Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification

Recently, graph convolutional network (GCN) has progressed significantly and gained increasing attention in hyperspectral image (HSI) classification due to its impressive representation power. However, existing GCN-based methods do not give full consideration to the multiscale spatial information, since the convolution operations are governed by fixed neighborhood. As a result, their performances can be limited, particularly in the regions with diverse land cover appearances. In this article, we develop a new dual interactive GCN (DIGCN) which introduces the dual GCN branches to capture spatial information at different scales. More significantly, the dual interactive module is embedded across the GCN branches, so that the correlation of multiscale spatial information can be leveraged to refine the graph information. To be concrete, the edge information contained in one GCN branch can be refined by incorporating the feature representations from the other branch. Analogously, improved feature representations can be generated in one GCN branch by fusing the edge information from the other branch. As such, the refined graph information can help enhance the representation power of the model. Furthermore, to avoid the negative effects of the manually constructed graph, our proposed model adaptively learns a discriminative region-induced graph, which also accelerates the convolution operation. We comprehensively evaluate the proposed method on four commonly used HSI benchmark data sets, and the state-of-the-art results can be achieved when compared with several typical HSI classification methods.
Anti-Inflammatory and Antioxidant Activities of Rhubarb Roots Extract

International Journal of Pharmaceutical Sciences Review and Research International Journal of Pharmaceutical Sciences Review and Research Available online at www.globalresearchonline. net © Copyright protected. Unauthorised republication, reproduction, distribution, dissemination and copying of this document in whole or in part is strictly prohibited. Available online at www.globalresearchonline. net 93 Eman A. Ibrahim, Doha H. Abou Baker, Farouk K. El-Baz* Plant Biochemistry Department, National Research Centre (NRC), 33 EL Bohouth St. (Former EL Tahrir st.), Dokki, Giza, Egypt. Medicinal and Aromatic Plant Department, National Research Centre (NRC), 33 El Bohouth St. (former El Tahrir st.), Dokki, Giza, Egypt. *Corresponding author’s E-mail: fa_elbaz@hotmail.com
Relationship Between Efficiency, Management Risk, and Profitability: An Empirical Study of Listed Banks in Saudi Arabia

This paper examines the relationship between efficiency and management risks and profitability ratios in eight of the thirteen Saudi banks listed on the Saudi Capital Market Authority over the period 2005 to 2019. This study employs panel data and two specific Estimation Methods were adopted: Panel ordinary least square (POLS), and panel feasible generalized least square (PFGLS). These two methods were used to identify the imbalances represented by autocorrelation and heteroscedasticity coming from fixed and random effects related to cross-section and periods data set. The results show that the profitability of Saudi banks is negatively affected by increasing the capital adequacy ratio and current ratio and positively affected by the employment ratios. It also found that managing banking risks represented by bad debts and credit risk was a significant negative effect on the profitability of banks. These results clearly show that Saudi banks have an excess of liquidity and an increase in the capital adequacy ratio that sometimes exceeds international standards (Basel III), positively affects the investment of funds and thus the profitability of banks. Hence, managers of Saudi Arabia’s publicly listed banks must formulate prudent monetary policies to solve the liquidity crisis and increase profitability.
Complement Factor H and the Bilaterality of Age-Related Macular Degeneration: The Blue Mountains Eye Study

Methods: The Blue Mountains Eye Study (BMES) followed up 3654 participants 49 years and older (BMES 1, 1992-1994), including 2335 (75.3% of survivors) at the 5-year (BMES 2, 1997-1999) and 1952 (76.5%) at the 10-year (BMES 3, 2002-2004) examinations. Agerelated macular degeneration retinal photographic grading used the Wisconsin system. Early and late AMD included prevalent and incident cases from all visits. CFH genotyping used TaqMan assays.
The Art in Pain on Becoming A Tattooed Person: A Grounded Theory

