Miracle-dz/UniFAR-FTUs huggingface dataset:
Positive Interval System Dynamics Explored via Vertex Representatives vs. Vertex Majorizations

The paper explores the properties of positive interval dynamic systems in continuous-time, via two types of techniques, and develops a comparative study between the two approaches. The first type is based on the properties of the row and column representatives corresponding to the vertex set of the interval matrix $\mathbb {A}=[A^{-}, A^{+}]\subset \mathbb {R}^{n\times n}$ The second type employs the properties of the dominant vertex $A^{+}$ of the interval matrix. The results, separately derived for the two approaches, show the equivalence between the Hurwitz stability of matrix $A^{+}$, the existence of several classes of Lyapunov functions, and the existence of several classes of exponentially decreasing sets that are positively invariant with respect to the interval system dynamics.
Registration and Deformation of 3D Shape Data through Parameterized Formulation

In this paper, we investigate conventional registration implementation, consisting of rotation and translation, to design the most precise registration so as to accurately restore the 3D shape of an object. To achieve the most accurate registration, our registration implementation needs robustness against data noise, or initial pose and position of data. To verify the accuracy of our implemented registration, we compare the registration behavior with the registration behavior of conventional methods, and evaluate the numerical accuracy of transformation parameter obtained by our registration. However, registration by rigid-body transformation is not enough for modeling and shape comparison: registration with deformation is needed. In this paper, we extend our robust registration to simultaneously estimate the shape parameter as well as the rigid-body transformation parameter. This extension method assumes that the deformation is formulated strictly from the deformation mechanism. We additionally introduce the applications of our extension method.
Feature Selection for Effective Health Index Diagnoses of Power Transformers

This letter investigates an approach based on feature selection and classification techniques to reduce assessment complexities of power transformers. This approach decreases the number of features by extracting the most influential ones when determining the transformers health index (HI). Several filters and wrapper-based feature selection methods are investigated. The effectiveness of the selected features is validated through performance evaluations of various classification models. The experimental results demonstrate that water content, acidity, breakdown voltage, and FFA (Furan), are the most influential testing parameters in determining the transformer HI.
DISMEVAL Developing and validating disease management evaluation methods for European healthcare systems

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Multi-Band Balanced Couplers With Broadband Common-Mode Suppression

Three novel single-/multi-band balanced couplers with wide-band common-mode suppression are proposed. In these double-functionality balanced-coupler architectures, double-sided parallel-strip line 180° phase inverters are used to realize the broadband common-mode rejection. Furthermore, by loading quarter-wavelength open/short-ended coupled lines at all ports of the single-band differential-mode coupler, dual/triple-band balanced operation with high isolation for the differential-mode power-division bands can be realized into it. For practical verification, three balanced couplers with single-, dual-, and triple-band operation at 1 GHz, 0.72/1.24 GHz, and 0.66/1/1.36 GHz, respectively, are constructed in microstrip technology and tested.
Detecting Sex From Handwritten Examples

There are several tasks that human excel at and computers do not and vice-versa. Just until a few years ago computers were as good as a storage for images and videos. However, in the past 6 years with the boon in artificial neural network, labeled data and computation power; machines have started becoming smart at tasks like recognizing images, detecting different objects in images, captioning images, understanding and summarizing videos, detecting semantic actions in videos and so on. Deep learning researchers and practitioners have started demonstrating notable performance of AI(Artificial Intelligence) on many different tasks that pushes the boundaries and as a continuation of that process, we took one specific problem to solve using deep learning that even human can not solve. We have taken Bangla handwritten characters, then trained them applying several deep learning techniques such as Convolutional Neural Network and Recurrent Neural Network to predict the sex of the writer. Consequently, we have got 91.85% accuracy rate and also demonstrated further analysis of the results that we got.
Proximal Alternating Minimization for Analysis Dictionary Learning and Convergence Analysis

The sparse analysis model is an alternative approach to the sparse synthesis model that has emerged recently. Most analysis dictionary learning problems based on the sparse analysis model require solving a class of challenging nonsmooth and even nonconvex optimization problems. Despite the fact that many numerical methods have been developed for solving these problems, it remains an open problem to find a numerical method that is not only empirically fast, but also has mathematically guaranteed strong convergence. In this paper, to promote stronger sparsity in solutions than the $\ell _{1}$-norm, we employ the nonsmooth and nonconvex $\ell _{1/2}$-norm as a regularizer, and then we propose to use the proximal alternating minimization scheme for solving the nonconvex and nonsmooth problem, leading to an efficient and fast algorithm. More importantly, a rigorous convergence analysis shows that the proposed method satisfies the global convergence property: The whole sequence of iterates is convergent and converges to a critical point. The proposed algorithm has two stages: the analysis sparse-coding stage and the analysis dictionary-update stage. Besides the theoretical soundness, the practical benefit of the proposed method is validated by the synthetic and real-world data. Experiments show that the proposed method achieves better results with faster convergence compared to the state-of-the-art algorithms.
Generation of motor neurons requires spatiotemporal coordination between retinoic acid and Mib-mediated Notch signaling

