Miracle-dz/UniFAR-FTUs huggingface dataset:
Ephrins as negative regulators of adult neurogenesis in diverse regions of the central nervous system

In the central nervous system (CNS) of adult mammals, neurogenesis occurs in only two restricted areas, the subgranular zone (SGZ) of the hippocampus and the subventricular zone (SVZ). Isolation of multipotent progenitor cells from other CNS regions suggests that their neurogenic potential is dictated by local environmental cues. Here, we report that astrocytes in areas outside of the SGZ and SVZ of adult mice express high levels of ephrin-A2 and -A3, which present an inhibitory niche, negatively regulating neural progenitor cell growth. Adult mice lacking both ephrin-A2 and -A3 display active ongoing neurogenesis throughout the CNS. These findings suggest that neural cell replacement therapies for neurodegeneration or injury in the adult CNS may be achieved by manipulating ephrin signaling pathways.
The Impact of Climate Change on Hydrology with Geomorphology in Northeast Texas

This research evaluates the responses of hydrology and geomorphology regarding climate change and illustrates the change in regional streamflow during the period 1955-2001. The Neches River Basin, Texas, is an important source of water for farming, cities, and electrical power production. A 15.9% increase in precipitation and a 20.4% increase in streamflow discharge were observed. The areas of river-flow boundaries also increased. The hydrologic changes appear to be associated with the geomorphic adjustments. To accomplish this research, the Neches River Basin is evaluated using hydro-climate data, historical aerial photography, and GIS in a multiscale approach by using linked geomorphic systems. Changes in the streamflow discharge are main factors that must be considered in undertaking a hydrological impact assessment of climate change.
Prognostic significance of syndecan-1 expression in cervical cancers

Objective Syndecans are reported to have variable expression in several solid tumors and blood cancers. The cause provoking altered expression of syndecans is not known to date. We studied copy number status of syndecan-1 (SDC1) and significance of SDC1 gene product (syndecan-1, SDC1) expression in cervical cancers. Methods Using 121 cases of cervical cancer tissues, we screened SDC1 expression pattern using immunohistochemistry. We analyzed the relationship between SDC1 expression and clinicopathological parameters. To find possible causes of the expression change, we exploited interphase fluorescent in situ hybridization to screen copy number alteration of SDC1. Results Among 121 cases, 101 (83.5%) were positive and 20 (16.4%) were negative for SDC1. Among the parameters, age, histological type, and grade were significantly associated with SDC1 expression (p<0.05). Strong SDC1 expression in the cytoplasm showed better patient survival (p=0.02). In multivariate regression model, grade and SDC1 expression were independent prognostic factors (p<0.05). SDC1 in cervical cancers did not show copy number alteration. Conclusion Strong SDC1 expression in the cytoplasm of tumor cells predicts better patient survival. The change of SDC1 expression in cervical cancers is not caused by copy number alteration of the gene.
Role of Formins in Actin Assembly: Nucleation and Barbed-End Association

Nucleation of branched actin filaments by the Arp2/3 complex is a conserved process in eukaryotic cells, yet the source of unbranched actin filaments has remained obscure. In yeast, formins stimulate assembly of actin cables independently of Arp2/3. Here, the conserved core of formin homology domains 1 and 2 of Bni1p (Bni1pFH1FH2) was found to nucleate unbranched actin filaments in vitro.Bni1pFH2 provided the minimal region sufficient for nucleation. Unique among actin nucleators, Bni1pFH1FH2 remained associated with the growing barbed ends of filaments. This combination of properties suggests a direct role for formins in regulating nucleation and polarization of unbranched filamentous actin structures.
Towards Dependability in Everyday Software Using Software Telemetry

Application-level software dependability is difficult to ensure. Thus it's typically used only in custom systems and is achieved using one-of-a-kind, handcrafted solutions. We are interested in understanding whether and how these techniques can be applied to more common, lower-end systems. To this end, we have adapted a condition-based maintenance (CBM) approach called the multivariate state estimation technique (MSET). This approach automatically creates sophisticated statistical models that predict system failure well before failures occur, leading to simpler and more successful recoveries. We have packaged this approach in the Software Dependability Framework (SDF). The SDF consists of instrumentation and data management libraries, a CBM module, performance visualization tools, and a software architecture that supports system designers. Finally, we evaluated our framework on a simple video game application. Our results suggest that we can cheaply and reliably predict impending runtime failures and respond to them in time to improve the system's dependability
Seawater acclimation causes independent alterations in Na+/K+- and H+-ATPase activity in isolated mitochondria-rich cell subtypes of the rainbow trout gill

