Miracle-dz/UniFAR-FTUs huggingface dataset:
The attackers' potential influence on the tactical assessments produced by standard alert correlation systems

This work shows that knowledgeable attackers can influence the tactical assessments output by INFOSEC alert correlation systems solely through manipulating the timing characteristics of their attacks. The approach taken is to assume that the defender's goal is to thwart attackers by enact optimal tactical responses. It is then shown that, even in an idealized environment, the defender has no guarantee that the correlation system's estimates of the enacted attacks are correct. A theoretical path always exists by which the attacker can influence the contents of the correlation system's low-level alert clusters. As these low-level clusters form the basis of all higher level analyses, this is sufficient to show that the attacker has influence over the tactical assessments reported by correlation systems. In essence, the attackers can cause the defender to mis-correlate an attack's generated INFOSEC alerts in a manner which can go undetected and is to the attacker's advantage. This capability is shown to hinge on there being attacks whose identification requires the analysis of shared alerts (i.e., alerts generated by two or more distinct attacks).
A novel ML-based frequency offset estimator for OFDM systems

A novel carrier frequency offset (CFO) estimation algorithm based on the maximum-likelihood (ML) criterion for orthogonal frequency division multiplexing (OFDM) systems is proposed. In the proposed method, a well-known preamble with excellent timing synchronization is modified, and based on the improved preamble three fractional frequency offset estimators are investigated. The estimation range and the mean-square-error (MSE) performance under various signal-to-noise ratios (SNR) of the estimators are discussed. Finally, our proposed estimators are compared with the traditional Schmidl (SC) algorithm in terms of MSE. Simulation results demonstrate that the proposed methods have better performance than the SC frequency offset estimation algorithm in AWGN and multipath fading channels without increasing complexity. Moreover, the special characteristics of the improved preamble lead to a superior timing performance.
Thresholding for Top-k Recommendation with Temporal Dynamics

This work focuses on top-k recommendation in domains where underlying data distribution shifts overtime. We propose to learn a time-dependent bias for each item over whatever existing recommendation engine. Such a bias learning process alleviates data sparsity in constructing the engine, and at the same time captures recent trend shift observed in data. We present an alternating optimization framework to resolve the bias learning problem, and develop methods to handle a variety of commonly used recommendation evaluation criteria, as well as large number of items and users in practice. The proposed algorithm is examined, both offline and online, using real world data sets collected from the largest retailer worldwide. Empirical results demonstrate that the bias learning can almost always boost recommendation performance. We encourage other practitioners to adopt it as a standard component in recommender systems where temporal dynamics is a norm.
Influence of Steep Time on Polyphenol Content and Antioxidant Capacity of Black, Green, Rooibos, and Herbal Teas

Potential health benefits of tea consumption are often attributed to the antioxidant activity of polyphenols. Whether steep time, often variable in a real-life situation, makes a biological difference in terms of polyphenol content and antioxidant activity is uncertain. The study objective was to characterize eight popular and commercially available teas for total polyphenol content (TPC) and antioxidant capacity in relation to steep time. Dragonwell (DW), Sencha (S), English Breakfast (EB), Golden Monkey (GM), Green Rooibos (GR), Red Rooibos (RR), Chamomile (C), and Peppermint (P) loose leaf teas were individually steeped in water for 1–10 min at 1 min intervals. TPC increased with longer durations of steep time; however, the majority of polyphenols observed after 10 minutes were extracted in the first 5 min regardless of tea type. After 5 min of steeping, differences (p DW > GM~GR~RR > C). Different teas also varied in their ability to inhibit the free radical 2, 2-diphenyl-1-picrylhydrazyl (DPPH) when normalized for polyphenol concentration (1 µg/mL) and there was no effect due to steep time. Predicted antioxidant capacity of teas also demonstrated significant differences among teas after 5 and 10 min. In conclusion, steep time modulates TPC but not the antioxidative capacity of tea polyphenols.
Constraining Dark Energy and Cosmological Transition Redshift with Type Ia Supernovae

The property of dark energy and the physical reason for the acceleration of the present universe are two of the most difficult problems in modern cosmology. The dark energy contributes about two-thirds of the critical density of the present universe from the observations of type-Ia supernovae (SNe Ia) and anisotropy of cosmic microwave background (CMB). The SN Ia observations also suggest that the universe expanded from a deceleration to an acceleration phase at some redshift, implying the existence of a nearly uniform component of dark energy with negative pressure. We use the ``Gold'' sample containing 157 SNe Ia and two recent well-measured additions, SNe Ia 1994ae and 1998aq to explore the properties of dark energy and the transition redshift. For a flat universe with the cosmological constant, we measure Ω M = 0.28 −0.05 +0.04 , which is consistent with Riess et al. The transition redshift is z T = 0.60 −0.08 +0.06 . We also discuss several dark energy models that define w ( z ) of the parameterized equation of state of dark energy including one parameter and two parameters ( w ( z ) being the ratio of the pressure to energy density). Our calculations show that the accurately calculated transition redshift varies from z T = 0.29 −0.06 +0.07 to z T = 0.60 −0.08 +0.06 across these models. We also calculate the minimum redshift z c at which the current observations need the universe to accelerate.
ICOS is associated with poor prognosis in breast cancer as it promotes the amplification of immunosuppressive CD4+ T cells by plasmacytoid dendritic cells

