Miracle-dz/UniFAR-FTUs huggingface dataset:
Local feature representation based on linear filtering with feature pooling and divisive normalization for remote sensing image classification

Abstract. We propose a local feature representation based on two types of linear filtering, feature pooling, and nonlinear divisive normalization for remote sensing image classification. First, images are decomposed using a bank of log-Gabor and Gaussian derivative filters to obtain filtering responses that are robust to changes in various lighting conditions. Second, the filtering responses computed using the same filter at nearby locations are pooled together to enhance position invariance and compact representation. Third, divisive normalization with channel-wise strategy, in which each pooled feature is divided by a common factor plus the sum of the neighboring features to reduce dependencies among nearby locations, is introduced to extract divisive normalization features (DNFs). Power-law transformation and principal component analysis are applied to make DNF significantly distinguishable, followed by feature fusion to enhance local description. Finally, feature encoding is used to aggregate DNFs into a global representation. Experiments on 21-class land use and 19-class satellite scene datasets demonstrate the effectiveness of the channel-wise divisive normalization compared with standard normalization across channels and the fusion of the two types of linear filtering in improving classification accuracy. The experiments also illustrate that the proposed method is competitive with state-of-the-art approaches.
Endovascular revascularization vs. open surgical revascularization for patients with lower extremity artery disease: a systematic review and meta-analysis

Background Currently, the main treatment for lower extremity artery disease (LEAD) is revascularization, including endovascular revascularization (EVR) and open surgical revascularization (OSR), but the specific revascularization strategy for LEAD is controversial. This review provided the comprehensive and recent evidence for the treatment of LEAD. Methods Medline, Embase, and the Cochrane Library databases were searched for relevant articles. Randomized controlled trials (RCTs) and cohort studies comparing the short-term or long-term outcomes between EVR and OSR of LEAD were identified. Short-term outcomes were 30-day mortality, major amputation, wound complication, major adverse cardiovascular events (MACEs), and length of hospital stay (LOS), while long-term outcomes included overall survival (OS), amputation-free survival (AFS), freedom from re-intervention (FFR), primary patency (PP), and secondary patency (SP). Results 11 RCTs and 105 cohorts involving 750,134 patients were included in this analysis. For the pooled results of cohort studies, EVR markedly decreased the risk of 30-day mortality, wound complication, MACEs, LOS, but increased the risk of OS, FFR, PP, and SP. For the pooled outcomes of RCTs, EVR was associated with obviously lower 30-day mortality, less wound complication and shorter LOS, but higher risk of PP, and SP. However, both RCTs and cohorts did not show obvious difference in 30-day major amputation and AFS. Conclusions Both the pooled results of cohorts and RCTs indicated that EVR was associated with a lower short-term risk for LEAD, while OSR was accompanied by a substantially lower long-term risk. Therefore, the life expectancy of LEAD should be strictly considered when choosing the revascularization modality. As the current findings mainly based on data of retrospective cohort studies, additional high-quality studies are essential to substantiate these results. Systematic Review Registration https://www.crd. york.ac. uk/PROSPERO/#recordDetails, identifier CRD42022317239.
Productive Waqf Development Model: A Comparative Study between Indonesia and Malaysia

The development of the productive waqf model has become a topic of conversation for Muslim countries, especially Indonesia and Malaysia. This is because waqf is one of the Islamic social financial instruments that can move the economic sector of society. This research will examine the productive waqf development model between Indonesia and Malaysia and to see how the opportunities and challenges are being faced. The method used is qualitative, in which researchers conducted interviews with waqf academics and practitioners in both Indonesia and Malaysia. In addition to describing the opportunities and challenges researchers use SWOT analysis. The results of the study show that Indonesia and Malaysia have strengths and weaknesses in terms of productive waqf management. Furthermore, collaboration and initiative are needed as well as experience to overcome various existing problems. Efforts to increase awareness, transparency, and partnerships can promote sustainable waqf.
Effect of Particle Migration on the Stress Field in Microfluidic Flows of Blood Analog Fluids at High Reynolds Numbers

