Miracle-dz/UniFAR-FTUs huggingface dataset:
Theory of networks for learning

Many neural networks are constructed to learn an input-output mapping from examples. This problem is related to classical approximation techniques including regularization theory. Regularization is equivalent to a class of threelayer networks which we call regularization networks or Hyper Basis Functions. The strong theoretical foundation of regularization networks provides us with a better understanding of why they work and how to best choose a specific network and parameters for a given problem. Classical regularization theory can be extended in order to improve the quality of learning performed by Hyper Basis Functions. For example the centers of the basis functions and the norm weights can be optimized. Many Radial Basis Functions often used for function interpolation are provably Hyper Basis Functions. 1.
On the Perfect Gravity-Balance of a Spatial N-DOF Manipulator Based on the Localized Pseudo-Base

This paper offers an exact solution for the perfect gravity-balance of a class of spatial manipulators with no translational joints. The methodology used is based on the concept of conservation of the gravitational and elastic potential energy of the system. The overall gravitational potential energy of a serial-connected, n-link manipulator is identified to be contributed by n subsystems, where each subsystem is kinematically equivalent to one of the primary links of the manipulator, and possesses the accumulated mass of its post-connected links with a fixed mass center located on the subsystem. The gravitational potential energy of such a subsystem can be fully balanced by the elastic potential energy of the spring fitted between the link and its adjacent pseudo-base. Since the rotation axis of the pseudo-base is required to be in the direction of gravity, n serial-connected RSSR modules are constituted along the primary chain of the manipulator to provide a pseudo-base for each of the primary links. With one linear, zero-free-length spring fitted between each of the primary links of the manipulator and its associated pseudo-base, a static equilibrium of the considered mechanism in any configuration can be reached. A numerical example of the model of a six-DOF industrial robot has demonstrated the success of the proposed methodology.Copyright © 2009 by ASME
Determination of the convex hull of radiating or scattering systems: a new, simple and effective approach

This paper presents a novel, effective, simple and computationally inexpensive approach to detect, from electromagnetic or acoustic data at a fixed frequency, the convex hull of a set of radiators (scatterers or sources) whose dimension is comparable with the wavelength. The method, presented here for 2D geometry, is based on a new concept of the point source spectral content of the reduced field. Without any restriction on the shape of the observation domain, the searching algorithm evaluates the convex hull as the intersection of the minimum cones, with vertex on the observation domain, containing the radiators. The numerical analysis proves the effectiveness of the approach in the case of sources and perfectly conducting scatterers and shows its robustness against noise.
Restarted LBFGS Algorithm for Power Amplifier Predistortion

For the linearization of power amplifiers, a digital pre-distorter is proposed to compensate nonlinear distortion in this paper. The pre-distorter is realized by Volterra series, and a restarted limited memory BFGS(LBFGS) algorithm is proposed for training the nonlinear pre-distorter. Training of Volterra series can be switched between gradient descend algorithm and quasi Newton algorithm by setting a switching condition, and LBFGS algorithm can be used for high dimensional iterative matrix of BFGS algorithm. These make the new algorithm much more stable with a fast convergence rate. The pre-distorter is used for OFDM power amplifiers and it high efficiency is proved by simulation results. Moreover, the convergence rate of the proposed algorithm is greatly faster than that of the gradient algorithm.
Search and Learning for Unsupervised Text Generation

With the advances of deep learning techniques, text generation is attracting increasing interest in the artificial intelligence (AI) community, because of its wide applications and because it is an essential component of AI. Traditional text generation systems are trained in a supervised way, requiring massive labeled parallel corpora. In this paper, I will introduce our recent work on search and learning approaches to unsupervised text generation, where a heuristic objective function estimates the quality of a candidate sentence, and discrete search algorithms generate a sentence by maximizing the search objective. A machine learning model further learns from the search results to smooth out noise and improve efficiency. Our approach is important to the industry for building minimal viable products for a new task; it also has high social impacts for saving human annotation labor and for processing low-resource languages.
Digital deblurring based on linear-scale differential analysis

A novel method of sharpness improvement is proposed for digital images. This method is realized via linear multi-scale analysis of source image and sequent synthesis of restored image. The analysis comprises the procedure of computation of intensity gradient values using the special filters providing simultaneous edge detection and noise filtering. Restoration of image sharpness is achieved by simple subtraction of some discrete recovery function from blurred image. Said recovery function is calculated as a sum of several normalized gradient responses found by linear multi-scale analysis using the operation of spatial transposition of those gradient response values relative the points of zero-crossing of first derivatives of gradients. The proposed method provides the restoration of sharpness of edges in digital image without additional operation of spatial noise filtering and a priori knowledge of blur kernel.
Case Report: The first reported case of pulmonary alveolar proteinosis with myasthenia gravis in a 27-year-old patient

