Miracle-dz/UniFAR-FTUs huggingface dataset:
El monzón del suroeste de Norteamérica (TRAVASON/ SWAMP).

A scientific experiment to investigate the atmospheric circulation, the mesoscale convective systems and the precipitation associated with the monsoon overnorthwestern mexico and southwestern united states was carried out during the northern summer of 1990. a number of institutions and universities participated in the experiment. special observations were made over the mexican states of Baja California, Baja California Sur, Sonora, Sinaloa, Durango, Coahuila, Chihuahua and in the United States, Arizona. a wide variety of metereological observations were made, including special pilot ballon and radiosonde soundings, research aircraft flights (including use of airborne doppler radar), special surface observations, as well as more routine satellite, surface and upper-air observations over the region. The observations have been processed and compiled bye the National Severa StormsLaboratory (NSSL) and the Center for Scientific Study and Higher Education of Ensenada (CICESE), in a data bank with the ooperation of Nationa Water Commission (CNA) and the Sonora Institute of Technology (ITSON). Different atmospheroc phenomena are being investigated, including the horizontal transport of water vapor and the studies to date using the 1990 data identify the ‘Sierra Madre Occidental’, particularly important to the formation from the tropical Americas converge. The Mexican watersheds from the Pacific and the Gulf of California show higher precipitation over the Sierra madre, as compared with the watersheds from Chihuahua and the Gulf o Mexico, suggesting the Pacific ocean as the main source of moisture for monsoon circulation over northwestern Mexico.
On the use and evaluation of prospective scan methods for health‐related surveillance

Summary. We review some prospective scan‐based methods that are used in health‐related applications to detect increased rates of mortality or morbidity and to detect bioterrorism or active clusters of disease. We relate these methods to the use of the moving average chart in industrial applications. Issues that are related to the performance evaluation of spatiotemporal scan‐based methods are discussed. In particular we clarify the definition of a recurrence interval and demonstrate that this measure does not reflect some important aspects of the statistical performance of scan‐based, and other, surveillance methods. Some research needs in this area are given.
N-GPETS: Neural Attention Graph-Based Pretrained Statistical Model for Extractive Text Summarization

The extractive summarization approach involves selecting the source document's salient sentences to build a summary. One of the most important aspects of extractive summarization is learning and modelling cross-sentence associations. Inspired by the popularity of Transformer-based Bidirectional Encoder Representations (BERT) pretrained linguistic model and graph attention network (GAT) having a sophisticated network that captures intersentence associations, this research work proposes a novel neural model N-GPETS by combining heterogeneous graph attention network with BERT model along with statistical approach using TF-IDF values for extractive summarization task. Apart from sentence nodes, N-GPETS also works with different semantic word nodes of varying granularity levels that serve as a link between sentences, improving intersentence interaction. Furthermore, proposed N-GPETS becomes more improved and feature-rich by integrating graph layer with BERT encoder at graph initialization step rather than employing other neural network encoders such as CNN or LSTM. To the best of our knowledge, this work is the first attempt to combine the BERT encoder and TF-IDF values of the entire document with a heterogeneous attention graph structure for the extractive summarization task. The empirical outcomes on benchmark news data sets CNN/DM show that the proposed model N-GPETS gets favorable results in comparison with other heterogeneous graph structures employing the BERT model and graph structures without the BERT model.
The Microstructure of Cumulus Cloud. Part I. General Features of the Droplet Spectrum

Abstract From the examination of a large number of droplet samples in cumulus clouds it is found that many droplet-size distributions have neither positive skewness nor a single mode. Bimodal distributions increase in frequency with height above cloud base and with decreasing stability in the cloud environment, and it is suggested that they are produced by mixing between the cloud and its environment. The relative uniformity observed in the shape of the spectrum at a constant level across the cloud, and the fact that bimodal distributions are not confined to the cloud edges, lead to the belief that entrainment inward from the cloud edges is not dominant; rather, it is the mixing at the growing cloud top as it builds which determines the shape of the droplet spectrum.
Direct Absorption Spectroscopy of CO2 Using a Coherent White Light Continuum

