bluuebunny/crossref_metadata_2025_split huggingface dataset:
Green consumers’ behavioral intention and loyalty to use mobile organic food delivery applications: the role of social supports, sustainability perceptions, and religious consciousness
Authors: Hasan Md. Mahedi , Al Amin Md. , Arefin Md. Shamsul , Mostafa Tanjim 
Published: May 2023

AbstractConsumer behavior in the food industry has undergone significant changes in recent years, largely driven by growing consumer awareness of environmental, technological, religious, and social concerns. As a result, organic food has emerged as a popular alternative to conventionally produced food. Many emerging nations, including Bangladesh, promote its consumption due to its perceived health and safety benefits. Despite this growing trend, there remains a need for more understanding of consumer behavior, particularly concerning their motivations for continuous purchases toward mobile organic food delivery applications. In order to fill this knowledge gap, this study looks at how six indirect predictors (emotional support, informational support, environmental consciousness, religious consciousness, trust, and technological consciousness) affect customer loyalty through the intention to use organic food. This study employed a purposive sampling technique (i.e., judgmental sampling) and collected data from 386 respondents across three cities in Bangladesh. Data analysis was conducted using SmartPLS 3 software. The study found that all predictors, except for technological consciousness, significantly influenced behavioral intention, which, in turn, significantly influenced loyalty. Additionally, the study revealed that the five predictors, excluding technological consciousness, indirectly influenced loyalty through behavioral intention. The results of this study add to the existing literature on organic food by extending social support theory to include consumers' primary motivations, such as environmental, religious, technological, and social consciousness, as predictors of loyalty to use mobile organic food delivery applications. The study highlights the importance of sustainable food consumption in promoting environmental protection, ensuring social justice, creating economic success, and providing valuable insights for implementers looking to expand the organic food market.
Graphical abstract
Sustainability assessment of optimal location of electric vehicle charge stations: a conceptual framework for green energy into smart cities
Authors: Abdel-Basset Mohamed , Gamal Abduallah , Hezam Ibrahim M. , Sallam Karam M. 
Published: May 2023

AbstractElectric vehicles (EVs) have achieved a great deal of success, indicating that the motor industry will soon be emission-free. They run on electricity stored in batteries, which their drivers can recharge using an external source of electricity. Therefore, the development of an infrastructure for charging EVs has become a necessity. In this paper, a real case study in Zagazig, Egypt, for evaluating, operating, and determining the most sustainable location for an EV charging station is presented. Identifying such a location is a complex task that requires considering many influencing factors and their sub-factors. Consequently, a general evaluation system that includes six key factors, in addition to nineteen sub-factors, has been developed. A multi-criteria decision-making (MCDM) approach is applied to deal with this problem. The neutrosophic theory with type-2 neutrosophic numbers (T2NNs) and a type-2 neutrosophic number weighted averaging (T2NNWA) operator are used to combine expert and specialized views since they are ambiguous and uncertain. Firstly, the Decision-making Trial and Evaluation Laboratory (DEMATEL) method is applied to prioritize key factors and sub-factors. Then, the Complex Proportional Assessment (COPRAS) technique selects six sustainable sites for EV charging stations. Also, comparison and sensitivity evaluations verify the approach's reliability, strength, stability, and performance. Finally, this article provides good information for policymakers and the results of the case study indicate that the economic factor is the most important factor in selecting the optimal location followed by the technical factor.
Dual-use implications of AI text generation
Authors: Koplin Julian J. 
Published: May 2023

AbstractAI researchers have developed sophisticated language models capable of generating paragraphs of 'synthetic text' on topics specified by the user. While AI text generation has legitimate benefits, it could also be misused, potentially to grave effect. For example, AI text generators could be used to automate the production of convincing fake news, or to inundate social media platforms with machine-generated disinformation. This paper argues that AI text generators should be conceptualised as a dual-use technology, outlines some relevant lessons from earlier debates on dual-use life sciences research, and calls for closer collaboration between ethicists and the machine learning community to address AI language models’ dual-use implications.
The vertebrate sialylation machinery: structure-function and molecular evolution of GT-29 sialyltransferases
Authors: Harduin-Lepers Anne 
Published: May 2023

