Miracle-dz/UniFAR-FTUs huggingface dataset:
3’UTR Remodelling of Axonal Transcripts in Sympathetic Neurons

Asymmetric localization of mRNAs is a mechanism that constrains protein synthesis to subcellular compartments. In neurons, mRNA transcripts are transported to both dendrites and axons where they are rapidly translated in response to extracellular stimuli. To characterize the 3’ UTR isoforms localized in axons and cell bodies of sympathetic neurons we performed 3’ end-RNA sequencing. We discovered that isoforms transported to axons had significantly longer 3’ UTRs compared to cell bodies. Moreover, more than 100 short 3’ UTR isoforms were uniquely expressed in axons. Analysis of the long 3’ UTR of IMPA1 indicated that a multiprotein complex including Upf1, HuD and Ago2 mediated 3’ UTR cleavage. This event enhanced IMPA1 translation and was necessary for maintaining axon integrity. 3’ UTR cleavage took place in axons and was not limited to IMPA1 but extended to other transcripts with similar expression patterns. We conclude that the 3’ UTR of neuronal transcripts undergo post-transcriptional remodelling and describe an alternative mechanism that regulates local protein synthesis. HIGHLIGHTS 3’end-Seq reveals distinct expression of alternative 3’UTR isoforms in axons and cell bodies of sympathetic neurons. Short 3’UTR isoforms uniquely detected in axons are generated in situ by cleavage of longer precursors. A protein complex containing Upf1, HuD, Pabpc4 and Ago2 mediates the cleavage of 3’UTRs.
Ultrahigh flexoelectricity of 3D interconnected porous PDMS and its application as flexible passive sensors

Non-conductive materials have the property of flexoelectricity, which means they can generate electricity when bent and twisted. However, a small scale irregular shape or a peculiar load has been the necessary condition, and the weight-specific ratios of flexoelectricity are limited. Here, we report the ultrahigh flexoelectric response of porous polydimethylsiloxane (PDMS). The porous PDMS with 3D micron-scale interconnected structures exhibits two orders of magnitude higher weight-specific flexoelectric response than that of solid PDMS. Due to diverse and irregular internal micro-structures, the porous materials can exhibit flexoelectricity under arbitrary loading forms. The flexoelectric signal was found linearly proportional to the applied strain, the microstructural size and the frequency, which makes porous material promising for flexible, ultralight, sensitive and multi-functional passive sensor applications without external applied electric power. Our work highlights the new potential of porous structured materials with remarkable flexoelectric effect in sensing, actuating, energy harvesting, and biomimetics as light-weight materials.
PSGfinder: fast identification of genes under divergent positive selection using the dynamic windows method

Summary Orthologous genes evolving under divergent positive selection are those involved in divergent adaptive trajectories between related species. Current methods to identify such genes are complex and conservative or present some imperfections, limiting genome-wide searches. We present a simple method, Dynamic Windows, to detect regions of protein-coding genes evolving under divergent positive selection. This method is implemented in PSGfinder, a user-friendly and flexible software, allowing rapid genome-wide screenings of regions with a dN/dS >1. PSGfinder additionally includes an alignment cleaning procedure and an adapted multiple comparison correction to identify significant signals of positive selection. Availability and Implementation PSGfinder is a software that implements the DWin method, is written in Python and is freely available with its documentation at: https://genev.unige.ch/research/laboratory/Juan-Montoya or at: https://github.com/joel-tuberosa/psgfinder Contact juan.montoya@unige.ch; joel.tuberosa@unige.ch
Using the MLR and Neuro-Fuzzy Methods to Forecast Air Pollution Datasets

The forecasting of time series data is essential by following statistical and intelligent techniques. Particular matter (PM10) is a time series dataset used to scale the air pollution as a dependent variable while there are many types of pollutants used as independent variables. MLR model has been used as a traditional linear approach to forecasting PM 10 data. Combining NF as a nonlinear intelligent method with MLR in a hybrid MLR-NF method has been proposed for improving PM 10 forecasts and handling the nonlinearity of datasets. The forecasting results reflected that the hybrid method outperformed the traditional method. Although a multiple linear regression (MLR) model has been used for air quality forecasting depending on several meteorological variables in many recent studies, the MLR model is unable to identify the nonlinear pattern of these types of data. Malaysian datasets of PM10 and several climate pollutants will be studied in this paper. The objective of this study is to forecast PM10 and obtain the best results and minimum forecasting error. In this paper, the dependent variable will be forecasted by using traditional and intelligent methods. MLR has been used as a traditional method to forecast PM10. Neuro-fuzzy (NF) in the adapted copy, which calls the adaptive neuro-fuzzy inference system (ANFIS) is combined with MLR and used as an intelligent method to forecast PM10. The results reflect that MLR-NF outperformed MLR for forecasting PM10 data. In conclusion, MLR-NF can be used to forecast PM10 for more accurate results compared to traditional methods.
An Online Intelligent Method to Calibrate Radar and Camera Sensors for Data Fusing

