnability of entanglements in planning, in terms of how the learning process can be influenced by the quantity and the quality of the training data. So, we aim to investigate whether a small number of training planning problems is sufficient for learning a good quality set of (compatible) entanglements. Quality of the training data refers to situations where (suboptimal) plans often consist of 'flaws' (e.g. unnecessary actions). Therefore, we will investigate how the current entanglement learning approach handles such 'flaws' in training plans. Also, we will investigate whether training plans generated by different planners lead to different results of the learning process.
Ultrasonic Robot Eye for Shape Recognition Employing a Genetic Algorithm

This paper describes an ultrasonic robot eye for shape recognition using ultrasound pressure data and a Genetic Algorithm. This type of robot eye has commonly used a Neural Network (NN) for shape recognition. However, a NN perform poorly when lacking learned data. In order to overcome this problem when using a NN, we here attempt to replace the NN with a Genetic Algorithm (GA). Unlike a NN, the GA can recognize shapes without depending on learned data. Experimental results demonstrate that the recognition ratios of the proposed ultrasonic robot eye using the GA are higher than that of a conventional ultrasonic robot eye using a NN. Therefore, it is shown that our robot eye is effective for many robotic applications.
Assessment of spatial attention after brain damage with a dynamic reaction time test

Lateralized spatial biases after brain damage are commonly assessed using batteries of paper-and-pencil tests. These tests hardly allow quantification of performance in different locations in space, and they tend to lose sensitivity along the course of recovery. We tested the dynamic Starry Night Test (SNT), a novel computerized test measuring reaction time and detection accuracy for visual target stimuli in a dynamic background, in 32 inpatients with right hemisphere stroke (RHS), 16 patients with left hemisphere stroke (LHS), and 9 healthy controls. As a group, only the RHS patients were significantly slower to respond to contralesional targets. Individually, 21 (66%) RHS patients and 5 (31%) LHS patients showed statistically significant contralateral deficits. In a number of RHS patients the SNT was more sensitive to the ipsilesional bias of spatial attention than the Behavioral Inattention Test (BIT), a standardized paper-and-pencil test battery of unilateral spatial neglect. Two illustrative case reports show that the dynamic SNT, but not the BIT, was sensitive to the spatial deficit in recovered patients, one of whom was involved in repeated car accidents. The SNT overcomes serious shortcomings of paper-and-pencil tests of unilateral neglect. It provides a simple quantitative tool for monitoring the natural and treatment-induced recovery of patients. (JINS, 2005, 11, 697–707.)Part of the data was presented in abstract form at the EBBS EuroConference on Cognitive and Neural Bases of Spatial Neglect, September 14–17, 2000, Como, Italy.
Factors Enabling Information and Communication Technology Diffusion and Actual Implementation in Construction Organisations

SUMMARY: Emerging information and communication technology (ICT) introduces opportunities for improving communication to enhance effectiveness of many construction processes at each project phase as well as creating new business opportunities. Thus, perceived ICT benefits have motivated numerous construction organisations to adopt and invest in this technology. However, many construction organisations have found that the ICT investment has failed to meet their expectations. One significant problem is a lack of understanding of how to actually implement ICT into a construction organisation. This may lead to ICT implementation failure or retardation by all users within a construction organisation. In addition, a lack of focus on actual ICT implementation may explain why ICT implementation problems still occur. Before substantial progress can be made to remedy deficiencies in ICT implementation, a better understanding is needed about the context and influence of a range of workplace, organisational and personal factors on ICT implementation. The general focus of this paper is directed upon ICT implementation in construction organisations, with a specific focus using results from a study of a small but indicative sample of Australian ICT literate construction organisations. An improved understanding of ICT implementation can be achieved through a general survey of the literature and then testing theory developed from the literature using a representative pool of general construction organisation. Alternatively, a narrow focus could be directed at organisations that are already well experienced in the use of ICT. The authors concentrated upon Australian construction organisations with over a decade of experience in ICT implementation so that salient lessons learned could be more readily available for dissemination more widely. This paper attempts to fill ICT implementation gaps by focusing on ICT diffusion at the actual implementation stage. Its primary objective is to understand the nature of ICT diffusion within a construction organisation. It focuses on a review of the theory relating to ICT implementation. A list of 46 essential variables was developed from integration of three main theories: innovation diffusion, change management, and knowledge management. The paper also provides a brief summary of the variables tested through using factor analysis. Results indicate that these 46 variables formed 11 factors that can be grouped into management, individual characteristics, technology and workplace environment clusters. The contribution that this paper makes is to rigorously identify and discuss the nature and extent of intraorganisational factors influencing ICT diffusion within large ICT-experienced construction organisations. This will be useful for those interested in this area and provides a current literature review.
IgE-based immunotherapy of cancer: challenges and chances

Passive immunotherapy with monoclonal antibodies is an indispensable cornerstone of clinical oncology. Notably, all FDA‐approved antibodies comprise the IgG class, although numerous research articles proposed monoclonal antibodies of the IgM, IgG, IgA and IgE classes directed specifically against tumor‐associated antigens. In particular, for the IgE isotype class, several recent studies could demonstrate high tumoricidic efficacy. Therefore, this review specifically highlights the latest developments toward IgE‐based immunotherapy of cancer. Possible mechanisms and safety aspects of IgE‐mediated tumor cell death are discussed with special focus on the attracted immune cells. An outlook is given on how especially comparative oncology could contribute to further developments. Humans and dogs have a highly comparable IgE biology, suggesting that translational AllergoOncology studies in patients with canine cancer could have predictive value for the potential of IgE‐based anticancer immunotherapy in human clinical oncology.