bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of intrapartum oxytocin administration on neonatal sucking behavior and breastfeeding
Authors: Omaru Machiko , Kajiwara Setsu , Wakamatsu Eri , Kuroishi Sumiko , Ochiai Yukifumi , Oniki Kentaro , Kato Kiyoko , Morokuma Seiichi
Published: March 2024

This study aimed to examine the effect of intrapartum oxytocin administration on neonatal sucking behavior and breastfeeding. A total of 64 pairs (29 in the group treated with intrapartum oxytocin and 35 in the control group) of normal infants within 24–48 h of birth and their mothers were recruited. Sucking ability was evaluated by measuring Non-Nutritive Sucking (NNS) for 5 min. Data on the rate of exclusive breastfeeding at 1 month postpartum were collected. In the adjusted multiple regression models, intrapartum oxytocin exposure was significantly associated with fewer total NNS bursts (95% confidence interval (CI), −7.02 to −0.22), longer pause times (95% CI, 1.33 to 10.21), and greater pause-time variability (95% CI, 3.63 to 63.92). Effects estimated using structural equation modeling revealed that intrapartum oxytocin exposure had a significant negative and direct effect on the practice of exclusive breastfeeding 1 month postpartum (β = −0.238, p = 0.047). However, no NNS-mediated indirect effects were observed. This report demonstrates that infants born to mothers who receive intrapartum oxytocin may have impaired sucking ability for at least the first 48 h after birth, and breastfeeding support should be provided.
Development and validation of prognostic machine learning models for short- and long-term mortality among acutely admitted patients based on blood tests
Authors: Jawad Baker Nawfal , Shaker Shakir Maytham , Altintas Izzet , Eugen-Olsen Jesper , Nehlin Jan O. , Andersen Ove , Kallemose Thomas
Published: March 2024

Several scores predicting mortality at the emergency department have been developed. However, all with shortcomings either simple and applicable in a clinical setting, with poor performance, or advanced, with high performance, but clinically difficult to implement. This study aimed to explore if machine learning algorithms could predict all-cause short- and long-term mortality based on the routine blood test collected at admission. Methods: We analyzed data from a retrospective cohort study, including patients > 18 years admitted to the Emergency Department (ED) of Copenhagen University Hospital Hvidovre, Denmark between November 2013 and March 2017. The primary outcomes were 3-, 10-, 30-, and 365-day mortality after admission. PyCaret, an automated machine learning library, was used to evaluate the predictive performance of fifteen machine learning algorithms using the area under the receiver operating characteristic curve (AUC). Results: Data from 48,841 admissions were analyzed, of these 34,190 (70%) were randomly divided into training data, and 14,651 (30%) were in test data. Eight machine learning algorithms achieved very good to excellent results of AUC on test data in a of range 0.85–0.93. In prediction of short-term mortality, lactate dehydrogenase (LDH), leukocyte counts and differentials, Blood urea nitrogen (BUN) and mean corpuscular hemoglobin concentration (MCHC) were the best predictors, whereas prediction of long-term mortality was favored by age, LDH, soluble urokinase plasminogen activator receptor (suPAR), albumin, and blood urea nitrogen (BUN). Conclusion: The findings suggest that measures of biomarkers taken from one blood sample during admission to the ED can identify patients at high risk of short-and long-term mortality following emergency admissions.
An integrated approach for the benthic habitat mapping based on innovative surveying technologies and ecosystem functioning measurements
Authors: Piazzolla Daniele , Scanu Sergio , Mancuso Francesco Paolo , Bosch-Belmar Mar , Bonamano Simone , Madonia Alice , Scagnoli Elena , Tantillo Mario Francesco , Russi Martina , Savini Alessandra , Fersini Giorgio , Sarà Gianluca , Coppini Giovanni , Marcelli Marco , Piermattei Viviana
Published: March 2024

Among marine ecosystems globally, those in the Mediterranean Sea, are facing many threats. New technologies are crucial for enhancing our understanding of marine habitats and ecosystems, which can be complex and resource-intensive to analyse using traditional techniques. We tested, for the first time, an integrated multi-platform approach for mapping the coastal benthic habitat in the Civitavecchia (northern Latium, Italy) coastal area. This approach includes the use of an Unmanned Surface Vehicle (USV), a Remote Operated Vehicle (ROV), and in situ measurements of ecosystem functionality. The echosounder data allowed us to reconstruct the distribution of bottom types, as well as the canopy height and coverage of the seagrass Posidonia oceanica. Our study further involved assessing the respiration (Rd) and net primary production (NCP) rates of P. oceanica and its associated community through in situ benthic chamber incubation. By combining these findings with the results of USV surveys, we were able to develop a preliminary spatial distribution model for P. oceanica primary production (PP-SDM). The P. oceanica PP-SDM was applied between the depths of 8 and 10 m in the studied area and the obtained results showed similarities with other sites in the Mediterranean Sea. Though in the early stages, our results highlight the significance of multi-platform observation data for a thorough exploration of marine ecosystems, emphasizing their utility in forecasting biogeochemical processes in the marine environment.
Cascade and pre-slip models oversimplify the complexity of earthquake preparation in nature
Authors: Martínez-Garzón Patricia , Poli Piero
Published: March 2024

