bluuebunny/crossref_metadata_2025 huggingface dataset:
Efecto de distintas concentraciones de mucílago de cacao (Theobroma cacao L.) y café (Coffea arabica) en la elaboración de una bebida energética
Authors: López-Narváez Sindy Paola , Guapi-Alava Gina Mariuxi , Guerrón-Troya Vicente Alberto , Revilla-Escobar Karol Yannela , Aldas-Morejon Jhonnatan Placido , Barzola-Miranda Sonnia Esther
Published: January 2024

El mucílago de cacao es un subproducto muy poco industrializado debido al desconocimiento de sus propiedades fisicoquímicas y a la carencia de innovación tecnológica para su manejo y transformación. Es por ello, que la presente investigación tuvo como objetivo evaluar el efecto de distintas concentraciones de mucílago de cacao y café en la elaboración de una bebida energética. Se utilizó un Diseño Completamente al Azar (D.C.A), evaluando 6 tratamientos con tres repeticiones, para determinar diferencias estadísticas se aplicó una prueba de significación Tukey (p<0.05). Las distintas concentraciones de mucílago de cacao y café influyeron significativamente en las características fisicoquímicas (pH, acidez titulable, °Brix, ceniza, humedad, proteína, densidad y carbohidratos) de la bebida, también, los tratamientos presentaron un alto contenido de energía (43,08kcal a 58,60kcal). En relación a las características sensoriales, el T5 = 20% pulpa de mucílago de cacao nacional y 1% de café, obtuvo una mayor aceptación por parte de los catadores con la categoría “me gusta mucho”, además, presentó un color ámbar, sabor y aroma con leves notas a cacao-café. Con esto, se concluye que el mucílago de cacao, puede ser una alternativa en el mercado de las bebidas energéticas.
Utilización de extracto natural del Muicle (Justicia spicigera) en la elaboración de chocolate a partir de dos variedades de cacao (Theobroma bicolor Humb. & Bonpl. y Theobroma cacao L.)
Authors: Alvarado-Vásquez Kerly Estefanía , Rivadeneira-Barcia Christian Simón , Intriago-Flor Frank Guillermo
Published: January 2024

Se propuso fomentar la incorporación del extracto natural del Muicle (Justicia spicigera) en la producción de chocolate, utilizando dos variedades de cacao: Theobroma bicolor Humb. & Bonpl y Theobroma cacao L. Para evaluar los efectos, se implementó un diseño estadístico completamente al azar con arreglo bifactorial, compuesto por 6 tratamientos y 3 repeticiones. Como factor A se evaluó dos tipos de Theobromas y factor B las concentraciones del extracto de Justicia Spicigera (0%, 3% y 6%). Se realizó la toma de las variables morfológicas para la comparación entre variedades, Theobroma bicolor Humb. & Bonpl presentó un peso de mazorca promedio de 969, mientras que Theobroma cacao L. tubo un promedio de 787 g. Durante la fermentación se tomó la temperatura inicial que fue de 21 - 48°C, pH inicial de 3,88 - 5,46 y °Brix 21- 6°Brix. La capacidad antioxidante se determinó mediante los métodos ABTS y DPPH, con valores de 239,83 y 176,49 µmol. Se requirió de 25 catadores semientrenados, se evaluó el aroma, intensidad, color y sabor. La adición del extracto de Justicia Spicigera mejoró significativamente las notas sensoriales y la aceptabilidad del chocolate.
Efecto del prebiótico Bio Optimize® sobre el bienestar animal y variables productivas de pollos de engorde
Authors:   Universidad Central de Venezuela, Facultad de Agronomía, Departamento de Producción Animal, Apartado postal 4579, Maracay, Venezuela, Chacón Zapata Elías , de Basilio Vasco ,   Universidad Central de Venezuela, Facultad de Agronomía, Departamento de Producción Animal, Apartado postal 4579, Maracay, Venezuela, Nuraef Hedy ,   TECNOAgua, Pampatar, estado Nueva Esparta, Venezuela
Published: January 2024

The objective was to evaluate the use of the BIO OPTIMIZE® prebiotic on indicator variables of well-being and production of Ross 308 hybrid broiler chickens. Three treatments were evaluated: 1.- Control without the inclusion of the prebiotic; 2.-Prebiotic applied in the litter from day 9 and from day 21 in the drinking water and 3.-Prebiotic only applied in the litter from day 9 of the birds' productive cycle. 144 chickens were used in a completely randomized design, with three treatments, six repetitions and the experimental unit consisting of eight chickens. The environmental temperature and relative humidity of the breeding units were monitored, in addition to the temperature of the bedding and drinking water. Body temperature, hyperventilation levels, ammonia levels in the litter, feed consumption and conversion, and weight gain of the chickens were quantified. The temperature and relative humidity were outside the comfort range; there was a direct relationship between the environmental temperature and the temperature of the drinking water, while the temperature of the bed increased during the evaluation period. The application of BioOptimize® to the litter from 28 days onwards reduced ammonia levels in the breeding units, reduced body temperature and increased hyperventilation levels in the chickens. The best feed conversion index was obtained in the treatment without prebiotic derived from an inverse behavior in feed consumption.
IMPLEMENTASI SISTEM INFORMASI PENGELOLAAN BARANG INVENTARIS MILIK NEGARA STUDI KASUS BALAI DIKLAT KEAGAMAAN MEDAN
Authors: Monica Situmeang  , Alif Fahrezy M , Shella Fahdilla Sari  , Aidil Halim Lubis
Published: January 2024

