bluuebunny/crossref_metadata_2025_split huggingface dataset:
HUBUNGAN USIA DAN JUMLAH PARITAS DENGAN TIPE KARSINOMA ENDOMETRIUM DI RSUD PROF. DR. MARGONO SOEKARJO
Authors: Nusa Arifah Pelangi , Nawangtantrini Gita , Aditiyono Aditiyono , Novrial Dody , Yamsum M 
Published: September 2023

Latar Belakang: Kanker endometrium menempati urutan ke-15 dengan jumlah kasus baru terbanyak pada tahun 2020 di dunia. Masih terdapat perbedaan hasil penelitian tentang hubungan usia dan dan jumlah paritas dengan karsinoma endometrium. Tujuan: Untuk mengetahui hubungan usia dan jumlah paritas dengan tipe kersinoma endometrium di RSUD Prof. Dr. Margono Soekarjo. Metode: Penelitian ini merupakan penelitian analitik observasional dengan studi cross sectional. Teknik pengambilan sampel menggunakan total sampling. Jumlah subjek dalam penelitian ini sebanyak 129 pasien karsinoma endometrium di RSUD Prof. Dr. Margono Soekarjo pada tahun 2017-2022. Data yang diambil merupakan data sekunder dari rekam medik RSUD Prof. Dr. Margono Soekarjo. Variabel usia dan jumlah paritas merupakan data yang tercantum di dokumen rekam medis. Data dianalisis menggunakan uji statistik chi-square. Hasil: Total sampel yang didapatkan adalah 129 pasien kanker endometrium. Usia paling banyak ditemukan pada usia 51-60 tahun (41,1%) dan paling sedikit pada usia <40 tahun (7,8%). Jumlah paritas paling banyak ditemukan yaitu paritas ≥2 (55,8%) dan yang paling sedikit adalah paritas 1 (15,5%). Hasil uji uji statistik chi-square usia dengan tipe karsinoma endometrium menunjukkan nilai p = 0,159 (p>0,05). Berdasarkan hasil analisis menunjukkan tidak ada hubungan yang bermakna antara usia dengan tipe kanker endometrium. Hasil uji uji statistik chi-square jumlah dengan tipe karsinoma endometrium menunjukkan nilai p = 0,02 (p<0,05). Berdasarkan hasil analisis menunjukkan ada hubungan yang bermakna antara jumlah paritas dengan tipe kanker endometrium. Kesimpulan: Tidak terdapat hubungan yang bermakna antara usia dengan tipe karsinoma endometrium dan terdapat hubungan yang bermakna antara jumlah paritas dengan tipe karsinoma endometrium di RSUD Prof. Dr. Margono Soekarjo.
BEETROOT (Beta vulgaris L.) AND ITS POTENTIAL AS AN ANEMIA TREATMENT IN PREGNANCY
Authors: Fadlilah Synta Haqqul , Suhartomo Dalri Muhammad , Yusan Rizak Tiara , Yudhawan Indra 
Published: September 2023

Anemia is one of the most common nutritional problems in pregnant women. It is defined as a condition in which the hemoglobin (Hb) level is lower than normal. The main cause of anemia in obstetrics is iron deficiency. To prevent this condition, the Government of Indonesia through the Ministry of Health made a rule by giving iron tablets to pregnant women at least 90 tablets during pregnancy (Kemenkes RI, 2022). However, some people are often bored with this pharmacological therapy due to the nausea and vomiting effect of the iron smell. Therefore, the development of alternative anemia therapy has been done to minimize those problems. One of the herbal ingredients that are being studied for its potential as anti-anemia in pregnancy is beetroot (Beta vulgaris L.). This research is included in the type of literature review. The selected literature is research articles published in the last 10 years (2013 to 2023). There are 10 articles that match the topic of study. A total of 7 publications demonstrated the effect of beetroot on anemia in pregnant women during the pregnancy period, and 2 articles in the post-partum period. A study performed in vivo experiments on pregnant female rats. Almost all of the studies did intervention by giving subjects beetroot juice. Only one study used beets as an intervention as ice cream. The results show that beetroot has the potential to prevent and treat anemia in pregnancy by increasing hemoglobin levels and the amounts of hematocrit. It contains a high level of folic acid which is important for normal cell and tissue growth. The iron content of beetroot also plays an essential role in the human body transporting oxygen to red blood cells, so it helps to cure anemia.
Multi-Objective Optimization for High-Performance Building Facade Design: A Systematic Literature Review
Authors: Shan Rudai 
Published: September 2023