Earthquake precursory processes have been central to scientific inquiry for nearly a century. Recent advancements in earthquake monitoring, geodesy, and data analysis including artificial intelligence, have substantially improved our understanding of how earthquake sequences unfold leading to the mainshock. We examine the available seismological and geodetic evidence describing preparatory processes in 33 earthquake sequences with MW [3.2–9.0] across different tectonic and stress conditions. Our analysis reveals common patterns, and sheds light on the interplay of structural, tectonic and other boundary conditions that influence the dynamics of earthquake sequences, and hence, in the seismo-geodetic observables prior to the mainshock. We place particular emphasis on connecting observed phenomena to the underlying physical processes driving the sequences. From our findings, we propose a conceptual framework viewing earthquake preparation as a process involving several juxtaposed driving physical mechanisms on different temporal and spatial scales, jointly leading to the stress increase in the future epicenter.
Kupffer cells dictate hepatic responses to the atherogenic dyslipidemic insult
Authors: Di Nunzio Giada , Hellberg Sanna , Zhang Yuyang , Ahmed Osman , Wang Jiawen , Zhang Xueming , Björck Hanna M. , Chizh Veronika , Schipper Ruby , Aulin Hanna , Francis Roy , Fagerberg Linn , Gisterå Anton , Metso Jari , Manfé Valentina , Franco-Cereceda Anders , Eriksson Per , Jauhiainen Matti , Hagberg Carolina E. , Olofsson Peder S. , Malin Stephen G.
Published: March 2024

Apolipoprotein-B (APOB)-containing lipoproteins cause atherosclerosis. Whether the vasculature is the initially responding site or if atherogenic dyslipidemia affects other organs simultaneously is unknown. Here we show that the liver responds to a dyslipidemic insult based on inducible models of familial hypercholesterolemia and APOB tracing. An acute transition to atherogenic APOB lipoprotein levels resulted in uptake by Kupffer cells and rapid accumulation of triglycerides and cholesterol in the liver. Bulk and single-cell RNA sequencing revealed a Kupffer-cell-specific transcriptional program that was not activated by a high-fat diet alone or detected in standard liver function or pathological assays, even in the presence of fulminant atherosclerosis. Depletion of Kupffer cells altered the dynamic of plasma and liver lipid concentrations, indicating that these liver macrophages help restrain and buffer atherogenic lipoproteins while simultaneously secreting atherosclerosis-modulating factors into plasma. Our results place Kupffer cells as key sentinels in organizing systemic responses to lipoproteins at the initiation of atherosclerosis.
AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor
Authors: Trepte Philipp , Secker Christopher , Olivet Julien , Blavier Jeremy , Kostova Simona , Maseko Sibusiso B , Minia Igor , Silva Ramos Eduardo , Cassonnet Patricia , Golusik Sabrina , Zenkner Martina , Beetz Stephanie , Liebich Mara J , Scharek Nadine , Schütz Anja , Sperling Marcel , Lisurek Michael , Wang Yang , Spirohn Kerstin , Hao Tong , Calderwood Michael A , Hill David E , Landthaler Markus , Choi Soon Gang , Twizere Jean-Claude , Vidal Marc , Wanker Erich E
Published: March 2024

Protein–protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.
Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease
Authors: Bhosle Amrisha , Bae Sena , Zhang Yancong , Chun Eunyoung , Avila-Pacheco Julian , Geistlinger Ludwig , Pishchany Gleb , Glickman Jonathan N , Michaud Monia , Waldron Levi , Clish Clary B , Xavier Ramnik J , Vlamakis Hera , Franzosa Eric A , Garrett Wendy S , Huttenhower Curtis
Published: March 2024

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.
Transplantation of a bioengineered tissue patch promotes uterine repair in the sheep
Authors: Sehic Edina , de Miguel Gómez Lucía , Rabe Hardis , Thorén Emy , Gudmundsdottir Ingigerdur , Oltean Mihai , Akouri Randa , Brännström Mats , Hellström Mats
Published: March 2024

Innovative bioengineering strategies utilizing extracellular matrix (ECM) based scaffolds derived from decellularized tissue offer new prospects for restoring damaged uterine tissue.
Synthesis and photophysical properties of charge transfer cocrystals based on TCNB and fluorene and its derivatives
Authors: Yao Wenxiu , Wu Pengfei , Xie Yidan , Shen Xinyu , Xia Shuwei , Yu Liangmin
Published: March 2024

A series of charge transfer cocrystals with fluorescence properties involving 1,2,4,5-tetracyanobenzene as acceptor, fluorene, 2-bromofluorene, carbazole and 2-bromocarbazole as donor were synthesized via cocrystal design strategies.
Lithium-grafted Si-doped γ-graphyne as a reversible hydrogen storage host material
Authors: Duhan Nidhi , Dhilip Kumar T. J.
Published: March 2024

