bluuebunny/crossref_metadata_2025_split huggingface dataset:
Color representations of normals and congenital red–green color deficiencies: Estimation of individual results based on color vision model
Authors: Ohkoba Minoru , Ishikawa Tomoharu , Hira Shoko , Ohtsuka Sakuichi , Ayama Miyoshi 
Published: December 2021

AbstractDifference scaling experiment was conducted to investigate the mental color representation of congenital color‐deficient observers and observers with normal color vision. Two decks of cards, high and medium chroma, each containing 10 Munsell chips, were prepared. A total of 45 pairs of hues were prepared for each of the decks. Ten protans, 10 deutans, and 10 people with normal color vision participated as observers, with each asked to rate the perceptual distance between two colors on a given color card. The results were analyzed using the multidimensional scaling method. All observers with normal color vision showed a circular shape close to the Munsell hue circle, while the majority of color‐deficient observers showed a concave shape bending at Y and PB. To indicate the degree of distortion from a circle, the distortion index was proposed to quantitatively evaluate intergroup and individual differences. To investigate the underlying mechanism of intergroup differences as well as individual differences in color representations of observers with normal color vision and color‐deficient observers, we proposed a model that considers various levels of human color vision mechanism from the cone pigment absorption, the luminance and opponent‐color coding level, and nonlinear transformation to difference‐scaling judgment. The circular shape for observers with normal color vision and some color‐deficient observers, as well as concave shapes for most color‐deficient observers were estimated. The correlation coefficient between the estimation and experiment‐based difference ranged from r = 0.64 to r = 0.94 with the grand average of r = 0.82, with p‐values less than 0.001 for all observers, suggesting that the concept of proposed model is appropriate.
Off to new shores: Climate niche expansion in invasive mosquitofish (Gambusia spp.)
Authors: Jourdan Jonas , Riesch Rüdiger , Cunze Sarah 
Published: December 2021

AbstractAimFormerly introduced for their presumed value in controlling mosquito‐borne diseases, the two mosquitofish Gambusia affinis and G. holbrooki (Poeciliidae) are now among the world's most widespread invasive alien species, negatively impacting aquatic ecosystems around the world. These inconspicuous freshwater fish are, once their presence is noticed, difficult to eradicate. It is, therefore, of utmost importance to assess their geographic potential and to identify their likely ability to persist under novel climatic conditions.LocationGlobal.MethodsWe build species distribution models using occurrence data from the native and introduced distribution ranges to identify putative niche shifts and further ascertain the areas climatically suitable for the establishment and possible spread of mosquitofish.ResultsWe found significant niche expansions into climatic regions outside their natural climatic conditions, emphasizing the importance of integrating climatic niches of both native and invasive ranges into projections. In particular, there was a marked shift toward tropical regions in Asia and a clear niche shift of European G. holbrooki. This ecological flexibility partly explains the massive success of the two species, and substantially increases the risk for further range expansion. We also showed that the potential for additional expansion resulting from climate change is enormous—especially in Europe.Main conclusionsDespite the successful invasion history and ongoing range expansions, many countries still lack proper preventive measures. Thus, we urge policy makers to carefully evaluate the risk both mosquitofish pose to a particular area and to initiate appropriate management strategies.
Sex‐associated differences in the network roles of pollinators
Authors: Smith Gordon P. , Gardner Joel , Gibbs Jason , Griswold Terry , Hauser Martin , Yanega Doug , Ponisio Lauren C. 
Published: December 2021

AbstractSex‐associated differences in behavior can have large ecological consequences, especially in plant–pollinator communities where floral visitor behavior affects plant reproduction. Whether these differences are prevalent enough to impact community‐level processes, however, is unknown. Using 256 plant–pollinator communities, we built networks where the floral interactions of each sex were modeled separately, comparing observations to simulated networks where sex was randomized. We found that (1) in many species the sexes differed in their network roles and visited different partners, with females tending to visit more species and more peripheral species than males; (2) more generalist species differed more in network roles between the sexes; and (3) networks where nodes were separated by sex were more specialized than simulated networks, but were similarly resistant to perturbations. These findings suggest that despite variation among species, sex‐associated differences in behavior are large enough to impact the network roles of male and female pollinators and common enough to influence the interaction patterns of entire plant–pollinator communities.
Setting the foundation for renewal: restoring sponge communities aids the ecological recovery of Florida Bay
Authors: Butler Jack , Sharp William C. , Hunt John H. , Butler Mark J. 
Published: December 2021

