Miracle-dz/UniFAR-FTUs huggingface dataset:
Complicaciones de la hernioplastia inguinal laparoscópica

Las hernias que se ubican en la pared abdominal son consideradas una patología de alta prevalencia en la población mundial, ya que se estima que el 55 % de las personas se ve afectada en algún momento de su vida por esta enfermedad. Además, se someten anualmente más de 20 millones de pacientes a nivel mundial a reparación de hernia inguinal, como gran parte de estos pacientes presentan comorbilidades, es importante conocer las complicaciones que conlleva este procedimiento. Objetivo. Identificar estrategias para reducir la incidencia de complicaciones y mejorar los resultados a largo plazo de la hernioplastia inguinal laparoscópica. Metodología. Se realizó una revisión sistemática, de estudios observacionales, donde las principales bases de datos utilizados fueron PubMed y Google Scholar cuyos descriptores DeCS-MeSH se presentan con el siguiente algoritmo de búsqueda “Complications” AND “laparoscopic” AND “inguinal” AND “hernioplasty”. Se incluyeron los trabajos relacionados con el tema de investigación, publicados en español o inglés en periodos más recientes o publicados dentro de los últimos 5 años. Conclusión. La incidencia de hernias inguinales aumenta con la edad, especialmente entre la quinta y la séptima década de la vida por lo cual conlleva a complicaciones que van desde morbilidad de la herida, recurrencia de la hernia, dolor crónico y problemas relacionados con la malla. A pesar de las complicaciones que presenta la reparación de hernia inguinal vía laparoscópica es una de las técnicas más usada actualmente y que brinda una recuperación más rápida.
Magnetohydrodynamic modelling of supersonic jets and colliding blast waves for laboratory astrophysics investigation

The thesis is related to laboratory astrophysics, and investigates with this technique, the launching mechanism for young stellar object jets and the interaction of two supernovae remnant in the Sedov-Taylor regime. Recent experiments performed at Imperial College on the pulsed-power magpie facility have successfully shown the formation of magnetically driven radiatively cooled plasmas jets formed from radial wire arrays, which are relevant to studying the launching mechanisms of astrophysical jets [A. Ciardi, et al. Phys. Plasmas 14, p056501 (2007)]. The experiments have been now extended to study episodic mass ejection ( 25 ns [F. A. Suzuki-Vidal, et al. 49th Annual Meeting of the Division of Plasma Physics, UO4.00007 (2007)]) and the interaction of jets and magnetic bubbles with an ambient gas. The dynamics of the interaction is investigated through three-dimensional resistive magneto-hydrodynamic simulations using the code gorgon [A. Ciardi, et al. Phys. Plasmas 14, p056501 (2007) – J.P. Chittenden, et al. Plasma Phys. Control. Fusion 46 B457 (2004)]. In particular ablation of the cathode is investigated numerically to explain the periodicity and subsequent formation of multiple bubbles. Comparison with experiments is offered to validate the results. The complex structure of the magnetic field is investigated, the conservation of the magnetic flux is explained and the consequent confinement offered to the central jet. Furthermore the interaction of the plasma outflows with an ambient gas is investigated. The formation of shocks in the ambient gas, as well as the formation of three-dimensional Mach stems is analyzed. In addition, recent experiment at Imperial College performed by the QOLS group, by laser-heating a medium of atomic clusters [R. A. Smith, et al. 2007 Plasma Phys. Control. Fusion 49 B117-B124 (2007)], shows the
Remarques sur les problèmes de réflexion oblique

Nous obtenons un resultat d'unicite pour le probleme de reflexion oblique dans le cas ou la direction de reflexion est seulement une fonction lipschitzienne sur le bord et dans le cas d'ouverts bornes reguliers. Nous decrivons ensuite une methode permettant de prouver la convergence de procedes d'approximation qui s'applique, en particulier, a ce type de problemes de reflexion
Ghost artifact reduction in EPI (Echo Planar Imaging) with Sensitivity Encoding (SENSE)

