bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rectovaginal Fistula in Crohn's Disease: When and How to Operate?
Authors: Meyer Jeremy , Ris Frédéric , Parkes Miles , Davies Justin 
Published: January 2022

AbstractRectovaginal fistula (RVF) occurring during the course of Crohn's disease (CD) constitutes a therapeutic challenge and is characterized by a high rate of recurrence. To optimize the outcome of CD-related RVF repair, the best conditions for correct healing should be obtained. Remission of CD should be achieved with no active proctitis, the perianal CD activity should be minimized, and local septic complications should be controlled. The objective of surgical repair is to close the fistula tract with minimal recurrence and functional disturbance. Several therapeutic strategies exist and the approach should be tailored to the anatomy of the RVF and the quality of the local supporting tissues. Herein, we review the medical and surgical management of CD-related RVF.
Molecular diversity and nutriment studies of common bean (
Authors: Choudhary Neeraj , Anjali  , Gupta Moni , Shafi Safoora , Jan Sofora , Hamid Mir Asma , Singh Bikram , Rouf Mir Reyazul 
Published: January 2022

The diverse microclimatic belts of the Western Himalayan region of India are considered hot spots for genetic diversity of common bean (Phaseolus vulgaris L.). Western Himalayan beans are known for various agronomically superior/important traits including unique aroma, taste and cooking quality. In the present study, 25 unlinked genomic simple sequence repeat (SSR) markers distributed across the common bean genome were used to assess the genetic/allelic diversity among and within populations belonging to the Jammu and Kashmir regions of the Western Himalayas. These two regions are considered most important hot-spots for common bean diversity in western-Himalayas. The analysis of genotypic data of SSR markers revealed a total of 263 alleles with an average of 10.52 alleles per locus. The genetic diversity analysis revealed higher variability in bean landraces belonging to Jammu region (He = 0.73) as compared to genotypes from Kashmir region (He = 0.647) and some exotic genotypes (0.71). The genotypes were also phenotyped for four important nutritional traits and the analysis of trait data revealed that sugar content was highest in common bean genotypes from Jammu region, while protein, starch and phenol content were highest in exotic common bean genotypes. Therefore, the superiority of common bean germplasm from Jammu region may be due to a higher level of allelic diversity, more private alleles and higher sugar content. The diverse genotypes based on genotypic data and trait performance will prove useful in future breeding programs aimed at enhancing nutritional contents of common bean varieties.
Trade-offs between bycatch and target catches in static versus dynamic fishery closures
Authors: Pons Maite , Watson Jordan T. , Ovando Daniel , Andraka Sandra , Brodie Stephanie , Domingo Andrés , Fitchett Mark , Forselledo Rodrigo , Hall Martin , Hazen Elliott L. , Jannot Jason E. , Herrera Miguel , Jiménez Sebastián , Kaplan David M. , Kerwath Sven , Lopez Jon , McVeigh Jon , Pacheco Lucas , Rendon Liliana , Richerson Kate , Sant’Ana Rodrigo , Sharma Rishi , Smith James A. , Somers Kayleigh , Hilborn Ray 
Published: January 2022

Significance
The incidental catch of threatened species is still one of the main barriers to fisheries sustainability. What would happen if we closed 30% of the ocean to fishing with the goal of reducing bycatch? Analyzing 15 different fisheries around the globe, we found that under static area management, such as classic no-take marine area closures, observed bycatch could be reduced by 16%. However, under dynamic ocean management based on observed bycatch and closing the same total area but fragmented in smaller areas that can move year to year, that reduction can increase up to 57% at minimal or no loss of target catch.
La2Pd2In: superconductivity and lattice properties at ambient and elevated pressures
Authors: Král P , Diviš M , Havela L , Proschek P , Doležal P , Kaštil J , Vondráčková B , Prchal J 
Published: January 2022