This study utilized a Straussian grounded theory approach to create a theory of being and becoming a tattooed person. Co-researchers were chosen using purposive and snow-balling sampling. A semi-structured interview was audiorecorded. This study answered the grand tour question “What does it mean to be a person with tattoos? ” The data was meticulously transcribed, coded, and analyzed using constant comparative analysis. The findings revealed that there were quite a few changes that happened after acquiring a tattoo. Changes in physical, social, emotional, and mental aspect were shown. However, the perception of the society about tattoos was explored wherein those in favor of tattooing urges others to acquire tattoos, yet negative ideas are still associated with tattoos like delinquency. Prejudice and its psychological and social effects were also tackled in this study. Moreover, there were concepts and roots expounded in uncovering the decision making in undergoing tattoo. Thus, 13 categories emerged from the data and were connected and analyzed to create a successful theoretical grounding and process on becoming a tattooed person.
Genetic diversity and population structure of cassava ethno-varieties grown in six municipalities in the state of Mato Grosso, Brazil

Cassava is one of the main energy foods for millions of people, and has a great diversity of ethno-varieties that have specific characteristics often not found in commercial varieties. These constitute a gene pool and therefore a genetic resource that should be conserved and preserved. In this context, the objective of our study was to evaluate the genetic diversity and population structure of ethno-varieties of cassava grown in six municipalities of the state of Mato Grosso, with the aim of characterization and conservation of the varieties found in this area. The study was carried out with 157 samples of cassava. For the molecular analyses, 15 fluorochrome-labeled SSR loci were used. Microsatellite markers amplified a total of 158 alleles. The polymorphism information content for each locus varied from 0.132 (SSRY126) to 0.838
Humanitarian Mapping with Deep Learning

This paper uses satellite imagery to support map creation in the developing world. I gather my own dataset by downloading imagery released through the U.S. State De-partment’s MapGive project and using map data provided by the Humanitarian OpenStreetMap Team. Using this data, I train several Convolutional Neural Network models designed after the SegNet architecture to perform semantic image segmentation. The output of these models are map-like images that may in a later step be used to reconstruct map data, accelerating the work of online remote mapping volunteers. This paper details progress made towards this goal; my best model’s pixel-average test accuracy of about 69% does not allow production use yet. I conclude on notes for future work.
Fabric-Attached Memory

Recent progress in Non-Volatile Memory (NVM) and Gen-Z Interconnect introduce a new type of memory pool called Fabric-Attached Memory(FAM). Until today, the massive memory pools are built via shared memory but often with severe overhead. Unlike existing solutions, FAM provides scalable memory pool with a near-local access latency. However, such hardware changes entail huge changes in software platform. To this end, we propose a scalable software platform based on the container which is widely deployed in many scalable systems. First, our platform provides extensible control plane to containers by employing broker container that accepts OpenFAM APIs. Second, we designed the data plane using bind mount to keep FAM’s direct access with memory semantic. Our control plane showed only average 7.62% drops in IOPS and 8.13% latency increase compared to without container. Also there is only negligible overhead in our data plane.
Wavelet analysis of Brazil Malvinas Confluence variation forced by wind pseudostress in different locations

Brazil Malvinas Confluence (BMC) region is one of the most energetics of the world and presents a high variability. The latitude of the confluence is well marked by the annual cycle: it is found more to the north during the austral winter and more to the south in the austral summer. Many studies were made about the variability of BMC and its possible forcing mechanisms. Thus, the aim of this study is to better understand the confluence variability and its relation to wind stress forcing in different locations. The latitude of BC separation from the coast was used as a proxy of BMC. It was obtained through the interception point between 18oC isotherm and 1000 m isobath. SST data was obtained from NOAA OISSTv2 and the zonal wind pseudostress data was extracted from CCMP project of NASA/GSFC/NOAA. The BC separation latitude presents a pronounced southward trend of 0.43o/year (±0,24), during the analyzed period. Both wind pseudostress series present negative trends too: 2.4 m2s/year (±0,96) in CBM region and 0.36 m2s/year without significance in Drake Passage. The wavelet analysis was used for each time series, and the XWT and WTC was performed using the zonal wind pseudostress for the BMC and Drake Passage region with the BC separation latitude. The winds in BMC region could be related directly to the local annual variation, and the winds in Drake Passage are responsible for the interannual variation, and, after 2004, a significant semiannual variation. Key-words: Southwest South Atlantic, Drake Passage, cross wavelet, wavelet coherence, remote sensing
THE INDUSTRIAL INSTITUTE FOR ECONOMIC AND SOCIAL RESEARCH