Dalam era ini Teknologi memegang peranan sangat penting dalam meningkatkan efisiensi kegiatan pemerintahan. Barang Milik Negara (BMN) merupakan aset yang wajib dipertanggungjawabkan oleh penguasa yang memilikinya. Kajian BMN Medan mengangkat persoalan barang milik negara yang diangkut dari ruangan ke ruangan tanpa sepengetahuan pengelola, sehingga berdampak pada pengelolaan barang tanpa memperhatikan data sebenarnya di lapangan. Tujuan dari penelitian ini adalah mengimplementasikan sistem informasi SIMA agar pendataan angkutan barang  lebih efektif. Metode deskriptif kualitatif  digunakan untuk membantu pengguna sistem informasi SIMAN Pusdiklat Keagamaan Medan agar lebih memahami sistem informasi tersebut. Penelusuran menemukan bahwa sistem informasi tidak efektif dalam pengelolaan barang milik negara di Pusdiklat Keagamaan Medan  karena kurangnya pelatihan ulang dalam penggunaan sistem informasi dan kurangnya kewenangan sebelumnya dalam mengelola barang tersebut. Oleh karena itu, pemahaman penggunaan sistem informasi SIMA berdampak signifikan terhadap efektivitas pengelolaan properti nasional.
Assessing the Solar Activity and Geomagnetic Disturbance during Minimum Phase of Solar Cycle 24 across the Globe.
Authors: Segara Ajose Anthony , Olanrewaju Kayode Yusuf , Jude Alomaja Adegoke
Published: January 2024

Understanding solar activity and its implications on the Earth’s environment has become necessary. Most importantly, events that characterized the minimum phase of solar cycle 24 (2019) and geomagnetic disturbance experienced during this period calls for an assessment. To assess this, the study has therefore used INTERMAGNET data from geomagnetic stations across the globe during the solar minimum year of solar cycle 24. A total of nine geomagnetic stations data of five disturbed days in a month were used, and were averaged in a minute interval for year 2019. The stations were selected with reference to their geomagnetic locations (latitudes and longitudes) as well as analyzing their horizontal magnetic field (H-Component) from the X and Y component of the geomagnetic field to reveal the variance in the global pattern of solar variations. The seasonal variations were studied across various latitudes and longitudes to understand the impact of solar activities on the earth surface as a result of geomagnetic field disturbance on Earth’s magnetosphere at the end of cycle 24 (2019). The results of stations revealed ABK and DRV with 350nT and 150nT of H component respectively which are the highest while other stations have 60nT below. This study shows that low geomagnetic disturbance was witnessed during the end of the cycle due to the minimum solar activity which was as a result of low number of sunspot during this period.
Evaluation de l’intéret des technologies de l’information et de la communication éducatives dans l’apprentissage par les étudiants en Médecine Dentaire
Authors: Ines AZOUZI , Kallela Rim , Ouertani Hend , Gassara Yosra , Nouira Zohra , Belhssan Harzallah , Cherif Mounir , Khattech Mohamed Bassem
Published: January 2024

Objective- Evaluate the interest of the use of Information and Educational Technologies in the initial training of dental medicine students at the faculty of dental medicine of Monastir. Methods- This was a descriptive study conducted at the FDMM in 2022. Data was collected through a questionnaire. It was composed of four parts and posted beteween May 1st and June 30th, 2022. Results- Of the 253 interns, 208 responded and 177 responsers were retained. The survey participants were connected to the internet almost all the time but 26.1% spent less than 30 minutes a day on their studies, mainly to access online courses or conduct literature research. The principle search engine were Google (93.8%) and Wikipedia (48%); Facebook was the principal social media (91%) used during learning. Almost half of the internal trainees were familiar with e-learning platforms although 72% of them had no previous experience. They preferred online courses to lectures (68.4 %) in order to consult the course at any time. More than 90% of respondents were unaware of MOOCs (Massive Open Online Courses). Conclusion- This study demonstrated the importance of the introduction of the Information and Educational Technologies in the university curriculum.
Evaluation des pratiques des personnels de santé tunisiens face aux traumatismes dentaires liés à l’intubation orotrachéale à propos d’une étude transversale
Authors: Mabrouk Yosra , Bekri Sana , Labidi Amel , Grayaa Amal , Benyoussef Souha
Published: January 2024

Objective- Evaluate the interest of the use of Information and Educational Technologies in the initial training of dental medicine students at the faculty of dental medicine of Monastir. Methods- This was a descriptive study conducted at the FDMM in 2022. Data was collected through a questionnaire. It was composed of four parts and posted beteween May 1st and June 30th, 2022. Results- Of the 253 interns, 208 responded and 177 responsers were retained. The survey participants were connected to the internet almost all the time but 26.1% spent less than 30 minutes a day on their studies, mainly to access online courses or conduct literature research. The principle search engine were Google (93.8%) and Wikipedia (48%); Facebook was the principal social media (91%) used during learning. Almost half of the internal trainees were familiar with e-learning platforms although 72% of them had no previous experience. They preferred online courses to lectures (68.4 %) in order to consult the course at any time. More than 90% of respondents were unaware of MOOCs (Massive Open Online Courses).
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Authors: Hünerbein Anja , Bley Sebastian , Deneke Hartwig , Meirink Jan Fokke , van Zadelhoff Gerd-Jan , Walther Andi
Published: January 2024

