Miracle-dz/UniFAR-FTUs huggingface dataset:
PELAYANAN KESEHATAN PRAKONSEPSI UNTUK MENCEGAH RESIKO STUNTING : A SCOOPING REVIEW

Pada intervensi spesifik program pencegahan stunting diantaranya melalui pemberian layanan kesehatan reproduksi pada prakonsepsi. Penelitian ini bertujuan untuk mengidentifikasi gambaran pelaksanaan pelayanan kesehatan reproduksi pada prakonsepsi dan faktor determinannya terkait dengan pencegahan resiko anak stunting. Penelitian ini dilakukan dengan metode scoping review pada artikel jurnal yang telah dipublikasi pada periode tahun 2017 sampai dengan 2021 pada media PubMed dan Google Cendekia. Kata kunci yang digunakan adalah Pelayanan Kesehatan Prakonsepsi, Pencegahan Stunting, Bidan, Kader, dan PKK . Hasil pencarian ditemukan 642 artikel dan didapatkan 12 artikel terpilih. Berdasarkan analisa ditemukan bahwa Preconception Care (PCC) belum banyak diperkenalkan kepada masyarakat serta belum ada pelatihan pelayanan PCC bagi Bidan maupun Kader. Ada korelasi antara PCC yang konsisten dengan penurunan konsumsi alkohol dan kehamilan yang sehat. Faktor yang mempengaruhi melakukan PCC diantaranya usia, pendidikan, status kesehatan, pekerjaan dan informasi dari pemberi layanan. Media konseling pada PCC dapat berupa booklet atau video interaktif, dengan pemberi layanan meliputi Bidan sebagai pemeriksa kesehatan dan pemberi intervensi, Kader Posyandu sebagai fasilitator dan Pengawas Minum Obat, serta Kader PKK dalam penjaringan prakonsepsi. Untuk meningkatkan kunjungan kesehatan reproduksi pada prakonsepsi dapat dilakukan dengan melakukan sosialisasi dari pemberi layanan tentang pemeriksaan kesehatan prakonsepsi, penyusunan standar operasional prosedur, pelatihan bagi pemberi layanan, dan pembuatan media konseling standar. Selain itu juga diperlukan kerja sama antara Bidan dengan Kader dan PKK untuk mengajak masyarakat aktif melakukan pemeriksaan kesehatan prakonsepsi terutama pada calon pengantin.
Voltage Regulation in Second-Order Dc-Dc Converters Via the Inverse Optimal Control Design with Proportional-Integral Action

This article addresses the problem regarding power regulation in classical DC-DC second-order converters by means of a nonlinear control technique based on inverse optimal control theory. There are few papers that describe inverse optimal control for DC-DC converters in the literature. Therefore, this study constitutes a contribution to the state of the art on nonlinear control techniques for DC-DC converters. In this vein, the main objective of this research was to implement inverse optimal control theory with integral action to the typical DC-DC conversion topologies for power regulation, regardless of the load variations and the application. The converter topologies analyzed were: (i) Buck; (ii) Boost; (iii) Buck-Boost; and (iv) Non-Inverting Buck-Boost. A dynamical model was proposed as a function of the state variable error, which helped to demonstrate that the inverse optimal control law with proportional-integral action implemented in the different converters ensures stability in each closed-loop operation via Lyapunov’s theorem. Numerical validations were carried out by means of simulations in the PSIM software, comparing the established control law, the passivity-based PI control law, and an open-loop control. As a conclusion, it was possible to determine that the proposed model is easier to implement and has a better dynamical behavior than the PI-PBC, ensuring asymptotic stability from the closed-loop control design.
Isometry groups of proper metric spaces

Given a locally compact Polish space X, a necessary and sufficient condition for a group G of homeomorphisms of X to be the full isometry group of (X,d) for some proper metric d on X is given. It is shown that every locally compact Polish group G acts freely on GxY as the full isometry group of GxY with respect to a certain proper metric on GxY, where Y is an arbitrary locally compact Polish space with (card(G),card(Y)) different from (1,2). Locally compact Polish groups which act effectively and almost transitively on complete metric spaces as full isometry groups are characterized. Locally compact Polish non-Abelian groups on which every left invariant metric is automatically right invariant are characterized and fully classified. It is demonstrated that for every locally compact Polish space X having more than two points the set of proper metrics d such that Iso(X,d) = {id} is dense in the space of all proper metrics on X.
Light Interception and Radiation Use Efficiency of Three Cassava Genotypes with Different Plant Types and Seasonal Variations

