Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Observation Problems ∗

We introduce and study problems of distributed observation with bounded or unbounded memory. We are given a system modeled as a finite-word language L over some finite alphabetΣ and subalphabets Σ1, . ,Σn of Σ modeling n distinct observation points. We want to build (when there exist)n observers which collect projections of a behavior in L ontoΣ1, . ,Σn, then send them to a central decision point. The latter must determine whether the original behavior was in a givenK ⊆ L. In the unbounded-memory case, observers record the entire sequence they observe. In the bounded-memory case, they are required to be finite-
Collaborative Coordination and Control for an Implemented Heterogeneous Swarm of UAVs and UGVs

the last few years, cooperative autonomous systems have become a more popular solution for accomplishing tasks that are otherwise performed by human operators. Several strides have been made with homogeneous systems of vehicles in areas of localization, formation behaviors, path planning, task allocation, and vehicle controls. This paper describes both work completed and the future goals in the Machine Intelligence Lab (MIL) on the development of a heterogeneous system of platforms consisting of unmanned ground vehicles (UGS) and unmanned aerial vehicles (UAVs) that cooperatively work together to accomplish tasks such as search and rescue in an outdoor environment. The Robot Operating System (ROS) is used between and within each vehicle to handle cooperative high level planning and task allocation, as well as control each vehicle's individual capabilities, specializing in identification or classification. High level planning between vehicles includes formation behaviors, heterogeneous path planning and task allocation, and basic levels of localization. A description of the system and a planned implementation in a practical testing environment is also given.
Invading ethnography: A queer of color reflexive practice

This article proposes invading ethnography as reflexive practice that disrupts normative representations of gender and sexuality. Writing from the perspective of the queer of color, this reflexive practice plays on the idea of the ethnographic researcher as an alien entity that invades a social setting, thereby calling attention to ethnography’s colonial history. I model this practice by sharing an ethnographic narrative from my research with a Ghanaian community in Houston, Texas. Rather than contain reflexivity to a methodological appendix or footnote, invading ethnography strategically interrupts the ethnographic narrative to illustrate how normative assumptions about gender and sexuality not only shape the organization of social spaces, but also inform ethnographic possibilities. In so doing, this article performs a decolonial option by destabilizing the powerful position of the narrator through an interruption of the ethnographic narrative.
Wayfinding : embedding knowledge in hospital environments

The traditional use of signs has failed to overcome the problem of wayfinding in hospitals. As wayfinding problems are clearly linked to healthcare outcomes there is need to find a more integrated approach to solving the problem. In this paper it is shown that it is possible to embed forms of knowledge that make it easier for people to find their way with little need for signs. Evidence from literature and from fieldwork supports this assertion. Methods used for our research included direct observation, analysis of photographs and discussion with members of staff and other users of the setting.
Hierarchical models for assessing variability among functions

In many applications of functional data analysis, summarising functional variation based on fits, without taking account of the estimation process, runs the risk of attributing the estimation variation to the functional variation, thereby overstating the latter. For example, the first eigenvalue of a sample covariance matrix computed from estimated functions may be biased upwards. We display a set of estimated neuronal Poisson-process intensity functions where this bias is substantial, and we discuss two methods for accounting for estimation variation. One method uses a random-coefficient model, which requires all functions to be fitted with the same basis functions. An alternative method removes the same-basis restriction by means of a hierarchical Gaussian process model. In a small simulation study the hierarchical Gaussian process model outperformed the randomcoefficient model and greatly reduced the bias in the estimated first eigenvalue that would result from ignoring estimation variability. For the neuronal data the hierarchical Gaussian process estimate of the first eigenvalue was much smaller than the naive estimate that ignored variability due to function estimation. The neuronal setting also illustrates the benefit of incorporating alignment parameters into the hierarchical scheme. Copyright 2005, Oxford University Press.
Recent Attempts to Measure the General Relativistic Lense-Thirring Effect with Natural and Artificial Bodies in the Solar System

According to general relativity, a spinning body of mass M and angular momentum S, like a star or a planet, generates a gravitomagnetic field which induces, among other phenomena, also the Lense-Thirring effect, i.e. secular precessions of the path of a test particle orbiting it. Direct and indisputable tests of such a relativistic prediction are still missing. We discuss some performed attempts to measure it in the gravitational fields of several bodies in the Solar System with natural and artificial objects. The focus is on the realistic evaluation of the impact of some competing classical forces regarded as sources of systematic uncertainties degrading the total accuracy obtainable.
Pax6 Is Required for Making Specific Subpopulations of Granule and Periglomerular Neurons in the Olfactory Bulb