Abstract. The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) is the first mission that will provide measurements from active profiling, passive imaging and a broadband radiometer from a single satellite platform. The passive multi-spectral imager (MSI) features four solar and three thermal infrared channels, and has a swath of 150 km and a spatial pixel resolution of 500 m. The MSI observations will provide across-track information on clouds and aerosol to extend the active profiling information into the swath. In this paper, we present the algorithm used for retrieving the cloud optical and physical products (M-COP), specifically cloud optical thickness, effective radius and top height. The algorithm is based on the solar and terrestrial MSI channels within an optimal estimation framework. This framework enables full error propagation given by the uncertainties in measurements and a priori information. The MSI cloud algorithm has been successfully exercised on different imagers and on synthetically generated MSI observations.
Absolute radiance calibration in the UV and visible spectral range using atmospheric observations during twilight
Authors: Wagner Thomas , Puķīte Jānis
Published: January 2024

Abstract. We present an improved radiance calibration method for UV–Vis spectroscopic instruments with a narrow field of view (up to a few degrees) based on the calibration method by Wagner et al. (2015). The updated method uses only measurements during the twilight period instead of several hours as for the original method. The calibration is based on the comparison of measurements and simulations of the radiance of zenith-scattered sunlight. The main advantage of our method compared to radiance calibration methods in the laboratory is that the calibration can be directly applied in the field. This allows routine radiance calibrations whenever the sky is clear during twilight. The calibration can also be performed retrospectively and will thus be applicable for the large number of existing data sets. Also, potential changes in the instrument properties during transport from the laboratory to the field are avoided. The new version of the calibration method presented here has two main advantages. First, the required measurement period can be rather short (only a few minutes during twilight for cloud-free conditions). Second, even without knowledge of the aerosol optical depth (AOD), the errors in the calibration method are rather small, especially in the UV spectral range where they range from about 4 % at 340 nm to 8 % at 420 nm. If the AOD is known, the uncertainties are even smaller (about 3 % at 340 nm to 4 % at 420 nm). For visible wavelengths, good accuracy is only obtained if the AOD is approximately known with uncertainties from about 4 % at 420 nm to 10 % between about 550 and 700 nm (generally the AOD is nevertheless smaller in the visible than in the UV spectral range). One shortcoming of the method is that it is not possible to determine the AOD exactly at the time of the (twilight) measurements because AOD observations from sun photometer measurements or the MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) measurements are usually not meaningful for such high solar zenith angle (SZA). But the related uncertainty can be minimised by repeating the radiance calibrations during the twilight periods of several days.
Coupling numerical models of deltaic wetlands with AirSWOT, UAVSAR, and AVIRIS-NG remote sensing data
Authors: Cortese Luca , Donatelli Carmine , Zhang Xiaohe , Nghiem Justin A. , Simard Marc , Jones Cathleen E. , Denbina Michael , Fichot Cédric G. , Harringmeyer Joshua P. , Fagherazzi Sergio
Published: January 2024

Abstract. Coastal marsh survival relies on the ability to increase elevation and offset sea level rise. It is therefore important to realistically model sediment fluxes between marshes, tidal channels, and bays as sediment availability controls accretion. Traditionally, numerical models have been calibrated and validated using in situ measurements at a few locations within the domain of interest. These datasets typically provide temporal information but lack spatial variability. This paper explores the potential of coupling numerical models with high-resolution remote sensing imagery. Products from three sensors from the NASA Delta-X airborne mission are used. Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provides vertical water level change on the marshland and was used to adjust the bathymetry and calibrate water fluxes over the marsh. AirSWOT yields water surface elevation within bays, lakes, and channels, and was used to calibrate the Chezy bottom friction coefficient. Finally, imagery from AVIRIS-NG provides maps of total suspended solids (TSS) concentration that were used to calibrate sediment parameters of settling velocity and critical shear stress for erosion. Three numerical models were developed at different locations along coastal Louisiana using Delft3D. The coupling enabled a spatial evaluation of model performance that was not possible using simple point measurements. Overall, the study shows that calibration of numerical models and their general performance will greatly benefit from remote sensing.
A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study
Authors: Rutherford Krysten , Bianucci Laura , Floyd William
Published: January 2024

Abstract. High-resolution numerical ocean models can be used to help interpret sparse observations in the nearshore as well as to help understand the impacts of climate change and extreme events on these dynamically complex coastal areas. However, these high-resolution ocean models require inputs with comparably high resolution, which is particularly difficult to achieve for freshwater discharge. Here, we explored a simple rain-based hydrological model as inputs into a high-resolution (≳13 m) model of Quatsino Sound – a fjord system located on the northwest coast of Vancouver Island, British Columbia, Canada. Through a series of sensitivity tests using an application of the Finite Volume Community Ocean Model (FVCOM version 4.1), we found that model performance was hindered by the lack of knowledge of ungauged rivers and streams. In this case study, including the only major gauged river implied ignoring 538 other watersheds of various sizes and accounted for only about a quarter of the total estimated freshwater discharge. We found that including at least 60 % and ideally closer to 75–80 % of total freshwater fluxes gave similar model performance to including all possible 539 freshwater sources; in our model simulations, this percentage of freshwater flux meant including rivers with watersheds greater than 20–50 km2, or 7–19 total rivers. Further sensitivity tests also indicated that knowing the main outpour locations into the nearshore ocean is an important factor, but not as important as the total freshwater discharge included. Overall, this study illustrates the complexities of studying the land-ocean connection and offers a simple and accessible tool to help address a common problem in nearshore modelling.
Monitoring European anthropogenic NOx emissions from space
Authors: van der A Ronald Johannes , Ding Jieying , Eskes Henk
Published: January 2024

