Miracle-dz/UniFAR-FTUs huggingface dataset:
Pigment and Virulence Deficiencies Associated with Mutations in the <italic toggle='yes'>aroE</italic> Gene of <italic toggle='yes'>Xanthomonas oryzae</italic>pv. oryzae

Xanthomonadins are yellow, membrane-bound pigments produced by members of the genus Xanthomonas. We identified an ethyl methanesulfonate-induced Xanthomonas oryzae pv. oryzae mutant (BXO65) that is deficient for xanthomonadin production and virulence on rice, as well as auxotrophic for aromatic amino acids (Pig Vir Aro). Reversion analysis indicated that these multiple phenotypes are due to a single mutation. A genomic library of the wild-type strain was used to isolate a 7.0-kb clone that complements BXO65. By transposon mutagenesis, marker exchange, sequence analysis, and subcloning, the complementing activity was localized to a 849-bp open reading frame (ORF). This ORF is homologous to the aroE gene, which encodes shikimate dehydrogenase in various bacterial species. Shikimate dehydrogenase activity was present in the wild-type strain and the mutant with the complementing clone, whereas no activity was found in BXO65. This clone also complemented an Escherichia coli aroE mutant for prototrophy, indicating that aroE is functionally conserved in X. oryzae pv. oryzae and E. coli. The nucleotide sequence of the 2.9-kb region containing aroE revealed that a putative DNA helicase gene is located adjacent to aroE. Our results indicate that aroE is required for normal levels of virulence and xanthomonadin production in X. oryzae pv. oryzae.
Read the Room, Robot! Exploring Audiovisual Methods to Improve the Effectiveness of Robotic Comedians

—Social robots with the ability to read the room and work the crowd hold potential for more effective and engaging interactions with people, but such human performer-inspired abilities for robots are currently limited. We propose that audiovisual data and comedian-inspired decision-making can enhance the performance of social robots in settings from live performance to healthcare. The present paper describes a preliminary robotic system for comedy performance, which includes integration with OpenFace facial behavior analysis software for real-time detection of Facial Action Units and gaze information. In parallel to the robotic system creation and initial validation, we are planning to survey human comedy performers to learn more about the audience cues they use to assess joke success and decide on performance adaptations. Preliminary results show promise for OpenFace to aid with the proposed real-time recognition, and future steps will more thoroughly assess proposed behavior recognition models and robot performance adaptation approaches. The products of this work can inform social roboticists who wish to create more compelling and entertaining systems.
SVAR Identification From Higher Moments: Has the Simultaneous Causality Problem Been Solved?

Two recent strands of the literature on Structural Vector Autoregressions (SVARs) use higher moments for identification. One of them exploits independence and non-Gaussianity of the shocks; the other, stochastic volatility (heteroskedasticity). These approaches achieve point identification without imposing exclusion or sign restrictions. We review this work critically, and contrast its goals with the separate research program that has pushed for macroeconometrics to rely more heavily on credible economic restrictions and institutional knowledge, as is the standard in microeconometric policy evaluation. Identification based on higher moments imposes substantively stronger assumptions on the shock process than standard secondorder SVAR identification methods do. We recommend that these assumptions be tested in applied work. Even when the assumptions are not rejected, inference based on higher moments necessarily demands more from a finite sample than standard approaches do. Thus, in our view, weak identification issues should be given high priority by applied users.
Detecting Ephemeral Optical Events with OpTel

Degradation or failure events in optical backbone networks affect the service level agreements for cloud services. It is critical to detect and troubleshoot these events promptly to minimize their impact. Existing telemetry systems rely on arcane tools (e.g., SNMP) and vendor-speciﬁc controllers to collect optical data, which affects both the ﬂexibility and scale of these systems. As a result, they fail to collect the required data on time to detect and troubleshoot degradation or failure events in a timely fashion. This paper presents the design and implementation of OpTel, an optical telemetry system that uses a centralized vendor-agnostic controller to collect optical data in a streaming fashion. More speciﬁcally, it offers ﬂexible vendor-agnostic interfaces between the optical devices and the controller and ofﬂoads data-management tasks (e.g., creating a queryable database) from the devices to the controller. As a result, OpTel enables the collection of ﬁne-grained optical telemetry data at the one-second granularity. It has been running in Tencent’s optical backbone network for the past six months. The ﬁne-grained data collection enables the detection of short-lived events (i.e., ephemeral events). Compared to existing telemetry systems, OpTel accurately detects 2 × more optical events. It also enables troubleshooting of these optical events in a few seconds, which is orders of magnitude faster than the state-of-the-art.
Efﬁcient Learning of Socially Aware Robot Approaching Behavior Toward Groups via Meta-Reinforcement Learning

