bluuebunny/crossref_metadata_2025 huggingface dataset:
Self-Replicating RNA Viruses for Vaccine Development Against Infectious Diseases and Cancer
Authors: Lundstrom Kenneth
Published: July 2021

Alphaviruses, flaviviruses, measles viruses and rhabdoviruses are enveloped single-stranded RNA viruses, which have been engineered as expression vector systems for recombinant protein expression and vaccine development. Due to the presence of non-structural genes encoding the replicase complex, a 200,000-fold amplification of viral RNA occurs in the cytoplasm of infected cells providing extreme transgene expression levels, which is why they are named self-replicating RNA viruses. Expression of surface proteins of pathogens causing infectious disease and tumor antigens provide the basis for vaccine development against infectious diseases and cancer. The self-replicating RNA viral vectors can be administered as replicon RNA, recombinant viral particles, or layered DNA/RNA replicons. Self-replicating RNA viral vectors have been applied for vaccine development against influenza virus, HIV, hepatitis B virus, human papilloma virus, Ebola virus and recently coronaviruses, especially SARS-CoV-2 the causative agent of the COVID-19 pandemic. Measles virus and rhabdovirus vector-based SARS-CoV-2 vaccine candidates have been subjected to clinical trials. Moreover, RNA vaccine candidates based on self-amplifying alphaviruses have also been evaluated in clinical settings. Various cancers such as brain, breast, lung, ovarian, prostate cancer and melanoma have also been targeted for vaccine development. Robust immune responses and protection have been demonstrated in animal models. Clinical trials have shown good safety and target-specific immune responses. Ervebo, the VSV-based vaccine against Ebola virus disease has been approved for human use.
Pemodelan Matematika Karakteristik Pengeringan Lada Putih Pada Pengering Spouted Bed Dengan Perlakuan Preheating Gelombang Mikro
Authors: Mukhlis Andi Muhammad Akram , Fadhilah Nurul
Published: July 2021

Untuk mempelajari pengaruh pengeringan terhadap biji lada putih diperlukan pengetahuan yang mendalam tentang kinetika pengeringan. Kinetika pengeringan bahan dapat dijelaskan melalui model matematika yang biasanya digunakan untuk memperkirakan waktu pengeringan bahan. Penelitian ini bertujuan untuk menentukan model matematika pengeringan yang tepat untuk pengeringan spouted bed lada putih dengan perlakuan preheating gelombang mikro. Peralatan yang digunakan dalam penelitian ini adalah alat pengering spouted bed yang dirancang untuk skala laboratorium. Bahan yang digunakan dalam penelitian ini berupa biji lada putih basah yang diperoleh dari perkebunan rakyat di kabupaten Enrekang provinsi Sulawesi Selatan dengan umur kira-kira 8-9 bulan setelah pembungaan. Lada putih langsung dimasukkan ke dalam ruang pengeringan spouted bed untuk perlakuan non-preheating sedangkan untuk perlakuan preheating lada disimpan dalam wadah kemudian dimasukkan ke dalam oven microwave terlebih dahulu selama 2 menit. Selama proses pengeringan, beberapa parameter untuk analisis pengeringan diukur. Terdapat tujuh model matematika pengeringan berbeda yang dievaluasi. Dalam penentuan model matematika yang paling sesuai, diperlukan validasi model melalui metode statistika. Metode statistik yang digunakan adalah analisis korelasi, uji chi-square (χ2) tereduksi dan analisis root mean square error (RMSE). Berdasarkan hasil analisis, model Weibull memenuhi kriteria untuk dijadikan model terbaik dengan koefisien korelasi r (0,99990) adalah yang tertinggi serta dan nilai χ2 (0,00001) serta nilai RMSE (0,00385) adalah yang terendah. Dengan demikian, model Weibull dapat digunakan untuk memprediksi waktu dan kadar air pengeringan.
Equal Access to the Vaccination of Covid-19 in Southeast Asia: Can ASEAN be a Catalyst?
Authors: Tarigan Muhammad Insan , Hafandi Raisha
Published: July 2021

Since the time Covid-19 was discovered in Southeast Asia, around 2.5 million people have been infected and more than 54 thousand have died by early March 2021. Even though ASEAN members have followed most of the WHO recommendations to deal with Covid-19, cases are still liable to increase. Therefore, vaccine utilization is the best chance which people believe in to fight the pandemic for now. However, the vaccine’s availability and distribution are a dilemma for the ASEAN member countries. Therefore, this article aims to determine the possibility of ASEAN’s role in creating equal access to the Covid-19 vaccine for everyone. According to the juridical normative research, ASEAN is committed to protect and promote human rights and to realize the Sustainable Development Goals (SDGs). On that basis, the organization tends to play an important role in Covid-19 vaccination in Southeast Asia by cooperating with its partners to research and create the required vaccine.
Hasil Belajar Keterampilan Proses Sains Siswa Berbasis Pendekatan Inkuiri Pada Materi Teori Kinetik Gas
Authors: Fitriana Dea
Published: July 2021

