Miracle-dz/UniFAR-FTUs huggingface dataset:
International Comparison of Stroke Cost Studies

Purpose— With the rapid international spread of interventions, there is a need to understand the economic implications of these changes and to interpret these economic implications on the international level. The purpose of this study is to systematically compare total health care expenditures on stroke, the costs of stroke per capita, and the distribution of stroke costs within different countries, with special attention to the allocation of resources among different health care facilities. Methods— Studies for this literature review were selected by conducting a literature search from January 1966 to July 2003. Key methodological, country-related, and monetary issues of the selected stroke cost studies were evaluated using a checklist. Results— After selection, 25 stroke cost studies were reviewed. Although the selected cost of illness studies used different methodologies, the estimated expenditures for stroke are approximately similar. The proportion of national health care in the 8 countries studied is unequivocal for the more recent studies, ie, ≈3% of total health care expenditures. A shift is observed from the inpatient treatment costs (in the first year) toward outpatient treatment and long-term care costs (in the latter years). Furthermore, it is remarkable that in the studies, little attention is paid to costs borne by the patient and family or to the costs of comorbidity. Conclusions— This study highlights the importance of studying the economic consequences of stroke and of interpreting the results on the international level. The results of stroke cost studies provide insight into the distribution of the costs of stroke and the impact of stroke on the national expenditure on health care.
Differentiation Therapy Exerts Antitumor Effects on Stem-like Glioma Cells

Purpose: Stem-like tumor cells comprise a highly tumorigenic and therapy-resistant tumor subpopulation, which is believed to substantially influence tumor initiation and therapy resistance in glioma. Currently, therapeutic, drug-induced differentiation is considered as a promising approach to eradicate this tumor-driving cell population; retinoic acid is well known as a potent modulator of differentiation and proliferation in normal stem cells. In glioma, knowledge about the efficacy of retinoic acid–induced differentiation to target the stem-like tumor cell pool could have therapeutic implications. Experimental Design: Stem-like glioma cells (SLGC) were differentiated with all-trans retinoic acid–containing medium to study the effect of differentiation on angiogenesis, invasive growth, as well as radioresistance and chemoresistance of SLGCs. In vivo effects were studied using live microscopy in a cranial window model. Results: Our data suggest that in vitro differentiation of SLGCs induces therapy-sensitizing effects, impairs the secretion of angiogenic cytokines, and disrupts SLGCs motility. Further, ex vivo differentiation reduces tumorigenicity of SLGCs. Finally, we show that all-trans retinoic acid treatment alone can induce antitumor effects in vivo. Conclusions: Altogether, these results highlight the potential of differentiation treatment to target the stem-like cell population in glioblastoma. Clin Cancer Res; 16(10); 2715–28. ©2010 AACR.
A visual servoing system for an aquatic swimming robot

This paper describes a visual servoing system for an underwater legged robotic system named AQUA and initial experiments with the system performed in the open sea. A large class of significant applications can be leveraged by allowing such a robot to follow a diver or some other moving target. The robot uses a suite of sensing technologies, primarily based on computer vision, to allow it to navigate in shallow-water environments. The visual servoing system described here allows the robot to track and follow a given target underwater. The servo package is made up of two distinct parts: a tracker and a feedback controller. The system has been evaluated in the sea water and under natural lighting conditions. The servo system has been tested underwater, and with minor modifications, the system can be used while the robot is walking on the ground as well.
The single stator dual rotor PMSM for HEV: Two windings and 4 leg inverter control

This paper proposes a single stator dual rotor PMSM for HEV drive-system with two distinct stator windings in Δ connection, four leg inverter and two capacitors connected in series, with Field Oriented Control new solution. The four leg inverter that drives the two rotors should result in additional reliability and compactness through at the cost of addition kVA rating. The A and B phases of both machines are connected to dedicated legs whereas C phase of both machines is connected to the neutral point of the two-split capacitors. The standard PWM technique in three-phase voltage source inverters is not directly applicable because only two phases may be modulated. So, a dedicated PWM strategy that reduces the capacitor middle point voltage pulsations is introduced and “tested” through extensive digital results.
Anisotropic Feature-Preserving Denoising of Height Fields and Bivariate Data