Regulatory T cells (Tregs) and plasmacytoid dendritic cells (pDCs) that infiltrate primary breast tumors impair patient survival. The ICOS-mediated interaction between tumor-infiltrating CD4+ T cells and pDCs leads to the amplification of Tregs and interleukin-10 secretion. Importantly, ICOS+ cell infiltration correlates with adverse patient prognosis, identifying ICOS as a new target for cancer immunotherapy.
Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia

A short memory process that encounters occa- sional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I(d) processes. In this paper we em- ployed a procedure for estimating the fractional differencing parameter in semiparametric contexts proposed by Geweke and Porter-Hudak (1983) to analyse nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long memory. Furthermore, an empirical fluctuation process using the ordinary least square (OLS)-based cumula- tive sum (CUSUM) test for the break date was applied. Break dates were detected in all data sets. The data sets were parti- tioned according to their respective break date, and a further test for long memory was applied for all subseries. Results show that all subseries follows the same pattern as the origi- nal series. The estimate of the fractional parameters d1 andd2 on the subseries obtained by splitting the original series at the break date confirms that there is a long memory in the data generating process (DGP). Therefore this evidence shows a true long memory not due to structural break.
Claudin-1 Acts through c-Abl-Protein Kinase Cδ (PKCδ) Signaling and Has a Causal Role in the Acquisition of Invasive Capacity in Human Liver Cells*

Claudins are identified as members of the tetraspanin family of proteins, which are integral to the structure and function of tight junction. Recent studies showed an increase in expression of claudins during tumorigenesis, which is associated with loss of cell-cell contact, dedifferentiation, and invasiveness. However, the molecular basis for the causal relationship between claudin expression and cancer progression is not fully understood yet. In this study, we show that claudin-1 plays a causal role in the acquisition of invasive capacity in human liver cells and that c-Abl-protein kinase Cδ (PKCδ) signaling is critical for the malignant progression induced by claudin-1. Overexpression of claudin-1 clearly induced expression of matrix metalloproteinase-2 (MMP-2) and cell invasion and migration in normal liver cells as well as in non-invasive human hepatocellular carcinoma (HCC) cells. Conversely, small interfering RNA targeting of claudin-1 in invasive HCC cells completely inhibited cell invasion. Both c-Abl and PKCδ are found to be activated in normal liver cell line clones that stably overexpress claudin-1. Inhibition of either c-Abl or PKCδ alone clearly attenuated MMP-2 activation and impeded cell invasion and migration in both human HCC and normal liver cells expressing claudin-1. These results indicate that claudin-1 is both necessary and sufficient to induce invasive behavior in human liver cells and that activation of c-Abl-PKCδ signaling pathway is critically required for the claudin-1-induced acquisition of the malignant phenotype. The present observations raise the possibility of exploiting claudin-1 as a potential biomarker for the spread of liver cancer and might provide pivotal points for therapeutic intervention in HCC.
Disaster Risk Reduction for International Residents in Japan: Barriers and Facilitators to Knowledge Sharing in Times of Disaster

This study finds that local governments admit limited progress in development of disaster risk reduction measures for international residents with limited Japanese proficiency, during the five-year period following the 2011 Great East Japan Earthquake and Tsunami, based on a questionnaire survey. Local governments' security management includes an issue of knowledge sharing in times of disaster. Our survey analyzes barriers and facilitators to knowledge sharing with international residents on disaster risk reduction. From the perspective of international residents, knowledge sharing barriers are reported as very limited relationship with the local community, and very limited Japanese proficiency. From the perspective of local governments, one of knowledge sharing barriers is reported as limited human resources of multi-cultural management. Local governments in Japan plan and prioritize disaster-related knowledge sharing facilitators such as building multi-lingual information websites and encouraging neighborly relations between international residents and the local community on a regular basis.
Some Stable Difference Approximations to a Fourth-Order Parabolic Partial Differential Equation

where £i = * and A = 0 -11 . 1 o J' Since A AA' = 0 and A'1 = —A, (4) is a Schrodinger type system of partial differential equations, (Kreiss [6]). Richtmyer [11] and Evans [5] have derived finite difference methods for the numerical solution of Eq. (4) which are based on well-known algorithms for the numerical solution of the scalar equation , _. dv _ d"v {o) Tt~dx~*Received February 21, 1966.
Repetitive Transcranial Magnetic Stimulation of Broca's Area Affects Verbal Responses to Gesture Observation