SUMMARY Mitochondria-rich cells (MR cells) of the gills of rainbow trout undergo changes in relative distribution and biochemical function during acclimation to partial-strength (10‰) and full-strength (30‰) seawater. In isolated total gill cells, Na+/K+-ATPase activity increased fivefold and H+-ATPase activity decreased fourfold when trout were acclimated to either 10‰ or 30‰ seawater. When total MR gill cells were separated based on differential binding to peanut lectin agglutinin (PNA), the PNA subtypes underwent a change in relative distribution in seawater-acclimated fish. In freshwater, the ratio of PNA–:PNA+ was 65:35 while in seawater the distribution changed to 20:80 PNA–:PNA+. Additionally, differential changes in Na+/K+-ATPase and H+-ATPase activity in each of the independent cell types occurred during seawater acclimation; Na+/K+-ATPase activity in the PNA– cells increased by 197% while in PNA+ cells Na+/K+-ATPase decreased by 57%. However, H+-ATPase activity was decreased in both PNA– (84%) and PNA+ (72%) subtypes during acclimation to seawater.
Research Evidence for Reducing Sugar Sweetened Beverages in Children

Aims and Objectives: Sugar sweetened beverages (SSBs) have become commonplace in our society and are positively associated with an increase in body mass index (BMI) in our youth. Methods: This project presents an evidence-based review of the current research literature from 2001 to 2009 to examine the association between SSBs and children’s BMI. Results: An analysis of nine primary research studies is reported and eight of nine studies support that a decrease or reduction in SSBs by our youth can have a positive impact on their BMI. Conclusion: Education and political action by nurses to promote a decrease in SSB intake is a step in the right direction in reducing obesity in our children.
CNFET-based high throughput register file architecture

A Carbon Nanotube field-effect transistor (CNFET) is a promising alternative to a traditional metal-oxide-semiconductor field-effect transistor (MOSFET) to overcome the “Power Wall” challenge. However, CNFETs are inherently subject to much larger process variation and thereby they can incur a significant design cost to build high-performance processors. Particularly, the large register files (RF) of SIMD GPU-style processors suffer more from such process variations because the number of critical paths are multiplied by the SIMD width and thread count. In this paper, we first show that RF organizations coupled with architectural techniques are critical to RF performance under CNFET-specific variations. Second, we propose several architectural techniques to mitigate the performance degradation, leveraging distinctive characteristics of CNFETs and unique features of SIMD processors. Our experiments demonstrate that the average RF performance is 53% higher than the worst design under variation and only 7% lower than the design with no variation.
Optimal Sensorimotor Control in Eye Movement Sequences

Fast and accurate motor behavior requires combining noisy and delayed sensory information with knowledge of self-generated body motion; much evidence indicates that humans do this in a near-optimal manner during arm movements. However, it is unclear whether this principle applies to eye movements. We measured the relative contributions of visual sensory feedback and the motor efference copy (and/or proprioceptive feedback) when humans perform two saccades in rapid succession, the first saccade to a visual target and the second to a memorized target. Unbeknownst to the subject, we introduced an artificial motor error by randomly “jumping” the visual target during the first saccade. The correction of the memory-guided saccade allowed us to measure the relative contributions of visual feedback and efferent copy (and/or proprioceptive feedback) to motor-plan updating. In a control experiment, we extinguished the target during the saccade rather than changing its location to measure the relative contribution of motor noise and target localization error to saccade variability without any visual feedback. The motor noise contribution increased with saccade amplitude, but remained <30% of the total variability. Subjects adjusted the gain of their visual feedback for different saccade amplitudes as a function of its reliability. Even during trials where subjects performed a corrective saccade to compensate for the target-jump, the correction by the visual feedback, while stronger, remained far below 100%. In all conditions, an optimal controller predicted the visual feedback gain well, suggesting that humans combine optimally their efferent copy and sensory feedback when performing eye movements.
Qualifying Number Restrictions in Concept Languages

We investigate the subsumption problem in logic-based knowledge representation languages of the KL-ONE family. The language presented in this paper provides the constructs for conjunction, disjunction, and negation of concepts, as well as qualifying number restrictions. The latter ones generalize the well-known role quantifications (such as value restrictions) and ordinary number restrictions, which are present in almost all KL-ONE based systems. Until now, only little attempts were made to integrate qualifying number restrictions into concept languages. It turns out that all known subsumption algorithms which try to handle these constructs are incomplete, and thus detecting only few subsumption relations between concepts. We present a subsumption algorithm for our language which is sound and complete. Subsequently we discuss why the subsumption problem in this language is rather hard from a computational point of view. This leads to an idea of how to recognize concepts which cause tractable problems.
Wearable Photoplethysmographic Sensors—Past and Present