This paper introduces an intelligent method to calibrate radar and camera sensors for data fusing. Camera can recognize pedestrians, non-motor vehicles, motor vehicles high accuracy by advanced deep learning neural networks. But it’s hard to acquire the target’s spatial position and speed information simply relying on image. For the radar sensor, it’s easy to acquire the target’s spatial position and speed information by itself, but it cannot recognize target. In other words, the advantage of radar is the disadvantage of camera, and the advantage of camera is the disadvantage of radar. So combining these two complementary sensors is valid and necessary for solving the problem: Who is doing what. Then the first and foremost thing is to calibrate the radar and camera sensors. Calibration includes time synchronization and space calibration, which will seriously affect the sensors data fusing performance. This paper emphasizes on spatial calibration. Traditional methods (based on the principle of geometric projection or four-point calibration method) cannot acquire enough high calibration accuracy in the general scenarios with low time cost or easy operation. So this paper introduces an online intelligent method to calibrate radar and camera sensor without human assistance operation in the general scenarios. Firstly, we introduce what is spatial calibration. Secondly, we introduce two conventional methods and their defects. And then we introduce the online intelligent calibration method. At last we compare three calibration methods with the actual data to further explain the advance of our new method.
Construction of Almost Everywhere C2 Continuous Shape Interpolating Spaces Via Progressive Interpolation of Loop Subdivision

Shape interpolation is an important methodology for 3D modeling in digital geometry processing. It has been widely applied in computer animation, geometric design, and so on. This paper proposes a framework for producing smooth interpolation sequences on a high dimensional manifold, which is spanned by given 3D keyframes represented as meshes with the same connectivity. Speci(cid:28)cally, we convert each keyframe to a high dimensional vector stacked with edge lengths and dihedral angles and regard it as a point in the corresponding shape space. We then project these points (keyframes) onto a planar space and further triangulate the 2D projections into a mesh. A 2D manifold embedded in the shape space can be obtained by using Loop subdivision surface to interpolate the high-dimensional mesh which is constructed by transferring the connectivity of the 2D mesh onto the corresponding keyframes. For the convenience of modeling, we design an interactive interface which supports sampling C 2 continuous animation sequences on the manifold by drawing cubic B-splines on its projected plane. Thorough experiments show that our approach is e(cid:30)cient and capable of producing high quality animation sequences, compared to the state-of-the-art 3D shape interpolation methods.
RE(DIS)COVERING MULTICULTURAL CAPITAL IN LEICESTER’S SCHOOLS AND COLLEGES: HISTORICAL LEGACIES AND POSSIBILITIES FOR CHANGE

ABSTRACT This paper empirically re(dis)covers a moment of conjuncture within Leicester when an opportunity opened up through multicultural/anti-racist education for schools and colleges to develop their ‘multicultural capital’. It does this through the thematic analysis of the key proximate document Report of the Working Party on Multicultural Education as well as drawing on interview data provided by two important agents who helped to implement Leicester’s/Leicestershire’s moment of multicultural education. This moment generated a symbolic, ideational, and conceptual shift within Leicester’s education provision toward a more culturally inclusive position that began to recognise the cultural capital of non-white students. However, this moment was to be lost in the ‘neoliberal epoch’. It is argued in this paper that neoliberal education policy/practice has become an enabling mechanism for renascent colonial ideology. By re(dis)covering this vision for the official recognition of non-white cultural capital, this paper demonstrates the possibilities for alternative directions within Leicester’s schools and colleges that can challenge neoliberal and colonial conceptions of education. It suggests that there are still spaces and structures that can be re(dis)covered in order for this vision to be enabled.
START-UPS AND INTERNATIONALISATION: THE CASE OF ROMANIA. PART 2. EMPIRICAL RESEARCH