Building facade design plays an essential role in enhancing energy efficiency and reducing environmental impact in high-performance building design. Balancing the conflicts among various building facade design parameters to satisfy different optimization objectives constitutes a highly complex optimization problem. The rapidly increasing number of studies demonstrates a significant interest in implementing multi-objective optimization methods to tackle building facade optimization problems.
This study conducts a systematic review of optimization methods for building facade optimization (BFO). The optimization objectives and design variables are categorized based on their characteristics. The efficiency and effectiveness of optimization algorithms in addressing BFO problems are compared. Building optimization techniques and tools are showcased, along with their functions and limitations.
Key findings highlight the robust feasibility and effectiveness of optimization algorithms, methods, and techniques in resolving a diverse range of BFO challenges. The limitations, challenges, and future potential of these methods are summarized and proposed.
Staged Repair of Simultaneous Bilateral Proximal Hamstring Rupture and 2 Year Outcome
Authors: Olowofela Bankole O. , Parrish Ryan , Zeppieri Giorgio , Farmer Kevin W. , Pazik Marissa , Roach Ryan P. 
Published: September 2023

Case:
A 53-year-old man presented with simultaneous, bilateral proximal hamstring ruptures. He underwent open, staged surgical repair of the proximal hamstrings, followed by a modified course of rehabilitation. At 2-year follow-up, the patient reports excellent outcomes.

Conclusion:
Simultaneous, bilateral, 3-tendon rupture of the proximal hamstrings is a rare lower extremity injury. Surgical treatment of such injuries presents several unique challenges. Staged surgical repair is an effective treatment option.
Rapid Inference of Reservoir Permeability from Inversion of Traveltime Data Under a Fast Marching Method-Based Deep Learning Framework
Authors: Li Chen , Yan Bicheng , Kou Rui , Gao Sunhua 
Published: September 2023

Summary
The fast marching method (FMM) is a highly efficient numerical algorithm used to solve the Eikonal equation. It calculates traveltime from the source point to different spatial locations and provides a geometric description of the advancing front in anisotropic and heterogeneous media. As the Eikonal solution, the diffusive time of flight (DTOF) can be used to formulate an asymptotic approximation to the pressure diffusivity equation to describe transient flow behavior in subsurface porous media.
For the infinite-acting flow that occurs in porous media with smoothly varying heterogeneity, traveltime of the pressure front from the active production or injection well to the observation well can be directly estimated from the DTOF using the concept of radius (or depth) of investigation (ROI or DOI), which is defined as the moment when a maximum magnitude of the partial derivative of pressure to time occurs. Based on the ROI or DOI definition, we propose a deep neural network called the inversion neural network (INN) to inversely estimate heterogeneous reservoir permeability by inverting the traveltime data.
The INN is trained by traveltime data created for a large data set of distinct permeability fields from FMM simulations, which can be two orders of magnitude faster than conventional reservoir simulators. A convolutional neural network (CNN), the U-Net architecture, is incorporated into the INN, which establishes a nonlinear mapping between the heterogeneous permeability fields and the traveltime data collected at sparse observation wells. The loss function used for the INN is defined as the root mean square error (RMSE) between the logarithm of the predicted permeability and the logarithm of the true permeability.
The performance of the INN is tested on reservoir models with both smoothly varying heterogeneity and high-contrast media properties. For the 2D smoothly varying heterogeneous models with a grid size of 49×49, the permeability predicted by the INN has an average estimation error of 8.73% when a set of 7×7 uniformly distributed observation wells is used to collect “observational” traveltime data from the FMM simulation. For models with the same grid size and observation well density but with high-contrast media properties, the INN can still capture the general heterogeneity distribution, although with reduced prediction accuracy. Using a graphics processing unit (GPU) for training and prediction allows the entire inverse modeling process for a 2D 49×49 reservoir model to be completed within 7 minutes.
Numerical Analysis of Permeability Changes for Clogging and Microcracks Induced by the Invasion of Fracturing Fluid
Authors: Liu Bailong , Yang Deyi , Ito Takatoshi 
Published: September 2023

