Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Harvesting Methods for Transmission Lines: A Comprehensive Review

Humanity faces important challenges concerning the optimal use, security, and availability of energy systems, particularly electrical power systems and transmission lines. In this context, data-driven predictive maintenance plans make it possible to increase the safety, stability, reliability, and availability of electrical power systems. In contrast, strategies such as dynamic line rating (DLR) make it possible to optimize the use of power lines. However, these approaches require developing monitoring plans based on acquiring electrical data in real-time using different types of wireless sensors placed in strategic locations. Due to the specific conditions of the transmission lines, e.g., high electric and magnetic fields, this a challenging problem, aggravated by the harsh outdoor environments where power lines are built. Such sensors must also incorporate an energy harvesting (EH) unit that supplies the necessary electronics. Therefore, the EH unit plays a key role, so when designing such electronic systems, care must be taken to select the most suitable EH technology, which is currently evolving rapidly. This work reviews and analyzes the state-of-the-art technology for EH focused on transmission lines, as it is an area with enormous potential for expansion. In addition to recent advances, it also discusses the research needs and challenges that need to be addressed. Despite the importance of this topic, there is still much to investigate, as this area is still in its infancy. Although EH systems for transmission lines are reviewed, many other applications could potentially benefit from introducing wireless sensors with EH capabilities, such as power transformers, distribution switches, or low- and medium-voltage power lines, among others.
Enhanced Cardiorenal Protective Effects of Combining SGLT2 Inhibition, Endothelin Receptor Antagonism and RAS Blockade in Type 2 Diabetic Mice

Treatments with sodium–glucose 2 cotransporter inhibitors (SGLT2i) or endothelin receptor antagonists (ERA) have shown cardiorenal protective effects. The present study aimed to evaluate the cardiorenal beneficial effects of the combination of SGLT2i and ERA on top of renin–angiotensin system (RAS) blockade. Type 2 diabetic mice (db/db) were treated with different combinations of an SGLT2i (empagliflozin), an ERA (atrasentan), and an angiotensin-converting enzyme inhibitor (ramipril) for 8 weeks. Vehicle-treated diabetic mice and non-diabetic mice were included as controls. Weight, blood glucose, blood pressure, and kidney and heart function were monitored during the study. Kidneys and heart were collected for histological examination and to study the intrarenal RAS. Treatment with empagliflozin alone or combined significantly decreased blood glucose compared to vehicle-treated db/db. The dual and triple therapies achieved significantly greater reductions in diastolic blood pressure than ramipril alone. Compared to vehicle-treated db/db, empagliflozin combined with ramipril or in triple therapy significantly prevented GFR increase, but only the triple combination exerted greater protection against podocyte loss. In the heart, empagliflozin alone or combined reduced cardiac isovolumetric relaxation time (IVRT) and left atrium (LA) diameter as compared to vehicle-treated db/db. However, only the triple therapy was able to reduce cardiomyocyte area. Importantly, the add-on triple therapy further enhanced the intrarenal ACE2/Ang(1-7)/Mas protective arm of the RAS. These data suggest that triple therapy with empagliflozin, atrasentan and ramipril show synergistic cardiorenal protective effects in a type 2 diabetic mouse model.
Fermented Total Mixed Ration with Cottonseed Meal or Rapeseed Meal Improved Growth Performance and Meat Quality of Hu Lamb Compared to Total Mixed Ration with Soybean Meal