A white light continuum was generated by focusing the terawatt 800 nm femtosecond laser pulse in Kr gas. The white light spectrum spanned in a broad wavelength range from 300 to more than 2200 nm. The white light continuum was used for the first time to perform direct absorption spectroscopy of CO2 at around 2000 nm in a laboratory absorption cell. The present system can be used for measuring the CO2 concentrations with an accuracy of 1–2 ppm (ca. 0.5%) in atmosphere for around 5.5 km propagation lengths through the air.
Convergence properties of relaxation versus the surface-Newton generalized-conjugate residual algorithm for self-consistent electromechanical analysis of 3-D micro-electro-mechanical structures

Electrostatic sensors and microactuators are typically controlled by applied voltages which create electrostatic forces that deform the structure. Therefore, accurately analyzing the performance of these sensors and actuators requires self-consistent electromechanical analysis. However, self-consistent electromechanical analysis is a difficult computational problem because the discretization grid used must track the electrostatically deformed boundaries of the structure. Self-consistent electromechanical analysis of complicated three-dimensional structures can be performed by combining a fast multipole-accelerated scheme for electrostatic analysis with a standard finite-element method for mechanical system analysis. There are two approaches for combining these analyses, one using a straight-forward relaxation scheme, and a second based on a surface-Newton method combined with a matrix-free generalized conjugate residual based solver (SNGCR). In this paper, the convergence properties of these two methods are examined. In particular, we show that relaxation will converge if the applied voltage is small enough, or if Young's modulus is large enough, but will diverge otherwise. We also show by example that although the SNGCR algorithm is guaranteed to converge only given a sufficiently close initial guess, it converges much more frequently than relaxation. <<ETX>>
Analysis prcedures for ROSAT XRT/PSPC observations of extended objects and the diffuse background

Proper reduction of ROSAT observations of extended sources or the diffuse background requires techniques that are quite different from the standard point-source analysis. We describe in detail an appropriate set of procedures for this purpose for the X-ray Telescope (XRT), Position Sensitive Proportional Counter (PSPC). We define a standard set of pulse-height bands recommended for analyzing extended structure and describe the use of detector efficiency maps for proper flat-fielding of images. Sources of noncosmic background contamination and their modeling and subtraction are discussed and demonstrated. IDL routines for implementing these data reduction procedures are being made available to the community through the ROSAT IDL library maintained at Goddard Space Flight Center (GSFC).
Catalytic mechanism and properties of pyridoxal 5'-phosphate independent racemases: how enzymes alter mismatched acidity and basicity.

Covering: up to March 2019Amino acid racemases and epimerases are key enzymes that invert the configuration of common amino acids and supply many corresponding d-isomers in living organisms. Some d-amino acids are inherently bioactive, whereas others are building blocks for important biomolecules, for example lipid II, the bacterial cell wall precursor. Peptides containing them have enhanced proteolytic stability and can act as important recognition elements in mammalian systems. Selective inhibition of certain amino acid racemases (e.g. glutamate racemase) is believed to offer a promising target for new antibacterial drugs effective against pathogens resistant to current antibiotics. Many amino acid racemases employ imine formation with pyridoxal phosphate (PLP) as a cofactor to accelerate the abstraction of the alpha proton. However, the group reviewed herein achieves racemization of free amino acids without the use of cofactors or metals, and uses a thiol/thiolate pair for deprotonation and reprotonation. All bacteria and higher plants contain such enzymes, for example diaminopimelate epimerase, which is required for lysine biosynthesis in these organisms. This process cannot be accomplished without an enzyme catalyst as the acidities of a thiol and the substrate α-hydrogen are inherently mismatched by at least 10 orders of magnitude. This review describes the structural and mechanistic studies on PLP-independent racemases and the evolving view of key enzymatic machinery that accomplishes these remarkable transformations.
Passive FM locking in InGaAsP semiconductor lasers