Introduction Nyquist ghosting artifacts degrade the quality of Echo Planar Imaging (EPI) due to the alternating offset of the k-space lines. Acquisition of separate reference image [1], modification of EPI sequences [2] or algorithmic correction schemes [3] have been applied to correct the artifacts. These artifacts do not appear in the most imaging sequence except the EPI because each line of k-space is traversed in the same direction and all k-space lines have nearly the same offset [3]. In order to reconstruct the images with a same traverse direction in k-space, we were motivated to use only even echoes or odd echoes of k-space in reconstruction, respectively. This type of approach reduces the field of view (FOV) to one-half in phase encoding direction, therefore is immune to Nyquist ghost artifacts inherently. Consequently, issues aliasing artifact associated with reduced-FOV approach can be effectively reduced by Sensitivity Encoding (SENSE) [4].
Inertial accelerated algorithms for solving a split feasibility problem

Inspired by the inertial proximal algorithms for finding a zero of a maximal monotone operator, in this paper, we propose two inertial accelerated algorithms to solve the split feasibility problem. One is an inertial relaxed-CQ algorithm constructed by applying inertial technique to a relaxed-CQ algorithm, the other is a modified inertial relaxed-CQ algorithm which combines the KM method with the inertial relaxed-CQ algorithm. We prove their asymptotical convergence under some suitable conditions. Numerical results are reported to show the effectiveness of the proposed algorithms.
Edukasi Komposisi Desain dan Konten Iklan Bagi UMKM Lumintu

Kondisi yang sudah terkendali pasca pandemi Covid-19 menjadi pemacu UMKM untuk berbenah diri agar bisa bertahan dan berkembang. Masing – masing melakukan berbagai upaya untuk mempromosikan produk secara lebih masif. Hal ini sebagaimana juga dilakukan oleh UMKM Lumintu yang berdiri sejak tahun 2020 dan terus berkembang secara positif. Meskipun bisa bertahan dan menjual produk, faktanya UMKM Lumintu masih kesulitan mempromosikan usaha secara online. Saat ini strategi promosi yang dilakukan masih konvensional yakni menawarkan produk dari mulut ke mulut dan ditawarkan dalam lingkup yang masih terbatas. Di sisi lain, semakin pesatnya penggunaan internet dan media sosial mendorong UMKM harus meningkatkan kemampuan dalam mengiklankan produknya secara lebih komunikatif dan menarik. Berdasarkan permasalahan tersebut diperlukan pelatihan edukasi komposisi desain dan konten iklan bagi UMKM Lumintu sebagai langkah awal untuk membuat iklan secara mandiri yang memanfaatkan aset hasil sendiri melalui pemanfaatan aplikasi Canva dan perangkat smartphone yang telah dimiliki. Hasil kegiatan ini yaitu desain media iklan sederhana yang bisa dirancang dimanapun, kapanpun, dan oleh siapapun karena mudah diterapkan dan hasilnya bisa diunggah menjadi konten story whatsapp, feed instagram, hingga status facebook. Kegiatan ini bisa dilanjutkan untuk lebih memaksimalkan peran aktif pelaku UMKM dalam mempromosikan produk melalui iklan yang bisa dirancang sendiri (doi t yourself).
Polarimetric Radar Metrics Related to Tornado Life Cycles and Intensity in Supercell Storms

AbstractPolarimetric radar signatures have been related to the typical evolution of supercell storms, including through tornado life cycles. Now that polarimetric radar observations are available for a large sample of supercell storms, time series of new radar metrics can be derived. These metrics can be compared with phases of known tornado life cycles in an effort to develop new methods of anticipating tornadoes and to increase understanding of storm-scale structural and microphysical changes through supercell and tornado life cycles. In this paper, radar metrics including measures of differential reflectivity ZDR columns, ZDR arcs, polarimetrically inferred hailfall regions, and mean value of copolar correlation coefficient ρhv in the echo appendage are compared to the tornado life cycle and to storm-maximum tornado intensity in a sample of 35 tornadic supercells. It is shown that these radar metrics may change repeatedly and thus can be used to distinguish tornadic and nontornadic periods in single su.
Error estimation for surrogate models with noisy small-sized training sets