Photoplethysmography (PPG) technology has been used to develop small, wearable, pulse rate sensors. These devices, consisting of infrared light-emitting diodes (LEDs) and photodetectors, offer a simple, reliable, low-cost means of monitoring the pulse rate noninvasively. Recent advances in optical technology have facilitated the use of high-intensity green LEDs for PPG, increasing the adoption of this measurement technique. In this review, we briefly present the history of PPG and recent developments in wearable pulse rate sensors with green LEDs. The application of wearable pulse rate monitors is discussed.
An adaptive approach to control broadcast traffic in wireless mesh networks based IEEE 802.11s

In wireless multi-hop networks, broadcasting by flooding generates frequent retransmissions of unnecessary packets that participate heavily in increasing contention and collision probability. These problems become increasingly likely in a wireless mesh network which can interface to other external networks, thus leading to a significant increase in broadcast traffic. In this paper we have focused on IEEE 802.11s based wireless mesh networks and we have designed a new adaptive approach based on self-pruning to control broadcast traffic forwarding. Our algorithm uses two-hop neighbor information to ascertain the forwarding decision. Simulation results show the advantages of our approach which has contributed to significantly reduce unnecessary rebroadcasts while improving average end to end delay, network load and throughput.
The bubble cursor: enhancing target acquisition by dynamic resizing of the cursor's activation area

We present the bubble cursor - a new target acquisition technique based on area cursors. The bubble cursor improves upon area cursors by dynamically resizing its activation area depending on the proximity of surrounding targets, such that only one target is selectable at any time. We also present two controlled experiments that evaluate bubble cursor performance in 1D and 2D target acquisition tasks, in complex situations with multiple targets of varying layout densities. Results show that the bubble cursor significantly outperforms the point cursor and the object pointing technique [7], and that bubble cursor performance can be accurately modeled and predicted using Fitts' law.
Managing water consumption per capita using performance indicators: a case study

Water scarcity represents a significant challenge in Jordan, exacerbated by increasing domestic, industrial, and agricultural water demands amidst the backdrop of limited available water resources. The current study utilized water consumption per capita per day (PCD) as a productivity measure that aligns with the goals of water utilities to provide safe and enough water to customers. It identified and explained the critical performance indicators (PIs) affecting PCD. The study was conducted based on the time series secondary data of the applied PIs collected from Jordan Water Company (Miyahuna) between 2009 and 2018. To identify the PIs most strongly associated with the PCD variable, a correlation analysis was performed using IBM SPSS Statistics software. Indicators showing significant correlation with the PCD underwent further analysis as potential independent variables. Non-revenue water and water resources use per capita indicators showed pivotal and significant effects on PCD, exhibiting negative and positive impacts, respectively. In pursuit of improved indicators’ performance, this research advocates for the implementation of Active Leakage Control methods, the adoption of innovative techniques to desalinate brack-ish water, the promotion of water harvesting initiatives
Motion Planning for Unlabeled Discs with Optimality Guarantees

We study the problem of path planning for unlabeled (indistinguishable) unit-disc robots in a planar environment cluttered with polygonal obstacles. We introduce an algorithm which minimizes the total path length, i.e., the sum of lengths of the individual paths. Our algorithm is guaranteed to find a solution if one exists, or report that none exists otherwise. It runs in time $\tilde{O}(m^4+m^2n^2)$, where $m$ is the number of robots and $n$ is the total complexity of the workspace. Moreover, the total length of the returned solution is at most $\text{OPT}+4m$, where OPT is the optimal solution cost. To the best of our knowledge this is the first algorithm for the problem that has such guarantees. The algorithm has been implemented in an exact manner and we present experimental results that attest to its efficiency.
R-Tree based Searching and Ranking on Spatial Data

Spatial databases have enormous number of applications, especially in mobile and wireless communications. Range queries are one of the best available tools to retrieve useful information from these databases. Range query usually returns large results. These results are neither communication effective nor informative. Finding spatial data that fit best for the intended use is the main challenge of all spatial search engines. Result of search for spatial data is a list of all items indicated as relevant by the algorithm used in the search engine. Depending on the type of input to the system, various techniques can be used for ranking the results. In order to address these problems, we propose an idea of r-tree based searching and ranking. Such an r-tree based searching & ranking reduces the costs of communication, increases the Usefulness, and also provides interactive exploration. Proposed system defines that the handheld device query will be provided effectively and nontrivial algorithm found good results approximately.
A cooperative co-evolutionary multi-agent system for multi-objective layout optimization of satellite module

