Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological sequence analysis using probabilistic logic generalizations of hidden Markov Models

Motivation: Probabilistic logic programming offers a powerful way to describe and evaluate structured statistical models. To investigate the practicality of probabilistic logic programming for structure learning in bioinformatics, we undertook a simplified bacterial gene-finding benchmark in PRISM, a probabilistic dialect of Prolog. Results: We evaluate Hidden Markov Model structures for bacterial protein-coding gene potential, including a simple null model structure, three structures based on existing bacterial gene finders and two novel model structures. We test standard versions as well as ADPH length modeling and three-state versions of the five model structures. The models are all represented as probabilistic logic programs and evaluated using the PRISM machine learning system in terms of statistical information criteria and gene-finding prediction accuracy, in two bacterial genomes. Neither of our implementations of the two currently most used model structures are best performing in terms of statistical information criteria or prediction performances, suggesting that better-fitting models might be achievable. Availability: The source code of all PRISM models, data and additional scripts are freely available for download at: http://github . com/somork/codonhmm. Contact: soer@ruc.dk Supplementary information: Supplementary data are available at Bioinformatics online. Received on July 7, 2011; revised on December 13, 2011; accepted on December 19, 2011
Consensus Algorithms and Distributed Ledger Technology for Decentralized Systems

: Blockchain is an example of a decentralized system that relies heavily on two key technologies: consensus algorithms and distributed ledger technology. These technologies make it possible to conduct trustless and secure transactions without the requirement for a central authority to oversee them. In this article, we will discuss the history of decentralized systems, the function of consensus algorithms, as well as the positives and negatives associated with distributed ledger technology. In addition, we conduct an analysis of a selection of consensus algorithms and give case studies of distributed systems that make use of a variety of consensus algorithms. The purpose of this work is to contribute to the current body of research by providing a comprehensive review of consensus algorithms, distributed ledger technology, and the practical applications of these topics. In conclusion, we will examine the ramifications of this fast-advancing topic as well as the potential it presents for future research.
Numerical Modelling of Tissue-Equivalent Proportional Counters

In this paper a survey is given of the various numerical techniques employed to study the transport of ionising particles inside a TEPC. The first part is devoted to the description of the general concept of particle transport calculations. Thereafter, the different methods available to study transport phenomena and energy deposition in the sensitive volume and in counter walls are described. Finally, the basic ionisation mechanisms which may occur in a counter are described, and the nonequilibrium phenomena which play an important role mainly for counters that are to be used in measurements at the nanodosemeter level are studied.
Transcription of HOX Genes Is Significantly Increased during Neuronal Differentiation of iPSCs Derived from Patients with Parkinson’s Disease

Parkinson’s disease (PD) is the most serious movement disorder, but the actual cause of this disease is still unknown. Induced pluripotent stem cell-derived neural cultures from PD patients carry the potential for experimental modeling of underlying molecular events. We analyzed the RNA-seq data of iPSC-derived neural precursor cells (NPCs) and terminally differentiated neurons (TDNs) from healthy donors (HD) and PD patients with mutations in PARK2 published previously. The high level of transcription of HOX family protein-coding genes and lncRNA transcribed from the HOX clusters was revealed in the neural cultures from PD patients, while in HD NPCs and TDNs, the majority of these genes were not expressed or slightly transcribed. The results of this analysis were generally confirmed by qPCR. The HOX paralogs in the 3′ clusters were activated more strongly than the genes of the 5′ cluster. The abnormal activation of the HOX gene program upon neuronal differentiation in the cells of PD patients raises the possibility that the abnormal expression of these key regulators of neuronal development impacts PD pathology. Further research is needed to investigate this hypothesis.
Cronobacter Species in the Built Food Production Environment: A Review on Persistence, Pathogenicity, Regulation and Detection Methods

The powdered formula market is large and growing, with sales and manufacturing increasing by 120% between 2012 and 2021. With this growing market, there must come an increasing emphasis on maintaining a high standard of hygiene to ensure a safe product. In particular, Cronobacter species pose a risk to public health through their potential to cause severe illness in susceptible infants who consume contaminated powdered infant formula (PIF). Assessment of this risk is dependent on determining prevalence in PIF-producing factories, which can be challenging to measure with the heterogeneity observed in the design of built process facilities. There is also a potential risk of bacterial growth occurring during rehydration, given the observed persistence of Cronobacter in desiccated conditions. In addition, novel detection methods are emerging to effectively track and monitor Cronobacter species across the food chain. This review will explore the different vehicles that lead to Cronobacter species’ environmental persistence in the food production environment, as well as their pathogenicity, detection methods and the regulatory framework surrounding PIF manufacturing that ensures a safe product for the global consumer.
Asynchronous Bidirectional Communication in Cell-Free Networks