Abstrak

Proses pembelajaran pada materi teori kinetik gas masih cenderung monoton, siswa tidak dilibatkan secara aktif selama proses pembelajaran berlangsung. Hal ini menyebabkan kurangnya pemahaman siswa terhadap konsep yang disampaikan pada materi ini. Guru harus mampu merancang kegiatan pembelajaran yang berorientasi pada proses, sehingga siswa dapat mengembangkan keterampilan ilmiah yang dimiliki. Dalam hal ini proses pembelajaran berbasis pendekatan inkuiri sesuai untuk melatih siswa agar tercipta sikap aktif, berpikir kritis, mampu memecahkan masalah, sehingga tercapai hasil belajar yang baik. Penelitian ini bertujuan untuk mendeskripsikan hasil belajar keterampilan proses siswa melalui penerapan media pembelajaran teori kinetika gas berdasarkan pendekatan inkuiri. Metode yang digunakan dalam penelitian ini adalah desain One Shoot Case Study. Subjek penelitian ini adalah kelas XI MIA 3 SMA Negeri 4 Pekanbaru. Instrumen pengumpulan data adalah tes hasil belajar keterampilan proses pembelajaran. Teknik analisis data yang digunakan adalah analisis deskriptif. Hasil penelitian menunjukkan rata-rata daya serap keterampilan proses siswa berada pada kategori baik sebesar 74,95%. Tingkat keterampilan proses menunjukkan 81,25% siswa memiliki keterampilan dasar yang baik, sedangkan keterampilan terintegrasi adalah 68,75%. Dapat disimpulkan bahwa penerapan media pembelajaran dalam bentuk perangkat eksperimental berdasarkan pendekatan inkuiri dapat meningkatkan hasil belajar keterampilan proses siswa dalam materi teori kinetik gas.

Kata kunci: Hasil Belajar, Keterampilan Proses, Inkuiri
Analisis Kemampuan Argumentasi Siswa SMP pada Materi Pencemaran Lingkungan
Authors: Ambarawati Dwi Siti Hartinah Eny , Muslim Muslim , Hernani Hernani
Published: July 2021

Penelitian ini bertujuan untuk mengetahui kemampuan argumentasi siswa SMP terkait materi pencemaran lingkungan. Penelitian ini menggunakan metode penelitian deskriptif dengan pendekatan kuantitatif. Penelitian dilaksanakan di salah satu SMP yang berlokasi di Lembang, Kabupaten Bandung Barat pada 29 orang siswa kelas VII sebagai sampel yang telah dipilih menggunakan teknik random sampling. Instrumen penelitian yaitu tes berbentuk uraian (essay) sebanyak 6 butir soal yang disusun berdasarkan indikator kemampuan argumentasi (claim, data, warrant, backing). Instrumen yang digunakan divalidasi oleh tiga validator yaitu dua dosen ahli dan satu guru bidang studi IPA. Jawaban siswa dianalisis berdasarkan komponen argumentasi yang terkandung didalamnya. Hasil penelitian menunjukkan bahwa 93,10% siswa menuliskan claim, 54,02% siswa menuliskan data, 48,85% siswa menuliskan warrant, dan 45,40% siswa dapat menuliskan backing. Secara keseluruhan dapat disimpulkan bahwa sebagian besar siswa mampu menuliskan claim namun mulai mengalami kesulitan untuk mengemukakan data, warrant, dan backing. Persentase kemampuan awal siswa dalam berargumentasi tersebut dapat dijadikan sebagai acuan bagi guru sehingga kedepannya dapat menentukan desain atau kegiatan pembelajaran yang tidak hanya berfokus pada pemahaman konsep tetapi juga dapat membangun atau melatih kemampuan argumentasi siswa.
Development of Puzzel Learning Media by Crossword Puzzel
Authors: Titisari Prima Wahyu , Pratiwi Febi Acitika
Published: July 2021

Abstract. Learning media is a teaching and learning process that tends to be interpreted as graphical, photographic, or electronic tools to capture, process, and reconstruct visual or verbal information. Crosswords are a kind of word play. The learning media developed to facilitate teachers and students in the process of learning and teaching at Junior High School grade VIII. The purpose of this study was to prodice puzzle learning media by crossword puzzle and feasible to be developed as rearning media on human eireulatory system material. Based on the results of the observations that have been carried out, the teacher only uses descourse and less varied learning  which makes students bored in learning. The method used in this study is the research and development (R & D), by ADDIE method, the researcher produced a crossword puzzle and its feasibility will be tested. The results of the study after the media were tested on the validator of media experts and material experts got a very decent category. The results of the research from the science teacher, get a very feasible assessment to be developed. The results of research on peer review get a very feasible category to be tested. And the results obtained during the trial of students with trials of small groups, middle groups and large groups led to a very decent category. To we it can be concluded that, puzzle learning media by crossword puzzles is very feasible to develop.

Keywords: Puzzle learning media, crossword puzzles
PEMBELAJARAN FISIKA MELALUI INKUIRI TERBIMBING DENGAN MENGGUNAKAN MEDIA KIT LISTRIK PAKET DAN SWAKARYA DITINJAU DARI KREATIVITAS DAN KECERDASAN KINESTETIK SISWA
Authors: Purnami Wahyuni , Sarwanto Sarwanto , Masykuri Muhammad
Published: July 2021