Passive FM locking of the longitudinal modes in MOVPE (metalorganic vapor-phase epitaxy)-grown InGaAsP semiconductor lasers due to four-wave mixing is discussed. Due to the locking, the lasing field closely resembles a single-frequency modulated wave with a modulation frequency equal to the cavity mode spacing of about 160 GHz, when the lasers are well above threshold. The existence of this FM wave is demonstrated by comparing the fundamental and the second-harmonic spectrum. A simplified analysis of the FM operation which explains the experimental data rather well is presented. >
Enhanced Nuclear Accumulation of Doxorubicin Delivered by pH-Triggered Polydopamine-Shelled Mesoporous Silica for Chemo-Photothermal Therapy

Adequate delivery of therapeutic agents to their intended molecular targets is crucial in tumor therapy. Versatile drug carriers need to overcome the challenges coming from the systemic circulation, membrane barriers, and endo-lysosomal degradation. Herein, hyaluronic acid-conjugated polydopamine (HA-PDA)-shelled mesoporous silica nanoparticles encapsulated with doxorubicin (MSNs-DOX) were successfully fabricated for targeted tumor therapy. Compared with reported studies focusing on the pH-sensitive release in tumors, we especially revealed the significant role of lysosomal release in DOX nuclear accumulation. After active targeting and CD44-mediated endocytosis in tumor cells, the PDA layer of the nanoparticles would be peeled off to trigger drug release owing to MSNs gatekeeper in acidic lysosomes. Subsequently, DOX molecules passively diffused into nuclei. The intracellular DOX transportation was evidenced by DOX accumulation in nuclei, lysosomal location of nanoparticles, and lysosome acidification inhibition test. After discharging of the cargoes from nanoparticles, PDA shells from residual nanoparticles were able to produce localized hyperthermia under NIR irradiation entrapped in lysosomes, inducing synergistic chemo-photothermal effect. Under NIR treatment, HA-PDA@MSNs-DOX presented a prominent tumor inhibition rate without obvious side effects. This study indicated the potent nuclear delivery and synergetic chemo-photothermal therapy achieved by HA-PDA-shelled MSNs.
Clinical utility of RNA sequencing to resolve unusual GNE myopathy with a novel promoter deletion

Introduction: UDP N‐acetylglucosamine2‐epimerase/N‐acetylmannosamine‐kinase (GNE) gene mutations can cause mostly autosomal‐recessive myopathy with juvenile‐onset known as hereditary inclusion‐body myopathy (HIBM). Methods: We describe a family of a patient showing an unusual HIBM with both vacuolar myopathy and myositis without quadriceps‐sparing, hindering diagnosis. We show how genetic testing with functional assays, clinical transcriptome sequencing (RNA‐seq) in particular, helped facilitate both the diagnosis and a better understanding of the genotype‐phenotype relationship. Results: We identified a novel 7.08 kb pathogenic deletion upstream of GNE using array comparative genomic hybridization (aCGH) and a common Val727Met variant. Using RNA‐seq, we found only monoallelic (Val727Met‐allele) expression, leading to ~50% GNE reduction in muscle. Importantly, α‐dystroglycan is hypoglycosylated in the patient muscle, suggesting HIBM could be a “dystroglycanopathy. ” Conclusions: Our study shows the importance of considering aCGH for GNE‐myopathies, and the potential of RNA‐seq for faster, definitive molecular diagnosis of unusual myopathies. Muscle Nerve, 2019
Automatic transcription of simple polyphonic music

A novel computational system has been constructed which is capable of transcribing piano performances of four‐voice Bach chorales written in the style of 18th century counterpoint. The system is based on the ‘‘blackboard’’ architecture, which combines top‐down and bottom‐up processing with a representation that is natural for the stated musical domain. Knowledge from auditory physiology, physical sound production, and musical practice has been successfully integrated in the current implementation, enabling the system to infer the presence of octaves, thereby overcoming a common pitfall of many traditional bottom‐up transcription systems. The architecture and incorporated knowledge will be presented, along with an appraisal of the system’s performance and comparisons with other systems in the literature. [Work supported by NSF. ]
Energy conservation for reflectivity and transmissivity at a very rough surface

