Miracle-dz/UniFAR-FTUs huggingface dataset:
Fed-batch Pre-industrial Production and Purification of a Consensus Tetratricopeptide Repeat (CTPR) Scaffold as Container for Fluorescent Proteins (FPs)

White light-emitting diodes (WLEDs) are big news in the field of lighting, however, current production processes are still very expensive or based on unsustainable inorganic metals such as inorganic phosphorus. The EU-funded ARTIBLED project aims to produce low-cost and high-efficiency Bio-hybrid light-emitting diodes (Bio-HLEDs). This can be achieved using artificially synthesized fluorescent proteins linked in biological scaffolds like the packaging to obtain LED for lighting applications containing a biogenic phosphor. This study aims to optimize the protein scaffold CTPR10 production process to obtain a high number of scaffolds with a good purity level for Bio-HLEDs construction. Different fed-batch fermentation procedures were investigated and it was possible to produce more than two times of biomass and intracellular proteins compared to a conventional fed-batch strategy. The improvement in production leads both to the reduction of costs related to the amount of IPTG used and the isolation of a consistent amount of CTPR10 through rapid and highly efficient purification techniques. The realization of this project represents a significant milestone for Europe which will be at the forefront of innovation in the lighting sector.
The State Space Subdivision Filter for SE(3)

Estimating the position and orientation of 3-D objects is a ubiquitous challenge. In our novel filter, the position and orientation of objects are modeled using the Cartesian product of ℝ for the position and a 3-D hyperhemisphere. The latter is used to describe orientations in the form of unit quaternions. The hyperhemisphere is subdivided into equally sized areas. The joint density for the position and orientation is split up into a marginal density for the orientation and a density for the position that is conditioned on the orientation. In our filter, we assume that the function values of the marginal density and the conditional density is the same for all points within that area. By assuming all conditional densities to be Gaussians, efficient formulae can be implemented for the update and prediction steps. The filter is evaluated based on a simulation scenario, for which it showed very high accuracy at low run times.
International Journal of Electrical and Computer Engineering (IJECE)

Received Apr 29, 2021 Revised May 26, 2022 Accepted Jun 25, 2022 Constructing a stabilized route in dynamic topology and decentralized architecture is still an unsolved problem in mobile Ad-hoc networks. There are various research contributions where received signal strength has been used to enhance the routing performance. We reviewed the existing technique and found that adopting the current signal strength-based mechanism is not efficient enough to deal with overhead and energy consumption in mobile Ad-hoc networks (MANETs). The present manuscript introduces a novel routing schema called MROSS or minimizing routing overhead using signal strength (MROSS) that jointly addresses the problems of communication and network lifetime. The outcome of the study was developed using an analytical modeling approach to find MROSS significantly reduces routing overhead and energy consumption in comparison to existing routing techniques in mobile Ad-hoc network.
VET5G: A Virtual End-to-End Testbed for 5G Network Security Experimentation

As 5G networks are gradually rolled out worldwide, it is important to ensure that their network infrastructures are resilient against malicious attacks. This work presents VET5G, a new virtual end-to-end testbed for 5G network security research experiments or training activities such as Capture-The-Flag competitions. The distinguishing features of VET5G include a home-grown 5G core network emulator written in Rust to ensure memory and thread safety, integration of OpenAirInterface’s Radio Access Network emulator and the official Android emulator to achieve full end-to-end 5G network emulation, inclusion of a reference P4 software switch to assist with prototyping of defense mechanisms for 5G data planes, implementation of Python APIs for easy 5G network experimentation, and adoption of JupyterHub to support multi-user experimentation. In our experiments we demonstrate how to use VET5G for two attack scenarios in 5G networks as well as its performance when it is used in a 5G hacking project for a Mobile Systems Security course.
Cognitive Modeling of Semantic Fluency Using Transformers

Can deep language models be explanatory models of human cognition? If so, what are their limits? In order to explore this question, we propose an approach called hyperparameter hypothesization that uses predictive hyperparameter tuning in order to find individuating descriptors of cognitive-behavioral profiles. We take the first step in this approach by predicting human performance in the semantic fluency task (SFT), a well-studied task in cognitive science that has never before been modeled using transformer-based language models (TLMs). In our task setup, we compare several approaches to predicting which word an individual performing SFT will utter next. We report preliminary evidence suggesting that, despite obvious implementational differences in how people and TLMs learn and use language, TLMs can be used to identify individual differences in human fluency task behaviors better than existing computational models, and may offer insights into human memory retrieval strategies -- cognitive process not typically considered to be the kinds of things TLMs can model. Finally, we discuss the implications of this work for cognitive modeling of knowledge representations.
DIY hyperspectral imaging via polarization-induced spectral filters