This paper analyzes the simultaneous relationship between R&D and foreign sales in Swedish multinational enterprises in the manufacturing sector. We argue that this two-way relationship should especially apply to multinationals based in small open economies due to the firms' high dependence on foreign markets. The only previous study addressing this issue used data on multinationals originating from the United States, a country with a large domestic market, and it did not find evidence of the hypothesized simultaneous relationship. Our empirical results suggest a positive and significant effect in both directions. JEL Classification: F23; 032.
Mediating Effect of C-reactive Protein and Aspartate Aminotransferase on Diabetes Mellitus and Myocardial Infarction Risk

Hui Zhao The Fourth A liated Hospital, Anhui Medical Univ Miao-miao Jiang The Fourth A liated Hospital, Anhui Medical Univ Sang Hu The Fourth A liated Hospital, Anhui Medical Univ Chang Su The Fourth A liated Hospital, Anhui Medical Univ Li Zhang The Fourth A liated Hospital, Anhui Medical Univ Zi-ping Cheng The Fourth A liated Hospital, Anhui Medical Univ Zhao-ping Liu The Fourth A liated Hospital, Anhui Medical Univ Qin Jiang The Fourth A liated Hospital, Anhui Medical Univ Wen Ji The Fourth A liated Hospital, Anhui Medical Univ Jing-fang Hong The Fourth A liated Hospital, Anhui Medical Univ Hui Zhang (  zhanghui310@126.com ) The Fourth A liated Hospital, Anhui Medical University, Hefei 230022, China https://orcid.org/0000-0002-34527156
Systematic characterization of generative models for de novo design of regulatory DNA

Generative machine learning algorithms have been developed for de novo generation of realistic images and videos. Recently, these approaches have also been adapted for designing and optimizing biomolecules with desired properties. However, systematic comparison of these methods for modeling regulatory DNA sequences have been lacking. Here, we present a taxonomy of generative learning algorithms and a uni-ﬁed implementation ( https://github.com/ kundajelab/seq_gen ) that enables complementary classes of algorithms to be seamlessly combined in novel ways via a common API. We then systematically characterize the performance of these methods for de novo designing gene promoter elements to optimize gene expression in yeast. We identify biologically relevant stopping criteria as critically important for the generation of meaningful novel sequence elements, and pro-pose leveraging a previously-introduced 1-nearest neighbor (1NN) approach for evaluating divergence from realistic elements. We also introduce a new generative model called a “supervised GAN”, and evaluate its performance using the aforementioned metrics. Taken together, our results constitute a valuable stepping stone towards robust de novo design of regulatory DNA sequences.
Respiratory Movement for Health Assessment by Using Internal-external Cross Correlation Investigation

Respiratory belt is a full-service home medical equipment to monitor respiration for homecare. Respiratory belt indicates breathing strength and characterizes breathing patterns. This paper describes a noninvasive respiratory movement monitoring using Magnetic Resonance Imaging (MRI) and respiratory belt simultaneously to investigate internal-external correlation. Twenty healthy subjects participated in this study and they all performed paced breathing (12 cycles/minute) during experiment. The diaphragmatic movement area and the anterior-posterior (AP) diameter of the body contour were represented as indexes of internal respiratory movement. The respiratory belt signal was represented as the external index. Cross correlation was used to evaluate the similarity between internal and external respiratory movement. The results indicated that diaphragmatic movement area versus respiratory belt signal performed strong negative correlation (R value is -0.847±0.06). The AP diameter of the body contour versus respiratory belt performed strong positive correlation (R value is 0.837±0.09). In conclusion, respiratory belt correlates strongly with diaphragmatic movement area and AP diameter of the body contour. Therefore, respiratory belt is a reliable external respiratory monitoring technique to detect respiratory movement in homecare. Keywords-cross correlation; respiratiory movement; respiratory belt; internal-external information
Perspectives On İntegrating Anti-Corruption Curriculum İn Indonesian Secondary School Education

