bluuebunny/crossref_metadata_2025_split huggingface dataset:
Model Perencanaan Pembiayaan Pendidikan Berbasis Mutu di Madrasah Aliyah Negeri 2 Mataram
Authors: Mufida Nur Hayati , Arifin Syamsul 
Published: October 2023

This research aim to describe the quality-based education financing planning model at Madrasah Aliyah Negeri 2 Mataram. To achieve this goal, this researc used descriptive qualitative approach. Research datas were obtainet through in-dept review technique, supported by observation and documentation techniques. The respondents in this research were the leaders, teachers, and employees of MAN 2 Mataram. This study shows that the quality-based education financing planning model at MAN 2 Mataram is pursued through three stages, namely; 1) identifying sources of costs and needs; 2) prioritizing; 3) making a budget plan. Each stage taken is based on the standard planning theory including procedures, principles, characteristics, objectives. In addition, it is also based on regulations and quality-oriented. This model has implications for the achievements of students and institutions that have improved qualitatively and quantitatively. To improve the quality of this financing plan, in the future MAN 2 needs to maximize the economic potential of the madrasah, expand econimic networks, and empower alumni.
Abstrak: Tujuan penelitian ini adalah mendeskripsikan model perencanaan pembiayaan pendidikan berbasis mutu di Madrasah Aliyah Negeri 2 Mataram. Untuk mencapai tujuan tersebut, penelitian ini menggunakan pendekatan kualitatif yang bersifat deskriptif. Data penelitian diperoleh melalui teknik wawancara mendalam dan didukung dengan teknik observasi dan dokumentasi. Adapun responden dalam penelitian ini adalah jajaran pimpinan, guru, dan karyawan MAN 2 Mataram. Hasil penelitian ini menunjukkan bahwa model perencanan pembiayaan pendidikan berbasis mutu di MAN 2 Mataram ditempuh melalui tiga tahapan berupa; 1) identifikasi sumber biaya dan kebutuhan; 2) membuat prioritas; 3) membuat rencana anggaran. Setiap tahapan yang ditempuh berpijak pada standar teori perencanaan mencakup prosedur, prinsip, sifat, tujuan. Di samping itu juga berpijak pada regulasi dan berorientasi pada mutu. Wujud model ini berimplikasi pada prestasi-prestasi siswa dan lembaga yang mengalami peningkatan secara kualitatif dan kuantitatif. Untuk meningkatkan kualitas perencanaan pembiayaan ini, ke depan MAN 2 perlu lebih memaksimalkan potensi ekonomi madrasah, memperluas jaringan di bidang ekonomi, dan memberdayakan alumni.
An Algorithmic Approach to Understanding Osteoarthritic Knee Pain
Authors: Hill Brandon G. , Byrum Travis , Zou Anthony , Schilling Peter L. 
Published: October 2023

Update
This article was updated on November 3, 2023, because of a previous error. In the byline on page 1 and in the list of authors' names on page 8, the last name of the third author that had read “Zhou” now reads “Zou.”
An erratum has been published: JBJS Open Access. 2023;8(4):e23.00039ER.

Background:
Osteoarthritic knee pain is a complex phenomenon, and multiple factors, both within the knee and external to it, can contribute to how the patient perceives pain. We sought to determine how well a deep neural network could predict osteoarthritic knee pain and other symptoms solely from a single radiograph view.

Methods:
We used data from the Osteoarthritis Initiative, a 10-year observational study of patients with knee osteoarthritis. We paired >50,000 weight-bearing, posteroanterior knee radiographs with corresponding Knee Injury and Osteoarthritis Outcome Score (KOOS) pain, symptoms, and activities of daily living subscores and used them to train a series of deep learning models to predict those scores solely from raw radiographic input. We created regression models for specific score predictions and classification models to predict whether the modeled KOOS subscore exceeded a range of thresholds.

Results:
The root-mean-square errors were 15.7 for KOOS pain, 13.1 for KOOS symptoms, and 14.2 for KOOS activities of daily living. Modeling was performed to predict whether pain was above or below given pain thresholds, and was able to predict extreme pain (KOOS pain < 40) with an area under the curve (AUC) of 0.78. Notably, the system was also able to correctly predict numerous cases where the Kellgren-Lawrence (KL) grade assigned by the radiologist was 0 but patient pain was high, and cases where the KL grade was 4 but patient pain was low.