The yield potential of cassava might be increased by enhancing light interception and the ability to convert energy into biomass and yield, which is described as radiation use efficiency (RUE). The objective of this study was to determine light interception, extinction coefficient (k), and RUE of three cassava genotypes (Kasetsart 50 (KU50), Rayong 11 (RY11), and CMR38-125-77) under seasonal variations. The field experiments were conducted in a randomized complete block design with four replications, using two planting dates for 2 years at Khon Kaen, Thailand. Data were recorded for weather conditions, light interception, leaf area index (LAI), and biomass. Solar radiation interception, RUE, and k were calculated. Light interception of the crop planted in May sharply increased in the early growth stage, whereas the crop planted in November slowly increased and could maintain higher light interception from the mid–late growth stages. Light interception and LAI had a moderate to high coefficient of determination (R2 = 0.61–0.89) for three cassava genotypes and all planting dates. The k values ranged from 0.59 to 0.94, varying by genotypes and planting dates, indicating that the leaf orientation of the three cassava genotypes was horizontally oriented. The relationship between biomass accumulation and cumulative solar radiation produced a high value of R2 (0.86–0.99). The RUE for biomass (RUEbi) varied by genotype and planting date, ranging from 0.66 g MJ−1 to 0.97 g MJ−1. However, the RUE for storage root dry weight (RUEsr) ranged from 0.29 g MJ−1 to 0.66 g MJ−1. The RUEbi and RUEsr in each genotype on each planting date were significantly different. The highest RUEbi and RUEsr were found at 4–6 and 7–9 MAP for almost all genotypes and planting dates, except for the crop planted in November 2015, when both RY11 and CMR38-125-77 had the highest RUEbi at 10–12 MAP. RY11 had a lower LAI compared to other genotypes, which contributed to lower light disruption and lower RUEbi and RUEsr. KU50 and CMR38-125-77 could maintain canopy light interception during canopy development and storage root accumulation stages and had high RUEbi and RUEsr, resulting in high biomass and crop yield.
Arithmetic Moduli and Lifting of Enriques Surfaces

We construct the moduli space of Enriques surfaces in positive characteristic and eventually over the integers, and determine its local and global structure. As an application, we show lifting of Enriques surfaces to characteristic zero. The key observation is that the canonical double cover of an Enriques surface is birational to the complete intersection of three quadrics in IP^5, even in characteristic 2.
Classification of rotations on the torus $\mathbb{T}^2$

We consider rotations on the torus $\mathbb{T}^2$, and we classify them with respect to the complexity functions. In dimension one, a minimal rotation can be coded by a sturmian word. A sturmian word has complexity $n+1$ by the Morse-Hedlund theorem. Here we make a generalization in dimension two.
Struct2Hair: A hair shape descriptor for hairstyle modeling

In recent years, it becomes possible to extract hair information for hair reconstruction from multiple cameras or monocular camera. Using a single image as the input avoids the high cost setups and complex calibration compared to multiviewed reconstruction. Taking advantage of an extendible hairstyle database, this paper introduced Struct2Hair, a novel single‐viewed hair modelling approach by extracting hair shape descriptor (HSD). The HSD is defined as the fundamental structure‐aware feature, which is a combination of critical shapes in a hairstyle. A complete dataset of critical hair shapes is constructed from a known database of three‐dimensional (3D) hair models. We first analyze the input two‐dimensional (2D) image to extract the orientation information and 2D hair sketch automatically. The extracted information is then used to retrieve the corresponding critical shapes with optimization to build the robust HSD. Finally, the HSD constructs a weighted 3D hair orientation field to guide full‐head hair model generation. Our method can preserve local geometric features of hair and retain the whole shape of the hairstyle globally owing to the HSD, which will benefit further hair editing and stylization.
Adaptive Learning Models for Getting Insights into Multimodal Lifelog Data