The novel monolayer Si-doped γ-graphyne offers a high capacity and reversible hydrogen storage.
Analysis of hydrogen in a hydrogenated, 3D-printed Ti–6Al–4V alloy by glow discharge optical emission spectroscopy: sample heating effects
Authors: Weiss Zdeněk , Čapek Jaroslav , Kačenka Zdeněk , Ekrt Ondřej , Kopeček Jaromír , Losertová Monika , Vojtěch Dalibor
Published: March 2024

In the analysis of hydrogen in a hydrogenated, 3D-printed Ti–6Al–4V alloy by GDOES, hydrogen diffuses from the depth due to sample heating, enters the plasma and affects the signal response. A model of heat conduction within the sample is presented.
One-pot hydrothermal synthesis of FeNbO4 microspheres for effective sonocatalysis
Authors: He Min , Li Defa , Liu Yu , Li Taohai , Li Feng , Fernández-Catalá Javier , Cao Wei
Published: March 2024

FeNbO4 can effectively sonocatalytically remove AO7.
Convenient construction of tetraphenylethene (TPE) derivatives through Cu(ii) mediated cascade dehydrogenation of EWG-activated diphenylmethane
Authors: Liu Qing , Ye Lihua , Wang Qing , Gong Siming , Xie Yongfa , Yan Zhangqiang , Yue Shusheng , Wei Zhenhong , Cai Hu
Published: March 2024

A sequential dehydrogenation reaction of activated diarylmethane derivatives mediated by copper(ii) pivalate was developed, for preparation of electron-deficient tetraphenylethene (TPE) derivatives.
Accurate and sensitive low-density lipoprotein (LDL) detection based on the proximity ligation assisted rolling circle amplification (RCA)
Authors: Zhang Xingyu , Li Jie , Yang Mei , Huang Hong , Wang Hao , Zhang Hongmin
Published: March 2024

Accurate and sensitive low-density lipoprotein (LDL) detection.
Experimental and theoretical insights for designing Zn2+ complexes to trigger chemo-selective hetero-coupling of alcohols
Authors: Samanta Arup , Behera Prativa , Chaubey Amit , Mondal Avijit , Pal Debjyoti , Mohar Kailash , Roy Lisa , Srimani Dipankar
Published: March 2024

Designing well-defined Zn-complexes for chemo-selective cross-coupling of primary and secondary alcohols overcoming the difficulties associated with activating Zn2+(d10)-metal species.
Color-resolved mechanoluminescence of Eu and Mn co-doped SrMg2(PO4)2
Authors: He Qingshan , Yan Yajing , Wang Ting , Guo Longchao , Yue Yang , Zhu Nannan , Bu Weifang , An Xin , Duan Bosong , Zhu Xuanyu , Yu Xue
Published: March 2024

The linear relationship between the ML intensity ratio (MLIR) and stress of this phosphor leads to a change in ML color, resulting in visualization of ML performance of knee motion via the artificial skin based on SMP:Eu,Mn phosphor.
First-principles studies of enhanced oxygen reduction reactions on graphene- and nitrogen-doped graphene-coated platinum surfaces
Authors: Nam Ho Ngoc , Phung Quan Manh , Choeichom Pongpol , Yamauchi Yusuke , Saito Nagahiro
Published: March 2024

Graphene coating and N-doped graphene coating are not only good physical protective layers but also have efficient ORR catalytic activity on platinum surfaces, which is important for promoting high-performance fuel cell technology.
Magic cluster sizes of cationic and anionic sodium chloride clusters explained by statistical modeling of the complete phase space
Authors: Hartmann Jessica C. , Madlener Sarah J. , van der Linde Christian , Ončák Milan , Beyer Martin K.
Published: March 2024

Sodium chloride clusters show rich structural diversity. Magic cluster sizes like the (NaCl)4Na+ cluster are not always energetically favoured. Their high abundance in mass spectra is explained by their kinetic stability against dissociation.
Role of Lewis acid/base anchor atoms in catalyst regeneration: a comprehensive study on biomimetic EP3Fe nitrogenases
Authors: Kfoury Joseph , Oláh Julianna
Published: March 2024

Exploration of anchor atoms in Fe-nitrogenase catalysts demonstrates superior N2 reduction with Lewis acidic atoms (B, Al, Ga), particularly boron, over Lewis basic counterparts (N, P).
Catalytic production of 1,4-pentanediol from lignocellulosic biomass
Authors: Zhu Shanhui , Lv Zexiang , Wang Jiamin , Jia Xiangyu , Li Xiaoming , Dong Mei , Wang Jianguo , Fan Weibin
Published: March 2024

This review gives a broad overview of the conversion of biomass-derived levulinic acid (LA) and furfural into valuable 1,4-pentanediol (1,4-PDO), which is a degradable polyester monomer.
A reflection on ‘A shape-memory scaffold for macroscale assembly of functional nanoscale building blocks’
Authors: Meng Xiang-Sen , Mao Li-Bo , Yu Shu-Hong
Published: March 2024

Yu et al. reflect on their first Materials Horizons paper (Mater. Horiz., 2014, https://doi.org/10.1039/c3mh00040k) published in the inaugural issue of the journal, and discuss how their work may have influenced the research field over the past decade.
Intensification of silver nanoparticle synthesis through continuous flow split and recombine microreactors
Authors: Ghosh Amritendu Bhuson , Kumar Rakesh , Atta Arnab
Published: March 2024

