bluuebunny/crossref_metadata_2025_split huggingface dataset:
Extreme Gradient Boosting algorithm classification for predicting lifespan-extending chemical compounds
Authors: Yarmolenko Mariia , Howlin Brendan 
Published: October 2022

Abstract
Human ageing has a great impact on global economy and society’s health with the risk factors for many chronic diseases. Discovery of the pharmaceutical interventions with the potential of promoting longevity and delaying the onset of age-associated diseases is one of the most challenging tasks in anti-ageing research today.
The aim of this study was to build a new machine learning model based on the data of the DrugAge database to predict whether a chemical compound will extend the lifespan of the worm species Caenorhabditis elegans. The predictive models were built using the optimized Extreme Gradient Boosting algorithm with molecular fingerprints and molecular descriptors as features. The ranking of the models’ features was done with the built-in Extreme Gradient Boosting feature importance function and interpreted with confidence using Shapley values. The top 15 most important features included 2D molecular descriptors related to the subdivided surface areas, atom and bond counts, and electrostatic properties. The best performing model was applied to predict the class of compounds in the external database, DrugBank, consisting of approved small-molecules. The chemical compounds of the external database with a predictive probability of for increasing the lifespan of Caenorhabditis elegans were broadly separated into (i) flavonoids and isoflavonoids, (ii) fatty acids and conjugates, and (iii) other classes of compounds.
Low-Tech Passive Solar Design Concepts for reducing Life Cycle GHG Emissions of Buildings - Life Cycle Assessment of Regenerative Design Strategies (2/2)
Authors: Mouton Lise , Trigaux Damien , Allacker Karen , Röck Martin 
Published: October 2022

Abstract

In order to achieve the necessary reduction of greenhouse gas (GHG) emissions and decarbonization of building construction and operation, both high- and low-tech building design strategies are promoted. Amongst particularly promising strategies are the deployment of energy efficiency measures, for reducing operational energy use and related impacts, as well as the application of low-carbon, bio-based construction materials, for reducing embodied impacts. In part two of our study on the life cycle assessment (LCA) of regenerative design strategies, LCA is applied to investigate the environmental impacts and reduction potentials of strategies at building level by analyzing two low-tech, passive building concepts – the be2226 building and the N11 SolarHouse – in both their original designs as well as optimized alternatives applying bio-based material solutions. The analysis includes three steps. In a first step the life cycle GHG emissions of the original buildings are assessed, revealing strengths and weaknesses on both operational and embodied GHG emissions. Environmental hotspots are identified across environmental indicators, life cycle stages and building elements. In a second step the case studies are remodeled with bio-based building element alternatives showing substantial embodied GHG emissions reduction potential compared to the original case studies. Finally, the results of all building variants are compared with climate targets for buildings revealing that the N11 building meets established climate targets already in its original version, and that a straw-based material optimization can even enable meeting more ambitious climate targets.
Carbonate system in the Cabo Frio upwelling
Authors: Silva Carlos Augusto Ramos e , Fernandes Livia Viana de Godoy , de Souza Flavo Elano Soares , Marotta Humberto , Fernandes Flavio da Costa , Mello Thaise Machado Senez , Monteiro Nicole Silva Caliman , Rocha Anderson Araújo , Damasceno Raimundo Nonato , Santos Ludmila Caetano dos 
Published: October 2022

Abstract
The quantitative assessment of the carbonate system represents one of the biggest challenges toward the "Sustainable Development Goals" defined by the United Nations in 2015. In this sense, the present study investigated the Spatio-temporal dynamics of the carbonate system and the effects of the phenoms ENOS and ENSO over the Cabo Frio upwelling area. The physical characterization of the site was carried out through data on wind speed and sea surface temperature (SST). Water samples were also collected during the oceanographic cruise onboard the Diadorim Oceanographic Research Vessel. From these samples, the parameters of absolute and practical salinity, density, pH, total alkalinity, carbonate, calcite, aragonite, \(C{O}_{3}^{2-}\), \(HC{O}_{3}^{-}\), dissolved inorganic carbon, carbon dioxide, partial pressure of carbon, calcium, and total boron were obtained. After the physical-chemical survey described above, the same parameters were calculated through thermodynamic modeling with the Marine Chemical Analysis (AQM) software loaded with temperature, salinity, TA, and pH parameters. This manuscript presents original data on the carbonate system and the "acidification" process influenced by the Cabo Frio upwelling, which directly depends on the El Niño and La Niña phenomena oscillations in the sea surface temperature (SST).
FusionPDB: a unique knowledgebase of human fusion proteins of consistent annotation across genome/ transcript/ protein/ interaction levels
Authors: Kumar Himansu , Tang Lin-Ya , Yang Chengyuan , Kim Pora 
Published: October 2022