Regular exercise and scientific eating can support weight control and benefit everyone’s health, especially athletes. In recent years, although much research has been conducted in this field, only small groups of people were studied, and a few models revealed links between weight and speed attributes (e.g., activities, wellbeing, habits) to extract tips to assist people in controlling their weight and running speed. In this research, we propose an approach that uses pattern mining and correlation discovery techniques to discover the most optimal attributes over time to forecast the weight and speed of an athlete for a sports event. Furthermore, we propose Adaptive Learning Models, which can learn from personal and public data to forecast a person’s weight or speed in various age groups, such as young adults, middle-aged adults, and female or male members. Based on the above analysis, different approaches to building prediction models of athletes’ weight or running speed are being examined based on the primary data. Our suggested approach yields encouraging results when tested on public and private data sets.
THE DIMENSION OF A SUBCATEGORY OF MODULES

Let $R$ be a commutative noetherian local ring. As an analog of the notion of the dimension of a triangulated category defined by Rouquier, the notion of the dimension of a subcategory of finitely generated $R$-modules is introduced in this paper. We found evidence that certain categories over nice singularities have small dimensions. When $R$ is Cohen–Macaulay, under a mild assumption it is proved that finiteness of the dimension of the full subcategory consisting of maximal Cohen–Macaulay modules which are locally free on the punctured spectrum is equivalent to saying that $R$ is an isolated singularity. As an application, the celebrated theorem of Auslander, Huneke, Leuschke, and Wiegand is not only recovered but also improved. The dimensions of stable categories of maximal Cohen–Macaulay modules as triangulated categories are also investigated in the case where $R$ is Gorenstein, and special cases of the recent results of Aihara and Takahashi, and Oppermann and Št́ovíček are recovered and improved. Our key technique involves a careful study of annihilators and supports of $\mathsf{Tor}$, $\mathsf{Ext}$, and $\underline{\mathsf{Hom}}$ between two subcategories.
Altruistic defense traits in structured populations

We propose a model for the frequency of an altruistic defense trait. More precisely, we consider LotkaVolterra-type models involving a host/prey population consisting of two types and a parasite/predator population where one type of host individuals (modeling carriers of a defense trait) is more effective in defending against the parasite but has a weak reproductive disadvantage. Under certain assumptions we prove that the relative frequency of these altruistic individuals in the total host population converges to spatially structured Wright-Fisher diffusions with frequency-dependent migration rates. For the manydemes limit (mean-field approximation) hereof, we show that the defense trait goes to fixation/extinction if and only if the selective disadvantage is smaller/larger than an explicit function of the ecological model parameters.
Simulation of Laser-Heating and Energetic Plasma Plume Expansion in Pulsed Laser Deposition of Y3Fe5O12

In the present study, numerically iterative models are employed to study two processes involved in the pulsed laser deposition of an Y3Fe5O12 target. The 1D conduction heat model is used to evaluate the temperature of the target irradiated by a nano-second pulse laser, taking into account the plasma shielding effect. Further, the gas dynamics model is employed to simulate the kinetic of plasma plume expansion. The results may be important in obtaining high-quality Y3Fe5O12 thin films.
On the complexity of calculation of differentials and gradients

We obtain bounds for the complexity of circuit realisation of the system of differentials of orders from one to k of an arbitrary elementary function in terms of the circuit complexity of this function. Similar bounds are obtained for the complexities of realisation of the Jacobian and Hessian matrices. We point out some applications to deduction of bounds for complexities of polynomials in several variables, linear transformations, and quadratic forms.
Survey of Cybersecurity Governance, Threats, and Countermeasures for the Power Grid