We propose a novel design for a do-it-yourself hyperspectral imaging system which operates by taking multiple photographs through tunable, polarization-induced, spectral filters. Prior approaches in this do-it-yourself arena achieve hyperspectral imaging by selecting from a discrete set of spectra baked into existing products. In contrast, our approach is capable of generating a continuous family of broadband transmission spectra by simple rotations of stacked polarizers and waveplates. This greatly expands the potential range of representable spectra from a fixed-dimensional to an arbitrary-dimensional space. We analyze the theoretical spectral gamut of our approach and demonstrate its viability for spectral surface reflectance reconstruction both in simulation and with a low-cost physical prototype. Our prototype demonstrates that our approach can achieve comparable quality to prior work at reduced cost, while the new design space holds ample opportunity for increased quality and flexibility with professional manufacturing.
Validity and Reliability Evidence of the Functional Independence Measurement (FIM) for individuals with Neurological Disorders in Greece

Background: The Functional Independence Measurement (FIM) is a valid and reliable instrument of examining the patients’ functional independence (FI) in daily activities. The FIM reliability and validity, to date has not been established by Greek clinicians. The aim of the study therefore was to provide reliability and validity evidence of the FIM in a sample of Greek patients with neurological disorders (ND). Methods: The sample was consisted from inpatients with stroke (N=50) and traumatic brain injury (N=24), who had been admitted to Greek hospitals and rehabilitation centers and healthy individuals (N=33) with corresponding demographic characteristics. Inpatients were evaluated by the lead researcher. Thirty inpatients were evaluated by two researchers to determine the inter-rater reliability. The FIM structural validity was determined by the differences between (i) inpatients and healthy individuals and (ii) inpatients of varying severity. The synchronic validity was determined with the WHODAS 2.0, the Sit-to-Stand-Test, the Time-Up-and-Go-Test and the 10Meter- Walking-Test. The FIM sensitivity of change in the patients’ clinical condition was evaluated through the differences between admission and discharge. Results: The results revealed sufficient evidence of validity (synchronic & structural), reliability (inter-rater & intra-rater) and sensitivity (admission- discharge) of the FIM in Greece. Conclusion: The FIM may be used in the future for ND inpatients assessment in Greece.
All in One: A Multi-Task Learning for Emoji, Sentiment and Emotion Analysis in Code-Mixed Text

Code mixed language and emojis are being ex-001 tensively used in social media to express opin-002 ions. In this paper, we propose a novel task that 003 focuses on suggesting appropriate emojis in 004 English-Hindi code-mixed sentences. We aim 005 to exploit the dependency between emotion, 006 sentiment, and emojis for building an end-to-007 end framework that can simultaneously iden-008 tify the emotion, sentiment and emojis in code-009 mixed sentences. We introduce the Code-Mixed 010 Emoji, Emotion and Sentiment aware Dataset 011 (CMEESD) which is an extension of the Se-012 mEval 2020 Task 9 . We establish strong base-013 lines to predict the correct emojis by simul-014 taneously identifying the emotion and senti-015 ment of a given tweet. The sentiment and emo-016 tion prediction in turn helps for the appropri-017 ate emoji classification. Empirical results on 018 the CMEESD dataset demonstrate that the pro-019 posed multi-task framework yields better per-020 formance over the single-task framework. 021
Technical note: Large‐eddy simulation of cloudy boundary layer with the Advanced Research WRF model

A thorough evaluation of the large‐eddy simulation (LES) mode of the Advanced Research WRF model is performed with use of three cloudy boundary layer cases developed as LES intercomparison cases by the GEWEX Cloud System Study. Our evaluation reveals two problems that must be recognized and carefully addressed before proceeding with production runs. These are (i) sensitivity of results to the prescribed number of acoustic time steps per physical time step; and (ii) the assumption of saturation adjustment in the initial cloudy state. A temporary, but effective method of how to cope with these issues is suggested. With the proper treatment, the simulation results are comparable to the ensemble mean of the other LES models, and sometimes closer to the observational estimate than the ensemble mean. In order to ease the burden for configuration and post‐processing, two new packages are developed and implemented. A detailed description of each package is presented. These packages are freely available to the public.
Herald: An Embedding Scheduler for Distributed Embedding Model Training