AbstractCoastal ecosystems are constantly buffeted by anthropogenic forces that degrade habitats and alter ecological processes and functions; in turn, this habitat degradation diminishes the ecosystem goods and services on which humans rely. Within the last few decades, the field of restoration ecology has burgeoned into a discipline that marries scientific rigor with functional restoration practice—an idea championed by Pete Peterson and his research. Here, we describe our efforts to restore the hard‐bottom sponge communities of Florida Bay, FL (USA)—a once‐diverse subtropical lagoon severely degraded by cyanobacteria blooms—and the scientific and practical lessons learned from those efforts. Sponge community restoration yielded insights into basic sponge biology and ecology (e.g., density‐dependent growth rates) and hastened the recovery of ecological processes (e.g., rates of sedimentation, structuring of water column characteristics, soundscape productions). Because the results of our initial restoration efforts were promising, our collaboration among academic researchers, natural resource managers, and non‐governmental organizations has begun scaling up restoration efforts to re‐establish the sponge communities over large areas of degraded hard‐bottom to “jump start” the ecological recovery of Florida Bay. Though our efforts show promise for ecological recovery, restoration will require a concerted effort by scientists, resource managers, and citizens to stem the anthropogenic drivers of ecological degradation of this unique South Florida ecosystem.
Documenting pollinators, floral hosts, and plant–pollinator interactions in U.S. Pacific Northwest agroecosystems
Authors: Bloom Elias H. , Oeller Elisabeth C. , Olsson Rachel L. , Brousil Matthew R. , Schaeffer Robert N. , Basu Saumik , Fu Zhen , Crowder David W. 
Published: December 2021

AbstractThe abundance and diversity of pollinator populations are in global decline. Managed pollinator species, like honey bees, and wild species are key ecosystem service providers in both natural and managed agroecosystems. However, relatively few studies have exhaustively characterized pollinator populations in diverse agroecosystems over multiple years, while also thoroughly documenting plant–pollinator interactions. Yet, such studies are needed to fulfill the national pollinator protection plans that have been released by the United States and other nations. Our research is among the first studies to respond to these directives by systematically documenting bee and plant biodiversity, bee–plant interactions, and bee‐mediated pollen movement in farming systems of the Pacific Northwest, USA. Our data provides insight into the processes mediating pollinator and plant community assembly, persistence, and resilience across landscapes with variable crop and landscape diversity and agroecosystem management practices. These data will also contribute to the development of a United States pollinator database, supporting the United States' plan to promote pollinators. With few publicly available data sets that systematically take account of agroecosystem practices, plant populations, and pollinators, our research will provide future users the means to conduct synesthetic studies of pollinators and ecosystem function in a period of rapid and global pollinator declines. There are no copyright or proprietary restrictions for research or teaching purposes. Usage of the data set must be cited.
Hobit and Blimp‐1 instruct the differentiation of iNKT cells into resident‐phenotype lymphocytes after lineage commitment
Authors: Kragten Natasja AM , Taggenbrock Renske LRE , Parga Vidal Loreto , van Lier Rene AW , Stark Regina , van Gisbergen Klaas PJM 
Published: December 2021