AbstractEvery eukaryotic cell is covered with a thick layer of complex carbohydrates with essential roles in their social life. In Deuterostoma, sialic acids present at the outermost positions of glycans of glycoconjugates are known to be key players in cellular interactions including host-pathogen interactions. Their negative charge and hydrophilic properties enable their roles in various normal and pathological states and their expression is altered in many diseases including cancers. Sialylation of glycoproteins and glycolipids is orchestrated by the regulated expression of twenty sialyltransferases in human tissues with distinct enzymatic characteristics and preferences for substrates and linkages formed. However, still very little is known on the functional organization of sialyltransferases in the Golgi apparatus and how the sialylation machinery is finely regulated to provide the ad hoc sialome to the cell. This review summarizes current knowledge on sialyltransferases, their structure–function relationships, molecular evolution, and their implications in human biology.
Inventory of on-farm sorghum landrace diversity and climate adaptation in Tigray, Northern Ethiopia: implications for sorghum breeding and conservation
Authors: Semere Tesfakiros , Fjellheim Siri , Tsehaye Yemane , Westengen Ola T. 
Published: May 2023

AbstractThe study was conducted with the aim of inventorying and assessing the level of sorghum landraces richness, estimating the extent and patterns of phenotypic diversity, identifying race type, and predicting suitable areas of production using future climate scenarios in Tigray, Northern Ethiopia. Overall, 358 landraces from 125 independent farmers’ fields in 20 districts belonging to four zones of Tigray were surveyed. Landraces richness, frequency of character states, and diversity levels were estimated via Margalef’s, Menhinick’s and Shannon–Weaver (H′) indices for each zone and altitude classes. Suitable areas for sorghum cultivation in the future were predicted using DIVA-GIS. Altogether, 140 distinctly named landraces were identified and collected. Southern zone has the highest richness (DMg = 10.74, DMn = 5.0) followed by central (DMg = 8.54, DMn = 3.80). The estimated H′ for the phenotypic character states ranged from 0.24 (seed form) to 0.95 (rachis branch length). Highest diversity estimate was found in northwest (H′ = 0.71) followed by central zone (H′ = 0.64). Respectively, H′ was 0.70, 0.68, and 0.61 in lowland, intermediate, and highland elevations. In general, lowlands of northwest, central, and southern zones are identified as potential sites for germplasm conservation and utilization. The races durra, bicolor, caudatum, and durra-bicolor were found with durra as the dominant race (79%). All the currently surveyed areas and many other sites in Tigray are predicted to be suitable for future sorghum production under the changing climate scenario. Copies of all the 358 sorghum landraces are deposited in the national gene bank for use in future sorghum breeding work. The wealth of sorghum landraces diversity could be used in sorghum improvement programs.
Assessment of optimal growth conditions for biomass and exopolysaccharides production in the thermotolerant cyanobacterium Phormidium sp. ETS-05
Authors: Zampieri Raffaella Margherita , Caldara Fabrizio , La Rocca Nicoletta 
Published: May 2023

AbstractPhormidium sp. ETS-05 is one of the target cyanobacteria species conferring anti-inflammatory properties to the therapeutic muds applied by spas of the Euganean Thermal District (Italy) to treat arthro-rheumatic pathologies. Beneficial mud is prepared by spas following a traditional method, called maturation, leading to the growth of a specific microbiota on natural raw clay irrigated by flowing thermal water at 37–47 °C for about two months. The effectiveness of the mud is related to heat, electrolytes and bioactive molecules synthesized by the microbiota. A clear role in the anti-inflammatory activity of muds has been demonstrated for the exopolysaccharides, EPS, produced by the entire microbiota and Phormidium sp. ETS-05. Considering the interest in this species, we assessed its optimal growth conditions to obtain the higher EPS production in relation to temperature, light spectra, and intensity and nitrogen availability. The production of biomass and pigments was also taken into account, as other high-value compounds can be obtained in parallel with EPS. We found that exposure to a temperature of 45 °C under white light at 100 µmol photons m−2 s−1 is optimal to reach the highest biomass (1.13 g L−1) and an average production of 75 mg gDW−1 phycocyanin and of 150 mg gDW−1 EPS for Phormidium sp. ETS-05 cultured in lab-scale photobioreactors for 9 days. Putative genes linked with EPS assembly and export have also been identified in its genome, some of which have been investigated for their expression levels, opening up the possibility of biotechnologically boost EPS production.
Applications of Microct Imaging to Archaeobotanical Research
Authors: Barron Aleese 
Published: May 2023

