Miracle-dz/UniFAR-FTUs huggingface dataset:
reservoirpy: A Simple and Flexible Reservoir Computing Tool in Python

This paper presents reservoirpy , a Python library for Reservoir Computing (RC) models design and training, with a particular focus on Echo State Networks (ESNs). The library contains basic building blocks for a large variety of recurrent neural networks defined within the field of RC, along with both offline and online learning rules. Advanced features of the library enable compositions of RC building blocks to create complex “deep” models, delayed connections between these blocks to convey feedback signals, and empower users to create their own recurrent operators or neuronal connections topology. This tool is solely based on Python standard scientific packages such as numpy and scipy . It improves RC time efficiency with parallelism using joblib package, making it accessible to a large academic or industrial audience even with a low computational budget. Source code, tutorials and examples from the RC literature can be found at https://github.com/reservoirpy/ reservoirpy while documentation can be found at https://reservoirpy.readthedocs.
Potential Role of Promoter in Production Level of Bacillus sphaericus Phenylalanine Dehydrogenase in Escherchia coli Expression System

In order to investigate the Potential role of promoter in production level of phenylalanine dehydrogenase in E. coli expression system this study was made. The L-phenylalanine dehydrogenase gene (pdh ) was isolated from B. sphaericus . The pdh gene was cloned into two expression vectors; pET-23a and pPR37 differing in their promoter, which were T7 and λλλλλ PR respectively. Expression of gene was induced by adding 1 mM (final concentration) of IPTG for vector carrying T7 promoter or by temperature shift from 30 to 42 °C for vector carrying λλλλλ PR. The highest rate of expression was observed in pETpdh/BL21(DE3)plysS construction. The level of expression of other construction was very low. PheDH was purified by Ni-NTA chromatography column. The relative molecular mass of PheDH subunit was about 41KDa by SDS-PAGE 10%. Applying this method for purification the specific activity of enzyme was 705 U/mg protein. The purity and amount of proteins were assessed by SDS-PAGE. Our polyhistidine-tag enzyme can be ideally used for the immobilization on a nickel coated microliter plate surface.
AN IMPROVED DISTANCE AND MASS ESTIMATE FOR SGR A* FROM A MULTISTAR ORBIT ANALYSIS

We present new, more precise measurements of the mass and distance of our Galaxy’s central supermassive black hole, Sgr A*. These results stem from a new analysis that more than doubles the time baseline for astrometry of faint stars orbiting Sgr A*, combining 2 decades of speckle imaging and adaptive optics data. Specifically, we improve our analysis of the speckle images by using information about a star’s orbit from the deep adaptive optics data (2005–2013) to inform the search for the star in the speckle years (1995–2005). When this new analysis technique is combined with the first complete re-reduction of Keck Galactic Center speckle images using speckle holography, we are able to track the short-period star S0-38 (K-band magnitude = 17, orbital period = 19 yr) through the speckle years. We use the kinematic measurements from speckle holography and adaptive optics to estimate the orbits of S0-38 and S0-2 and thereby improve our constraints of the mass (Mbh) and distance (Ro) of Sgr A*: Mbh = (4.02 ± 0.16 ± 0.04) × 106 M⊙ and 7.86 ± 0.14 ± 0.04 kpc. The uncertainties in Mbh and Ro as determined by the combined orbital fit of S0-2 and S0-38 are improved by a factor of 2 and 2.5, respectively, compared to an orbital fit of S0-2 alone and a factor of ∼2.5 compared to previous results from stellar orbits. This analysis also limits the extended dark mass within 0.01 pc to less than 0.13 × 106 M⊙ at 99.7% confidence, a factor of 3 lower compared to prior work.
Challenges for conceptualising EU MOOC for vulnerable learner groups