Conclusions:
A deep neural network can be trained to predict the osteoarthritic knee pain that a patient experienced and other symptoms with reasonable accuracy from a single posteroanterior view of the knee, even using low-resolution images. The system can predict pain and dysfunction that the traditional KL grade does not capture. Deep learning applied to raw imaging inputs holds promise for disentangling sources of pain within the knee from aggravating factors external to the knee.

Level of Evidence:
Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Mitigasi Bencana Tsunami Pantai Pangandaran, Jawa Barat
Authors: Lestari Aulia Setya , Muzani Muzani , Setiawan Cahyadi 
Published: October 2023

Abstrak: Pantai Pangandaran ialah salah satu dari beberapa pantai yang berada di selatan Pulau Jawa yang letaknya berada pada zona tumbukan (subduksi) antara Lempeng Indo-Australia dan Eurasia sehingga menyebabkan Pantai Pangandaran rawan akan terjadinya gempa bumi dan tsunami. Tujuan dari penelitian ini untuk mengetahui bentuk upaya mitigasi bencana tsunami Pantai Pangandaran. Metode yang digunakan dalam penelitian ini adalah deskriptif dan analisis evaluatif. Analisis spasial digunakan untuk mengkaji bahaya, sedangkan deskriptif evaluatif untuk mengkaji mitigasi bencana tsunami. Hasil penelitian menunjukan bentuk mitigasi yang dilakukan secara struktural yaitu penanaman mangrove, pembuatan jalur evakuasi, membangun tempat evakuasi sementara dengan jarak kurang lebih 500 m dari pantai, membuat benteng sebagai pemecah ombak, dan memasang peringatan dini tsunami. Upaya mitigasi non struktural terkait adanya penerapan kebijakan tentang tata guna lahan, pengembangan sistem peringatan dini dan dipublikasikan melalui berbagai media, serta mengadakan simulasi mitigasi bencana tsunami. Adapun program inovasi mitigasi bencana tsunami yaitu Anak TK Mitigasi, Wisata Edukasi Bencana Goes To School, Silaturahmi Empati Berbagi Edukasi Bencana, Bunda Belajar Mitigasi, Forum Kesiapsiagaan Dini Masyarakat, dan Hotel dan Restauran Tangguh Bencana.
Kata Kunci: Mitigasi Bencana, Tsunami, Pantai Pangandaran.
Karakteristik Sineresis dan Kadar Air Yoghurt Buah Naga Merah (Hylocereus polyrhizus L) yang Ditambahkan dengan Gula Kelapa Kristal
Authors: Famuji Agung , Zulaikhah Siti Rahmawati , Sidhi Arif Harnowo 
Published: October 2023

Susu merupakan bahan makanan yang bergizi tinggi karena di dalam susu segar mengandung berbagai zat makanan lengkap dan seimbang seperti protein, lemak, karbohidrat, mineral, dan vitamin sehingga menjadi media yang sempurna bagi pertumbuhan mikroorganisme. Salah satu cara mengatasi hal tersebut adalah fermentasi menjadi yoghurt. Fermentasi yoghurt yang terlalu masam dan tidak cocok bagi lidah orang Indonesia dapat ditambah dengan gula kelapa kristal, Penambahan gula kelapa juga dapat menjadi sumber energi bakteri asam laktat (BAL) dan sebagai sumber karbon untuk memicu pertumbuhan bakteri pada susu fermentasi dan juga bisa berpengaruh terhadap kadar air dan sineresis yoghurt. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh level penambahan gula kelapa kristal terhadap karakteristik Kadar air dan Sineresis yoghurt buah naga merah. Penelitian ini dilaksanakan menggunakan metode eksperimental dengan Rancangan Acak Lengkap (RAL) dengan menggunakan 4 perlakuan dan 5 ulangan. Perlakuan dalam penelitian ini adalah penambahan berbagai level gula kelapa kristal 0%, 5%, 10% dan 15% (b/v). Data yang diperoleh kemudian di uji menggunakan uji Analisis Variansi (ANOVA). Apabila perlakuan sajaberpengaruh nyata terhadap variable maka dilanjutkan dengan uji Duncan Multiple Range Test (DMRT). Variabel yang diamati adalah kadar air dan sineresis pada yoghurt buah naga merah. Hasil penelitian menunjukan pengaruh perlakuan berbeda nyata pada kadar air dan sineresis yoghurt buah naga merah. Berdasarkan uji lanjut menggunakan DMRT menunjukan bahwa semakin tinggi level gula kelapa kristal yang ditambah maka kadar air dan sineresis semakin rendah.
Predicting the Stress in Marcellus Shale Horizontal Wells from the Drilling and Well Log Data
Authors: Alawadh Moudhi , El Sgher Mohammed , Aminian Kashy , Ameri Samuel 
Published: October 2023