The convergence of Information Technologies and Operational Technology systems in industrial networks presents many challenges related to availability, integrity, and confidentiality. In this paper, we evaluate the various cybersecurity risks in industrial control systems and how they may affect these areas of concern, with a particular focus on energy-sector Operational Technology systems. There are multiple threats and countermeasures that Operational Technology and Information Technology systems share. Since Information Technology cybersecurity is a relatively mature field, this paper emphasizes on threats with particular applicability to Operational Technology and their respective countermeasures. We identify regulations, standards, frameworks and typical system architectures associated with this domain. We review relevant challenges, threats, and countermeasures, as well as critical differences in priorities between Information and Operational Technology cybersecurity efforts and implications. These results are then examined against the recommended National Institute of Standards and Technology framework for gap analysis to provide a complete approach to energy sector cybersecurity. We provide analysis of countermeasure implementation to align with the continuous functions recommended for a sound cybersecurity framework.
Arithmetic Analogues of Derivations

w x In 1 the author introduced an arithmetic analogue of derivations, called p-derivations; this concept was used to prove a series of arithmetic w x analogues of results about algebraic differential equations 1, 2, 3 . Although the usefulness of this concept is probably well illustrated by these papers, the question arises of how ‘‘natural’’ these p-derivation operators are and what other choices one has in defining arithmetic analogues of ‘‘usual’’ derivations. The present note is an attempt to answer this question: we will introduce an a priori quite general notion of jet operator on a ring and prove that any such operator on a local domain of characteristic zero is ‘‘equivalent’’ to one of the following: a difference operator, a Ž derivation operator, a p-difference operator cf. the definition in the . w x following text , or a p-derivation operator in the sense of 1 . The first three kinds of operators are always trivial on the rational integers; so one w x is left with the fourth kind, i.e., with the p-derivations of 1 , as the ‘‘only’’ possibility, within our paradigm, for an arithmetic analogue of usual derivations. Throughout this paper rings are always assumed to be commutative, with unit element, and all ring homomorphisms preserve units.
Imbalanced Sample Fault Diagnosis of Rolling Bearing Using Deep Condition Multidomain Generative Adversarial Network

Rolling bearing fault diagnosis plays a crucial role in ensuring the safety and reliability of rotary machine, and some methods that employ deep-learning technology are grounded on the assumption that there are large-scale failure data. In reality, it is difficult to acquire more failure rolling bearing data under the different failure rates. In this article, a novel condition multidomain generative adversarial network (CMDGAN) is introduced for imbalanced sample fault diagnosis. This framework effectively captures the sample distribution information by a fusion of two-domain information when there are limited raw samples. Also, the introduced self-adaptive sample condition is no prior knowledge needed and contributes to the different state of synthetic data. Finally, an improved fault diagnostic model with the self-attention module implements the fusion of local fault feature and global periodic fault feature. Multiple sets of experiments on the Case Western Reserve University (CWRU) and Dalian University of Technology Vibration Lab (DUT-VL) datasets reveal the efficiency of our proposed approach, and the generating samples improve the fault diagnosis performance, which outperforms the contrasting methods.
Noncommutative Geometry: A Functorial Approach

The book covers basics of noncommutative geometry and its applications in topology, algebraic geometry and number theory. A brief survey of main parts of noncommutative geometry with historical remarks, bibliography and a list of exercises is attached. Our notes are intended for the graduate students and faculty with interests in noncommutative geometry; they can be read by non-experts in the field.
Metallic-like to nonmetallic transitions in a variety of heavily oxygen deficient ferroelectrics

The coupling between ferroelectric distortions and electron transport is an important factor in understanding ferroelectric/noncentrosymmetric materials with metallic conductivities and ferroelectric-based thermoelectrics. Here, multiple d0 ferroelectrics with a variety of crystal structures are doped via oxygen deficiency, resulting in metallic-like conduction in the paraelectric state. It is found that most of the studied systems show a metallic-like to nonmetallic transition near the paraelectric-ferroelectric transition. The metallic-like to nonmetallic transition temperature can be shifted using mechanisms that shift the paraelectric-ferroelectric transition temperature. It was found that the metallic-like to nonmetallic transition temperature could be shifted from 373 K to 273 K by varying (Ba1−xSrx)TiO3−δ from x = 0 to x = 0.3 and x = 1. The most probable mechanism for ferroelectric-electron transport coupling was determined to be Anderson localization associated with polarization with short-range .
Identification of metabolic fingerprints in severe obstructive sleep apnea using gas chromatography–Mass spectrometry

