bluuebunny/crossref_metadata_2025_split huggingface dataset:
Static and dynamic magnetization models of magnetic nanoparticles: an appraisal
Authors: Yari Parsa , Chugh Vinit Kumar , Saha Renata , Tonini Denis , Rezaei Bahareh , Mostufa Shahriar , Xu Kanglin , Wang Jian-Ping , Wu Kai 
Published: July 2023

Abstract
Nowadays, magnetic nanoparticles (MNPs) have been extensively used in biomedical fields such as labels for magnetic biosensors, contrast agents in magnetic imaging, carriers for drug/gene delivery, and heating sources for hyperthermia, among others. They are also utilized in various industries, including data and energy storage and heterogeneous catalysis. Each application exploits one or more physicochemical properties of MNPs, including magnetic moments, magnetophoretic forces, nonlinear dynamic magnetic responses, magnetic hysteresis loops, and others. It is generally accepted that the static and dynamic magnetizations of MNPs can vary due to factors such as material composition, crystal structure, defects, size, shape of the MNP, as well as external conditions like the applied magnetic fields, temperature, carrier fluid, and inter-particle interactions (i.e., MNP concentrations). A subtle change in any of these factors leads to different magnetization responses. In order to optimize the MNP design and external conditions for the best performance in different applications, researchers have been striving to model the macroscopic properties of individual MNPs and MNP ensembles. In this review, we summarize several popular mathematical models that have been used to describe, explain, and predict the static and dynamic magnetization responses of MNPs. These models encompass both individual MNPs and MNP ensembles and include the Stoner-Wohlfarth model, Langevin model, zero/non-zero field Brownian and Néel relaxation models, Debye model, empirical Brownian and Néel relaxation models under AC fields, the Landau–Lifshitz–Gilbert (LLG) equation, and the stochastic Langevin equation for coupled Brownian and Néel relaxations, as well as the Fokker–Planck equations for coupled/decoupled Brownian and Néel relaxations. In addition, we provide our peers with the advantages, disadvantages, as well as suitable conditions for each model introduced in this review. The shrinking size of magnetic materials brings about a significant surface spin canting effect, resulting in higher anisotropy and lower magnetization in MNPs compared to bulk materials. Accurate prediction of static and dynamic magnetizations in MNPs Requires both precise data on their magnetic properties and an accurate mathematical model. Hence, we introduced the spin canting effect and models to estimate anisotropy and saturation magnetization in MNPs.
Direct speech reconstruction from sensorimotor brain activity with optimized deep learning models
Authors: Berezutskaya Julia , Freudenburg Zachary V , Vansteensel Mariska J , Aarnoutse Erik J , Ramsey Nick F , van Gerven Marcel A J 
Published: July 2023

Abstract

Objective. Development of brain–computer interface (BCI) technology is key for enabling communication in individuals who have lost the faculty of speech due to severe motor paralysis. A BCI control strategy that is gaining attention employs speech decoding from neural data. Recent studies have shown that a combination of direct neural recordings and advanced computational models can provide promising results. Understanding which decoding strategies deliver best and directly applicable results is crucial for advancing the field. Approach. In this paper, we optimized and validated a decoding approach based on speech reconstruction directly from high-density electrocorticography recordings from sensorimotor cortex during a speech production task. Main results. We show that (1) dedicated machine learning optimization of reconstruction models is key for achieving the best reconstruction performance; (2) individual word decoding in reconstructed speech achieves 92%–100% accuracy (chance level is 8%); (3) direct reconstruction from sensorimotor brain activity produces intelligible speech. Significance. These results underline the need for model optimization in achieving best speech decoding results and highlight the potential that reconstruction-based speech decoding from sensorimotor cortex can offer for development of next-generation BCI technology for communication.
Food and lifestyle impact on breath VOCs using portable mass spectrometer—pilot study across European countries
Authors: Aleksić Milena , Simeon Andrea , Vujić Djordje , Giannoukos Stamatios , Brkić Boris 
Published: July 2023