Abstract
Lattice and electronic properties of La2Pd2In were studied at ambient and elevated pressures so as to determine features related to a specific atomic coordination without any influence of magnetism. We describe temperature dependences of lattice parameters, heat capacity and electrical resistivity of single-crystalline La2Pd2In (s.g. P4/mbm) in a broad temperature range 0.09–300 K. Together with the anisotropic effect of hydrostatic pressure, showing that the lattice is more compressible in the basal plane, we can conclude that the lattice is affected by degrees of freedom of the La atoms with positions not imposed by symmetry. The lattice anisotropy is smaller than that found for isostructural ferromagnet Ce2Pd2In. The equilibrium bulk modulus B
0 = (48 ± 3) GPa was determined on the basis of individual linear compressibilities. Measurement of electrical resistivity indicated a superconducting state below T = 0.59 K with a low critical field 0.005 T at T = 380 mK. The onset of superconducting state as a bulk property of La2Pd2In was confirmed by measurements of specific heat and AC magnetic susceptibility. Experimental data can be accounted by first-principles electronic-structure calculations based on density-functional theory. The measured Sommerfeld coefficient γ = 10.6 mJ mol−1 K−2, only marginally exceeding the calculated γ = 9.34 mJ mol−1 K−2, indicates only weak electronic correlations.
A deep convolutional neural network for estimating hemodynamic response function with reduction of motion artifacts in fNIRS
Authors: Kim MinWoo , Lee Seonjin , Dan Ippeita , Tak Sungho 
Published: January 2022

Abstract

Objective. Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique for monitoring hemoglobin concentration changes in a non-invasive manner. However, subject movements are often significant sources of artifacts. While several methods have been developed for suppressing this confounding noise, the conventional techniques have limitations on optimal selections of model parameters across participants or brain regions. To address this shortcoming, we aim to propose a method based on a deep convolutional neural network (CNN). Approach. The U-net is employed as a CNN architecture. Specifically, large-scale training and testing data are generated by combining variants of hemodynamic response function (HRF) with experimental measurements of motion noises. The neural network is then trained to reconstruct hemodynamic response coupled to neuronal activity with a reduction of motion artifacts. Main results. Using extensive analysis, we show that the proposed method estimates the task-related HRF more accurately than the existing methods of wavelet decomposition and autoregressive models. Specifically, the mean squared error and variance of HRF estimates, based on the CNN, are the smallest among all methods considered in this study. These results are more prominent when the semi-simulated data contain variants of shapes and amplitudes of HRF. Significance. The proposed CNN method allows for accurately estimating amplitude and shape of HRF with significant reduction of motion artifacts. This method may have a great potential for monitoring HRF changes in real-life settings that involve excessive motion artifacts.
A comparison between diffusion tensor imaging and generalized q-sampling imaging in the age prediction of healthy adults via machine learning approaches
Authors: Guo Yingying , Yang Xi , Yuan Zilong , Qiu Jianfeng , Lu Weizhao 
Published: January 2022

Abstract

Objective. Brain age, which is predicted using neuroimaging data, has become an important biomarker in aging research. This study applied diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) model to predict age respectively, with the purpose of evaluating which diffusion model is more accurate in estimating age and revealing age-related changes in the brain. Approach. Diffusion MRI data of 125 subjects from two sites were collected. Fractional anisotropy (FA) and quantitative anisotropy (QA) from the two diffusion models were calculated and were used as features of machine learning models. Sequential backward elimination algorithm was used for feature selection. Six machine learning approaches including linear regression, ridge regression, support vector regression (SVR) with linear kernel, quadratic kernel and radial basis function (RBF) kernel and feedforward neural network were used to predict age using FA and QA features respectively. Main results. Age predictions using FA features were more accurate than predictions using QA features for all the six machine learning algorithms. Post-hoc analysis revealed that FA was more sensitive to age-related white matter alterations in the brain. In addition, SVR with RBF kernel based on FA features achieved better performances than the competing algorithms with mean absolute error ranging from 7.74 to 10.54, mean square error (MSE) ranging from 87.79 to 150.86, and normalized MSE ranging from 0.05 to 0.14. Significance. FA from DTI model was more suitable than QA from GQI model in age prediction. FA metric was more sensitive to age-related white matter changes in the brain and FA of several brain regions could be used as white matter biomarkers in aging.
SOLPS-ITER analysis of drift effects on plasma profiles in the EAST scrape-off layer
Authors: Wang Fuqiong , Liang Y. , Zha X.J. , Zhong F.C. , Mao S.T. , Duan Y.M. , Hu L.Q. , Wang L. , Liu J.B. , Yan N. , Liu S.C. 
Published: January 2022