ABSTRACT Mind bomb (Mib) is an E3 ubiquitin ligase that activates the Notch signaling pathway. A previous study demonstrated that the generation of late-born GABAergic neurons may be regulated by the interplay between Mib and retinoic acid (RA). However, the relationship between Mib function and the retinoid pathway during the generation of late-born motor neurons remains unclear. We investigated the differentiation of neural progenitors into motor neurons by inhibition of Notch signaling and administration of RA to Tg[hsp70-Mib:EGFP] embryos. The number of motor neurons in the ventral spinal cord increased or decreased depending on the temporal inhibition of Mib-mediated Notch signaling. Inhibition of the retinoid pathway by citral treatment had a synergistic effect with overexpression of Mib:EGFP on the generation of ectopic motor neurons. Additionally, the proteolytic fragment of Mib was detected in differentiated P19 cells following treatment with RA. Our observations imply that the function of Mib may be attenuated by the retinoid pathway, and that Mib-mediated Notch signaling and the retinoid pathway play critical roles in the spatiotemporal differentiation of motor neurons.
Deep analysis of Loop L1 HVRs1-4 region of the hexon gene of adenovirus field strains isolated in Poland

Background To date, studies on loop L1 HVRs1-4 region of the hexon gene in fowl adenovirus genome (FAdVs) lack comprehensive molecular data. In this study detailed prospectively obtained sequences from field adenovirus strains, NVRI, Poland have been analyzed. Methods Overall hundred and thirty seven adenovirus strains were collected, evaluated, and examined of hyper variable loop L1 region HVRs1-4 of the hexon gene for the presence of similarity, mutations, tertiary structure, and spinal conformation. Results Sequences were characterized, and divided for five species and seven types, FAdV-A-E/FAdV-1/2/4/5/7/8a/8b/11. The presence of predicted tertiary structure depending on type/species were determined. Analysis of specific selected sequences: GQMTN 1/A, 7/E, and 8b/E, GQMTT 2/11/D, GQLSN 4/C, GQMTH 5/B, and GQMSN 8a/E in examined HVRs1-4 Loop L1 region of hexon gene compared to tertiary structure indicated that this visibly conservative region represents the antigenic binging activity. Conclusion This is the first molecular study on tertiary structure on HVRs1-4 region in adenovirus genome conducted in Poland. Analysis indicated specific sequence in Loop L1 HVR1-4 region which is strictly responsible for antibodies binding. This information could assist during the process connected with specific preventive strategies based on their molecular genome investigation and new facilitate studies. This study will help to better understand the mechanisms of pathogenicity of adenovirus strains provide a guide for disease control in birds.
Virtual screening of a natural compound library at orthosteric and allosteric binding sites of the neurotensin receptor

Abstract Molecular dynamics (MD) simulation using the AMBER force field has been performed on the neurotensin (NT) receptor, a class A type G-protein-coupled receptor in its activated conformation co-crystallized with the non-peptide agonists. For structure-based hit molecule identification via natural chemical compound library, orthosteric sites on NT receptor have been mapped by docking using AutoDock4.0 and Vina with the known agonists and antagonists SR48692, SR142948, ML301 and ML314 of the receptor. Furthermore, clustering analysis on the MD trajectories by SIMULAID has been performed to filter receptor conformations for the allosteric binders from the Otava natural compound library. Comparative mappings of contrasting binding region patterns have been done between the crystal structure orthosteric sites as well as the binding regions in the SIMULAID-based cluster center conformations from MD trajectories with the FTmap server using the small organic molecule fragments as the probes. The distinct binding region in the cluster-based conformations in the extracellular region of the receptor has been identified for targeted docking by Otava natural chemical compound library using AutoDock4.0 and Vina docking suites to obtain putative allosteric binders. A group of compounds from the Otava library has been identified as showing high free energy in both AutoDock4.0 and Vina docking suites. Biophysical assessments on the natural compound computational hit molecules will be done to identify lead structures from the hit molecules. Communicated by Ramaswamy H. Sarma
Comparing decoding mechanisms for parsing argumentative structures

Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the 'argumentative microtext corpus' [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp.Â 801-815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance.
Total nutrient digestibility and small intestine starch digestion in Nellore and Angus young bulls fed a whole shelled corn diet