The transmissivity and reflectivity obtained from Huygen’s principle and the geometrical optics approach by integration over angular variables over the hemispheres are shown to violate the conservation of energy. Energy conservation is observed when the integration limits are modified. The modified transmissivity and reflectivity have the additional advantage that they can be evaluated with asymptotic methods to bring out explicitly the rough surface effects. This has direct application to passive remote sensing of a rough surface where the emissivity is to be calculated.
Superconductivity at 215 K in lanthanum hydride at high pressures

We synthesized lanthanum hydride (LaHx) by laser heating of lanthanum in hydrogen atmosphere at pressure P = 170 GPa. The sample shows a superconducting step at 209 K and 170 GPa and temperature dependence of resistance. By releasing the pressure to 150 GPa, the superconducting transition temperature Tc increases to 215 K - the record Tc. This finding supports a way of achieving Tc higher than the one in H3S (203 K) in hydrides with sodalite-like structures, first proposed for CaH6 (Tc=245 K) and later for yttrium and lanthanum hydrides where higher, room temperature superconductivity is expected.
Poster Abstract: OrderlessFL: A CRDT-Enabled Permissioned Blockchain for Federated Learning

Industries produce a large amount of data that can improve Machine Learning models. However, due to privacy issues, the data cannot be shared. Several Federated Learning (FL) systems have been introduced as private alternatives without considering Byzantine actors.Also,thesesystemsareaffectedbythegradientstalenessprob-lem.Severalblockchain-basedFLsystemsareintroducedtoaddress Byzantineactors,whichrelyon Proof-of-Work-based(PoW) protocols and suffer from their limitations. We introduce OrderlessFL, a safe permissioned blockchain-based FL system using flCRDT, a CRDT for concurrent ML training and mitigating gradient staleness.
Chromatic adaptation and color constancy: A possible dichotomy

Differences between chromatic adaptation and color constancy are discussed, in order to call into question the commonly held view that chromatic adaptation is the mechanism of color constancy. Whereas chromatic adaptation requires many seconds of time and occurs for simple visual scenes, color constancy asserts itself immediately and is most powerful in complex visual scenes. Furthermore, models of chromatic adaptation are not so illuminant invariant as other models of color vision. Therefore, a new operational foundation for color constancy is proposed, and existing non-adaptation models of color constancy are enumerated for future tests.
Исследование возможности применения свёрточных нейронных сетей для обработки фотограмметрических изображений

Close-range photogrammetry is widely used to measure the surface shape of various objects and its deformations. Usually, a stereo pair of images of the object under study, obtained from different angles by means of several digital video cameras, is used for this purpose. The surface shape is measured by triangulating a set of corresponding two-dimensional points from these images using a predetermined location of cameras relative to each other. Various algorithms are used to find these points. Several photogrammetric methods use cross-correlation for this purpose. This paper discusses the possibility of replacing the correlation algorithm with neural networks to determine ГрафиКон 2022: 32-я Международная конференция по компьютерной графике и машинному зрению, 19-22 сентября 2022 г. , Рязанский государственный радиотехнический университет им. В. Ф. Уткина, Рязань, Россия EMAIL: vpinchukov@list.ru (В.В. Пинчуков); poroykovay@gmail.com (А.Ю. Поройков); shmatko.97@bk.ru (Е.В. Шматко) ORCID: 0000-0002-5816-0424 (В.В. Пинчуков); 0000-0002-9284-1397 (А.Ю. Поройков); 0000-0003-3565-9502 (Е.В. Шматко) ©� 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). GraphiCon 2022 Научная визуализация и визуальная аналитика 19–22 сентября 2022, Рязань, Россия 341 offsets in the images. They allow to increase the calculation speed and the spatial resolution of the measurement results. To verify the possibility of their application, a series of experimental images of surfaces with different deformations were obtained. Computational experiments were performed to process these images using selected neural networks and a classical cross-correlation algorithm. The limitations on the use of the compared algorithms were determined and their error in restoring the three-dimensional shape of the surface was estimated. The physical simulation to verify the selected neural networks for image processing for the task of photogrammetry showed their performance and efficiency.
School-Based Intervention for Academic Achievement: Targeting Cognitive, Motivational and Affective Factors T