In the present paper, we investigate how the reductions in shear stresses and pressure losses in microfluidic gaps are directly linked to the local characteristics of cell-free layers (CFLs) at channel Reynolds numbers relevant to ventricular assist device (VAD) applications. For this, detailed studies of local particle distributions of a particulate blood analog fluid are combined with wall shear stress and pressure loss measurements in two complementary set-ups with identical flow geometry, bulk Reynolds numbers and particle Reynolds numbers. For all investigated particle volume fractions of up to 5%, reductions in the stress and pressure loss were measured in comparison to a flow of an equivalent homogeneous fluid (without particles). We could explain this due to the formation of a CFL ranging from 10 to 20 μm. Variations in the channel Reynolds number between Re = 50 and 150 did not lead to measurable changes in CFL heights or stress reductions for all investigated particle volume fractions. These measurements were used to describe the complete chain of how CFL formation leads to a stress reduction, which reduces the apparent viscosity of the suspension and results in the Fåhræus–Lindqvist effect. This chain of causes was investigated for the first time for flows with high Reynolds numbers (Re∼100), representing a flow regime which can be found in the narrow gaps of a VAD.
Low loss GaInNAs/GaAs gain waveguides with U-bend geometry for single-facet coupling in hybrid photonic integration

We report a low loss U-bend waveguide for realization of GaAs-based gain elements employed in hybrid photonic integration. This architecture allows us to position the input and output ports of the gain waveguide on the same facet and thus alleviates the geometrical constrains in hybrid integration, i.e., the need for precise alignment with silicon photonic waveguides on both ends of the III–V chip. As an exemplary demonstration, we report the loss and gain characteristics of GaInNAs/GaAs U-bend waveguides operating at 1.3 μm. In particular, we demonstrate a bending loss as low as 1.1 dB for an 83 μm bending radius. Efficient laser diode operation is also demonstrated.We report a low loss U-bend waveguide for realization of GaAs-based gain elements employed in hybrid photonic integration. This architecture allows us to position the input and output ports of the gain waveguide on the same facet and thus alleviates the geometrical constrains in hybrid integration, i.e., the need for precise alignment with silicon photonic waveguides on both ends of the III–V chip. As an exemplary demonstration, we report the loss and gain characteristics of GaInNAs/GaAs U-bend waveguides operating at 1.3 μm. In particular, we demonstrate a bending loss as low as 1.1 dB for an 83 μm bending radius. Efficient laser diode operation is also demonstrated.
A real algebraic and symbolic-numeric algorithm

Solving systems of polynomial equations is a classical problem of mathematics with an emerging number of modern applications, such as coding theory, robotics, computational statistics, etc. Its importance is reflected by the broad literature that deals with algorithms, ranging from numerical continuation methods to exact methods based e.g. on Grobner or border bases; see e.g. the monograph [1] and the references therein. However in many practical applications one is only interested in real solutions. The literature tailored to the problem of real solving systems of polynomials is by far not as broad. In [2] the authors provide a semidefinite characterization and an algorithm for computing VK(I) (K = R,C) as well as a border or Grobner basis of the radical ideal I(VK(I)). The approach utilizes well established semidefinite programming techniques and standard numerical linear algebra. At the heart of the method in [2] is the fact that all information needed to compute the above objects is contained in the so-called moment matrix (whose entries depend on the polynomials generating the ideal I) and the geometry behind when this matrix is required to be positive semidefinite with maximum rank. For computing the real roots and the real radical ideal R √ I = I(VR(I)), the method is real algebraic in nature, as it does not compute (implicitly or explicitly) any complex element of VC(I). However, one might have to work with semidefinite matrices of possibly large size. This latter remark motivates the present paper in which we revisit the elimination algorithm of [3] for computing VC(I) and show that, by adding certain positive semidefiniteness constraints, we obtain an algorithm tailored for extracting real roots; in particular our new algorithm terminates assuming VR(I) finite (while VC(I) could be infinite). Thus the new algorithm combines ideas from [2] and [3]. An advantage over [2] is that it may terminate earlier, thus leading to more efficiency as one may have to handle positive
Edit Propagation using Geometric Analogies

