Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovering Transcriptional Regulation by Integrating Protein-Protein Interaction, Gene Expression and Transcriptional Interaction Data

Understanding transcriptional regulation (TR) principles and mechanisms is a hot topic in the genomics and transcriptome research. Many experimental and computational methods have been proposed to investigate this problem. However, perhaps partially because the high complexity in the transcriptional regulation mechanism, or partially because the noise in the high-throughput detection experiments, integrative approaches are demanded to discover underlying TRs which could be missed when only single source of information is considered. In this paper, we explore the biological ideas behind co-regulated protein complexes to study this problem. Co-regulated protein complex has three remarkable characteristics: coding genes of member proteins share the same transcription factor, coding genes usually express coordinately and member proteins intensively interact and form a complex to implement a common biological function. It implies close relation- ships among co-regulation, co-expression and intensive interaction at the levels of transcriptional regulation, gene expression and protein-protein interaction. Based on these ideas, we integrate protein-protein interaction (PPI), gene expression (GE) and transcriptional interaction (TI) data and use them to form a framework to discover new TR relationships. Experiments on the yeast in three conditions of cell cycle, diauxic shift and DNA damaging were conducted, and 20 novel TRs were predicted and explained.
Espoused Organizational Culture Traits and Internet Technology Adoption

The Technology Acceptance Model, popularly known as the TAM, has been widely used in the information systems literature to explain individual adoption of information technology. In the late 1990’s, and the early part of this century, a number of studies either extended the model by identifying antecedents to technology acceptance or have replicated and validated the model. An aspect that has captured the interest of information systems researchers is the role of culture in the acceptance, adoption, and diffusion. We examine the role of espoused organizational culture traits in technology acceptance, adoption and diffusion, that is, we consider organizational cultural values to be antecedents of TAM. We empirically test this model in an e-government setting in a developing country and report on our findings.
Expression of Mitochondrial Regulators PGC1α and TFAM as Putative Markers of Subtype and Chemoresistance in Epithelial Ovarian Carcinoma

Epithelial ovarian carcinoma (EOC), the major cause of gynaecological cancer death, is a heterogeneous disease classified into five subtypes. Each subtype has distinct clinical characteristics and is associated with different genetic risk factors and molecular events, but all are treated with surgery and platinum/taxane regimes. Tumour progression and chemoresistance is generally associated with major metabolic alterations, notably altered mitochondrial function(s). Here, we report for the first time that the expression of the mitochondrial regulators PGC1α and TFAM varies between EOC subtypes; furthermore, we have identified a profile in clear-cell carcinoma consisting of undetectability of PGC1α/TFAM, and low ERα/Ki-67. By contrast, high-grade serous carcinomas were characterised by a converse state of PGC1α/TFAM, ERα positivity and a high Ki-67 index. Interestingly, loss of PGC1α/TFAM and ERα was found also in a non-clear cell EOC cell line made highly resistant to platinum in vitro. Similar to clear-cell carcinomas, these resistant cells also showed accumulation of glycogen. Altogether, our data provide mechanistic insights into the chemoresistant nature of ovarian clear-cell carcinomas. Furthermore, these findings corroborate the need to take into account the diversity of EOC and to develop subtype specific treatment strategies.
The applicability of human-centred automation guidelines in the fighter aircraft domain

Motivation -- To guide the development of human-centred automation within the fighter aircraft domain. Research approach -- Identified human-centred automation guidelines have been analysed in relation to existing fighter aircraft automated functions together with system developers at Saab Aeronautics. Findings/Design -- The results show that the human-centred automation guidelines have been considered during the development process. From these results, implications for the design of guidelines and for the design of automated systems in the aircraft domain are drawn. Research limitations/Implications -- Deeper analysis of how automated functions can support pilots in future fighter aircraft is needed since the proposed guidelines are too general for the military fighter aircraft domain. Thus, future work involves an evaluation of the guidelines together with fighter aircraft system developers and/or military strategists. Such analysis must be carried out with specific automated functions in mind. Originality/Value -- By comparing with existing automated functions, the research makes contributions to HCA guidelines to be used in the fighter aircraft domain. Suggestions of human-centred automation improvements within the fighter aircraft domain are presented. The analysis has also identified differences between the proposed guidelines and parts of the studied implementation examples. Take away message -- The HCA guidelines must be adapted according to the specific tasks that the automated functions are intended to assist the operators with. To adapt the automation according to the level of experience of the operators as well as to expand the cooperative automation functions between aircraft in a team have been identified as future directions for automation improvements within the fighter aircraft domain.
Embedding integration: How European integration splits mainstream parties

