Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for multiple chemical ordering in AlGaN grown by metalorganic chemical vapor deposition

In contrast to the GaN/InN system where there is a misfit of about 10%, the misfit between AlN and GaN is only 2.5%, and one would expect the growth of AlGaN to be more stable. In this work, it is shown that the growth of AlGaN can be complicated. Even in the low Al composition range, 10%–15%, many types of chemical ordering take place: AlN/GaN (1:1), Al0.25Ga0. 75N(3:1) only recently noticed in InGaN, and we show evidence for an additional type of chemical ordering which corresponds to Al0.16Ga0. 84N(10:2). The three types were found to coexist in the same layers, meaning that the growth may lead to nonhomogeneous composition in the AlGaN layer.
Reduced pressure–chemical vapor deposition of Ge thick layers on Si(001) for 1.3–1.55-μm photodetection

Ge-based photodetectors operating in the low loss windows (1.3–1.6 μm) of silica fibers are highly desirable for the development of optical interconnections on silicon-on-insulator substrates. We have therefore investigated the structural and optical properties of Ge thick films grown directly onto Si(001) substrates using a production-compatible reduced pressure chemical vapor deposition system. We have first of all evidenced a Ge growth regime which is akin to a supply-limited one in the 400–750 °C temperature range (Ea=6.9 kcal mol−1). The thick Ge layers grown using a low-temperature/high-temperature approach are in a definite tensile-strain configuration, with a threading dislocation density for as-grown layers of the order of 9×108 cm−2 (annealed: <2×108 cm−2). The surface of those Ge thick layers is rather smooth, especially when considering the large lattice mismatch between Ge and Si. The root-mean-square roughness is indeed of the order of 0.6 nm (2 nm) only for as-grown (annealed) layers. A che.
SlMYB72 affects pollen development by regulating autophagy in tomato

Abstract The formation and development of pollen are among the most critical processes for reproduction and genetic diversity in the life cycle of flowering plants. The present study found that SlMYB72 was highly expressed in the pollen and tapetum of tomato flowers. Downregulation of SlMYB72 led to a decrease in the amounts of seeds due to abnormal pollen development compared with wild-type plants. Downregulation of SlMYB72 delayed tapetum degradation and inhibited autophagy in tomato anther. Overexpression of SlMYB72 led to abnormal pollen development and delayed tapetum degradation. Expression levels of some autophagy-related genes (ATGs) were decreased in SlMYB72 downregulated plants and increased in overexpression plants. SlMYB72 was directly bound to ACCAAC/ACCAAA motif of the SlATG7 promoter and activated its expression. Downregulation of SlATG7 inhibited the autophagy process and tapetum degradation, resulting in abnormal pollen development in tomatoes. These results indicated SlMYB72 affects the tapetum degradation and pollen development by transcriptional activation of SlATG7 and autophagy in tomato anther. The study expands the understanding of the regulation of autophagy by SlMYB72, uncovers the critical role that autophagy plays in pollen development, and provides potential candidate genes for the production of male-sterility in plants.
Global mapping of greenhouse gases and air pollutants

beyond, for only thus will he fully understand the world in which he lives, Socrates (470-399 B.C.) observed. Two and a half millennia later satellites orbiting the earth duly obliged, taking images spectrally resolved of the earth atmosphere in order to gain a better understanding of ozone chemistry, air pollution and of climate change. SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartograghY) fighting light and shadow in Greek mythology, is an optical spectrometer [1,2,3 and see Box 1] developed by German, Dutch and Belgian scientists and industry as a contribution in kind to ENVISAT, Europe’s biggest satellite (see Box 2). Launched on March 1 2002 by a European Ariane-5 rocket, it has since completed nearly 30.000 orbits around the earth, producing more than 35 million measurement scenes. Its projected 5 year lifetime has now passed. Time to take stock.
Human Action Recognition of Triangle Mesh Sequence Representation