Companies’ creation and growth are a fervently debated topic in the literature and economic policies, at least for the fact that they are related to maintaining a critical number of active companies, an essential aspect of the functioning of the economy and society. Growth is associated with overcoming the stage of survival and ensures the development and consolidation of existing companies, meanwhile the establishment of the new ones means the replacement of those that disappear from the economic landscape. The launch and expansion of young companies could lead to a positive balance in terms of employment, income, incentive of demand to other sectors and regions, boosting their development. New firms are often associated with innovation and technological change, competitiveness and competition on the market. The survival, growth and consolidation of companies occurs not only as a result of quantitative accumulations, but also as a result of the incorporation of new technologies, an open attitude towards innovation, whether it is technical, managerial or commercial. Growth is therefore a normal phenomenon in the life of a company, which must be encouraged and supported by public measures as part of a smart and forward-looking economic policy. Growth may be local, but it usually takes place at national, regional and international levels. In the first part of this article we have presented and discussed the theoretical background as it results of previous researches and official studies and reports, internationalization opportunities and some features and trends of internationalization of companies in the EU, and Romania, respectively. We now present our investigation to determine whether, and to what extent, internationalisation is relevant to start-ups, if there is a possible correlation between the 6 selected indicators of internationalisation as revealed by World Bank Data on one hand, and the number of start-ups in Romania on the other hand.
The relationship between prolactin and adipose tissue and metabolic parameters in patients with polycystic ovary syndrome

Objectives: Polycystic ovary syndrome is a reproductive endocrinopathy, predominantly accompanied by insulin resistance, obesity, and metabolic disorder. In this study, we aimed to investigate the possible relationship between prolactin and adipose tissue and metabolic parameters in patients with polycystic ovary syndrome (PCOS). Methods: A total of 58 patients with PCOS and 34 body mass index (BMI)-matched healthy controls between September 2018 and March 2019 were included in the study. Visceral and subcutaneous adipose tissues were measured using ultrasonography. Serum prolactin, fasting blood glucose, insulin, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride, total cholesterol, luteinizing hormone (LH), total testosterone, dehydroepiandrosterone sulfate (DHEA-S), and 17-hydroxyprogesterone (17-OHP) levels were measured. Results: The median BMI ( p = 0.001), waist circumference ( p = 0.002), hip circumference ( p = 0.003), waist-to-hip ratio ( p = 0.013), LH ( p = 0.012), total testosterone ( p = 0.004), DHEA-S ( p = 0.049), 17-OHP ( p = 0.001), insulin ( p = 0.001), minimum preperitoneal fat thickness ( p = 0.001), maximum preperitoneal fat thickness ( p = 0.048), and intraperitoneal fat thickness ( p = 0.018) were significantly higher in the PCOS group compared to the control group. However, there was no significant correlation between prolactin levels and adipose tissue parameters and insulin levels in the patients with PCOS. Conclusions: Although there was an increase in the preperitoneal and intraperitoneal fat thickness in the PCOS group compared to the control group, no significant correlation was observed between prolactin and visceral and subcutaneous adipose tissues and metabolic parameters.
Sibilant consonants classification comparison with multi‐ and single‐class neural networks

Many children with speech sound disorders cannot pronounce the sibilant consonants correctly. We have developed a serious game, which is controlled by the children's voices in real time, with the purpose of helping children on practicing the production of European Portuguese (EP) sibilant consonants. For this, the game uses a sibilant consonant classifier. Since the game does not require any type of adult supervision, children can practice producing these sounds more often, which may lead to faster improvements of their speech. Recently, the use of deep neural networks has given considerable improvements in the classification of a variety of use cases, from image classification to speech and language processing. Here, we propose to use deep convolutional neural networks to classify sibilant phonemes of EP in our serious game for speech and language therapy. We compared the performance of several different artificial neural networks that used Mel frequency cepstral coefficients or log Mel filterbanks. Our best deep learning model achieves classification scores of 95.48% using a 2D convolutional model with log Mel filterbanks as input features. Such results are then further improved for specific classes with simple binary classifiers.
Nine Measures to Take—Unlocking the Potential for Biomass Heat in the German Industry and the Trade, Commerce, and Service Sector

Solid biofuels have the potential of making a major contribution to achieving the objectives of the Paris Climate Agreement if they are used more extensively for covering the heat demand of the industry and the trade, commerce, and service (TCS) sector. To unlock this potential, a holistic analysis of the supply chain from producer to end customer was performed, involving consultants, planners, and financial institutions. The focus is on the deployment of larger biomass heating boilers (with heat loads spanning several 100 kW to several MW). The study identifies the most important barriers for expanding the use of solid biofuels for heat in the German TCS sector as well as in the industry sector. Nine sets of measures were identified for overcoming the most critical barriers, among others, by drawing on best practice approaches and solutions from other German and European contexts. Based on these measures, political recommendations were derived to shape the regulatory framework conditions accordingly. These recommendations can in turn offer a stimulus for other countries to foster a more efficient and climate-effective use of biomass.
Breadth and Dynamics of HLA-A2– and HLA-B7–Restricted CD8+ T Cell Responses against Nonstructural Viral Proteins in Acute Human Tick-Borne Encephalitis Virus Infection