Regulating continuous synthesis of silver nanoparticles in split and recombine microreactors employing enhanced capabilities of curvature induced secondary flows.
A trusted and regulated data trading scheme based on blockchain and zero‐knowledge proof
Authors: Li Dongmei , Ke Xiaohui , Zhang Xiaomei , Zhang Yujin
Published: March 2024

To meet the demand for high‐quality healthcare services, data trading can effectively promote the circulation of medical data and improve the level of healthcare services. To address the existing problems of data regulation difficulties and data privacy leakage in medical data trading, a trusted and regulated data trading scheme based on blockchain and zero‐knowledge proof is proposed. In this scheme, a regulatory institution is introduced to control the issuance of authorized tokens and ensure the controllability of data sharing activities. The blockchain takes over the task of generating public parameters to reduce the computational overhead of the system. Based on homomorphic proxy re‐encryption technology, users can perform data analysis in the cloud to ensure data security. Smart contracts and zero‐knowledge proof technology can automatically verify the validity of data to protect the rights and interests of data users; at the same time, efficient consensus algorithms can also increase the rate of transactions processed by the blockchain system. Finally, as the security and performance analysis shows, the scheme in this paper has better security, higher efficiency and more comprehensive functions.
Probabilistic 3D motion model for object tracking in aerial applications
Authors: Mirtajadini Seyed Hojat , Amiri Atashgah MohammadAli , Shahbazi Mohammad
Published: March 2024

Visual object tracking, crucial in aerial applications such as surveillance, cinematography, and chasing, faces challenges despite AI advancements. Current solutions lack full reliability, leading to common tracking failures in the presence of fast motions or long‐term occlusions of the subject. To tackle this issue, a 3D motion model is proposed that employs camera/vehicle states to locate a subject in the inertial coordinates. Next, a probability distribution is generated over future trajectories and they are sampled using a Monte Carlo technique to provide search regions that are fed into an online appearance learning process. This 3D motion model incorporates machine‐learning approaches for direct range estimation from monocular images. The model adapts computationally by adjusting search areas based on tracking confidence. It is integrated into DiMP, an online and deep learning‐based appearance model. The resulting tracker is evaluated on the VIOT dataset with sequences of both images and camera states, achieving a 68.9% tracking precision compared to DiMP's 49.7%. This approach demonstrates increased tracking duration, improved recovery after occlusions, and faster motions. Additionally, this strategy outperforms random searches by about 3.0%.
A robust state estimation by optimal placement of measurement units considering loads/renewable generations and measurements uncertainty
Authors: Asadzadeh Babak , Tousi Behrouz , Galvani Sadjad , Talavat Vahid
Published: March 2024

The supervisory control and data acquisition (SCADA) system is one of the key requirements for monitoring the power systems state. The power system state is estimated from the state estimation (SE) function, which uses the measurements results from different points. Inaccurate estimation may cause inefficient management of power systems and making decisions. Usually, the number of measurement units (MUs) is limited so the optimal location of MUs is very important in successful and accurate state estimation. The optimal placement of MUs gets more complicated when the actual state of the power system is uncertain due to the high penetration of renewable generation and load uncertainties. Considering the power system's actual state uncertainty and measurement units’ inherent error, this work presents a probabilistic model for the uncertainty of measuring based on the K‐medoids data clustering technique. Then the probabilistic optimal placement of MUs is solved by a binary particle swarm optimization (PSO) method. Considering the mentioned uncertainties makes the obtained solution robust against all the probable scenarios. The proposed technique is implemented on the IEEE 14‐bus test system and the results are discussed. Results show the effectiveness of the proposed method in improving the accuracy of power system state estimation.
Development of Ceramic Decorative Rotary Tool Technology Based on the Internet of Things as a Learning Media to Support Creative Industries
Authors: Hidayat Rahmat , Adriansyah Andi , Kurniawan Febi
Published: March 2024

Indonesia is a rich and diverse country for crafts and creative industries. In supporting the creative industry, it is necessary to have skills through learning creative crafts in the community of Rangdumulya Village, Pedes District, Karawang. The problem that occurs is that currently, the younger generation is less interested in creative crafts such as pottery, ceramics, and batik. In making pottery and ceramics, turntable equipment is needed to make pottery products that can be formed into jugs, teapots, glasses, and jars. The lack of digital turntable tools is helping the work of pottery craftsmen in the process of making and forming pottery, which can be used to accelerate the production process. The purpose of this research is to create, design, and implement to have a positive impact on the emergence of new technological products and the creation of pottery technology, which is considered very necessary to help the learning process of creative crafts in the village to become an independent village. The focus of this research is the development of internet-of-things-based ceramic decorative rotary tool technology as a learning medium to support creative industries. The result of this research is that Internet-of-Things-Based Ceramic Decorative Rotary Tool Technology can work, have a positive impact on pottery craftsmen, and increase the productivity of youth skills in the field of creative crafts, especially in making pottery or ceramics.
The Effect of 0.8% Polyethylene Terephthalate Plastic Waste Substitution on the Flexural Strength on K-175 Concrete
Authors: Utomo Gunaedy , Indriani Andi Marini , Damayanti Dinda Indah
Published: March 2024