: Considering the existing research works of human motion recognition are based on skeleton and video representations, a human motion classification method for triangle mesh sequence representation is proposed. Firstly, selecting the first frame of the triangle mesh sequence as the template model, the difference between each subsequent frame of the sequence and the template model is calculated by using the shape difference operator, which is expressed as the shape difference information tensor; Then, the shape difference information tensor is input into the deep network composed of two-dimensional convolution network and long short-term memory network to extract sequential action features for human action classification. The experimental results show that the classification accuracy of this method on human motion dataset AMASS reaches 100.00%.
EMPLOYEE PERFORMANCE HINGED ON INTERNAL CAPABILITY: A PEEP INTO DEPOSIT MONEY BANKS IN ANAMBRA STATE

This work determined the influence of internal capabilities on employee performance in selected deposit money banks in Anambra state. Specifically, however, the study assessed the effect of employee training on customer satisfaction and identified the nature of the relationship between operational flexibility and customer retention. This study was anchored on the Knowledge Base Theory. A survey research design was deployed for this work with a population of all the staff of 6 selected deposit money banks in Anambra state Nigeria, which was put at 1,110 staff. However, a sampled size of 285 was used, after the application of Krejcie and Morgan's (1970) sample size determination formula. Data for the study was collected using a structured questionnaire, which was subjected to both validity and reliability tests. The data analysis technique for the study was simple regression and hypotheses were tested at a 5% level of significance. The results revealed that employee training has a statistically significant effect on customer satisfaction (r = .970; R-Square = .940, P-value < 0.05) and that there is a statistically significant relationship between operational flexibility and customer retention in DMBs in Anambra state (r = .971; R-Square = .943, P-value < 0.05). The study therefore concluded that internal capabilities have an influence on the performance of employees because training and operational flexibility were seen to be positively related to customer satisfaction and retention respectively. On the strength of this, it was recommended that the management of the banks should continue training and retraining employees especially in the area of customer relations as it has been seen to be responsible for customer satisfaction in DMBs in Anambra state. Keywords: Employee Performance, Internal Capability, Employee Training, Customer Satisfaction, Operational Flexibility and Customer Retention.
General Relativity and the Divergence Problem in Quantum Field Theory

Possible physical consequences of general relativity for the elementary particle problem have usually been assumed to be negligible, due to the weakness of the gravitational coupling constant. It has been felt that since the effects of the new particles and the energies at which current theory becomes invalid occur very much below the domain for which gravitation becomes significant, a correct future theory will obviate the necessity of considering relativity in this context. It is presumed that, in any case, such a correct theory will differ so radically from current ideas, that arguments based on these will lose their validity. Further, general relativity is sometimes thought to be purely macroscopic in applicability, and to lose its meaning in subatomic regions where the concept of metric (or possibly metric operator) is not very transparent.
A Pilot Study on the Effect of Virgin Coconut Oil On Serum Lipid Profile and HS CRP Level Among Post Acute Coronary Syndrome Patients: A Randomized Controlled Trial

ABSTRACT Introduction: Acute coronary syndrome (ACS) is a leading cause of death in Malaysia and worldwide. Besides, teh current treatment which involves teh prescription of statins is found to TEMPhas several side TEMPeffects on ACS patients. Those side TEMPeffects TEMPhas guided teh author to introduce virgin coconut oil (VCO) as supplemental management of ACS. However, its benefits TEMPhas not been widely tested on humans. Methodology: dis study examines teh use of VCO among ACS patients via a crossover trial. It seeks to ascertain teh TEMPeffect of VCO on serum lipid profile and hs-CRP level among ACS patients. Result: VCO was found to be statistically significant in reducing serum lipid level and hs-CRP level (p<0.001). These findings measured from small to moderate Cohen’s d TEMPeffect size, thus proving teh results from dis study as statistically and clinically significant. Conclusion: These findings suggest dat dietary intake wif saturated fatty acid (C6 to C12) can improve health condition. Keywords: virgin coconut oil, acute coronary syndrome, saturated fatty acid, medium-chain triglycerides
An Adaptive Design for Multi-Arm Clinical Trials