Protein sources in livestock feed include cottonseed meals (CSM) or rapeseed meals (RSM). However, their use in feed diets is restricted due to anti-nutritional elements such as free gossypol or glucosinolate. The main objective of this study was to determine the effect of microbial fermentation of total mixed ration (TMR) with CSM/RSM on the growth performance and meat quality of Hu lamb. Fifty-one male Hu lambs (4 months old) with a 22.51 kg body weight were randomly assigned to three treatments and fed unfermented TMR with soybean meal (control group), FTMR (fermented total mixed ration) with CSM or RSM, respectively. The experiment lasted 97 days. Growth performance, rumen fermentation, and meat quality were measured. Overall dry matter intake (DMI), average daily gain (ADG), and final body weight (FBW) were similar among treatments (p > 0.05). There were no significant differences in the lightness (L*), redness (a*), and yellowness (b*) of longissimus thoracis (LT) muscle meat. There were no significant differences between the FTMR-CSM/RSM and control groups in drip loss, cooking loss, cooking percentage rate, or shear force of LT muscle meat. Lambs fed FTMR-CSM had significantly higher rumen fluid total volatile fatty acid values than those in control or FTMR-RSM groups (p < 0.05). Meat from lambs fed FTMR-RSM had a higher level of saturated fatty acids than lambs fed the control diet. The LT muscle meat of lamb fed FTMR-CSM had more unsaturated fatty acids than the control group (p < 0.001). In conclusion, FTMR with cottonseed or rapeseed meal can be fed without causing any adverse effects on Hu lamb.
Identification of new small molecules as dual FoxM1 and Hsp70 inhibitors using computational methods

Background and purpose: FoxM1 and Hsp70 proteins are highly expressed in many cancers. Thus, their inhibition serves as Bonafede targets in cancer treatment. Experimental approach: FDI-6, an inhibitor of FoxM1, was selected as a template, and based on its structure, a new library from the ZINC database was obtained. Virtual screening was then performed using the created pharmacophore model. The second virtual screening phase was conducted with molecular docking to get the best inhibitor for both FoxM1 and Hsp70 active sites. In silico, ADMET properties were also calculated. Finally, molecular dynamics simulation was performed on the best ligand, ZINC1152745, for both Hsp70 and FoxM1 proteins during 100 ns. Findings / Results: The results of this study indicated that ZINC1152745 was stable in the active site of both proteins, Hsp70 and FoxM1. The final scaffold identified by the presented computational approach could offer a hit compound for designing promising anticancer agents targeting both FoxM1 and Hsp70. Conclusion and implications: Molecular dynamics simulations were performed on ZINC1152745 targeting FoxM1 and Hsp70 active sites. The results of several hydrogen bonds, the radius of gyration, RMSF, RMSD, and free energy during the simulations showed good stability of ZINC1152745 with FoxM1 and Hsp70.
Probing Subcellular Iron Availability with Genetically Encoded Nitric Oxide Biosensors

Cellular iron supply is required for various biochemical processes. Measuring bioavailable iron in cells aids in obtaining a better understanding of its biochemical activities but is technically challenging. Existing techniques have several constraints that make precise localization difficult, and the lack of a functional readout makes it unclear whether the tested labile iron is available for metalloproteins. Here, we use geNOps; a ferrous iron-dependent genetically encoded fluorescent nitric oxide (NO) biosensor, to measure available iron in cellular locales. We exploited the nitrosylation-dependent fluorescence quenching of geNOps as a direct readout for cellular iron absorption, distribution, and availability. Our findings show that, in addition to ferrous iron salts, the complex of iron (III) with N,N’-bis (2-hydroxybenzyl)ethylenediamine-N,N’-diacetic acid (HBED) can activate the iron (II)-dependent NO probe within intact cells. Cell treatment for only 20 min with iron sucrose was also sufficient to activate the biosensor in the cytosol and mitochondria significantly; however, ferric carboxymaltose failed to functionalize the probe, even after 2 h of cell treatment. Our findings show that the geNOps approach detects available iron (II) in cultured cells and can be applied to assay functional iron (II) at the (sub)cellular level.
Phases of New Physics in the BAO Spectrum

We show that the phase of the spectrum of baryon acoustic oscillations (BAO) is immune to the effects of nonlinear evolution. This suggests that any new physics that contributes to the initial phase of the BAO spectrum, such as extra light species in the early universe, can be extracted reliably at late times. We provide three arguments in support of our claim: first, we point out that a phase shift of the BAO spectrum maps to a characteristic sign change in the real space correlation function and that this feature cannot be generated or modified by nonlinear dynamics. Second, we confirm this intuition through an explicit computation, valid to all orders in cosmological perturbation theory. Finally, we provide a nonperturbative argument using general analytic properties of the linear response to the initial oscillations. Our result motivates measuring the phase of the BAO spectrum as a robust probe of new physics.
Polyacrylonitrile/Aminated Polymeric Nanosphere Nanofibers as Efficient Adsorbents for Cr(VI) Removal