This exploratory paper picks up elements from the European Commission’s educational vision and philosophy behind Opening up Education, the resulting initiative of the OpenupEd.eu MOOC platform, and takes this as a starting point to look at potential challenges for developing MOOCs that include vulnerable learner groups. In order to align the future conceptualization of MOOCs with the vision and philosophy of Europe, potential tensions of contemporary and future education are listed. The current dichotomy of xMOOC and cMOOC are used to mark some of the unexplored MOOC territory. Practical answers to contemporary, ICT-supported educational challenges are provided as options to fuel the debate. The challenges and options for future online education initiatives are based on insights and ideas of international scholars and researchers reflecting on potential barriers for learners and online education. This paper aims to stimulate discussion of the potential for new educational technologies to ensure social inclusion for virtual and physical vulnerable learner groups.
Phytome: a platform for plant comparative genomics

Phytome is an online comparative genomics resource that can be applied to functional plant genomics, molecular breeding and evolutionary studies. It contains predicted protein sequences, protein family assignments, multiple sequence alignments, phylogenies and functional annotations for proteins from a large, phylogenetically diverse set of plant taxa. Phytome serves as a glue between disparate plant gene databases both by identifying the evolutionary relationships among orthologous and paralogous protein sequences from different species and by enabling cross-references between different versions of the same gene curated independently by different database groups. The web interface enables sophisticated queries on lineage-specific patterns of gene/protein family proliferation and loss. This rich dataset is serving as a platform for the unification of sequence-anchored comparative maps across taxonomic families of plants. The Phytome web interface can be accessed at the following URL: . Batch homology searches and bulk downloads are available upon free registration.
An Object-oriented Spatial and Temporal Bayesian Network for Managing Willows in an American Heritage River Catchment

Willow encroachment into the naturally mixed landscape of vegetation types in the Upper St. Johns River Basin in Florida, USA, impacts upon biodiversity, aesthetic and recreational values. To control the extent of willows and their rate of expansion into other extant wetlands, spatial context is critical to decision making. Modelling the spread of willows requires spatially explicit data on occupancy, an understanding of seed production, dispersal and how the key life-history stages respond to environmental factors and management actions. Nicholson et al. (2012) outlined the architecture of a management tool to integrate GIS spatial data, an external seed dispersal model and a state-transition dynamic Bayesian network (ST-DBN) for modelling the influence of environmental and management factors on temporal changes in willow stages. That paper concentrated on the knowledge engineering and expert elicitation process for the construction and scenario-based evaluation of the prototype ST-DBN. This paper extends that work by using object-oriented techniques to generalise the knowledge organisational structure of the willow ST-DBN and to construct an object-oriented spatial Bayesian network (OOSBN) for modelling the neighbourhood spatial interactions that underlie seed dispersal processes. We present an updated architecture for the management tool together with algorithms for implementing the dispersal OOSBN and for combining all components into an integrated tool.
Does Online Anonymous Market Vendor Reputation Matter?

Reputation is crucial for trust in underground markets such as online anonymous marketplaces (OAMs), where there is little recourse against unscrupulous vendors. These markets rely on eBay-like feedback scores and forum reviews as reputation signals to ensure market safety, driving away dishonest vendors and ﬂagging low-quality or dangerous products. Despite their importance, there has been scant work exploring the correlation (or lack thereof) between reputation signals and vendor success. To ﬁll this gap, we study vendor success from two angles: (i) longevity and (ii) future ﬁnancial success, by studying eight OAMs from 2011 to 2023. We complement market data with social network features extracted from a OAM forum, and by qualitatively coding reputation signals from over 15,000 posts and comments across two subreddits. Using survival analysis techniques and simple Random Forest models, we show that feedback scores (including those imported from other markets) can explain vendors’ longevity, but fail to predict vendor disappearance in the short term. Further, feedback scores are not the main predictors of future ﬁnancial success. Rather, vendors who quickly generate revenue when they start on a market typically end up acquiring the most wealth overall. We show that our models generalize across different markets and time periods spanning over a decade. Our ﬁndings provide empirical insights into early identiﬁcation of potential high-scale vendors, effectiveness of “reputation poisoning” strategies, and how reputation systems could contribute to harm reduction in OAMs. We ﬁnd in particular that, despite their coarseness, existing reputation signals are useful to identify potentially dishonest sellers, and highlight some possible improvements.
Trade Patterns and International Technology Spillovers:Theory and Evidence from Patent Citations