Abstract
In the modern world, many people are changing old dietary and lifestyle habits to improve the quality of their living—to treat or just prevent possible diseases. The main goal of this pilot study was to assess the food and lifestyle impact on exhaled breath volatile organic compounds (VOCs) in various population groups. It was done by employing a recently validated portable membrane-inlet mass spectrometer—MIMS. Thus, the obtained results would also represent the additional confirmation for the employment of the new instrument in the breath analysis. The pilot study involved 151 participants across Europe, including people with overweight, obesity, type 2 diabetes mellitus, cardiovascular disease, people with poor-quality diet and professional athletes. Exhaled breath acetone, ethanol, isoprene, and n-pentane levels were determined in samples before the meal, and 120 min after the meal. Obtained basal ppbv values were mainly in accordance with previously reported, which confirms that MIMS instrument can be used in the breath analysis. Combining the quantified levels along with the information about the participants’ lifestyle habits collected via questionnaire, an assessment of the food and lifestyle impact was obtained. Notable alteration in examined VOC levels upon meal consumption was detected in more than 70% of all participants, with exception for isoprene, which was affected in about half of participants. Lifestyle parameters impact was examined using statistical analysis of variance (ANOVA) on ranks test. Statistically significant differences in basal breath VOC levels were observed among all examined population groups. Also, n-pentane and ethanol levels significantly differed in people of different ages, as well as acetone levels in people with different physical activity habits. These findings are promising for further, more focused research using MIMS technique in breath analysis.
Is it possible to achieve High-Quality Concrete with Partial Substitution of Fly Ash?
Authors: Rahman Mohammad Junaedy , Arfandi Anas , Pangestu Gangsar 
Published: July 2023

Abstract
This study aims to determine the characteristics of high-quality concrete using fly ash as a partial replacement for PCC cement. Tests include slump testing, density factor and concrete compressive strength testing. Two variations of the concrete mix are made, namely the variation without fly ash and the 15% fly ash mixture. The results of this study indicate that the characteristics of concrete with fly ash substitution require the same amount of water as the concrete without fly ash to achieve the desired slump value. The density factor values obtained are also the same. In the concrete compressive strength test, the variation of the 15% fly ash mixture was higher than that of the 0% fly ash mixture.
Analysis of Bioactive Compounds Content and Toxicity Test on Mangrove Leaf Extract
Authors: Fadilah Ratnawaty , Sukainah Andi , Taufieq Nur Anny Suryaningsih , Putra Reski Praja , Adriani Mimi 
Published: July 2023

Abstract
Mangroves are plants that have a significant role in coastal areas, which also contain various bioactive components. Although it is rich in bioactive compounds, its utilization is still minimal. For this excuse, it is crucial to study and analyze the mixtures of bioactive compounds and toxicity tests on some mangrove leaf extracts. This research aimed to specify the content and toxicity of bioactive compounds of several mangrove leaf extracts. The procedures of the research consist of sampling and sample preparation, extraction with 70% alcohol, the Brine Shrimp Lethality Test (BSLT) toxicity testing, and data analysis using probit analysis. The bioactive compounds were measured by qualitative research. The results showed that four mangrove extracts (Avicennia sp., R.apiculata, A.illicifolius, and S.alba) had moderate toxic content. Avicennia sp. has the lowest LC50 value of 4.87 μg / ml. Four types of mangroves have a bioactive range, as well as saponins, flavonoids, alkaloids, tannins, and phenolic compounds.
Domestic Waste Management Study of Community Based in Kupang City
Authors: Ramang Ruslan , Dirawan Gufran Darma , Ruslan Rusneni 
Published: July 2023

Abstract
This research aims to find the existing waste management system and create a development model of waste technology management. Besides, this study will focus specifically on the variables that influence participatory community-based waste management technology. This study uses descriptive analysis crosstab and chi-square. The data collected using distributing questionnaires and interviews with respondents randomly. The results of this study are mostly waste generated by society and less managed well. The integration of variable dimensions of public participation can cultivate people’s willingness to reduce waste generation. Community participation can increase recycling and composting activities that waste going into a landfill can be reduced. Variable work and income results have a relationship with the waste that the people in Kupang did sorting. Simultaneously, the variables age, gender, education, type of housing, and the number of people do not have a significant relationship with waste sorting. Not all respondents addressed the garbage by the janitor, so most of them deal with their waste by burning and dispose of vacant land.
The Analysis of Mercury Concentrations of Water in Gold Mining Environment at Poboya, East Palu Subdistrict, Palu, Central Sulawesi Province
Authors: Okviyani Nur , Trimahyuni Enni , Al Faizah Ma’rif A. 
Published: July 2023