Modeling complex geometrical shapes, like city scenes or terrains with dense vegetation, is a time-consuming task that cannot be automated trivially. The problem of creating and editing many similar, but not identical models requires specialized methods that understand what makes these objects similar in order to either create new variations of these models from scratch or to propagate edit operations from one object to all similar objects. In this thesis, we present new methods to significantly reduce the effort required to model complex scenes. For 2D scenes containing deformable objects, such as fish or snakes, we present a method to find partial matches between deformed shapes that can be used to transfer localized properties such as texture between matching shapes. Shapes are considered similar if they are related by pointwise correspondences and if neighboring points have correspondences with similar transformation parameters. Unlike previous work, this approach allows us to successfully establish matches between strongly deformed objects, even in the presence of occlusions and sparse or unevenly distributed sets of matching features. For scenes consisting of 2D shape arrangements, such as floor plans, we propose methods to find similar locations in the arrangements, even though the arrangements themselves are dissimilar. Edit operations, such as object placements, can be propagated between similar locations. Our approach is based on simple geometric relationships between the location and the shape arrangement, such as the distance of the location to a shape boundary or the direction to the closest shape corner. Two locations are similar of they have many similar relations to their surrounding shape arrangement. To the best of our knowledge, there is no method that explicitly attempts to find similar locations in dissimilar shape arrangements. We demonstrate populating large scenes such as floor plans with hundreds of objects like pieces of furniture, using relatively few edit operations. Additionally, we show that providing several examples of an edit operation helps narrowing down the supposed modeling intention of the user and improves the quality of the edit propagation. A probabilistic model is learned from the examples and used to suggest similar edit operations. Also, extensions are shown that allow application of this method in 3D scenes. Compared to previous approaches that use entire scenes as examples, our method provides more user control and has no need for large databases of example scenes or domain-specific knowledge. We demonstrate generating 3D interior decoration and complex city scenes, including buildings with detailed facades, using only few edit operations.
The Specified Finite-Time Distributed Observers-Based Velocity-Free Attitude Synchronization for Rigid Bodies on SO(3)

In this paper, the problems of specified finite-time distributed attitude estimation and velocity-free attitude synchronization are studied for rigid bodies on special orthogonal group SO(3). Using the geometric convexity on SO(3), the exponential distributed observers are proposed for each rigid body to estimate the common time-varying reference states which are only available to a part of followers. Then, the specified finite-time distributed observers are proposed by using the time-rescaling approach, where the finite terminal time can be specified in advance according to the task requirements. The advantage of time-rescaling method is that the asymptotic, exponential, or finite-time distributed observers can be converted to the specified finite-time distributed observers via choosing an appropriate continuously differentiable scaling function that satisfies some required properties to rescale time. Based on the distributed observers, the velocity-free attitude synchronization control torques are designed by virtue of observer-like systems. The performances of the specified finite-time distributed observers and the velocity-free attitude synchronization with distributed observers are illustrated through numerical/SimMechanics simulations.
Multi-Motion Segmentation via Co-Attention-Induced Heterogeneous Model Fitting