In this paper, we present an efficient way to denoise bivariate data like height fields, color pictures or vector fields, while preserving edges and other features. Mixing surface area minimization, graph flow, and nonlinear edge-preservation metrics, our method generalizes previous anisotropic diffusion approaches in image processing, and is applicable to data of arbitrary dimension. Another notable difference is the use of a more robust discrete differential operator, which captures the fundamental surface properties. We demonstrate the method on range images and height fields, as well as greyscale or color images. CR Categories: I.3. 7 [Computer Graphics] Three-Dimensional Graphics and Realism; I.4. 3 [Image Processing and Computer Vision] Enhancement.
Influence of Altitude on Free Radical Scavenging Potential and Total Reducing Capacity of Medicinal Plant Yarrow ( Achillea wilhelmsii

To evaluate the effects of altitude on free radical scavenging potential and total reducing capacity of the medicinal plant Achillea wilhelmsii C. Koch, aerial parts of yarrow were collected at the flowering stage from four altitude of Dena (2448, 1890, 1800and 1739 m) and three altitude ofBoyer –Ahmad(2373, 1793 and 1485 m) districts located in Kohgiluyeh and Boyer-Ahmad province (latitude 30.67 N, longitude 51.60E). Free radical scavenging potential and total reducing capacity of methanolic extracts of the plant samples were determined by DPPH (1,1-diphenyl-2-picrylhydrazylradical) and Folin-Ciocalteu assays, respectively. Free radical scavenging potential expressed as µmol Trolox equivalent g -1 DW (µmol TE g -1 DW) ranged from 508.27 to 155.50. Samples collected from the lowest altitude of Dena and Boyer-Ahmad-districts (samples “D” and “G”) showed the highest free radical scavenging potential. Total reducing capacity ranged from 65.15 to 51.83 mg gallic acid equivalent g -1 DW (mg GAE g -1 DW). Samples collected from the lowest altitude of Boyer-Ahmad district (Samples “G”) showed the highest total reducing capacity with 22.6 percent increase compared to the highest altitude in this region. Although free radical scavenging potential and total reducing capacity both increased with reduced altitude in Boyer-Ahmad, such close relationship was not observed in Dena district. It is concluded that free radical scavenging potential and total reducing capacity of the medicinal plant yarrow is affected by altitude and lower altitude may favor higher antioxidant capacity.
High-Dimensional Shape Fitting in Linear Time

Abstract Let $P$ be a set of $n$ points in $\Re^d$. The {\em radius} of a $k$-dimensional flat ${\cal F}$ with respect to $P$, which we denote by ${\cal RD}({\cal F},P)$, is defined to be $\max_{p \in P} \mathop{\rm dist}({\cal F},p)$, where $\mathop{\rm dist}({\cal F},p)$ denotes the Euclidean distance between $p$ and its projection onto ${\cal F}$. The $k$-flat radius of $P$, which we denote by ${R^{\rm opt}_k}(P)$, is the minimum, over all $k$-dimensional flats ${\cal F}$, of ${\cal RD}({\cal F},P)$. We consider the problem of computing ${R^{\rm opt}_k}(P)$ for a given set of points $P$. We are interested in the high-dimensional case where $d$ is a part of the input and not a constant. This problem is NP-hard even for $k = 1$. We present an algorithm that, given $P$ and a parameter $0 < \eps \leq 1$, returns a $k$-flat ${\cal F}$ such that ${\cal RD}({\cal F},P) \leq (1 + \eps) {R^{\rm opt}_k}(P)$. The algorithm runs in $O(nd C_{\eps,k})$ time, where $C_{\eps,k}$ is a constant that depends only on $\eps$ and $k$. Thus the algorithm runs in time linear in the size of the point set and is a substantial improvement over previous known algorithms, whose running time is of the order of $d n^{O(k/\eps^c)}$, where $c$ is an appropriate constant.
Topical Review on Stomata and Water Use Ef fi ciency Stomatal Size , Speed , and Responsiveness Impact on Photosynthesis and Water Use Ef fi ciency 1 [ C ]