Simulation-driven shape optimization often uses surrogate models, i.e. approximate models fitted through a dataset of simulation results for a limited number of designs. The shape optimization is then performed over this surrogate model. For efficiency, modern approaches often construct the datasets adaptively, adding simulation points one by one where they are most likely to discover the optimum design [3]. The uncertainty estimation of the surrogate model is essential to guide the choice of new sample points: underestimation of the uncertainty leads to sampling in suboptimal regions, missing the true optimum. Gaussian process regression naturally provides uncertainty estimations [4] and Stochastic Radial Basis Functions (SRBF) surrogate models estimate the uncertainty based on the spread of RBF fits with different kernels [5]. In the context of SRBF, this paper discusses two issues with uncertainty estimation. The first is that most existing techniques rely on knowledge about the global behaviour of the data, such as spatial correlations. However, the number of datapoints can be too small to reconstruct this global information from the data. We argue that in this situation, user-provided estimation of the function behaviour is a better choice (section 3). The second issue is that the dataset may contain noise, i.e. random errors without spatial correlation. Surrogate models can filter out this noise, but it introduces two separate uncertainties: the optimum amount of noise filtering is unknown, and for a small dataset (even with perfect noise filtering) the local mean of the data may not correspond to the true simulation response. In section 4 we introduce estimators for both uncertainties.
Simulation of Severe Dust Events over Egypt Using Tuned Dust Schemes in Weather Research Forecast (WRF-Chem)

Weather Research and Forecasting model coupled with chemistry (WRF-Chem) was used to simulate selected severe dust storm events over Egypt in terms of the aerosol optical depth (AOD). Two severe events, which occurred on 22 January 2004 and 31 March 2013, are examined. The analysis includes three dust emission schemes: Goddard Chemistry Aerosol Radiation and Transport (GOCART), GOCART with Air Force Weather Agency (GOCART-AFWA), and GOCART with University of Cologne (GOCART-UOC). Each scheme was tested by adjusting coefficients related to the dust flux. The AOD and Single scattering albedo (SSA) from the model were compared against the same parameters derived from the Moderate-resolution Imaging Spectroradiometer (MODIS). The grid spacing for both of the data sets is 10 km. Results from the March 2013 event were also compared against point measurements from an Aerosol Robotic Network (AERONET) station in Cairo. Using WRF with built-in coefficients, all schemes resulted in underestimating AOD. After tuning the coefficients, it was possible to bring the model results closer to the observations from satellite and AERONET. Each severe event required a different tuning, depending on the origin and composition of the dust storm. Sensitivity analysis for each case is performed to identify the scheme that best simulates the given events based on spatial error distribution. A novel comparison of eigenvalue structures for images of both for AOD and SSA from model and MODIS was used. After tuning, the adjusted coefficient GOCART scheme is found to simulate AOD best across the country in both events. However, the results for the 2004 event from GOCART-UOC were closest to MODIS AOD over Cairo (within 5% bias). On the other hand, GOCART-AFWA produced nearest estimate of AOD for the 2013 event when compared to AERONET measurements (within 7% bias). For both of the events, SSA from GOCART and GOCART-AFWA schemes were found to be comparable to MODIS measurements with accuracy that was close to 98%. The accuracy from GOCART-UOC was around 93%.
Real-valued, time-periodic weak solutions for a semilinear wave equation with periodic $\delta$-potential

We consider the semilinear wave equation $V(x) u_{tt} -u_{xx} = \pm \vert u\vert^{p-1} u$ with $p\in (1,\frac{5}{3})$ and a periodically extended delta potential $V(x)=\alpha+\beta\delta_{\rm per}(x)$. Both the "+" and the "-" case can be treated. We prove the existence of time-periodic real-valued solutions that are localized in the space direction. Our result builds upon a Fourier-Floquet-Bloch expansion of the solution and a detailed analysis of the spectrum of the wave operator. In fact, it turns out that by a careful choice of the parameters $\alpha,\beta$ and the spatial and temporal periods, the spectrum of the wave operator $V(x)\partial_t^2-\partial_x^2$ (considered on suitable space of time-periodic functions) is bounded away from $0$. This allows to find weak solutions as critical points of a functional on a suitable Hilbert space and to apply tools for indefinite variational problems.
Deep Curious Feature Selection: A Recurrent, Intrinsic-Reward Reinforcement Learning Approach to Feature Selection

