bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative evaluation of bioethanol fermentation process parameters using RSM, ANN and ANFIS
Authors: Taiwo Abiola E. , Musonge Paul 
Published: March 2023

AbstractThe drive for renewable energy as an alternative to fossil fuel is on the increase globally. Modeling a renewable energy process is crucial for increasing process monitoring and control of plant efficiency for the ultimate objective of optimal biorefinery operations. This study aims to develop and compare models that best predict the fermentation process parameters of bioethanol production using corn‐steep liquor (CSL) as a media supplement. The response surface method (RSM), artificial neural networks (ANNs) and adaptive neuro‐fuzzy inference system (ANFIS) were tested in the modeling of bioethanol fermentation processes. Box–Behnken design was used to investigate fermentation process parameters considering the effect of CSL (0.5–5.5 w/v), pH (4, 5), time (12–36 h), temperature (25–35°C) and inoculum size (0.5–5.5 v/v). The results from the kinetics study show media formulation with corn steep liquor results in a comparable yield with that substituted with yeast extract. The study shows that, for CSL, a maximum ethanol concentration of 17.40 g L−1 was obtained after 48 h of fermentation while 21.53 g L−1 was attained after 6 h for the media formulation with yeast extract. Based on the model evaluation using statistical error indices, ANN predictability was better at R2 = 0.90; R = 0.95; SEP = 1.73. The ANN models described the process better than ANFIS and RSM. This study shows the intelligent predictive ability of ANN that could be useful for the scale‐up process of ethanol production in industry. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.
Tuning fluorescence of dapoxetine by blocking of photoinduced electron transfer (PET): Application in real human plasma
Authors: Elsayed Mohamed Ahmed , Abbas Khaled Abdel‐Hakam , Abdelmontaleb Hani Shaaban , Mohamed Abobakr A. 
Published: March 2023

AbstractPhotoinduced electron transfer (PET) is the most common mechanism proposed to account for quenching of fluorophores. Herein, the intrinsic fluorescence of dapoxetine (DPX) hydrochloride is in the “OFF” state, owing to the deactivation effect of PET. When the amine moiety is protonated, the fluorescence is restored. Protonation of the nitrogen atom of the tertiary amine moiety in DPX leads to “ON” state of fluorescence due to hindrance of the deactivating effect of PET by protonation of the amine moiety. This permits specific and sensitive determination of DPX in human plasma [lower limit of quantification (LLOQ) = 30.0
]. The suggested method adopts protonation of DPX using 0.25 M hydrochloric acid in anionic micelles [6.94 mM sodium dodecyl sulfate (SDS)] leads to a marked enhancement of DPX‐fluorescence, after excitation at 290 nm.
Personality traits and disorders in Alzheimer's disease
Authors: Henriques‐Calado Joana 
Published: March 2023

AbstractBackgroundThe relationships between axis II personality disorders and the normative personality traits were explored in the context of current and pre‐morbid personality assessment in Alzheimer's disease (AD).MethodsThe study was conducted with four groups who were administered the NEO‐FFI and the PDQ‐4+, in the form of individual interview sessions. Current personality measure: consisting of 44 female participants (AD group) and, the control group, consisting of 80 female participants from the population at large. Pre‐morbid personality measure: AD group informants (n = 40); control group informants (n = 42).ResultsThe results are in line with the literature review and provide new research data. By factorial discriminant analysis, the current and pre‐morbid personality variables that differentiate AD from control groups are identified. The personality traits variables are the best discriminators such as low agreeableness, low openness to experience, and high neuroticism, suggesting that the maladaptive personality functioning can be described extending the range of psychopathology to a dimensional approach.ConclusionsThe study of personality variables seems to suggest, in their inclusion, the possibility to increase sensitivity toward an assessment in AD.
Exploration of the Production of Three Thiodiketopiperazines by an Endophytic Fungal Strain of Cophinforma mamane
Authors: Pacheco‐Tapia Romina , Ortíz Sergio , Jargeat Patricia , Amasifuen Carlos , Vansteelandt Marieke , Haddad Mohamed 
Published: March 2023

