Miracle-dz/UniFAR-FTUs huggingface dataset:
Retinal ganglion cell topography and spatial resolving power in the river hippopotamus (Hippopotamus amphibius)

The river hippopotamus (Hippopotamus amphibius), one of the closest extant relatives to cetaceans, is a large African even‐toed ungulate (Artiodactyla) that grazes and has a semiaquatic lifestyle. Given its unusual phenotype, ecology, and evolutionary history, we sought to measure the topographic distribution of retinal ganglion cell density using stereology and retinal wholemounts. We estimated a total of 243,000 ganglion cells of which 3.4% (8,300) comprise alpha cells. The topographic distribution of both total and alpha cells reveal a dual topographic organization of a temporal and nasal area embedded within a well‐defined horizontal streak. Using maximum density of total ganglion cells and eye size (35 mm, axial length), we estimated upper limits of spatial resolving power of 8 cycles/deg (temporal area, 1,800 cells/mm2), 7.7 cycles/deg (nasal area, 1,700 cells/mm2), and 4.2 cycles/deg (horizontal streak, 250 cells/mm2). Enhanced resolution of the temporal area toward the frontal visual field may facilitate grazing, while resolution of the horizontal streak and nasal area may help the discrimination of objects (predators, conspecifics) in the lateral and posterior visual fields, respectively. Given the presumed role of alpha cells to detect brisk transient stimuli, their similar distribution to the total ganglion cell population may facilitate the detection of approaching objects in equivalent portions of the visual field. Our finding of a nasal area in the river hippopotamus retina supports the notion that this specialization may enhance visual sampling in the posterior visual field to compensate for limited neck mobility as suggested for rhinoceroses and cetaceans.
Study of Flexoelectricity in Graphene Composite Structures

This paper introduces the theoretical and experimental investigation of flexoelectric behavior in a graphene composite structure consisting of multilayer CVD-graphene deposited on an ALD-platinum catalyst layer deposited on top of n-silicon substrate. The polarization induced by varying the radius of curvature from 200–1500 mm by applying bending stresses was investigated experimentally. Meanwhile, due to the cluster-growth nature of the ALD-platinum catalyst layer, a strong correlation was observed between the resulting number of graphene layers and the Pt catalyst layer thickness, which subsequently had a strong impact on the induced polarization. A polarization current of up to 7.4 mA was detected when the composite structure was bent through a 600-mm radius of curvature. Residual stresses at the interface of the different layers were estimated experimentally in the order of 85–217 MPa. The effect of thermally-induced stresses, residual stresses at the interface layers, thickness of graphene layers, and radius of curvature were investigated theoretically using the finite element method (FEM) and first-principle analyses. Theoretically, it was confirmed that non-uniform strain results in an appreciable non-uniform graphene band gap opening, in addition to non-uniform change of the band structure across the surface and thickness which results in increasing the potential energy difference between the graphene layers. FEM confirmed that thermally induced strains could further enhance the power output of the device by inducing a flexoelectric current combined with the thermionic response. This is verified by estimating a lattice displacement up to 0.31 Å in response to 2-mW heat flux, which corresponds to an appreciable graphene band opening and a potential energy difference across the graphene layers in the order of 1.23 eV, as estimated by the tight binding model.
Cartilage growth and remodeling : modulation of growth phenotype and tensile integrity

Articular cartilage function as a low friction, wear- resistant, load-bearing material in joints depends on the molecular composition and structure of the extracellular tissue matrix. The proteoglycan component provides the tissue with a fixed negative charge, which imparts a swelling pressure. The crosslinked collagen network resists the swelling tendency of the proteoglycans, and provides the tissue with tensile integrity. During growth of articular cartilage in vivo, composition and function evolve dramatically and both chemical and mechanical stimuli have profound regulatory effects. However, it is unknown how immature tissue evolves into its adult form, and if and how various types of chemical stimuli modulate this process. The overall hypothesis proposed here is that cartilage growth results from a chemically regulated dynamic imbalance between the swelling pressure of glycosaminoglycans (GAG) and the restraining function of the collagen network. Manipulation of matrix content, metabolism, and assembly distinctly altered the growth phenotype of immature articular cartilage, as assessed by culture-associated variations in tissue geometry, composition, and function. In vitro growth of cartilage explants was regulated differentially by growth factors. Overall, cartilage explants grew in volume, as GAG content, an indicator of swelling pressure, increased and tensile modulus and strength, indicators of collagen network integrity, decreased. The propensity of cartilage tissue to grow was additionally enhanced during growth in presence of an inhibitor of collagen crosslink formation, and reduced during growth of explants which were depleted of GAG prior to culture. Thus, factors that lead to growth of cartilage explants in vitro involve a shift in the balance between the swelling pressure of the proteoglycans and the restraining ability of the collagen network, toward an overall expansive effect resulting from the swelling pressure. The tensile integrity of articular cartilage was modulated through depletion of certain extracellular matrix components; however the extent of this modulation was dependent on the maturity of the source tissue. Certain resident matrix components of articular cartilage were implicated in the development of tensile integrity. An understanding of cartilage growth mechanisms may ultimately allow the development of methods to guide appropriate growth of cartilage tissue grafts for emerging tissue engineering and cartilage repair therapies
Frightening Small Children and Disconcerting Grown-ups: Concurrency in the Linux Kernel