Penelitian ini bertujuan untuk mengetahui perbedaan hasil belajar antara pembelajaran dengan inkuiri terbimbing dengan menggunakan media kit listrik paket dan swakarya, kreativitas, kecerdasan kinestetik, dan interaksinya. Penelitian ini dilaksanakan pada bulan Februari–November 2012 dengan menggunakan metode kuasi eksperimen. Populasi penelitian adalah seluruh siswa kelas IX SMPN 5 Klaten, Jawa Tengah. Penentuan sampel menggunakan teknik cluster random sampling, yang terdiri dari kelas IX A dan kelas IX C. Kelas IX A diberi pembelajaran dengan menggunakan kit listrik paket dan kelas IX C menggunakan kit listrik swakarya. Instrumen tes digunakan untuk mengukur data hasil belajar kognitif. Observasi unjuk kerja dan angket digunakan untuk mengukur kreativitas dan kecerdasan kinestetik. Analisis data menggunakan anava tiga jalan dengan desain faktorial 2 x 2 x 2 dan dilanjutkan dengan uji Scheffe. Dari penelitian ini disimpulkan bahwa: 1) ada perbedaan hasil belajar yang signifikan antara siswa yang diberi pembelajaran dengan menggunakan metode inkuiri terbimbing dengan menggunakan media kit listrik paket dan swakarya; 2) ada perbedaan hasil belajar yang signifikan antara siswa yang mempunyai kreativitas tinggi dan rendah; 3) ada perbedaan hasil belajar yang signifikan antara siswa yang mempunyai kecerdasan kinestetik tinggi dan rendah; 4) tidak ada interaksi antara media dan kreativitas terhadap hasil belajar; 5) tidak ada interaksi antara media dan kecerdasan kinestetik terhadap hasil belajar siswa; 6) ada interaksi antara kreativitas dan kecerdasan kinestetik terhadap hasil belajar siswa; 7) tidak ada interaksi antara media, kreativitas, dan kecerdasan kinestetik terhadap hasil belajar siswa.

 

Kata Kunci:  Metode inkuiri terbimbing, kit listrik, kreativitas siswa, kecerdasan kinestetik
PENGEMBANGAN MODUL FISIKA BERBASIS MASALAH PADA MATERI LISTRIK DINAMIS UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KREATIF SISWA KELAS X SMA/MA
Authors: Sudaryati Asri , Suparmi Suparmi , Sarwanto Sarwanto
Published: July 2021

Penelitian ini bertujuan untuk: (1) mengetahui karakteristik modul fisika berbasis masalah pada materi listrik dinamis, (2) mengetahui kelayakan modul fisika berbasis masalah pada materi listrik dinamis, (3) mengetahui efektivitas modul fisika berbasis masalah pada materi listrik dinamis untuk meningkatkan kemampuan berpikir kreatif siswa. Jenis penelitian ini adalah penelitian dan pengembangan (Research and Development) menggunakan model Borg and Gall (1983) dengan 10 tahapan, yaitu: 1) penelitian dan pengumpulan informasi, instrument yang digunakan berupa pedoman wawancara dan lembar angket kebutuhan, 2) perencanaan, instrument yang digunakan berupa matrik keterkaiatan PBM dengan berpikir kreatif, 3) pengembangan produk awal, instrument yang digunakan berupa draf modul, silabus, RPP, kisi angket validasi, kisi angket keterbacaan, kisi angket respon, kisi soal tes berpikir kreatif, dan kisi angket penyebaran, 4) uji coba produk awal, instrument yang digunakan berupa lembar validasi, 5) revisi produk pertama, instrument yang digunakan berupa draf modul, 6) uji coba lapangan terbatas, instrument yang digunakan berupa lembar angket keterbacaan, 7) revisi produk kedua, instrument yang digunakan berupa LKS siswa, 8) uji lapangan operasional, instrument yang digunakan berupa soal tes uraian, lembar observasi, dan lembar angket respon siswa, 9) revisi produk akhir, instrument yang digunakan berupa LKS siswa, 10) diseminasi dan implementasi, instrument yang digunakan berupa lembar angket respon guru. Teknik analisis data yang digunakan yaitu analisis deskriptif, analisis kelayakan modul berdasarkan skor kriteria, dan analisis tes kemampuan berpikir kreatif melalui uji Paired T-Test dan dihitung menggunakan N-Gain ternormalisasi. Sampel penelitian dan pengembangan meliputi: 1) validator ahli (materi, media, dan bahasa) dan  praktisi pendidikan (2 guru fisika), 2) sampel uji coba lapangan terbatas sejumlah 12 siswa kelas XD, 3) sampel uji coba lapangan operasional sejumlah 24 siswa kelas XA. Hasil penelitian ini adalah: 1) karakteristik modul fisika, dikembangkan dengan berbasis masalah pada materi listrik dinamis untuk meningkatkan kemampuan berpikir kreatif. Tahapan pembelajaran berbasis masalah yang dimunculkan sebagai kerangka dalam modul meliputi: (1) mengorientasi siswa kepada masalah, (2) mengorganisasikan siswa untuk belajar, (3) membimbing penyelidikan individual maupun kelompok, (4) mengembangkan dan menyajikan hasil karya, (5) menganalisis dan mengevaluasi proses pemecahan masalah, 2) modul dikategorikan layak dengan skor rata-rata 3,62, 3) modul fisika berbasis masalah pada materi listrik dinamis efektif untuk meningkatkan kemampuan berpikir kreatif siswa pada kategori sedang dengan N-Gain sebesar 0,52.
Intercalation and calcination as methods to reduce expansive soil properties
Authors: Wiratama Ristiya Adi , Hanudin Eko , Purwanto Benito Heru
Published: July 2021