Abstract
The distribution of the anisotropic minimum horizontal stress, both in horizontal and vertical directions, is necessary for effective hydraulic fracture treatment design in Marcellus Shale horizontal wells. Typically, the minimum horizontal stress can be estimated sonic logs. However, sonic log data is not commonly available for the horizontal Marcellus shale wells due to the complexity and cost. The objective of this study is to predict the anisotropic minimum horizontal stress by utilizing drilling parameters including depth, weight-on-bit (WOB), revolution per minute (RPM), standpipe pressure, torque, pump flow rate, and the rate of penetration (ROP). More specifically, artificial neural network (ANN) models will be developed to predict the anisotropic minimum horizontal stress for a horizontal Marcellus shale well from the drilling and well log data. Artificial neural networks are particularly useful to identify complex relationships to predict the properties of unconventional formations.
The available data from a Marcellus Shale horizontal well was collected and filtered to prepare data sets for ANN training, testing, and validation purposes. Two networks, for the vertical and lateral sections of the well, were developed. The preliminary results indicated that inclusion of lithology, gamma-ray, and bulk density well log data as inputs can improve the predictability of the networks. Finally, the networks were used to predict the anisotropic minimum horizontal stress in a different Marcellus shale horizontal well with the available sonic log data. To evaluate the applicability of the ANN models, the predicted stresses by the networks were compared against those estimated from the sonic logs. The predictions by both networks (vertical and horizontal) were found to be in close agreement with those estimated from the sonic logs. The results of this study can be utilized as a predictive tool to help fill in the need for an accurate estimation of static geomechanical properties including the minimum horizontal stress in Marcellus Shale horizontal wells and to improve the fracturing treatment design.
Application of Oilfield Geomechanics Techniques to Geologic Carbon Capture, Utilization, and Storage (CCUS) Projects
Authors: Alt R. C. 
Published: October 2023

Abstract
With increasing industry and government attention directed toward climate change mitigation, CO2 injection wells are expected to play a vital role in America’s emerging energy infrastructure and to make up an ever-increasing share of commercial wellbore geoscience activities. The Environmental Protection Agency (EPA) assigns CO2 injection wells to a category distinct from oil and gas wells, asserts regulatory primacy, and imposes a specific set of regulatory guidelines that drive well planning procedures for what it defines as Class VI injectors. These permitting requirements for a Class VI injector are notably stricter than for a traditional hydrocarbon producing well, which also drives an expectation for greater precision in quantifying several geologic parameters during well planning. For geomechanics teams, this presents a valuable opportunity to develop customized models to optimize drilling and injection procedures, following in the footsteps of what has already been accomplished with horizontal drilling and hydraulic fracturing in the onshore unconventional space over the past two decades.
In this paper, we examine the application of oilfield geomechanics techniques, including pore pressure prediction, rock strength estimation, and wellbore stability analysis to assist in drilling and completion of CCUS wells. We walk through the workflow to build a robust 1-D geomechanical model, calibrated to available offset data utilizing field and wellbore scale geomechanical modeling platforms. Next, we identify best practices for drilling and completing CO2 injectors. Finally, we apply the geomechanical modeling methodology to CCUS wells, focusing on four key operational risks that are exacerbated compared to similarly situated oil and gas wells: overpressure, borehole breakout, fault reactivation, and stress changes with depletion and injection. We conclude by considering future research opportunities in this field.
Enhancing Unconventional Reservoir Performance: Integrating Real-Time Fracture-Driven-Interactions (FDIs) and Post-Stage Fall-Off Analysis
Authors: Ibrahim A. F. , Assem A. I. , Sinkey M. , Johnston T. 
Published: October 2023