Concurrency in the Linux kernel can be a contentious topic. The Linux kernel mailing list features numerous discussions related to consistency models, including those of the more than 30 CPU architectures supported by the kernel and that of the kernel itself. How are Linux programs supposed to behave? Do they behave correctly on exotic hardware? A formal model can help address such questions. Better yet, an executable model allows programmers to experiment with the model to develop their intuition. Thus we offer a model written in the cat language, making it not only formal, but also executable by the herd simulator. We tested our model against hardware and refined it in consultation with maintainers. Finally, we formalised the fundamental law of the Read-Copy-Update synchronisation mechanism, and proved that one of its implementations satisfies this law.
Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods

An exciting avenue of neuroscientific research involves quantifying the time-varying properties of functional connectivity networks. As a result, many methods have been proposed to estimate the dynamic properties of such networks. However, one of the challenges associated with such methods involves the interpretation and visualization of high-dimensional, dynamic networks. In this work, we employ graph embedding algorithms to provide low-dimensional vector representations of networks, thus facilitating traditional objectives such as visualization, interpretation and classification. We focus on linear graph embedding methods based on principal component analysis and regularized linear discriminant analysis. The proposed graph embedding methods are validated through a series of simulations and applied to fMRI data from the Human Connectome Project.
Indirect comparison of bronchial thermoplasty versus omalizumab for uncontrolled severe asthma

ABSTRACT Objective: Bronchial thermoplasty (BT) as an add-on therapy for uncontrolled severe asthma is an alternative to biologic therapies like omalizumab (OM). We conducted an indirect treatment comparison (ITC) to appraise comparative effectiveness of BT and OM. Methods: A systematic literature review identified relevant randomized controlled trials. The ITC followed accepted methodology. Results: The ITC comprised a sham-controlled trial of BT (AIR2) and two placebo-controlled trials of OM (INNOVATE; EXTRA). Comparing the BT post-treatment period to ongoing treatment with OM, showed no significant differences in the rate ratios (RRs) for severe exacerbations (RR of BT versus OM = 0.91 [95% CI: 0.64, 1.30]; p = 0.62) or hospitalizations (RR = 0.57 [95% CI: 0.17, 1.86]; p = 0.53); emergency department visits were significantly reduced by 75% with BT (RR = 0.25 [95% CI: 0.07, 0.91]; p = 0.04); the proportions of patients with clinically meaningful response on the asthma quality-of-life questionnaire were comparable (RR = 1.06 [95% CI: 0.86, 1.34]; p = 0.59). The RR for exacerbations statistically favours OM over the total study period in AIR2 (RR = 1.50 [95% CI: 1.11, 2.02]; p = 0.009) likely reflecting a transient increase in events during the BT peri-treatment period. Conclusions: The ITC should be interpreted cautiously considering the differences between patient populations in the included trials. However, based on the analysis, BT compares well with a potentially more costly pharmacotherapy for asthma. Clinicians evaluating the relative merits of using these treatments should consider the totality of evidence and patient preferences to make an informed decision.
Effects of Exercise on Cognitive Function in Older People with Dementia: A Randomized Controlled Trial

Background: Although physical exercise has been suggested to influence cognitive function, previous exercise studies show inconsistent results in people with dementia. Objectives: To investigate effects of exercise on cognitive function in people with dementia. Method: The Umeå Dementia and Exercise (UMDEX) study, a cluster-randomized controlled trial, was set in 16 nursing homes in Umeå, Sweden. One hundred-and-forty-one women and 45 men with dementia; mean age of 85 y and mean Mini-Mental State Examination (MMSE) score of 15, were randomized to a High-Intensity Functional Exercise program or a seated attention control activity. Blinded assessors measured global cognitive function using the MMSE and the Alzheimer’s disease Assessment Scale – Cognitive subscale (ADAS-Cog), and executive function using Verbal fluency (VF) at baseline and 4 months (directly after intervention completion), and MMSE and VF at 7 months. Results: Linear mixed models showed no between-group effects in mean difference from baseline (95% confidence intervals, CI) at 4 months in MMSE (–0.27; 95% CI –1.4 to 0.87, p = 0.644), ADAS-Cog (–1.04, 95% CI –4 to 1.92, p = 0.491), or VF (–0.53, 95% CI –1.42 to 0.35, p = 0.241) or at 7 months in MMSE (–1.15, 95% CI –2.32 to 0.03, p = 0.056) or VF (–0.18, 95% CI –1.09 to 0.74, p = 0.707). Conclusion: A 4-month, high-intensity functional exercise program had no superior effects on global cognition or executive function in people with dementia living in nursing homes when compared with an attention control activity.
Sulong, and Thanks for All the Bugs: Finding Errors in C Programs by Abstracting from the Native Execution Model