We consider a bidirectional communication between two single-antenna transceivers using multiple multi-antenna access points (APs) in a cell-free network architecture. In such a network, because of different propagation delays associated with different APs, the end-to-end link is a multi-path channel that results in inter-symbol-interference (ISI) in the signals received at the transceivers. To tackle ISI, we resort to cyclic prefix (CP) assisted block transmission of the information symbols and employ joint pre- and post-channel equalizers at both the transceivers to mitigate the impact of intra-block interference. Considering the amplify-and-forward technique at the APs, we cast the joint design of equalizers, beamforming matrices, and transceivers’ transmit powers as a power minimization problem while guaranteeing predefined data rates at the transceivers. Assuming symmetric beamforming matrices at the APs, we devise a semi-closed-form solution for this problem. We prove rigorously that at the optimum only a synchronous subset of the APs should participate in the information exchange between the two transceivers. This is achieved by proving that at the optimum, the pre-equalizer matrices should be unitary and the post-equalizer matrices should be invertible.
TwIdw—A Novel Method for Feature Extraction from Unstructured Texts

This research proposes a novel technique for fake news classification using natural language processing (NLP) methods. The proposed technique, TwIdw (Term weight–inverse document weight), is used for feature extraction and is based on TfIdf, with the term frequencies replaced by the depth of the words in documents. The effectiveness of the TwIdw technique is compared to another feature extraction method—basic TfIdf. Classification models were created using the random forest and feedforward neural networks, and within those, three different datasets were used. The feedforward neural network method with the KaiDMML dataset showed an increase in accuracy of up to 3.9%. The random forest method with TwIdw was not as successful as the neural network method and only showed an increase in accuracy with the KaiDMML dataset (1%). The feedforward neural network, on the other hand, showed an increase in accuracy with the TwIdw technique for all datasets. Precision and recall measures also confirmed good results, particularly for the neural network method. The TwIdw technique has the potential to be used in various NLP applications, including fake news classification and other NLP classification problems.
In Vitro Biofouling Performance of Boron-Doped Diamond Microelectrodes for Serotonin Detection Using Fast-Scan Cyclic Voltammetry

Neurotransmitter release is important to study in order to better understand neurological diseases and treatment approaches. Serotonin is a neurotransmitter known to play key roles in the etiology of neuropsychiatric disorders. Fast-scan cyclic voltammetry (FSCV) has enabled the detection of neurochemicals, including serotonin, on a sub-second timescale via the well-established carbon fiber microelectrode (CFME). However, poor chronic stability and biofouling, i.e., the adsorption of interferent proteins to the electrode surface upon implantation, pose challenges in the natural physiological environment. We have recently developed a uniquely designed, freestanding, all-diamond boron-doped diamond microelectrode (BDDME) for electrochemical measurements. Key potential advantages of the device include customizable electrode site layouts, a wider working potential window, improved stability, and resistance to biofouling. Here, we present a first report on the electrochemical behavior of the BDDME in comparison with CFME by investigating in vitro serotonin (5-HT) responses with varying FSCV waveform parameters and biofouling conditions. While the CFME delivered lower limits of detection, we also found that BDDMEs showed more sustained 5-HT responses to increasing or changing FSCV waveform-switching potential and frequency, as well as to higher analyte concentrations. Biofouling-induced current reductions were significantly less pronounced at the BDDME when using a “Jackson” waveform compared to CFMEs. These findings are important steps towards the development and optimization of the BDDME as a chronically implanted biosensor for in vivo neurotransmitter detection.
Multi-Objective Optimization Design of Hybrid Excitation Double Stator Permanent Magnet Synchronous Machine

In this article, a novel hybrid excitation double stator permanent magnet synchronous machine (HEDS-PMSM) is designed. The permanent magnets and field windings work together to provide air gap magnetic field, and different currents are applied to the field windings to enhance or weaken the air gap magnetic field to achieve a wide speed regulation range. Considering the complex structure of double-stator machine, the multi-objective optimization method is proposed to optimize the machine parameters. To optimize the machine accurately and efficiently, the sensitivity analysis of the main design variables of the machine is carried out, and the design variables with high sensitivity are selected. Then, the kriging response surface model is used to analyze the high sensitivity design variables of the machine. In order to obtain the optimal design variables, Non-Dominated Sorted Genetic Algorithm-II (NSGA-II) algorithm is used to optimize the HEDS-PMSM iteratively. Based on the finite element simulation software, the output torque, torque ripple, core loss and other electromagnetic performance of the machine are analyzed. A prototype is made for experimental verification. The experimental results show that the multi-objective optimization design method for the proposed HEDS-PMSM is reasonable and effective.
Social Performance Disclosed by European Companies: The Role of the Board Attributes and the Country’s Legal System