In this paper, we develop a two-country model of monopolistic competition with quality differentiation by extending the model of Melitz and Ottaviano (2008) and examine the relationship between the bilateral trade structure and international technology spillovers. We show that bilateral trade patterns and the extent of technology spillovers will change, depending on the technology gap between two countries. We then test predictions of the model by using bilateral trade data among 44 countries and patent citation data at the U.S., European, and Japanese Patent Offices. We use patent citations as a proxy for spillovers of technological knowledge. Trade patterns are categorized into three types: one-way trade (OWT), horizontal intra-industry trade (HIIT), and vertical intra-industry trade (VIIT). Each of OWT and VIIT is further divided into two subcategories, based on the direction of trade. We find that intra-industry trade plays a significant role in technology spillovers. In particular, HIIT is associated with larger technology spillovers than VIIT, which confirms the predictions of the model.
ScholarWorks@UARK ScholarWorks@UARK

Prospective person memory (PPM) is the process of remembering to perform some action after encountering a target individual, such as identifying and reporting a missing person sighting after viewing a missing person alert (Moore et al., 2021). Research has shown that identification rates generally tend to be low in simulated missing person studies (Lampinen & Moore, 2016b). The purpose of the current research is to determine how to improve missing person recognition rates. This project explores the potential effects of using videos in missing person reports as compared to using static images. We also consider differences between rigid and non-rigid facial movements. The study conformed to a 2 (Format: Video, Static) x 2 (Motion Type: Rigid, Non-Rigid) factorial design. Our hypotheses propose a) the video conditions will outperform the static image conditions, and b) non-rigid movements will yield greater identification accuracy than rigid movements. However, our hypotheses were not supported as our results showed the rigid-static stimulus condition had the best identification performance overall. These findings provide future researchers insight into the process of encoding and recollecting human faces and provide authorities information on the stimuli that is most advantageous to use for real-world missing person cases.
Extraction of grasp-related features by human dual-hand object exploration

We consider the problem of objects exploration for grasping purposes, specifically in cases where vision based methods are not applicable. A novel dual-hand object exploration method is proposed that takes benefits from a human demonstration to enrich knowledge about an object. The user handles an object freely using both hands, without restricting the object pose. A set of grasp-related features obtained during exploration is demonstrated and utilized to generate grasp oriented bounding boxes that are basis for pre-grasp hypothesis. We believe that such exploration done in a natural and user friendly way creates important link between an operator intention and a robot action.
Theoretical and Experimental Analysis of a Rolled-Dipole Antenna for Low-Resolution GPR

In this paper a rolled dipole antenna for low-resolution impulse ground penetrating radar (GPR) is theoretically and experimentally investigated. The antenna has been designed for transmission of monocycle pulses with duration of 5 ns (200 MHz central frequency) suitable for low-resolution GPR applications. The dipole is rolled to considerably reduce its length and resistive loading with the Wu-King profile is applied for suppression of late-time ringing, important for GPR. It is shown theoretically that the antenna radiates the pulse with no late-time ringing. Furthermore, by rolling the wires the antenna length is reduced by a factor of 4 with no evident negative impact on the antenna's characteristics. A shield for the antenna has been designed, constructed and integrated with the antenna. Furthermore, it has been found that a tapered bow tie can be combined with the antenna in such a way that a significant increase in the antenna efficiency is obtained, resulting in a unique hybrid of a dipole and a bow-tie antenna.
Active Convergence of the India‐Burma‐Sunda Plates Revealed by a New Continuous GPS Network