The subventricular zone (SVZ) produces different subclasses of olfactory bulb (OB) interneurons throughout life. Little is known about the molecular mechanisms controlling the production of different types of interneurons. Here we show that most proliferating adult SVZ progenitors express the transcription factor Pax6, but only a small subpopulation of migrating neuroblasts and new OB interneurons derived from these progenitors retains Pax6 expression. To elucidate the cell-autonomous role of Pax6 in OB neurogenesis, we transplanted green fluorescent protein-expressing embryonic forebrain progenitors of the dorsal lateral ganglionic eminence from Pax6 mutant Small Eye (Pax6Sey/Sey) mice into the SVZ of adult wild-type mice. Pax6Sey/Sey progenitors produce neuroblasts capable of migrating into the OB but fail to generate dopaminergic periglomerular and superficial granule cells. Interestingly, superficial granule neurons also express mRNA for tyrosine hydroxylase, the rate-limiting enzyme in dopamine synthesis. Our data show that SVZ neuroblasts are heterogeneous and that Pax6 is required in a cell-autonomous manner for the production of cells in the dopaminergic lineage.
Movement qualities as interaction modality

In this paper, we explore the use of movement qualities as interaction modality. The notion of movement qualities is widely used in dance practice and can be understood as how the movement is performed, independently of its specific trajectory in space. We implemented our approach in the context of an artistic installation called A light touch. This installation invites the participant to interact with a moving light spot reacting to the hand movement qualities. We conducted a user experiment that showed that such an interaction based on movement qualities tends to enhance the user experience favouring explorative and expressive usage.
LQG-based voltage control of the single-phase inverter for noisy environment

Linear Quadratic Gaussian (LQG) based phase voltage control is implemented. The regulation performance, estimation accuracy and interference sensitivity of different LQG control schemes is evaluated and compared. Paper reveals that it is possible to make the control system more insensitive to EMI when compared to dual-loop PI control and that the synchronous co-ordinate control scheme's all-around performance is the best.
SimWiz3D - visualising biochemical simulation results

Thanks to modern experimental technologies knowledge of the processes in living cells has been increasing rapidly in recent years. This is resulting in masses of data that need to be handled, analysed and interpreted. In addition, simulation and modelling which are being more and more frequently used to support experimental investigations leading to large amounts of numerical data, e.g. times series. Therefore, it becomes increasingly important to develop visualisation tools which facilitate the analysis of the respective data. This paper introduces the novel software tool SimWiz3D which visualises time series data in a concise way using a three-dimensional representation and provides the user with a lot of different ways to interact with and utilise the simulation data.
Tumor Suppressor Function of the SEMA3B Gene in Human Lung and Renal Cancers

The SEMA3B gene is located in the 3p21.3 LUCA region, which is frequently affected in different types of cancer. The objective of our study was to expand our knowledge of the SEMA3B gene as a tumor suppressor and the mechanisms of its inactivation. In this study, several experimental approaches were used: tumor growth analyses and apoptosis assays in vitro and in SCID mice, expression and methylation assays and other. With the use of the small cell lung cancer cell line U2020 we confirmed the function of SEMA3B as a tumor suppressor, and showed that the suppression can be realized through the induction of apoptosis and, possibly, associated with the inhibition of angiogenesis. In addition, for the first time, high methylation frequencies have been observed in both intronic (32-39%) and promoter (44-52%) CpG-islands in 38 non-small cell lung carcinomas, including 16 squamous cell carcinomas (SCC) and 22 adenocarcinomas (ADC), and in 83 clear cell renal cell carcinomas (ccRCC). Correlations between the methylation frequencies of the promoter and the intronic CpG-islands of SEMA3B with tumor stage and grade have been revealed for SCC, ADC and ccRCC. The association between the decrease of the SEMA3B mRNA level and hypermethylation of the promoter and the intronic CpG-islands has been estimated in renal primary tumors (P < 0.01). Using qPCR, we observed on the average 10- and 14-fold decrease of the SEMA3B mRNA level in SCC and ADC, respectively, and a 4-fold decrease in ccRCC. The frequency of this effect was high in both lung (92-95%) and renal (84%) tumor samples. Moreover, we showed a clear difference (P < 0.05) of the SEMA3B relative mRNA levels in ADC with and without lymph node metastases. We conclude that aberrant expression and methylation of SEMA3B could be suggested as markers of lung and renal cancer progression.
Transcriptomic Analysis of Metabolic Pathways in Milkfish That Respond to Salinity and Temperature Changes