Abstract
Hydraulic fracturing near depleted fractured rocks is a major cause of fracture hits, leading to damage in parent wells and reduced fracture efficiency in the child well due to significant fluid and proppant losses to the parent well. This behavior is exacerbated by tight well spacing and the depletion time of the parent wells. To address this issue, the current study aims to combine real-time fracture-driven-interactions (FDIs) and post-stage pressure transient analysis (PTA) to accurately estimate fracture half-length for each stage during hydraulic fracturing operations.
During hydraulic fracture operations, pressure gauges are installed in offset wells to measure pressure changes during each stage completion in the child well, taking well interference into account. The post-stage fall-off pressure data is then used to calculate the connected fracture surface area (FSA). By analyzing the real-time FDIs with an offset depleted zone, the methodology can estimate higher stage fracture half-length, indicating lower cluster efficiency. The summation of stages with high fracture half-length enables the estimation of the well interference value.
To validate the proposed methodology, actual field cases from oil and gas shale frac data are presented, showcasing live FDIs measurements for each stage, followed by stage-by-stage PTA. The preliminary results reveal that over 20% of the stages experience fracture hits due to the higher fracture half-length and lower cluster efficiency. Furthermore, the well interference value has been verified using actual production data.
Integrating FDI measurements with PTA for detecting frac stage interference in unconventional wells provides a faster, more accurate, and cost-effective fracture diagnostic tool that optimizes well spacing.
Unique Production Conditions of Unconventional Wells in the Appalachian Basin; A Multi-Dimensional Assessment on Recovery
Authors: Rozploch T. , Ayers K. , Jacot H. , Eshbaugh K. 
Published: October 2023

Abstract
This paper delves into the effects of long-term shut-in periods and production cycling on unconventional wet gas wells in the Appalachian Basin, where unique operational circumstances led to a long-term shut-in period.
The unconventional Marcellus and Burkett wells were of a variety of production age. Ranging from depleted and operating under artificial lift, while others were recently flowed back and still in wellbore cleanup. A "long-term shut-in" refers to a shut-in period that occurs after a well has been in production for a substantial time period, rather than an intentional delay of production post-stimulation, known as "seasoning." The term "production cycling" refers to turning wells online to production for short periods of time and then shut-in for short periods of time. This was due to pipeline constraints, lease agreements, and/or transient operational conditions.
The paper discusses the results of a comprehensive analysis, which included decline curve analysis, statistical analysis, hydraulic fracture modeling, build-up analysis, and rate transient analysis. The study considered many factors, such as inter-well spacing, stimulation, generational effects, wellbore boundaries, and reservoir/geologic characteristics.
Overall, the study revealed a wide range of both positive and negative effects from both a reservoir and a production perspective, suggesting that factors such as well age, generation, spacing, and stimulation size were drivers. Near-term improvements were observed in previously damaged parent wells following the shut-in period. Several of the wells experienced a second, higher initial production rate than during flow back due to fluid cleanup effects. However, certain tightly spaced wells experienced negative effects on production in the longer term.
In conclusion, this paper provides a comprehensive analysis of the effects of long-term shut-in periods and production cycling on unconventional wet gas wells in the Appalachian Basin. In real-time operations, many unique challenges are presented, gaining a deeper understanding of the downhole reservoir and long-term production effects will aid in more informed operational decisions in the future. The research outcomes emphasize the need for a more nuanced approach to unconventional reservoir development, and a careful consideration of the specific circumstances of each well. This study contributes to the ongoing efforts to improve the recovery of unconventional resources as these assets mature.
Discovery of Initial SARS-CoV-2 as DNA Viruses and Reliable Interactive COVID-19 DNA Methylation Markers and Druggable Targets and Potential Malignant Diseases with Long Incubation Period
Authors: Zhang Zhengjun 
Published: October 2023

