Miracle-dz/UniFAR-FTUs huggingface dataset:
Alpha1-antitrypsin protects the immature mouse brain following hypoxic-ischemic injury

Introduction: Preterm brain injury often leads to lifelong disabilities affecting both cognitive and motor functions, and effective therapies are limited. Alpha1-antitrypsin (AAT), an endogenous inhibitor of serine proteinases with anti-inflammatory, anti-apoptotic, and cytoprotective properties, might be beneficial in treating preterm brain injury. The aim of this study was to investigate whether AAT has neuroprotective effects in a mouse preterm brain injury model. Methods: Preterm brain injury was induced on postnatal day 5, and mouse pups’ right common carotid arteries were cut between two ligations followed by hypoxia induction. Brain injury was evaluated through immunohistochemistry staining and magnetic resonance imaging. Fluoro-Jade B and immunohistochemistry staining were performed to investigate the neuronal cell death and blood-brain barrier (BBB) permeability. The motor function and anxiety-like behaviors were revealed by CatWalk gait analysis and the open field test. Results: After hypoxia-ischemia (HI) insult, brain injury was alleviated by AAT treatment, and this was accompanied by reduced BBB permeability, reduced neuronal cell death and caspase-3 activation, and inhibition of microglia activation. In addition, AAT administration significantly improved HI-induced motor function deficiencies in mice. The neuroprotective effect of AAT was more pronounced in male mice. Conclusion: AAT treatment is neuroprotective against preterm brain injury in neonatal mice, and the effect is more pronounced in males.
Superficial white matter shape characterization using hierarchical clustering and a multi-subject bundle atlas

The description of the superficial white matter (SWM) functional and structural organization is still an unachieved task. In particular, their shape has not been assessed in detail using diffusion Magnetic Resonance Imaging (dMRI) tractography. This work aims to characterize the different shapes of the short-range association connections present in an SWM multi-subject bundle atlas derived from probabilistic dMRI tractography datasets. First, we calculated a representative centroid shape for each atlas bundle. Next, we computed a distance matrix that encodes the similarity between every pair of centroids. For the distance matrix computation, centroids were first aligned using a streamline-based registration, reducing the 3D spatial separation effect and allowing us to focus only on shape differences. Then, we applied a hierarchical clustering algorithm over the affinity graph derived from the distance matrix. As a result, we obtained ten classes with distinctive shapes, ranging from a straight line form to U and C arrangements. The most predominant shapes were: (i) short open U, (ii) short closed U, and (iii) short C. Moreover, we used the shape information to filter out noisy streamlines in the atlas bundles and applied an automatic segmentation algorithm to 25 subjects of the HCP database. Our results show that the filtering steps help to segment more dense bundles with fewer outliers, improving the identification of the brain’s short fibers.
The transfer learning gap: quantifying transfer learning in a medical image case

Transfer learning is a widely used technique in medical imaging and other research fields where a scarcity of available data limit the training of machine learning algorithms. Despite its widespread use and extensive supporting body of research, the specific mechanisms behind transfer learning are not completely understood. In this work, we quantify the effectiveness of transfer learning in medical image classification scenarios for different numbers of training set images. We trained ResNet50, a popular deep learning model used in medical image classification, using two scenarios: 1) applying transfer learning to a pre-trained network and 2) training the same model from scratch (i.e., starting with randomly selected weights). We analyzed the performance of the model under both scenarios as the number of training set images increased from 5,000 to 160,000 medical images. We introduced and evaluated a metric, the transfer learning gap (TLG), to quantify the differences between the two scenarios. The TLG measured the difference in the area under the loss curves (AULCs) when transfer learning was applied and when the model was trained from scratch. Our experiments show that as the training set size increases, the TLG trends to zero, suggesting that the advantage of using transfer learning decreases. The trend in the AULC suggests a training set size where the two scenarios would have equal losses. At this point, the model reaches the same performance regardless of if transfer learning or training from scratch was used. This study is important because it provides a novel metric to understand and quantify the effect of transfer learning.
On zeros of sampled systems

