Miracle-dz/UniFAR-FTUs huggingface dataset:
A Proposed Methodology for the Spatial Characterization of Foliage Backgrounds.

Abstract : The role of camouflage patterns is briefly described, and the need for quantification of visual texture in this context developed. A procedure is described for developing a perceptually-based measure of the similarity of foliage textures. The procedure is based on first determining the perceptual dimensions underlying judgements of texture similarity, followed by the derivation of mathematical descriptors of these dimensions, based on digital encodings of textures. Keywords: Test methods; Australia.
Semantic dementia: autobiographical contribution to preservation of meaning

Abstract Five patients with a progressive semantic disorder were noted to produce a surprising range of nominal terms in their everyday conversation in contrast to their grossly impaired naming and word comprehension on formal tests. It was hypothesised that since general conversation revolves around autobiographical topics, a key factor in preservation of vocabulary might be the relevance of concepts to personal experience. The possible contribution of direct experience in maintenance of both verbal and nonverbal meaning was evaluated in three experiments, involving identification of (1) names of people; (2) names of places; and (3) objects. Patients performed consistently better for personally relevant than for nonpersonal names and places, a pattern of findings not seen in a control group of amnesic Alzheimer patients. Moreover, a study of object recognition in one patient revealed superior recognition for her own compared to alternative examples of the same object. The findings highlight the role of a.
Comparisons of Image Compression Using Different Transformation Techniques

— For image compression, it is very necessary that the selection of transform should reduce the size of the resultant data as compared to the original data set. For continuous and discrete time cases, wavelet transform and wavelet packet transform has emerged as popular techniques. While integer wavelet using the lifting scheme significantly reduces the computation time, a completely new approach for further speeding up the computation. First, wavelet packet transforms (WPT) and lifting scheme (LS) are used. Then an application of the LS to WPT is presented which leads to the generation of integer wavelet packet transform (IWPT). another technique is used for image compression is fractal image compression (FIC) is based on the partitioned iterated function system (PIFS) which utilizes the self-similarity property in the image to achieve the purpose of compression. , the linear regression technique from robust statistics is embedded into the encoding procedure of the fractal image compression. Another drawback of FIC is the poor retrieved image qualities when compressing corrupted images, the fractal image compression scheme should be insensitive to those noises presented in the corrupted image. This leads to a new concept of robust fractal image compression.Another technique for image compression is new multi-layered representation technique for image compression, which combine Curvelet transform and local DCT in order to benefit from the advantages of each. Curvelet transform is one of the recently developed multiscale transform, which possess directional features and provides optimally sparse representation of objects with edges, but not for the textured feature. We exploit morphological component analysis (MCA) method to separate the image into two layers: piecewise smooth layer and textured structure layer, respectively associated to curvelet transform and local DCT. Each layer is encoded independently with a different transform at a different bit rate.
Adjustment in the Workplace: The Impact of WFH on Working Mothers in Indonesia

Work from Home (WFH) has formed a new work culture in Indonesia since the Covid-19 pandemic. Positive and negative impacts are also felt during WFH. Especially for working mothers who are faced with domestic affairs and work in the same space and time. A study on 385 respondents of working mothers in Indonesia showed the effect of WFH on Work-Life-Balance (WLB). Flexibility at work time and place is the main factor that gets a positive assessment of working mothers. However, cultural views on the main role of women in the household can weaken the effectiveness of WFH implementation. The difﬁculty of dividing time between family and work makes more than half of respondents disagree if WFH continues to be implemented even though the pandemic is over. Further research is needed to analyse other factors that inﬂuence WLB during WFH.
La vacuna contra el Virus del Papiloma Humano: estado de la cuestión, principio de proporcionalidad y consentimiento informado