The control of gaseous exchange between the leaf and bulk atmosphere by stomata governs CO2 uptake for photosynthesis and transpiration, determining plant productivity and water use efficiency. The balance between these two processes depends on stomatal responses to environmental and internal cues and the synchrony of stomatal behavior relative to mesophyll demands for CO2. Here we examine the rapidity of stomatal responses with attention to their relationship to photosynthetic CO2 uptake and the consequences for water use. We discuss the influence of anatomical characteristics on the velocity of changes in stomatal conductance and explore the potential for manipulating the physical as well as physiological characteristics of stomatal guard cells in order to accelerate stomatal movements in synchrony with mesophyll CO2 demand and to improve water use efficiency without substantial cost to photosynthetic carbon fixation. We conclude that manipulating guard cell transport and metabolism is just as, if not more likely to yield useful benefits as manipulations of their physical and anatomical characteristics. Achieving these benefits should be greatly facilitated by quantitative systems analysis that connects directly the molecular properties of the guard cells to their function in the field.
The push-pull intercrop Desmodium does not repel, but intercepts and 1 kills pests 2

18 Over two decades ago, an intercropping strategy was developed that received critical acclaim for 19 synergizing food security with ecosystem resilience in smallholder farming. The push-pull strategy 20 reportedly suppresses lepidopteran pests in maize through a combination of a repellent intercrop 21 (push), commonly Desmodium spp. , and an attractive, border crop (pull). Key in the system is the 22 intercrop’s constitutive release of volatile terpenoids that repel herbivores. However, the earlier 23 described volatiles were not detectable in the headspace of Desmodium , and only minimally upon 24 herbivory. This was independent of soil type, microbiome composition, and whether collections were 25 made in the laboratory or in the field. Further, in oviposition choice tests in a wind tunnel, maize with 26 or without an odor background of Desmodium was equally attractive for the invasive pest Spodoptera 27 frugiperda . In search of an alternative mechanism, we found that neonate larvae strongly preferred 28 Desmodium over maize. However, their development stagnated
B RO GN ET : M OMENTUM C ONSERVING G RAPH N EU - RAL S TOCHASTIC D IFFERENTIAL E QUATION FOR L EARNING B ROWNIAN D YNAMICS

Neural networks (NNs) that exploit strong inductive biases based on physical laws and symmetries have shown remarkable success in learning the dynamics of physical systems directly from their trajectory. However, these works focus only on the systems that follow deterministic dynamics, such as Newtonian or Hamiltonian. Here, we propose a framework, namely Brownian graph neural networks (B RO GN ET ), combining stochastic differential equations (SDEs) and G NN s to learn Brownian dynamics directly from the trajectory. We modify the architecture of B RO GN ET to enforce linear momentum conservation of the system, which, in turn, provides superior performance on learning dynamics as revealed empirically. We demonstrate this approach on several systems, namely, linear spring, linear spring with binary particle types, and non-linear spring systems, all following Brownian dynamics at finite temperatures. We show that B RO GN ET significantly outperforms proposed baselines across all the benchmarked Brownian systems. In addition, we demonstrate zero-shot generalizability of B RO GN ET to simulate unseen system sizes that are two orders of magnitude larger and to different temperatures than those used during training. Finally, we show that B RO GN ET conserves the momentum of the system resulting in superior performance and data efficiency. Altogether, our study contributes to advancing the understanding of the intricate dynamics of Brownian motion and demonstrates the effectiveness of graph neural networks in modeling such complex systems.
FE Modelling of Two Femur Fixation Implants