Abstract. Since the launch of TROPOMI on the S5p satellite, NO2 observations have become available with a resolution of 3.5x5 km, which makes monitoring NOx emissions possible at the scale of city districts and industrial facilities. For Europe, emissions are reported on an annual basis for country totals and large industrial facilities and made publicly available via the European Environmental Agency (EEA). Satellite observations can provide independent and more timely information on NOx emissions. A new version of the inversion algorithm DECSO (Daily Emissions Constraint by Satellite Observations) has been developed for deriving NOx emissions for Europe on a daily basis, averaged to monthly mean maps. The estimated precision of these monthly emissions is about 25 % for individual grid cells. These satellite-derived emissions from DECSO have been compared to the officially reported European emissions and spatial-temporal disaggregated emission inventories. The country total DECSO NOx emissions are close to the reported emissions and the emissions compiled by the Copernicus Atmospheric Monitoring Service (CAMS). The comparison of the spatial distributed NOx emissions of DECSO and CAMS showed that the satellite-derived emissions are often higher in cities, while similar for large power plants and slightly lower in rural areas.
Future prediction of Siberian wildfire and aerosol emissions via the improved fire module of the spatially explicit individual-based dynamic global vegetation model
Authors: Nurrohman Reza Kusuma , Kato Tomomichi , Ninomiya Hideki , Végh Lea , Delbart Nicolas , Miyauchi Tatsuya , Sato Hisashi , Shiraishi Tomohiro , Hirata Ryuichi
Published: January 2024

Abstract. Fires are among the most influential disturbances affecting ecosystem structure and biogeochemical cycles in Siberia. Therefore, precise fire modeling via dynamic global vegetation models is important for predicting greenhouse gas emissions and other burning biomass emissions to understand changes in biogeochemical cycles. In this study, we integrated the widely used SPread and InTensity of FIRE (SPITFIRE) fire module into the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM) to improve the accuracy of fire predictions and then simulated future fire regimes to better understand their impacts. Under the Representative Concentration Pathways 8.5 climate scenario, we estimated that the CO2, CO, PM2.5, total particulate matter (TPM), and total particulate carbon (TPC) emissions in Siberia will continue to increase annually until 2100 by an average of 214.4, 17.16, 2.8, 2.1, and 1.47 Gg species year-1, respectively. Under the same scenario and period, 185 trees ha-1 year-1 are estimated to be killed by wildfires, resulting in a 319.3 g C m-2 year-1 loss of net primary production (NPP). These findings show that Siberia faces an increasing frequency of extreme fire events due to changing climate conditions. Our study offers insights into future fire regimes and provides helpful information for development strategies for enhancing regional resilience and for mitigating the broader environmental consequences of heightened fire activity in Siberia.
First comprehensive assessment of industrial era land heat uptake from multiple sources
Authors: García-Pereira Félix , González-Rouco Jesús Fidel , Melo-Aguilar Camilo , Steinert Norman Julius , García-Bustamante Elena , de Vrese Philip , Jungclaus Johann , Lorenz Stephan , Hagemann Stefan , Cuesta-Valero Francisco José , García-García Almudena , Beltrami Hugo
Published: January 2024

Abstract. The anthropogenically-intensified greenhouse effect has caused a radiative imbalance at the top of the atmosphere during the industrial period. This, in turn, has led to an energy surplus in various components of the Earth system, with the ocean storing the largest part. The land contribution ranks second with the latest observational estimates based on borehole temperature profiles, which quantify the terrestrial energy surplus to be 6 % in the last five decades, whereas studies based on state-of-the-art climate models scale it down to 2 %. This underestimation stems from land surface models (LSMs) having a too shallow subsurface, which severely constrains the land heat uptake simulated by Earth System Models (ESMs). A forced simulation of the last 2000 years with the Max Planck Institute ESM (MPI-ESM) using a deep LSM captures 4 times more heat than the standard shallow MPI-ESM simulations in the historical period, well above the estimates provided by other ESMs. However, deepening the LSM does not remarkably affect the simulated surface temperature. It is shown that the heat stored during the historical period by an ESM using a deep LSM component can be accurately estimated by considering the surface temperatures simulated by the ESM using a shallow LSM and propagating them with a standalone forward model. This result is used to derive estimates of land heat uptake using all available observational datasets, reanalysis products, and state-of-the-art ESM experiments. This approach yields values of 10.5–16.0 ZJ for 1971–2018, slightly smaller than the latest borehole-based estimates (18.2 ZJ).
Flood simulation with the RiverCure approach: the open dataset of the 2016 Águeda flood event
Authors: Ricardo Ana M. , Ferreira Rui M. L. , Rodrigues da Silva Alberto , Estima Jacinto , Marques Jorge , Gamito Ivo , Serra Alexandre
Published: January 2024