Background: Pulmonary alveolar proteinosis is a very rare diffuse lung disease characterized by the accumulation of amorphous and periodic acid Schiff-positive lipoproteinaceous material in the alveolar spaces due to impaired surfactant clearance by alveolar macrophages. Three main types were identified: Autoimmune, secondary and congenital. Pulmonary alveolar proteinosis has been previously reported to be associated with several systemic auto-immune diseases. Accordingly, we present the first case report of pulmonary alveolar proteinosis associated with myasthenia gravis. Case: A 27-year-old female patient, ex-smoker, developed a dyspnea on exertion in 2020. The chest X-ray detected diffuse symmetric alveolar opacities. Pulmonary infection was ruled out, particularly COVID-19 infection. The chest scan revealed the “crazy paving” pattern. The bronchoalveolar lavage showed a rosy liquid with granular acellular eosinophilic material Periodic acid-Schiff positive. According to the lung biopsy results, she was diagnosed with pulmonary alveolar proteinosis. The granulocyte macrophage colony-stimulating factor autoantibodies were negative. Nine months later, she was diagnosed with bulbar seronegative myasthenia gravis, confirmed with the electroneuromyography with repetitive nerve stimulation showing significant amplitude decrement of the trapezius and spinal muscles. She was treated with pyridostigmine, oral corticosteroids and azathioprine. Given the worsening respiratory condition of the patient, a bilateral whole lung lavage was performed with a partial resolution of symptoms. Thus, this previously unreported association was treated successfully with rituximab, including improvement of dyspnea, diplopia and muscle fatigability at six months of follow-up. Conclusions: This case emphasizes on the possible association of auto-immune disease to PAP, which could worsen the disease course, as the specific treatment does not exist yet. Hence, further studies are needed to establish clear-cut guidelines for PAP management, particularly when associated to auto-immune diseases.
Discrete velocity method in the theory of kinetic equations

Abstract A general method of constructing the discrete models for the Boltzmann equation is suggested. This method allows us to get the discrete models which approximate the Boltzmann equation in any bounded domain of the velocity space and preserve the main properties of this equation-the conservation laws and H-theorem. Three different types of discrete models, depending on the kind of the differential collision cross-section, are considered.
Clarifying the Role of ENSO on Easter Island Precipitation Changes: Potential Environmental Implications for the Last Millennium

El Niño Southern Oscillation (ENSO) events yield precipitation deficits and ensuing droughts, often damaging regional forests, in many parts of the world. The relative roles of ENSO, other natural climate changes, and anthropogenic factors on the forest clearing of Easter Island over the last millennium are still debated. Here, we analyze Easter Island precipitation changes using in situ, satellite‐derived and reanalysis products spanning the last 4–7 decades, and 46 monthly 156‐year‐long (1850–2014) simulations derived from 25 CMIP5 and 21 CMIP6 (Coupled Model Intercomparison Project phases 5 and 6) General Circulation Models. Our analysis shows that La Niña events, the cold phases of ENSO, cause precipitation deficits of −0.2 to −0.3 standard deviation (relative to long‐term mean) in all analyzed data types. ENSO‐like events are further examined over the last millennium (850–1981). A new multiproxy reconstruction of the NINO3.4 index based on proxy records from the Past Global Changes 2k database and Random Forest method is produced. Our reconstruction reveals unusual high recurrences of La Niña‐like situations during the fifteenth to seventeenth centuries, which likely induced significant precipitation deficits on the island. These situations are compared to published vegetation reconstructions based on pollen analyses derived from sedimentary cores collected in three island sites. We conclude the environmental consequences of cumulative precipitation deficits over long‐lasting La Niña‐like situations reconstructed here over the fifteenth to seventeenth centuries were likely favoring drought and forest flammability. La Niña events should be better accounted for among the causes of forest clearing on Easter Island.
Preference of Subterranean Termites among Community Timber Species in
 Bogor, Indonesia