Article History: Purpose The sole objective of the current study is to determine the impact of anti-corruption awareness and the anticorruption initiatives on ethical values and the citizenship behavior. Research Methodology In a quantitative paradigm, the mediating role of ethical values is examined between anti-corruption awareness, anti-corruption initiatives and citizenship behavior. The sample size comprised 310 eleventhgrade students from Malang, East Java, Indonesia. A questionnaire was distributed to collect the data. SEM-PLS technique was adopted to analyse the data. Findings Finding of the study reveal that there is a significant effect of anti-corruption awareness and anti-corruption initiatives on ethical values. Received: 23 Feb. 2021 Received in revised form: 5 Apr. 2021 Accepted: 13 May 2021 DOI: 10.14689/ejer.2021. 93.20
The impact of income inequality on public environmental expenditure with green consumerism

This article analyzes the impact of income inequality on environmental policy in the presence of green consumers. We ﬁrst develop a model with two main ingredients: citizens, with diﬀerent income capacities, have access to two commodities whose consumption diﬀers in terms of price and environmental impact, and they vote on the environmental policy. In this setting, there exists a unique political equilibrium in which the population is split into two groups, that diﬀer in the type of good, conventional vs. green, they consume. The analysis shows that a change in the level of inequality induces variations in both the size and composition of these two groups of citizens. This in turn determines whether or not more inequality stimulates the public policy. We then conduct an empirical investigation on a panel of European countries over the period 1996-2019. We ﬁnd the existence of an inverted J-shape relationship between inequality and public environmental spending. This outcome can be explained by the combination of a composition eﬀect, aﬀecting the green group, and a substitution eﬀect between private green consumption and public environmental spending.
Some Permanent Magnet Synchronous Motor (PMSM) Sensorless Control Methods based on Operation Speed Area

This paper compares some sensorless Permanent Magnet Synchronous Motor (PMSM) controls for driving an electric vehicle in terms of operating speed. Sensorless control is a type of control method in which sensors, such as speed and position sensors, are not used to measure controlled variables. The controlled variable value is estimated from the stator current measurement. Sensorless control performance is not as good as a sensor-based system. This paper aims are to recommend a control method for the PMSM sensorless controls that would be used to drive an electric vehicle. The methods that we will discuss are divided into four categories based on the operation speed area. They are a startup, low speed, high speed, and low and high-speed areas. The low and high-speed area will be divided into with and without switching. If PMSM more work at high speed, the most speed area that is used, we prefer to choose the method that works at high speed, that is, the modification or combination of two or more conventional methods.
Knitting 4D garments with elasticity controlled for body motion

In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in different elastic levels by single-jersey jacquard (SJJ) with two yarns. We design the distribution of elasticity for a garment by physics-based computation, the optimized elasticity on the garment is then converted into instructions for a digital knitting machine by two algorithms proposed in this paper. Specifically, a graph-based algorithm is proposed to generate knittable stitch meshes that can accurately capture the 3D shape of a garment, and a tiling algorithm is employed to assign SJJ patterns on the stitch mesh to realize the designed distribution of elasticity. The effectiveness of our approach is verified on simulation results and on specimens physically fabricated by knitting machines.
Machine versus Human Attention in Deep Reinforcement Learning Tasks