 Abstract — Outcome in any learning process should target three goals – propelling the underachiever’s engagement in the learning process, enhancing the drive to achieve, and modifying attitudes and beliefs in his/her capabilities. An intervention study with a three-pronged approach incorporating self-regulatory training targeting three categories of strategies – cognitive, metacognitive and motivational – was designed adopting the before and after control-experimental group design. The evaluation of the training process was based on pre- and post-intervention measures obtained through three indices of measurement – academic scores based on grades on school examinations and comprehension tests, affective variables scores and level of strategy use obtained through responses on scales and questionnaires, and content analysis of subjective responses to open-ended probes. The evaluation relied on three sources – student, teacher and parent. The t-test results for the experimental and control groups on the pre- and post-intervention measurements indicate a significant increase on comprehension tasks for the experimental group. Though statistically significant difference was not found on the school examination scores for the experimental group, there was considerable decline in performance for the control group. Analysis of covariance (ANCOVA) was applied on the scores obtained on affective variables, namely, self-esteem, personal achievement goals, personal ego goals, personal task goals, and locus of control. The experimental group showed increase in personal achievement goals and personal ego goals as compared to the control group. Responses given by the experimental group to the open-ended probes on causal attributions indicated a considerable shift from external to internal causes when moving from the pre- to post-intervention stage. ANCOVA results revealed significantly higher use of learning strategies inclusive of mental learning strategies, behavioral learning strategies, self-regulatory strategies, and an improvement in study orientation encompassing study habits and study attitudes among the experimental group students. Parents and teachers reported significant progressive transformation towards constructive engagement with study material and self-imposed regulation. The implications of this study are three-fold: firstly, strategies training (cognitive, metacognitive and motivational) should be embedded into daily classroom routine; secondly, scaffolding by teachers through activities based on curriculum will eventually enable students to rely more on their own judgements of effective strategy use; thirdly, enhanced confidence will radiate to the affective aspects with enduring effects on other domains of life as well. The cyclic nature of the interaction between utilizing one’s resources, managing effort and regulating emotions forms the foundation for academic achievement.
Statics and dynamics in giant magnetostrictive Tb/sub x/Fe/sub 1-x/-Fe/sub 0.6/Co/sub 0.4/ multilayers for MEMS

In the present paper, giant magnetostrictive (GMS) thin films have been investigated for future microelectromechanical systems (MEMS) purposes. To this end, flexural and torsional motions have been studied in low-field anisotropic GMS single-domain state (SDS) exchange-coupled TbFe-FeCo multilayers (ECML). The magnetoelastic (ME) coefficient b/sup /spl gamma/,2/ depends strongly on the ECML structures, compositions, and sputtering deposition parameters. GMS multilayers with a high b/sup /spl gamma/,2/ (18 MPa for TbFe/sub 2//Fe/sub 0.6/Co/sub 0.4/ compared to 11 MPa for TbFe/sub 2//Fe) were obtained with or without an in-plane easy axis with a controlled direction, and without any annealing postprocess. Dynamical excitations of the actuators have been investigated under various conditions. An enhancement up to a factor 5 of the oscillations compared to the TbFe-Fe multilayers is observed with the possibility to tune the flexural/torsional dynamical behavior of these cantilevers. The corresponding very large dynamical ME susceptibility of these improved uniaxial ECML gives the possibility to control GMS MEMS with further reduction of the excitation field down to a few oersteds.