The Rakhine (Arakan)‐Bangladesh megathrust, along which the Indian and Burma plates collide, is assumed by some to be inactive/aseismic due to the lack of notable interplate earthquakes in the modern instrumental catalog. However, geological and historical evidence of the great 1762 Arakan earthquake suggest the megathrust can produce M~8 events that could adversely affect the lives of millions of people in the region. To investigate the seismogenic potential and determine the slip budget of the megathrust, we first need to solve for India‐Burma‐Sunda relative plate motions. We present a new set of 24 GPS velocities (2011–2017) from the Myanmar‐India‐Bangladesh‐Bhutan continuous GPS network. We use the new velocities and those from previously published studies to explore the geometries and slip rates of three major faults (Rakhine‐Bangladesh megathrust, Churachandpur‐Mao Fault, and Sagaing Fault) that accommodate the India‐Burma‐Sunda plate motion. Our results suggest that the three major faults we studied are likely fully coupled; the modern shortening rate across the Burma plate is 12–24 mm/year, while the total dextral shear rate is 25–32 mm/year. The possibly fully coupled shallow megathrust, and splay faults that may sole into it, are geodetically invisible while they are not slipping. However, we can identify the transition from coupling to steady creep on the deeper extension of the megathrust; we use this to show active oblique India‐Burma convergence and to map along‐strike and along‐dip variations in dip‐slip and strike‐slip motion. This implies that the megathrust is currently accumulating strain which will eventually be released in earthquakes.
A study of information retrieval on accumulative social descriptions using the generation features

This paper is concerned with the study of information retrieval (IR) on Accumulative Social Descriptions (ASDs). ASDs refer to Web texts that accumulated by many Web users describing certain Web resources, such as anchor texts, search logs and social annotations. There have been some studies working on leveraging ASDs for improving search performance in both internet and intranet. However, to the best of our knowledge, no prior study has concerned the specific generation features of ASDs, which are the focus point of this paper. Specifically, we consider the generation features from two perspectives, the generation processes and the generated distributions. Further, three probabilistic IR models are derived based on them. The three models are first demonstrated with one toy dataset and then empirically evaluated with two real datasets: an internet dataset consisting of 90,295 Web pages, with 25,845,818 social annotations crawled from Del.icio. us and 31,320,005 pieces of anchor texts crawled through Yahoo! API, and an intranet dataset consisting of 179,835 Web pages with 1,245,522 annotations dumped from the intranet tagging system in IBM, named as Dogear. Extensive experimental results show that the proposed methods, which fully leverage the generation features of ASDs, improve the performance of both internet and intranet search significantly.
Architectural Changes in the TCR:CD3 Complex Induced by MHC:Peptide Ligation1

A hallmark of T cell activation is the ligation-induced down-modulation of the TCR:CD3 complex. However, little is known about the molecular events that drive this process. The CD3 ζ-chain has been shown to play a unique role in regulating the assembly, transport, and cell surface expression of the TCR:CD3 complex. In this study we have investigated the relationship between CD3ζ and the TCRαβCD3εδγ complex after ligation by MHC:peptide complexes. Our results show that there is a significant increase in free surface CD3ζ, which is not associated with the TCR:CD3 complex, after T cell stimulation. This may reflect dissociation of CD3ζ from the TCRαβCD3εδγ complex or transport of intracellular CD3ζ directly to the cell surface. We also show that MHC:peptide ligation also results in exposure of the TCR-associated CD3ζ NH2 terminus, which is ordinarily buried in the complex. These observations appears to be dependent on Src family protein tyrosine kinases, which are known to be critical for efficient T cell activation. These data suggest a mechanism by which ligated TCR may be differentiated from unligated TCR and selectively down-modulated.
Structured Prioritized Sweeping

The structured policy iteration (SPI) algorithm (Boutilier et al., 1995) constructs structured solutions to Markov decision problems (MDPs). It finds the optimal value function by treating all states which have the same value under a particular policy as a single aggregate state. Here we show that this approach can also be applied locally in a structured version of prioritized sweeping, a model-based reinforcement learning algorithm that attempts to focus the learning agent’s limited computational resources on states where the model is most likely to be incorrect. In structured prioritized sweeping we maintain a structured value function and update the values of aggregate states. This increases the scope of local value function changes, and the rate at which they propagate across the state space, which makes learning more efficient, particularly in larger problems.
A Binary Classification Framework for Two-Stage Multiple Kernel Learning

