bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrasi Pesantren dan Sekolah (Kajian atas Pemikiran Abdurrahman Wahid)
Authors: Wicaksono Herman 
Published: February 2022

Abstract
Pesantren and schools should be integrated where they need to work together to improve the quality of education in Indonesia. Aside from the benefits and drawbacks of the pesantren education model, Abdurrahman Wahid, the "child" of pesantren, has demonstrated that pesantren can generate a nation's competent and competitive generation. As a result, the researcher was able to unearth Abdurrahman Wahid's views through library research involving books, kitab, periodicals, journals, and other connected materials. Abdurrahman Wahid has unique ideas regarding pesantren and school integration. Abdurrahman Wahid believes that this integration is critical in eliminating the knowledge divide and meeting the demands of today's career prospects. If the pesantren are still cut off from the new system that has joined the pesantren system, this will be impossible to do.

Keywords: integration, pesantren, school, Abdurrahman Wahid

Abstrak
Pesantren dan sekolah harus terintegrasi di mana mereka perlu bekerja sama untuk meningkatkan kualitas pendidikan di Indonesia. Selain kelebihan dan kekurangan model pendidikan pesantren, Abdurrahman Wahid, “anak” pesantren, telah menunjukkan bahwa pesantren dapat menghasilkan generasi bangsa yang kompeten dan berdaya saing. Hasilnya, peneliti mampu menggali pandangan Abdurrahman Wahid melalui studi pustaka yang melibatkan buku, kitab, majalah, jurnal, dan materi terkait lainnya. Abdurrahman Wahid memiliki ide unik tentang integrasi pesantren dan sekolah. Abdurrahman Wahid percaya bahwa integrasi ini sangat penting dalam menghilangkan kesenjangan pengetahuan dan memenuhi tuntutan prospek karir saat ini. Jika pesantren masih terputus dari sistem baru yang telah bergabung dengan sistem pesantren, hal ini tidak mungkin dilakukan.

Kata kunci: integrasi, pesantren, sekolah, Abdurrahman Wahid
Impact of Economic Uncertainty on Foreign Direct Investment Inflows of Sri Lanka
Authors: Rodrigo W. P. S. , Randika P. A. D. D. 
Published: February 2022

Foreign direct investment is the heart of economic growth. Sri Lanka faces foreign reserve shortage. Therefore, the researcher studied how foreign investors react on investment flows of Sri Lanka under world, regional, and domestic uncertainty situations of Sri Lanka. The researcher studied on impact of economic uncertainty on foreign direct investment inflows using world, regional and domestic uncertainty indexes which are newly constructed indexes. This study has been used quantitative analysis for impact on economic uncertainty on foreign direct investment inflows of Sri Lanka. The researcher used secondary data for the sample period of 1st quarter, 1996 to 4th quarter, 2019. The researcher used the autoregressive distributed lag model, error correction model for analyzing the short-run and long-run impact on economic uncertainty on FDI inflows of Sri Lanka. Regional economic uncertainty has a significantly impact on foreign direct investment inflows of Sri Lanka in short run and long run. In domestic economic uncertainty has significantly impact on foreign direct investment inflows of Sri Lanka in short run and long run. However, World economic uncertainty has not significantly impacted on foreign direct investment inflows of Sri Lanka This study has used world, regional, and domestic uncertainty of Sri Lanka indexes, which were newly built to capture uncertainties. Findings of the study could be used for the changes of policies to attract foreign direct investment inflows of Sri Lanka.
Влияние автотранспорта на содержание вредных веществ в окружающей среде
Authors: Шевелева Варвара 
Published: February 2022

Актуальность проекта: Данный проект актуален, потому что содержание токсичных веществ в окружающей среде находится в критичном состоянии. В результате накоплений таких веществ в природе могут произойти ужасные события, способные сделать жизнь человека на Земле невыносимой или вовсе ее уничтожить.

Цель проекта: оценить влияние автотранспорта на содержание вредных веществ в окружающей среде.