Given the ability to represent categorical features, embedding models have gained great success on many internet services. State-of-the-art training frameworks enable embedding cache in GPU workers to benefit from hardware acceleration while supporting massive category representations (embeddings) in the limited-capacity GPU device memory. However, based on our measurements, naively adopting a cache system in embedding model training leads to non-negligible communications overhead between caches and the global parameter server. We observe that many such communications are avoidable, given the predictability and sparsity natures of embedding cache accesses in distributed training. In this paper, we propose Herald, a runtime embedding scheduler that significantly reduces the cache overhead by leveraging information about the required embeddings in the input samples and the locations of those embeddings. Herald is composed of two key optimizations: It allocates samples in a training batch to proper workers for a high cache hit rate via a heuristic location-aware inputs partition mechanism, and applies an on-demand synchronization strategy for a low frequency of embedding synchronization. Preliminary simulation results show that Herald can reduce cache overhead by 39.3%-53.7% compared to a naive cache-enabled training system across different realistic datasets.
International Journal of Electrical and Computer Engineering (IJECE)

Received Nov 29, 2021 Revised Aug 8, 2022 Accepted Sep 3, 2022 The main objective of this paper is to study the correlation between investment in information technologies and especially information systems and information system success based on data collection and a multi-criteria decision-making approach using technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) methods. The criteria of the hierarchical model for evaluating the information system success are chosen from Delone and McLean information systems (IS) success model. The proposed approach has been implemented in 3 sectors recognized by their variation in the use of information systems: the financial sector, the service companies sector, and the construction industry sector. Therefore, the results of this implementation show that massive investment in information systems does not always guarantee good information system success, and information system success is not always the result of massive investment in the information system.
Intermittent-Aware Distributed Concurrency Control

Internet of Things (IoT) devices are gradually adopting battery-less, energy harvesting solutions, thereby driving the development of an intermittent computing paradigm to accumulate computation progress across multiple power cycles. While many attempts have been made to enable standalone intermittent systems, little attention has focused on IoT networks formed by intermittent devices. We observe that the computation progress improved by distributed task concurrency in an intermittent network can be significantly offset by data unavailability due to frequent system failures. This article presents an intermittent-aware distributed concurrency control protocol which leverages existing data copies inherently created in the network to improve the computation progress of concurrently executed tasks. In particular, we propose a borrowing-based data management method to increase data availability and an intermittent two-phase commit procedure incorporated with distributed backward validation to ensure data consistency in the network. The proposed protocol was integrated into a FreeRTOS-extended intermittent operating system running on Texas Instruments devices. Experimental results show that the computation progress can be significantly improved, and this improvement is more apparent under weaker power, where more devices will remain offline for longer duration.
Using electroacupuncture to recover muscle strength in knee osteoarthritic patients after total knee arthroplasty: a study protocol for a double-blinded, randomized and placebo-controlled trial

Background: Total knee arthroplasty (TKA) has recently become an almost irreplaceable and effective means to relieve pain, reconstruct knee motor function and improve the quality of life of patients with end-stage knee osteoarthritis (KOA). However, the muscle strength after TKA is usually difficult to recover. Although electroacupuncture (EA) can enhance the muscle strength of lower extremity, there is hardly any literature on the effect of EA on the muscle strength of lower extremity in patients after TKA. To address this problem, this trial is intended to evaluate the efficacy of EA after TKA for recovering the muscle strength of lower extremity, esp. in the early post-TKA period.Methods/design: This is a double-blinded, randomized and controlled trial. It will be conducted between January, 2020 and June, 2020. A total of 94 participants with KOA will have undergone unilateral TKA and they will then be randomized into a treatment group and a control group, viz. the EA group and the sham EA group. The former will receive EA at acupuncture points of ST37, ST36, SP10 and SP9. The latter, the control group will receive sham EA at sham locations for the acupuncture points of ST37, ST36, SP10 and SP9. The participants will be given 5 sessions of treatment per day for 2 weeks. The primary outcomes include a change in the amount of muscle strength and the Hospital for Special Surgery (HSS) score at the second week from a baseline (POD 3). The secondary outcomes include a 6-minute walking test, Numerical rating scale (NRS), the Hamilton Anxiety Scale and additional use of analgesia. The additional outcomes include incidence of analgesia-related side effects and rate of participant satisfaction. Blinding of the participants will also be assessed. The participants will be asked to guess whether they have received EA after the latest intervention. Adverse events of EA will be documented and assessed throughout the trial.Discussion: EA is helpful for the recovery and enhancement of muscle strength of the lower limb after TKA.
Edge-Based Technique for Ultra-Fast Gating of Large Array Imagers