Within the current discussions on immunization practices, Human Papillomavirus (HPV) made various challenges from bioethics: firstly, there are controversies regarding the efficacy and safety profile of marketed vaccines, and with respect to their cost-effectiveness. Around the discussion is evident in empirical studies that the informed consent process does not provide the necessary elements for the patients and their legal representatives can participate meaningfully in the process of making decisions about vaccination. This article presents an overview of the status of the issue, with an analysis from bioethics from the principle of proportionality and the deliberative syncretic method and suggests some input to optimize the process of informed consent for the HPV vaccine.
Forest dynamics at regional scales: predictive models constrained with inventory data

Few studies have quantified regional variation in tree mortality, or explored whether species compositional changes or within-species variation are responsible for regional patterns, despite the fact that mortality has direct effects on the dynamics of woody biomass, species composition, stand structure, wood production and forest response to climate change. Using Bayesian analysis of over 430,000 tree records from a large eastern US forest database we characterised tree mortality as a function of climate, soils, species and size (stem diameter). We found (1) mortality is U-shaped vs. stem diameter for all 21 species examined; (2) mortality is hump-shaped vs. plot basal area for most species; (3) geographical variation in mortality is substantial, and correlated with several environmental factors; and (4) individual species vary substantially from the combined average in the nature and magnitude of their mortality responses to environmental variation. Regional variation in mortality is therefore the product of variation in species composition combined with highly varied mortality-environment correlations within species. The results imply that variation in mortality is a crucial part of variation in the forest carbon cycle.
How Well Can Aerosol Measurements from the Terra Morning Polar Orbiting Satellite Represent the Daily Aerosol Abundance and Properties

The Terra mission, launched at the dawn of 1999, and Aqua mission to be launched soon, will possess innovative measurements of the aerosol daily spatial distribution, distinguish between dust, smoke and regional pollution and measure aerosol radiative forcing of climate. Their polar orbit gives daily global coverage, however measurements are acquired at specific time of the day. To what degree can present measurements'from Terra taken between 10:00 and 11:30 AM local time, represent the daily average aerosol forcing of climate? Here we answer this question using 7 years of data from the distributed ground based 50-70 instrument Aerosol Robotic Network (AERONET). This AERONET half a million measurement data set shows that Terra aerosol measurements represent the daily average values within 5%. The excellent representation is found for large dust particles or small aerosol particles from fires or regional pollution and for any range of the optical thickness, a measure of the amount of aerosol in the atmosphere. https://ntrs.nasa. gov/search.jsp? R=20000085547 2020-04-17T10:52:12+00:00Z
ICASE Report No . 97-64 On the Universality of the Kolmogorov Constant in Numerical Simulations of Turbulence

Motivated by a recent survey of experimental data [K.R. Sreenivasan, Phys. Fluids 7, 2778 (1995)], we examine data on the Kolmogorov spectrum constant in numerical simulations of isotropic turbulence, using results both from previous studies and from new direct numerical simulations over a range of Reynolds numbers (up to 240 on the Taylor scale) at grid resolutions up to 512. It is noted that in addition to k−5/3 scaling, identification of a true inertial range requires spectral isotropy in the same wavenumber range. We found that a plateau in the compensated three-dimensional energy spectrum at kη ≈ 0.1−−0.2, commonly used to infer the Kolmogorov constant from the compensated three-dimensional energy spectrum, actually does not represent proper inertial range behavior. Rather, a proper, if still approximate, inertial range emerges at kη ≈ 0.02−0.05 when Rλ increases beyond 140. The new simulations indicate proportionality constants C1 and C in the oneand three-dimensional energy spectra respectively about 0.60 and 1.62. If the turbulence were perfectly isotropic then use of isotropy relations in wavenumber space (C1 = 18/55 C) would imply that C1 ≈ 0.53 for C = 1.62, in excellent agreement with experiments. However the oneand three-dimensional estimates are not fully consistent, because of departures (due to numerical and statistical limitations) from isotropy of the computed spectra at low wavenumbers. The inertial scaling of structure functions in physical space is briefly addressed. Since DNS is still restricted to moderate Reynolds numbers, an accurate evaluation of the Kolmogorov constant is very difficult. We focus on providing new insights on the interpretation of Kolmogorov 1941 similarity in the DNS literature and do not consider issues pertaining to the refined similarity hypotheses of Kolmogorov (K62).
The civil society and democracy in Gulf and Maghreb countries (a comparative study)