AbstractiNKT cells are CD1d‐restricted T cells that play a pro‐inflammatory or regulatory role in infectious and autoimmune diseases. Thymic precursors of iNKT cells eventually develop into distinct iNKT1, iNKT2, and iNKT17 lineages in the periphery. It remains unclear whether iNKT cells retain developmental potential after lineage commitment. iNKT cells acquire a similar phenotype as tissue‐resident memory T cells, suggesting that they also differentiate along a trajectory that enables them to persist in peripheral tissues. Here, we addressed whether lineage commitment and memory differentiation are parallel or sequential developmental programs of iNKT cells. We defined three subsets of peripheral iNKT cells using CD62L and CD69 expression that separate central, effector, and resident memory phenotype cells. The majority of iNKT1 cells displayed a resident phenotype in contrast to iNKT2 and iNKT17 cells. The transcription factor Hobit, which is upregulated in iNKT cells, plays an essential role in their development together with its homolog Blimp‐1. Hobit and Blimp‐1 instructed the differentiation of central memory iNKT cells into resident memory iNKT cells, but did not impact commitment into iNKT1, iNKT2, or iNKT17 lineages. Thus, we conclude that memory differentiation and the establishment of residency occur after lineage commitment through a Hobit and Blimp‐1‐driven transcriptional program.
Ferrocene‐Functionalized Multiwalled Carbon Nanotubes for the Simultaneous Determination of Dopamine, Uric Acid, and Xanthine
Authors: Wang Junyan , Khorasani Motlagh Mozhgan , Noroozifar Meissam , Kerman Kagan , Kraatz Heinz‐Bernhard 
Published: December 2021

AbstractIn this proof‐of‐concept study, ferrocene‐modified multiwalled carbon nanotubes (Fc‐MWCNT) were synthesized by amide coupling and the resulting product was characterized by transmission electron microscopy and Fourier‐transform infrared spectroscopy. The Fc‐MWCNT were used in a graphite paste electrode (GPE) for the highly sensitive simultaneous determination of dopamine (DA), uric acid (UA), xanthine (XA) by differential pulse voltammetry. The sensor displayed a linear range up to 4.5, 14, and 82.0 μM with a limit of detection of 2.0, 10.0 and 5 nM for DA, UA, and XA, respectively. In addition, the modified GPE/Fc‐MWCNT displayed a high stability, reproducibility, and repeatability. The GPE/Fc‐MWCNT was used for simultaneous determination of DA, UA, and XA in two different real samples with a recovery rate of 95–104 %.
One‐Pot Transformation of Lignin and Lignin Model Compounds into Benzimidazoles
Authors: Guo Tao , Liu Tianwei , He Jianghua , Zhang Yuetao 
Published: December 2021

AbstractIt is a challenging task to simultaneously achieve selective depolymerization and valorization of lignin due to their complex structure and relatively stable bonds. We herein report an efficient depolymerization strategy that employs 2,3‐dichloro‐5,6‐dicyano‐1,4‐benzoquinone (DDQ) as oxidant/catalyst to selectively convert different oxidized lignin models to a wide variety of 2‐phenylbenzimidazole‐based compounds in up to 94 % yields, by reacting with o‐phenylenediamines with varied substituents. This method could take full advantage of both Cβ and/or Cγ atom in lignin structure to furnish the desirable products instead of forming byproducts, thus exhibiting high atom economy. Furthermore, this strategy can effectively transform both the oxidized hardwood (birch) and softwood (pine) lignin into the corresponding degradation products in up to 45 wt% and 30 wt%, respectively. Through a “one‐pot” process, we have successfully realized the oxidation/depolymerization/valorization of natural birch lignin at the same time and produced the benzimidazole derivatives in up to 67 wt% total yields.
Rationally designed high‐conductivity Hydrangea macrophylla‐like Si@NiO@Ni/C composites as a high‐performance anode material for lithium‐ion batteries
Authors: Yu Kunxiang , Liu Junhao , Gong Xuzhong , Zhang Xianren , Wang Zhi 
Published: December 2021

AbstractReasonable design of the core‐shell structure with a high conductive stable substrate is an effective way to solve the huge volume expansion and low intrinsic conductivity of Si‐based anode materials in Li‐ion batteries (LIBs). In this work, the Hydrangea macrophylla‐like composites (Si@NiO@Ni/C) have been successfully synthesized by staged calcination of the Si@Ni(OH)2@C precursor. This design achieved a stable loading of Si nanoparticles on the high conductive substrate by forming chemical bonds and provided enough space for the expansion of Si. Furthermore, the existence of a hybrid coating layer could stabilize the formation of the solid electrolyte layer and accelerate the migration of Li+ and electrons, which greatly improved the kinetics performance on the electrode surface. As a consequence, the design showed excellent cycle stability (1265.5 mAh g–1 after 300 cycles at 0.5 A/g) and rate performance (982.2, 876.1, 766.6, 645.8, 572 mAh/g at 0.2, 0.5, 1, 2, 3 A/g, respectively), providing a simple and controllable method to synthesize Si‐based anode materials for high‐performance LIBs.
Resource allocation for joint energy and spectral efficiency in cloud radio access network based on deep reinforcement learning
Authors: Iqbal Amjad , Tham Mau‐Luen , Chang Yoong Choon 
Published: December 2021