Tick-borne encephalitis virus (TBEV) is a leading cause of viral meningoencephalitis in many parts of Europe and eastwards in Asia, with high morbidity and often long-term neurologic sequelae. With no treatment available, studies of the immune response to TBEV are essential for the understanding of the immunopathogenesis of tick-borne encephalitis and for the development of therapeutics. We have previously demonstrated that CD8+ T cell responses in peripheral blood in patients with acute TBEV peak at around 7 d after hospitalization in the neuroinvasive phase of the disease. In this study, we identified six novel TBEV HLA-A2– and HLA-B7–restricted epitopes, all derived from the nonstructural proteins of TBEV. This identification allowed for a comprehensive phenotypic and temporal analysis of the HLA-A2– and HLA-B7–restricted Ag-specific CD8+ T cell response during the acute stages of human TBEV infection. HLA-A2– and HLA-B7–restricted TBEV epitope–specific effector cells predominantly displayed a CD45RA−CCR7−CD27+CD57− phenotype at day 7, which transitioned into separate distinct phenotypes for HLA-A2– and HLA-B7–restricted TBEV-specific CD8+ T cells, respectively. At day 21, the most prevalent phenotype in the HLA-A2–restricted CD8+ T cell populations was CD45RA−CCR7−CD27+CD57+, whereas the HLA-B7–restricted CD8+ T cell population was predominantly CD45RA+CCR7−CD27+CD57+. Almost all TBEV epitope–specific CD8+ T cells expressed α4 and β1 integrins at days 7 and 21, whereas the bulk CD8+ T cells expressed lower integrin levels. Taken together, human TBEV infection elicits broad responses to multiple epitopes, predominantly derived from the nonstructural part of the virus, establishing distinct maturation patterns for HLA-A2– and HLA-B7–restricted TBEV epitope–specific CD8+ T cells.
Motion and physiological noise effects on amygdala real-time fMRI neurofeedback learning

Real-time fMRI neurofeedback allows to learn control over activity in a localized brain region. However, with fMRI, physiological factors such as the cardiac cycle and respiration interfere with the measurement of brain activation. In conventional fMRI studies this is usually mitigated by inclusion of motion parameters and/or physiological parameters as nuisance regressors at the analysis stage, allowing to correct for and filter out such confounders. In real-time fMRI, however, such an approach is not routinely feasible due to the necessity to process all signals during the runtime of an experiment. The absence of on-line correction can therefore compromise real-time fMRI study outcomes reporting volitional self-regulation capability as BOLD signal changes. This is especially true for BOLD signal changes in subcortical regions situated close to blood vessels or air cavities, such as the amygdala. We therefore aimed to establish the effects of motion, heart rate, heart rate variability, and respiratory volume on learning effects, which means here an increase in BOLD signal change over NF training, in an amygdala neurofeedback experiment. Specifically, we investigate motion parameters from two emotion regulation studies - performed at 3T and 7T scanners - and additionally acquired physiological variance for the latter one. Our results revealed differences in these parameters between groups and especially between regulation and resting periods within each participant. However, strictly considering these parameters as nuisance regressors in data analysis revealed that the learning of volitional self-regulation of the amygdala is not driven by motion and physiological changes. As validation of our real-time findings, we compare them to the gold standard of assessment of motion and physiology from the Human Connectome Project. Based on this, we recommend to carefully report neurofeedback study results including physiological nuisance regression. To our knowledge, this is the first study investigating the effects of motion and physiological noise correction on neurofeedback BOLD effects.
Scale effects and a method to evaluate similarity in electrochemical micromachining of Nitinol

ABSTRACT In this manuscript, Electrochemical Micromachining (ECM) is well designed with the important concept called scale effect. The main objective is to evaluate the scale effects that occur when the machining parameters is transferred from micro ECM to macro ECM. Similarity theory is used to evaluate the scale effects quantitatively. Input process parameters such as feed rate, duty ratio and voltage are taken and designed as single factor orthogonal experiments to evaluate the scale effect occurred by response parameters such as Material removal rate (MRR) and geometrical features. Utilization of this concept provides improvement in the machining performances, reduction in the energy involved and also useful in optimizing the processing parameters. The similarity precision of the micro and macro systems is calculated. A positive scale effect is observed when the output values of MRR and geometrical features are normalized. No negative scale effect is observed in experimental results.
The effect of different crops and slopes on runoff and soil erosion

Runoff and soil erosion are serious environmental issues in farmland management. In a field experiment in Xingmu, China, data from nine plots with different slopes and crops were collected, and the crops' leaf area index (LAI) used to represent the impact of vegetation on runoff and soil erosion. The results show that slope and crop both have significant effects on runoff and soil erosion, and that the LAI can indicate the effects of different crops.