Abstract. Floods are among the most common natural disasters responsible for severe damages and human losses. Numerically produced data, managed by user-friendly tools for geographically referenced data, have been adopted to increase preparedness and reduce vulnerabilities. This paper describes the locally sensed and numerically produced data that characterize a flood event that occurred in February 2016 in the Portuguese Águeda River, referred to as Agueda.2016Flood for short. The data were managed through the RiverCure portal, a collaborative web platform connected to a validated shallow-water model featuring modelled dynamic bed geometries and sediment transport. The dataset provides a synthesis of topo-bathymetric, hydrometric and numerically produced data from a calibrated hydrodynamic model. Due to the lack of measured hydrometric data near the city, the numerically produced data are crucial for a complete description of the flood event. The Agueda.2016Flood dataset constitutes a complete validation test for flood forecasting models and a tool to better mitigate floods in this river and in similar rivers. Thus, Agueda.2016Flood is a relevant dataset for Águeda River stakeholders as well as for the community of flood modellers, as it provides a well-documented validation event for forecasting tools. The dataset can be accessed at https://doi.org/10.4211/hs.937927473a3a4e66a07a2e2fdd9d581e (Ricardo et al., 2024).
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
Authors: Raffuse Sean , O'Neill Susan , Schmidt Rebecca
Published: January 2024

Abstract. Urban smoke exposure events from large wildfires have become increasingly common in California and throughout the western United States. The ability to study the impacts of high smoke aerosol exposures from these events on the public is limited by the availability of high-quality, spatially resolved estimates of aerosol concentrations. Methods for assigning aerosol exposure often employ multiple data sets that are time-consuming to create and difficult to reproduce. As these events have gone from occasional to nearly annual in frequency, the need for rapid smoke exposure assessments has increased. The rapidfire (relatively accurate particulate information derived from inputs retrieved easily) R package (version 0.1.3) provides a suite of tools for developing exposure assignments using data sets that are routinely generated and publicly available within a month of the event. Specifically, rapidfire harvests official air quality monitoring, satellite observations, meteorological modeling, operational predictive smoke modeling, and low-cost sensor networks. A machine learning approach, random forest (RF) regression, is used to fuse the different data sets. Using rapidfire, we produced estimates of ground-level 24 h average particulate matter for several large wildfire smoke events in California from 2017–2021. These estimates show excellent agreement with independent measures from filter-based networks.
Truly conserving with conservative remapping methods
Authors: Taylor Karl E.
Published: January 2024

Abstract. Conservative mapping of data from one horizontal grid to another should preserve certain integral or mean properties of the original data. This may be essential in some model applications, including ensuring realistic exchange of energy and mass between coupled model components. It can also be essential for certain types of analysis, such as evaluating how far a system is from an equilibrium state. For some common grids, existing remapping algorithms may fail to perfectly represent the shapes and sizes of grid cells, which leads to errors in the remapped fields. A procedure is presented here that enables users to rely on the mapping weights generated by remapping algorithms but corrects for their deficiencies. With this procedure, for a given pair of source and destination grids, a single set of remapping weights can be applied to remap any variable, including those with grid cells that are partially or fully masked.
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Authors: Wang Shuaitao , Thieu Vincent , Billen Gilles , Garnier Josette , Silvestre Marie , Marescaux Audrey , Yan Xingcheng , Flipo Nicolas
Published: January 2024

Abstract. Research on mechanisms of organic matter degradation, bacterial activities, phytoplankton dynamics, and other processes has led to the development of numerous sophisticated water quality models. The earliest model, dating back to 1925, was based on first-order kinetics for organic matter degradation. The community-centered freshwater biogeochemistry model RIVE was initially developed in 1994 and has subsequently been integrated into several software programs such as Seneque-Riverstrahler, pyNuts-Riverstrahler, ProSe/ProSe-PA, and Barman. After 30 years of research, the use of different programming languages including QBasic, Visual Basic, Fortran, ANSI C, and Python, as well as parallel evolution and the addition of new formalisms, raises questions about their comparability. This paper presents a unified version of the RIVE model for the water column, including formalisms for bacterial communities (heterotrophic and nitrifying), primary producers, zooplankton, nutrients, inorganic carbon, and dissolved oxygen cycles. The unified RIVE model is open-source and implemented in Python 3 to create pyRIVE 1.0 and in ANSI C to create C-RIVE 0.32. The organic matter degradation module is validated by simulating batch experiments. The comparability of the pyRIVE 1.0 and C-RIVE 0.32 software is verified by modeling a river stretch case study. The case study considers the full biogeochemical cycles (microorganisms, nutrients, carbon, and oxygen) in the water column, as well as the effects of light and water temperature. The results show that the simulated concentrations of all state variables, including microorganisms and chemical species, are very similar for pyRIVE 1.0 and C-RIVE 0.32. This open-source project highly encourages contributions from the freshwater biogeochemistry community to further advance the project and achieve common objectives.
Shoreline and Land Use Land Cover Changes along the 2004 tsunami-affected South Andaman Coast: Understanding Changing Hazard Susceptibility
Authors: Ghadamode Vikas , Aruna K. Kumari , Pandey Anand K. , Srivastava Kirti
Published: January 2024