In C, memory errors, such as buffer overflows, are among the most dangerous software errors; as we show, they are still on the rise. Current dynamic bug-finding tools that try to detect such errors are based on the low-level execution model of the underlying machine. They insert additional checks in an ad-hoc fashion, which makes them prone to omitting checks for corner cases. To address this, we devised a novel approach to finding bugs during the execution of a program. At the core of this approach is an interpreter written in a high-level language that performs automatic checks (such as bounds, NULL, and type checks). By mapping data structures in C to those of the high-level language, accesses are automatically checked and bugs discovered. We have implemented this approach and show that our tool (called Safe Sulong) can find bugs that state-of-the-art tools overlook, such as out-of-bounds accesses to the main function arguments.
Partition-Based Distributed Kalman Filter With Plug and Play Features

In this paper, we propose a novel partition-based distributed state estimation scheme for non-overlapping subsystems based on Kalman filter. The estimation scheme is designed in order to account, in a rigorous fashion, for dynamic coupling terms between subsystems, and for the uncertainty related to the state estimates performed by the neighboring subsystems. The online implementation of the proposed estimation scheme is scalable, since it involves (i ) small-scale matrix operations to be carried out by the estimator embedded in each subsystem and (ii ) neighbor-to-neighbor transmission of a limited amount of data. We provide theoretical conditions ensuring the estimation convergence. Reconfigurability of the proposed estimation scheme is allowed in case of plug and play operations. Simulation tests are provided to illustrate the effectiveness of the proposed algorithm.
On the High Sensitivity of the Electronic States of 1 nm Gold Particles to Pretreatments and Modifiers

In this paper, the effect of modifiers and pretreatments on the electronic states of 1 nm gold nanoparticles (AuNPs) supported on silica was systematically studied. AuNPs deposited on silica (particle size of 2–4 nm) modified with Ce, La and Fe oxides, were studied by FTIR of adsorbed CO after different redox treatments at 100, 300 and 500 °C. This study was conducted at room temperature to allow detecting the electronic states of gold, which is more likely involved in CO oxidation at the same temperature. AuNP size distribution was measured by HRTEM. It is shown that the electronic state of gold species (Aunδ−, Au0, Aunδ+, Au+) in 1 nm AuNPs is sensitive to the modifier as well as to the temperatures of redox pretreatments. Supports modified with the same additives but containing larger AuNPs (~3, 4, 5, and 7 nm) were also studied. They showed that Au0 remains stable irrespective of additives and redox pretreatments, indicating no significant effect of such treatments on the electronic properties of larger AuNPs. Samples with a predominant AuNP size of 2 nm are an intermediate case between these two groups of materials.
Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography

This paper presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood reconstruction that maximizes a task-based imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index (<inline-formula> <tex-math notation="LaTeX">${d}\,'$ </tex-math></inline-formula>) throughout the image. The optimization algorithm alternates between FFM (represented by low-dimensional basis functions) and local regularization (including the regularization strength and directional penalty weights). The task-driven approach was compared with three FFM strategies commonly proposed for FBP reconstruction (as well as a task-driven TCM strategy) for a discrimination task in an abdomen phantom. The task-driven FFM assigned more fluence to less attenuating anteroposterior views and yielded approximately constant fluence behind the object. The optimal regularization was almost uniform throughout image. Furthermore, the task-driven FFM strategy redistribute fluence across detector elements in order to prescribe more fluence to the more attenuating central region of the phantom. Compared with all strategies, the task-driven FFM strategy not only improved minimum <inline-formula> <tex-math notation="LaTeX">${d}\,'$ </tex-math></inline-formula> by at least 17.8%, but yielded higher <inline-formula> <tex-math notation="LaTeX">${d}\,'$ </tex-math></inline-formula> over a large area inside the object. The optimal FFM was highly dependent on the amount of regularization, indicating the importance of a joint optimization. Sample reconstructions of simulated data generally support the performance estimates based on computed <inline-formula> <tex-math notation="LaTeX">${d}\,'$ </tex-math></inline-formula>. The improvements in detectability show the potential of the task-driven imaging framework to improve imaging performance at a fixed dose, or, equivalently, to provide a similar level of performance at reduced dose.
Robust visual tracking with the cross-bin metric