The expansive ability of soil causes a series of problems in various sectors. The dominance of smectite clay minerals significantly affects expansive ability because they have an unstable interlayer structure. Cation intercalation and calcination is a treatment method that can increase the stability of the clay interlayer structure. This research investigated the effects of intercalation cations and calcination treatment on the swelling ability and cracking properties in the clay from vertisols; the cations used for intercalation were aluminum and iron. The intercalation tested doses were based on the equivalent weight of 0x, 0.5x, and 1x cation exchange capacity (CEC) clay value. The calcination treatments used were 200°C, 300°C, and no calcination. Each treatment interaction was repeated three times. Parameters observed were the total area, average crack width, average lump area, total number of lumps, moisture content, swelling volume, and pH after treatment. The results showed that each treatment had a significant effect. Clay with an Al intercalation dose of 1x CEC without calcination treatment had the highest total area after drying, which was 41.035 cm2; the lowest average crack width was 0.153 cm, and the smallest swelling volume was 3.6 cm3. In contrast, the clay without intercalation and calcination treatments had a swelling volume up to 10 cm3 on the 7th day. The clay with an Al intercalation dose of 1x CEC with 200°C calcination exhibited the best results in reducing the expansive clay ability and can be used as a guideline for further testing to reduce the soil’s expansive ability.
Comparative performance of multiple linear regression and artificial neural network models in estimating solute-transport parameters
Authors: Mojid Mohammad Abdul , Hossain A.B.M. Zahid
Published: July 2021

Indirect estimate of solute-transport parameters through pedo-transfer functions (PTFs) is becoming important due to expensive and time-consuming direct measurement of the parameters for a large number of soils and solutes. This study evaluated the relative performance of PTFs of multiple linear regression (MLR) and Artificial Neural Network (ANN) models in predicting velocity (V), dispersion coefficient (D) and retardation factor (R) of CaCl2, NaAsO2, Cd(NO3)2, Pb(NO3)2 and C9H9N3O2 (carbendazim) in five agricultural soils. V, D and R of the solutes were determined in repacked soil columns under steady-state unsaturated water flow conditions. Textural class, particle size distribution, bulk density, organic carbon, relative pH, clay%, grain size, and uniformity coefficient of the soils were determined. MLR and ANN models were calibrated with the measured data of four soils and verified for another soil. Root-Mean Square Error (RMSE) is significantly smaller (0.015) and modelling efficiency (EF) is significantly larger (0.999) for ANN model than those (0.096 and 0.954, respectively) for MLR model. Negative Mean Absolute Error (MAE) (-0.0002) of MLR model indicates overestimation, while positive MAE (0.00003) of ANN model indicates minimal underestimation. The ANN model is less biased than the MLR model during prediction. Thus, the ANN model can significantly enhance pollution transport prediction through soils with good accuracy.
The relationship between the normalized difference vegetation index, rainfall, and potential evapotranspiration in a banana plantation of Venezuela
Authors: Olivares Campos Barlin Orlando , Paredes Franklin , Rey Juan Carlos , Lobo Deyanira , Galvis-Causil Stephanie
Published: July 2021

The water supply for rainfed crops such as bananas in the Aragua state of Venezuela is often uncertain, particularly towards the beginning of the rainy season (April-May). Where climatic conditions are seasonal, the temporal evolution of the NDVI (Normalized Difference Vegetation Index) closely accompanies the interannual variation of vegetation growth in response to thermal and hydric factors. The aim of the study is to assess the relationship between NDVI, rainfall and potential evapotranspiration during the period of January/2016 to December/2017 in a Venezuelan banana plantation. In this study, the NDVI derived from the GIMMS MODIS Terra product, the daily accumulated precipitation data (mm) and the daily mean air temperature (°C) were used as the only way to estimate the potential evapotranspiration. The results showed that the GMOD09Q1-based NDVI reflects reasonably well the spatiotemporal variation in biomass accumulation. Besides, this provides information on the water stress conditions in banana plants at the plot level. The influence of Precipitation and potential evapotranspiration on the NDVI was more evident when a lag of 1 month was considered in terms of the Spearman r, implying that there is a delay in the banana phonological response to rainfall changes and dryness conditions.  However, due to its low spatial resolution (i.e. 250 m), it is not adequate for the identiﬁcation of banana wilt disease. Therefore, future studies are needed to assess other satellite-derived spectral indices for monitoring the health of banana plants over different sites in Venezuela.
DECISION SUPPORT SYSTEM FOR DETERMINING THE OPTIMAL COMPOSITION OF THE TEAM OF PERFORMERS ON THE EXAMPLE OF THE SPORTS VERSION OF THE GAME “WHAT? WHERE? WHEN?"
Authors: Melnykov Oleksandr
Published: July 2021