Summary
Hydraulic fracturing can produce a main fracture and increase flow efficiency. It can also result in the invasion of fracturing fluid, which can produce clay swelling. The invasion can block the pores and throats in the porous media and damage matrix permeability, while it can also induce microcracks under certain conditions. This study developed a numerical model to evaluate the permeability change induced by the invasion. Both pore-throat clogging and microcracks are integrated into the model. The numerical model coupled a flow model based on the pore-scale network method (PNM), a solid model, and a permeability evaluation model. The solid model and permeability evaluation model are based on our microcrack performance model reported previously. We validated the flow model by analytical results and the coupled model by previous experiments of the soaking test. Simulation results show that the invasion can decrease the permeability for the clogging effect and increase the permeability for the microcrack generation. The generation of microcracks can greatly increase the permeability even with the clogging effect for clay swelling. Our simulation results indicated that rock properties can affect the effect of clogging and microcracks on permeability. This study provides an approach for the selection of fracturing fluid and the design of fracturing fluid flowback. This is crucial for the understanding of the invasion on permeability and can serve as a guide for fracturing operations.
Computational Fluid Dynamics-Discrete Element Method Modeling and Analysis of Proppant Transportation Inside Different Degrees of Inclined Tortuous Hydraulic Fractures
Authors: Li Jun 
Published: September 2023

Summary
Optimal proppant transportation and distribution in inclined fractures play a critical role in maximizing the flow conductivity of complex fracture networks in unconventional gas/oil reservoirs. However, existing fracture models have ignored the effect of the tortuosity of inclined fractures, and more efforts are needed in this regard. To address this gap, a comprehensive integration of computational fluid dynamics and the discrete element method (CFD-DEM) is used in this study to numerically simulate the behavior of proppant transport in inclined fractures with tortuous shapes. The results reveal that, as the inclination angle varies, the proppant transport distance and packing height exhibit a nearly linear trend in straight fractures, while, in tortuous fractures, they follow a nonlinear pattern. Additionally, the proppant velocity, fluid velocity, and proppant force chain within inclined fractures with tortuous shapes exhibit significant disparities when compared with their straight counterparts.
Machine-Learned Surrogate Models for Efficient Oil Well Placement Under Operational Reservoir Constraints
Authors: Mousavi Seyed Mahdi , Bakhtiarimanesh Pouya , Enzmann Frieder , Kersten Michael , Sadeghnejad Saeid 
Published: September 2023

Summary
Recent predictive analytics and soft computing methods enhanced the exploration of new hydrocarbon reserves. Machine learning (ML) has showed a promising role in oil and gas explorations in recent years. Among the applications, determining a proper location for injection and production wells along with their optimum operating conditions is a complex problem. This research aims to develop a unified process using surrogate proxy models to address this issue. Five robust ML models, (i) extreme gradient boosting (XGBoost), (ii) light gradient boosting machine (LightGBM), (iii) gradient boosting with categorical features support (CatBoost), (iv) support vector regression (SVR), and (v) multilayer perceptron (MLP), are implemented to create surrogate proxy models for estimating the net present value (NPV) of an oil reservoir. A systematic approach is used to find the best-fit hyperparameter inputs for these models. The objective of this method was to refine a broad set of hyperparameters through a random cross-validation search technique. This grid cross-validation method investigates the space narrowed in more accurate intervals. Four reservoir scenarios are considered: (i) production from a single well in a homogeneous reservoir, (ii) production from a single well in a heterogeneous channelized reservoir, (iii) production from multiple wells in a heterogeneous reservoir, and (iv) waterflooding into a heterogeneous reservoir. A reservoir simulator is implemented to create a data set of reservoir realizations with various input parameters (i.e., well location, number of wells‚ production-injection well distance, and interwell angles) in a broad range of operating conditions. The prediction of gradient boosting and MLP models showed a better fit to the simulated data with an R-squared (R2) above 95% in the first three scenarios and 75% in the fourth scenario. The results indicate that the implemented proxies are promising approaches to efficiently estimate the NPV of the reservoir models both during primary and secondary recovery scenarios.
Production and distribution planning, scheduling and routing problem in a yogurt supply chain under robust fuzzy uncertainty: a case study
Authors: javadi babak , Akbari Amir Hossein , Salimzadeh Zeinab , Yadegari Mahla 
Published: September 2023