AbstractThe rapid increase of user data traffic demand has promoted the telecommunication sector toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network (CRAN) has gained considerable attention to satisfy the high traffic demand in the 5G network via deployment and intelligent management of multiple remote radio units (RRHs). However, optimizing the instantaneous network performance may lead to myopic decision‐making, such as excessive on/off switching of RRHs. This paper proposes a deep reinforcement learning (DRL) based framework, with the goal of maximizing the long‐term tradeoff between energy efficiency (EE) and spectral efficiency (SE). To this end, we specifically formulate the joint optimization problem as a Markov decision process (MDP) subject to the constraints on per‐RRH transmission power and user quality of service (QoS) demands. Meanwhile, considering the spatio‐temporal channel state information (CSI), we adopt machine learning (ML) techniques to extract generalized features before feeding them into the input of DRL. Combining with RRH status and QoS requirements, the proposed algorithm can learn the near‐optimal control strategy to turn on/off RRHs, followed by solving a power optimization problem. Simulation results reveal that the proposed method yields better performance as compared to myopic and DRL methods without considering CSI generalization.
Detecting attacks on IoT devices with probabilistic Bayesian neural networks and hunger games search optimization approaches
Authors: Toğaçar Mesut 
Published: December 2021

AbstractTechnologies that enable physical objects to communicate with each other are attracting a lot of interest day by day. Internet of Things (IoT) is a communication network that is used to connect with technological devices and systems. The growth of IoT networks has led to malicious targeting of these systems by third parties. To prevent such malicious purposes, network security should be at the forefront. Recently, artificial intelligence‐based approaches have been used in security domains. Two accessible datasets were used in this study. The datasets consist of simulated bot IoT network traffic data containing distributed denial‐of‐service (DDoS) attack types. In the proposed approach, probabilistic Bayesian neural networks and normal Bayesian neural networks are used as the deep learning models. All features of the dataset were trained using two models. Then, the datasets were optimized using hunger games search (HGS) method and the most efficient parameters of the datasets were selected and retrained using deep learning models. In the analysis performed using the proposed approach, an overall accuracy of 100% was obtained for the dataset used in the first experiment and 99.99% for the dataset used in the second experiment. It was also observed that metaheuristic optimization helps the proposed approach to save time in detecting DDoS attacks.
Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models
Authors: Lu Xinjie , Ma Feng , Wang Jiqian , Liu Jing 
Published: December 2021

AbstractThis study adds ample evidences on forecasting oil futures realized range‐based volatility (RRV) in the mixed data sampling (MIDAS) framework. Considering the features and frequent extreme risk in oil futures trading in practice, we investigate the effect of jumps, leverage effect, and regime switching. The results highlight the great importance of combing jumps, leverage effect, and regime switching simultaneously in oil futures RRV forecasting, which still holds the best predictability during a highly volatile state. Moreover, considering regime switching can also improve forecast accuracy for longer forecasting horizons such as weekly, biweekly, and monthly. The conclusions are robust to various settings and criteria. Our findings are essential for oil enterprises and quantitative investors to have a good command of crude oil futures market characteristics and achieve risk aversion.
Effect of thermal radiation on an unsteady MHD flow over an impulse vertical infinite plate with variant temperature in existence of Hall current
Authors: Appidi Lakshmi , Malga Bala Siddulu , Pramod Kumar P. 
Published: December 2021