Democracy is the optimal goal for many nations; however, reaching it is not an easy task as more efforts should be devoted, environment should be paved, and many roles should be played. Civil society organizations are supposed to have a fundamental role in the transformation to democracy. While the Arab countries before the Tunisian and Egyptian revolution lack democratic political systems, many scholars and donors believe that associations could help in pushing democracy. This paper focuses on two main sub region blocs in the Arab world which are the Gulf and the Maghreb. In Maghreb bloc the paper highlights the cases of Algeria, Morocco and Tunisia; concerning the Gulf countries the paper discusses the Gulf Cooperation Countries (GCC) which are Bahrain, Oman, Saudi Arabia, Kuwait, Qatar and the Emirates. Both blocs have distinctive characteristics as sub regions within the Arab World. The paper discusses the current and the expected role of civil society in pushing the political reform and democracy in the Arab countries.
THE TRANSFORMATION OF ACADEMIC WORK: FACTS AND ANALYSIS

This paper outlines the main changes that have effected a transformation in the nature of academic work: on the one hand, the increasing diversification and specialisation of academic tasks, and on the other, new forms of control over academic work. An analysis of these trends leads to a discussion of the relationships between the evolution of academic work and non-academic work. The academic profession has always been in the process of change. While reading historical research or looking at academics’ reflections on their situation over time (for instance Wilson, 1980; Rice, 1986; Altbach, 1980, 1996, and 1998; Clark, 1987), it is striking that, whatever their particular historical moment, these writers all comment that the academic profession is no longer the same. There is clearly no ideal, universal, and stable state of the academic profession. Like all social bodies, this profession is a living entity, adaptive and responsive to external changes, but it also seeks to enact its own environment. These developments affect the relationships between the academic profession and other parts of society, as well as the position of this particular profession within society. These changes also affect the profession’s internal modes of regulation and its autonomy and ability to avoid the intervention of external forces. Finally, the content of academic activities themselves and the norms according to which they are to be achieved are also subject to change. writing academic conclusion: professoriate. ” the
Alcohol consumption during pregnancy: the result of a risky consumption trajectory?

This article is published in Open Access under the Creative Commons Attribution license, which allows use, distribution, and reproduction in any medium, without restrictions, as long as the original work is correctly cited. The article by Cabral et al. 1, published in this issue of CSP, addresses a public health problem in Brazil and worldwide: the high prevalence of alcohol consumption during pregnancy and its effect on the health of the mother and fetus. Alcohol consumption during pregnancy is associated with many gestational outcomes, including stillbirth, miscarriage, preterm delivery, intrauterine growth retardation and low birth weight 2,3,4, and a variety of lifelong conditions known as fetal alcohol spectrum disorders (FASDs) 5,6. One of the most disabling potential outcomes of alcohol consumption during pregnancy is the risk of developing fetal alcohol syndrome (FAS), the most severe and visibly identifiable FASD, which causes permanent brain damage, congenital anomalies, and deficits in cognitive behavioral, emotional, and adaptive functioning 7. To mitigate the problem, for more than a decade, guidelines from international organizations/institutions have recommended that women who are pregnant or planning to become pregnant abstain from any alcohol consumption during this period 8,9. Despite this, the prevalence of this consumption during pregnancy remains high worldwide. However, Brazil has a gap on this topic, with few studies and most of them conducted in specific populations. The article by Cabral et al. 1 fills this gap as the first nationally representative population study to evaluate the set of factors related to the Brazilian reality of inequalities in access to services and social vulnerability that contribute to the high prevalence of alcohol consumption among pregnant women. Among the factors associated with higher prevalence of alcohol consumption during pregnancy and the presumptive diagnosis of misuse, young age at pregnancy stands out, especially among adolescents aged 12 to 19 years. This is one of the most important indicators of social vulnerability, causing psychosocial and economic harm in women’s lives. Thus, understanding the role of early alcohol consumption in this scenario will allow the development of public policies aimed at greater surveillance of alcohol consumption in this age group and the screening of groups at higher risk for alcohol consumption during pregnancy. To what extent does the high prevalence of alcohol consumption among women in adolescence and early adulthood affect its persistence during pregnancy? To answer this question, we need to take a step back and consider trends in alcohol consumption among adolescents and young adults in recent decades. Alcohol consumption during pregnancy: the result of a risky consumption trajectory?
Metric Residual Networks for Sample Efficient Goal-conditioned Reinforcement Learning