Abstract
Drift effects on the plasma profiles of the scrape-off layer (SOL) in the Experimental Advanced Superconducting Tokamak (EAST) have been numerically investigated using the comprehensive 2D edge modeling package, SOLPS-ITER, based on a generic magnetic equilibrium with lower single null configuration. SOL particle diffusivity (D
SOL) has been scanned from high (1.0 m2 s−1) to extremely low (0.02 m2 s−1), to gradually highlight the role of drift-based neoclassical mechanisms in radial particle transport. To address the impact of magnetic field direction on drift-driven transport, plasma profiles, flows and currents in the SOL of EAST plasmas, with the toroidal magnetic field (B
T) direction favorable and unfavorable for H-mode access, i.e. with the ion B × ∇B drift pointing towards and away from the active X-point, are simulated and analyzed. Results demonstrated that drift-driven transport, considered as the key process in the formation of SOL plasma profiles, is dependent on magnetic field direction and thus SOL flows and currents, as well as SOL widths, can obviously be affected by the direction of drifts. With B
T changed from the favorable direction to the unfavorable one, the flattening of the density radial profile as well as the increase in power decay length, in the SOL, can be achieved and can be further enhanced as the weight of turbulent transport (i.e. D
SOL) gets reduced, due to the increased contribution of ion parallel viscosity to the radial ion flow. In particular, with D
SOL ⩽ 0.05 m2 s−1 in the simulations, the dominant role of drift-based neoclassical mechanisms in the radial particle transport will lead to the formation of the so-called edge density-shelf in plasmas with unfavorable B
T. The power scrape-off width in plasmas with unfavorable B
T is very insensitive to the turbulent transport level and can remain relatively high even when D
SOL has been decreased to an extremely low level. Due to the compressing/widening effect of the drift-driven inward/outward radial particle flow, the simulated power scrape-off width exhibits an in-out asymmetry, which is also dependent on magnetic field direction . This work represents a step towards a deeper understanding of the physics mechanisms determining SOL widths in EAST.
Sigma chromatic numbers of the middle graph of some families of graphs
Authors: Manamtam J A , Garciano A D , Tolentino M A C 
Published: January 2022

Abstract
Let G be a nontrivial connected graph and let c : V (G) → ℕ be a vertex coloring of G, where adjacent vertices may have the same color. For a vertex υ of G, the color sum σ(υ) of υ is the sum of the colors of the vertices adjacent to υ. The coloring c is said to be a sigma coloring of G if σ(u) ≠ σ(υ) whenever u and υ are adjacent vertices in G. The minimum number of colors that can be used in a sigma coloring of G is called the sigma chromatic number of G and is denoted by σ(G). In this study, we investigate sigma coloring in relation to a unary graph operation called middle graph. We will show that the sigma chromatic number of the middle graph of any path, cycle, sunlet graph, tadpole graph, ladder graph, or triangular snake graph is 2 except for some small cases. We also determine the sigma chromatic number of the middle graph of stars.
The rainbow vertex antimagic coloring of tree graphs
Authors: Marsidi  , Agustin Ika Hesti , Dafik  , Kurniawati Elsa Yuli , Nisviasari Rosanita 
Published: January 2022

AbstractLetG(V(G),E(G)) be a connected, simple, and finite graph. Letfbe a bijective function of labeling on graphGfrom the edge setE(G) to natural number up to the number of edges ofG. A rainbow vertex antimagic labeling of graphGis a functionfunder the condition all internal vertices of a pathu–υ, Ɐu, υ∈V(G) have different weight (denoted byw(u)), wherew(u) = ∑uu′∈E(G)f(uu′). IfGhas a rainbow vertex antimagic labeling, then G is a rainbow vertex antimagic coloring, where the every vertex is assigned with the colorw(u). Thervac(G) is a notation of rainbow vertex antimagic connection number of graphGwhich means the minimum colors taken over all rainbow vertex antimagic coloring induced by rainbow vertex antimagic labeling of graphG. The results of this research are the exact value of the rainbow vertex antimagic connection number of star (Sn), double star (DSn), and broom graph (Brn, m).
Decision-making using fuzzy TOPSIS for selecting beginner UMKM that receive business funding
Authors: Negari N L , Riski A , Pradjaningsih A , Kamsyakawuni A 
Published: January 2022