Abstract
Gold mining activities influence the environment, mainly the aquatic environment, due to the heavy metal and mercury detected in settling pond and river waters. Based on laboratory analysis, it is known that Mercury concentrations in settling pond water of inlet, transition, and outlet zones respectively are 0.075 mg/L, 0.042 mg/L, and 0.027 mg/L. These are shown that mercury concentration in water was not passed Government Regulation of the Minister of Environment No. 202 the year 2004 about quality standards of liquid waste, which said that the standard is 0.005 mg/L. The Heavy metal concentrations, especially mercury in river water at 1, 2, 3, 4, and 5 stations respectively, are 0.004 mg/L, 0.009 mg/L, 0.050 mg/L, and 0.006 mg/L, which do not meet the government regulation of water quality standard 0.001 mg/L.
Modeling and Simulation of High-Temperature Heat Pump Combined with Solar Energy
Authors: Djuanda  , Pasek Ari Darmawan , Tandian Nathanael P. 
Published: July 2023

Abstract
Heat pumps can utilize various sources of heat to increase the temperature of a room or water. This study uses solar energy as a heat source for high-temperature heat pumps. The type of heat pump used is a vapor compression heat pump and is used to produce steam. The study created a model and simulation of a heat pump combined with solar energy. System modeling is divided into three subsystems: solar collector, thermal storage, and a heat pump—the WinDali program used in heat pump simulation. The Simulation results show a close relationship between solar intensity and system performance. The maximum COP obtained is 1.32. The heat pump can generate steam for 7.25 hours, and the lifted temperature obtained is 28°C.
The Preliminary Microwave Metamaterial Absorber Based on Ring-Shaped for Stealth Technology
Authors: Yudistira Hadi Teguh , Kananda Kiki 
Published: July 2023

Abstract
Controlling electromagnetic waves on the material is needed by several applications such as sensors, stealth technology, and energy harvesting. An artificial material that could control electromagnetic waves is called metamaterial. Meanwhile, a metamaterial absorber can absorb the electromagnetic wave. Two concepts can be used to explain the absorbing phenomena on metamaterial absorber: the matching impedance of the air and the part of the imaginary that is high of the index of refractive collectively or the theory of interference that is destructive. The correlation of matching air impedance with destructive interference theory has been found by Yudistira in his previous works. In this study, the preliminary research of metamaterial absorbers based on ring shape is presented. The 40 mm, 35 mm, 30 mm, and 25 mm ring-shaped widths are applied to this work. We used numerical simulation work to understand the performance of metamaterial absorbers based on ring-shaped. CST microwave studio was used for numerical simulation work. The absorbance peak results for w=20, w=17.5, w=15, and w=12.5 mm are 0.92 at 3.43 GHz, 0.95 at 3.7 GHz, 0.95 at 4.04 GHz and 0.99 at 4.47 GHz, severally. The maximum absorbance is yielded to 0.99 absorbances for 25 mm of the width of the ring-shaped.
The Implementation of Classification and Spectral Transformation Methods, Based on Extraction Landsat Imagery for Growth Center Mamminasata Region
Authors: Rasyidi Emil Salim , Arief Rimba , Taking Muh. Idris 
Published: July 2023

Abstract
Urban growth begins from a center and affects its surrounding area, and this is due to the emergence of additional centers that will serve as a growth pole. Assessment of the dynamics of urban growth, some data, and extraction analysis methods are needed. This research examines various information by extracting of growth center area of Landsat 8 OLI / TIRS 2017 and utilizing spectral resolution on Landsat images in the Mamminasata region. The classification method tested is the OBIA classification and the Maximum Likelihood classification methods. Simultaneously, the Landsat image’s spectral resolution is maximized by spectral channel transformation sensitive to the building object. It is usually called the urban index. This study indicates that the OBIA classification method and NDBI spectral transformation proved to produce maps. It can also show center location growth with the best accuracy, especially in the Mamminasata region. Total accuracy from the accuracy-test matrix is 71.48% for building intensity and 78.57% for growth centers.
Artificial Climate Prototype for IoT-Based Vines
Authors: Fathahillah  , Zain Satria Gunawan , Andayani Dyah Darma 
Published: July 2023