Abstract

Tumorigenic functions due to the formation of fusion genes were targeted for cancer therapeutics (i.e., kinase inhibitors). However, there are still many fusion proteins awaiting being targeted for therapeutics with multiple different mechanisms. Due to the lack of knowledge of the fusion protein sequence and 3D structure, there were not many studies available. To fill this gap, we developed a new computational pipeline and a resource of human fusion proteins, named FusionPDB available at https://compbio.uth.edu/FusionPDB. FusionPDB provides ~ 42K fusion protein sequences (of 16K in-frame fusion genes), 2300 + 1267 fusion protein 3D structures (of 2300 recurrent in-frame fusion genes and 266 manually curated in-frame fusion genes), and virtual screening results of 1267 fusion proteins. FusionPDB is the only resource providing whole 3D structures of fusion proteins and comprehensive knowledge of human fusion proteins. It will be regularly updated until covering all human fusion proteins in the future.
Comparison of bankruptcy methods in the operation management of the Karkheh River Basin to allocate more water to the Hawr-Al-Azim Wetland
Authors: Pournabi Nima , Janatrostami Somaye , Ashrafzadeh Afshin , Mohammadi Kourosh 
Published: October 2022

Abstract
Bankruptcy methods are straightforward practical methods to address the problem of allocating limited sources of water to different users in regions where claims exceed assets. In the present study, three levels of restoration for the Hawr-Al-Azim wetland (35, 50, and 100%) and two agricultural-related scenarios, maintaining the current cultivation area and decreasing the area under cultivation, were considered and assessed using classical bankruptcy methods. The results showed that, because of climatic conditions and agricultural demands, full wetland restoration was out of reach and led to minimum satisfaction levels for agricultural beneficiaries. The results also showed that the modified bankruptcy method led to the highest satisfaction levels for beneficiaries in the scenario of maintaining the current cultivation area. In addition, the percentage of the water supply was increased by applying the scenario of crop restriction in the conditions of the full restoration of the wetland; for example, in the Abbas Plain region, this increase was achieved by almost 10–15% in all methods. On the other hand, decreasing the area under cultivation shifted the allocation problem in the basin to a non-bankruptcy one.
The effect of pH on taste and odor production and control of drinking water
Authors: Adams Hunter , Burlingame Gary , Ikehata Keisuke , Furatian Laith , Suffet I. H. (Mel) 
Published: October 2022

Abstract
There is general agreement that pH is an important parameter in many drinking water treatment and control processes such as taste and odor (T&O) control. However, pH is not usually targeted as a primary control parameter and its effects on T&O are often overlooked in favor of other treatment issues. When it comes to T&O control, treatment alternatives typically focus on oxidation and adsorption processes. Whether within these processes or separately, pH plays an important role and the effects on T&O should be considered. For example, pH plays a role in the speciation of odorous chemicals in the environment, some of which arise in wastewater treatment and others from the occurrence of metals in water. During blooms of algae and cyanobacteria in surface water, pH is an important parameter affecting water quality and T&O. Finally, as pH is important for the sample preservation and analysis of T&O compounds, pH is important in the fate and control of T&O. The objective of this article is to better understand the various ways that pH can influence T&O production, control, and analysis of odorants in water and encourage advancement in the state of the science of pH optimization for T&O control.
Performance evaluation of univariate time-series techniques for forecasting monthly rainfall data
Authors: Kabbilawsh P. , Kumar D. Sathish , Chithra N. R. 
Published: October 2022