This paper aims to analyze factors that influence social performance-related information disclosure in European countries. Specifically, the objective is to investigate the Board’s attributes (Diversity, Inclusion, People Development and Controversies). To achieve the goal, an empirical analysis was conducted with 2494 listed companies in Europe as support for the economic year 2021. To measure a possible link between the variables under study, a regression analysis was performed. Our results show that Board Diversity, Inclusion and People Development contribute positively to social performance disclosure, whereas Board Controversies negatively affect the dependent variable. Furthermore, the study results reveal that the country’s legal system is relevant to the company’s transparency. The model variables determine 62% of the social performance reporting variance. Our Results are useful for all non-financial information users, governments and organizations in developing sustainability reporting standards.
Study on phase-space reconstruction of chaotic signal based on wavelet transform

Using the methods of the wavelet transform and the nonlinear dynamics, the b ehavior of chaotic signals in phase space is studied. It is indicated that, in p hase space reconstruction, the wavelet transform of chaotic time series is essen tia lly a projection of strange attractor on the axis of the space that filter vect ors opened, which in correspondance with the method of phase space reconstructio n proposed by Packard et al. The experimental results show that, after d oing wavelet transform, the architecture of attractor trajectory is similar to t he original one, and the nonlinear invariants such as correlation dimension and Kolmogorov entropy are reserved. These results show that wavelet transform is ef fective for studying chaotic signal.
POTENTIAL OF MOBILE MAPPING TO CREATE DIGITAL TWINS OF FORESTS

Abstract. Forests are irreplaceable and are being studied extensively. Better forest inventory and understanding necessitate effective mapping, modeling, and automatic analysis. As a result, considerable research effort is being devoted to digitizing forest environments. Recently, digital twins have come to the attention of the geospatial community as a virtual representation of the Earth’s surface linked to its corresponding physical asset. This concept is applicable to forests and has been studied in the literature. This requires initial input data obtained through reality capture. Among mapping techniques, laser scanning has emerged as a state-of-the-art technology for vegetation modeling. In this paper, we look into the potential of mobile laser scanning for forest digital twinning. While most studies concentrate on single tree detection, modeling, and estimation of dendrometric parameters, we also include lower vegetation in our investigations. To accomplish this, we first detect single trees and then investigate different vegetation densities and levels using geometric metrics. We also demonstrate how to model the underlying layers of vegetation in a digital twin. We perform the tests on data from mobile laser scanning (MLS) and compare the results to those from airborne laser scanning (ALS). We show that single tree detection based on crown separation using MLS data works similarly to or slightly better than ALS data. Furthermore, we demonstrate that MLS data allows for more detailed analysis of understory vegetation taking into account different height levels and a multi-level representation, whereas ALS data only allows for rough analysis of the lower parts of forest vegetation.
Radix-64 Floating-Point Division and Square Root: Iterative and Pipelined Units

Digit-recurrence algorithms are widely used in actual microprocessors to compute floating-point division and square root. These iterative algorithms present a good trade-off in terms of performance, area and power. Traditionally, commercial processors have iterative division and square root units where the iteration logic is used over several cycles. The main drawbacks of these iterative units are long latency and low throughput due to the reuse of part of the logic over several cycles, and its hardware complexity with separated logic for division and square root. We present a radix-64 floating-point division and square root algorithm with a common iteration for division and square root and where, to have an affordable implementation, each radix-64 iteration is made of two simpler radix-8 iterations. The radix-64 algorithm allows to get low-latency operations, and the common division and square root radix-64 iteration results in some area reduction. The algorithm is mapped into two different microarchitectures: a low-latency and low area iterative unit, and a low-latency and high-throughput pipelined unit. In both units speculation between consecutive radix-8 iterations is used to reduce the timing.
UV-LIGA: a promising and low-cost variant for microsystem technology

A low-cost surface microstructuring technique is described and examples provided of its recent application. The new technology, UV-LIGA combines depth UV lithographic patterning of very thick photoresists and electrodepositing of structural materials into the patterned resist moulds. Both UV lithography and electrodeposition do not need any expensive or special equipment. Movable three dimensional microstructures with a high aspect ratio can be obtained by combining the UV-LIGA process with a sacrificial layer technique. As an example of the advanced application in microsystems, fabrication of 3D accelerometers has been presented, using titanium as a sacrificial layer and nickel as the structural material.
The Role of Integrins for Mediating Nanodrugs to Improve Performance in Tumor Diagnosis and Treatment