—Despite the recent rapid advancement of applying reinforcement learning in social robotics, the current state-of-the-art algorithms are still not able to adapt quickly when facing a similar but new social scenario. In this study, we examine meta-reinforcement learning (Meta-RL) methods in a task where a robot needs to learn to approach a group of human agents. For the robot to learn socially aware behavior quickly and effectively in multiple similar but different robot approaching scenarios, we incorporate proximal policy optimization (PPO) with the model-agnostic meta-learning frameworks, i.e., MAML and Reptile, in the training process. Our results show that the Meta-RL methods are feasible to be adopted in learning robot approaching behavior toward groups and they outperform the baseline PPO algorithm (train from scratch), measured by accumulated reward and time.
Ion Distributions in Water/Graphene Interface: A Molecular Dynamics Study

Classical Molecular Dynamics (MD) with a non-polarizable force field is used to quantify the ion size effect on structure and dynamics of the confined electrolyte solution by considering the series of sodium halides (NaX with X = = F, Cl, Br, and I). Ions and water transport were simulated through a rigid and neutral atomistic carbon wall (graphene). The results showed that the solid surface has a major effect on the ion distribution in nano-aqueous solutions near interfaces. Cl, Br, and I tend to be repelled from the regions where the density of water is high, while F was found to be significantly solvated by water. Due to confinement, the dynamical properties of the electrolyte solution were also observed on the anions and cations pairing through determining the self-diffusion coefficient.
FINITE-ELEMENT ANALYSIS OF STRENGTHENING THE SUBGRADE ON THE BASIS OF BORING AND MIXING TECHNOLOGY

One of the effective techniques to strengthen the subgrade is boring and mixing technology, which is based on the immersion of vertical elements – piles into the subgrade. This method of strengthening significantly affects the stress state of the track superstructure. Two options of the placement of strengthening elements are examined in this paper. To determine the influence of position of strengthening elements on the stress state of the track superstructure, appropriate finite-element models were created. The models fully reflect the geometric and deformation characteristics of a real subgrade, which is strengthened by piles. The calculated stress state of the track superstructure is shown and analyzed in this paper. The main contribution of the paper lies in optimization of the geometric parameters of the technology to reduce the stress state of the "track superstructure–subgrade–soil basement" system. The results show that the location of piles near the rails is more effective than the location of piles near the ballast section.
PREDICTING STUDENTS PERFORMANCE USING PERSONALIZED ANALYTICS

: This paper focuses on predicting student performance using personalized analytics based on educational databases. Predicting student performance becomes more challenging due to the huge amount of databases. We present two different approaches to improving student achievements. Both approaches are validated on one course which was offered to students of the school of computing between the years of 2012 and 2015. The first approach is based on regression algorithms to predict student performance. Regression is a data mining function that predicts a number. The main goal is to find how well a student can perform in the programming language by predicting grades based on their school background and performance in mathematics and English. In the model build (training) process, a regression algorithm estimates the value of the dependent variable as a function of the predictors in the build data based on the independent variables. These relationships between predictors and target are summarized in a model, which can then be applied to a different dataset in which the target values are unknown. The Second approach is to find the error rate of regression algorithms by using root mean square error. The obtained results reveal that the school background also plays a major role in predicting grades. Finally, we can identify the students who are at risk and provide better additional training for the weak students.
Identifying Online Advice-Seekers for Recovering from Opioid Use Disorder

Background: Online communities can provide social support for those recovering from opioid use disorder. However, advice-seekers on these platforms risk exposure to uncurated medical advice, potentially harming their health or recovery efforts. The objective of this analysis is to combine text annotation, social network analysis, and statistical modeling to identify advice-seekers on online social media for buprenorphine-naloxone use and study their characteristics. Methods: We collected 5,258 posts and their comments from Reddit between 2014 and 2019. Among 202 posts which met our inclusion criteria, we annotated each post to determine which were advice-seeking (n=137) and not advice-seeking (n=65). We also annotated each posting user's medication use stage and quantified their connectedness using social network analysis. In order to analyze the relationship between advice-seeking with a user's social connectivity and medication use stage, we constructed four models which varied in explanatory variables. Results: The stepwise model (containing "total degree" (P=0.002), "using: inducting/tapering" (P<0.001), and "using: other" (P=0.01) as significant explanatory variables) outperformed all other models. We found that users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than users who are well-connected and no longer using the medication, respectively. Importantly, advice-seeking behavior is most accurately predicted using a combination of network characteristics and medication use status, rather than either factor alone. Conclusions: Our findings provide insights for the clinical care of people recovering from opioid use disorder and the nature of online medical advice-seeking overall. Clinicians should be especially attentive (e.g., through frequent follow-up) to patients who are inducting or tapering buprenorphine-naloxone or signal limited social support.
A comparison between anaerobic and aerobic biological treatment for real wastewater containing high concentration of dimethylamine: case study of wastewater from artificial leather production