AbstractThe potential applications of microCT scanning in the field of archaeobotany are only just beginning to be explored. The imaging technique can extract new archaeobotanical information from existing archaeobotanical collections as well as create new archaeobotanical assemblages within ancient ceramics and other artefact types. The technique could aid in answering archaeobotanical questions about the early histories of some of the world’s most important food crops from geographical regions with amongst the poorest rates of archaeobotanical preservation and where ancient plant exploitation remains poorly understood. This paper reviews current uses of microCT imaging in the investigation of archaeobotanical questions, as well as in cognate fields of geosciences, geoarchaeology, botany and palaeobotany. The technique has to date been used in a small number of novel methodological studies to extract internal anatomical morphologies and three-dimensional quantitative data from a range of food crops, which includes sexually-propagated cereals and legumes, and asexually-propagated underground storage organs (USOs). The large three-dimensional, digital datasets produced by microCT scanning have been shown to aid in taxonomic identification of archaeobotanical specimens, as well as robustly assess domestication status. In the future, as scanning technology, computer processing power and data storage capacities continue to improve, the possible applications of microCT scanning to archaeobotanical studies will only increase with the development of machine and deep learning networks enabling the automation of analyses of large archaeobotanical assemblages.
Inherited CD19 Deficiency Does Not Impair Plasma Cell Formation or Response to CXCL12
Authors: Walker Kieran , Mistry Anoop , Watson Christopher M. , Nadat Fatima , O’Callaghan Eleanor , Care Matthew , Crinnion Laura A. , Arumugakani Gururaj , Bonthron David T. , Carter Clive , Doody Gina M. , Savic Sinisa 
Published: May 2023

AbstractBackgroundThe human CD19 antigen is expressed throughout B cell ontogeny with the exception of neoplastic plasma cells and a subset of normal plasma cells. CD19 plays a role in propagating signals from the B cell receptor and other receptors such as CXCR4 in mature B cells. Studies of CD19-deficient patients have confirmed its function during the initial stages of B cell activation and the production of memory B cells; however, its role in the later stages of B cell differentiation is unclear.ObjectiveUsing B cells from a newly identified CD19-deficient individual, we investigated the role of CD19 in the generation and function of plasma cells using an in vitro differentiation model.MethodsFlow cytometry and long-read nanopore sequencing using locus-specific long-range amplification products were used to screen a patient with suspected primary immunodeficiency. Purified B cells from the patient and healthy controls were activated with CD40L, IL-21, IL-2, and anti-Ig, then transferred to different cytokine conditions to induce plasma cell differentiation. Subsequently, the cells were stimulated with CXCL12 to induce signalling through CXCR4. Phosphorylation of key downstream proteins including ERK and AKT was assessed by Western blotting. RNA-seq was also performed on in vitro differentiating cells.ResultsLong-read nanopore sequencing identified the homozygous pathogenic mutation c.622del (p.Ser208Profs*19) which was corroborated by the lack of CD19 cell surface staining. CD19-deficient B cells that are predominantly naïve generate phenotypically normal plasma cells with expected patterns of differentiation-associated genes and normal levels of CXCR4. Differentiated CD19-deficient cells were capable of responding to CXCL12; however, plasma cells derived from naïve B cells, both CD19-deficient and sufficient, had relatively diminished signaling compared to those generated from total B cells. Additionally, CD19 ligation on normal plasma cells results in AKT phosphorylation.ConclusionCD19 is not required for generation of antibody-secreting cells or the responses of these populations to CXCL12, but may alter the response other ligands that require CD19 potentially affecting localization, proliferation, or survival. The observed hypogammaglobulinemia in CD19-deficient individuals is therefore likely attributable to the lack of memory B cells.
Solubility of Gases in Liquids. 23: High-Precision Determination of Henry’s Law Constants of Propane Dissolved in Liquid Water from T = 278 K to T = 318 K
Authors: Rettich T. R. , Battino Rubin , Wilhelm Emmerich 
Published: May 2023