Eighteen Nellore and 18 Angus young bulls with BW of 381 ± 12 kg were randomly assigned into two feeding groups (whole shelled corn [WSC] or ground corn with silage [GC]) to evaluate the interaction of breed and diet on total nutrient digestibility, pancreatic α-amylase, and maltase activity and SLC5A1expression in the small intestine. Experimental diets (DM basis) included (a) a diet containing 30% corn silage and 70% GC and soya bean meal-based concentrate and (b) a diet containing 85% WSC and 15% of a soya bean meal- and mineral-based pelleted supplement. The treatments were Nellore fed GC diet; Nellore fed WSC diet; Angus fed GC diet; and Angus fed WSC diet. Total faecal collection for the digestibility trial occurred from day 48 until day 50 of the experimental period. Feeding the WSC diet reduced DM and NDF intake (p < 0.01). Angus had greater DM and nutrient intake in kg/day (p < 0.01). However, there was no breed effect on DM and nutrient intakes based on percentage of BW (p > 0.19). Angus had greater starch digestibility (p = 0.03) than Nellore. Cattle fed the WSC diet had greater DM, NDF and starch digestibility (p < 0.01) compared with those fed the GC diet. The activity of pancreatic α-amylase (U/g of protein) was greater in Nellore (p < 0.01) and was not affected by diet (p = 0.52). In duodenum, maltase activity (U/g of protein) was greater in bulls fed GC diet (p = 0.02). Expression of the gene SLC5A1was not affected by breed or diet (p > 0.05). In conclusion, Nellore had less capacity to digest starch. However, they did not have less pancreatic α-amylase and duodenal maltase activity compared to Angus. The use of the WSC diet increases DM and total nutrient digestibility.
Two-Dimensional Non-periodic Metasurface for Dual Polarization Retroreflection

Traditionally. , retroreflection (or blazing) of an obliquely incident wave can be realized by periodic blazed gratings. In this work, the non-periodic design method is used to achieve retroreflection for both TE and TM plane wave. We discretize the finite surface into subwavelength elements and characterize the element with its phase response. The scattering response of the entire surface (demonstrated by retroreflection case in this paper) can then be determined by optimizing the local phase response for both polarizations. The computation cost is low, and the algorithm can be easily adjusted to reach more flexible objectives. This theoretical method has been verified by both full-wave simulation and measurement at 10 GHz.
Clinicoetiological profile, immediate outcome and short-term follow-up of term babies with hyperbilirubinemia

Neonatal Jaundice is one of the most common conditions requiring medical attention in newborn babies. Approximately 60% of term babies and 80% of preterm babies develop jaundice in first week of life. Neonatal jaundice refers to yellowish discolouration of skin and sclera of newborn babies that results in accumulation of unconjugated bilirubin in skin and mucous membrane. This is associated with a raised level of bilirubin in the circulation, a condition known as Hyperbilirubinemia.
Lutzomyia longipalpis Saliva Induces Heme Oxygenase-1 Expression at Bite Sites

Sand flies bite mammalian hosts to obtain a blood meal, driving changes in the host inflammatory response that support the establishment of Leishmania infection. This effect is partially attributed to components of sand fly saliva, which are able to recruit and activate leukocytes. Our group has shown that heme oxygenase-1 (HO-1) favors Leishmania survival in infected cells by reducing inflammatory responses. Here, we show that exposure to sand fly bites is associated with induction of HO-1 in vivo. Histopathological analyses of skin specimens from human volunteers experimentally exposed to sand fly bites revealed that HO-1 and Nrf2 are produced at bite sites in the skin. These results were recapitulated in mice ears injected with a salivary gland sonicate (SGS) or exposed to sand fly bites, indicating that vector saliva may be a key factor in triggering HO-1 expression. Resident skin macrophages were the main source HO-1 at 24–48 h after bites. Additionally, assays in vivo after bites and in vitro after stimulation with saliva both demonstrated that HO-1 production by macrophages was Nrf2-dependent. Collectively, our data demonstrates that vector saliva induces early HO-1 production at the bite sites, representing a major event associated with establishment of naturally-transmitted Leishmania infections.
The Pytorch-kaldi Speech Recognition Toolkit