The paper describes the task to create a decision support system that allows you to determine the optimal composition of the team of performers. The sports version of the game “What? Where? When?" is chosen. The principles of holding tournaments on the intellectual game “What? Where? When?" and the rules for the formation of teams to participate in such competitions. It is concluded that to predict the impact of changes in the team composition on the result, it is advisable to use modern mathematical and intellectual methods, including the method of artificial neural networks. The available data on the results of synchronous tournaments LUK (ST) since 2011 and city tournaments (GT) since 2017 are presented, the main indicators for each competition are characterized. The introduction of the output factors is substantiated: the ratio of the team’s result to the average result and the ratio of the team’s result to the winner’s result. The forecasting problem is formulated as a prediction of the relative result of a team on a specific game based on the available list of team players for this game. It is proposed to take into account the location of a particular game, and fix the participation of players in the form of a “share” of the contribution to the team’s result, while the sum of the “shares” of all players should be equal to one. A method of artificial neural networks with a two-layer perceptron architecture, a sigmoid activation function and an error propagation algorithm for training a network is proposed. Examples of calculation in the Deductor Studio Lite environment are given. It is concluded that for the practical application of the model, the constant use of standard packages is inapplicable. In addition, it is also necessary to solve the problem of automating the selection of the team composition. Described is an application developed in a visual programming environment – a decision support system that allows you to import source data from an XLS file, configure input and output factors, change the architecture of the neural network (the number of hidden layers and the number of neurons in each layer), train the neural network using the backpropagation of errors, save the trained network on disk and load it again, calculate values for the input data, search for options for the composition of the team. The developed decision support system makes it possible to give recommendations on the formation of a team for a specific tournament by enumerating options.

Keywords: intellectual games, questions package, team building, forecasting, artificial neural network, perceptron, sigmoid, network training.
MODELLING SEMANTIC KERNEL OF WEB RESOURCE
Authors: Orekhov Sergey , Malyhon Hennadiy
Published: July 2021

The article presents an attempt to describe mathematically the effect of the semantic kernel of a web resource on the Internet. In accordance with the theory of marketing, the product that we want to sell on the network is characterized by the following basic properties: price, time and place. In other words, a potential buyer wants to receive a given product in the right place at a given time. To satisfy this need, it is necessary to use the classic component of marketing, product promotion. However, this component is now becoming a fully virtual instrument. This tool functions in a hypertext, video and image environment. Therefore, the user analyzes the meaning of these elements in order to get the desired product. The results of web projects carried out in this area indicate the emergence of a new phenomenon, which reflects the main meaning of virtual promotion – this is the semantic core. The core is a short annotation of the main properties of the product, its location and time of appearance. Therefore, the purpose of this article is both a presentation of a new object of research and a mathematical description. It is assumed that the semantic core is formed on the basis of natural language terms. In other words, the semantic core is a set of keywords that are grouped by meaning. We propose to use data mining approaches for clustering to group terms. The classic clustering method at the moment is k-means. The article presents a model of the semantic core based on this method. This method and its distance function are considered as the second stage of web content processing. At the first stage, web content is converted into a semantic web. However, the k-means technique has significant drawbacks when modeling the semantic core. Therefore, in the development of this idea, the work shows an alternative way to modeling the kernel. As an alternative approach, the construction of clusters based on the concept of maximum flow is considered. This approach has the significant advantage that the type of links in the semantic network overlaps with the type of distance function in this method. As a result, on a real web project, the effect of the connection between the semantic core model and the level of new users of the web resource was demonstrated over the past five years.

Keywords: semantic kernel, keyword, k-means, max flow.
SIMULATION OF THERMAL PROCESSES OF A NPP STEAM GENERETOR FOR INFORMATION TECHNOLOGY OPTIMIZED CONTROL
Authors: Nikulina Olena , Severyn Valerii , Kotsiuba Nina , Bubnov Anton
Published: July 2021

Mathematical models of thermal processes in the form of Cauchy in the state space with relative variables of the steam generator PGV-1000 of the power unit of a nuclear power plant with a nuclear reactor VVER-1000 have been developed for the using of models in information technology for optimizing the control of a steam generator. The working thermal processes in the PGV-1000 steam generator associated with the supply of feed water to it from the water treatment system and the coolant from the nuclear reactor and the removal of vapors to the main steam header are considered. The design diagram of the steam generator is presented, which reflects the working processes in it under the evaporation mirror and above it. On the basis of differential equations of the heat balance of the heat carrier in the steam generator and in the metal heat exchange tubes, the simulation of heat transfer from the heat carrier to the feed water in the steam generator is carried out. The heat transfer model in the form of a linear system of differential equations in relative state variables is developed. The processes of vaporization during heating of feed water by the heat transfer surface are considered. Differential equations of material and heat balances of dynamic processes of vaporization in a steam generator are compiled, which are not equations in the Cauchy form. Transformations of the differential equations of material and heat balances in the steam generator to the Cauchy form are carried out. A nonlinear system of differential equations for the balance of vaporization in relative state variables is obtained. The values of the constant parameters of the models for the steam generator PGV-1000 are calculated. The mathematical model of thermal processes in the PGV-1000 steam generator, which is presented in the form of a system of differential equations and includes the processes of heat transfer and steam generation, will make it possible to identify and optimize the steam generator control system with the help of information optimization technology.

Keywords: nuclear power plant, steam generator, thermal processes, mathematical model, differential equations, optimization, control, information technology.
Fenomena Natural Resource Curse dalam Pembangunan Wilayah di Indonesia
Authors: Rahma Hania , Fauzi Akhmad , Juanda Bambang , Widjojanto Bambang
Published: July 2021