AbstractEndophytic fungi possess a versatile metabolism which is related to their ability to live in diverse ecological niches. While culturing under laboratory conditions, their metabolism is mainly influenced by the culture media, time of incubation and other physicochemical factors. In this study, we focused on the production of 3 thiodiketopiperazines (TDKPs) botryosulfuranols A−C produced by an endophytic strain of Cophinforma mamane isolated from the leaves of Bixa orellana L collected in the Peruvian Amazon. We studied the time‐course production of botryosulfuranols A−C during 28 days and evaluated the variations in the production of secondary metabolites, including the TDKPs, produced by C. mamane in response to different culture media, light versus dark conditions and different incubation times. We observed a short time‐frame production of botryosulfuranol C while its production was significantly affected by the light conditions and nutrients of the culture media. Botryosulfuranols A and B showed a similar production pattern and a similar response to culturing conditions. Molecular networking allowed us to detect three compounds related to TDKPs that will be the focus of future experiments.
Synthesis of Ester‐Linked Ursolic Acid‐Based Hybrid Compounds: Potential Antibacterial and Anticancer Agents
Authors: Khwaza Vuyolwethu , Oyedeji Opeoluwa O. , Oselusi Samson O. , Morifi Eric , Nwamadi Mutshinyalo , Tantoh Ndinteh Derek , Ramushu P. , Matsebatlela Thabe , Aderibigbe Blessing A. 
Published: March 2023

AbstractThe molecular hybridization of two or more drugs into a single molecule is an effective drug design approach to reduce pill burden and improve patient treatment adherence. Ursolic acid‐based hybrid compounds were synthesized and characterized followed by molecular docking studies. In vitro studies against various bacterial strains and human cancer cells (MDA‐MB‐231, HeLa, and MCF‐7) were performed. Compounds 14–19, 21, 34, 31, and 30 demonstrated significant antibacterial activities with MIC values of 15.625 μg/ml. Compounds 29 and 34 were more cytotoxic than ursolic acid, with IC50 values of 46.99 and 48.18 μg/ml. Compounds 29 and 34 in the docking studies presented favourable binding interactions and better docking energy against the Epidermal Growth Factor Receptor (EGFR) than the parent compound, ursolic acid. The findings revealed that the ursolic acid scaffold is a promising precursor for the development of molecules with promising anticancer and antimicrobial activities. However, more studies are needed to fully understand their mode of action.
Taking Synthetic Biology to the Seas: From Blue Chassis Organisms to Marine Aquaforming
Authors: Schada von Borzyskowski Lennart 
Published: March 2023

AbstractOceans cover 71 % of Earth's surface and are home to hundreds of thousands of species, many of which are microbial. Knowledge about marine microbes has strongly increased in the past decades due to global sampling expeditions, and hundreds of detailed studies on marine microbial ecology, physiology, and biogeochemistry. However, the translation of this knowledge into biotechnological applications or synthetic biology approaches using marine microbes has been limited so far. This review highlights key examples of marine bacteria in synthetic biology and metabolic engineering, and outlines possible future work based on the emerging marine chassis organisms Vibrio natriegens and Halomonas bluephagenesis. Furthermore, the valorization of algal polysaccharides by genetically enhanced microbes is presented as an example of the opportunities and challenges associated with blue biotechnology. Finally, new roles for marine synthetic biology in tackling pressing global challenges, including climate change and marine pollution, are discussed.
Protein Backbone Alteration in Non‐Hairpin β‐Turns: Impacts on Tertiary Folded Structure and Folded Stability
Authors: Harmon Thomas W. , Horne W. Seth 
Published: March 2023

AbstractThe importance of β‐turns to protein folding has motivated extensive efforts to stabilize the motif with non‐canonical backbone connectivity. Prior work has focused almost exclusively on turns between strands in a β‐sheet (i. e., hairpins). Turns in other structural contexts are also common in nature and have distinct conformational preferences; however, design principles for their mimicry remain poorly understood. Here, we report strategies that stabilize non‐hairpin β‐turns through systematic evaluation of the impacts of backbone alteration on the high‐resolution folded structure and folded stability of a helix‐loop‐helix prototype protein. Several well‐established hairpin turn mimetics are shown detrimental to folded stability and/or hydrophobic core packing, while less‐explored modification schemes that reinforce alternate turn types lead to improved stability and more faithful structural mimicry. Collectively, these results have implications in control over protein folding through chemical modification as well as the design of protein mimetics.
Ashwagandha‐induced acute liver injury: A case report
Authors: Tóth Marcell , Benedek Andrea E. , Longerich Thomas , Seitz Helmut‐Karl 
Published: March 2023