Abstract
Regarding the gradual evolution of the food industry and all challenges it faces, like the high perishability of the product, managing the food industry supply chain has become an attractive issue for researchers and decision-makers. Over time the integration of uncertain aspects has continuously gained importance for managerial decision-making. Among these, the industry of yogurt products is one of the most challenging industries. In this study, we investigate the problem of production and distribution planning, scheduling, and routing in the yogurt industry supply chain network. The problem is a multi-product, single plant, multi-distribution center, multi-period, and multi-transportation track. A mixed-integer non- linear programming (MINLP) model is presented to minimize the total costs, including production, setup, overtime, unmet demand, and transportation. Besides, a robust fuzzy programming approach is applied to the problem under uncertainty. A meta-heuristic approach based on the Genetic algorithm was developed to solve the problem. In addition, the required modifications to make GA applicable are the problem mentioned. Tested experiments indicate that the proposed algorithm has an average gap of less than 0.4 percent from the optimal solution within a reasonable time. A real-world case is considered, and the proposed GA method compared to CPLEX and the results show the effectiveness of the model and the average objective function had approximately a 10% improvement.
Efficient Prediction of Residual Stress in Additive Manufacturing Based on Semi-Analytical Solution
Authors: Yang Maohong , Wu Guiyi , Li Xiangwei , Zhang Ruiyao , Zhang Shuyan , Wang Honghong 
Published: September 2023

Abstract
In order to improve the efficiency of residual stress simulation in laser powder feeding additive manufacturing, a finite element modelling method that only requires to solve the stress field is proposed and established in this paper. First, the analytical solution of the heat conduction equation is simplified, and a new temperature field model is developed, which can be directly input into the stress field model for calculation, thereby eliminating the calculation of the temperature field in the thermal-mechanical coupling simulation process and improving the simulation efficiency of residual stress in additive manufacturing. On this basis, the effectiveness of the method is verified by a single-pass single-layer cladding simulation. Meanwhile, the residual stress of single-pass multi-layer cladding is calculated and compared with the measured results, and the distribution characteristics of residual stress in additive manufacturing are studied. It is demonstrated that the result of the established model is closed to that of thermal-mechanical coupled finite element method. The established model can reflect the residual stress of laser powder feeding additive manufacturing process. Compared with the traditional thermal-mechanical coupled finite element method, the computational efficiency of the model established in this study is greatly improved.
Psychosocial Problems of the Elderly During COVID-19: A Systematic Review
Authors: Dangroo Ashfaq Ahmad , Singh Ravinder 
Published: September 2023