Abstract
COVID-19 research needs interactive reliable biomarkers at genomic and genetic levels. Earlier research has established the existence of reliable interactive genomic biomarkers. However, reliable DNA methylation markers haven't been identified at the epigenetic level, not to mention interactiveness. This study, from 865,859 methylation sites, discovers two miniature sets of Infinium MethylationEPIC sites, each having seven (CpG sites, genes) to interact with each other and with disease subtypes. They lead to nearly perfect (96.87-100% accuracy) prediction of COVID-19 patients from patients with other diseases or healthy controls. These CpG sites can jointly explain some post-COVID-19-related conditions. These CpG sites and the optimum performed genomic biomarkers reported in our earlier work rise to be potential druggable targets. Among these CpG sites, diseases associated with cg16785077 (gene MX1) can have an incubation period of up to six to eight years, which raises a serious (or urgent) issue to investigate now or sooner. The gene PARP9 (cg25932713) is one of the only three human genes that contain both PARP domains and macrodomains. MX1 and PARP9 together were linked to SARS-CoV-1, MERS-CoV, and SARS-CoV-2. The new findings of CpG sites cg16785077 (gene MX1) and cg25932713 (PARP9, cg22930808) in COVID-19 at DNA methylation levels indicate that the initial SARS-CoV-2 may be better treated as transcribed viral DNA into RNA virus due to the long incubation feature of MX1 associated diseases, i.e., not as an RNA virus that has been concerned by scientists. Such a discovery will significantly change the scientific thinking and knowledge of viruses.
An optoacoustic field-programmable perceptron for recurrent neural networks
Authors: Becker Steven , Englund Dirk , Stiller Birgit 
Published: October 2023

Abstract
A critical feature in signal processing is the ability to interpret correlations in time series signals, such as speech. Machine learning systems process this contextual information by tracking internal states in recurrent neural networks (RNNs), but these can cause memory and processor bottlenecks in applications from edge devices to data centers, motivating research into new analog inference architectures. But whereas photonic accelerators have demonstrated big leaps in uni-directional feedforward deep neural network (DNN) inference, the bi-directional architecture of RNNs presents a unique challenge: the need for a short-term memory that (i) programmably transforms optical waveforms with phase coherence , (ii) minimizes added noise, and (iii) enables programmable readily scales to large neuron counts. Here, we address this challenge by introducing an optoacoustic recurrent operator (OREO) that simultaneously meets (i,ii,iii). Specifically, we experimentally demonstrate an OREO that contextualizes and computes the information carried by a sequence of optical pulses via acoustic waves. We show that the acoustic waves act as a link between the different optical pulses, capturing the optical information and using it to manipulate the subsequent operations. Our approach can be controlled optically on a pulse-by-pulse basis, offering simple reconfigurability. We use this feature to demonstrate a recurrent drop-out, which excludes optical input pulses from the recurrent operation.
We apply OREO as an acceptor to recognize up-to 27 patterns in a sequence of optical pulses. Finally,
we introduce a DNN architecture that uses the OREO as bi-directional perceptrons to enable new classes of DNNs in coherent optical signal processing.
The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses
Authors: Walker Rosie , Chong Michael , Perrot Nicolas , Pigeyre Marie , Gadd Danni , Stolicyn Aleks , Shi Liu , Whalley Heather , Nevado-Holgado Alejo , McIntosh Andrew , Heitmeier Stefan , Rangarajan Sumathy , O'Donnell Martin , Smith Eric , Yusuf Salim , Whiteley William , Campbell Archie , Shen Xueyi , Pare Guillaume 
Published: October 2023

Abstract
Decline in cognitive function is the most feared aspect of ageing. Poorer midlife cognitive function is associated with increased dementia and stroke risk. The mechanisms underlying variation in cognitive function are uncertain. Here, we assessed associations between 1160 proteins’ plasma levels and two measures of cognitive function, the digit symbol substitution test (DSST) and the Montreal Cognitive Assessment in 1198 PURE-MIND participants. We identified five DSST performance-associated proteins (NCAN, BCAN, CA14, MOG, CDCP1), with NCAN and CDCP1 showing replicated association in an independent cohort, GS (N=1053). MRI-assessed structural brain phenotypes partially mediated (8-19%) associations between NCAN, BCAN, and MOG, and DSST performance. Mendelian randomisation analyses suggested higher CA14 levels might cause larger hippocampal volume and increased stroke risk, whilst higher CDCP1 levels might increase stroke and intracranial aneurysm risk. Our findings highlight candidates for further study and the potential for drug repurposing to reduce risk of stroke and cognitive decline.