The aim of the present study was to determine whether Broca's area is involved in translating some aspects of arm gesture representations into mouth articulation gestures. In Experiment 1, we applied low-frequency repetitive transcranial magnetic stimulation over Broca's area and over the symmetrical loci of the right hemisphere of participants responding verbally to communicative spoken words, to gestures, or to the simultaneous presentation of the two signals. We performed also sham stimulation over the left stimulation loci. In Experiment 2, we performed the same stimulations as in Experiment 1 to participants responding with words congruent and incongruent with gestures. After sham stimulation voicing parameters were enhanced when responding to communicative spoken words or to gestures as compared to a control condition of word reading. This effect increased when participants responded to the simultaneous presentation of both communicative signals. In contrast, voicing was interfered when the verbal responses were incongruent with gestures. The left stimulation neither induced enhancement on voicing parameters of words congruent with gestures nor interference on words incongruent with gestures. We interpreted the enhancement of the verbal response to gesturing in terms of intention to interact directly. Consequently, we proposed that Broca's area is involved in the process of translating into speech aspects concerning the social intention coded by the gesture. Moreover, we discussed the results in terms of evolution to support the theory [Corballis, M. C. (2002). From hand to mouth: The origins of language. Princeton, NJ: Princeton University Press] proposing spoken language as evolved from an ancient communication system using arm gestures.
Agricultural commercialization, economic development, and nutrition.

The commercialization of agriculture has been the cornerstone of economic development for many developing countries. Yet there continues to be concern about the effects of commercialization on poverty and nutrition in countries that are promoting the shift away from subsistence agriculture. In "Agricultural Commercialization, Economic Development and Nutrition", Joachim von Braun and Eileen Kennedy bring together a distinguished group of authorities who present solid empirical data based on a comprehensive conceptual framework. The authors examine the driving forces of commercialization, such as trade policy and infrastructure, and analyze potential risks to the poor. Original case studies - based on one to three years of field work by multidisciplinary teams - focus on the Gambia, Kenya, Malawi, Sierra Leone, Rwanda, Zambia, Guatemala, India, China, Indonesia, Papua New Guinea and the Philippines. The authors conclude that commercialization of agriculture can enhance economic development through employment and income growth, which bring about improvements in nutrition - especially for the poor. This is a comprehensive treatment of the issues that link agricultural commercialization, development and nutrition.
An Information Architecture for Future Power Systems and Its Reliability Analysis

Analysis of 162 disturbances from 1979-1995 reported by the North American Electric Reliability Council (NERC) indicates the importance of information systems under the regulated and competitive environment. This paper points out the major deficiencies in current communication and information systems and proposes a new power system information architecture aimed at correcting these deficiencies. The proposed architecture includes automation and control systems at all levels, from substation control system to independent system operator (ISO) operating center, taking into account the requirements of real-time data, security, availability, scalability, and appropriate quality of service. It uses multiple communication channels employing a wide variety of technologies to transmit real-time operating data and control signals. The real-time operating and control system is modeled with various redundancy configurations. The reliabilities of different configurations are studied and compared for practical values of component failure rates and repair rates.
Human head detection based on multi-stage CNN with voting strategy

As a classical problem in target detection, human head detection based on head features is an important basis of intelligent vehicle driving and people counting. Due to the irregularity and complexity of human head, artificial designed feature description methods have lower recognition rate and worse robustness. As an important part of deep learning, convolutional neural network (CNN) has applied to image recognition and speech analysis successfully. In view of the instability and hard description of head features, a new head detection method based on multi-stage CNN with voting strategy is proposed in this paper. Firstly, we use features abstracted by multi-stage CNN from different layers to classify respectively. Then, we use the results to get the final classification through voting strategy. Experimental results show that new method has higher recognition rate compared with traditional ones.
Building a New Structure for School Leadership.