AbstractDrug‐induced liver injury became one of the most important liver disorders and diagnostic challenge for clinicians and pathologists. Here, we report a rare case of ashwagandha‐induced acute liver injury. The patient developed jaundice 2 weeks after starting ashwagandha intake and recovered within 5 months after withdrawal without any specific treatment.
Data Glove with Integrated Polyethylene‐Carbon Composite‐Based Strain Sensor for Virtual Reality Applications
Authors: Lee Kok Tong , Chee Pei Song , Lim Eng Hock , Kam Yu Heng 
Published: March 2023

AbstractA data glove enables fine motion control in virtual reality (VR). This work presents a cost‐effective data glove made of a commercial nylon‐based glove with integrated polyethylene‐carbon composites (Velostat). The resistance of the Velostat varies when a finger is bent. This piezoresistive behavior was explored by designing the Velostat as the strain sensor. The strain sensor was characterized for its flexure sensing by connecting it to a data acquisition circuit. The circuit is designed to process the output of the joint angles and feed it to the computer. A linear resistance output was measured with a sensitivity/gauge factor of 1.45 % per degree with a response time of 0.0158 seconds when the strain sensor bends from 0° to 30°. To control the 3D virtual hand's movement, the data glove was coupled with two inertial measurement unit sensors at the forearm and upper arm to identify its coordinates. The fabricated data glove successfully performs a proof‐of‐concept by picking‐and‐placing multiple objects in a VR environment.
Flow Field Simulation and Measurement in Packed Beds Based on 4D‐X‐Ray Computed Tomography
Authors: Martinez-Garcia Jorge , Fenk Benjamin , Gwerder Damian , Schiffmann David , Delgado-Diaz William , Stamatiou Anastasia , Fischer Ludger J. , Schuetz Philipp 
Published: March 2023

AbstractX‐ray computed tomography (XCT) combined with computational fluid dynamics (CFD) simulations have proved to be a powerful and versatile tool to describe fluids flow through packed bed systems. In this contribution, two examples of the application of XCT experiments to track the fluid flow and fluid penetration in packed bed systems are shown. The first one shows how geometrical information extracted from XCT measurements can be coupled to CFD simulations to assess fluid flows reliably. Here the example of a packed bed of three‐dimensional (3D) printed cylindrical‐shaped particles is considered. Finally, a short case study on the monitoring of the progress of the water penetration front in a packed bed composed of glass spheres using four‐dimensional (4D) XCT imaging data is presented.
Leaf temperatures and environmental conditions predict daily stem radial variations in a temperate coniferous forest
Authors: Weygint William A. , Eitel Jan U. H. , Maguire Andrew J. , Vierling Lee A. , Johnson Daniel M. , Campbell Colin S. , Griffin Kevin L. 
Published: March 2023

AbstractHourly‐resolved measurements of stem radial variations (SRVs) provide valuable insights into how climate‐induced changes in hydrological regimes affect tree water status and tree stem radial growth. However, while SRVs are easily measured at the individual tree level, currently no methods are available to monitor this phenomenon across broad regions at intra‐annual (daily to weekly) scales. Near‐surface (in situ) thermal remote sensing—with its sensitivity to plant water status—may provide an approach for monitoring intra‐annual SRVs, with the potential for scaling these approaches to the landscape level. Thus, we explored the suitability of in situ thermal remote sensing, in combination with other environmental data, to monitor SRVs in a coniferous forest of the North American Intermountain West. Specifically, we were interested in answering two main questions: Can we use in situ thermal remote sensing by itself and in combination with environmental variables (i.e., photoperiod, photosynthetically active radiation, and soil moisture) to predict (1) daily tree water status and (2) daily tree stem radial growth derived from SRVs? We used data collected by an environmental monitoring network in central Idaho over three growing seasons (2019–2021) to address these questions. Results showed that leaf temperature (TL) in combination with environmental variables explained up to three‐quarters of the SRV‐based variability in daily tree water status (in the form of tree water deficit [TWD]) and approximately one‐half of the variability in daily stem radial growth. The time of day when TL was acquired also appeared to change the strength, shape, and predictive power of the models, with acquisition times in the morning and evening showing stronger relationships with daily SRVs than other times of the day. Overall, these results highlight the promise of utilizing thermal remote sensing data to derive tree hydrological and growth status, and reveal key considerations (e.g., the time of data acquisition) for future observational and modeling efforts. This study also provides a benchmark against which to compare future efforts to test these observed relationships at coarser spatial scales.
Risk‐targeted importance factors for prescriptive seismic design of critical buildings
Authors: Badal Prakash S. , Sinha Ravi 
Published: March 2023