Abstract
This climate manipulation prototype is a tool that helps monitor vine condition and automatically carries out the treatment. The design of this climate manipulation prototype can also make it easier to monitor and care for plants remotely. The plant state can be controlled with the android application which can display the condition of the plants in real-time. This type of research is research & development and uses a waterfall development model, which has stages: analysis, design, coding, and testing. Based on the results, a prototype of climate manipulation for IoT-based vines was produced. After designing the prototype, climate manipulation conducts quality testing based on functionality suitability testing. Testing aspects of functionality suitability using the black box testing method, carried out by two system experts where the test results are worth 1 with a very decent category and have met the functionality aspect.
Predicting metabolite–disease associations based on auto-encoder and non-negative matrix factorization
Authors: Gao Hongyan , Sun Jianqiang , Wang Yukun , Lu Yuer , Liu Liyu , Zhao Qi , Shuai Jianwei 
Published: July 2023

Abstract
Metabolism refers to a series of orderly chemical reactions used to maintain life activities in organisms. In healthy individuals, metabolism remains within a normal range. However, specific diseases can lead to abnormalities in the levels of certain metabolites, causing them to either increase or decrease. Detecting these deviations in metabolite levels can aid in diagnosing a disease. Traditional biological experiments often rely on a lot of manpower to do repeated experiments, which is time consuming and labor intensive. To address this issue, we develop a deep learning model based on the auto-encoder and non-negative matrix factorization named as MDA-AENMF to predict the potential associations between metabolites and diseases. We integrate a variety of similarity networks and then acquire the characteristics of both metabolites and diseases through three specific modules. First, we get the disease characteristics from the five-layer auto-encoder module. Later, in the non-negative matrix factorization module, we extract both the metabolite and disease characteristics. Furthermore, the graph attention auto-encoder module helps us obtain metabolite characteristics. After obtaining the features from three modules, these characteristics are merged into a single, comprehensive feature vector for each metabolite–disease pair. Finally, we send the corresponding feature vector and label to the multi-layer perceptron for training. The experiment demonstrates our area under the receiver operating characteristic curve of 0.975 and area under the precision–recall curve of 0.973 in 5-fold cross-validation, which are superior to those of existing state-of-the-art predictive methods. Through case studies, most of the new associations obtained by MDA-AENMF have been verified, further highlighting the reliability of MDA-AENMF in predicting the potential relationships between metabolites and diseases.
Durability of the First Biologic in Patients with Crohn’s Disease: A Nationwide Study from the epi-IIRN
Authors: Atia Ohad , Friss Chagit , Focht Gili , Magen Rimon Ramit , Ledderman Natan , Greenfeld Shira , Ben-Tov Amir , Loewenberg Weisband Yiska , Matz Eran , Gorelik Yuri , Chowers Yehuda , Dotan Iris , Turner Dan 
Published: July 2023

Abstract

Background
In this nationwide study we aimed to compare the durability of the first initiated biologic in Crohn’s disease [CD], stratified by monotherapy and combotherapy.

Methods
We used data from the epi-IIRN cohort, which includes 98% of the Israeli inflammatory bowel disease population [2005–2020]. Durability was defined as consistent treatment without surgery or added medications [except for combination therapy with thiopurines or methotrexate]. All comparisons were based on stringent propensity-score matching and paired time-to-event analyses.

Results
A total of 19 264 patients with CD were included, of whom 7452 [39%] received biologics with a median follow-up of 6.8 years (interquartile range [IQR] 3.6–10.7). Time to biologics decreased gradually from 6.7 years [IQR 2.7–10.4] in 2005 to 0.2 years [0.07–0.23] in 2020. The durability of the first biologic after 1 and 3 years was higher with adalimumab monotherapy [88%/61%] than vedolizumab monotherapy [81%/59%; n = 394 matched patients, p = 0.04] and similar between infliximab monotherapy and vedolizumab monotherapy [65%/43%; n = 182 matched patients, p = 0.1]. Durability was higher in adalimumab monotherapy vs infliximab monotherapy [83%/62% vs 71%/48% at 1/3 years; p &lt;0.001] and it was similar in adalimumab monotherapy vs infliximab combotherapy [87%/63% vs 80%/58%, respectively; p = 0.1]. Durability was higher in combotherapy compared with monotherapy for both infliximab [85%/64% vs 67%/43%, respectively; n = 496 matched pairs, p &lt;0.001], and adalimumab [93%/76% vs 82%/62%, respectively; n = 540 matched pairs, p &lt;0.001].