In this work, a feasibility study into the treatment process of artificial leather wastewater using both activated and anaerobic sludge was performed. The effects of biomass concentration, different feed dilutions as well as the presence of a nutrient medium in both conditions were examined. The results indicated that as the mixed liquor suspended solids were increased from 800 to 3000 mg/L, chemical oxygen demand (COD) removal increased 41% and 10% in aerobic and anaerobic conditions respectively. Adding nutrient medium had no significant effect on COD removal in both conditions. Under aerobic conditions and at a lower hydraulic retention time of 3 d, COD removal was about 99% while in anaerobic conditions and in similar situations maximum COD removal was up to 60% during 7 d. The effects of amendment of two carbon sources (glucose and methanol) were investigated and results indicated that in comparison with methanol, using glucose as the carbon source could lead to higher COD removal, under anaerobic conditions (23%) while it has no significant effect at the aerobic condition. In conclusion, COD removal was higher under aerobic conditions than anaerobic conditions. Furthermore, dimethylamine concentration in treated wastewater under aerobic conditions was below the detected limit of the analyzer (<1 ppb).
Adoption and intention of the usage of shared mobility through Technology Acceptance Models: Systemic analysis of literature through PROKNOW-C

The quick development and popularization of comunication techlonogies has made the modalities associated with shared mobility leverage through internet platforms operating e-hailing services in cities around the whole world. The long-term development of a shared mobility service depends on the continued use of its users. In order to revise the availeable literature about this subjet, the PROKNOW-C was utilized, performing the bibliometric and systemic analysis of the literature. The results lead to the making of a portifolium of 21 articles, highlighting the more relevant authors, journals and keywords. The systemic analysis concluded that: the survey methodology is the most used in articles; while the main constructs that are directly and indirectly linked to the intention to use the service stand out. The results confirm that the theoretical models of technology acceptance are tools that allow the understanding of determinant factors reguarding the intention of usage and continuity of shared mobility. The research made possible to highlight that these models can explain the user's intents, ranking which constructs have greater influence, thus representing an important contribuition to the extension of technology intent models.
Learning Multi-Stage Tasks with One Demonstration via Self-Replay

In this work, we introduce a novel method to learn everyday-like multi-stage tasks from a single human demonstration, without requiring any prior object knowledge. Inspired by the recent Coarse-to-Fine Imitation Learning method, we model imitation learning as a learned object reaching phase followed by an open-loop replay of the demonstrator's actions. We build upon this for multi-stage tasks where, following the human demonstration, the robot can autonomously collect image data for the entire multi-stage task, by reaching the next object in the sequence and then replaying the demonstration, and then repeating in a loop for all stages of the task. We evaluate with real-world experiments on a set of everyday-like multi-stage tasks, which we show that our method can solve from a single demonstration. Videos and supplementary material can be found at https://www.robot-learning.uk/self-replay.
Influence of the ratio of organic solvent on the deposition of graphene oxide by spin-coating

In this work we investigate influence of the organic solvent addition on the deposition of graphene oxide solution by spin-coating. In order to overcome the poor wettability of polyethylene terephthalate substrate by water graphene oxide suspension we made series of multicomponent solution with different n-methylpyrrolidone to water ratio. We successfully showed possibility and good uniformity of graphene oxide films deposited from the multicomponent solution. According to AFM and Raman spectroscopy we achieved good local uniformity in all cases. The most uniform films were made with 2,35 mg/ml GO concentration. We also found that in case of 0,47 and 1,175 mg/ml concentrations we achieved few-layered graphene oxide with film thickness about 3 nm and less.
The effect of Norway rats on coastal waterbirds of the Falkland Islands : a preliminary analysis

The Falkland Islands have been aff ected by anthropogenic-induced habitat modifi cation including introduction of invasive species and grazing by livestock. Introduced Norway rats are known to have a large eff ect on native Falklands passerines but their eff ect on other native birds has not been explored. We investigated the eff ects of several environmental variables, including the presence of Norway rats and chronic grazing by livestock, on an assemblage of 22 species of coastal waterbirds by comparing species richness and relative abundance of birds among 65 rat-infested islands, 29 rateradicated islands and 76 historically rat-free islands. Bird count data from 299 km of coastline were used to estimate relative bird abundance, expressed as the number of individuals per kilometre of coastline for each species. Our study provided three key results. First, coastal waterbird abundance on islands historically without rats was twice as high as that on islands where rats were present. Second, bird abundance on rat-eradicated islands was intermediate between that of historically rat-free and rat-infested islands. Third, habitat modifi cation by grazing appeared to reduce bird abundance in both rat-free and rat-infested habitats. From a conservation perspective, this study suggests that rat eradication programmes in the Falkland Islands are eff ective at restoring coastal waterbird abundance and would be even more so if carried out in conjunction with restoration of native coastal plant communities.
ART AND IMAGE PROCESSING