While newly contested issues connected with internationalism, such as European integration and migration, have become more politically salient, much of the literature sees these as largely the domain of ideologically extremist and challenger parties. By contrast, building on work by Kriesi et al, this article argues that international issues are far more embedded in party stances across the left- right spectrum than the niche and extremist models or Kriesi et al suggest. Accordingly, we develop a typology for categorizing parties according to their stances on left-right ideology and their positions on integration. Our analysis employs expert surveys on the stances of all electorally significant parties conducted in 24 European countries in 2013. The results have important implications for understanding the impact of international issues on how parties now appeal to voters.
A Holistic Approach for Enriching Information Security Analysis and Security Policy Formation

Past literature has indicated the need for addressing information security from both the social and technical perspective. However, previous research has lacked in providing any clear direction for how these two perspectives can be brought together in a coherent or holistic manner to analyze information security in an organization. Thus, this paper develops a conceptual framework for identifying, bringing together, and interpreting the deep-rooted social and technical issues that pertain to information systems security. The framework is grounded in semiotics and is validated by the analysis of a specific case study. Findings in this research indicate that the social and technical elements of security can be brought together in a holistic manner via six layers of abstraction where each layer addresses deep-rooted issues that pertain to information security. The output of each layer is then used to inform other layers in a collaborative manner creating a final product that contains elements for enriching security analysis and enhancing security policy formation.
Images matching based on edge maps and wavelet transform

A structure-based image similarity measurement called DTWT-SSIM is presented. The main idea behind DTWT-SSIM is to combine the shift-invariance advantage of dual-tree wavelet transform (DTWT) with the structure-preserving property of the structural similarity metrics (SSIM). A series of experimental results show the improved measurement to be an effective and stable metric in the comparison of edge maps when small noise and distortion appear in the images.
Particle grid tracking system for stereovision based environment perception

This paper presents an occupancy grid tracking solution based on particles. The particles will have a dual nature - they will denote hypotheses, as in the particle filtering algorithms, but they will also be the building blocks of our modeled world. The particles have position and speed, and they can migrate in the grid from cell to cell depending on their motion model and motion parameters, but they will also be created and destroyed using a weighting-resampling mechanism specific to particle filter algorithms. An obstacle grid derived from processing a stereovision-generated elevation map is used as measurement information, and the measurement model takes into account the uncertainties of the stereo reconstruction. The resulted system is a flexible, real-time tracking solution for dynamic unstructured driving environments.
Speech Translation with Phrase Based Stochastic Finite-State Transducers

Stochastic finite-state transducers constitute a type of word-based models that allow an easy integration with acoustic model for speech translation. The aim of this work is to develop a novel approach to phrase-based statistical finite-state transducers. In this work, we explore the use of linguistically motivated phrases to build phrase-based models. The proposed phrase-based transducer has been tested and compared to a word-based equivalent machine, yielding promising results in the reported preliminary text and speech translation experiments.
A comparative study on software vulnerability static analysis techniques and tools

Using static analysis tools can detect software vulnerabilities, which is important for improving the security of software. Static analysis technology has developed rapidly, but the comparison and evaluation of static analysis techniques and tools are not much. This paper focuses on software vulnerability static analysis techniques and tools. First we discuss the commonly-used static analysis techniques and tools, and compare these tools in a technical perspective, and then we analyze the characteristics of these tools through the experiment, finally, combining dynamic analysis, we propose an efficient software vulnerability detection method.
They do not suffer like us : The differential attribution of social pain as a dehumanization criterion in children

Resumen Background: Social pain is considered a feature of humanity. The goal of this study was to confi rm whether children, like adults, dehumanise out-group members attributing them less capacity to experience social pain than to in-group members. Methods: A total of 119 participants aged between 9 and 13 years responded to a questionnaire which collected information about situations that caused physical pain and situations that caused social pain. The task of the participants was to indicate to what extent they considered that two persons (a member of the in-group and a member of an out-group) would experience pain in each situation. Results: The results indicated that there was a higher estimate of social pain suffered by in-group members. There were no signifi cant differences in the case of situations that generated physical in the groups. Conclusions: The results were analysed from the dehumanisation perspective.
Transperformative education: Toward a new educational paradigm based on transdisciplinarity and artistic performativity