AbstractIn this paper, the effects of thermal radiation on unsteady MHD flow viscous incompressible electrically conducting fluid past an impulsively started oscillating vertical plate with variable temperature and constant mass diffusion in the presence of Hall current have been presented. The dimensionless governing partial differential equations of the flow have been solved numerically by using the Galerkin finite element method. The numerical solutions for fluid velocity, angular velocity, temperature, and concentration are represented graphically whereas the numerical results of primary skin friction, rate of heat and mass transfer are presented in tabular form for various parameters involved. The current results were compared to the existing analytical solution based on the Crank–Nicolson implicit finite difference technique. The current study's findings have been shown to be extremely consistent with earlier findings.
Optimization of hydrogen‐enriched diesel/n‐Amyl alcohol‐fueled engine to meet emission standards through varying nozzle opening pressure and static injection timing
Authors: Seelam Navyasree , Gugulothu S. K. , Bhasker Burra , Panda Jibitesh K. , Reddy Ragireddy V. 
Published: December 2021

AbstractImportant injection parameters such as fuel injection timing (FIT) and fuel injection pressure (FIP) on different piston bowl geometries substantially impact the performance, emissions, and combustion characteristics of a common rail direct injection engine. The aim of this study deals with the effects of piston bowl geometry (hemispherical bowl [HSB], troded bowl [TRB], and re‐entrant bowl [REB]), FIP (200, 220, and 240 bar), and variable FIT (20, 24, and 28°bTDC) with hydrogen‐diesel/1‐pentanol (B20) (80% diesel and 20% pentanol) with a constant flow rate of hydrogen at 12 Lpm. Furthermore, to decrease emission standards and energy consumption, biodiesel and hydrogen are the ideal substitutes for conventional fuels. REB outperforms HSB and TRB in terms of brake thermal efficiency (5.67%) and hydrocarbon (8% reduction), increasing the FIP at full load (240 bar). However, with the increase in the FIP in the REB, a slight reduction in nitrogen oxide (NOx) emissions (2%) is observed. With an increase in FIP in the case of REB, net heat release rate, peak pressure (in‐cylinder), and rate of pressure rise all rise significantly by 3.4%, 4.2%, and 2.3%. NOxemissions are marginally enhanced with higher FIP and advanced FIT. It is found that changing the piston shape and FIP simultaneously is a potential alternative for improving engine performance and lowering emissions.
Accountant CFOs and corporate tax avoidance
Authors: Gao Li 
Published: December 2021

AbstractThis paper examines the association between Chief Financial Officers (CFOs) with accounting expertise (i.e., Accountant CFOs) and corporate tax avoidance. Specifically, I attempt to explore the impact of specialized accounting knowledge of CFOs on general and aggressive tax avoidance strategies. Consistent with my conjectures, I find that having accounting competence among CFOs is positively associated with their general tax avoidance behavior, suggesting that CFOs take advantage of their professional knowledge to reduce corporate tax payment to related tax authorities. In addition, the empirical evidence that I found also shows that accountant CFOs are less likely to involve in aggressive tax avoidance strategies. This conclusion is consistent with prior studies arguing that accountant CFOs are risk averse and conservative. In summary, accountant CFOs have quite different attitudes towards various tax avoidance activities depending on the underlying tax position of the tax planning behavior.
Role of T‐box genes in cancer, epithelial‐mesenchymal transition, and cancer stem cells
Authors: Niu Gengle , Hao Jin , Sheng Surui , Wen Fangyuan 
Published: December 2021

AbstractSharing a common DNA binding motif called T‐box, transcription factor T‐box gene family controls embryonic development and is also involved in cancer progression and metastasis. Cancer metastasis shows therapy resistance and involves complex processes. Among them, epithelial‐mesenchymal transition (EMT) triggers cancer cell invasiveness and the acquisition of stemness of cancer cells, called cancer stem cells (CSCs). CSCs are a small fraction of tumor bulk and are capable of self‐renewal and tumorsphere formation. Recent progress has highlighted the critical roles of T‐box genes in cancer progression, EMT, and CSC function, and such regulatory functions of T‐box genes have emerged as potential therapeutic candidates for cancer. Herein we summarize the current understanding of the regulatory mechanisms of T‐box genes in cancer, EMT, and CSCs, and discuss the implications of targeting T‐box genes as anticancer therapeutics.