This paper presents a discussion on the junction between art and engineering, with special reference to image processing. The aim is to highlight areas in image processing where the two disciplines intersect. The historical context of this interaction is provided along with examples of works from artists and engineers. For both the computer artist and engineer, images are central to their work, they use the same platform, the computer, and share a common vocabulary, words such as edge, contour, colour and texture. The paper includes art works and computer vision systems that show how a working knowledge of the other discipline can be beneﬁcial to both the artist and engineer. There is currently no prescribed literature dealing with the overlap between these two disciplines. This paper aims to draw attention to this fact.
The Impact of Different Image Thresholding based Mammogram 1 Image Segmentation-A Review

Images are examined and discretized numerical capacities. The goal of computerized image 7 processing is to enhance the nature of pictorial data and to encourage programmed machine 8 elucidation. A computerized imaging framework ought to have fundamental segments for 9 picture procurement, exceptional equipment for encouraging picture applications, and a 10 tremendous measure of memory for capacity and info/yield gadgets. Picture segmentation is 11 the field broadly scrutinized particularly in numerous restorative applications and still offers 12 different diﬀiculties for the specialists. Segmentation is a critical errand to recognize districts 13 suspicious of tumor in computerized mammograms. Every last picture have distinctive sorts of 14 edges and diverse levels of limits. In picture transforming, the most regularly utilized strategy 15 as a part of extricating articles from a picture is ”thresholding”. Thresholding is a prevalent 16 device for picture segmentation for its straightforwardness, particularly in the fields where 17 ongoing handling is required.
Use of Interactive Computer Model STREAK for Transportation Planning

STREAK, an interactive set of computer programs for transportation planning, is described in both nontechnical and technical terms, and some experience in its use is discussed. The program uses portable desk-top terminals and conventional telephone lines. Outputs on the portable terminal include responsive dialogue (questions and answers), tabular arrays, and data plotted by coordinates for use with overlaid maps. Capabilities of the model include multimodal network development, pathfinding in multimodal networks, travel demand estimation for all modes, travel assignment
Towards providing explanations for robot motion planning

Recent research in AI ethics has put forth explainability as an essential principle for AI algorithms. However, it is still unclear how this is to be implemented in practice for specific classes of algorithms—such as motion planners. In this paper we unpack the concept of explanation in the context of motion planning, introducing a new taxonomy of kinds and purposes of explanations in this context. We focus not only on explanations of failure (previously addressed in motion planning literature) but also on contrastive explanations—which explain why a trajectory A was returned by a planner, instead of a different trajectory B expected by the user. We develop two explainable motion planners, one based on optimization, the other on sampling, which are capable of answering failure and constrastive questions. We use simulation experiments and a user study to motivate a technical and social research agenda.
The Effect of Infrastructure Availability on FDI Inflow in D8 Countries

This paper analyzes the effect of infrastructure availability on FDI inflow in D8 countries (Bangladesh, Indonesia, Iran, Egypt, Nigeria, Malaysia, Pakistan and Turkey). Panel data for the period 1997-2012 has been used and the analysis has been done using the fix and random effect model suggested by Hausman specification test. The study find out positive and significant effect between infrastructure along with other variables like market size, trade openness on FDI inflows, while in case of macroeconomic variable that is exchange rate it has negative but significant effect on FDI inflows.
Association between diabetes and periodontitis : A cross sectional study based on findings from Tromsø 7 study

The 2017 reports published by Diabetesforbundet Norway showed an estimated 378 000 people living with diabetes (28 000 with Type 1 and 350 000 with Type 2) [1]. Mealey et al. (2006) showed that diabetes increases the risk for periodontitis, influenced by inflammatory processes. The formation of inflammatory molecules (e.g. Advanced glycation end products) leads to gingival attachment loss, periodontal pockets, bleeding; and in prolonged situation, it results in alveolar bone defects and subsequent tooth mobility/loss [2]. On the contrary, a study by Kowall et al. (2015) observed that people with pre-diabetes and well-controlled diabetes are not at risk for periodontitis [3]. Due to an insufficient number of studies for diabetes-periodontitis relationship especially in Northern Norway, this cross-sectional study aims to examine the association between diabetes and periodontitis, among those who participated for dental examination of Tromsø 7 study.