AbstractIn this article, the performance evaluation of four univariate time-series forecasting techniques, namely Hyndman Khandakar-Seasonal Autoregressive Integrated Moving Average (HK-SARIMA), Non-Stationary Thomas-Fiering (NSTF), Yeo-Johnson Transformed Non-Stationary Thomas-Fiering (YJNSTF) and Seasonal Naïve (SN) method, is carried out. The techniques are applied to forecast the rainfall time series of the stations located in Kerala. It enables an assessment of the significant difference in the rainfall characteristics at various locations that influence the relative forecasting accuracies of the models. Along with this, the effectiveness of Yeo-Johnson transformation (YJT) in improving the forecast accuracy of the models is assessed. Rainfall time series of 18 stations in Kerala, India, starting from 1981 and ending in 2013, is used. A classification system based on root mean square error (RMSE), mean absolute error (MAE) and Nash–Sutcliffe model efficiency coefficient (NSE) is proposed and applied to find the best forecasting model. The models HK-SARIMA and YJNSTF performed well in the Western lowlands and Eastern highlands. In the Central midlands, out of 12 stations, the performance indices of 8 stations are in favour of the HK-SARIMA model. It can be concluded that HK-SARIMA models are more reliable for forecasting the monthly rainfall of the stations located in all geographic regions in the state of Kerala.
Comparison of multi-objective genetic algorithms for optimization of cascade reservoir systems
Authors: Wang Manlin , Zhang Yu , Lu Yan , Wan Xinyu , Xu Bin , Yu Lei 
Published: October 2022

Abstract
Multi-objective genetic algorithms (MOGAs) are widely used for multi-reservoir systems’ optimization due to their high efficiency and fast convergence. However, the computational cost grows exponentially with the expansion of multi-reservoir systems and the increased dimensions of optimization problems, posing a great challenge to multi-reservoir operations. Therefore, it is important to find a suitable and efficient multi-objective algorithm for multi-reservoir system optimization. In this study, three representative MOGAs were selected, namely the Non-dominated Sorting Genetic Algorithm II (NSGA-II), Non-Dominated Sorting Genetic Algorithm III (NSGA-III), and Reference Vector Guided Evolutionary Algorithm (RVEA), and three multi-objective optimization models were then developed accordingly. Numerical experiments were conducted to evaluate the performance of these three algorithms for the optimization of a cascaded reservoir system. The results show that for the two-objective model, the non-dominant size generation rate (NDSGR) of NSGA-II is 1.66 and 4.01 times that of NSGA-III and RVEA, respectively. NSGA-II is more suitable for solving the optimization operation problem with two objectives. Based on the comprehensive evaluation, NSGA-III seems to be more appropriate for more than two objectives. These results emphasize the importance of using appropriate algorithms and provide further insights into the choice of algorithms for the optimization of hydropower systems.
Water, sanitation, and hygiene access in Senegal and its impact on the occurrence of diarrhea in children under 5 years old
Authors: Daffe Mouhamadou Lamine , Diop Cheikh , Dounebaine Bonheur , Diop Samba Sagor , Peleka Jessica Carmelia Mbemba , Bah Fatoumata , Thiam Salimata , Ndong Awa , Cabral Mathilde , Toure Aminata , Lam Absa , Fall Mamadou 
Published: October 2022

Abstract
Diarrheal diseases are the second leading cause of child mortality worldwide, occurring in about one in every nine child deaths, and were associated with water, sanitation, and hygiene (WASH) access. In this study, we provided an overview of WASH indicators' evolution from 2000 to 2017 and their impact on the occurrence of diarrhea in children under 5 years old in Senegal. It was a retrospective cross-sectional study, in which we did a secondary analysis of data from the Joint Monitoring Program (JMP) for water supply and sanitation and from the Senegal Demographic and Health Survey 2018. Our results showed that access to safely managed services increased by 18.1 and 19.1%, respectively, for water and sanitation. The prevalence of diarrhea estimated at 18.16% was associated with straining water through a cloth (adjusted odds ratio (AOR) [95% confidence interval (CI)]: 1.21 [1.00–1.45]) and getting water supplies from a source not located in a dwelling (AOR [95% CI]: 1.59 [1.21–2.09]). The prevalence of diarrhea among children under 5 years old was still relatively high in Senegal and was significantly associated with a lack of WASH access. Although the latter continues to increase, additional efforts to make water safer to drink will significantly reduce the occurrence of diarrheal diseases among children under 5 years old in Senegal.
Eficiencia productiva en cerdos de levante alimentados con materias primas alternativas de países tropicales: meta-análisis
Authors: Agudelo Quintero Janeth , Mesa-Granda Martha 
Published: October 2022

