Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncovering microbial inter-domain interactions in complex communities

Interactions between unicellular eukaryotes and bacteria are difficult to characterize in the environment owing to their large number and inherently microscopic scale. Although particular co-occurrences can be recovered through targeted approaches, e.g. single-cell sequencing or fluorescence in situ hybridization, the vast majority of the interactions remain unseen. Here, we discuss Emulsion, Paired Isolation and Concatenation polymerase chain reaction (epicPCR) as a tool to uncover these interactions in very high throughput. Originally developed for taxonomy-to-function linkage in bacterial communities, epicPCR has the potential to recover the complete interaction network in a given environment at single-cell resolution. This approach relies on the encapsulation of protistan single cells in emulsion droplets that can subsequently be gelified into beads. In this way, encapsulated cells can be exposed to lysis reagents and further phylogenetic paired marker amplification. A bacterium that physically co-occurs with the eukaryote will be jointly trapped, and the amplification will generate a concatenated PCR product containing physically coupled taxonomic markers from both partners, creating a link. Further amplification and sequencing enable the construction of an association pattern with statistically verified physical co-occurrences. Here, we discuss the potential, challenges and limitations of epicPCR. We argue that the microscopic scale at which epicPCR operates, the high throughput it delivers and its exploratory nature make it an unparalleled approach to unravel associations between microbes directly from environmental samples. This article is part of a discussion meeting issue ‘Single cell ecology’.
Realizing the potential of full-length transcriptome sequencing

Long-read sequencing holds great potential for transcriptome analysis because it offers researchers an affordable method to annotate the transcriptomes of non-model organisms. This, in turn, will greatly benefit future work on less-researched organisms like unicellular eukaryotes that cannot rely on large consortia to generate these transcriptome annotations. However, to realize this potential, several remaining molecular and computational challenges will have to be overcome. In this review, we have outlined the limitations of short-read sequencing technology and how long-read sequencing technology overcomes these limitations. We have also highlighted the unique challenges still present for long-read sequencing technology and provided some suggestions on how to overcome these challenges going forward. This article is part of a discussion meeting issue ‘Single cell ecology’.
Evaluating the user experience in interactive installations: a case study

Currently, digital technologies are present in many areas of our lives and are used for various purposes. The ubiquitous technology landscape through ubiquitous and pervasive technologies has brought new forms of interaction. In this context, Human-Computer Interaction (HCI) community has been directing efforts towards its methods. Among the challenges are the types of evaluations commonly performed to improve the quality of systems. In this work, we explored different methods to evaluate the user experience with nine interactive installations developed in a Human-Computer Interaction discipline project. The User Experience evaluation was made using AttrakDiff, which seeks to measure hedonic, pragmatic, and attractiveness qualities in an interaction. The second method was a combination of the Pleasure Framework (its thirteen categories of pleasure) and the Self-Assessment Manikin (SAM) in its Pleasure dimension. The choice of methods was given by the nature of the interactive installations, equally valuating pragmatic qualities as well as hedonic ones. The results show that triangulation approaches, such as the used in this work, were effective because they brought qualitative aspects of the experience, considering both pragmatic and hedonic aspects of the interaction. Particularly in our case study, artifacts with high hedonic qualities obtained good ratings in the pleasure categories.
Congestion Control by Deviation Routing in Electromagnetic Nanonetworks

Pulse-based wireless nanonetworks differ in many ways from traditional wireless networks. This paper investigates congestion in multi hop nanonetworks, which do not behave as usual due to the specifics of the channel and the physical layer. Most protocols and network models assume that each node can listen to all of the traffic sent on their channel. In wireless nanonetworks, the capacity (in the order of Tb/s) of the shared channel is well beyond the processing capability of an individual node. Consequently, congestion arises from the limited buffers of individual nodes on the path instead of limited channel bandwidth. After defining congestion in this context, we propose a solution suitable to large, wireless nanonetworks. Instead of decreasing the sending rate to reduce overall traffic and congestion, we use the SLR routing protocol to find less saturated routes. Our evaluation demonstrates the effectiveness of this solution and shows that the throughput can be preserved with moderate activity overhead and latency cost.
Analyzing Destination Attributes Under Fuzzy Environment: A Case Study in Eskişehir