AbstractThe post‐earthquake recovery of a community depends on the ability of important buildings to perform their functions. Lifeline and other critical buildings that meet a predictable enhanced seismic performance increase the community's disaster risk management capacity. In prescriptive force‐based design standards, the seismic design force for these buildings is typically enhanced using an importance factor depending on the risk category. The present paper proposes an innovative framework based on performance‐based seismic design (PBSD) principles using risk‐targeted importance factors suitable for use with prescriptive standards. The framework decouples probabilistic assessments of building typologies to experts, while the structural designers can continue the conventional design approach. The framework explicitly considers probabilistic seismic demand, uncertainty in the performance of the building, and the inter‐building variation within a particular building typology in seismic performance. Six special reinforced concrete (RC) frame buildings conforming to Indian standards are selected to illustrate the framework. Sensitivity studies on parameter selection are used to establish the framework's robustness. An expression for the importance factors is also proposed. The use of the proposed importance factor expression is shown to meet a wide range of risk targets corresponding to different performance levels. The paper also proposes design factors for enhanced performance objectives suitable for the risk‐targeted prescriptive design. Further, the framework is implemented to estimate the seismic risk associated with existing building typology conforming to prevalent design standards. The assembly‐ and critical‐category RC buildings are found to require higher importance factors for achieving enhanced performance objectives than currently prescribed.
(Dis)connectivity in hydro‐geomorphic systems – emerging concepts and their applications
Authors: Poeppl Ronald E. , Polvi Lina E. , Turnbull Laura 
Published: March 2023

AbstractIn geomorphology, connectivity has emerged as a framework for understanding the transfer of water and sediment through landscapes. Over the past decade, sessions on (dis)connectivity at the General Assembly of the European Geosciences Union (EGU), and more recently, three mini‐conferences in 2020 and 2021 called ‘Connectivity Conversations’, organized by the International Association of Geomorphologists (IAG) working group on ‘Connectivity in Geomorphology’, have created a space for the exchange of ideas relating to (dis)connectivity in geomorphology and related disciplines. The result of these initiatives has been a collection of research articles related to a special issue (SI) entitled ‘(Dis)connectivity in hydro‐geomorphic systems – emerging concepts and their applications’. In this article, we provide a synthesis that embraces the SI contributions related to the application of the connectivity concept in different environments and geomorphic process domains, spatial and temporal scales, types and spatial dimensions of connectivity and the role of human impacts and associated river and catchment management aspects.
Rehydration modeling and characterization of dehydrated sweet corn
Authors: Nayi Pratik , Kumar Navneet , Kachchadiya Sagar , Chen Ho‐Hsien , Singh Punit , Shrestha Pratiksha , Pandiselvam Ravi 
Published: March 2023