We herein propose a new collaborative framework, called cooperative co-evolutionary multi-agent system(CCEMAS), for solving multi-objective layout optimization problems. Every agent in CCEMAS is encoded as a multi-objective cooperative co-evolutionary strategy, including an algorithm and its setting. In the iterative procedure, the strategies will evolve along with the evolution of the agent team, and use different algorithms and settings during different stages of problem solving. A multi-objective optimization of satellite module is solved to validate the method and obtain the Pareto optimal solutions. Finally, the evolution process of multi-objective cooperative co-evolutionary strategies in agents is analyzed for constructing new multi-objective cooperative co-evolutionary algorithms for this problem in the future.
Sensor Networks for Optimal Target Localization with Bearings-Only Measurements in Constrained Three-Dimensional Scenarios

In this paper, we address the problem of determining the optimal geometric configuration of an acoustic sensor network that will maximize the angle-related information available for underwater target positioning. In the set-up adopted, a set of autonomous vehicles carries a network of acoustic units that measure the elevation and azimuth angles between a target and each of the receivers on board the vehicles. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using tools from estimation theory, the problem is converted into that of minimizing, by proper choice of the sensor positions, the trace of the inverse of the Fisher Information Matrix (also called the Cramer-Rao Bound matrix) to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration of the sensors depends explicitly on the intensity of the measurement noise, the constraints imposed on the sensor configuration, the target depth and the probabilistic distribution that defines the prior uncertainty in the target position. Simulation examples illustrate the key results derived.
A 3D Reconstruction Strategy of Vehicle Outline Based on Single-Pass Single-Polarization CSAR Data

In the last few years, interest in circular synthetic aperture radar (CSAR) acquisitions has arisen as a consequence of the potential achievement of 3D reconstructions over 360° azimuth angle variation. In real-world scenarios, full 3D reconstructions of arbitrary targets need multi-pass data, which makes the processing complex, money-consuming, and time expending. In this paper, we propose a processing strategy for the 3D reconstruction of vehicle, which can avoid using multi-pass data by introducing a priori information of vehicle’s shape. Besides, the proposed strategy just needs the single-pass single-polarization CSAR data to perform vehicle’s 3D reconstruction, which makes the processing much more economic and efficient. First, an analysis of the distribution of attributed scattering centers from vehicle facet model is presented. And the analysis results show that a smooth and continuous basic outline of vehicle could be extracted from the peak curve of a noncoherent processing image. Second, the 3D location of vehicle roofline is inferred from layover with empirical insets of the basic outline. At last, the basic line and roofline of the vehicle are used to estimate the vehicle’s 3D information and constitute the vehicle’s 3D outline. The simulated and measured data processing results prove the correctness and effectiveness of our proposed strategy.
An Antimicrobial Peptidomimetic Induces Mucorales Cell Death through Mitochondria-Mediated Apoptosis

The incidence of mucormycosis has dramatically increased in immunocompromised patients. Moreover, the array of cellular targets whose inhibition results in fungal cell death is rather limited. Mitochondria have been mechanistically identified as central regulators of detoxification and virulence in fungi. Our group has previously designed and developed a proteolytically-resistant peptidomimetic motif D(KLAKLAK)2 with pleiotropic action ranging from targeted (i.e., ligand-directed) activity against cancer and obesity to non-targeted activity against antibiotic resistant gram-negative rods. Here we evaluated whether this non-targeted peptidomimetic motif is active against Mucorales. We show that D(KLAKLAK)2 has marked fungicidal action, inhibits germination, and reduces hyphal viability. We have also observed cellular changes characteristic of apoptosis in D(KLAKLAK)2-treated Mucorales cells. Moreover, the fungicidal activity was directly correlated with vacuolar injury, mitochondrial swelling and mitochondrial membrane depolarization, intracellular reactive oxygen species accumulation (ROS), and increased caspase-like enzymatic activity. Finally, these apoptotic features were prevented by the addition of the ROS scavenger N-acetyl-cysteine indicating mechanistic pathway specificity. Together, these findings indicate that D(KLAKLAK)2 makes Mucorales exquisitely susceptible via mitochondrial injury-induced apoptosis. This prototype may serve as a candidate drug for the development of translational applications against mucormycosis and perhaps other fungal infections.
Earth Mover ’ s Distance and Equivalent Metrics for Spaces with Hierarchical Partition trees

partition tree, and prove their equivalence. Similar metrics have previously been defined in more restrictive settings; in particular, the well-known Earth Mover’s Distance is widely used in machine learning. We adapt the definitions of these metrics to a much broader class of geometries, and use machinery from abstract harmonic analysis to prove they are all equivalent. We validate the theoretical results with numerical experiments.