Deep reinforcement learning (RL) algorithms are powerful tools for solving visuomotor decision tasks. However, the trained models are often difficult to interpret, because they are represented as end-to-end deep neural networks. In this paper, we shed light on the inner workings of such trained models by analyzing the pixels that they attend to during task execution, and comparing them with the pixels attended to by humans executing the same tasks. To this end, we investigate the following two questions that, to the best of our knowledge, have not been previously studied. 1) How similar are the visual representations learned by RL agents and humans when performing the same task? and, 2) How do similarities and differences in these learned representations explain RL agents' performance on these tasks? Specifically, we compare the saliency maps of RL agents against visual attention models of human experts when learning to play Atari games. Further, we analyze how hyperparameters of the deep RL algorithm affect the learned representations and saliency maps of the trained agents. The insights provided have the potential to inform novel algorithms for closing the performance gap between human experts and RL agents.
Modeling and simulation of laser micro welding

Laser welding using fiber lasers of high power and quality facilitate the joining of highly conductive materials while attaining high aspect ratio welds at spot sizes in the micrometer range. Industrial applications are laser bonding of copper contacts in power electronics and battery modules. An important quality feature is a defined weld seam geometry which is determined by the physical transport phenomena during the process. This contribution targets the development of a model that serves as a basis for experimental control strategies. Reasonable assumptions for reducing the model's complexity are made by exploiting the characteristic length and time scales of the process. Laser absorption at the metal surface and heat conduction in the material are considered as the dominant phenomena to define the shape of the keyhole. Simulations are subjected to parameter variations and validated by experimental reference data.
Optoelectrical improvement of ultra‐thin Cu(In,Ga)Se2 solar cells through microstructured MgF2 and Al2O3 back contact passivation layer

Decreasing the absorber layer thickness of thin‐film solar cells can be an effective solution for cost reduction of photovoltaic electricity generation. Unfortunately, this reduction leads to detrimental effects such as incomplete photon absorption and increased charge carrier recombination at the rear electrode. To tackle these losses in ultra‐thin 0.5 µm Cu(In,Ga)Se2 (CIGS) solar cells, we developed different passivation structures made of MgF2 and Al2O3 at the molybdenum–CIGS interface, leading to localized back contacts. The influence of the distance between those contacts on the cell performance was studied by varying the periodicity of the applied 1D patterns from 6 μm to 30 μm. Thus, an increase in performance was measured for microstructured layers with a periodicity of up to 12 µm. More precisely, a MgF2 layer yielded an increase in power conversion efficiency (PCE) of up to 9%rel compared to an unpassivated cell design, and a passivation layer comprising Al2O3 led to up to a 5%rel increase in PCE. The gains were primarily attributed to an increased reflectivity of the back contact, while the formation of a negative backside field in the case of Al2O3 might have contributed to this increase by preventing electrons from recombining at the backside interface. Our findings indicate a high lateral conductivity for holes inside the multicrystalline CIGS compound over few tens of micrometres, which allows an independent design of future back contacts and light‐trapping schemes. False‐colour scanning electron microscopy cross‐section picture of a passivated solar cell, with the front contact layers coloured in green, the 0.5 µm CIGS absorber in dark red, the MgF2 passivation layer in blue, and the Mo back contact in grey.
Thermal structure of Venus upper atmosphere by a self-consistent ground-to-thermosphere GCM

We present here the thermal structure of the upper atmosphere of Venus predicted by a full self-consistent Venus General Circulation Model (GCM). The Venus GCM developed at Laboratoire de Meteorologie Dynamique (LMD) [1] is currently operational up to 150 km and it is one of the leading models in the community. Recent improvements (i.e the inclusion of physical processes relevant in the upper atmosphere, the coupling with a photochemical model) contributed to a better understanding of the upper mesosphere/lower thermosphere of Venus. Our aim is to describe the role of radiative, photochemical and dynamical effects in the observed thermal structure of those upper layers, and to evaluate the impact of current parameterisations and theoretical uncertainties on the temperature fields. Several sensitivity tests will be performed to understand the data-model discrepancies and to improve the comparison.