Milkfish (Chanos chanos), an important marine aquaculture species in southern Taiwan, show considerable euryhalinity but have low tolerance to sudden drops in water temperatures in winter. Here, we used high throughput next-generation sequencing (NGS) to identify molecular and biological processes involved in the responses to environmental changes. Preliminary tests revealed that seawater (SW)-acclimated milkfish tolerated lower temperatures than the fresh water (FW)-acclimated group. Although FW- and SW-acclimated milkfish have different levels of tolerance for hypothermal stress, to date, the molecular physiological basis of this difference has not been elucidated. Here, we performed a next-generation sequence analysis of mRNAs from four groups of milkfish. We obtained 29669 unigenes with an average length of approximately 1936 base pairs. Gene ontology (GO) analysis was performed after gene annotation. A large number of genes for molecular regulation were identified through a transcriptomic comparison in a KEGG analysis. Basal metabolic pathways involved in hypothermal tolerance, such as glycolysis, fatty acid metabolism, amino acid catabolism and oxidative phosphorylation, were analyzed using PathVisio and Cytoscape software. Our results indicate that in response to hypothermal stress, genes for oxidative phosphorylation, e.g., succinate dehydrogenase, were more highly up-regulated in SW than FW fish. Moreover, SW and FW milkfish used different strategies when exposed to hypothermal stress: SW milkfish up-regulated oxidative phosphorylation and catabolism genes to produce more energy budget, whereas FW milkfish down-regulated genes related to basal metabolism to reduce energy loss.
Cassandra – A Decentralized Structured Storage System

Cassandra is a distributed database bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model. It is highly scalable both in terms of storage volume and request throughput while not being subject to any single point of failure. This paper presents an architectural overview of Cassandra and also discusses how its design is founded in fundamental principles of distributed systems. Some practical applications that use Cassandra are also listed. This paper also presents why Cassandra may not be a good choice for some applications by highlighting its limitations.
Complexity measurement metric for innovation implementation and product management

This paper derives a metric for the complexity measurement in network industries (e.g., telecommunication) by adapting a well-established method from the manufacturing industry. This metric consists of four dimensions: multiplicity, variety, interaction and dynamics, which have been further objectified by industry specific indicators. After having validated the dimensions and their interplay with industry experts from the telecommunication sector, 47 communication service providers (CSPs) have been interviewed worldwide, which reflects nearly the whole spectrum of CSPs in terms of size, region, product range and degree of state regulation. Based on the results of a cluster analysis three complexity groups with specific ranges in each complexity dimension have been identified. By assuming a complexity group depending configuration need for the innovation and product management, the authors prove the practical relevance of the metric by answering how appropriate design elements can be chosen according to the company’s complexity level.
Bacillus subtilis protein interaction network analysis

Identifying functionally important proteins that are essential to the survival of a bacterial cell is of considerable interest in the development of new antimicrobial agents. Recent studies have shown that functionally important components in protein interaction networks may also be structurally important. We studied the protein interaction network of Bacillus subtilis to identify structurally essential proteins. Fifty-four percent of the structurally essential proteins identified by our methods were encoded by functionally essential genes.
RADIATION PROPERTIES ENHANCEMENT OF TRIANGULAR PATCH MICROSTRIP ANTENNA ARRAY USING HEXAGONAL DEFECTED GROUND STRUCTURE

This paper presents a hexagonal shape defected ground structure (DGS) implemented on two element triangular patch microstrip antenna array. The radiation performance of the antenna is characterized by varying the geometry and dimension of the DGS and also by locating the DGS at specific position which were simulated. Simulation and measurement results have verified that the antenna with DGS had improved the antenna without DGS. Measurement results of the hexagonal DGS have axial ratio bandwidth enhancement of 10 MHz, return loss improvement of 35%, mutual coupling reduction of 3 dB and gain enhancement of 1 dB.
CO investigation of z = 0.4–1.5 galaxies

We report on the results of an IRAM-30 m search for CO emission lines in three galaxies at intermediate redshifts. The idea was to investigate the molecular content of galaxies that are bright in the infrared at $z=0.4{-}1.5$, a redshift desert for molecular line studies because poorly investigated as yet. We integrated 8-10 h per source and did not succeed in detecting any of the sources. From our upper limits, we were able to constrain the molecular gas content in these systems to less than 4 to 8 $\times$ $10^9~M_\odot$, assuming a CO-to-H 2 conversion factor ($\alpha=0.8~M_\odot$/(K km s -1 pc 2 )). We stress the current difficulty of selecting sources with a detectable molecular content, a problem that will be faced by the ALMA First Science projects.
Life Event Perception: A Structural Equation Modeling Approach To The Antecedents Of The Life Stress Response