AbstractThe solubility of propane (C3H8, component 2) in pure liquid water (H2O, component 1) was determined at a total pressure of about 100 kPa from about T = 278 K to T = 318 K using an analytical method characterized by an imprecision of about ± 0.1% or less. The measurements were made with a Benson-Krause-type apparatus at roughly 5 K intervals. From the experimental results, Henry’s law constants $$h_{2,1} \left( {T,P_{\sigma ,1} } \right)$$

h

2
,
1

T
,

P

σ
,
1

, also known as Henry fugacities, at the vapor pressure $$P_{\sigma ,1} \left( T \right)$$

P

σ
,
1

T

of water, as well as the Ostwald coefficient $$L_{2,1}^{\infty } \left( {T,P_{{{\sigma ,}1}} } \right)$$

L

2
,
1

∞

T
,

P

σ
,

1

at infinite dilution are rigorously obtained. The temperature dependence is accounted for by a three-constant Benson-Krause equation, i.e., by fitting $$\ln \left[ {{{h_{2,1} \left( {T,P_{\sigma ,1} } \right)} \mathord{\left/ {\vphantom {{h_{2,1} \left( {T,P_{\sigma ,1} } \right)}{\text {kPa}}}} \right. \kern-0pt}{\text {kPa}}}} \right]$$

ln

h

2
,
1

T
,

P

σ
,
1

/

kPa

to a power series in 1/T. Subsequently, the partial molar enthalpy changes on solution $$\Delta H_{2}^{\infty }$$

Δ

H

2

∞

of propane in water, and the partial molar heat capacity changes on solution $$\Delta C_{P,2}^{\infty }$$

Δ

C

P
,
2

∞

, are reported (van ‘t Hoff analysis) and compared with calorimetrically determined quantities: agreement is highly satisfactory. We believe that our new values for the Henry fugacity and the Ostwald coefficient of propane dissolved in liquid water are the most reliable ones to date.
Optimality and Complexity in Measured Quantum-State Stochastic Processes
Authors: Venegas-Li Ariadna , Crutchfield James P. 
Published: May 2023

AbstractIf an experimentalist observes a sequence of emitted quantum states via either projective or positive-operator-valued measurements, the outcomes form a time series. Individual time series are realizations of a stochastic process over the measurements’ classical outcomes. We recently showed that, in general, the resulting stochastic process is highly complex in two specific senses: (i) it is inherently unpredictable to varying degrees that depend on measurement choice and (ii) optimal prediction requires using an infinite number of temporal features. Here, we identify the mechanism underlying this complicatedness as generator nonunifilarity—the degeneracy between sequences of generator states and sequences of measurement outcomes. This makes it possible to quantitatively explore the influence that measurement choice has on a quantum process’ degrees of randomness and structural complexity using recently introduced methods from ergodic theory. Progress in this, though, requires quantitative measures of structure and memory in observed time series. And, success requires accurate and efficient estimation algorithms that overcome the requirement to explicitly represent an infinite set of predictive features. We provide these metrics and associated algorithms, using them to design informationally-optimal measurements of open quantum dynamical systems.
Modeling Adolescent Social Inclusion to Improve School Completion
Authors: Renner Heidi M. , Rowland Bosco , Hutchinson Delyse , Toumbourou John W. 
Published: May 2023

AbstractEnhancing social inclusion in young people could increase engagement in education, yet few longitudinal studies have examined this relationship. This study aimed to identify whether social inclusion in an Australian adolescent sample predicted high school completion three years later. Using state-representative data from the International Youth Development Study, two waves of the youngest cohort (51.6% female and 94.6% Australian born) during mid-adolescence (n = 825, Mage = 15.99, SD = 0.39) and post-secondary school (n = 809, Mage = 19.03, SD = 0.44) were analyzed. Factor analysis identified a 4-factor structure that represented an overarching social inclusion construct: (1) Citizenship, (2) Connectedness to Community, (3) Connectedness to Family, and (4) Connectedness to and Participation in School. Multivariate regression analyses indicated higher social inclusion levels in mid-adolescence predicted an increased likelihood of high school completion three years later. The implementation of strategies that incorporate the enhancement of social inclusion may improve educational outcomes for young people.
Forest management scenarios drive future dynamics of Mediterranean planted pine forests under climate change
Authors: Suárez-Muñoz M. , Bonet-García F. J. , Navarro-Cerrillo R. , Herrero J. , Mina M. 
Published: May 2023