In this work, polyacrylonitrile/aminated polymeric nanosphere (PAN/APN) nanofibers were prepared by electrospinning of monodispersed aminated polymeric nanospheres (APNs) for removal of Cr(VI) from aqueous solution. Characterization results showed that obtained PAN/APNs possessed nitrogen functionalization. Furthermore, the adsorption application results indicated that PAN/APN nanofibers exhibited a high adsorption capacity of 556 mg/g at 298 K for Cr(VI) removal. The kinetic data showed that the adsorption process fits the pseudo-second order. A thermodynamic study revealed that the adsorption of Cr(VI) was spontaneous and endothermic. The coexisting ions Na+, Ca2+, K+, Cl−, NO3− and PO43− had little influence on Cr(VI) adsorption, while SO42− in solution dramatically decreased the removal performance. In the investigation of the removal mechanism, relative results indicated that the adsorption behavior possibly involved electrostatic adsorption, redox reaction and chelation. PAN/APN nanofibers can detoxify Cr(VI) to Cr(III) and subsequently chelate Cr(III) on its surface. The unique structure and nitrogen functionalization of PAN/APN nanofibers make them novel and prospective candidates in heavy metal removal.
3D printing biocompatible materials with Multi Jet Fusion for bioreactor applications

In the evolving three-dimensional (3D) printing technology, the involvement of different materials in any new 3D printing process necessitates a thorough evaluation of the product’s biocompatibility for biomedical application. Here, we examined the ability of Multi Jet Fusion (MJF)-printed PA-12 to support cell proliferation and osteogenesis. Our results show that leachate from MJF-printed PA-12 does not inhibit the growth of L929 fibroblast and MC3T3e1 osteoblast. The substrate supports the attachment and proliferation of both cell types, though not at a level comparable to conventional polystyrene culture plate. Neither plasma treatment, poly-D-lysine, nor collagen coatings narrowed the gap substantially, suggesting the possible influence of other limiting factors. The substrate can also support MC3T3e1 osteogenesis. However, MJF-printed PA-12 exhibits varying ability in supporting the proliferation of different cell types, especially in subsequent passages. While L929’s proliferation is comparable from passage-to-passage, MC3T3e1’s growth ability is noticeably compromised. Interestingly, our results show that L929 subcultured back to polystyrene plate retains the ability to grow as robustly as those on the conventional plate, suggesting that MJF-printed PA-12 does not permanently impair cell proliferation. In addition, we have shown the successful culture of bacterial Escherichia coli on MJF-printed PA-12. Together, our study demonstrated the potential of MJF-printed PA-12 for biological applications.
FOREST Unbiased Galactic Plane Imaging Survey with the Nobeyama 45 m telescope (FUGIN). V. Dense gas mass fraction of molecular gas in the Galactic plane

Recent observations of the nearby Galactic molecular clouds indicate that the dense gas in molecular clouds has quasi-universal properties on star formation, and observational studies of extra-galaxies have shown a galactic-scale correlation between the star formation rate (SFR) and the surface density of molecular gas. To reach a comprehensive understanding of both properties, it is important to quantify the fractional mass of dense gas in molecular clouds, fDG. In particular, for the Milky Way (MW) there are no previous studies resolving fDG disk over a scale of several kpc. In this study, fDG was measured over 5 kpc in the first quadrant of the MW, based on the CO J = 1–0 data in l = 10°–50° obtained as part of the FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN) project. The total molecular mass was measured using 12CO, and the dense gas mass was estimated using C18O. The fractional masses, including fDG, in the region within ±30% of the distances to the tangential points of the Galactic rotation (e.g., the Galactic Bar, Far-3 kpc Arm, Norma Arm, Scutum Arm, Sagittarius Arm, and inter-arm regions) were measured. As a result, an averaged fDG of $2.9^{+2.6}_{-2.6}$% was obtained for the entirety of the target region. This low value suggests that dense gas formation is the primary factor in inefficient star formation in galaxies. It was also found that fDG shows large variations depending on the structures in the MW disk. In the Galactic arms, fDG was estimated to be ∼4%–5%, while in the bar and inter-arm regions it was as small as ∼0.1%–0.4%. These results indicate that the formation/destruction processes of the dense gas and their timescales are different for different regions in the MW, leading to differences in Star formation efficiencies.
Methods, Algorithms and Tools for System Identification Based on Prior Knowledge