Задачи проекта:
1) Изучить вредные вещества, которые содержатся в выхлопных газах автотранспорта.
2) Провести социологический опрос по теме «Влияние автотранспорта на содержание вредных веществ в окружающей среде».
3) Рассказать об организациях и людях, которые борются с экологическими проблемами в современном мире.
Методы исследования:
1) Социологический опрос среди учащихся 10-11 классов МБОУ «ЦО №22 (3 Лицей искусств)»
2) Анализ.
Практическая значимость проекта:
1) Результаты данного проекта помогут получить дополнительные знания ученикам о выбросах, которые происходят из-за разного транспорта. А также о тех веществах, которые являются их компонентами.
2) Результаты данного проекта могут помочь людям принять участие в защите нашей хрупкой природы, обращать чаще внимание на свой образ жизни, который не всегда может благоприятно сказываться на окружающем нас мире.
Candida and Candidiasis - A review of Virulence Factors
Authors: Hamied Atyaf Saied 
Published: February 2022

The occurrences of invasive candidiasis has increased over the previous few decades. Although Candida albicans considers as one of the most common species of organisms, that cause acquired fungal infections.
Candida albicans is an opportunistic fungal pathogen and inherent in as a lifelong, the yeast is present in healthy individuals as a commensal, and can reside harmlessly in human body. However, in immuno-compromised individuals, the fungus can invade tissues, producing superficial infections and, in severe cases, life-threatening systemic infections. This review wills emphasis on virulence factor of C. albicans including (adhesion, invasion, candida proteinase, and phenotypic switching and biofilm formation.
Invasive Fungal diseases are result in very high morbidity as well as up to 60% mortality for people with severely susceptible hosts. This review will illustrate briefly the virulence factors in Candida albicans.
The relationship of eosinophil cationic protein / eosinophil count ratio and disease severity in allergic asthma patients
Authors: Qaddoori Yasir Basim , Salih Duha , Altaei Makarim 
Published: February 2022

Finding an applicable clinical biomarker in body fluids can be useful in asthma management. This study was conducted to support the investigations of probable immunological changes in asthmatic patients that may be useful therapeutic indicators. 61 matching patients and 23 apparently healthy individuals were included. Significant elevation in the level of eosinophil cationic protein (ECP) in asthmatics was found as compared with healthy controls, so as among asthma severity categories. The receiver operating characteristic curve analysis determined 29 ng/ml of serum ECP as the typical cut-off value of significant denotation for differentiation between asthmatic patients and healthy individuals, significant positive linear correlation between both ECP level and also ECP/Eosinophil ratio with clinically estimated asthma severity were observed. The median of serum total IgE and rate of 100 IU/ml overlapped serum total IgE individuals were significantly higher in asthmatics than healthy controls and so as among asthma severity categories, whereas no significant correlation between total serum IgE level and asthma severity was found. According to the results, determination of serum ECP can be considered as a diagnostic tool to distinguish asthma cases, besides it reflects the severity of the disease significantly, whereas calculation of ECP/Eo ratio may be an effective marker in reflecting asthma severity and the activity of eosinophils during the inflammation which may be useful in asthma control and in the assessment of the disease severity as well as the response to anti-inflammatory therapy, but it has no benefit for diagnosing asthma as no significant differences were recorded between asthmatics and healthy controls.
GANGGUAN KESEHATAN PADA ANAK USIA DINI AKIBAT KEKURANGAN GIZI DAN UPAYA PENCEGAHANNYA
Authors: Ufiyah Ramlah  
Published: February 2022