Although the phenomenon of natural resource curse is suspected to have occurred at the regional level in  Indonesia, no measurement of such a phenomenon has been carried out yet. This research is aimed to provide an index of measuring the degree of natural resource curse at provincial level in Indonesia. Two indices, the natural resource dependence index and regional sustainable development index, were used to formulate index of regional resource curse (RRCI) using geometric mean of conditional weighted product method. The results found that provinces with richer in mining tend to have higher resource curse index compared with those with less extractive resources. ------------------------------------------ Meski fenomena natural resource curse diduga terjadi di tingkat daerah di Indonesia, pengukuran terhadap fenomena tersebut belum pernah dilakukan. Penelitian ini bertujuan untuk mengukur besaran natural resource curse di tingkat provinsi di Indonesia. Dua indikator, yakni indeks ketergantungan sumber daya alam dan indeks pembangunan daerah berkelanjutan digunakan untuk menghitung regional resource curse index (RRCI) menggunakan rerata geometrik conditional weighted product method. Hasilnya menunjukkan bahwa provinsi dengan sumber daya alam tambang yang lebih kaya cenderung menghadapi fenomena resource curse yang lebih tinggi dibandingkan provinsi dengan sumber daya ekstraktif yang lebih sedikit.
Opioid Free Anesthesia to Prevent Post Operative Nausea/Vomiting
Authors: Acred Aleksander , Devineni Milena , Blake Lindsey
Published: July 2021

Purpose The purpose of this study is to compare the incidence of post-operative nausea and vomiting (PONV) in opioid-utilizing and opioid-free general anesthesia. Background PONV is an extremely common, potentially dangerous side effect of general anesthesia. PONV is caused by a collection of anesthetic and surgical interventions. Current practice to prevent PONV is to use 1-2 antiemetics during surgery, identify high risk patients and utilize tracheal intubation over laryngeal airways when indicated. Current research suggests minimizing the use of volatile anesthetics and opioids can reduce the incidence of PONV, but this does not reflect current practice. Methods In this scoping review, the MeSH search terms used to collect data were “anesthesia”, “postoperative nausea and vomiting”, “morbidity”, “retrospective studies”, “anesthesia, general”, “analgesics, opioid”, “pain postoperative”, “pain management” and “anesthesia, intravenous”. The Discovery Search engine, AccessMedicine and UpToDate were the search engines used to research this data. Filters were applied to these searches to ensure all the literature was peer-reviewed, full-text and preferably from academic journals. Results Opioid free anesthesia was found to decrease PONV by 69%. PONV incidence was overwhelming decreased with opioid free anesthesia in every study that was reviewed. Implications The future direction of opioid-free anesthesia and PONV prevention are broad topics to discuss, due to the nature of anesthesia. Administration of TIVA, esmolol and ketamine, as well as the decision to withhold opioids, are solely up to the anesthesia provider’s discretion. Increasing research and education in the importance of opioid-free anesthesia to decrease the incidence of PONV will be necessary to ensure anesthesia providers choose this protocol in their practice.
Analysis of The Influence of Islamic Income Ratio, Total Comprehensive Income, and NPF on Company Value with Profitability as Moderating Variables in Sharia Commercial Banks in Indonesia 2015-2019
Authors: Saidah Alfi , Bawono Anton
Published: July 2021

Economic Value Added is an approach to assessing company performance, with the aim that the company's ability to create added value can influence investors who will invest in the company. The concept used in this approach is to pay attention to the funders in terms of expectations, interests, and degrees of justice as measured by weighted measures and the existing initial capital structure. The population in this study are Islamic Commercial Banks registered with the Financial Services Authority, totaling 11 Islamic Banks. In selecting the sample the method used is purposive sampling with the criteria that the author has set. The collection method in this study was carried out by looking at the annual financial statements of each Islamic bank registered with the Financial Services Authority. Based on the results of the moderation regression test, the results showed that IIR, TCI, NPF had no significant positive effect on EVA. ROA is not able to moderate IIR against EVA. ROA is not able to moderate TCI against EVA. ROA is not able to moderate NPF against EVA.
Bridging the gap between markers’ tacit knowledge and students’ assessment literacy
Authors: Mansi Gemma
Published: July 2021

There has been an increasing emphasis within higher education on the need for explicit articulation of assessment standards and requirements and for these to be communicated effectively to students (O’Donovan et al., 2004; Sadler, 2010; Bloxham et al., 2011; McGrath et al., 2019). However, in practice, this can be difficult to achieve, depending, firstly, on markers’ abilities to effectively articulate their tacit knowledge and expectations and, secondly, on the knowledge and understanding of assessments that students bring with them into their degree. This student ability often depends on their previous varied educational experiences. Both students and staff may therefore find this a matter of challenge and frustration.This case study is based on discussions with students on the Childhood and Youth Studies (Extended) programme at the University of Greenwich and with staff across the University, as well as on the researcher’s personal reflections on the findings. It highlights: how important it is for staff to work in partnership with students early on in their studies, so as to develop their understanding of assessment language and the standards expected; how staff consider the experiences students have had with assessment and academic writing; and how they draw implications for assessment practices in their teaching context. Furthermore, the study aims to provide innovative recommendations for how markers can develop a continuing, meaningful dialogue with students, to enable them to build an understanding of their markers’ tacit knowledge about assessment and feedback in their discipline.
Editorial Team 14, 2
Authors: Keyms Gillian
Published: July 2021

.
Introduction to volume 14, issue 2 of Compass, Journal of Learning & Teaching
Authors: George Rachel , Yang Yang
Published: July 2021

.
Training Image Optimization Method Based on Convolutional Neural Network and Its Application in Discrete Fracture Network Model Selection
Authors: Yu Siyu , Li Shaohua
Published: July 2021