The randomized play-the-winner (RPW) rule is very useful in clinical trials for patient allocation with two treatments. L. J. Wei (1979, Ann. Statist.7, 291? 296) introduces the generalized Friedman's urn (GFU) model to clinical trials of K treatments (as an extension of the RPW). In this paper, we propose a new adaptive design for multi-arm clinical trials. The proposed adaptive design proportionally depends on the success rates of each treatment, so that a treatment which is doing well is more likely to be assigned in future trials than a treatment which is doing poorly. The new design is more reasonable although it is no longer a GFU model. In the paper we show that the new design has some desirable asymptotic properties and that it has wider and easier applications in practice. Some simulations also support this new design.
Improvement of Pain and Function by Using Botulinum Toxin Type A Injection in Patients with an Osteoarthritic Knee with Patellar Malalignment: An Electromyographic Study

Objective: To determine the pain and electromyographic (EMG) amplitude ratio of the vastus medialis oblique (VMO) to the vastus lateralis (VL) after botulinum toxin type A (BTA) was injected in the bilateral osteoarthritic knee of patients with patellar malalignment for analysis. Material and methods: A total of fifteen patients were recruited; the more symptomatic knee of each patient received a BTA injection (BTA side). The other set of patients were left untreated. In all, fifteen healthy participants comprised the control group. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and numeric rating scale (NRS) for pain were assessed. The EMG amplitude of VL and VMO activity was recorded using an isokinetic dynamometer and synchronized using the BIOPAC MP100. The data were collected before and at 4, 8, and 12 weeks post–BTA injection. Results: The EMG ratios of the patient group were lower than those of the control group at all testing velocities (p < 0.05). The VMO/VL ratio improved significantly on the BTA side only. The VMO/VL ratios on the BTA side were higher than those on the untreated side (p < 0.05). Knee pain decreased significantly after the BTA injection. The EMG ratios were negatively correlated with the NRS and WOMAC scores. Conclusion: BTA injection effectively reduces knee pain and restores the EMG ratio between the VMO and VL.
Hölder continuity results for nonconvex parametric generalized vector quasiequilibrium problems via nonlinear scalarizing functions

In this paper, new results for Hölder continuity of the unique solution to a parametric generalized vector quasiequilibrium problem are established via nonlinear scalarization, with and without using the free-disposal condition. Especially, a new kind of monotonicity hypothesis is proposed. The globally Lipschitz property together with other useful properties of the well-known Gerstewitz nonlinear scalarization function are fully exploited for proving. Moreover, our approach does not impose any convexity condition on the considered model. The oriented distance function is also employed for studying Hölder continuity.
A constrained proper orthogonal decomposition model for upscaling permeability

Reservoir modeling and simulation are vital components of modern reservoir management processes. Despite the advances in computing power and the advent of smart technologies, the implementation of model‐based operational/control strategies has been limited by the inherent complexity of reservoir models. Thus, reduce order models that not only reduce the cost of the implementation but also provide geological consistent prediction are essential. This article introduces reduced‐order models based on the proper orthogonal decomposition (POD) coupled with linear interpolation for upscaling. First, using POD‐based models, low rank approximate (LRA) are obtained by projecting the high dimensional permeability dataset to a low dimensional subspace spanned by its trajectories to decorrelate the dataset. Next, the LRA is integrated into the interpolation algorithm to generate upscaled values. This technique is highly scalable since low‐rank approximations are achieved by the variation in the number of modes used for reconstruction. To test the validity and reliability of the model, we show its application to the practical dataset from SPE10 benchmark case2. From statistics of the error analysis, the classical POD algorithm seems to be more preferred for LRA; however, since non‐negativity of the permeability data set is a priority, the constrained POD (non‐negative POD) algorithm described in this article is more appropriate. Finally, we compared the POD‐based models to a traditional industry‐standard upscaling technique (e.g., arithmetic mean) to highlight our model benefits/performance. Results show that the POD‐based models, particularly the non‐negative POD model, produce considerably less error than the arithmetic mean model in the upscaling process.
An interior-point method for minimizing the maximum eigenvalue of a linear combination of matrices