The Astrom-Hagander-Sternby theorem (1984) on asymptotic zeros of the pulse transfer function is extended by determining the accuracy of the asymptotic results for both the sampling and the intrinsic zeros when the sampling interval is small. Closed form formulae are derived that express the degree of the principal term of Taylor expansion of the difference between the true zeros and asymptotic ones as a function of the relative degree of the underlying continuous-time system, and the value of the corresponding coefficient itself. The results are illustrated by an example.
Research on Surface Defect Detection of Aluminum Based on Improved Cascade R-CNN

Aluminum profiles are widely used in many industries with good characteristics. Surface defects of aluminum profiles will affect the quality, reliability and safety of products. In recent years, deep learning has been applied in aluminum profile surface defect detection. However, there are still some problems unsolved. The tiny and narrow defects are easily ignored in feature extraction. The length-width ratio of different aluminum surface defects varies widely, but the fixed anchor boxes in traditional deep learning algorithms will easily miss defects. Due to the lack of training on background images, some backgrounds are easily misidentified as defects. To address these problems, a novel Cascade R-CNN network with deformable convolution, guided anchoring and sample augmentation (GAE-Cascade R-CNN model) is proposed. The deformable convolution enhances the feature extraction ability of the network. The guided anchoring reduces the missed detection by automatically generating anchors to match narrow defects. The sample augmentation effectively reduces missed defect detection by training a large number of background images. The experimental results show that the proposed GAE-Cascade R-CNN model can achieve accuracy of 98.85% for identification and mean average precision (mAP) of 80.55% for surface defect detection of aluminum profiles. The performance of the proposed network outperforms other deep learning methods in terms of both missed detection rate and false detection rate.
Propagation of SH-waves in a layered medium

Summary. A set of recurrence relations similar to that of Kennett suitable for SH-wave generation in an (n+ l)-layered half-space is presented. The recurrence relations contain no growing terms, thus providing a stable and efficient algorithm for computing complete SH synthetic seismograms. The complete expansion of these recurrence relations gives the explicit form of the transfer function for SH-waves. The transfer function for a point source in layer s of the stratification is a series of 2n terms in the denominator and a series of 2n−s+1 terms in the numerator. The result of Wang from ray summation is shown to be a special case of our general result. Numerical comparison of the algorithm of this paper with the propagator matrix method is also made.
Algorithmic Advances in Stochastic Combinatorial Optimization and Applications

In this dissertation, we study two-stage stochastic combinatorial optimization (SCO) problems in which both first and second stage decisions include some binary variables. The common theme is the use of decomposition techniques together with valid inequalities to solve these problems. Potential computational speed-ups are first explored in solving SCOs with pure binary first-stage variables and mixedbinary second-stage variables. We propose new cuts of value function convexification, and a decomposition procedure for cut generation for the second-stage mixed-integer programming problem. These enhancements result in approximately 50% reduction in CPU time, compared to the best performance reported in the literature. Next, we develop a coupled branch-and-bound algorithm for a broader class of stochastic mixed-integer programming problems allowing continuous as well as integer variables in both stages. We present the finite convergence property of this algorithm, and illustrate the method via a numerical instance. We next allow the random variables in the model to have infinitely many outcomes, and propose the first decompositionbased sequential sampling algorithm for two-stage SCOs. Asymptotic convergence properties of this algorithm are presented and preliminary computational results are also reported. Finally, we develop a stochastic mixed-integer programming model to design the next-generation IP-over-optical network. Such network must ensure the feasibility of the state-of-the-art network restoration under any potential network ii failure. We propose customized decomposition methods and corresponding valid inequalities to solve large-scale practical instances.
Hypoxia enhances interactions between Na+/H+ exchanger isoform 1 and actin filaments via ezrin in pulmonary vascular smooth muscle