Abstract“Usaha Kecil Mikro dan Menengah”(UMKM) is a productive business unit of individuals or business entities in each economic sector. Currently, many UMKMs face difficulty in developing their business due to a lack of working capital. Therefore, the government provides business funding for the UMKM through“Dinas Koperasi dan UMKM”(Diskopum). Diskopum has various business funding; one of them is business funding for a beginner UMKM. The beginner UMKM that can get the business funding must complete the requirements that Diskopum requested. Among the requirements requested, there are several fuzzy criteria. This research solves the problem of determining the business funding for the beginner UMKM using the fuzzy TOPSIS method. The method was chosen because the output is in the form of ranking. Since the data used in this study is the submission data from 2019, the data already has the actual results. There are several differences between the actual ranking and the result using the fuzzy TOPSIS method, but the difference is insignificant. That result proved that the fuzzy TOPSIS method could determine the ranking of the business capital fund as an alternative method.
Implementation of the ACS-RVND algorithm on the VRP variant and its application to distribution optimization
Authors: Wahyuningsih Sapti , Satyananda Darmawan , Oktoviana Lucky Tri 
Published: January 2022

Abstract
Distribution optimization has an important role to distribute products to consumers. The selection of the right route will have an impact on the distribution process resulting in minimal costs. The application of graph theory that can be used to determine the optimum route in the distribution process is the study of the Vehicle Routing Problem (VRP) variant. The VRP variants discussed in this article are MDVRP and VRPTW. The method used to solve the VRP variant of this article is the ACS-RVND algorithm. The ACS-RVND algorithm consists of several main stages, namely the initial solution formation stage using the ACS algorithm, the solution improvement stage using the RVND procedure and the acceptance criteria stage. The data needed for the application of the ACS-RVND algorithm in solving the distribution optimization problem of MDVRP cases are the number of depots, the number of customers, the capacity of the vehicle, the number of ants, the number of iterations, the number of customer requests and the distance between customers. While in the case of VRPTW data multiple depots are replaced by time windows depot and service time. The results of solving distribution optimization problems in the form of the route, the total distance traveled and the result of the route in the graph model. The performance of the ACS RVND algorithm can be compared with the performance of the ant colony optimization (ACO) algorithm and the Hybrid Ant Coloy Optimization (HACO) algorithm. Analysis of the results using several dataset test cases showed that the ACS RVND algorithm on MDVRP obtained a better solution than the ACO algorithm and the ACS RVND algorithm on VRPTW was better than the Hybrid Ant Coloy Optimization (HACO) algorithm when viewed from the total distance distribution route.
Profitability estimation of XYZ company using H-infinity and Ensemble Kalman Filter
Authors: Anshori M Y , Herlambang T , Katias P , Susanto F A , Rasyid R R 
Published: January 2022

Abstract
One strategy for a company to develop and grow bigger and stronger in competition is by business expansion. According to Moin (2010:2), there are two strategic ways to maintain and expand a business, that is, an internal expansion strategy by building a new business or business unit from scratch and an external expansion strategy in the form of a business merger by buying an existing company through a merger, acquisitions and consolidations which are fast-track to new markets. Profitability is a factor that gets important attention because it can attract investors to make investment in the company. Profit is the gab beetwen revenue and expenses in a certain period in a company. It has very important role for either internal or external of the company. One way to reduce the risk of company losses is by using an estimation method to find out the company’s estimated profit for the next month or next year. In this study the estimation method for travel company was used, that is, by using the Ensemble Kalman Filter (EnKF) and H-infinity, as a policy making chart in order to maintain and increase company profits. Based on the analysis of results computation with 100, 200 and 300 iterations, it showed an error of less than 3%.
Oscillation and Asymptotic Behavior of Second-Order Half-Linear Noncanonical Difference Equations of Advanced Type
Authors: Gopalakrishnan P , Murugesan A , Dafik  , Agustin I H 
Published: January 2022