Training image (TI) is important for multipoint statistics simulation method (MPS), since it captures the spatial geological pattern of target reservoir to be modeled. Generally, one optimal TI is selected before applying MPS by evaluating the similarities between many TIs and the well interpretations of target reservoir. In this paper, we propose a new training image optimization approach based on the convolutional neural network (CNN). First, candidate TIs were randomly sampled several times to obtain the sample dataset. Then, the CNN was used to conduct transfer learning for all samples, and finally, the optimal TI of the conditioning well data is selected through the trained CNN model. By taking advantage of the strong learning ability of CNN in image feature recognition, the proposed method can automatically identify differences in spatial features between the conditioning well data and the samples of the training image. Hence, it effectively resolves the difficulty of spatial matching between discrete datapoints and grid structures. We demonstrated the applicability of our model via 2D and 3D training image selection examples. The proposed methods effectively selected the appropriate TI, and then the pretreatment techniques for improving the accuracy of continuous TI selection were achieved. Moreover, the proposed method was successfully applied to training image selection of a discrete fracture network model. Finally, sensitivity analysis was carried out to show that sufficient conditioning data volume can reduce the uncertainty of the optimization results. By comparing with the improved MDevD method, the advantages of the new method are verified in terms of efficiency and reliability.
Artificial Intelligence Coreflooding Simulator for Special Core Data Analysis
Authors: Mathew Eric Sonny , Tembely Moussa , AlAmeri Waleed , Al-Shalabi Emad W. , Shaik Abdul Ravoof
Published: July 2021

Two of the most critical properties for multiphase flow in a reservoir are relative permeability (Kr) and capillary pressure (Pc). To determine these parameters, careful interpretation of coreflooding and centrifuge experiments is necessary. In this work, a machine learning (ML) technique was incorporated to assist in the determination of these parameters quickly and synchronously for steady-state drainage coreflooding experiments. A state-of-the-art framework was developed in which a large database of Kr and Pc curves was generated based on existing mathematical models. This database was used to perform thousands of coreflood simulation runs representing oil-water drainage steady-state experiments. The results obtained from the corefloods including pressure drop and water saturation profile, along with other conventional core analysis data, were fed as features into the ML model. The entire data set was split into 70% for training, 15% for validation, and the remaining 15% for the blind testing of the model. The 70% of the data set for training teaches the model to capture fluid flow behavior inside the core, and then 15% of the data set was used to validate the trained model and to optimize the hyperparameters of the ML algorithm. The remaining 15% of the data set was used for testing the model and assessing the model performance scores. In addition, K-fold split technique was used to split the 15% testing data set to provide an unbiased estimate of the final model performance. The trained/tested model was thereby used to estimate Kr and Pc curves based on available experimental results.

The values of the coefficient of determination (R2) were used to assess the accuracy and efficiency of the developed model. The respective crossplots indicate that the model is capable of making accurate predictions with an error percentage of less than 2% on history matching experimental data. This implies that the artificial-intelligence- (AI-) based model is capable of determining Kr and Pc curves. The present work could be an alternative approach to existing methods for interpreting Kr and Pc curves. In addition, the ML model can be adapted to produce results that include multiple options for Kr and Pc curves from which the best solution can be determined using engineering judgment. This is unlike solutions from some of the existing commercial codes, which usually provide only a single solution. The model currently focuses on the prediction of Kr and Pc curves for drainage steady-state experiments; however, the work can be extended to capture the imbibition cycle as well.
For a Decade of Hope Not Austerity in the Middle East and North Africa: Towards a fair and inclusive recovery to fight inequality
Authors: Abdo Nabil , Almasri Shaddin
Published: July 2021

Even before the coronavirus crisis struck, people in the Middle East and North Africa were protesting against the injustice and inequality wrought by a decade of austerity. The pandemic and the lockdown measures taken by governments have paralysed economies and threaten to tip millions of people into poverty, with women, refugees, migrant workers and those working in the informal economy among the worst affected. A huge increase in inequality is very likely. More austerity following this crisis will mean more uprisings, more inequality, and more conflict. This paper argues that if another decade of pain is to be averted, governments need to take immediate action to reduce inequality through providing public services to protect ordinary people by taxing the richest and guaranteeing decent work.
Research Ethics: A practical guide
Authors: Mager Franziska , Galandini Silvia
Published: July 2021

Any research must follow ethical principles, particularly when it involves people as participants and is likely to impact them. This is standard practice in academic research and a legal requirement in medical trials, but also applies to research carried out by Oxfam. Oxfam’s work focuses on vulnerable populations, and takes place under difficult circumstances. When research takes place in such vulnerable and fragile contexts, high ethical standards need to be met and tailored to the specific characteristics of each situation. Oxfam welcomes the adaptation of this guideline by other NGOs, community organizations and researchers working in fragile contexts and with vulnerable communities. The guideline should be read together with other relevant Oxfam and Oxfam GB policies and protocols, including the guidelines on Writing Terms of Reference for Research, Integrating Gender in Research Planning and Doing Research with Enumerators. A flowchart summarizing the guideline is also available to download on this page.
COVID-19 and Vulnerable, Hardworking Kenyans: Why it's time for a strong social protection plan
Authors: Gikandi Levi
Published: July 2021