Exposure to hypoxia, due to high altitude or chronic lung disease, leads to structural changes in the pulmonary vascular wall, including hyperplasia and migration of pulmonary arterial smooth muscle cells (PASMCs). Previous studies showed that hypoxia upregulates the expression of Na+/H+ exchanger isoform 1 (NHE1) and that inhibition or loss of NHE1 prevents hypoxia-induced PASMC migration and proliferation. The exact mechanism by which NHE1 controls PASMC function has not been fully delineated. In fibroblasts, NHE1 has been shown to act as a membrane anchor for actin filaments, via binding of the adaptor protein, ezrin. Thus, in this study, we tested the role of ezrin and NHE1/actin interactions in controlling PASMC function. Using rat PASMCs exposed to in vitro hypoxia (4% O2, 24 h) we found that hypoxic exposure increased phosphorylation (activation) of ezrin, and promoted interactions between NHE1, phosphorylated ezrin and smooth muscle specific α-actin (SMA) as measured via immunoprecipitation and co-localization. Overexpression of wild-type human NHE1 in the absence of hypoxia was sufficient to induce PASMC migration and proliferation, whereas inhibiting ezrin phosphorylation with NSC668394 suppressed NHE1/SMA co-localization and migration in hypoxic PASMCs. Finally, overexpressing a version of human NHE1 in which amino acids were mutated to prevent NHE1/ezrin/SMA interactions was unable to increase PASMC migration and proliferation despite exhibiting normal Na+/H+ exchange activity. From these results, we conclude that hypoxic exposure increases ezrin phosphorylation in PASMCs, leading to enhanced ezrin/NHE1/SMA interaction. We further speculate that these interactions promote anchoring of the actin cytoskeleton to the membrane to facilitate the changes in cell movement and shape required for migration and proliferation.
Two-dimensional microwave imaging approach based on a genetic algorithm

A multi-illumination multiview approach to microwave imaging is proposed, which is based on a genetic algorithm (GA). The inverse problem is recast in an optimization problem, solved in the framework of the Born approximation. The formulation of the approach is described and images of reconstructed circular (multilayer) cylinders are reported.
Free-carrier absorption at low temperatures in uniaxially stressed n-type Ge, Si and GaAs

The effect of uniaxial compressive stress of up to 6*109 dyn cm-2 on free-carrier absorption in various doped Ge, Si and GaAs crystals has been investigated. Absorption measurements were made at 18.5K and 79K over the wavelength range 8 mu m to 24 mu m with radiation polarized parallel or perpendicular to stress. The latter was applied along (111), (110) or (100) directions in Ge, (110) or (100) directions in GaAs but (100) directions only in Si. Changes in absorption produced in all but one of the germanium crystals are explained by a simple electron-transfer model in which the total electron concentration in the conduction band remains constant and electrons merely transfer between the (111) multivalley states as they are split by stress. For the other germanium crystal, the behaviour under (111) stress was similar to that found in silicon under (100) stress.
Zero-sum problems in finite cyclic groups

The purpose of this thesis is to investigate some open problems in the area of combinatorial number theory referred to as zero-sum theory. A zero-sequence in a finite cyclic group G is said to have the basic property if it is equivalent under group automorphism to one which has sum precisely IGI when this sum is viewed as an integer. This thesis investigates two major problems, the first of which is referred to as the basic pair problem. This problem seeks to determine conditions for which every zero-sequence of a given length in a finite abelian group has the basic property. We resolve an open problem regarding basic pairs in cyclic groups by demonstrating that every sequence of length four in Zp has the basic property, and we conjecture on the complete solution of this problem. The second problem is a 1988 conjecture of Kleitman and Lemke, part of which claims that every sequence of length n in Zn has a subsequence with the basic property. If one considers the special case where n is an odd integer we believe this conjecture to hold true. We verify this is the case for all prime integers less than 40, and all odd integers less than 26. In addition, we resolve the Kleitman-Lemke conjecture for general n in the negative. That is, we demonstrate a sequence in any finite abelian group isomorphic to Z2p (for p ~ 11 a prime) containing no subsequence with the basic property. These results, as well as the results found along the way, contribute to many other problems in zero-sum theory.
CaSPDS, a Spermidine Synthase Gene from Pepper (Capsicum annuum L.), Plays an Important Role in Response to Cold Stress