Abstract
We established new single-condition criteria for the oscillation of all solutions to a second-order half-linear advanced equation of the form ∆(φ(ζ)(∆x(ζ))
ν
) + ρ(ζ)x

ν
(ζ + η) = 0; ζ
≥
ζ
0 under the conditions that

∑

s
=
ζ

∞

1

ϕ

1

v

(
s
)

<
∞

. We derive new single-condition constraints for the oscillation of all unimprovable constant solutions to equation. Even in the linear case, the significant result is new and improves all of the prior results to the best of our knowledge. The advantage of our technique is the simple proof, solely relying on the monotonicities of a positive solution sequentially improved. Examples of our conclusions are presented.
Hybrid clustering and classification methods to find out the pattern of the spread of covid-19 in East Java province
Authors: Umam M W F , Fatekurohman M , Anggraeni D 
Published: January 2022

Abstract
Covid-19 entered Indonesia in March 2020, which had an extraordinary impact on all aspects of life. The real impact is the economic and social sectors. Various efforts and policies from the Indonesian government were made to suppress the increase in the rate of Covid-19 cases. The spread of Covid-19 cases in Indonesia has been evenly distributed in various provinces, one of which is East Java. East Java has 38 districts/cities, where the case of each district is different, there are green, yellow, red, and black zones. To find out the pattern of spread of each district/city zone, clustering is used. The method used in this study was to use the hybrid method of clustering with K-means and classification with its algorithm Decision Tree. The purpose of this study to prepare mitigation measures to inhibit the rate of spread of Covid-19 in East Java Province. The variables used include the number of positive, the number of dead, the number of recovered, the number of suspects, and the number of probable. With this grouped data, it is expected to help make the right decision in reducing the spread and minimizing the number of positive patients. Based on the results of the study, there will be cluster results, namely 7 very high-risk areas (C0), 1 high risk district (C1), 29 moderate risk districts (C2), and 1 low-risk district (C3). It also has a validity index level of 0.356 as measured by the Davies-Bouldin Index.
High order thinking skills: can it arise when a prospective teacher solves a controversial mathematics problem?
Authors: Rosyadi Alfiani Athma Putri , Sa’dijah Cholis , Susiswo  , Rahardjo Swasono 
Published: January 2022

AbstractHigh order thinking skills are important for prospective mathematics teachers. This study aims to describe whether High Order Thinking Skills (HOTS) can appear when prospective teachers solve controversial math problems. This research has been conducted using descriptive qualitative research. The instruments that have been used are controversial math test questions and interviews. The research subjects used were 150 prospective mathematics teachers, and three people who experienced controversy were taken to find out their HOTS. The results showed that from the three subjects, information was obtained that analysis and evaluation had emerged when solving controversial problems, but only one subject appeared for creating. Suggestions for the next researcher is to combine critical thinking and HOTS to bring up aspects of creating.
Science process skills students on cells and tissues concept during the covid-19 pandemic: how did it achieve?
Authors: Fitrianingrum H , Noor M F 
Published: January 2022

AbstractThe purpose of this study was to measure the achievement of students’ science process skills (SPS) on cells and tissues concept during pandemic. The research was conducted in January 2021 at high school in Depok City. The sampling technique used purposive random sampling. SPS tested consist of 7 aspects (observing, applying concepts, interpreting, asking, communicating, classifying, and concluding). Data collection using an essay test with 16 questions and teacher-student interviews. The instrument was validated by five expert validators and calculated with the Aiken’s V formula reaches 0.74 (valid) and the reliability test value with Cronbach-Alpha reaches 0.81 (reliable). The non-parametric normality test reach 0.361 (sample is normally distributed). The non-parametric Mann-Whitney test reach 0.011 (hypothesis accepted; there is a difference in achievement between grade XI and XII). The results of the survey showed that the students’ SPS were in the moderate (grade XII) and less category (grade XI). The easiest aspect of SPS in both is the questioning aspect. The aspect that gets the least category is communicating (grade XII) and classification (grade XI). This can be influenced by the level of students’ understanding of the concept and scientific process, experience in observing, and doing all scientific process.