Goal-conditioned reinforcement learning (GCRL) has a wide range of potential real-world applications, including manipulation and navigation problems in robotics. Especially in such robotics tasks, sample efficiency is of the utmost importance for GCRL since, by default, the agent is only rewarded when it reaches its goal. While several methods have been proposed to improve the sample efficiency of GCRL, one relatively under-studied approach is the design of neural architectures to support sample efficiency. In this work, we introduce a novel neural architecture for GCRL that achieves significantly better sample efficiency than the commonly-used monolithic network architecture. The key insight is that the optimal action-value function Q^*(s, a, g) must satisfy the triangle inequality in a specific sense. Furthermore, we introduce the metric residual network (MRN) that deliberately decomposes the action-value function Q(s,a,g) into the negated summation of a metric plus a residual asymmetric component. MRN provably approximates any optimal action-value function Q^*(s,a,g), thus making it a fitting neural architecture for GCRL. We conduct comprehensive experiments across 12 standard benchmark environments in GCRL. The empirical results demonstrate that MRN uniformly outperforms other state-of-the-art GCRL neural architectures in terms of sample efficiency.
Principles of Glacier Mechanics

Why study glaciers? some basic concepts mass balance flow of a crystalline material the velocity field in a glacier temperature distribution in polar ice sheets the coupling between a glacier and its bed water flow in and under glaciers - geomorphic implications stress and deformation stress and velocity distribution in an idealized glacier applications of stress and deformation principles to classical problems response of glaciers to changes in mass balance problems.
Ecology of Melastoma malabathricum L. in West Sabah

Melastoma malabathricum L. is a well known wayside shrub found commonly in Malaysia and is the commonest member in the family Melastomataceae. In this study, the distribution of M malabathricum in Klias Peat Swamp Forest and Universiti Malaysia Sabah (UMS) Hill was studied and compared by using random selective sampling method. The soil properties such as moisture, organic content and pH of these two study sites were analyzed according British Standard laboratory manual. Growth rate of plants and flower visitor observation were also included in this study. The results showed that there was a significant difference in density between the two study sites (p<0.05). The density and coverage percentage of M malabathricum plants in Klias Peat Swamp Forest was higher than that of UMS Hill. In Klias Peat Swamp Forest, 524 individuals were found and the density was 1.40 plant/m2. There were 125 individuals found in UMS Hill and the density was 0.33 plant/m2. The moisture content, organic content and pH of soil in the two study sites also showed significant difference. The soil pH acidity, percentage of moisture and organic content of soil in Klias Peat Swamp Forest were higher than in UMS Hill. The density of plants had significant strong positive correlation relationship with moisture content (r= 0.667, p<0.05) and organic contents of soil samples (r= 0.554, p<0.05). However, the density of plants had significant strong negative correlation with soil pH (r= -0.615, p<0.05). Mean of tree growth rate were different in stem and branches. The growth rate of stem is faster compared to branches. Ants were the most common visitor to M malabathricum flowers. Insect activity was highest between 0700 to 1200hrs
DECOUPLING-BASED APPROACH TO CENTRALITY DETECTION IN HETEROGENEOUS MULTILAYER NETWORKS by KIRAN MUKUNDA