Given the understanding that destination attributes will often provide access to deep rooted knowledge repositories as well as offer historic facts, for a given tourist destination, it is vital to mention that there still is insufficient research being undertaken, conceptual or empirical, on the subject. Therefore, it is believed more research effort is required to further develop and increase knowledge on this subject matter. This study being carried out is in a bid to contribute towards the continued development of this body of knowledge and to also, increase domain expertise in this field. Within this study, there were two main objectives. First, was the ranking of Eskişehir’s - one of Turkey’s well-known cultural destinations - destination attributes in terms of its relative importance, by making use of tourism experts’ opinions. A fuzzy ranking methodology was adopted to help achieve this output for the study. Recognizing there are several fuzzy ranking approaches covered in our literature review, the choice made was to adopt the four most commonly used methodologies for the study. Hence, the second objective of this study was to test for statistically significant differences, between output results from all four fuzzy ranking methodologies adopted. This study is equally important because it contributes to the body of knowledge exploring the adoption and use of fuzzy ranking, in the evaluation of destination attributes. Consequently, results from this research will offer a guide to other researchers planning to apply fuzzy ranking to similar studies.
Using Summarization to Optimize Text Classification

This study demonstrates the impact of the summary on document classification. The document used is 100 background thesis problems, formatted. txt. Each document will be through preprocessing (case folding, splitting sentence, splitting word, filtering, stop word removal and TF-IDF). Then the document is summarized using the method of extraction. Then all the documents are classified using the FKNNC method. The results of this study were obtained by compiling the classification process to be faster ie for 5 minutes, this is due to the reduced extraction features used. Therefore, the summary can be used to reduce the features in the classification.
The moderator Rôle of family support between depression and suicidal ideation: discrepancy between male and female military population in Taiwan

Objectives: In this study, the authors intended to study the moderator rôle of family support (FS) between depression and suicidal ideation (SI) as well as between the mediation effects of the following three components of the interpersonal theory of suicide – thwarted belongingness, perceived burdensomeness, and capacity for suicide among the military population. sMethods: We enrolled 845 military active-duty personnel (male: female = 679: 166) who attended our mental health education series from 2017 to 2018 in Taiwan. The participants were asked to complete self-administrated copies of the Interpersonal Needs Questionnaire, the Acquired Capability for Suicide Scale, the Beck Depression Inventory, the Columbia-Suicide Severity Rating Scale for SI, and the family Adaptation, Partnership, Growth, Affection, and Resolve scale for FS. After comparing baseline characteristics between genders, we did moderated mediation linear analysis, to clarify the moderation effects of FS on the relationship between depression and SI as well as the possible mediation in the relationship. Results: In general, FS plays a protective moderator rôle in the depression → SI (Dep - SI) path (p < 0.05). In male samples, perceived burdensomeness was significantly mediated the effect of depression on SI (p < 0.05). But FS failed to reach a significant level for moderating the medication effect of perceived burdensomeness on the Dep–SI pathway (p > 0.05). On the other hand, in female samples, perceived burdensomeness failed to significantly mediate the effect of depression on suicidal ideation (p > 0.05), but FS significantly and negatively moderated the effect of depression on perceived burdensomeness (p < 0.05). Otherwise, FS showed negative moderation effect for the effect of depression on capacity for suicide in the male samples (p < 0.05) although capacity for suicide failed to become a statistically significant mediator in the Dep–SI path (p > 0.05). Conclusion: In this study, we found that, among military population, a protective moderation effect of FS can reduce the effect of depression on SI and different mechanisms between sexes. We suggest that programs improving FS could be another consideration for military suicidal prevention.
An Authentic Self: Big Data and Passive Digital Footprints

The ability to allow users to create online communities of interest and to share a variety of personal information, collectively referred to as social media, is gradually being built into an expanding range of applications. Some of these applications, such as computer operating systems, were not originally intended to collect information from the user. Thus, users may not be aware that their digital information is being collected. Devices such as smart televisions, smart cars, and even smart grids, are now collecting massive quantities of user data without the user’s knowledge. Users of social media, and the internet in general, leave fragments of their activities and intentions behind them across an increasing range of technologies. These fragments collectively and passively create a hidden identity built up from metadata of which the user is mostly unaware. Given that the user builds this hidden identity during the normal course of their day, without editing elements that the user may not wish to share with others, might the passive digital footprint more accurately reveal the individual's genuine or authentic self than the individual realises? We propose that an aggregated, passively collected digital portrait of a user's unconscious but connected activities may reveal a more genuine view of that person's self than would be deduced from sources over which the user has conscious control. This more accurate and potentially revealing portrait of the individual requires a review of how privacy has been classically defined in both legal as well as ethical constructs.
NDN-ABS: Attribute-Based Signature Scheme for Named Data Networking