We consider the problem of finding $${\lambda ^{opt}}: = \mathop {\inf }\limits_{x \in {R^m}} \{ {\lambda _{\max }}({A^{(0)}} + \sum\limits_{i = 1}^m {{x_i}{A^{(i)}}} )\} $$ (1) and an optimal solution xopt if it exists. Here, the A (i) are given symmetric matrices in IR n×n for 0 ≤ i ≤ m, and αmax(A) is the largest eigenvalue of a matrix A. Problem (1) can be rewritten as a convex difFerentiable problem with a positive definite constraint. Positive definiteness can easily be verified numerically (via Cholesky decomposition). Moreover, the cone of positive definite matrices A is characterized by the domain of the smooth convex barrier function $$ - \log \;{\det _ + }(A) $$ .
Multifunctional behavior of ZnO supported Bi1−xDyxFeO3 nanorods

We have shown that it is possible to realize multifunctional Bi1−xDyxFeO3 (BDFO) nanorods by coating BDFO film on ZnO nanorods. These BDFO coated ZnO (BDFO/ZnO) nanorods are obtained by depositing BDFO on vertical ZnO nanorods grown on Si substrate by using pulsed laser deposition technique. The BDFO/ZnO rods exhibit coexistence of ferroelectric and ferromagnetic properties with significant coupling between two order parameters at room temperature. Moreover, the piezoresponse of these nanorods is found to be even superior to pure ZnO nanorods. The unique multifunctional behavior of these nanorods at room temperature could find different applications in nanodevices like sensors, power generators, etc. with ease and flexibility in operation.
Switching Heavy Chain Constant Domains Denatures the Paratope 3D Architecture of Influenza Monoclonal Antibodies

Several human monoclonal Abs for treating Influenza have been evaluated in clinical trials with limited success despite demonstrating superiority in preclinical animal models including mice. To conduct efficacy studies in mice, human monoclonal Abs are genetically engineered to contain mouse heavy chain constant domain to facilitate the engagement of Fc-receptors on mouse immune effector cells. Although studies have consistently reported discrepancies in Ab effectiveness following genetic engineering, the structural and mechanistic basis for these inconsistencies remain uncharacterized. Here, we use homology modeling to predict variable region (VR) analogous monoclonal Abs possessing human IgG1, mouse IgG1, and mouse IgG2a heavy chain constant domains. We then examine predicted 3D structures for variations in the spatial location and orientation of corresponding paratope amino acid residues. By structurally aligning crystal structures of Fabs in complex with hemagglutinin (HA), we show that corresponding paratope amino acid residues for VR-analogous human IgG1, mouse IgG1, and mouse IgG2a monoclonal Abs interact differentially with HA suggesting that their epitopes might not be identical. To demonstrate that variations in the paratope 3D fine architecture have implications for Ab specificity and effectiveness, we genetically engineered VR-analogous human IgG1, human IgG4, mouse IgG1, and mouse IgG2a monoclonal Abs and explored their specificity and effectiveness in protecting MDCK cells from infection by pandemic H1N1 and H3N2 Influenza viruses. We found that VR-analogous monoclonal Abs placed on mouse heavy chain constant domains were more efficacious at protecting MDCK cells from Influenza virus infection relative to those on human heavy chain constant domains. Interestingly, mouse but not human heavy chain constant domains increased target breadth in some monoclonal Abs. These data suggest that heavy chain constant domain sequences play a role in shaping Ab repertoires that go beyond class or sub-class differences in immune effector recruitment. This represents a facet of Ab biology that can potentially be exploited to improve the scope and utilization of current therapeutic or prophylactic candidates for influenza.
How Useful is Learning in Mitigating Mismatch Between Digital Twins and Physical Systems?