The use of plastics in daily life continues to increase in a variety of uses. One of the most commonly used plastic that is difficult to decompose is Polyethylene Terephthalate (PET) plastic. In recent years, such as the construction industry, has been trying to reuse the waste as construction material. Therefore, this research aims to contribute by exploring the effect of PET plastic fiber substitution as fine aggregate on the flexural strength of concrete. PET plastic fibers were used at 0.8% as partial replacement of fine aggregates and then chopped to a size of 5 cm long, 1-3 mm wide. The test results indicate that concrete containing 0.8% PET plastic fiber as a substitution of fine aggregate has a higher flexural strength value of 4.32% which is better than normal concrete. Therefore, using recycled PET fiber in concrete is needed as an eco-friendly and sustainable construction material in the future in order to minimize PET plastic waste and replace it as a concrete constituent material.
Terrafloc Polymer Application to Increase Oil Recovery: Study Literature
Authors: Amri Sulthoni , Setiati Rini , Swadesi Boni
Published: March 2024

To determine the performance of terrafloc polymer, we must first know the characteristics of the polymer because all of these will affect the increase in oil recovery. Many factors affect the performance of the polymer. Here, using a micromodel to see the movement of oil in 2D, the sweep efficiency of the polymer injection can be seen clearly. The micromodel flooding method was carried out in a series of studies, starting with micromodel preparation, followed by waterflooding and polymer injection at a certain injection flow rate. The data was then analyzed using digital image analysis (DIA) to determine how much oil recovery increased after the injection of terrafloc polymer.
Application of Artificial Neural Networks for Predicting Relative Permeability in Talang Akar Formation
Authors: Fathaddin Muhammad Taufiq , Sari Alvita Kumala , Sutansyah Daddy , Ulfah Baiq Maulinda , Bae Wisup , Rakhmanto Pri Agung , Irawan Sonny
Published: March 2024

Relative permeability is a substantial parameter for estimating multi-phase fluid flow in porous rocks. It is a complex physical property that is influenced by the behavior and interactions between the fluid and rock phases. Relative permeability measurement of rock samples in laboratory can be carried out using steady-state or non-steady-state techniques. Permeability measurement is relatively difficult and time consuming. Because of the difficulty in measurement, empirical models are often used to estimate relative permeability or extrapolate to limited laboratory data. Artificial neural network (ANN) is a method that can be applied to obtain complex correlations of parameters that influence each other. In this study, ANN is used to predict the relative permeability of oil and water. The proposed model evaluates the relative permeability of a phase as a function of rock absolute permeability, porosity, depth, permeability of other phases and water saturation. A total of 159 relative permeability data from Talang Akar Formation were used for the training and testing processes. Based on the comparison between measured and calculated data, the correlation coefficients for relative permeability to water and oil using ANN method are 0.77 and 0.94 respectively. While those using regression analysis are 0.88 and 0.73 respectively.
The Statistic Analysis of Instruments and Temperature Measurement of Freezer Wall Attached by Dry Ice Gel
Authors: Sena Boni , Amanah Nadia , Suhendra Bobie , Setiawan Reza , Alfakihuddin Muhammad Lukman Baihaqi
Published: March 2024

The need for electrical energy in Indonesia is increasing rapidly, and the use of electrical energy will increase carbon dioxide gas emissions by around 1.3% each year, which causes environmental damage. The electricity usage sector in households is higher than in industry and transportation. The need for electricity in households will increase from 49% in 2018 to 58% in the BAU (business as usual) scenario and 61% in the RK (low carbon) scenario in 2050. The leading cause of the high use of electrical energy in households is the use of cooling equipment such as air conditioners, refrigerators, and freezers. One strategy to increase energy efficiency that can be used in cooling equipment such as freezers is using phase change materials (PCM). The method in this research used phase change material of dry ice gel to maintain the temperature in the freezer although the electricity was off. The results showed that the dry ice gel PCM maintained the temperature under zero degree.
Utilization of Machines to Produce Craft Raw Materials from Doyo Leaf Fiber
Authors: Wulaningrum Ratna , Cahyadi Dwi , Suparno  , Setiawan Ferry Bayu
Published: March 2024

The limitation of raw materials for doyo leaf fiber crafts is that the fiber produced is still stiff so it is mostly used for crafts in the form of decoration only. Researchers made a machine to produce doyo leaf fiber with a finer texture to help local craftsmen improve the quality of their products. This research aims to test the use of machines by local craftsmen to produce raw materials from doyo leaf fiber. This research uses a comparative description method between the process of producing raw materials from doyo leaf fiber using a machine and manually. This research found empirical evidence that doyo leaf fiber processed by machine produces products with softer quality than when processed manually. The strength of the fibers produced by the machine is the same as if processed manually. The results of this study are useful for improving the quality and diversity of products produced by local craftsmen using doyo fiber as raw material. While doyo leaf fiber has been mostly used to make decorations, processing it using a machine produces fine fiber so it can be used for fashion products.
Comparison of River Stability using 2D HEC-RAS Newtonian and Non-Newtonian Flow Modelling (Case Study: Design of Sabo Dam in the Namo River Basin, Sigi Regency, Indonesia)
Authors: Ismail Taufik , Harlan Dhemi , Moerwanto Arie Setiadi
Published: March 2024