Spermidine synthase (SPDS) is a key enzyme in the polyamine anabolic pathway. SPDS genes help regulate plant response to environmental stresses, but their roles in pepper remain unclear. In this study, we identified and cloned a SPDS gene from pepper (Capsicum annuum L.), named CaSPDS (LOC107847831). Bioinformatics analysis indicated that CaSPDS contains two highly conserved domains: an SPDS tetramerisation domain and a spermine/SPDS domain. Quantitative reverse-transcription polymerase chain reaction results showed that CaSPDS was highly expressed in the stems, flowers, and mature fruits of pepper and was rapidly induced by cold stress. The function of CaSPDS in cold stress response was studied by silencing and overexpressing it in pepper and Arabidopsis, respectively. Cold injury was more serious and reactive oxygen species levels were greater in the CaSPDS-silenced seedlings than in the wild-type (WT) seedlings after cold treatment. Compared with the WT plants, the CaSPDS-overexpression Arabidopsis plants were more tolerant to cold stress and showed higher antioxidant enzyme activities, spermidine content, and cold-responsive gene (AtCOR15A, AtRD29A, AtCOR47, and AtKIN1) expression. These results indicate that CaSPDS plays important roles in cold stress response and is valuable in molecular breeding to enhance the cold tolerance of pepper.
Contribution of x-ray topography and high-resolution diffraction to the study of defects in SiC

A short review is presented of the various synchrotron white beam x-ray topography (SWBXT) imaging techniques developed for characterization of silicon carbide (SiC) crystals and thin films. These techniques, including back-reflection topography, reticulography, transmission topography, and a set of section topography techniques, are demonstrated to be particularly powerful for imaging hollow-core screw dislocations (micropipes) and closed-core threading screw dislocations, as well as other defects, in SiC. The geometrical diffraction mechanism commonly underlying these imaging processes is emphasized for understanding the nature and origins of these defects. Also introduced is the application of SWBXT combined with high-resolution x-ray diffraction techniques to complete characterization of 3C/4H or 3C/6H SiC heterostructures, including polytype identification, 3C variant mapping, and accurate lattice mismatch measurements.
Ethiopians' knowledge of and attitudes toward epilepsy: A systematic review and meta-analysis

Background Epilepsy remains one of the world's most common neurological diseases, but it appears to be widely misunderstood, particularly in under-resourced countries like Ethiopia. Improving individuals' knowledge and attitude toward epilepsy is critical for reducing the multifaceted impacts of epilepsy. Therefore, in this study, we sought to estimate the pooled levels of good knowledge and a favorable attitude toward epilepsy and also identify the associated factors using available data collected from different segments of the population. Methods Articles were searched in international electronic databases. A standardized Microsoft Excel spreadsheet and STATA software version 16 were used for data extraction and analysis, respectively. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist was used to write this report. The random-effect meta-analysis model was used to estimate Der Simonian-Laird's pooled effect. Statistical heterogeneity of the meta-analysis was checked via Higgins and Thompson's I2 statistics (0–100%), and Cochran's Q test at P < 0.10. Subgroups, based on the study regions, and sensitivity analyses were also performed. Publication bias was examined subjectively using funnel plots and objectively using the nonparametric rank correlation test of Begg and the regression-based test of Egger for small study effects with P < 0.05 considered to indicate potential publication bias. Furthermore, the Trim-and-fill method of Duval and Tweedie was used to explore sources of publication bias for the favorable level of attitudes toward epilepsy. Result A total of 12 studies with 6,373 study participants and 10 studies with 5,336 study participants were included to estimate the pooled level of good epilepsy knowledge and favorable attitudes respectively. The overall estimated levels of good epilepsy knowledge and favorable attitudes toward epilepsy among Ethiopians were 47.37% [(95% CI: 35.00, 59.74), I2 = 99.2, P < 0.001] and 46.83%[(95% CI: 32.75, 60.90), I2 = 99.2, P < 0.001] respectively. Subgroup analysis revealed that the pooled level of good epilepsy knowledge was 48.51% [(95% CI: 38.95, 58.06), I2 = 95.6%, P < 0.001] in the Amhara region. Conclusion In the current review, we found out that there is a huge knowledge gap and an unfavorable level of attitudes towardepilepsy, which demand immediate public health action as well as a targeted policy intervention.
Corrections to scaling and self-duality in the restricted solid-on-solid model