In the control of complex systems, we observe two diametrical trends: model-based control derived from digital twins, and model-free control through AI. There are also attempts to bridge the gap between the two by incorporating learning-based AI algorithms into digital twins to mitigate mismatches between the digital twin model and the physical system. One of the most straightforward approaches to this is direct input adaptation. In this paper, we ask whether it is useful to employ a generic learning algorithm in such a setting, and our conclusion is “not very”. We denote an algorithm to be more useful than another algorithm based on three aspects: 1) it requires fewer data samples to reach a desired minimal performance, 2) it achieves better performance for a reasonable number of data samples, and 3) it accumulates less regret. In our evaluation, we randomly sample problems from an industrially relevant geometry assurance context and measure the aforementioned performance indicators of 16 different algorithms. Our conclusion is that blackbox optimization algorithms, designed to leverage specific properties of the problem, generally perform better than generic learning algorithms, once again finding that “there is no free lunch”. Note to Practitioners—Digital twins have the potential to improve productivity and quality in complex systems such as manufacturing systems. Their impact on system performance hinges on the accuracy of their digital models around the system’s operating points. Difficult to measure phenomena, such as wear and tear of equipment, however, may cause a mismatch between the digital twin model and the physical system. In this paper, we formalize this problem and compare 16 potential solution strategies under practical aspects. We argue that readily available off-the-shelf blackbox optimization algorithms may prove more useful for this problem, than more recent learning-based approaches. Specifically, gradient-based algorithms will perform best in systems with high-dimensional, continuous, and non-linear performance functions–even in the presence of white measurement noise.
GROSC: uma proposta de segmentação de caracteres impressos 
orientada a regiões em níveis de cinza

Optical Character Recognition systems (OCR) refer generically to technologies applied to recognize characters from an image file that contains text. It allows, for example, that a scanned sheet of printed text could be converted into an editable text file. These systems have been widespread over the past years, with several commercial versions, including the ones embedded within scanner devices. One of the steps that define the success or failure of this type of system is the correct segmentation of text lines and characters that constitute it. Recently, it has gained importance the correct segmentation of words in the textto assist possible post-processing steps to correct deviations of recognition. This paper presents two different methods for segmentation of texts. The first method, called “Segmentation of Lines and Words based Teager energy operator” (SLP-TEO), based on the Teager energy operator (TEO), is used in the segmentation of text lines and words. The TEO is applied to the signal abstracted from the linear projection (horizontal or vertical) generated by the binary image of the text. A unique feature of this method is that it can be applied to printed texts or manuscripts, without prior arrangements. Moreover, the same algorithm is used to segmentation of text lines and segmentation of words, no matter if they are printed or handwritten. The adopteddatabase for this project (IAM-Database), widely used in OCR researches, has, for all printed text, handwritten transcripts that were also targeted using SLP-TEO method. The second method, called “gray-Region Oriented Segmentation of Characters” (gROSC) is applied to grayscale word images for the purpose of character segmentation. This method is based on region oriented methodswhere connected pixels that are visited and labeled. A unique feature of the method is that it should be applied to grayscale images of the segmented words. Moreover, using the Otsu threshold and knowing the gray levels of the image in advance, the method determines the maximum variation between shades of gray that allows or not to visit the neighboring pixel, adding it to the target region of interest. In the adopted database, there are three basic types of characters problems to solve: overlapping characters, connected characters, and font design. The gROSCmethod
THE THIRD POSITION—BEYOND ARTIFICIAL AND AUTOPOIETIC REDUCTION

The meaning of cybernetics of sociocultural systems is discussed in terms of two rival traditions. Both are reductionistic with respect to cognitive interaction: One seeks a reduction to (A) the Artificial Gestalt of symbolic representations; the other to (B) the Biological Gestalt of cellular reproduction. Cultural Gestalt‐switches and other irreducible properties, such as intersubjectivity and capacity for consciousness, call for a third position in terms of (D) Dialogue and Dualities, which comprises and transcends the complementarity of (A) and (B). Conditions are indicated for shifts between modes conforming to both, and for the prevalence and resolution of model monopoly. Examples are given from small group studies and socioeconomic planning in Norway.