River stability is a crucial factor in assessing and managing risks associated with natural disasters, such as debris flows. This study compares river stability using two-dimensional (2D) HEC-RAS modeling with both Newtonian and Non-Newtonian flow approaches. Typically, non-Newtonian flow models are used for modeling debris flows. However, this study examines how the differences in modeling using Newtonian and non-Newtonian flows affect the potential for debris and the stability of the river system. The study focuses on the Namo River located in Sigi Regency, Indonesia, which is prone to debris flow events. In order to mitigate debris flows in the Namo River, three Sabo Dams and one Consolidation Dam have been built. The conditions before and after the construction of the Sabo Dam and the Consolidation Dam will also be modeled in this study. By comparing the results obtained from these modeling techniques, the study aims to provide a comprehensive understanding of river stability and improve the accuracy of debris flow prediction. The findings from this study have significant implications for the management and planning of the Namo River and similar river systems, enabling effective measures to minimize the potential risks associated with debris flow events.
Employee Creativity as Moderation between Ambidexterity Organization and Innovation Performance: SMEs in East Kalimantan
Authors: Soeprapto Etwin Fibrianie , Partiwi Sri Gunani , Widyaningrum Retno
Published: March 2024

Product innovation is a point of interest for consumers to buy products. Organizational ambidexterity is the company's ability to pursue innovation through exploitative and explorative means, thereby influencing employee innovative performance. Technology readiness by organizations and employees is a benchmark for the success of product development. The problem that often occurs is that not all employees are ready for technology and innovation which has an impact on increasing innovation and product performance. Product innovation certainly cannot be separated from employee creativity. Creativity is important in creating competitive advantage and creative industry erformance. The purpose of this research is to investigate the importance of developing organizational ambidexterity and organizational technology readiness as well as employee creativity in improving organizational innovation performance. By doing this, this research tested the moderation of employee creativity (EC) on the relationship between organizational ambidexterity (AO) and innovation performance (IP). By applying a quantitative and cross- sectional design and analyzing the results of a questionnaire on 100 SMEs in East Kalimantan, it was found that AO had a positive and significant effect on IP, while EC had a positive and significant effect on AO but had a negative and insignificant effect on IP. EC moderates and has a positive and significant influence on the relationship between AO and IP as well as AO and IP. This research contributes to the advancement of organizational capability theory by adding the important role of employee creativity in achieving innovation performance.
Accessibility of Healthcare Services of COVID-19 and Its Impact on Fatalities in Jakarta, Indonesia
Authors: Jumadi  , Fikriyah Vidya Nahdiyatul , Hadibasyir Hamim Zaky , Sunariya Muhammad Iqbal T. , Novitasari Dewi , Priyana Yuli , Umrotun  , Furoida Khusna , Madani Darin T. , Nursanto Dodik , Mokhtar Ainul Akmar Bt
Published: March 2024

The COVID-19 pandemic began at the end of 2019 and quickly spread over the planet. It began in Jakarta, Indonesia, in the beginning of March 2020. Jakarta saw the greatest number of confirmed cases during the initial pandemic year due to its dense population. This has sparked worries about the responsiveness of the city’s healthcare systems and accessibility to healthcare, which is crucial for regulating the dynamics of illness and death. To address the need for hospital beds, a number of hospitals in Jakarta have been designated COVID-19 healthcare centers. Studies on healthcare accessibility are generally accessible, however there is a dearth of studies examining the effects of healthcare accessibility given the severity of the COVID-19 epidemic. In the first year of the COVID-19 pandemic, this study intends to analyze the spatiotemporal dynamics of healthcare accessibility in relation to COVID-19 cases and its impact on case fatality rate (CFR). In order to compare the accessibility of COVID-19 healthcare with the monthly statistics of the COVID-19 infected population, two stages floating catchment area was adopted. Following the accessibility scores are analyzed using Product Moment Pearson correlation with the CFR to look at the relationship. This study’s findings indicate that there is only a weak negative link between healthcare accessibility and CFR, which is not statistically significant.
Comic Strip Media Assisted by Digital Gamification: Increasing Student Behavior Targets and User Engagement in the Learning Process
Authors: Laksana Sigit Dwi , Ariyanto Ayok , Tajab Moh. , Syam Aldo Redho , Sumaryanti Lilis
Published: March 2024