AbstractThe increasing demand of rehydrated foods is due to its better storage stability at ambient conditions and not requiring refrigeration. Prior to drying at 55, 60, 65, and 70°C in a hot air tray dryer, hot water blanching (HB), steam blanching (SB), and microwave blanching (MB) were employed as pretreatments. Rehydration of dried pretreated sweet corn kernel was performed in boiling water. The pretreatments and drying temperatures were independent factors that affected the dependent factors such as rehydration ratio, total sugar, ascorbic acid, geometric mean diameter, color, sensory evaluation, water absorption, mass, and geometric mean diameter. Peleg, Weibull, and newly proposed models were considered to describe the change in moisture content during rehydration. The proposed model performed better than other models and indicated the rise in equilibrium moisture content of rehydrated sweet corn with an increase in dehydration temperature of sweet corn due to higher R2 (0.994), and lower chi‐square (0.005) and RMSE (0.064). The rehydrated sweet corn obtained from samples processed with microwave blanching and dehydration at 70°C showed higher retention of total sugar, ascorbic acid, geometric mean diameter, and color.
Deep time spatio‐temporal data analysis using pyGPlates with PlateTectonicTools and GPlately
Authors: Mather Ben R. , Müller R. Dietmar , Zahirovic Sabin , Cannon John , Chin Michael , Ilano Lauren , Wright Nicky M. , Alfonso Christopher , Williams Simon , Tetley Michael , Merdith Andrew 
Published: March 2023

AbstractPyGPlates is an open‐source Python library to visualize and edit plate tectonic reconstructions created using GPlates. The Python API affords a greater level of flexibility than GPlates to interrogate plate reconstructions and integrate with other Python workflows. GPlately was created to accelerate spatio‐temporal data analysis leveraging pyGPlates and PlateTectonicTools within a simplified Python interface. This object‐oriented package enables the reconstruction of data through deep geologic time (points, lines, polygons and rasters), the interrogation of plate kinematic information (plate velocities, rates of subduction and seafloor spreading), the rapid comparison between multiple plate motion models, and the plotting of reconstructed output data on maps. All tools are designed to be parallel‐safe to accelerate spatio‐temporal analysis over multiple CPU processors.
Analysis of performance and emission patterns of novel biofuel feedstock neat coconut fatty acid distillate (CFAD) fuelled single‐cylinder diesel engine
Authors: Rajesh K. , Sathiyamoorthi R. , Senthil S. , Murugapoopathi S. , Damodharan D. 
Published: March 2023

AbstractThis study examined the potential of using coconut fatty acid distillate (CFAD), a by‐product of the processing of edible oils, as a diesel engine fuel. The major novelty of this study is to assess the CFAD as a viable feedstock of biodiesel to address global energy demands. CFAD has not been specifically researched as a feedstock for producing biodiesel or as a fuel for diesel engines, despite the fact that numerous studies on the production and performance of biodiesel have already been conducted. Fourier transform infrared (FTIR) spectroscopy, gas chromatography (GC), and FTIR were used to analyze the fuel. According to the results of the GC test, CFAD oil contains 91.53% saturated fatty acids, compared with only 8.47% unsaturated fatty acids. High saturation values can be seen in myristic acid (16.92%) and lactic acid (45.33%). Longer hydrocarbon chain lengths indicate higher energy density and boiling point, which also indicate lesser volatility. At a frequency of 1708.54 cm−1, C─H stretching vibrations have been identified through FTIR investigation. The vibrations of C─C stretching at 1465.47 cm−1 indicate the presence of alkenes/fingerprint phase. The blends used for this investigation include 90% diesel with 10% CFAD (CFAD10), 80% diesel with 20% CFAD (CFAD20), 70% diesel with 30% CFAD (CFAD30), and 100% CFAD. The CFAD 10%, 20%, and 30% blends as well as the CFAD100 had brake thermal efficiency values of 27.24%, 26.23%, 24.88%, and 21.52%, correspondingly, at full load. The average increment in brake‐specific energy consumption for CFAD10, CFAD20, CFAD30, and CFAD100 over diesel fuel was 8.23%, 10.88%, 13.77%, and 25.90%, respectively. The behavior of CFAD exhibits reduced cylinder pressure because of the large content of moderate saturated fatty acids in this substance. The net heat release rate (NHRR) and cylinder pressure have a similar relationship in that the NHRR increases with increasing diesel volume. In comparison to diesel, the CO emissions from the CFAD20, CFAD30, and CFAD100 blends increased by 10.79%, 16.66%, and 35.89% at maximum load, respectively. It has been reported that NOx is reduced more significantly the more CFAD is present in the mixture. The blend CFAD10 had the least amount of smoke. The high viscosity of the CFAD and its blends influences the fuel droplets range and the development of spray in the cylinder, which results in delayed combustion and higher unburned hydrocarbon emissions.