Objective: Obstructive sleep apnea (OSA) is considered a major sleep-related breathing problem with an increasing prevalence rate. Retrospective studies have revealed the risk of various comorbidities associated with increased severity of OSA. This study aims to identify novel metabolic biomarkers associated with severe OSA. Methods: In total, 50 cases of OSA patients (49.74 ± 11.87 years) and 30 controls (39.20 ± 3.29 years) were included in the study. According to the polysomnography reports and questionnaire-based assessment, only patients with an apnea–hypopnea index (AHI >30 events/hour) exceeding the threshold representing severe OSA patients were considered for metabolite analysis. Plasma metabolites were analyzed using gas chromatography–mass spectrometry (GC-MS). Results: A total of 92 metabolites were identified in the OSA group compared with the control group after metabolic profiling. Metabolites and their correlated metabolic pathways were significantly altered in OSA patients with respect to controls. The fold-change analysis revealed markers of chronic kidney disease, cardiovascular risk, and oxidative stress-like indoxyl sulfate, 5-hydroxytryptamine, and 5-aminolevulenic acid, respectively, which were significantly upregulated in OSA patients. Conclusion: Identifying these metabolic signatures paves the way to monitor comorbid disease progression due to OSA. Results of this study suggest that blood plasma-based biomarkers may have the potential for disease management.
Gold Nanoparticles-Mediated Photothermal Therapy of Pancreas Using GATE: A New Simulation Platform

Simple Summary Laser irradiation of noble metal nanoparticles has recently been investigated to achieve a potential clinically relevant photothermal effect. This work presents the first study of gold nanorods (GNRs)-assisted therapy of a pancreas tumor using the Monte Carlo-based code developed with Geant4 Application for Emission Tomography (GATE). Having the possibility of setting the optical and thermal properties of nanoparticles, GATE platform allows for the modeling of the GNRs-mediated hyperthermia therapy as well as heat diffusion in tissue. The code was benchmarked to validate the heat distribution between the simulation and the experiment. Abstract This work presents the first investigation of gold nanorods (GNRs)-based photothermal therapy of the pancreas tumor using the Monte Carlo-based code implemented with Geant4 Application for Emission Tomography (GATE). The model of a human pancreas was obtained by segmenting an abdominal computed tomography (CT) scan, and its physical and chemical properties, were obtained from experimental and theoretical data. In GATE, GNRs-mediated hyperthermal therapy, simple heat diffusion as well as interstitial laser ablation were then modeled in the pancreas tumor by defining the optical parameters of this tissue when it is loaded with GNRs. Two different experimental setups on ex vivo pancreas tissue and GNRs-embedded water were devised to benchmark the developed Monte Carlo-based model for the hyperthermia in the pancreas alone and with GNRs, respectively. The influence of GNRs on heat distribution and temperature increase within the pancreas tumor was compared for two different power values (1.2 W and 2.1 W) when the tumor was exposed to 808 nm laser irradiation and with two different laser applicator diameters. Benchmark tests demonstrated the possibility of the accurate simulating of NPs-assisted thermal therapy and reproducing the experimental data with GATE software. Then, the output of the simulated GNR-mediated hyperthermia emphasized the importance of the precise evaluation of all of the parameters for optimizing the preplanning of cancer thermal therapy. Simulation results on temperature distribution in the pancreas tumor showed that the temperature enhancement caused by raising the power was increased with time in both the tumor with and without GNRs, but it was higher for the GNR-load tumor compared to tumor alone.
Estimation of chirp rates of music-adapted prolate spheroidal atoms using reassignment

We introduce a modified Matching Pursuit algorithm for estimating frequency and frequency slope of FM-modulated music signals. The use of Matching Pursuit with constant frequency atoms provides coarse estimates which could be improved with chirped atoms, more suited in principle to this kind of signals. Application of the reassignment method is suggested by its good localization properties for chirps. We start considering a family of atoms generated by modulation and scaling of a prolate spheroidal wave function. These functions are concentrated in frequency on intervals of a semitone centered at the frequencies of the well-tempered scale. At each stage of the pursuit, we search the atom most correlated with the signal. We then consider the spectral peaks at each frame of the spectrogram and calculate a modified frequency and frequency slope using the derivatives of the reassignment operators; this is then used to estimate the parameters of a cubic interpolation polynomial that models local pitch fluctuations. We apply the method both to synthetic and music signals.