Kesehatan adalah hal terpenting dan sangat berharga bagi masyarakat pada umumnya untuk mewujudkan kondisi ini, diperlukan asupan gizi yang cukup. Gizi merupakan zat makanan yang apabila dikonsumsi seseorang maka bisa mendatangkan kesehatan.Jadi kesehatan dan gizi sangat berhubungan. Menyiapkan asupan gizi untuk anak usia dini merupakan hal yang penting untuk diperhatikan oleh orangtua. Karena asupan gizi yang diterima anak usia dini akan mempengaruhi proses tumbuh kembang mereka diusia dewasa kelak.Gizi pada anak tidak dapat dipisahkan dan erat kaitannya dengan kesehatan dan kecerdasan anak. Selain itu, melalui gizi yang diterima anak akan menjadi faktor pendukung dari pertumbuhan dan perkembangan anak. Tujuan penelitian ini adalah untuk meningkatkan kesadaran pendidik maupun orang tua tentang pentingnya kecukupan asupan gizi untuk Anak. Metode yang digunakan dalam penelitian ini kajian pustaka hasil dan pembahasan penelitian yang searah dengan program yang akan diterapkan. Melalui penelitian ini diharapkan dapat memberikan pemahaman kepada pendidik ataupun orang tua yang ada di rumah, sebagai bentuk kesadaran pengawasan akan asupan dan kecukupan gizi anak yang juga sebagai salah satu faktor penting pendukung dari pertumbuhan dan perkembangnnya. factor penyebab kurang gizi; 1). Penyebab langsung, Makanan anak dan penyakit infeksi yang mungkin diderita anak. 2). Penyebab tidak langsung, Ketahanan pangan di keluarga, pola pengasuhan anak, serta kesehatan dan kesehatan lingkungan. Upaya pencegahan dini pada anak yang mengalami gizi buruk; dengan prinsip-prinsip sebagai berikut: 1).Upaya perbaikan status gizi ibu sejak masa remaja, 2). Pemenuhan kebutuhan gizi balita yang dimulai dari ejak lahir dengan “standar emas makanan bayi”: 3). Penapisan massal untuk menemukan hambatan pertumbuhan dan gizi kurang pada anak usia dini. 4). Perhatian khusus diberikan kepada bayi dan balita dengan factor resiko mengalami kekurangan gizi. 5). Dukungan program terkait. 6). Dukungan lintas sector. 7). Perhatian khusus diberikan kepada balita yang rentan memiliki gizi buruk.
PENYERDEHANAAN SURAT SUARA PEMILU DALAM PERSPEKTIF SISTEM PEMILU DAN PEMERINTAHAN PRESIDENSIAL
Authors: Raden Sahran , Ria Zumria 
Published: February 2022

This paper aims to analyze the ideas and policy proposals for simplification of ballot papers implemented in the 2024 simultaneous elections. This simplification of ballots is carried out in an effort to make it easier for voters to vote on voting day in the simultaneous elections, especially in getting to know election participants and their candidates in the right way and legitimate. In addition, simplification of ballot papers makes it easier for election organizers in the process of vote counting accuracy. The design of the electoral ballot must always be relevant to the electoral system and the context of a country's system of government. How is the design of election ballots in the context of the electoral system and the presidential government system adopted in Indonesia.
Abstrak
Tulisan ini bertujuan untuk menganalisis gagasan dan usulan kebijakan penyederhaan surat suara yang dilaksanakan dalam pemilu serentak 2024. Penyederhanaan surat suara ini dilakukan dalam upaya untuk memudahkan pemilih dalam memilih saat hari pemungutan suara pada pemilu serentak terutama dalam mengenal peserta pemilu dan kandidatnya dengan cara yang benar dan sah. Selain itu penyederhaan surat suara memberikan kemudahan bagi penyelenggara pemilu dalam proses akurasi penghitungan suara. Desain surat suara pemilu harus selalu relevan dengan sistem pemilu dan konteks sistem pemerintahan suatu negara. Bagaimana desain surat suara pemilu dalam konteks sistem pemilu dan sistem pemerintahan Presidensial yang dianut di Indonesia.
Integration of Seismic Lithology Cube into Petroleum System Modelling: A Case Study from S-Field, Malaysia
Authors: Lew Chean Lin , Kevin Teng Ging Ern , Ismail Hasnol Hady , Abd Kadir Zailani , Peter Abolins 
Published: February 2022