The corrections to scaling at and above the roughening transition TR in the restricted solid-on-solid model are studied by means of finite-size scaling for semi-infinite strips of width 2 to 10. It is shown that at a temperature TSD not far above the roughening temperature, where the restricted solid-on-solid model is invariant under the duality transformation of the five-state clock model, the fugacity of the sine-Gordon operator must vanish. For the dual truncated planar model this means that the core energy of the vortices diverges. Between TS and TR the corrections to scaling do not reach their asymptotic behaviour, but are dominated by the contributions from the ( Delta phi )4 operator associated with the restriction to steps of height one.
Generic Method for Deriving the General Shaking Force Balance Conditions of Parallel Manipulators with Application to a Redundant Planar 4-RRR Parallel Manipulator

This paper proposes a generic method for de- riving the general shaking force balance conditions of parallel manipulators. Instead of considering the balancing of a par- allel manipulator link-by-link or leg-by-leg, the architecture is considered altogether. The first step is to write the linear momentum of each ele- ment. The second step is to substitute the derivatives of the loop equations, by which the general force balance conditions are obtained. Subsequently specific kinematic conditions are investigated in order to find advantageous, simple balance so- lutions. As an example, the method is applied to a planar 4-RRR par- allel manipulator, for which the force balance conditions and solutions are discussed and illustrated for each step respec- tively. By including the loop equations, linear relations of the motion among mechanism elements lead to an increase of bal- ance possibilities. For specific kinematic conditions, additional linear relations among the motion of mechanism elements may be obtained, resulting in another increase of balance possibil- ities. For the latter, symmetric motion is an important feature for which a 4-RRR manipulator is advantageous.
Compactly supported multi-wavelets

In this paper we show some construction of compactly supported multi-wavelets in \(L^2(\mathbb{R}^d)\), \(d \geq 2\) which is based on the one-dimensional case, when \(d=1\). We also demonstrate that some methods, which are useful in the construction of wavelets with a compact support at \(d=1\), can be adapted to higher-dimensional cases if \(A \in M_{d \times d}(\mathbb{Z})\) is an expansive matrix of a special form.
Subepidermal Low-Echogenic Band—Its Utility in Clinical Practice: A Systematic Review

High-frequency ultrasonography (HF-USG) is a relatively new imaging method that allows the evaluation in a non-invasive manner of the skin layers and skin appendages. It is a diagnostic tool with increasing usefulness in numerous dermatological pathologies. High reproducibility, non-invasiveness and short diagnostic time make this method an increasingly used tool in dermatological practice. The subepidermal low-echogenic band is a relatively newly described parameter that seems to be a marker not only of intrinsic and extrinsic skin aging, but also of inflammatory processes taking place at the skin level. This systematic review aims to evaluate the role that SLEB has in the diagnosis and monitoring of the treatment of some inflammatory and non-inflammatory dermatological conditions, as well as its utility as a disease marker.