It has been often argued that life events have an impact on our physical and psychological well-being. In general, research supports this connection between life events and general health, though some argue that simply experiencing life events has a measurable and predictable impact our health, while others contend that this effect is mediated by the appraisal process. Further, research has identified a number of different factors (hypothetically stratified into pre-existing beliefs, external resources and demands, and behavioral activation and coping strategies) that may influence appraisal and general health. The current study attempts to integrate these findings by testing structural models of the relationship between life events, life stress, and general health while considering the appraisal process and other potential moderators of appraisal and general health. University students (N=204) were tested using 17 assessment measures representing 7 latent constructs of Life Events, Life Stress, Appraisal, General Health, Beliefs, External, and Activation. Results of the measurement models required model respecification to combine Appraisal and Beliefs into one construct and External and Activation into another construct, resulting in a five-factor hypothetical structural model. The resulting empirical structural model is a partially-mediated model that suggests that appraisal and pre-existing beliefs influence the relationship between life events and life stress, and that life events significantly impact measured life stress. The empirical model
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension

Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corpus, which is a time-consuming and costly process. On the other hand, unlabeled data is abundant and cheap to collect. In this paper, we propose a novel semi-supervised method for discourse relation classification based on the analysis of co-occurring features in unlabeled data, which is then taken into account for extending the feature vectors given to a classifier. Our experimental results on the RST Discourse Tree-bank corpus and Penn Discourse Treebank indicate that the proposed method brings a significant improvement in classification accuracy and macro-average F-score when small training datasets are used. For instance, with training sets of c.a. 1000 labeled instances, the proposed method brings improvements in accuracy and macro-average F-score up to 50% compared to a baseline classifier. We believe that the proposed method is a first step towards detecting low-occurrence relations, which is useful for domains with a lack of annotated data.
Enhancement of mammographic images for detection of microcalcifications

A novel approach to image enhancement of digital mammography images is introduced, for more accurate detection of microcalcification clusters. In original mammographic images obtained by X-ray radiography, most of the information is hidden to the human observer. The method is based on redundant discrete wavelet transform due to its good properties: shift invariance and numeric robustness. The procedure consists of three steps: low-frequency tissue density component removal, noise filtering, and microcalcification enhancement. The experimental results have shown good properties of the proposed method.
Distributional Semantic Models

Distributional semantic models (DSM) -also known as "word space" or "distributional similarity" models -are based on the assumption that the meaning of a word can (at least to a certain extent) be inferred from its usage, i.e. its distribution in text. Therefore, these models dynamically build semantic representations -in the form of highdimensional vector spaces -through a statistical analysis of the contexts in which words occur. DSMs are a promising technique for solving the lexical acquisition bottleneck by unsupervised learning, and their distributed representation provides a cognitively plausible, robust and flexible architecture for the organisation and processing of semantic information.
Techniques for Efficient Resource Management for Context-Sensitive Mobile Applications

Context-sensitive mobile applications require a certain amount of flexibility due to the fact that they have to provide services for many different situations. The limited resources available make resource management a major challenge in such applications. In this paper, we present different techniques for the efficient use of resources of mobile devices. These techniques support the development of adaptable and flexible context-sensitive applications.
Arabic Alphabet and Numbers Sign Language Recognition

This paper introduces an Arabic Alphabet and Numbers Sign Language Recognition (ArANSLR). It facilitates the communication between the deaf and normal people by recognizing the alphabet and numbers signs of Arabic sign language to text or speech. To achieve this target, the system able to visually recognize gestures from hand image input. The proposed algorithm uses hand geometry and the different shape of a hand in each sign for classifying letters shape by using Hidden Markov Model (HMM). Experiments on real-world datasets showed that the proposed algorithm for Arabic alphabet and numbers sign language recognition is suitability and reliability compared with other competitive algorithms. The experiment results show that the increasing of the gesture recognition rate depends on the increasing of the number of zones by dividing the rectangle surrounding the hand.
DO SELECTED VARIABLES SIGNIFICANTLY PREDICT AND EXPLAIN STUDENT HANDS-ON PERFORMANCE AND THEORY EXAM SCORES IN AN INTRODUCTORY INFORMATION SYSTEMS COURSE?

A focused review of the literature revealed few studies exploring student performance in information systems courses. Thus, this study sought to build upon this limited number of studies and explore the predictive and explanatory power of selected variables on student hands-on performance and theory exam scores in an introductory information systems course. Findings of the study indicate that the variables college GPA, computer liking, and computer systems test score were significant predictor and explanatory variables of student hands-on performance exam scores. By comparison, the variables college GPA, computer systems test score, and perceived computer confidence were found to be significant predictor and explanatory variables of student theory exam scores. Implications for instructional practice are offered.