Abstract
Lithology is an important input parameter into petroleum system modelling (PSM) as it carries information about thermal conductivity and reservoir quality. It can be obtained from the geological static model, gross depositional environment (GDE) maps, or seismic data. The objective of this study is to demonstrate the influence of lithology input on the PSM simulated models (pressure and temperature), by comparing the lithology input derived from seismic data against the one inferred from GDE maps, using S-field as case study.
The derivation of lithology information (Vshale) from seismic data is attempted using extended elastic impedance (EEI) inversion followed by normalization. We performed conversion of Vshale cube into the depth domain, then upscaling prior to utilization as input in PSM for the model simulation and calibration. The results of pressure and temperature models achieved using the lithology input from the GDE maps (homogeneous lithology assumption) served as the reference. These results are compared to the simulated pressure and temperature models obtained using Vshale cube as the lithology input parameters.
3 wells (SD-2, SD-1, S-5) available in S-field (located in Malay Basin) for the study. SD-2 is the calibration whereas SD-1 and S-5 are the blind tests for pressure and temperature models. The pressure model obtained using the seismic lithology cube shows better matching with the measured pore pressure data points when comparing to the pressure model achieved from the reference input. By quantifying the average error between the pressure model and the actual pressure data, the former lithology input contributes to lower pressure error of 161psi in contrast to 232psi using the later lithology input. The results from the blind tests show consistent findings with SD-2 where the lithology input from Vshale cube indicates better agreement with the measured pressure data as compared to the one obtained from GDE maps. The average pressure error has decreased from 220psi to 140psi and from 465psi to 296psi for SD-1 and S-5 respectively. From the temperature model perspective, subtle differences observed for the models for both types of lithology inputs. Both types of lithology inputs able to match well with the recoded temperature data points. In summary, integrating seismic lithology cube into PSM able to provide improved prediction due to detailed characterization of lithology distribution.
The paper has illustrated an attempt to leverage on seismic data for the derivation of lithology (Vshale) cube and using it as a lithology input for petroleum system modelling. The Vshale cube provides detailed and improve characterization of lithology distribution, which will influence the output of the simulated models from PSM as shown through the pressure and temperature models. This could be helpful information for well planning and drilling.
Improving Machine Learning Approaches to Seismic Fault Imaging Through Training Augmentation
Authors: Norlund Philip , Jiang Fan 
Published: February 2022

Abstract
Fault interpretation is critical for understanding subsurface challenges such as fluid migration and avoiding drilling hazards. Recently, Convolutional Neural Networks (CNN) have been shown to be effective tools for identifying faults in seismic data by utilizing image segmentation. However, selecting the optimal training data for building a model can be challenging. Fault shapes and relationships are highly variable due to the complexity of the regional geodynamic processes happening within the earth over time. How to properly select a training subset from a real (i.e., non-synthetic) data-set is crucial for the success of machine learning for seismic interpretation. In this paper, we attempt to quantify how models can be improved by augmenting the training data in various ways. These augmentations include varying the amount of real and synthetic data and including combinations of seismic attributes.
Advanced Coating to Mitigate PDC Cutter Thermal Degradation in PDC Bit Manufacturing
Authors: Xu Jianhui , Zhan Guodong David , Moellendick Timothy E. , Jiang Wenhui 
Published: February 2022

Abstract
Polycrystalline Diamond Compact (PDC) cutters on PDC drill bits are the primary cutting elements to shear and scrape the formations during drilling process. In the PDC drill bit manufacturing, PDC cutters are attached onto drill bit with silver-copper-zinc alloys by brazing process. PDC cutters face the challenge of thermal degradation during this brazing process. This paper studies the development of an advanced coating on PDC cutter to mitigate its thermal degradation in the brazing process. The advanced coating is applied by physical vapor deposition process on PDC cutter. The coated cutter surface is checked by scanning electron microscope (SEM) for the coating integrity. Both the coated and uncoated cutters are brazed and debrazed to mimic the heating cycle of drill bit manufacturing. They are then tested in a vertical turret lathe to shear a rotating granite rock. The volume losses from the wear scars of the cutters after specific passes are compared among those the coated and uncoated PDC cutters. The SEM results show that coating is in good integrity on the PDC cutter surfaces. The coating is continuous, dense without porosity or microcrack. No obvious oxidation is observed after a high-temperature heat treatment at 740 °C, which was used to mimic the overheating brazing process, which is commonly encountered during bit manufacturing. Then, the vertical turret lathe test results show that the coating on the PDC cutters improves the wear resistance by 50% when compared with that of uncoated cutters, after the brazing and de-brazing simulation. This work presents a solution to the thermal degradation of the PDC cutters after brazing process by using an advanced coating process. With the improved wear resistance due to the coating protection, the life of drill bit and its rate of penetration (ROP) during the drilling process can be significantly improved. It is expected to save a lot of drilling time and cost for the drilling operation in the E&P sector.
Joint History Matching of Production and Tracer Data Through an Iterative Ensemble Smoother: A 3D Field-Scale Case Study
Authors: Chalub Cruz William , Luo Xiaodong , Rachares Petvipusit Kurt 
Published: February 2022