Abstract. The 2004-tsunami affected the South Andaman coast experiencing dynamic changes in the coastal geomorphology making the region vulnerable. We focus on pre-and post-tsunami shoreline and Land Use Land Cover changes for the period 2004, 2005, and 2022 to analyse the dynamic change in hazard. We used GEBCO bathymetry data to calculate Run-up (m), arrival times (Min), and inundation (m) at 13 different locations using the 2004 Sumatra Earthquake source parameters. The Digital Shoreline Analysis System is used for the shoreline change estimates. The Landsat data is used to calculate shoreline and LULC change in five classes, namely Built-Up Areas, Forests, Inundation areas, Croplands, and water bodies during the above period. We examine the correlation between the LULC changes and the dynamic change in shoreline due to population flux, infrastructural growth, and Gross State Domestic Product growth. India industry estimates the Andaman & Nicobar Islands losses exceed INR 10 billion during 2004 that would see a five-fold increase in economic loss due to a doubling of built-up area, a three-fold increase in tourist inflow, and a population density growth. The unsustainable decline in the forest cover, mangroves and cropland would affect sustainability during a disaster despite coastal safety measures.
THE DYNAMICS OF THE COLORADO POTATO BEETLE POPULATION ON POTATO CROPS IN THE
CONDITIONS OF THE ALMATY REGION
Authors:   Kazakh Research Institute of
            plant protection and quarantine named after Zh.Zhiembayev LLP, Kazakhstan,
            Almaty, Sharipova D.S. , Alpysbaeva K.A. ,   Kazakh Research Institute of
            plant protection and quarantine named after Zh.ZhiembayevLLP, Kazakhstan,
            Almaty, Dinasilov A.S. ,   Kazakh Research Institute of
            plant protection and quarantine named after Zh.Zhiembayev LLP, Kazakhstan,
            Almaty, Sarsenbayeva G.B. ,   Kazakh Research Institute of
            plant protection and quarantine named after Zh.Zhiembayev LLP, Kazakhstan,
            Almaty
Published: January 2024

Картофель относится к роду Solanum L, семейства пасленовых, к секции Tuberarium
(Дик.) Вик., т.е. клубненосов. Ареал секции Tuberarium - Америка, исключая пояс
тропического климата, и простирается от южной части Чили и Аргентины (500 юж. ш.) через
все страны Южной и Центральной Америки до южных районов США. В Южной Америке
произрастает большая часть из 150 известных видов картофеля. Картофель служит одним из
излюбленных продуктов питания человечества. Он широко используется в животноводстве и
служит важным сырьем для пищевой промышленности. Поэтому каждый фактор, снижающий урожай
картофеля, приносит большой экономический ущерб. Одним из таких факторов в настоящее
время стал колорадский жук (Leptinotarsa decemlineata Say.), который за последние годы
превратился в важнейшего вредителя картофеля. Современный этап развития прогнозов в
области защиты растений характеризуется совершенствованием фундаментальных основ и
методологических принципов, разработкой новых методических приемов и технологических
решений, определяющих стратегию и тактику защиты растений. Прогноз фитосанитарного
состояния в защите растений рассматривается как вероятностное научно-обоснованное
суждение о динамике популяций вредных объектов в будущем, базирующееся на выявленных
закономерностях в прошлом. При этом достоверность и точность прогнозов зависят от
степени изученности факторов динамики численности объекта прогнозирования. В данной
статье приведены результаты исследований по определению динамики численности особо
опасного вредителя колорадского жука на посевах картофеля и меры борьбы с ними в
условиях Алматинской области.
THE RESULTS OF MONITORING AND RESEARCH OF INDIVIDUAL SIGNS OF ANIMALS OF THE
SMUSHKOVY DIRECTION OF PRODUCTIVITY
Authors:   Peoples' Friendship University
            named after Academician A.Kuatbekov, Shymkent, Republic of Kazakhstan, Mustiyar T.A. , Tenlibaeva A.S. ,   Zh.A. Tashenev University,
            Shymkent, Republic of Kazakhstan, Mamytova A. ,   Zh.A.Tashenev University,
            Shymkent, Republic of Kazakhstan
Published: January 2024

В статье приведены результаты селекционно-племенной работы с каракульскими овцами
популяции разных племенных хозяйств. Животные жомартской популяций жакетного смушкового
типа характеризуются: живая масса баранов 75-80 кг, маток- 45-50 кг; выход ягнят
жакетного типа - 86,0%, в том числе элиты -54,4%,Iкласса -45,6%; шелковистость и блеск
волоса – сильные; выход каракуля I сортов -84,0 -93,0%, из них жакетной группы – 86,0%,
в том числе «жакет 1» - 15,0-20,0%. Популяция овец ТОО «Жана-Тан» аналогичного
смушкового типа характеризуется: живая масса баранчиков при рождении- 4,6-4,8 кг, ярочек
- 4,3-4,5 кг, длина завитка у ягнят с разной интенсивности черных окрасок короткий-
3,5мм, средний - 36,8 мм,длинный - 59,7мм. Были использованыосновные
бараны-производители смушкового направления продуктивности черной окраски жакетного
смушкового типа в количестве 7 голов к/х «Жомарт» и 9 голов ТОО «Жана тан». Степень
интенсивности окраски черных ягнят, полученные от разных подборов родительских пар
бывает различной и изменчивы по своему оттенку. Высокий чисто интенсивно-черные окраски
получены в гомогенном подбре – 76,7%, а в гетерогенном – всего 23,8%. Исходя из
сказанного следует, что необходимо вести учет степени интенсивности пигментации черного
волосяного покрова ягнят при рождении.
The Role of Farmers in Developing the Existence of Madrasah Diniyah Takmiliyah Wustho Al-Munawaroh
Authors: Sulistiyawati Sulistiyawati , Amirudin Noor
Published: January 2024