Integrins are heterodimeric transmembrane proteins that mediate adhesive connections between cells and their surroundings, including surrounding cells and the extracellular matrix (ECM). They modulate tissue mechanics and regulate intracellular signaling, including cell generation, survival, proliferation, and differentiation, and the up-regulation of integrins in tumor cells has been confirmed to be associated with tumor development, invasion, angiogenesis, metastasis, and therapeutic resistance. Thus, integrins are expected to be an effective target to improve the efficacy of tumor therapy. A variety of integrin-targeting nanodrugs have been developed to improve the distribution and penetration of drugs in tumors, thereby, improving the efficiency of clinical tumor diagnosis and treatment. Herein, we focus on these innovative drug delivery systems and reveal the improved efficacy of integrin-targeting methods in tumor therapy, hoping to provide prospective guidance for the diagnosis and treatment of integrin-targeting tumors.
Type-B monoamine oxidase inhibitors in neurological diseases: clinical applications based on preclinical findings

Type-B monoamine oxidase inhibitors, encompassing selegiline, rasagiline, and safinamide, are available to treat Parkinson’s disease. These drugs ameliorate motor symptoms and improve motor fluctuation in the advanced stages of the disease. There is also evidence supporting the benefit of type-B monoamine oxidase inhibitors on non-motor symptoms of Parkinson’s disease, such as mood deflection, cognitive impairment, sleep disturbances, and fatigue. Preclinical studies indicate that type-B monoamine oxidase inhibitors hold a strong neuroprotective potential in Parkinson’s disease and other neurodegenerative diseases for reducing oxidative stress and stimulating the production and release of neurotrophic factors, particularly glial cell line-derived neurotrophic factor, which support dopaminergic neurons. Besides, safinamide may interfere with neurodegenerative mechanisms, counteracting excessive glutamate overdrive in basal ganglia motor circuit and reducing death from excitotoxicity. Due to the dual mechanism of action, the new generation of type-B monoamine oxidase inhibitors, including safinamide, is gaining interest in other neurological pathologies, and many supporting preclinical studies are now available. The potential fields of application concern epilepsy, Duchenne muscular dystrophy, multiple sclerosis, and above all, ischemic brain injury. The purpose of this review is to investigate the preclinical and clinical pharmacology of selegiline, rasagiline, and safinamide in Parkinson’s disease and beyond, focusing on possible future therapeutic applications.
The Role of Wild Boars in the Circulation of Tick-Borne Pathogens: The First Evidence of Rickettsia monacensis Presence

Simple Summary Wildlife has a major role in the transmission and maintenance of zoonotic agents, as most emerging infectious diseases are of wildlife origin. Among the great variety of wildlife species, wild boars (Sus scrofa) are species with continuously increasing abundance and geographical distribution. Wild boars were suggested as appropriate sentinel species for the distribution and abundance of certain tick species in America and Europe. Therefore, these species may also be suitable sentinel species for screening for tick-borne pathogens. The aim of this study was to evaluate the presence of tick-borne pathogens in wild boars in Romania. A total of 203 blood samples were collected from wild boars (Sus scrofa) from two Transylvanian counties (Cluj, Sălaj) in Romania. Three emerging zoonotic pathogens were identified, Anaplasma phagocytophilum and two Rickettsia species (R. helvetica, R. monacensis) DNA, in the blood of tested animals. These results suggest the involvement of wild boars in the epidemiology of Rickettsia species and A. phagocytophilum. Hence, this species may be used as a sentinel for the general surveillance of these zoonotic pathogens. Abstract Most wild mammals can serve as hosts both for tick-borne pathogens (TBPs) and for the ticks themselves. Among these, wild boars, due to their large body size, habitat and life span, show high exposure to ticks and TBPs. These species are now one of the widest-ranging mammals in the world, as well as the most widespread suid. Despite the fact that certain local populations have been decimated by African swine fever (ASF), wild boars are still considered overabundant in most parts of the world, including Europe. Altogether, their long-life expectancy, large home ranges including migration, feeding and social behaviors, wide distribution, overabundance and increased chances of interactions with livestock or humans make them suitable sentinel species for general health threats, such as antimicrobial-resistant microorganisms, pollution and ASF geographical distribution, as well as for the distribution and abundance of hard ticks and also for certain TBPs, such as Anaplasma phagocytophilum. The aim of this study was to evaluate the presence of rickettsial agents in wild boars from two counties in Romania. Among 203 blood samples of wild boars (Sus scrofa ssp. attila) collected during 3 (2019–2022) hunting seasons (September–February), 15 were found positive for tick-borne pathogen DNA. Six wild boars were positive for A. phagocytophilum DNA presence and nine for Rickettsia spp. The identified rickettsial species were R. monacensis (six) and R. helvetica (three). No animal was positive either for Borrelia spp. , Ehrlichia spp. or Babesia spp. To the best of our knowledge, this is the first report of R. monacensis in European wild boars, thus adding the third species from the SFG Rickettsia, in the epidemiology of which this wild species may have a role as a reservoir host.