Conclusion
Durability of the first biologic in CD was highest for adalimumab monotherapy. Combotherapy further increased the durability of adalimumab and infliximab. Unless otherwise indicated, our data may support using anti-tumour necrosis factors [TNFs] as first-line biologics in CD, particularly adalimumab if monotherapy is advised.
Domains and residues of the Saccharomyces cerevisiae hnRNP protein Hrp1 important for transcriptional autoregulation and noncoding RNA termination
Authors: Goguen Emma C , Brow David A 
Published: July 2023

Abstract
Proteins that bind the nascent transcript exiting RNA polymerase II can regulate transcription elongation. The essential Saccharomyces cerevisiae hnRNP protein Hrp1 is one such protein and participates in both cleavage and polyadenylation-coupled and Nrd1-Nab3-Sen1-dependent RNA polymerase II termination. Prior evidence that Hrp1 is a positive RNA polymerase II elongation factor suggests that its release from the elongation complex promotes termination. Here we report the effects of deletions and substitutions in Hrp1 on its autoregulation via an Nrd1-Nab3-Sen1-dependent transcription attenuator in the 5′-UTR of its mRNA and on the function of an Hrp1-dependent Nrd1-Nab3-Sen1 terminator in the SNR82 snoRNA gene. Deletion of either of two central RNA recognition motifs or either of the flanking low-sequence complexity domains is lethal. Smaller, viable deletions in the amino-terminal low-sequence complexity domain cause readthrough of both the HRP1 attenuator and SNR82 terminator. Substitutions that cause readthrough localized mostly to the RNA recognition motifs, although not always to the RNA-binding face. We found that autoregulation of Hrp1 mRNA synthesis is surprisingly robust, overcoming the expected lethal effects of the start codon and frameshift mutations via overexpression of the mRNA up to 40-fold. Our results suggest a model in which binding of attenuator or terminator elements in the nascent transcript by RNA recognition motifs 1 and 2 disrupts interactions between RNA recognition motif 2 and the RNA polymerase II elongation complex, increasing its susceptibility to termination.
Lipid metabolism in the immune niche of tumor-prone liver microenvironment
Authors: Chen Jintian , Chan Thomas T H , Zhou Jingying 
Published: July 2023

Abstract
The liver is a common primary site not only for tumorigenesis, but also for cancer metastasis. Advanced cancer patients with liver metastases also show reduced response rates and survival benefits when treated with immune checkpoint inhibitors. Accumulating evidence has highlighted the importance of the liver immune microenvironment in determining tumorigenesis, metastasis-organotropism, and immunotherapy resistance. Various immune cells such as T cells, natural killer and natural killer T cells, macrophages and dendritic cells, and stromal cells including liver sinusoidal endothelial cells, Kupffer cells, hepatic stellate cells, and hepatocytes are implicated in contributing to the immune niche of tumor-prone liver microenvironment. In parallel, as the major organ for lipid metabolism, the increased abundance of lipids and their metabolites is linked to processes crucial for nonalcoholic fatty liver disease and related liver cancer development. Furthermore, the proliferation, differentiation, and functions of hepatic immune and stromal cells are also reported to be regulated by lipid metabolism. Therefore, targeting lipid metabolism may hold great potential to reprogram the immunosuppressive liver microenvironment and synergistically enhance the immunotherapy efficacy in the circumstance of liver metastasis. In this review, we describe how the hepatic microenvironment adapts to the lipid metabolic alterations in pathologic conditions like nonalcoholic fatty liver disease. We also illustrate how these immunometabolic alterations promote the development of liver cancers and immunotherapy resistance. Finally, we discuss the current therapeutic options and hypothetic combination immunotherapies for the treatment of advanced liver cancers.