— Ultra-fast gating of large array imagers can be quite challenging to implement due to the distributed RC (Resistance Capacitance) nature of the metal wires used in all ICs (Integrated Circuits) for electrical connections. For the transmission of a signal across a long path, the metal line reduces the electrical bandwidth and adds a delay. The behavior of these lines has been modeled and a new solution is presented to circumvent these limitations. In this paper, we present an edge-based approach to the gating circuitry that allows sub nanosecond gating with a very low skew across the whole imager. Simulation data shows that our solution is an efficient way of reducing the effect of the distributed RC line delay with a small penalty on surface area and consumption.
Separationof lsoenzymesof AlkalinePhosphataseby Substrate-GelImprintafter Electrophoresison CelluloseAcetate on cellulose acetate of the serum isoenzymes

lsoenzymes of alkalinephosphatase, separated by electrophoresison celluloseacetate,were developed by a substrate-gel imprint. The gel was prepared in an alkalinebuffer and contained naphthyl acid phosphate, which was hydrolyzed to -naphthyl and phosphorus. The -naphthyl was coupled to the diazonium salt,Fast VioletB, and an insolublered compound was formed on a celluloseacetate stripto mark the sitesof enzyme activity. The electrophoreticmobilitiesof the isoenzymes were compared with those of serum proteins. Supporting data included thermostability and chemical inhibition (urea and phenylalanine) studies.This method was used to evaluate patterns in tissues and human sera.
New W-prime signals at the LHC

We study the W 0 phenomenology in composite Higgs/ warped extra dimensional models focusing on the eect of fermionic resonances at 1 TeV. After deriving the existing bounds from the current LHC-8 analyses, we highlight the most promising signatures for W 0 discovery at the 14 TeV LHC. We nd in particular very promising the study of W 0 decay modes into vector-like top partners, specically the decay into a doublet of custodian heavy fermions, T5=3T2=3, and the decay into a heavy fermion plus a Standard Model quark. We perform a detailed parton level analysis of the channel W 0 ! T5=3T2=3 in the same-sign dilepton nal state, nding that it is a very promising signature to test the region at high W 0
A Kushner-Stratonovich Monte Carlo Filter for Nonlinear Dynamical System Identification

A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which drives the innovation (observation-prediction mismatch) for a given time-step to a zero-mean Brownian motion in an artificially introduced pseudo-time variable. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter.
Embedding Electronics in Additive Manufacturing for Digital Musical Instrument Design

The fast-growing technology of additive manufacturing-(AM), 3D printing, enables unique features in numerous design areas including musical instrument design. The recent advancements further introduce incorporating electronics into 3D printing. While still in the proof of concept phase, the ability to fabricate embedded sensors with 3D printing offers promising applications for musical instrument design. In this paper, embedding sensors and functional parts in the additive manufacturing process is discussed. We present the design process of embedded sensing for rapid prototyping digital musical instruments (DMI). The establishment of 3D models and operation sequences for different musical applications can be challenging since they vary de-pending on the electronic components. In order to address this problem, we provide a set of design and manufacturing speciﬁcations to customize the prototyping process for embedding structural electronics. The application of this hybrid method is demonstrated with two case studies: modular structures for a wearable gestural controller and an augmented ﬂute. These instruments present the current stage of the technology which uses fused-deposition modeling (FDM) and the advantages and challenges of hybrid AM in musical instrument design as well as its future directions.
A Novel Ermakov–Painlevé II System: N+1 ‐Dimensional Coupled NLS and Elastodynamic Reductions

Wave packet ansätze are introduced into an N+1 ‐dimensional Manakov‐type system and key invariants are isolated. Reduction is made to a novel coupled Ermakov–Painlevé II system and an algorithm presented for the derivation of wave packet representations via the classical Ermakov nonlinear superposition principle. Application of the procedure in the context of certain transverse wave motions in a generalized Mooney–Rivlin hyperelastic material is likewise shown to lead an Ermakov–Painlevé II reduction.
Seed quality and germination in selected hybrids of oil palm ( Elaeis guineensis , Jacq.)

Different indigenous oil palm hybrids were evaluated with an objective to assess their quality and to develop seed quality standards in commercial seed production centers. Majority of the indigenous hybrids had large proportion of small seeds and their percentage of distribution varied according to the hybrids. The different hybrid combinations recorded coefficient of variation of 11.70, 11.28 and 15.35 for seed weight, shell weight and kernel weight, respectively. Large seed group in all the crosses had high seed weight, shell weight, shell thickness and kernel weight. Though shell thickness had significant differences among crosses and size groups, the coefficient of variation recorded (6.38%) was low compared to other characteristics. Selected hybrids had low average kernel weight of 1.63, 1.05 and 0.74 g for large, medium and small seeds, respectively. In this study, high and low germination percentage was recorded in all the categories of seed groups irrespective of their sizes. All the seed physical parameters studied were positively correlated which are highly significant.