In the pool of women over the age of 50, the likeliness of an atypical fracture increases drastically, partly due to osteoporosis. With a pre-existing implant in the femur bone, inserted due to a prior atypical fracture, treating a later femoral neck fracture is complex and risky. Currently, a fractured femoral diaphysis is treated using an intermedullary nail which is ﬁxed to the femur bone either through the femoral neck (Recon locking method) or through the lesser trochanter (Antegrade locking method). In a study conducted by Bögl et.al. JBJS 102.17 (2020), pp. 1486-1494 , it is found that the ﬁxation of the intermedullary nail through the femoral neck reduces the risk of future femoral neck fractures. The study also states that more than 50% of the patients with atypical femoral fractures related to biophosphonate treatment for osteoporosis (within the study sub population) were treated with the Antegrade locking implant. There does not exist much literature that reasons as to how one locking method is showing lesser risk of re-operation as compared to the other. The purpose of this study is to look into the effects these two implants have on the femur bone using the Finite Element Analysis (FEA). The study presented is aimed at comparing the results of the ﬁnite element analysis for the Recon implant model (Recon model) and Antegrade implant model (Antegrade model). The femur model without the implants (native bone model) is used to verify material behavior, while the other two are used for the comparison to study the stress-strain distribution, primarily in the neck region. This is a patient speciﬁc study, hence the femur bone model is generated using patient Computed Tomography (CT) scans. The bone model was assigned a heterogeneous isotropic material property derived from patient CT data. The ﬁnite element (FE) model of the bone was meshed using Hypermesh. The peak loading condition including the muscle forces were applied on the native bone model along with the Recon and the Antegrade model. While the loading conditions
the Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation.

Machine Learning (ML) is an increasingly popular tool for designing wireless systems, both for communication and sensing applications. We design and evaluate the impact of practically feasible adversarial attacks against such ML-based wireless systems. In doing so, we solve challenges that are unique to the wireless domain: lack of synchronization between a benign device and the adversarial device, and the effects of the wireless channel on adversarial noise. We build, RAFA (RA-dio Frequency Attack), the first hardware-implemented adversarial attack platform against ML-based wireless systems and evaluate it against two state-of-the-art communication and sensing approaches at the physical layer. Our results show that both these systems experience a significant performance drop in response to the adversarial attack.
Lifelong Learning: A Case Study.

Abstract : Machine learning has not yet succeeded in the design of robust learning algorithms that generalize well from very small datasets. In contrast, humans often generalize correctly from only a single training example, even if the number of potentially relevant features is large. To do so, they successfully exploit knowledge acquired in previous learning tasks, to bias subsequent learning. This paper investigates learning in a lifelong context. Lifelong learning addresses situations where a learner faces a stream of learning tasks. Such scenarios provide the opportunity for synergetic effects that arise if knowledge is transferred across multiple learning tasks. To study the utility of transfer, several approaches to lifelong learning are proposed and evaluated in an object recognition domain. It is shown that all these algorithms generalize consistently more accurately from scarce training data than comparable "single-task" approaches.
Geographic envelope of the Moon and the identification of Moon landscapes with the use of the axiomatic method

Abstract Three consequent concepts that build up the algorithm of the identification of modern landscapes on the Moon surface are suggested. They are anaglyphonosphere axiomatic and landscape concepts obtained with the use of the axiomatic method. The first concept depicts the geographic envelope of the Moon as an anaglyphonosphere layer (relief) that is a continuum (total environment). The latter becomes the research subject for both a geomorphologist and a landscape researcher. Continuity, dynamics, range (amplitude), and erosion potential determine anaglyphonosphere. Axiomatic concept means constructing the sole scheme (mathematically determined) of the search for the elementary surface units using the geometric interpretation of surface patterns of the Moon and its landscape interpretation. The landscape concept is based on the classical principles of the landscape theory and the axiomatic principles of the previous concept. The synthesis of concepts is implemented in the models of Moon landscapes of four scales: zero, linear, two- and three-dimensional. The paper offers the last two models of Davy Catena. Proposed concepts with appropriate correction can be used in parallel studies of the natural environment: geological, geomorphological, climatic, etc. The advantages of the axiomatic method consist in the objective approach to the division of the surface into specific units (the landscapes in our case). The proposed method of identifying and displaying the landscape complexes on the lunar surface can be a significant complement for the study and mapping of terrestrial planets, satellites of planet-giants, etc.
Independent-Double-Gate FinFET SRAM Technology