The study we are presenting in this article is based on an analysis of the critical observations of the state of the art of the prevailing educational systems today through evaluations by institutions like the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the Organisation for Economic Co-Operation and Development and the logical demand for reform that they call for. As a consequence, we posit an approach to the construction of an educational paradigm based on performative education that draws from performance art, transdisciplinary methodology, and a survey of the specialized literature that frames the epistemological and methodological field of education in complex, ever-changing settings. The methodology used is a heuristic comparison in a pedagogical sense that, based on our analysis of state of the art publications from the educational system, outlines the transfer of the characteristics of performance art and transdisciplinary methodology to the model we call Transperformative Education. As a result of this model, we came up with a proposal for a deep-seated paradigmatic shift that entails everything from the modification of institutional educational policies to the ways of teaching and learning, including, of course, a major challenge: a shift in the direction of educational research.
Weighted Sum-Rate Maximization for Full-Duplex MIMO Interference Channels

We consider a K link multiple-input multiple-output (MIMO) interference channel, where each link consists of two full-duplex (FD) nodes exchanging information simultaneously in a bi-directional communication fashion. The nodes in each pair suffer from self-interference due to operating in FD mode, and inter-user interference from other links due to simultaneous transmission at each link. We consider the transmit and receive filter design for weighted sum-rate (WSR) maximization problem subject to sum-power constraint of the system or individual power constraints at each node of the system. Based on the relationship between WSR and weighted minimum-mean-squared-error (WMMSE) problems for FD MIMO interference channels, we propose a low complexity alternating algorithm which converges to a local WSR optimum point. Moreover, we show that the proposed algorithm is not only applicable to FD MIMO interference channels, but also applicable to FD cellular systems in which a base station (BS) operating in FD mode serves multiple uplink (UL) and downlink (DL) users operating in half-duplex (HD) mode, simultaneously. It is shown in simulations that the sum-rate achieved by FD mode is higher than the sum-rate achieved by baseline HD schemes.
A New Simulation Technique for Study of Collisionless Shocks: Self‐Adaptive Simulations

The traditional technique for simulating physical systems modeled by partial differential equations is by means of time‐stepping methodology where the state of the system is updated at regular discrete time intervals. This method has inherent inefficiencies. In contrast to this methodology, we have developed a new asynchronous type of simulation based on a discrete‐event‐driven (as opposed to time‐driven) approach, where the simulation state is updated on a “need‐to‐be‐done‐only” basis. Here we report on this new technique, show an example of particle acceleration in a fast magnetosonic shockwave, and briefly discuss additional issues that we are addressing concerning algorithm development and parallel execution.
Characterizing the dynamic connectivity between genes by variable parameter regression and Kalman filtering based on temporal gene expression data

MOTIVATION One popular method for analyzing functional connectivity between genes is to cluster genes with similar expression profiles. The most popular metrics measuring the similarity (or dissimilarity) among genes include Pearson's correlation, linear regression coefficient and Euclidean distance. As these metrics only give some constant values, they can only depict a stationary connectivity between genes. However, the functional connectivity between genes usually changes with time. Here, we introduce a novel insight for characterizing the relationship between genes and find out a proper mathematical model, variable parameter regression and Kalman filtering to model it. RESULTS We applied our algorithm to some simulated data and two pairs of real gene expression data. The changes of connectivity in simulated data are closely identical with the truth and the results of two pairs of gene expression data show that our method has successfully demonstrated the dynamic connectivity between genes. CONTACT jiangtz@nlpr.ia. ac.cn.
Making the Student Learning Experience Fun, Memorable and Effective: A Case of Entrepreneurship Students