DECOUPLING-BASED APPROACH TO CENTRALITY DETECTION IN HETEROGENEOUS MULTILAYER NETWORKS Kiran Mukunda, M.S. The University of Texas at Arlington, 2021 Supervising Professor: Prof. Sharma Chakravarthy Graph analysis is one of the techniques widely used for data analysis. It is used extensively on single graphs. Its ability to capture entities and relationships makes it an attractive data model. Search on graphs, such as finding triangles, cliques, shortest paths, etc., and aggregate analysis, such as communities, substructure, or centrality measures have well-defined algorithms for single graphs. The centrality measure, which is the focus of this thesis, identifies the most important nodes in a graph or network. While there are many centrality measures, the most commonly used ones are degree and betweenness centrality. Algorithms for analyzing these measures are numerous for single graphs. In addition to graphs, multilayer networks (MLNs) are being used to model complex data sets. MLNs consist of several layers, each being a graph. If there are different types of entities in each layer and inter-layer edges are present, then the network is an example of a Heterogeneous Multilayer Network (HeMLN). Due to the lack of algorithms for HeMLNs, they are currently analyzed using aggregation of HeMLN
The Phytochemical Profiling, In Vitro Antioxidant, and Hepatoprotective Activity of Prenanthes purpurea L. and Caffeoylquinic Acids in Diclofenac-Induced Hepatotoxicity on HEP-G2 Cells

Oxidative stress is a common phenomenon of many liver disorders; it both affects patient survival and directly influences the applicability, effectiveness, and toxicity of drugs. In the pursuit of reliable natural remedies for hepatoprotection, this study reports on the complete phytochemical characterization, antioxidant, and hepatoprotective activities of the Prenanthes purpurea methanol-aqueous extract in an in vitro model of diclofenac-induced liver injury (DILI). An ultra high-performance liquid chromatography–high-resolution mass spectrometry analysis (UHPLC-HRMS) was conducted, delineating more than 100 secondary metabolites for the first time in the species, including a series of phenolic acid-hexosides, acylquinic, acylhydroxyquinic and acyltartaric acids, and flavonoids. Quinic acid, chlorogenic, 3,5-dicaffeoylquinic and 5-feruloylhydroxyquinic acid, caffeoyltartaric and cichoric acids, eryodictiol-O-hexuronide, and luteolin O-hexuronide dominated the phytochemical profile and most likely contributed to the observed hepatoprotective activity of the studied P. purpurea leaf extract. The potency and molecular basis of cellular protection were investigated in parallel with pure caffeoylquinic acids in a series of pretreatment experiments that verified the antiapoptotic and antioxidant properties of the natural products.
Multi-user, Scalable 3D Object Detection in AR Cloud

As AR Cloud gains importance, one key challenge is large scale, multi-user 3D object detection. Current approaches typically focus on the single-room, single-user scenarios. In this work, we present an approach for multi-user and scalable 3D object detection, based on distributed data association and fusion. We use an off-the-shelf detector to detect object instances in 2D and then combine them in 3D, per object while allowing asynchronous updates to the map. The distributed data association and fusion allows us to scale the detection to a large number of users concurrently, while maintaining a lower memory footprint without loss in accuracy. We show empirical results, where the distributed and centralized approaches achieve comparable accuracy on the ScanNet dataset while reducing the memory consumption by a factor of 15.
Zero-Threshold-Voltage MOSFETs: A Survey

—In this paper, we report an overview concerning zero-threshold-voltage MOS transistors and analyze the usefulness of this kind of transistor for low-voltage and low-power applications. Firstly, we compare the zero-V T transistors to other two types os MOSFETs from the IBM 130-µm CMOS technology. Then simulation results and measured data are used to derive design insight into the use of zero-V T devices, which in fact present a better overall performance for ultra-low supply voltages in comparison with low-threshold-voltage and standard MOSFETs in the same technology.