Independent-double-gate (IDG) FinFET SRAM technology has been developed. V th controllable IDG-FinFET technology enables noise margin enhancement of SRAM cells. The IDG-FinFET is also effective for the reduction of variation effect due to the work function variation (WFV) of the TiN metal-gate.
Analysis of Heart Rate and Body Temperature Data Retrieval in Smartband Design with Android Applications Using the Multiplexing Method

The use of two sensors for smartband requires the use of the multiplexer method so that data does not collide with each other due to the similarity of the two sensor systems. Monitoring and recording of the patient's medical record is very necessary if there are symptoms of a disease that must be treated immediately so that the patient's condition does not get worse and knows how the pattern of a disease attacks the body's condition, this is so that the patient's condition history data can be examined by a doctor to facilitate and improve the accuracy of the diagnosis doctor. The implication in this research is that due to the many cases where the sensors collide with each other and cannot be used because the data output by the sensors collide with each other, this can be overcome by one method, namely the multiplexing method where sensor data is taken alternately at different times so that making sensor output data retrieval not at the same time, the time lag in multiplexing is required to be as little as possible so that the data display does not experience too long a delay causing the data display to be further away from real time. The purpose of this study was to examine and determine the effect of multiplexing speed on data retrieval of 2 sensors. In this study, the Wemos D1 Mini microcontroller was used to process BPM and temperature data, as well as process time using a multiplexer from both sensors, then the BPM and temperature values were displayed on the OLED screen. Based on the results of the research that has been done, it can be concluded that smartband has the lowest error of 0.06% while the biggest error is 1.71%. This study has the advantage of a portable device design and is very suitable for everyday use to monitor patient conditions, so that patients are not disturbed by the presence of this smartband. This research has a development, namely the use of a larger battery so that its use can last longer, then the use of a medical grade standard temperature sensor.
Model based robot localization using onboard and distributed laser range finders

In this paper we present a method for estimating the position of mobile robots using a combination of both robotpsilas onboard sensors and sensors at fixed locations in the environment, where we use laser range finders as sensors. This is a situation which arises in so-called intelligent spaces, where there are both static sensors and mobile robots present. The method we present extends the robot localization methods based on occupancy grids, however here occupancy grids are used to represent not only the geometry of the environment but also that of the robot. For tracking the robot we employ a particle filter. The details of the method are given and experimental results are shown to illustrate the method.
on Recent Advances in Information Mining from Big Consumer Opinion Data for Product Design

In this paper, based on more than ten years’ studies on this dedicated research thrust, a comprehensive review concerning information mining from big consumer opinion data in order to assist product design is presented. First, the research background and the essential terminologies regarding online consumer opinion data are introduced. Next, studies concerning information extraction and information utilization of big consumer opinion data for product design are reviewed. Studies on information extraction of big consumer opinion data are explained from various perspectives, including data acquisition, opinion target recognition, feature identification and sentiment analysis, opinion summarization and sampling, etc. Reviews on information utilization of big consumer opinion data for product design are explored in terms of how to extract critical customer needs from big consumer opinion data, how to connect the voice of the customers with product design, how to make effective comparisons and reasonable ranking on similar products, how to identify ever-evolving customer concerns efficiently, and so on. Furthermore, significant and practical aspects of research trends are highlighted for future studies. This survey will facilitate researchers and practitioners to understand the latest development of relevant studies and applications centered on how big consumer opinion data can be processed, analyzed and exploited in aiding product design.
Temperature dependence of isotopic fractionation factors

-The temperature dependences of the partition function ratios of gaseous molecules at low and high temperatures, originally investigated by UREY (1947) and BIGELEISENand MAYER (1947), are derived and clarified. For diatomic molecules at low temperatures, the logarithm of the partition function ratio becomes