One of the most challenging problems in system identification is that of model structure selection. In this thesis we investigate how three different kinds of prior process knowledge can be utilized to deal with this fundamental issue.The material is presented in four parts. The first one reviews some basic modeling and identification concepts, algorithms and ideas from which the following main three parts take off.The second part considers linear model structures that benefit from prior knowledge about the time constants and resonance frequencies of the underlying system. The idea is to generalize FIR modeling by replacing the delay operator with discrete so-called Laguerre or Kautz filters. While the nice properties of the FIR structure (stability, linear regression formulation, good approximation capability, etc.) are retained, the prior is used to reduce the number of parameters typically needed in the models. Tailored and efficient identification algorithms for these structures are developed and analyzed. The usefulness of the proposed methods is also demonstrated through a number of concrete simulation and application studies.The next approach is termed semi-physical modeling. Starting with simple physical insight into the application, often in terms of a set of unstructured equations, we are here looking for suitable nonlinear transformations of the raw measurements, so as to come up with a reasonable model structure. The suggested modeling procedure shows a first step where symbolic computations are employed to determine a set of physically motivated regressors. We discuss and show how constructive tools from commutative and differential algebra can be applied for this. Then, to avoid unnecessarily complex models, we address the intertwined problem of selecting a "good" subset of these regressors and how to estimate the corresponding parameters. More informal tools such as the programming environment are also treated.The fourth part concerns fuzzy identification where the prior structural knowledge comes in terms of a set of linguistic production rules. We emphasize the close connections between a particular fuzzy model structure on one hand and neural networks, model trees, etc. on the other hand. Several estimation related issues for this fuzzy structure are discussed, e.g., what algorithms to use, the need for regularization, and so on. It is also shown that the expert knowledge easily can be lost in the estimation procedure, unless special parameter restrictions are imposed. In addition, we propose a simplified fuzzy model structure customized to reflect a monotone steady-state behavior. Two applications, a tank and a water heating system, are investigated and successfully modeled within this framework.Finally and quite importantly, prototype software tools supporting the suggested approaches have been designed and implemented. The usefulness of these is illustrated in a number of identification applications.
The Disadvantages of Distance Education Implementation, During the Covid-19 Pandemic: Greek Teachers’ Opinions

In Greece, as in several countries all over the world, schools were closed due to the COVID-19 pandemic, in the 2019-2020 school year. The Greek Ministry of Education tried to operate online platforms so that students could have access to education. The teachers managed to respond to this challenge using mainly their own resources while most of them had not received any relevant training. A nationwide survey was designed investigating teachers' views on distance learning disadvantages. 515 teachers working in Greek primary education sector - both at kindergartens and primary schools- participated in the research. Their answers show five main disadvantages from the distance learning implementation at school education: (a) deficit in the interaction and communication among students and among the teacher and his/her students, (b) the teaching methods used were mainly teacher-centered despite the prescripts of the National Curriculum, (c) inequalities that arose for specific social groups of students, (d) schools’ deficits in infrastructure and insubstantial teachers’ in-service training regarding I.C. T. use, and (e) teachers’ concern about the protection and the maintenance of students’ personal data. Despite these disadvantages mentioned, teachers do not overlook the fact that the distance education implementation during the Covid-19 pandemic was principally an attempt to psychologically empower students learning.
Randomized Successive Projection Algorithm