Community participation, both material and moral, is very important in efforts to develop the Diniyah takmiliyah Wustho madrasah. This research aims to analyze the role of the farming community in the development of Madrasah Diniyah Takmiliyah wustho in Timbuan Hamlet, Tambakmenjangan Village, Sarirejo District, Lamongan Regency. The subjects of this research are people who work as farmers in the hamlet who are in the development and existence of activities at Madrasah Diniyah Takmiliyah Wustho. This research method is a qualitative approach. Data collection techniques use participant observation, in-depth interviews, and documentation. The research results show that the farming community has an important role in the development of Madrasah Diniyah Takmiliyah Wustho. This is proven by the high enthusiasm of the Timbuan Hamlet farming community to contribute to the development and existence of activities at the madrasah. This enthusiasm is based on several factors, namely the opinion that the Diniyah takmiliyah wustho madrasah is an educational institution with complete knowledge because it teaches general knowledge and religious knowledge, the integration of learning Islamic religious knowledge into life, the view that rural communities still prioritize morals over knowledge, and the approach madrasas through regular monthly meetings. very affecting. From this it can be concluded that community relations in the world of education is a unique management function and supports the development and maintenance of community members, both communication and between organizations
ANALYSIS OF IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION (PSO) METHOD ON LECTURERS ASSIGNMENTS TO STUDENTS
Authors: Chaerullah Dhiesky , Chalid Iqbal , Solichin Achmad
Published: January 2024

When preparing a program for a conference, it is very important to divide teaching and learning tasks according to the areas in which you are involved for teaching and learning to be effective. At the University, the assignment process is still done manually which is very time consuming. Therefore, an appropriate optimization method is needed to handle this. This problem can be solved using a population-based heuristic approach, Particle Swarm Optimization (PSO) has been applied to various fields such as scheduling and assignment. The data used in this research is lecturer assignment data in the form of prioritizing lecturer interest in teaching certain subjects. Based on the calculation results, a test was carried out to determine the effect of the test parameters on the fitness value obtained. From the results of the PSO parameter test, the best number of particles is 100, the best number of repetitions is 100, and the speed combination parameters c1 and c2 are 1.5 and 1.5 with the appropriate value of 94878. The system results, the solution obtained gives good results, i.e. always within tolerance limits, the error scores obtained by placing teachers on subjects that suit their preferences are lower
TRANSFER LEARNING TO PREDICT GENRE BASED ON ANIME POSTERS
Authors: Kaka Kamaludin  , Woro Isti Rahayu  , Helmi Setywan Muhammad Yusril
Published: January 2024

Anime is an animated film with a distinctive graphic design originating from Japan, which is widely favored by various groups. anime itself has a genre like a movie in general, but there is a slight difference from ordinary films, anime has additional genres that are not in ordinary films, such as the Ecchi, Mahou Shoujou, Seinen, Shounen, and Josei genres. Since those genres only exist in anime, this research is devoted to predicting those anime genres. The prediction will use posters from the anime itself, with the help of image processing, namely the Convolutional Neural Network method and Transfer Learning. Transfer Learning will be implanted as a comparison of the performance of the existing architecture with the architecture that will be created, whether the architecture is able to process the dataset properly. The dataset to be used is a dataset of posters and csv documents containing images and details of the anime, the dataset contains anime data from 1980 to 2021 and contains 11651 anime poster data which has different resolution sizes. The ResNet50 model has the highest accuracy rate of 48% with a loss rate of 36%, while InceptionV3 produces 35% accuracy with 69% loss. At the time of testing ResNet50 gave the smallest genre percentage value of CustomModel and InceptionV3, while CustomModel gave the highest genre value. In addition to the value, all modes also predicted the genre well. Especially InceptionV3 is able to predict the music genre, because the music genre has a very small number of datasets, and this music genre is difficult to predict by the ResNet50 and CustomModel models.
RIAU PROVINCE TOURISM WEBSITE IMPROVEMENT PROGRAM USING E-GOVQUAL AND IMPORTANCE PERFORMANCE ANALYSIS METHODS
Authors: Ichsan Ahmad Gunawan  , Muhammad Jazman  , Tengku Khairil Ahsyar  , M. Afdal
Published: January 2024