Feature selection (FS) is an important step in the process of building machine learning-based models. The goal of the FS step is to find a small subset of features that will provide good prediction results by removing noisy, irrelevant, or repetitive features. Commonly used wrapper methods use a machine learning model as a black box and its performance as the goal function for evaluating different features' subsets and selecting the best one. To avoid examining all possible subsets (an NP-hard problem), search algorithms are used to find the subsets to be examined, in a heuristic way. As exhaustive search methods are computationally complicated, most methods use simple and greedy search methods that yield only locally optimal results and are not sensitive to possible features interactions, which means that a feature may be chosen at the expense of two others that are more informative together. We analyze the problem of searching the features subset space with reference to two dimensions, namely, memory of past selected features subset and future selected features. We propose a new wrapper FS method based on the deep artificial curiosity framework, which implements intrinsic reward reinforcement learning, with long short-term memory unit. This novel algorithm integrates these two elements of memory and future step. We show that our method, called the deep curious FS algorithm, deals with feature interactions, and provides a feature subset which improves the accuracy of learning models on artificial and real datasets.
Energy stable numerical method for the TDGL equation with the reticular free energy in hydrogel

Here we focus on the numerical simulation of the phase separation about macromolecule microsphere composite (MMC) hydrogel. The model is based on time-dependent Ginzburg-Landau (TDGL) equation with the reticular free energy. An unconditionally energy stable diﬀerence scheme is proposed based on the convex splitting of the corresponding energy functional. In the numerical experiments, we observe that simulating the whole process of the phase separation requires a considerably long time. We also notice that the total free energy changes signiﬁcantly in initial stage and varies slightly in the following time. Based on these properties, we apply the adaptive time stepping strategy to improve the computational eﬃciency. It is found that the application of time step adaptivity can not only resolve the dynamical changes of the solution accurately but also signiﬁcantly save CPU time for the long time simulation.
POLICY OF ESTABLISHING THE DATE OF THE PAYMENT OF RURAL AND URBAN LAND AND BUILDING TAXES IN INDRAGIRI HILIR DISTRICT

Payment of Land and Building Tax in the Rural and Urban Sector (PBB-P2) that exceeds the maturity limit will be subject to administrative sanctions in the form of interest of 2% per month calculated from a maximum period of 24 months from the time the tax becomes due. This could potentially lead to impartiality towards PBB P2 taxpayers who are late in paying taxes. This research is a type of normative legal research, which focuses on positive legal norms. This normative legal research method examines the law from an internal perspective with the object of research being legal norms. The purpose of the study was to analyze the setting of the due date for PBB-P2 payments and to analyze the legal concept of determining the due date for PBB-P2 payments. The results of the study explain that PBB-P2 through regional and central regulations does not provide administrative certainty in the payment and deposit of PBB-P2 and does not adjust the meaning of the tax year and can result in the obligation to pay PBB-P2 through the tax year. This will result in a lack of effectiveness in collecting PBB-P2 in the context of increasing local revenue. And it is necessary to harmonize existing regulations with the improvement of existing provisions and administration. This is important considering that local tax regulations and the tax itself are very important and of course adapted to the psychological, sociological and economic development of the community. Efforts to socialize the tax regulations made and the important thing is to urge taxpayers to fulfill their tax obligations clearly, correctly, on time and in the right amount.
Content Retrieval dengan Fasttext Word Embedding pada Learning Management System Olimpiade