Résumé – L’algorithme de projections successives (SPA) est un algorithme standard pour la factorisation non-négative de matrices (NMF). Il est basé sur l’hypothèse de séparabilité. En démélange hyperspectral, c’est-à-dire l’extraction des matériaux dans une image hyperspectrale, la séparabilité est équivalente à l’hypothèse du pixel pur et stipule que, pour chaque matériau présent dans l’image, il existe au moins un pixel composé uniquement de ce matériau. SPA est rapide et a été prouvé robuste au bruit, mais il est sensible aux valeurs aberrantes (outliers). Aussi, il est déterministe, et donc pour un problème donné il produit toujours la même solution. Or, il a été démontré empiriquement que l’algorithme non-déterministe vertex component analysis (VCA), lorsqu’il est exécuté un nombre assez grand de fois, produit souvent au moins une solution qui est meilleure que la solution de SPA. Dans cet article, nous cherchons à combiner ces qualités et introduisons une version aléatoire de SPA, appelée RandSPA, qui produit des résultats potentiellement différents à chaque exécution. Il peut être exécuté plusieurs fois pour conserver la meilleure solution, et il est encore garanti robuste au bruit. Des expériences de démélange d’images hyperspectrales montrent que la meilleure solution sur plusieurs exécutions de RandSPA est généralement meilleure que la solution du SPA original. Abstract – The successive projection algorithm (SPA) is a widely used algorithm for nonnegative matrix factorization (NMF). It is based on the separability assumption. In hyperspectral unmixing, that is, the extraction of materials in a hyperspectral image, separability is equivalent to the pure-pixel assumption and states that for each material present in the image there exists at least one pixel composed of only this material. SPA is fast and provably robust to noise, but it not robust to outliers. Also, it is deterministic, so for a given setting it always produces the same solution. Yet, it has been shown empirically that the non-deterministic algorithm vertex component analysis (VCA), when run sufficiently many times, often produces at least one solution that is better than the solution of SPA. In this paper, we combine the best of both worlds and introduce a randomized version of SPA dubbed RandSPA, that produces potentially different results at each run. It can be run several times to keep the best solution, and it is still provably robust to noise. Experiments on the unmixing of hyperspectral images show that the best solution among several runs of RandSPA is generally better that the solution of vanilla SPA.
StcU-2 Gene Mutation via CRISPR/Cas9 Leads to Misregulation of Spore-Cyst Formation in Ascosphaera apis

Ascosphaera apis is the causative agent of honey bee chalkbrood disease, and spores are the only known source of infections. Interference with sporulation is therefore a promising way to manage A. apis. The versicolorin reductase gene (StcU-2) is a ketoreductase protein related to sporulation and melanin biosynthesis. To study the StcU-2 gene in ascospore production of A. apis, CRISPR/Cas9 was used, and eight hygromycin B antibiotic-resistant transformants incorporating enhanced green fluorescent protein (EGFP) were made and analyzed. PCR amplification, gel electrophoresis, and sequence analysis were used for target gene editing analysis and verification. The CRISPR/Cas9 editing successfully knocked out the StcU-2 gene in A. apis. StcU-2 mutants had shown albino and non-functional spore-cyst development and lost effective sporulation. In conclusion, editing of StcU-2 gene has shown direct relation with sporulation and melanin biosynthesis of A. apis; this effective sporulation reduction would reduce the spread and pathogenicity of A. apis to managed honey bee. To the best of our knowledge, this is the first time CRISPR/Cas9-mediated gene editing has been efficiently performed in A. apis, a fungal honey bee brood pathogen, which offers a comprehensive set of procedural references that contributes to A. apis gene function studies and consequent control of chalkbrood disease.
STPIECE: Stata module to estimate piecewise-constant hazard rate models

stpiece is a wrapper that uses a number of existing Stata routines to estimate piecewise-constant hazard rate models. A piecewise-constant model is an exponential hazard rate model where the constant rate is allowed to vary within pre-defined time-segments. Estimation of this model in Stata is usually a multi-step process, since one must manually define the time pieces and if necessary split the spells. stpiece automates this process.