Se comparó la eficiencia productiva de concentrados comerciales con materias primas alternativas de países tropicales en cerdos de levante. Para la recolección de los datos se buscó información en artículos científicos indexados en la Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc) con palabras claves como “porcinos” “levante” “alimentación alternativa” “producción” “ganancia diaria” “conversión alimenticia”, trabajando los artículos encontrados mediante la metodología PRISMA. Se tuvo en cuenta los siguientes criterios de elegibilidad: revistas indexadas en idioma español, inglés, portugués y francés con artículos científicos completos sin importar el periodo de publicación. Porcinos en levante y cuya alimentación tuviera como base materias primas alternativas. Análisis de los parámetros productivos (consumo, ganancia de peso, conversión alimenticia). Validación de la eficiencia productiva de dichas materias primas alternativas mediante diseños experimentales y análisis estadístico. Como principales resultados de la revisión sistemática se encontró diferencia estadística significativa entre tratamientos (p<0,05), en cuanto al consumo y ganancia de peso al usar desechos animales se obtiene menor consumo y menor ganancia de peso, siendo similar el desempeño productivo al obtenido con animales alimentados con concentrado comercial. Las oleaginosas son las materias primas que, aunque no tienen un mayor consumo presentan la mejor ganancia de peso en los animales y por consiguiente mejor desempeño productivo (conversión alimenticia). Por ser países tropicales se tuvieron en cuenta las forrajeras y subproductos que, aunque no tienen un buen desempeño productivo pueden desarrollarse nuevas investigaciones desde costos productivos para determinar si realmente se pueden disminuir los gastos en alimentación con la inclusión de estas materias primas alternativas en las raciones de cerdos en etapa de levante.
Time Domain (TD) NMR Proton (1H) Mobility Sensor to Assess Oil Quality and Oxidation
Authors:   Ben Gurion University of the Negev, Wiesman Zeev , Linder Charles ,   Ben Gurion University of the Negev, Esfahanian Maliheh ,   Carnegie Institution for Science
Published: October 2022

The induction phase is the first step of oxidation, after which initiation phase occurs and is characterized by 1H abstraction and increasing peroxide levels. Later, the propagation cascade phase is generated with significant chemical and structural modification of the oil's fatty acids, causing increased concentrations of aldehydes. The process is terminated by the formation of toxic polymerization end products. A rapid and efficient analytical method of the different steps of oil oxidation are herein describe. Using a TD 1H NMR sensor capable of measuring proton mobility, it is possible to follow the segmental motion of the 1H population in each of the oil's segments, as well as describing the proton relaxation signals generated from the magnetic field that can measure and characterize important chemical and physical properties of the tested sample. In our research group's recent work, we demonstrated the ability to quantitatively measure the rates of self-diffusion (D) as well as ILT T1 and T2 spectral fingerprints of heated oils to correlate these values with chemical and morphological changes during oxidation. To simplify and reduce the time required for characterizing oil quality and oxidation using a TD 1H NMR sensor the present study focused on the relationship between D and the thermal and air conditions for enhancing oil oxidation. An excellent (R2>0.95) correlation of D with oil oxidation's conventional colorimeter standard tests (e.g., PV, p-Anisidine and TOTOX) was shown. These results were obtained from a high temperature (80°C) oxidation study of a list of saturated, monounsaturated and polyunsaturated edible oils (linseed, soy, olive, coconut, butter, respectively). The study clearly showed that self-diffusion D values, reflecting the mobility of 1H protons, is an accurate and rapid (< 1 minute) marker/indicator for the oil's quality with emphasis on the oils oxidation status, that be measured and used in the oil industry.
Updates on hydrothermal cleanup (HCU) pretreat
Authors:   Applied Research Associates, Goodwin Jocelyn 
Published: October 2022

Applied Research Associates developed the Hydrothermal Cleanup (HCU) Pretreat process to remove phosphorus and metals from fats, oils, and greases. HCU Pretreat is a continuous-flow process that hydrolyzes phospholipids to water-soluble salts and reduces residual phosphorus content from hundreds of ppm to less than 2 ppm in less than two minutes of residence time. Because phospholipids are hydrolyzed, fatty acids are retained and product yield is maximized, and no waste gums or solids are produced. Metals that are present, mostly in the form of soaps of fatty acids, are simultaneously reduced from hundreds of ppm to less than 10 ppm total. Two ARA HCU Pretreat units are under construction and a third unit is in detailed design. ARA expects its first HCU Pretreat unit to be operational in the summer of 2022 and to have two additional units operating by the summer of 2023 with a total capacity of over 900 million gallons per year.
Renewable diesel pretreatment: Focus on soybean oil
Authors:   Crown Iron Works Co, Harrington Patrick 
Published: October 2022