Abstract
Reservoir models are often subject to uncertainties, which, if not properly taken into account, may introduce biases to the subsequent reservoir management process. To improve reliability and reduce uncertainties, it is crucial to condition reservoir models on available field datasets through history matching. There are different types of field data. Among others, production data are the most common choice, but they are subject to a major limitation of carrying relatively low value of information. On the other hand, inter-well tracer data have been shown to provide additional information about well-to-well connectivity and reservoir dynamics. However, jointly history matching production and inter-well tracer data still remains challenging due to the lack of a coherent quantitative workflow to fully integrate them. This work can be considered a step towards tackling this noticed problem. To this end, we propose a non-intrusive and derivative-free ensemble history matching workflow, in which reservoir models are more coherently conditioned on both production and inter-well tracer data with the help of a recently developed technique (adaptive localization). The workflow is successfully implemented in the Brugge benchmark case. Our study indicates that the history matching algorithm matches the production data well, regardless of the presence or absence of the tracer data. Nevertheless, by including tracer data as an additional source of information, we are able to improve the quality of the estimated reservoir models, in terms of both improved data match and reduced model discrepancies. Furthermore, we show that the proposed workflow is robust and provides a reasonably good way of uncertainty quantification. In summary, with the help of the adaptive localization scheme, we are able to address the issues of proper uncertainty quantification, and more coherent utilization of different types of field datasets.
1-Click Automatic Well Design Using Integrated Cloud Software
Authors: Hassan Mohamed Ali , Strand Jim , Strømhaug Andreas , Erichsen Lene Lykke 
Published: February 2022

AbstractWell Construction Automation is gradually becoming more prominent in oil & gas industry. It encompasses the application of digital technology in all aspects of well drilling and completion (i.e., automatic well design, digi-talization of downhole tools & surface equipment, remote monitoring, real time data transmission, and robotic rig systems). This paper presents a new workflow of Automatic Well Design, at a mere click of a computer mouse, using integrated cloud software.A software tool, named WellDesign, is used to demonstrate Automatic Well Design workflow. It utilizes net-works and cloud computers for data storage and collaboration and offers a set of Application Programming In-terfaces (APIs), enabling full automation, where whole or parts of the software can be operated by other com-puters. The software GUI can be accessed via any modern web browser across all kinds of computers (Win-dows, Macs) and any other smart devices (tablets, phones).Two automatic design workflows shall be illustrated in detail:Automatic Well Trajectories Automatic Casing Design
Similarity Learning for Well Logs Prediction Using Machine Learning Algorithms
Authors: Rogulina Alina , Zaytsev Alexey , Ismailova Leyla , Kovalev Dmitry , Katterbauer Klemens , Marsala Alberto 
Published: February 2022

Abstract
Determining and predicting reservoir formation properties for newly drilled wells represents a significant challenge for oil and gas companies. Extensive well logs are available only while or after drilling, and thus they bear substantial financial, technical, and operational risks. We propose a new machine learning data-based model for determining well properties similarity and further derive and predict well logs before drilling in a specific geological context.
Our model starts with selecting crucial well intervals and aggregation of vital features that determine the petrophysical properties related to particular well layers. Then, a machine-learning algorithm uses this info as input to provide a similarity score between wells. Our fast-to-train nonlinear data-based model is a variant of gradient boosting. We show that this approach can work well in complex scenarios with missing data and inconsistent similarity measures.
We compare the modern machine learning algorithms for the evaluation of well similarity models based on aggregated features. The algorithms include gradient boosting and baseline logistic regression models. Our assessment for a real well log dataset via group cross-validation demonstrates that the gradient boosting model pretty accurately identifies well similarity. The receiver operating characteristic quality metric (ROC AUC) is 0.824.
The developed similarity learning framework provides a data-driven approach towards estimating well logs for planned and newly drilled wells. Therefore, it allows prediction, improves determination, and can drive an optimal selection of log measurements to be executed in a new well in a specific field / geological context.