The Named Data Networking architecture mandates cryptographic signatures of packets at the network layer. Traditional RSA and ECDSA public key signatures require obtaining signer's NDN certificate (and, if needed, the next-level certificates of the trust chain) to validate the signatures. This potentially creates two problems. First, the communication channels must be active in order to retrieve the certificates, which is not always the case in disruptive and ad hoc environments. Second, the certificate identifies the individual producer and thus producer anonymity cannot be guaranteed if necessary. In this paper, we present NDN-ABS, an alternative NDN signatures design based on the attribute-based signatures, to addresses both these problems. With NDN-ABS, data packets can be verified without the need for any network retrieval (provided the trust anchor is pre-configured) and attributes can be designed to only identify application-defined high-level producer anonymity sets, thus ensuring individual producer's anonymity. The paper uses an illustrative smart-campus environment to define and evaluate the design and highlight how the NDN trust schema can manage the validity of NDN-ABS signatures. The paper also discusses performance limitations of ABS and potential ways they can be overcome in a production environment.
Evaluating a voice-based interaction: a qualitative analysis

Natural User Interface provides the possibility of interaction with software through direct actions of human body, such as gesture and voice. In the case of voice, it is possible for the user to interact with the system quickly and directly, making the interaction simple and thus providing accessibility. Several studies were conducted with voice as a form of interaction between the user and system. Nevertheless, these studies are generally analyzed from a quantitative perspective and few perform a detailed qualitative analysis. The goal of this paper was to evaluate qualitatively a exploratory study with voice-based interaction. For this, two steps of the Grounded Theory (GT) method were used to obtain solid results. From these results, guidelines were proposed for the creation of digital text by voice so that possible users have this possibility of interaction when they write their texts.
Analysis of dynamic code updating in Android with security perspective

Attackers have been searching for security vulnerabilities to exploit in Android applications. Such security vulnerabilities include Android applications that could load code at runtime which helps attackers avoid detection by static analysis tools. In this study, an extensive analysis is conducted in order to see how attackers employ updating techniques to exploit such vulnerabilities and to assess the security risks of applications in the marketplace using these techniques. A comprehensive analysis was carried out on nearly 30,000 applications collected from three different Android markets and two malware datasets. Static, dynamic and permission-based analyses were employed in order to monitor malicious activities in such applications, and new malicious applications using updating techniques were discovered in Google Play. The results show that applications employing code updating techniques are on the rise. It is believed that this is the first study of its kind to monitor updating behaviours of applications during their execution. This analysis allows us to deeply analyse suspicious applications and thereby develop better security solutions.
Immersed in Fire: The Use of Virtual Reality as an Attitude Assessor and Boundary Object in Wildland Fire Management

Follow this and additional works at: https://digitalcommons.library. umaine.edu/etd Part of the Communication Technology and New Media Commons, Forest Management Commons, Other Forestry and Forest Sciences Commons, Social Influence and Political Communication Commons, Social Psychology and Interaction Commons, Sustainability Commons, Theory, Knowledge and Science Commons, and the Visual Studies Commons
Multi Sensor based Approach for Road Region Extraction for Autonomous Vehicles

Automatic road region extraction is an important component of intelligent and driverless vehicles towards providing smooth navigation. This paper presents a novel method of extracting road region using LiDAR and camera in coherence. The ground region is extracted from LiDAR while camera also gives input on the current scene in parallel. The data obtained from LiDAR and camera is mapped using trigonometric equations. A patch from the camera data is extracted and pixel values of the patch are sent to Gaussian Mixture Model-Expectation Maximization (GMM-EM) algorithm for training at periodic intervals. Based on this training, a drivable region is identified in every frame of the camera input. Thus, obtained drivable road region is further processed and is used in decision-making during navigation. The proposed system works efficiently on different kinds of roads with different lighting conditions and gives a good estimation of the drivable road region in presence of objects or obstacles.
Design of a Simplified Wireless Sensor Network Node based on MQTT Protocol