Seven NGOs, the Kenyan government, the European Union and the Danish and German governments are working together to implement a ’Safety Nets’ programme targeting Kenya’s millions of informal workers. With rising food insecurity and sexual and gender-based-violence, mounting job losses, poor access to water and sanitation, and a lack of formal safety nets, the Kenyan informal sector has suffered the brunt of the COVID-19 pandemic. The Safety Nets programme has revealed that cash transfers which support the most vulnerable people, and are implemented safely, transparently and accountably, have the potential to help vulnerable households stave off starvation, infection and eviction. They can also help reduce the vulnerability of survivors and those at risk of sexual and gender-based violence. The results of this programme demonstrate that nascent Kenyan ‘social protection’ programmes should be 1) immediately extended and expanded to the many vulnerable Kenyans currently not enrolled in any social protection programme; and 2) strengthened long-term to make them more effective, sustainable and accountable.
Oxfam GB Statement on Modern Slavery for the financial year 2019/20
Authors: Brill Sophie , Wallace Beck
Published: July 2021

The UK Modern Slavery Act 2015 requires organizations with a turnover of over £36m to make a public statement on the steps they are taking to identify and prevent modern slavery in their operations and supply chains. Oxfam GB advocated for this legislation to be enacted. In this, our fifth statement, we share our progress against the three-year objectives set last year, which focus on corporate responsibility governance, human rights due diligence and inclusion of our country programmes. Due to the particularly devastating impacts of the coronavirus pandemic, we have added a section to highlight our initial response in March 2020, which fell under this reporting period.
Epidemiological study on COVID-19 virus transmission network in northeast China
Authors: Feng Tianyu , Sun Helin , Sun Mengzi , Wang Yudan , Zhang He , Sun Chong , Li Kexin , Wang Yingshuang , Chai Ruiyu , Zheng Pingping , Chen Yang , Pan Pan , Bi Chunli , Zhang Yulong , Yao Yan
Published: July 2021

Objective: to analyze the epidemic situation of COVID-19 in northeast China, Liaoning and Jilin. To study the prevalence of COVID-19 virus in areas other than Hubei province. To understand the spread of COVID-19 in Liaoning and Jilin provinces by means of communication network. More in-depth understanding of COVID-19 epidemic, and put forward effective prevention and control recommendations. Methods: We collected the demographic characteristics, exposure history and course of action of patients with laboratory-confirmed infection with COVID-19 published by Liaoning Provincial Health Commission and Jilin Provincial Health Commission as of February 15, 2020. We describe the demographic characteristics, case characteristics, spatial distribution characteristics and related interpersonal network of these patients. To analyze the transmission of COVID-19 in two provinces. Results: By February 15, 2020, the cumulative number of infected people in Liaoning province was 119.The largest number was 27(22.7%) in Shenyang and the smallest in Fushun, with no reported cases of infection. Among them, 55(46.2%) have a history of sojourning in Hubei province. The mainly clinical symptoms of the infected patients were fever, and 67(56.3%) of them developed fever at the time of diagnosis. Cough, sneezing and other respiratory symptoms are less. The cumulative number of infected people in Jilin province was 89, with the highest number in Changchun city at 39(43.8%) and the lowest in Baishan city, with no reported infections. 21(23.6%) people with a history of sojourning in Hubei province. Most of those infected in the two provinces were related to Hubei province, and most of those infected in the second generation or more were infected by close contact with relatives. Conclusion: The COVID-19 outbreaks in Liaoning and Jilin provinces are gradually stabilizing, but have not yet reached the time required to lower the prevention and control level. The fatality rate of the two provinces is relatively low. There is no evidence of super-spreader in either province.
A Comprehensive Bioinformatics Analysis of TIMP2 in Multiple Malignancies
Authors: Wang Dan-Dan , Xu Wen-Xiu , Chen Wen-Quan , Yang Su-Jin , Zhang Jian , Tang Jinhai
Published: July 2021

Background: Tissue inhibitor of metalloproteinase-2 (TIMP2), an endogenous inhibitor of matrix metalloproteinases, has been disclosed to participate in the development and carcinogenesis of multiple malignancies. However, the prognosis of TIMP2 in different cancers and its correlation with tumor microenvironment and immunity have not been clarified.Methods: In this study, we conducted a comprehensive bioinformatics analysis to evaluate the prognostic and therapeutic value of TIMP2 in cancer patients by utilizing a series of databases, including ONCOMINE, GEPIA, cBioPortal, GeneMANIA, Metascape, and Sangerbox online tool. The expression of TIMP2 in different cancers were analyzed by Oncomine, TCGA and GTEx databases and mutation status of TIMP2 in cancers was then verified using cBioportal database. The protein-protein interaction (PPI) network of the TIMP family was exhibited by GeneMANIA. The prognosis of TIMP2 in cancers was performed though GEPIA database and cox regression. Additionally, the correlations between TIMP2 expression and immunity (immune cells, gene markers of immune cells, TMB, MSI, and neoantigen) were explored using Sangerbox online tool.Results: The transcriptional level of TIMP2 in most cancerous tissues were significantly elevated. Survival analysis revealed that elevated expression of TIMP2 was associated with unfavorable survival outcome in multiple cancers. Enrichment analysis demonstrated the possible mechanisms of TIMPs and their associated genes mainly involved in pathways including extracellular matrix (ECM) regulators, degradation of ECM and ECM disassembly, and several other signaling pathways. Conclusions: Our findings systematically dissected that TIMP2 was a potential prognostic maker in various cancers and use the inhibitor of TIMP2 may be an effective strategy for cancer therapy to improve the poor cancer survival and prognostic accuracy, but concrete mechanisms need to be validated by subsequent experiments.