Comics multiplying must become the center of attention for educators, especially educators at the elementary school (SD) level. Seeing this, the world of education began to approach the comic media. Comic media has already started to be developed in the field of education, an expert in psychology who is famous for behavioristic theory, Edward Lee Thorndike, has researched comics, the results of this study reveal that a child is accustomed to reading comic books more than usual, for example within one month, the child reads a minimum of 1 comic book, this is the same as the child reading several textbooks every year, of course, this will affect reading skills/abilities for children and will increase mastery and vocabulary which is far more than usual. A child who doesn't like reading comics. It is by the expression. One picture is worth a thousand words, meaning that one image has the same value as a thousand words. Educational comic media is an innovative media that can be used as an alternative media to overcome learning difficulties for children, primarily covering matters related to material interests and understanding. Based on the distribution of learning outcomes in the experimental class, which obtained an average value of 73.79 (high) learning outcomes. While the results of the distribution of learning outcomes for the control class received an average value of learning outcomes of 47.75 (moderate). Based on the research conducted, the researcher obtained a value (Sig. (2-tailed)) of 0.000 <0.05, which means that comic strip media has a significant effect on student learning outcomes.
AI for awareness: Involvement in climate change in the Tangier-Tetouan-Al Hoceima region (Morocco)
Authors: Tahri Ayoub , Beroho Mohamed , Boulahfa Imane , Aboumaria Khadija
Published: March 2024

This study is the first to use the novel artificial intelligence tool, Bing Image Creator, to produce predictive imagery that clearly illustrates the catastrophic consequences of expected temperature changes in the Tangier-Tetouan-Al Hoceima (TTA) region by the end of this century. Our objective is to bring these impacts closer to decision makers while evaluating the model's ability to produce relevant images in line with the region's unique social, economic, and natural characteristics. The results showed that the model faithfully reproduced these characteristics, providing both a comprehensive and alarming view of the potential economic and environmental losses due to the probable temperature increases projected in the TTA region.
The evolution of Kariat Arekmane Coast (province of Nador-Morocco) diachronic study and evaluation of proposed solutions
Authors: Elallati Samia , Ben harra Abdessalam , Bouhadi Amine , Falouss Safae , Issa Lamiae Khali , Raissouni Ahmed , El arrim Abdlekrim
Published: March 2024

The coastline of the Nador region, in particular at Kariat Arekmane, is undergoing rapid changes influenced by natural and human factors, including submersion and erosion. An analysis of the coastline in this area has been performed in order to better understand these changes. The study began with a granulometric analysis, followed by a diachronic analysis of the coastline using the DSAS method in a GIS-ARCGIS environment. The results reveal significant variations in the study area, alternating between accretion and erosion. On average, the annual erosion rate is 0.66 m/year, while the accretion rate is 0.21 m/year. The average coastal change at Kariat Arekmane is 1.102 m/year, divided into two sectors: the first, undergoing severe erosion, comprises sandy shores and cliff areas, while the second, the western beach, benefits from accretion due to protective rock structures. The main causes of these coastal changes are coastal infrastructures and hydrodynamic forces. To solve this problem, several solutions for preserving Arekmane's coastline are currently being proposed and evaluated. Appropriate coastal management is essential to protect this region and mitigate the adverse effects of coastal erosion.
Analysis of Spatiotemporal Variation of Oceanographic Parameters in the North Atlantic of Morocco
Authors: Falouss Safae , Ben harra Abdessalam , Elallati Samia , Bouhadi Amine , Issa Lamiae Khali , Raissouni Ahmed , El arrim Abdlekrim
Published: March 2024

Analysis of the spatiotemporal evolution of oceanographic parameters such as sea surface temperature (SST) and chlorophyll concentration (CHL) in the North Atlantic between 2018 and 2022 revealed interesting seasonal and interannual trends. Seasonal variations in SST and CHL are associated with factors such as sunlight, winds, and ocean currents. These two parameters showed an inverse relationship caused by several factors, of which the coastal upwelling is the most important. Interannual variations are influenced by weather conditions, extreme climatic events, and changes in ocean currents. The study of the spatiotemporal evolution of these two parameters is essential to understand environmental changes, assess the state of health of marine ecosystems and predict future changes. It also contributes to the establishment of appropriate management measures for the conservation of ocean ecosystems and to assess the impact of environmental disturbances.
Diachronic Study of Coastal Vegetation Cover in Al Hoceima (Morocco): A Geospatial Analysis Using Remote Sensing and GIS
Authors: Mouddou Alae , Taher Morad , Etebaai Issam
Published: March 2024

Coastal ecosystems are vital land-sea interfaces that are necessary to sustain environmental stability and biodiversity. In many places, the complex network of vegetation cover serves as an essential buffer, preventing erosion, sustaining a variety of habitats, and enhancing ecological resilience overall The study utilizes advanced technologies like GIS, remote sensing, and Landsat images to analyze vegetation changes in Sfiha and Swani's coastal regions over the past 18 years, aiming to understand the impact of land use, climate fluctuations, and human activities on the landscape, Sophisticated remote sensing technology, Landsat satellite images, and Geographic Information System (GIS) tools are among the materials employed. During the designated period, the proportions of changes in the plant cover in the research area are determined and interpreted with the help of these resources. The study reveals significant changes in vegetation cover in Sfiha and Swani, revealing patterns of 21% (2003), 25% (2010), 33% (2015), and 15% (2021), providing insight into the temporal evolution of the coastal ecosystem and influencing conservation strategies and sustainable management practices. This study underscores the broader relevance of employing advanced spatial technologies for the monitoring and management of coastal ecosystems.Introduction
A modern method for building damage evaluation using deep learning approach - Case study: Flash flooding in Derna, Libya
Authors: Sellami El Mehdi , Rhinane Hassan
Published: March 2024