Many Pretreatment operations for biofuels have focused on waste fats and oils due to their low carbon intensity, but a new wave of Soybean crushing plants takes aim at producing oil to meet the feedstock demand for the Renewable Diesel (RD) industry. Crown Iron Works, a leader in Soybean crushing and Soybean Oil Pretreatment technology, will explore these technologies and treated oil specifications from past, present, to future as they relate to biofuels and Renewable Diesel. As focus has increased on producing a Renewable-Diesel ready (RD ReadyTM) feedstock, innovations in Pretreatment are boosting process efficiency and yield while also helping shape new market trends.
Considering Clinician Competencies for the Implementation of Artificial Intelligence–Based Tools in Health Care: Findings From a Scoping Review
Authors: Garvey Kim V , Thomas Craig Kelly Jean , Russell Regina , Novak Laurie L , Moore Don , Miller Bonnie M 
Published: October 2022

Background
The use of artificial intelligence (AI)–based tools in the care of individual patients and patient populations is rapidly expanding.

Objective
The aim of this paper is to systematically identify research on provider competencies needed for the use of AI in clinical settings.

Methods
A scoping review was conducted to identify articles published between January 1, 2009, and May 1, 2020, from MEDLINE, CINAHL, and the Cochrane Library databases, using search queries for terms related to health care professionals (eg, medical, nursing, and pharmacy) and their professional development in all phases of clinical education, AI-based tools in all settings of clinical practice, and professional education domains of competencies and performance. Limits were provided for English language, studies on humans with abstracts, and settings in the United States.

Results
The searches identified 3476 records, of which 4 met the inclusion criteria. These studies described the use of AI in clinical practice and measured at least one aspect of clinician competence. While many studies measured the performance of the AI-based tool, only 4 measured clinician performance in terms of the knowledge, skills, or attitudes needed to understand and effectively use the new tools being tested. These 4 articles primarily focused on the ability of AI to enhance patient care and clinical decision-making by improving information flow and display, specifically for physicians.

Conclusions
While many research studies were identified that investigate the potential effectiveness of using AI technologies in health care, very few address specific competencies that are needed by clinicians to use them effectively. This highlights a critical gap.
Tối ưu hóa quy trình chiết xuất cao chiết giàu polyphenol và flavonoid có hoạt kháng vi khuẩn Vibrio spp. từ lá cây núc nác (Oroxylum indicum L.)
Authors: Võ Thị Tú Anh , Trần Chí Linh , Đỗ Minh Kha , Đái Thị Xuân Trang 
Published: October 2022

Phương pháp đáp ứng bề mặt được áp dụng để kiểm tra ảnh hưởng của các yếu tố chiết xuất đến hàm lượng polyphenol (TPC) và flavonoid (TFC) trong ​​lá núc nác (LNN). Điều kiện tối ưu được xác định để chiết xuất TPC và TFC là: nhiệt độ 59°C, ethanol 69%, thời gian 11 phút và tỷ lệ nguyên liệu/ dung môi là 1/25 (w/v). Quá trình chiết xuất được xác minh ở các điều kiện tối ưu đã được xác định. Các giá trị thực nghiệm (TPC=215,47±1,03 mg GAE/g cao chiết; TFC=158,01±1,12 mg QE/g cao chiết) cho thấy sự phù hợp tốt với giá trị dự đoán (TPC=214,09 mg GAE/g cao chiết; TFC=158,77 mg QE/g cao chiết). Hoạt tính kháng khuẩn của cao tối ưu LNN được nghiên cứu chống lại năm chủng Vibrio spp. (VC-1, VC-2, VC-3, VC-4, và VC-5). Cao tối ưu LNN có hoạt tính kháng khuẩn mạnh chống lại Vibrio spp. Nồng độ ức chế tối thiểu của cao tối ưu LNN dao động từ 320 đến 640 µg/mL. Kết quả nghiên cứu cho thấy nồng độ diệt khuẩn tối thiểu của cao tối ưu LNN dao động từ 640 đến 1280 µg/mL.