Motion segmentation is an essential task in artificial intelligence and computer vision. However, scene motion in real-world intelligent systems usually integrates multiple types of models, so specifying only one type of basic model may lead to the failure of scene-motion segmentation tasks. In this paper, we propose a novel and efficient heterogeneous model-fitting-based motion segmentation method (HMFMS) to accurately segment moving objects. HMFMS includes a new co-attention-induced heterogeneous model construction algorithm (HMC), an adaptive heterogeneous model refinement algorithm (HMR), and a heterogeneous model segmentation algorithm (HMS). First, we propose HMC to generate high-quality accumulated correlation matrices, by evaluating the quality of heterogeneous model hypotheses, based on the density estimation technique. Next, we propose HMR to construct sparse affinity matrices from the accumulated correlation matrices by applying information theory, effectively suppressing the values of correlations between different objects. Finally, we fuse the sparse affinity matrices and perform motion segmentation by using HMS, to obtain more accurate segmentation results. Experimental results show that HMFMS obtains superior performance on four challenging datasets (i.e., Hopkins155, Hopkins12, MTPV62 and KT3DMoSeg), compared with several subspace-based and model-fitting-based motion segmentation methods. More remarkably, HMFMS outperforms the state-of-the-art MCMS method by 57.1% and 1.8 times in terms of accuracy and computational efficiency on the representative KT3DMoSeg, respectively.
Interaction of Hoechst 33342 with POPC Membranes at Different pH Values

Hoechst 33342 (H33342) is a fluorescent probe that is commonly used to stain the DNA of living cells. To do so, it needs to interact with and permeate through cell membranes, despite its high overall charge at physiological pH values. In this work, we address the effect of pH in the association of H33342 with lipid bilayers using a combined experimental and computational approach. The partition of H33342 to 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid membranes was experimentally quantified using fluorescence spectroscopy and isothermal titration calorimetry (ITC) measurements. Quantum chemical calculations were performed to select the most stable isomer of H33342 for the overall charges 0, +1, and +2, expected to predominate across the 5 < pH < 10 range. The interaction of these isomers with POPC bilayers was then studied by both unrestrained and umbrella sampling molecular dynamics (MD) simulations. Both experimental results and computational free energy profiles indicate that the partition coefficient of H33342 displays a small variation over a wide pH range, not exceeding one order of magnitude. The enthalpy variation upon partition to the membrane suggests efficient hydrogen bonding between the probe and the lipid, namely, for the protonated +2 form, which was confirmed in the MD simulation studies. The relatively high lipophilicity obtained for the charged species contrasts with the decrease in their general hydrophobicity as estimated from octanol/water partition. This highlights the distinction between lipophilicity and hydrophobicity, as well as the importance of considering the association with lipid bilayers when predicting the affinity for biomembranes.
Low Altitude 3-D Coverage Performance Analysis of Cell-Free RAN for 6G Systems

In this article, we propose to utilize a more flexible and scalable cell-free radio access network (CF-RAN) for 6G systems to promote the coverage performance of the low altitude three-dimensional (3-D) scenarios, where unmanned aerial vehicles (UAVs) and ground users (GUEs) are coexisted. User-centric association strategy and scalable receiving schemes such as maximum ratio combing (MRC), partial zero-forcing (P-ZF) and partial minimum-mean-square error (P-MMSE) are adopted to reduce the interference between UAVs and GUEs and improve the scalability of signal processing. Closed-form expressions for uplink spectral efficiency (SE) are derived with considered receivers. Based on the derived closed-form expressions, we propose a power allocation strategy by solving a multi-objective optimization problem between maximizing the average SE of UAVs and GUEs simultaneously with intelligent algorithm——Deep Q-Network (DQN). Numerical results verify the accuracy of the derived closed-form expressions and the effectiveness of the proposed power allocation schemes for low altitude 3-D coverage with coexisted UAVs and GUEs. The coverage performance analysis under various system parameters offers much of flexibilities for the optimization of the low altitude CF-RAN systems.
Diffusion-Weighted MRI for Treatment Response Assessment in Osteoblastic Metastases—A Repeatability Study