Many methods have been explored to increase the palatability of pine ( Pinus merkusii ), the most common wood used for termite baiting. However, because of the undersupply of pine in Indonesia, it is crucial to vary the wood species for termite baiting and look for potential alternatives. Furthermore, various studies have shown that baiting time influences the intensity and pattern of termite attacks. Therefore, the present research aimed to study the preferences of subterranean termites and find the ideal baiting time among community wood species from Bogor, West Java, as a baiting alternative to pine. The woods tested were Acacia mangium (acacia), Falcataria moluccana (sengon), Anthocephalus cadamba (jabon), Maesopsis eminii (manii), Swietenia mahagoni (mahogany), Hevea brasiliensis (rubberwood), and P. merkusii (pine). Field tests were carried out based on the American Society for Testing and Materials D 1758-06 at the Arboretum, Faculty of Forestry and Environment, IPB University, with a baiting time of one to six months. The results led to the identification of four species of termites, namely Microtermes sp. , Macrotermes sp. , Shedorhinotermes sp. , and Capritermes sp. The frequency of termite attacks on the test site reached 93.1%. Rubberwood was the most potential wood bait for subterranean termites, indicated by the highest average weight loss value (65.8%) with a shorter optimal baiting time (up to one month) than that of other tested woods.
Reduced modelling through identification on 2D incompressible laminar flows

This article presents a model reduction of laminar incompressible fluid flows in two-dimensional geometries cases. The modal identification method [Petit, Hachette, and Veyret, A modal identification method to reduce a high order model: application to heat conduction modelling, Int. J. Model. Simulation, 17, 242–250; Girault and Petit, Identification methods in non linear heat conduction, Part I: model reduction; Int. J. Heat Mass Transfer, 2005, 48, 105–118; Balima, Favennec, Girault, and Petit, The modal identification method in non linear heat transfer problems, Proceedings 13 International Heat Transfer Conference, Sydney, Australia, 2006] is used to derive a structure for the reduced models (RMs). These RMs are identified through a minimization algorithm where the cost function gradient is computed with the adjoint method [Balima, Favennec, Girault, and Petit, The modal identification method in non linear heat transfer problems, Proceedings 13 International Heat Transfer Conference, Sydney, Australia, 2006; Favennec, Girault, and Petit, The adjoint method coupled with the modal identification method for non linear model reduction, Inverse Probl. Sci. Eng., 2006, 14, 153–170; Balima, Réduction de modéle non linéaire par identification modale: application en thermique et comparaison avec la méthode POD-Galerkin, PhD thesis, Université de Poitiers, France, 2006]. Two laminar steady fluid flows in a pipe and in a square cavity (lid-driven cavity) are used to illustrate the study. The results show that the identified RMs are able to reproduce with accuracy the behaviour of the considered model.
Material Flow Analysis for Assessing the Sustainability Solid Waste Management Strategy

With increasing income levels and accelerating consumption, municipal solid waste management (MSW) has become important in developing countries. This study intends to use material flow analysis (MFA) to assess the waste management strategy in Bogor-Indonesia. Moreover, this study also determines the extent of the waste flow path and provides suggestions for improvement. Waste volume data is carried out directly for ten days, referring to Indonesian Standards (SNI 3242: 2008 and SNI 19-3964-1994) related to waste management in settlements in Indonesia. Furthermore, the waste generation data were analyzed by applying the MFA Method. Data processing using STAN (Substance Flow Analysis Version 3) software makes Material Flow Analysis (MFA) images. The data shows that the waste generated is 20 kg to 140 kg per day. The existing conditions indicate that the waste is burned or disposed of in municipal landfills. The proposed waste management strategy model reveals 30.66 tons/year of inorganic waste that can be recovered through recycling and about 20.13 tons/year. The strategy that can be done is to establish a waste bank that applies Maggot BSF cultivation to recycle the organic waste produced. Decision-makers need future studies of material flows to be able to plan for changes in waste flows.
Phenomenology of ultrafine particle concentrations and size distribution across urban Europe.

The 2017-2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of <10 nm PNC are needed for full evaluation of the health effects of this size fraction.
Surface Forcing of the Infrared Cooling Profile over the Tibetan Plateau. Part I: Influence of Relative Longwave Radiative Heating at High Altitude.

Abstract The role of the Tibetan Plateau on the behavior of the surface longwave radiation budget is examined, and the behavior of the vertical profile of longwave cooling over the plateau, including its diurnal variation, is quantified. The investigation has been conducted with the aid of datasets obtained during the 1986 Tibetan Plateau Meteorological Experiment (TIPMEX-86). A medium spectral-resolution infrared radiative transfer model using a simple modification for applications in idealized complex (valley) terrain is developed for the study. This study focuses on the clear-sky case where the surface effects are most significant. The TIPMEX-86 data, obtained during the spring-summer transition into the East Asian monsoon season, are used to help validate the surface longwave radiation budget at two sites of varying elevation: Lasa (3650 m) and Naqu (4500 m). Based on the degree to which skin-temperature boundary conditions control the magnitude of infrared cooling, we define the concept of relative l.
Surface guided 3DCRT in deep-inspiration breath-hold for left sided breast cancer radiotherapy: implementation and first clinical experience in Iran