Abstract
Context
Planted pine forests are highly abundant communities in the Mediterranean Basin. Being the result of past reforestation, these forests show high species and structural homogeneity. Diversification to conifer-broadleaved mixed forests is recommended to promote adaptation to climate change and increase their resilience to perturbations.

Objectives
This study aims at evaluating how these planted pine forests will develop in the future as a result of the combined impacts of management and climate.

Methods
We applied a forest landscape model (LANDIS-II) to simulate different climate scenarios and management strategies designed in cooperation with forest managers to assess their effects on the performance of planted pine forests and their change in terms of forest composition.

Results
Climate change scenarios caused a shift in the phenological growth pattern of planted pine forests by reducing forest growth during summer and increasing photosynthetic productivity in spring and fall, particularly under high emission scenarios. Biomass increased through time and more strongly under climate change, but this increase differs among species, resulting in changes of forest types across the landscape. Our results portray natural succession as the main driver of forest change, but intensive management accelerated this process by limiting pine growth and promoting growth of oak species.

Conclusions
Our results highlight the importance of active management on planted pine forests to favour mixed and climate-adapted ecosystems in shorter time scales than offered by succession alone. Moreover, our spatially explicit modelling approach helps to identify areas where lack of seed dispersal and/or competitive exclusion prevent natural diversification, providing useful recommendations for interventions. However, the modelling approach has some limitations since it does not consider natural disturbances.

Graphical abstract
On the single partial Caputo derivatives for functions of two variables
Authors: Kamocki Rafał , Obczyński Cezary 
Published: May 2023

AbstractIn this work we propose definitions (distinguishable from the standard ones) of single partial derivatives in a Caputo sense of functions of two variables on the rectangle $$P=[0,a]\times [0,b]$$

P
=
[
0
,
a
]
×
[
0
,
b
]

. Next, we give an integral representation of functions possessing such derivatives. Finally, we apply these derivatives to the study of the existence and uniqueness of solutions and the continuous dependence of solutions on controls to a fractional counterpart of a nonlinear continuous Roesser type model.
Deep learning techniques for detection and prediction of pandemic diseases: a systematic literature review
Authors: Ajagbe Sunday Adeola , Adigun Matthew O. 
Published: May 2023

AbstractDeep learning (DL) is becoming a fast-growing field in the medical domain and it helps in the timely detection of any infectious disease (IDs) and is essential to the management of diseases and the prediction of future occurrences. Many scientists and scholars have implemented DL techniques for the detection and prediction of pandemics, IDs and other healthcare-related purposes, these outcomes are with various limitations and research gaps. For the purpose of achieving an accurate, efficient and less complicated DL-based system for the detection and prediction of pandemics, therefore, this study carried out a systematic literature review (SLR) on the detection and prediction of pandemics using DL techniques. The survey is anchored by four objectives and a state-of-the-art review of forty-five papers out of seven hundred and ninety papers retrieved from different scholarly databases was carried out in this study to analyze and evaluate the trend of DL techniques application areas in the detection and prediction of pandemics. This study used various tables and graphs to analyze the extracted related articles from various online scholarly repositories and the analysis showed that DL techniques have a good tool in pandemic detection and prediction. Scopus and Web of Science repositories are given attention in this current because they contain suitable scientific findings in the subject area. Finally, the state-of-the-art review presents forty-four (44) studies of various DL technique performances. The challenges identified from the literature include the low performance of the model due to computational complexities, improper labeling and the absence of a high-quality dataset among others. This survey suggests possible solutions such as the development of improved DL-based techniques or the reduction of the output layer of DL-based architecture for the detection and prediction of pandemic-prone diseases as future considerations.