Abstract
Background: The COVID-19 pandemic was a global emergency that simultaneously impacted numerous nations and communities. The physical isolation of individuals, families or communities exposed to virus have created a further risk for psychosocial problems. Current statistics for the elderly gives a prelude to a new set of medical, social and economic problems that could arise if a timely initiative in this direction is not taken.
Objective:To study the psychosocial problems of elderly during Covid 19 and to suggest the intervention measures.
Methods: A number of steps were made to help the literature review's quality. Peer-reviewed research publications and reports from worldwide, national, and local sources, including the World Health Organization (WHO), were taken into account. These were examined using both qualitative and quantitative methods, with an emphasis on the psychosocial issues that older people face during Covid 19.
Results: The majority of elderly persons feel that their family members have abandoned them. Many psychological and psychosocial problems have been encountered in the aged like loss of memory, lack of confidence in one’s own ability and adjustment, feeling of being redundant, unwanted and useless, neglected and humiliated, isolated and lonely, reduced interest, insecurity about life, constant feeling of tension, worry and anxiety.
Conclusion: We can conclude that the development of institutions is necessary that provide quality service in terms of treatment and prevention of psychosocial complaints among the elderly.
HIV knowledge and stigma among college students in Southwest China
Authors: Pei Fang , Pei Rong 
Published: September 2023

Abstract
Objectives: This study aimed to assess the knowledge on human immunodeficiency virus (HIV) and factors related to HIV stigma among college students to enlighten them on the development of HIV prevention strategies and better understand the additional benefit of HIV risk reduction.
Methods: This study was an analytical, cross-sectional study conducted between October and December 2020 comprising 10 colleges in southwest China. Survey questions included demographic information, HIV knowledge, HIV stigma, and self-esteem. Descriptive and inferential statistics were applied to summarize the data. Logistic regression was used to analyze factors related to HIV knowledge and stigma.
Results: A total of 4,133 participants were recruited in this study. The knowledge level of respondents on HIV was 74.2%. Stigma was highly prevalent in the form of fear of casual transmission (79.8%), moral judgment (71.1%), personal stigma (72.2%), and perceived community stigma (71.8%). The findings demonstrated that a high level of relevant knowledge regarding HIV was consistently associated with lower stigma levels in four dimensions, and that seven variables—, namely, gender, ethnicity, grade, only-child or not, sexual orientation, awareness of the HIV/acquired immunodeficiency syndrome epidemic, and self-esteem—, played different roles in affecting various dimensions of HIV stigma.
Conclusion: The level of HIV knowledge was low whereas HIV-associated stigma was high among college students in southwest China. Addressing HIV in colleges should incorporate efforts for reducing stigma associated with HIV.
Proton-Boron Fusion: A Dark Horse in the Fusion Race Shows Yield Much Beyond Expectation
Authors: Zhao Yongtao , Wei Wenqing , Zhang Shizheng , Deng Zhigang , Qi Wei , Xu Hao , Liu Lirong , Zhang Jialin , Li Fangfang , Xu Xing , Hu Zhongmin , Chen Benzheng , Ma Bubo , Li Jianxing , Ren Xueguang , Xu Zhongfeng , Hoffmann Dieter H. H. , Fan Quanping , Wang Weiwu , Wang Shaoyi , Teng Jian , Cui Bo , Lu Feng , Yang Lei , Gu Yuqiu , Zhao Zongqing , Cheng Rui , Wang Zhao , Lei Yu , Xiao Guoqing , Zhao Hongwei , Liu Bing , Zhao Guanchao , Liu Minsheng , Xie Huasheng , Cao Leifeng , Ren Jieru , Zhou Weimin 
Published: September 2023

Abstract
A novel intense beam-driven scheme for high yield of the tri-alpha reaction 11B(p,α)2αwas investigated. We used a foam target made of cellulose triacetate (TAC, C9H16O8) doped with boron.It was then heated volumetrically by soft X-ray radiation from a laser heated hohlraum and turned into a homogenous, and long living plasma. We employed a picosecond laser pulse to generate a high-intensity energetic proton beam via the well-known Target Normal Sheath Acceleration (TNSA) mechanism. We observed up to 10^10/sr αparticles per laser shot. This constitutes presently the highest yield value normalized to the laser energy on target. The measured fusion yield per proton exceeds the classical expectation of beam-target reactions by up to four orders of magnitude under high proton intensities. This enhancement is attributed to the strong electric fields and nonequilibrium thermonuclear fusion reactions as a result of the new method. Our approach shows opportunities to pursue ignition of aneutronic fusion.