Simple Summary Patients with many advanced cancers develop osteoblastic bone metastases that cannot be assessed by conventional imaging. There is an unmet need for a quantitative imaging technique that can assess the treatment response of osteoblastic metastases to further improve treatment of these patients. This article examines the difference in apparent diffusion coefficient (ADC) values found between viable and nonviable metastases in relation to the variability of repeated measurements as a basis for the potential use of diffusion-weighted MRI (DWI) for treatment response assessment. DWI is based on observing the movement of water molecules, which is often restricted in tumor tissue and is quantified using the ADC. It is shown that viable and nonviable metastases differ significantly in ADC value and that these differences are considerably higher than the variability of repeated measurements. This shows that DWI meets the basic technical requirements for reliable treatment response assessment of osteoblastic metastases. Abstract The apparent diffusion coefficient (ADC) is a candidate marker of treatment response in osteoblastic metastases that are not evaluable by morphologic imaging. However, it is unclear whether the ADC meets the basic requirement for reliable treatment response evaluation, namely a low variance of repeated measurements in relation to the differences found between viable and nonviable metastases. The present study addresses this question by analyzing repeated in vivo ADCmedian measurements of 65 osteoblastic metastases in nine patients, as well as phantom measurements. PSMA-PET served as a surrogate for bone metastasis viability. Measures quantifying repeatability were calculated and differences in mean ADC values according to PSMA-PET status were examined. The relative repeatability coefficient %RC of ADCmedian measurements was 5.8% and 12.9% for phantom and in vivo measurements, respectively. ADCmedian values of bone metastases ranged from 595×10−6mm2/s to 2090×10−6mm2/s with an average of 63% higher values in nonviable metastases compared with viable metastases (p < 0.001). ADC shows a small repeatability coefficient in relation to the difference in ADC values between viable and nonviable metastases. Therefore, ADC measurements fulfill the technical prerequisite for reliable treatment response evaluation in osteoblastic metastases.
Experiences of Black Male Doctoral Students in Psychology: A Focus on Protective Factors

Black male doctoral students in psychology face unique challenges that impact their learning environment and experience, especially with issues like race-related stress. The purpose of this qualitative study was to understand their lived experience as well as the specific sociocultural factors that helped to foster their resiliency. It suggests a strengths-focused approach to understanding proactive measures that can positively impact Black male students’ success in doctoral psychology programs and their subsequent positive consequences for the profession. A phenomenological study was conducted, interviewing five Black men in clinical and counseling psychology doctoral programs. A thematic analysis (Braun & Clarke, 2006) was utilized to analyze the interview responses. The findings suggest a community of support (family, mentors, peers, faculty, and relationships at professional conferences) helps, to foster awareness (educational, self-awareness, and contextual awareness) which, in turn, leads to the students engaging in meaningful action (representation, giving back, and self-care), returning to serve as members who make up the community of support for others within their community.
Optimal Design of a Dragonfly-Inspired Compliant Joint for Camera Positioning System of Nanoindentation Tester Based on a Hybrid Integration of Jaya-ANFIS

Camera positioning system is a critical member of a nanoindentation tester characterizing the mechanical properties such as hardness, creep, surface roughness, or elastic modulus of a material sample. This paper presents a design optimization for a dragonfly-inspired compliant joint. This joint is used to drive the camera positioning system. A new hybrid approach of Taguchi method, adaptive neuro-fuzzy inference system (ANFIS), and Jaya algorithm is developed to solve the multi-objective optimization problem. The Taguchi method is used to build the numerical data and to find the best membership functions for the ANFIS structure by minimizing the root mean squared error. Then, the weight factor of each objective function is determined by established equations well. Subsequently, a structure of ANFIS is developed to map the design parameters and responses. Sensitivity analysis of each controllable parameter is analyzed by the statistical method. Finally, Jaya algorithm is initialized to find the optimal solution. The results found that the optimal displacement, frequency, and stress are about 12581.11 μm, 67.76 Hz, and 333.68 MPa, respectively. The proposed hybrid optimization algorithm is a robust and effective optimizer and considered as soft computing technique for engineering optimization problems.