The Riau Province Tourism Office implements E-Government by building a website as a media public relations. This website is used to provide information on tourist destinations, facilities and news about Riau Province. Previously this website had never been evaluated so that the community's assessment of the quality of the Riau Province Tourism service site was unknown. For this reason, this study aims to analyze the service quality of the Riau Province Tourism Office website based on the perception or point of view of its users, in this case especially the people of Riau Province using the Electronic Government Quality (E-GovQual) and Importance Performance Analysis (IPA) methods. To assess the service quality of the Riau Province Tourism Office website using 6 dimensions and 28 E-GovQual attributes. The results of this study show that the total value of the performance score is Likert 3 (good) which is 3.30, the value of importance is 3.27, and the gap between performance and importance is 0.002 or > 0. The results of this study indicate that service performance has met the interests user. Thus the overall performance of the Riau Province Tourism Office website service is good and has fulfilled the interests of users. Furthermore, from the results of the IPA analysis, 7 attributes (EU1, TR1, FIE2, EU2, TR3, CS2, CAI3) are obtained with top priority and 5 attributes (EU3, FIE1, RB3, CA12, TR2) that need to be improved.
TOPIC MODELING IN COVID-19 VACCINATION REFUSAL CASES USING LATENT DIRICHLET ALLOCATION AND LATENT SEMANTIC ANALYSIS
Authors: Malihatin S Ulfah , Findawati Yulian , Indahyanti Uce
Published: January 2024

COVID -19 vaccination is a program provided by the Indonesian government to minimize the spread of the virus. The COVID-19 vaccination program in Indonesia goes hand in hand with issues that are circulating, causing controversy and rejection of vaccination on social media, especially Twitter. There are many factors that influence vaccine rejection on Twitter, to summarize frequently discussed topics and find out hidden topics, this study uses the Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) methods from 1797 Twitter scrapping data. Both models require a set of words that have been converted into a matrix, so before conducting LDA topic modeling, the dataset will undergo a bag of word (BOW) calculation. Meanwhile, in LSA topic modeling, the existing dataset will undergo word weighting of frequently occurring words using Term Frequency - Inverse Document Frequency (TF-IDF). This study was conducted to find and summarize hidden information in the form of frequently discussed topics, thus understanding public opinions related to the COVID -19 vaccination refusal case. LDA and LSA methods will display topics based on the probability and mathematical calculations of word occurrences in each topic in the document. The topics that appear will be further analyzed through coherence score by applying a limit of 20 topics to display the best value. Further modeling experiments are carried out to display topics through LDA and LSA models, this study takes 6 topics with the highest coherence values including the right of individuals to choose whether to be vaccinated or not (0.484607), the Ribka Tjiptaning controversy (0.473368), rejection of the COVID-19 vaccine by groups represented by public figures (0.463631), punishment for non-compliance in the form of fines (0.324924), and halal certification (0.312521).
HUMAN FACE RECOGNITION ON IMAGE VIDEO CONFERENCE APPLICATION USING SIAMESE NETWORK WITH SKIP CONNECTION SMALLER VGG MODEL
Authors: Tanuwijaya Evan , Setiawan Averill Saladin Atma , Arianindita Achmad Rijalu , Kristanto Timothy
Published: January 2024

Attendance recording is needed to find out someone's attendance at a meeting or meeting. These meetings are sometimes conducted online through the video conferencing application. Recording attendance at online meetings is using an online form that is distributed via chat. There are several problems such as chats piling up and meeting participants arriving late so they cannot access the form link. Therefore, facial recognition can be used to record attendance using screenshots as an attendance record with the aim of helping to facilitate attendance recording through video conferencing applications using computer vision technology. This study proposes a method of using the Siamese network with the Smaller VGG skip connection model to improve human face recognition in video conferencing application images. Has validation accuracy results in the training phase of 98%, precision of 98%, and recall of 98%. For the similarity phase where the model is applied to the Siamese network, the accuracy is 95%, the precision is 53%, and the recall is 78%. Then the model is applied to the pipeline system with the YOLO-face model to classify the results of face detection from Yolo with the faces in the database so that the model does not need to be retrained if there are new faces, it only needs to add facial images to the database to be compared with the query image..
APPLICATION OF NAÏVE BAYES CLASSIFIER ALGORITHM IN DETERMINING THE LEVEL OF CUSTOMER SATISFACTION WITH RUMBAI POST OFFICE SERVICES
Authors: Anisa Halifa  , Novita Rice
Published: January 2024

Technological advances make service and delivery of goods grow rapidly. Coupled with people's changing shopping habits by shopping online, shipping companies are increasingly needed. PT. POS Indonesia is the first expedition company in Indonesia. Currently PT. POS Indonesia has opened many POS Office branches in every region in Indonesia, one of which is the Rumbai POS Office located in Pekanbaru City. To continue to maintain the company while competing with other expeditions, the Rumbai POS Office must continue to maintain its customers by improving the quality of service. Survey analysis can be done to determine the extent of customer satisfaction with the services provided. To find out the level of customer satisfaction, you can use the classification method. Naive Bayes is a popular and effective machine learning algorithm for classification problems. The study used datasets sourced from the results of questionnaire distribution to customers of the Rumbai POS Office. The questionnaire used 14 indicators derived from the Community Satisfaction Index set by the Ministry of Agriculturein 2004. The classification resulted in a Satisfied class of 16 data with a percentage of 84.2% and a Dissatisfied class of 3 data with a percentage of 15.8%, it can be concluded that the service at the Rumbai POS Office is good. From the classification results, it is proven that the Naïve Bayes algorithm is able to predict well the level of customer satisfaction with an accuracy value of 94.74%, precision of 100%, and recall of 94.12%. The results of this research can later be used as information for the Rumbai POS Office to be able to improve service quality.