With the advent of kernel methods, automating the task of specifying a suitable kernel has become increasingly important. In this context, the Multiple Kernel Learning (MKL) problem of finding a combination of prespecified base kernels that is suitable for the task at hand has received significant attention from researchers. In this paper we show that Multiple Kernel Learning can be framed as a standard binary classification problem with additional constraints that ensure the positive definiteness of the learned kernel. Framing MKL in this way has the distinct advantage that it makes it easy to leverage the extensive research in binary classification to develop better performing and more scalable MKL algorithms that are conceptually simpler, and, arguably, more accessible to practitioners. Experiments on nine data sets from different domains show that, despite its simplicity, the proposed technique compares favorably with current leading MKL approaches.
Ontology Quality by Detection of Conflicts in Metadata

ontologies continue to be an important component in techniques and applications in semantic technologies. Thus, it is necessary to evaluate their quality. Our focus is the detection of conflicting information (within an ontology) as a criterion to improve the quality of an ontology. We describe different types of conflicts and propose a rule-based approach by which human experts can define conditions that signal a conflict in data. These rules (represented using RuleML) are used to automatically detect conflicts in populated ontologies. We describe a prototype application and evaluate the applicability of this approach.
A model based cable network simulator: development and experimental verification

Determination of the channel is a key to any data communication. Recently, a deterministic method to compute voltage ratios and input impedances of an indoor power line network has been proposed (2005). In our work, we extend this method based on the calculation of multipath reflected waves to the determination of reflection and transmission coefficients in cable networks. To assess the validity of our model, we measure the electrical characteristics of cables, develop a simulator based on the model, and incorporate the measured cable characteristics into the Simulator. We apply the model to a large variety of cable networks, and perform measurements on the same cable networks. An excellent agreement between the model and measurements is shown
cDNA Cloning and Molecular Characterization of Mink SMAD4

The Smad family of proteins have been implicated as major components of the TGF g signalling pathway and are important mediators of its pleiotrophic effects. Here we describe the cloning and characterization of the mink ( Mustela vison ) ortholog of Smad4. Mink Smad4 has a high level of conservation to its human counterpart showing 96% homology at the DNA level and 99% at the amino acid level. This is in agreement with the close homologies seen for the rat and mouse orthologs. In vitro transcription and translation shows the expression of a protein of predicted molecular weight, of identical size to its human counterpart.
A Physical Activity Reference Data-Set Recorded from Older Adults Using Body-Worn Inertial Sensors and Video Technology—The ADAPT Study Data-Set

Physical activity monitoring algorithms are often developed using conditions that do not represent real-life activities, not developed using the target population, or not labelled to a high enough resolution to capture the true detail of human movement. We have designed a semi-structured supervised laboratory-based activity protocol and an unsupervised free-living activity protocol and recorded 20 older adults performing both protocols while wearing up to 12 body-worn sensors. Subjects’ movements were recorded using synchronised cameras (≥25 fps), both deployed in a laboratory environment to capture the in-lab portion of the protocol and a body-worn camera for out-of-lab activities. Video labelling of the subjects’ movements was performed by five raters using 11 different category labels. The overall level of agreement was high (percentage of agreement >90.05%, and Cohen’s Kappa, corrected kappa, Krippendorff’s alpha and Fleiss’ kappa >0.86). A total of 43.92 h of activities were recorded, including 9.52 h of in-lab and 34.41 h of out-of-lab activities. A total of 88.37% and 152.01% of planned transitions were recorded during the in-lab and out-of-lab scenarios, respectively. This study has produced the most detailed dataset to date of inertial sensor data, synchronised with high frame-rate (≥25 fps) video labelled data recorded in a free-living environment from older adults living independently. This dataset is suitable for validation of existing activity classification systems and development of new activity classification algorithms.