Background The aim of the study is to evaluate the overall accuracy of the surface-guided radiotherapy (SGRT) workflow through a comprehensive commissioning and quality assurance procedures and assess the potential benefits of deep-inspiration breath-hold (DIBH) radiotherapy as a cardiac and lung dose reduction approach for left-sided breast cancer irradiation. Materials and methods Accuracy and reproducibility of the optical surface scanner used for DIBH treatment were evaluated using different phantoms. Patient positioning accuracy and reproducibility of DIBH treatment were evaluated. Twenty patients were studied for treatment plan quality in target dose coverage and healthy organ sparing for the two different treatment techniques. Results Reproducibility tests for the surface scanner showed good stability within 1 mm in all directions. The maximum position variation between applied shifts on the couch and the scanner measured offsets is 1 mm in all directions. The clinical study of 200 fractions showed good agreement between the surface scanner and portal imaging with the isocenter position deviation of less than 3 mm in each lateral, longitudinal, and vertical direction. The standard deviation of the DIBH level showed a value of < 2 mm during all evaluated DIBHs. Compared to the free breathing (FB) technique, DIBH showed significant reduction of 48% for heart mean dose, 43% for heart V25, and 20% for ipsilateral lung V20. Conclusion Surface-guided radiotherapy can be regarded as an accurate tool for patient positioning and monitoring in breast radiotherapy. DIBH treatment are considered to be effective techniques in heart and ipsilateral lung dose reductions for left breast radiotherapy.
Eigenvector selection indices for improving milk yield and persistency in Egyptian buffalo

The genetic gains were estimated for milk production and persistency, derived from random regression models, using eigenvector indices, and they were compared with the traditional selection index. The data set contained 4971 test day milk yield recorded for 691 buffalo cows, daughters of 120 sires and 532 dams. The model included the random effects of direct additive genetic, permanent environment and error, whereas the fixed effects were herd test day, year and season of calving and parity, and as a covariate, it was milk days. The first and the 2nd eigenvalues explained 73.1 and 22.9% of the variation of the random regression coefficients, respectively, suggesting that the use of the first two eigenvectors is sufficient. Genetic responses in total milk yield (TMY) based on the first eigenvector index (Ie1) and that based on the conventional selection (IMY) have close gain of about 171 kg in each index. The second eigenvector index (Ie2) showed an increase in TMY (9.91 kg), and thus an increase in the persistency (0.86 kg). The TMY and persistency are the two economically important traits in dairy production, additional genetic gains in persistency and high genetic gain for TMY could be obtained using the 2nd eigenvector index (I*2).
Towards the polymer nanocomposites based on hairy nanoparticles

Polymer nanocomposites exhibit versatility in their mechanical and structural features predominantly due to the huge surface area provided by nanoparticles. Interaction of the nanoparticles with polymer matrix selectively dictates the applications suitable for a particular polymer nanocomposite system. Novel hybrid polymer-derived materials based on polymer grafted nanoparticles (NPs) can either be mixed with the polymer matrix or self-suspended without matrix polymer. In both cases superior properties are demonstrated compared to the traditional polymer nanocomposites, most notably by 1) incorporation of NPs into polymers without “mixing problems” and 2) a wide range of the transport phenomena (from solids to viscous fluids). Hence, hairy nanoparticle-based nanocomposites are equipped to handle specific and unique challenges in manufacturing and processing methods. It is known that the transport properties can be tuned by altering the molecular design of hairy nanoparticles (i.e., grafted polymer chemistry, NP concentrations, grafting density, and polymer molecular weight) and matrix polymer (e.g., molecular weight). In this article, we review the 1) most common methods of synthesizing hairy nanoparticle, 2) their microscopic dynamics and structural features and 3) some interesting applications of nanocomposite based on hairy nanoparticles. We discuss the effect of various parameters like nanoparticle size, molecular weight of the polymer etc. on the features of nanocomposites and its implications on the properties.
Pseudopotential calculations of electron and hole addition spectra of InAs, InP, and Si quantum dots

The electron and hole addition energies, the quasiparticle gap, and the optical gap of InAs, InP, and Si quantum dots are calculated using microscopic pseudopotential wave functions. The effects of the dielectric mismatch between the quantum dot and the surrounding material are included using a realistic profile for the dielectric constant e(r). We find that the addition energies and the quasiparticle gap depend strongly on the dielectric constant of the environment eout , while the optical gap is rather insensitive to eout . We compare our results with recent tunneling spectroscopy measurements for InAs nanocrystals, finding excellent agreement. Our calculations for the addition energies and the quasiparticle gap of InP and Si nanocrystals serve as predictions for future experiments.