Unless there is a radical change in the structure of school leadership, few schools will be able to rise to the challenge of enabling all students to meet high standards, says Anrig Professor of Educational Leadership Richard F. Elmore. With accountability standards creating more public scrutiny than ever before, educational leaders must focus their efforts on instruction if they are to thrive and survive in the current conditions. Based on the essay "Building a New Structure for School Leadership," from Professor Elmore's book, School Reform from the Inside Out: Policy, Practice, and Performance (Harvard Education Press, 2004).
Resolution Control for Balancing Overview and Detail in Multivariate Spatial Analysis

Abstract Parallel coordinates, re-orderable matrices, and dendrograms, widely used methods for visual exploration of multivariate data, are systematically integrated in a complementary manner for supporting multi-resolution visual data analysis with an enhanced overview + detail exploratory strategy. There are three main topics: (1) dynamic control across resolutions at which data are explored; (2) coordination and color mapping among the views; and (3) enhanced features of each view designed for the overview + detail exploratory tasks. A case study analysis is used to demonstrate the potential for boosting productivity for exploration tasks by coordinating the views through user-controlled resolutions within a highly interactive analysis environment. The case study is focused on a complex, geographically referenced dataset including public health, demographic and environmental components.
Bioprocessing of Proximally Analyzed Wheat Straw for Enhanced Cellulase Production through Process Optimization with Trichodermaviride under SSF

The purpose of the present work was to study the production and process parameters optimization for the synthesis of cellulase from Trichoderma viride in solid state fermentation (SSF) using an agricultural wheat straw as substrates; as fungal conversion of lignocellulosic biomass for cellulase production is one among the major increasing demand for various biotechnological applications. An optimization of process parameters is a necessary step to get higher yield of product. Several kinetic parameters like pretreatment, extraction solvent, substrate concentration, initial moisture content, pH, incubation temperature and inoculum size were optimized for enhanced production of third most demanded industrially important cellulase. The maximum cellulase enzyme activity 398.10±2.43 μM/mL/min was achieved when proximally analyzed lignocellulosic substrate wheat straw inocubated at 2% HCl as pretreatment tool along with distilled water as extraction solvent, 3% substrate concentration 40% moisture content with optimum pH 5.5 at 45°C incubation temperature and 10% inoculum size. Keywords—Cellulase, Lignocellulosic residue, Process optimization, Proximal analysis, SSF, Trichoderma viride.
ANITA: a narrative interpretation of taxonomies for their adaptation to text collections

Taxonomies embody formalized knowledge and define aggregations between concepts/categories in a given domain, facilitating the organization of the data and making the contents easily accessible to the users. Since taxonomies have significant roles in the data annotation, search and navigation, they are often carefully engineered. However, especially in very dynamic content, they do not necessarily reflect the content knowledge. Thus, in this paper, we propose A Narrative Interpretation of Taxonomies for their Adaptation (ANITA) for re-structuring existing taxonomies to varying application contexts and we evaluate the proposed scheme by user studies that show that the proposed algorithm is able to adapt the taxonomy in a new compact and understandable structure from a human point of view.
Assisting e-patients in an Ask the Doctor Service

Ask the doctor services are personalized forums allowing patients to ask questions directly to doctors. Usually, patients must choose the most appropriate category for their question among lots of categories to be redirected to the most relevant physician. However, manual selection is tedious and error prone activity. In this work we propose to assist the patients in this task by recommending a short list of most appropriate categories.
Comparison of Different Virtual MIMO Detection Schemes for 3GPP LTE

This paper addresses the issues of MIMO detection schemes for LTE uplink at received port when V-MIMO scheme is deployed at transmitter, which is always a trade-off between performance and complexity. More specifically,the authors will focus on the deployment of of virtual MIMO in the UTRA LTE uplink and investigrate two different received detection algorithms,namely Zero-Forcing and Minimum Mean Squared Error Successive Interference Cancellation, proposed for V-MIMO dection considering performances and as well as computional complexity.Finally link level simulation results are provided to evaluate algorithms for implementation and feasibility.It has shown ZF-SIC outperforms somewhat MMSE-SIC in terms of BER under diverse practical scenarios dedicated for LTE systems.
Right Questions to Capture Knowledge

Existing tools that are used to support the process of transferring tacit knowledge into explicit knowledge do not support the affection of individuals and their knowledge, but rather data and information processing. A more personalised view of knowledge is required, and a toolbox has been constructed in order to increase the individual’s capacity to describe his/her own situation within organisations. This is assumed to motivate the person to contribute with knowledge. An empirical investigation of a prototypical nature has been conducted. The empirical results are positive for eliciting knowledge.
CameraMan: A multirobot system for nanohandling in a scanning electron microscope

This paper presents the detailed design of a nanohandling robot cell that can work inside an SEM's vacuum chamber and incorporates miniature video microscopes in order to enable fully automated nanohandling and -assembly. The geometrical and mechanical requirements are defined and addressed in a modular implementation. Image processing techniques can be used to recognize and track objects and three dimensional information can be obtained by stereo vision as well as the microscope's focus. To control this highly heterogeneous system, different low-level controllers are used, challenges for cooperatively controlling the multi-robot system are outlined, and high-level automation is discussed.