MQTT protocol is a publish/subscribe message protocol based on TCP/IP protocol. It has the characteristics of low power consumption, scalability, openness and simplicity. HTTP protocol is an open and low-cost request/reply message protocol based on TCP/IP protocol. It is the main protocol of Internet communication, but it is not suitable for the environment of computing, processing and bandwidth limited. In this paper, a simplified wireless sensor network node was designed based on MQTT protocol. The node was designed to use the Arduino development environment and use the WiFi for networking. It has the characteristics of simple structure, low power consumption and so on. The design can be widely used in smart home, environmental monitoring and medical applications, and is the main contents of the Internet of things (IoT).
Are cannabinoids effective for treatment of pain in patients with active cancer

Cannabinoids have been proposed for the treatment of patients with cancer pain, especially if standard treatment does not control symptoms. Using Epistemonikos database, which is maintained by searching 30 databases, we identified nine systematic reviews including seven trials that answer the question of interest, of which six are randomized trials. We performed a meta-analysis and generated a summary of findings table using the GRADE approach. We concluded it is unclear whether cannabinoids decrease pain and improve quality of life in patients with refractory cancer pain because the certainty of the evidence is very low, and it probably increases adverse effects substantially.
Comparison of robot trajectory tracking efficiency using various nonlinear control methods

The Denavit-Hartenberg algorithm and the Lagrange-Euler method are used to derive realistic kinematics and dynamic models of a three-axis electric driven articulated planar robot with viscous, dynamic and static frictions. These robot models are further used for testing the following presented nonlinear robot control methods: fuzzy control, variable-structure control and model-reference variable-structure control. In the fuzzy-logic control method seven fuzzy sets are defined for two input variables. Triangular input membership functions and the 7x7 fuzzy rule table are chosen. The fuzzy controller output value is calculated according to the centre of gravity principle. The same fuzzy control algorithm is used in all robot servo control loops with a proper scaling of the linguistic variables. To eliminate the chattering of the variable-structure control signal and to reduce energy consumption, sign function in the original variable-structure control law is replaced with the following functions: a continuous, saturation and exponential function, all of them with a very thin boundary layer. The same modifications are also made in the original model-reference variable-structure control method. In all presented control methods controller parameters are chosen according to the principle of maximal allowed tracking error and a minimum of energy consumption. These control methods are tested by computer simulations in C programming language in the case of moving the tool of the chosen robot arm. The simulation results proved similar efficiencies of all mentioned modified nonlinear robot control methods, although modified variablestructure control algorithms are the most suitable because of their simplicity and lower number of controller parameters.
Modeling Intraindividual Variability in Three-Level Multilevel Models

The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.
Limiting Bias from Test-Control Interference in Online Marketplace Experiments

In an A/B test, the typical objective is to measure the total average treatment effect (TATE), which measures the difference between the average outcome if all users were treated and the average outcome if all users were untreated. However, a simple difference-in-means estimator will give a biased estimate of the TATE when outcomes of control units depend on the outcomes of treatment units, an issue we refer to as test-control interference. Using a simulation built on top of data from Airbnb, this paper considers the use of methods from the network interference literature for online marketplace experimentation. We model the marketplace as a network in which an edge exists between two sellers if their goods substitute for one another. We then simulate seller outcomes, specifically considering a "status quo" context and "treatment" context that forces all sellers to lower their prices. We use the same simulation framework to approximate TATE distributions produced by using blocked graph cluster randomization, exposure modeling, and the Hajek estimator for the difference in means. We find that while blocked graph cluster randomization reduces the bias of the naive difference-in-means estimator by as much as 62%, it also significantly increases the variance of the estimator. On the other hand, the use of more sophisticated estimators produces mixed results. While some provide (small) additional reductions in bias and small reductions in variance, others lead to increased bias and variance. Overall, our results suggest that experiment design and analysis techniques from the network experimentation literature are promising tools for reducing bias due to test-control interference in marketplace experiments.
Contagion.

It is that time of year again - the time of sudden, wet sneezes and explosive, phlegmy coughs. It is the season we commuters dread, when every sticky handrail fills the heart with fear and our eyes dart from seat to seat on the lookout for inflamed noses and watery eyes.