Year after year, floods become more and more a frequent and destructive force of nature, causing significant infrastructure losses and loss of life. An accurate and rapid assessment is required to determine the degree of contamination. The present study proposes a modern method for building damage assessment using deep learning during the flash flood of Derna, Libya. For this reason, we first exploited SAR satellite data, captured before and after the flood, to accurately determine the flood extent. Next, the footprint of affected buildings within this extent was extracted using a deep learning approach (U-Net model) based on high-resolution satellite imagery (30 cm) from MAXAR. Finally, an additional analysis was carried out using VIIRS VNP46A2 data (500 m spatial resolution) to analyse the night light assessment. The results demonstrate the effectiveness of this method, given that 5877 buildings were submerged by water and 2002 buildings were totally or partially destroyed. Also taking into account the estimated night light, Derna's power supply was reduced by over 90% after the floods. The suggested approach is an effective tool for comprehending the global effects of floods and aiding in relief efforts.
Catalysing water treatments: A Comprehensive Examination of sludge, its treatment and Energy Valorisation Solutions
Authors: Boularbah Zakaria , El Khoumsi Wafae , Bourziza Rqia , El Fellah Youness
Published: March 2024

The escalating production of sewage sludge in WasteWater Treatment Plant (WWTP) due to urban population growth and its management poses a substantial risk to the energetic and environmental efficiency of WWTP. This paper aims to explore the potential for sludge as a renewable energy source to reduce reliance on traditional energy through a systematic literature review of peer-reviewed articles and case studies. This overview demonstrated that various treatment methods such as anaerobic digestion, incineration, gasification, and pyrolysis are the most used and the most promising in terms of their energy outputs and effectiveness. The paper discussed the complexity of sludge composition, its financial burden on WWTP, and the crucial role in the success of these systems. Moreover, a comparative analysis of the different valorisation techniques was conducted that highlighted the energy production potential existing within each method and its underlying constraints while emphasising on the proper sludge management for overall efficiency. Finally, this paper recommended the need for sustainable, cost-effective approaches, considering legal standards for efficient WWTP.
Forensisch-psychiatrische Patient*innen mit Intelligenzminderung aus
Sicht der Behandler*innen – Wie strukturelle, systemische und diagnosebezogene
Besonderheiten Behandlung und Entlassung erschweren
Authors: Querengässer Jan , Reinhardt Isabelle , Zielasek Jürgen , Hufnagel Sylvia , Gouzoulis-Mayfrank Euphrosyne
Published: March 2024

In forensisch-psychiatrischen Kliniken werden auch Menschen gemäß § 63
Strafgesetzbuch behandelt, die auf der Grundlage einer Intelligenzminderung
straffällig geworden sind. Diese Patient*innengruppe weist überdurchschnittlich
lange Verweildauern auf und aus der Praxis werden spezifische Schwierigkeiten in
der Versorgung und der Überleitung in nachsorgende Systeme berichtet. Die
vorliegende Studie basiert auf einer inhaltsanalytischen Auswertung von zehn
strukturierten Interviews mit Behandler*innen unterschiedlicher Professionen,
die mit der Versorgung dieser Patient*innengruppe in der forensischen
Psychiatrie vertraut sind. Damit sollten Behandlungserfahrungen und
Herausforderungen der stationär-forensischen Versorgung dieser Gruppe sowie
Veränderungsbedarfe und Verbesserungsvorschläge erhoben werden. Die Befragten
bestätigten die aus anderen Studien bekannten spezifischen Behandlungsbedarfe
und personen- und diagnosebezogener Herausforderungen, die als ursächlich für
lange Verweildauern und Entlassprobleme eingeschätzt wurden. Es wurden auch
zahlreiche strukturelle und systemische Hürden benannt, die einer möglichst
kurzzeitigen forensisch-stationären Versorgung und einer nahtlosen Überleitung
ins nicht-forensische Nachsorgesystem im Wege stehen. Dazu zählen auf der
strukturellen Ebene der Bedarf an personellen Ressourcen (quantitativ wie
qualitativ) und adaptierten Behandlungskonzepte. Professionelle Nachsorge wurde
bei dieser Patient*innengruppe als sehr wichtig eingeschätzt. Diesbezüglich
wurden die Nicht-Verfügbarkeit geeigneter Institutionen, lange Wartelisten und
Vorbehalte seitens dieser Einrichtungen gegenüber ehemals forensischen
Patient*innen problematisiert. Dass sich Patient*innen mit Intelligenzminderung
gegenüber anderen Patient*innen schlechter durchsetzen könnten und dadurch oft
weniger Aufmerksamkeit von den Behandler*innen erhielten, kann als systemische
Hürde bezeichnet werden. Dies gilt auch für die (zu) hohen Anforderungen, die
das forensische System mit seinem Ziel einer „Besserung“ durch Behandlung auch
an Menschen mit Intelligenzminderung stelle. Die in der Studie ermittelten
Befunde können genutzt werden, um auf systemischer und struktureller Ebene zu
einer Verbesserung der forensisch-stationären Versorgungssituation von Menschen
mit Intelligenzminderung beizutragen.