Learning Management System (LMS) merupakan jenis media pembelajaran daring yang digunakan siswa di berbagai tingkat. Penggunaannya pada keperluan kompetisi, secara khusus olimpiade, memiliki karakteristik tersendiri dibanding LMS untuk keperluan pembelajaran sehari-hari. Salah satunya adalah kemampuan sistem mengelola bank soal dan menyajikan kategori yang relevan kepada user. User pada LMS Olimpiade tersegmentasi sesuai bidang ilmu yang ingin ditekuni. Meski begitu, tiap bidang memiliki topik pembelajaran yang beragam jenisnya dan bahkan cenderung berkembang seiring waktu. Manajemen bank soal dengan anotasi topik di awal memerlukan tenaga ahli dan memakan waktu. Sedangkan fitur pencarian tanpa menggunakan informasi metadata tersebut tentu juga sulit dilakukan. Fitur pencarian semantik menjadi penting pada sistem seperti ini. Dibutuhkan skema pencarian berdasarkan konten yang mampu mengembalikan soal-soal yang relevan dengan topik di masing-masing bidang. Fitur pencarian dibangun menggunakan skema information retrieval yakni vector space model. Hasil eksperimen dan evaluasi responden menunjukkan representasi word embedding dengan performa pencarian terbaik adalah FastText word embedding. Efisiensi ukuran model dilakukan dengan menggunakan compressed version. Representasi ini selain dapat mengakomodasi hasil pencarian sesuai konteks kueri juga dapat mengatasi permasalahan out-of-vocabulary.
Attendance system based on facial recognition using multi-task convolutional neural network

Some businesses today do not keep track of their employees' attendance. Some of them are still using outdated techniques such as log-based manual inspections. These outdated methods of data collection require excessive paperwork, take time due to laborious recording procedures, and result in inaccurate data collection due to human error and inadequate assessment. The goal of this study is to create an attendance system that can make it simple and accurate for businesses to track their employees' attendance. The aim of this project is to create a system that will make it simple and automatic to record attendance using facial recognition. The result shows that the system is operational and possess a accurate and highly benefits the students and the faculty members.
Multi-model Fuzzy Modal Control of SISO Nonlinear Plant

Abstract The article presents the synthesis of a multi-model modal control of single input – single output nonlinear plant, based on Takagi-Sugeno fuzzy controller. For that purpose, the nonlinear static characteristic of the plant is presented by two linear parts. These two linear structures are described in state space. The feedback vectors and the coefficients ki of the modal controllers are calculated. An integral component in the control law is added.
Adapting a commercial spectral domain optical coherence tomography system for time-locked displacement and physiological measurements

Measuring vibration within the cochlear partition is important to understand sound transduction and nonlinear amplification within the cochlea. Here we describe the customization of a commercially available Spectral Domain Optical Coherence Tomography system, the Thorlabs Telesto, for displacement measurements in the cochlea using a technique called Spectral Domain Phase Microscopy (SDPM). The paper describes the SDOCT data analysis pipeline composed of background subtraction, interpolation, and spectral shaping of the raw photodetector data, followed by the implementation of SDPM for vibration measurements. It also details the software and hardware modification necessary to couple the Telesto to a Tucker-Davis Technologies data acquisition system to obtain time-locked vibration and electrophysiological measurements from the gerbil cochlea. The use of this commercial imaging system for auditory displacement measurements brings this powerful measurement tool within reach of many auditory researchers.Measuring vibration within the cochlear partition is important to understand sound transduction and nonlinear amplification within the cochlea. Here we describe the customization of a commercially available Spectral Domain Optical Coherence Tomography system, the Thorlabs Telesto, for displacement measurements in the cochlea using a technique called Spectral Domain Phase Microscopy (SDPM). The paper describes the SDOCT data analysis pipeline composed of background subtraction, interpolation, and spectral shaping of the raw photodetector data, followed by the implementation of SDPM for vibration measurements. It also details the software and hardware modification necessary to couple the Telesto to a Tucker-Davis Technologies data acquisition system to obtain time-locked vibration and electrophysiological measurements from the gerbil cochlea. The use of this commercial imaging system for auditory displacement measurements brings this powerful measurement tool within reach of many auditory researchers.
Strong convergence of the forward–backward splitting method with multiple parameters in Hilbert spaces

Abstract Many problems arising from machine learning, signal & image recovery, and compressed sensing can be casted into a monotone inclusion problem for finding a zero of the sum of two monotone operators. The forward–backward splitting algorithm is one of the most powerful and successful methods for solving such a problem. However, this algorithm has only weak convergence in the infinite dimensional settings. In this paper, we propose a new modification of the FBA so that it possesses a norm convergent property. Moreover, we establish two strong convergence theorems of the proposed algorithms under more general conditions.