The availability of open-source software is playing a remarkable role in the popularization of speech recognition and deep learning. Kaldi, for instance, is nowadays an established framework used to develop state-of-the-art speech recognizers. PyTorch is used to build neural networks with the Python language and has recently spawn tremendous interest within the machine learning community thanks to its simplicity and flexibility.The PyTorch-Kaldi project aims to bridge the gap between these popular toolkits, trying to inherit the efficiency of Kaldi and the flexibility of PyTorch. PyTorch-Kaldi is not only a simple interface between these software, but it embeds several useful features for developing modern speech recognizers. For instance, the code is specifically designed to naturally plug-in user-defined acoustic models. As an alternative, users can exploit several pre-implemented neural networks that can be customized using intuitive configuration files. PyTorch-Kaldi supports multiple feature and label streams as well as combinations of neural networks, enabling the use of complex neural architectures. The toolkit is publicly-released along with a rich documentation and is designed to properly work locally or on HPC clusters.Experiments, that are conducted on several datasets and tasks, show that PyTorch-Kaldi can effectively be used to develop modern state-of-the-art speech recognizers.
Direct Interaction between the Two Z Ring Membrane Anchors FtsA and ZipA

To divide, most bacteria first construct a protein machine at the plane of division and then recruit the machinery that will synthesize the division septum. In Escherichia coli, this first stage involves the assembly of FtsZ polymers at midcell, which directly bind to membrane-associated proteins FtsA and ZipA to form a discontinuous ring structure. Although FtsZ directly binds both FtsA and ZipA, it is unclear why FtsZ requires two separate membrane tethers. Here, we uncover a new direct interaction between the tethers, which involves a helix within FtsA that is adjacent to its ATP binding pocket. Our findings imply that in addition to their known roles as FtsZ membrane anchors, FtsA and ZipA may regulate each other’s structure and function. ABSTRACT The initiation of Escherichia coli cell division requires three proteins, FtsZ, FtsA, and ZipA, which assemble in a dynamic ring-like structure at midcell. Along with the transmembrane protein ZipA, the actin-like FtsA helps to tether treadmilling polymers of tubulin-like FtsZ to the membrane. In addition to forming homo-oligomers, FtsA and ZipA interact directly with the C-terminal conserved domain of FtsZ. Gain-of-function mutants of FtsA are deficient in forming oligomers and can bypass the need for ZipA, suggesting that ZipA may normally function to disrupt FtsA oligomers, although no direct interaction between FtsA and ZipA has been reported. Here, we use in vivo cross-linking to show that FtsA and ZipA indeed interact directly. We identify the exposed surface of FtsA helix 7, which also participates in binding to ATP through its internal surface, as a key interface needed for the interaction with ZipA. This interaction suggests that FtsZ’s membrane tethers may regulate each other’s activities. IMPORTANCE To divide, most bacteria first construct a protein machine at the plane of division and then recruit the machinery that will synthesize the division septum. In Escherichia coli, this first stage involves the assembly of FtsZ polymers at midcell, which directly bind to membrane-associated proteins FtsA and ZipA to form a discontinuous ring structure. Although FtsZ directly binds both FtsA and ZipA, it is unclear why FtsZ requires two separate membrane tethers. Here, we uncover a new direct interaction between the tethers, which involves a helix within FtsA that is adjacent to its ATP binding pocket. Our findings imply that in addition to their known roles as FtsZ membrane anchors, FtsA and ZipA may regulate each other’s structure and function.
Two Modes of Riboflavin-Mediated Extracellular Electron Transfer in Geobacter uraniireducens

Anaerobes respire extracellular electron acceptors by extracellular electron transfer (EET). It is widely recognized that flavins can act as electron shuttles to facilitate this process. Flavin synthesis genes are widely distributed in Geobacter species. However, the functions of flavins in the EET of Geobacter species are unclear. Here, we demonstrate that G. uraniireducens can secrete abundant riboflavin (up to 270 nM) to facilitate EET. When an electrode was used as the electron acceptor, the quick recovery of anodizing current after anolyte replacement and the electrochemical behavior of the G. uraniireducens biofilm characterized by differential pulse voltammetry suggest that the self-secreted riboflavin promoted EET by serving as bound redox cofactors for cytochromes. On the contrary, when Fe(III) oxide was the electron acceptor, free riboflavin acted as electron shuttle to mediate the reduction of Fe(III) oxide. The results demonstrate the flexibility of flavins in EET, suggesting that the properties of electron acceptors can affect the binding mode of extracellular flavins, and broaden the knowledge of the EET of Geobacter species.
Analysis of large sparse graphs using regular decomposition of graph distance matrices

Statistical analysis of large and sparse graphs is a challenging problem in data science due to the high dimensionality and nonlinearity of the problem. This paper presents a fast and scalable algorithm for partitioning such graphs into disjoint groups based on observed graph distances from a set of reference nodes. The resulting partition provides a low-dimensional approximation of the full distance matrix which helps to reveal global structural properties of the graph using only small samples of the distance matrix. The presented algorithm is inspired by the information-theoretic minimum description principle. We investigate the performance of this algorithm for selected real data sets and for synthetic graph data sets generated using stochastic block models and power-law random graphs, together with analytical considerations for sparse stochastic block models with bounded average degrees.