In this paper, we propose an adaptive particle filter method based on the cross-bin matching, which makes use of the fast and robust earth mover's distance with a thresholded ground distance (EMD) as the similarity measure, for robust visual tracking. In contrast to the traditional bin-by-bin metrics, the cross-bin metric used in the EMD is capable of efficiently capturing the intrinsic affinity relationships between bins, resulting in more accurate and effective tracking results. Experimental results demonstrate the effectiveness and robustness of the proposed tracking method in coping with the challenging situations, such as background clutters, occlusions, abrupt motions and jumps.
Asynchronous Localization With Mobility Prediction for Underwater Acoustic Sensor Networks

Most applications of underwater acoustic sensor networks (UASNs) rely upon reliable location information of sensor nodes. However, the harsh underwater environment makes localization more challenging as compared to terrestrial sensor networks. This paper is concerned with a localization issue for UASNs, subject to clock asynchronization and node mobility. A hybrid architecture including autonomous underwater vehicles (AUVs), active and passive sensor nodes is designed, where AUVs act as anchor nodes to provide localization information for sensor nodes. In order to eliminate the effect of asynchronous clocks and compensate the mobility of sensor nodes, an asynchronous localization algorithm with mobility prediction is provided for active and passive sensor nodes. Then, two localization optimization problems are formulated as minimizing the sum of all measurement errors. To solve the localization optimization problems, iterative least squares estimators are designed. In addition, the convergence analysis and Cramé r–Rao lower bound for the localization errors are also provided. Finally, simulation results show that the proposed localization approach can reduce the localization time by comparing with the exhaustive search-based localization method. Meanwhile, the asynchronous algorithm in this paper can effectively eliminate the impact of the clock asynchronization and node mobility.
Game Tree Search Based on Nondeterministic Action Scripts in Real-Time Strategy Games

Significant progress has been made in recent years toward stronger real-time strategy (RTS) game playing agents. Some of the latest approaches have focused on enhancing standard game tree search techniques with a smart sampling of the search space, or on directly reducing this search space. However, experiments have thus far only been performed using small scenarios. We provide experimental results on the performance of these agents on increasingly larger scenarios. Our main contribution is Puppet Search, a new adversarial search framework that reduces the search space by using scripts that can expose choice points to a look-ahead search procedure. Selecting a combination of a script and decisions for its choice points represents an abstract move to be applied next. Such moves can be directly executed in the actual game, or in an abstract representation of the game state, which can be used by an adversarial tree search algorithm. We tested Puppet Search in $\mu$RTS, an abstract RTS game popular within the research community, allowing us to directly compare our algorithm against state-of-the-art agents published in the last few years. We show a similar performance to other scripted and search based agents on smaller scenarios, while outperforming them on larger ones.
Critical review on biofilm methods

Abstract Biofilms are widespread in nature and constitute an important strategy implemented by microorganisms to survive in sometimes harsh environmental conditions. They can be beneficial or have a negative impact particularly when formed in industrial settings or on medical devices. As such, research into the formation and elimination of biofilms is important for many disciplines. Several new methodologies have been recently developed for, or adapted to, biofilm studies that have contributed to deeper knowledge on biofilm physiology, structure and composition. In this review, traditional and cutting-edge methods to study biofilm biomass, viability, structure, composition and physiology are addressed. Moreover, as there is a lack of consensus among the diversity of techniques used to grow and study biofilms. This review intends to remedy this, by giving a critical perspective, highlighting the advantages and limitations of several methods. Accordingly, this review aims at helping scientists in finding the most appropriate and up-to-date methods to study their biofilms.
Simulating the future urban growth in Xiongan New Area: a upcoming big city in China

China made the announement to create the Xiongan New Area in Hebei in April 1,2017. Thus a new magacity about 110km south west of Beijing will emerge. Xiongan New Area is of great practial significant and historical significant for transferring Beijing's non-capital function. Simulating the urban dynamics in Xiongan New Area can help planners to decide where to build the new urban and further manage the future urban growth. However, only a little research focus on the future urban development in Xiongan New Area. In addition, previous models are unable to simulate the urban dynamics in Xiongan New Area. Because there are no original high density urbna for these models to learn the transition rules.In this study, we proposed a C-FLUS model to solve such problems. This framework was implemented by coupling a modified Cellular automata(CA). An elaborately designed random planted seeds machanism based on local maximums is addressed in the CA model to better simulate the occurrence of the new urban. Through an analysis of the current driving forces, the C-FLUS can detect the potential start zone and simulate the urban development under different scenarios in Xiongan New Area. Our study shows that the new urban is most likely to occur in northwest of Xiongxian, and it will rapidly extend to Rongcheng and Anxin until almost cover the northern part of Xiongan New Area. Moreover, the method can help planners to evaluate the impact of urban expansion in Xiongan New Area.