The goal of every passionate educator is to ensure that his or her students adopt a deep learning approach to the material being taught so that they can apply these concepts in their lives beyond the classroom. This is particularly true for entrepreneurship students who are expected to establish their own businesses after graduating from university. In order to achieve this very important objective, it is vital that the educator does everything in his or her power to ensure that the students‘ learning experiences are made as enjoyable and as memorable as possible. This paper presents the achievement of this objective amongst a group of entrepreneurship students in Nigeria through the introduction of a team learning competition concept in an Organizational Behaviour course over two years. Students were required to form same-gender groups of five and establish companies. Each group was then required to make thirty-minute oral presentations explaining their company‘s organizational culture and the strategies adopted to ensure that the culture permeated every aspect of the business. The team with the best presentation was awarded a monetary prize at the end of the semester. Observations of the students‘ behaviours before, during and after the presentations revealed that the students‘ engagement in the course was exponentially enhanced as evidenced by their unbridled enthusiasm and creative approaches to the presentations. It is recommended that entrepreneurship and business educators adopt a similar approach so as to elevate the students‘ learning experiences, and make the university career a fun, memorable and effective one as opposed to the current tortuous grind that it is now, particularly from a Nigerian context.
Efficient extraction and analysis of preprocessor-based variability

The C Preprocessor (CPP) is the tool of choice for the implementation of variability in many large-scale configurable software projects. Linux, probably the most-configurable piece of software ever, employs more than 10,000 preprocessor variables for this purpose. However, this de-facto variability tends to be "hidden in the code"; which on the long term leads to variability defects, such as dead code or inconsistencies with respect to the intended (modeled) variability of the software. This calls for tool support for the efficient extraction of (and reasoning over) CPP-based variability. We suggest a novel approach to extract CPP-based variability. Our tool transforms CPP-based variability in O(n) complexity into a propositional formula that "mimics" all valid effects of conditional compilation and can be analyzed with standard SAT or BDD packages. Our evaluation results demonstrate the scalability and practicability of the approach. A dead-block-analysis on the complete Linux source tree takes less than 30 minutes; we thereby have revealed 60 dead blocks, 2 of which meanwhile have been confirmed as new (and long-lasting) bugs; the rest is still under investigation.
Anxiety detection during human-robot interaction

This paper describes an experiment to determine the feasibility of using physiological signals to determine the human response to robot motions during direct human-robot interaction. A robot manipulator is used to generate common interaction motions, and human subjects are asked to report their response to the motions. The human physiological response is also measured. Motion paths are generated using a classic potential field planner and a safe motion planner, which minimizes the potential collision force along the path. A fuzzy inference engine is developed to estimate the human response based on the physiological measures. Results show that emotional arousal can be detected using physiological signals and the inference engine. Comparison of initial results between the two planners shows that subjects report less anxiety and surprise with the safe planner for high planner speeds.
ALUPower: Data Dependent Power Consumption in GPUs

Existing architectural power models for GPUs count activities such as executing floating point or integer instructions, but do not consider the data values processed. While data value dependent power consumption can often be neglected when performing architectural simulations of high performance Out-of-Order (OoO) CPUs, we show that this approach is invalid for estimating the power consumption of GPUs. The throughput processing approach of GPUs reduces the amount of control logic and shifts the area and power budget towards functional units and register files. This makes accurate estimations of the power consumption of functional units even more crucial than in OoO CPUs. Using measurements from actual GPUs, we show that the processed data values influence the energy consumption of GPUs significantly. For example, the power consumption of one kernel varies between 155 and 257 Watt depending on the processed values. Existing architectural simulators are not able to model the influence of the data values on power consumption. RTL and gate level simulators usually consider data values in their power estimates but require detailed modeling of the employed units and are extremely slow. We first describe how the power consumption of GPU functional units can be measured and characterized using microbenchmarks. Then measurement results are presented and several opportunities for energy reduction by software developers or compilers are described. Finally, we demonstrate a simple and fast power macro model to estimate the power consumption of functional units and provide a significant improvement in accuracy compared to previously used constant energy per instruction models.
Plane geometry and convexity of polynomial stability regions

The set of controllers stabilizing a linear system is generally non-convex in the parameter space. In the case of two-parameter controller design (e.g. PI control or static output feedback with one input and two outputs), we observe however that quite often for benchmark problem instances, the set of stabilizing controllers seems to be convex. In this note we use elementary techniques from real algebraic geometry (resultants and Bezoutian matrices) to explain this phenomenon. As a byproduct, we derive a convex linear matrix inequality (LMI) formulation of two-parameter fixed-order controller design problem, when possible.