bluuebunny/crossref_metadata_2025_split huggingface dataset:
Challenges and Prospects of Phosphorus‐based Anode Materials for Secondary Batteries
Authors: Dong Shaowen , Wang Li , Huang Xiaolong , Liang Jie , He Xiangming 
Published: September 2023

AbstractThe research of new electrode materials is vital, among which anode materials have a significant role in the improvement of the overall energy density of batteries. Phosphorus‐based anode materials show tremendous potential in the exploration of anode materials due to their high theoretical capacity, natural abundance, and environmental friendliness. In this review, we sum up the latest research progress of red phosphorus‐based, black phosphorus‐based, and transition metal phosphide‐based anode materials for lithium‐ion batteries (LIBs) and sodium‐ion batteries (SIBs). The features of the phosphorus‐based materials, the preparation methods, and the advantages/disadvantages are introduced, as well as the electrochemical storage mechanism of LIBs and SIBs. On this basis, the problems of phosphorus‐based anode materials are considered and analyzed in depth and improvement strategies are proposed. Finally, the directions that phosphorus‐based materials will take in the future are examined. This paper is intended to advance knowledge of phosphorus‐based anode materials among researchers and to offer some recommendations for using such materials in LIBs and SIBs.
Identity state‐dependent self‐relevance and emotional intensity ratings of words in dissociative identity disorder: A controlled longitudinal study
Authors: Strouza Aikaterini I. , Lawrence Andrew J. , Vissia Eline M. , Kakouris Andreana , Akan Ayse , Nijenhuis Ellert R. S. , Draijer Nel , Chalavi Sima , Reinders Antje A. T. S. 
Published: September 2023

AbstractIntroductionDissociative identity disorder (DID) is characterized by, among others, amnesic episodes and the recurrence of different dissociative identity states. While consistently observed in clinical settings, to our knowledge, no controlled research study has shown the degree to which different identity states report autobiographical knowledge over time. Hence, the current study investigates self‐relevance and emotional intensity ratings of words longitudinally.MethodsData of 46 participants were included: 13 individuals with DID, 11 DID‐simulating actors, and a control group of 22 paired individuals. Individuals with DID and DID simulators participated once in the neutral identity state (NIS) and once in the trauma‐related dissociative identity state (TIS). The control group paired 11 healthy controls with 11 participants with posttraumatic stress disorder (PTSD) as a NIS–TIS pair. Self‐relevance ratings of different word types were collected in a baseline and a follow‐up session, on average 6 weeks apart. A mixed ANOVA design was used to assess the effects of group, session, word type, and dissociative identity state.ResultsAll participants in TIS and individuals with DID in NIS rated self‐relevant trauma‐related words more negatively. In the NIS, the control group rated self‐relevant trauma‐related words as less negative, whereas the ratings of simulating actors were intermediate. There was no group‐dependent longitudinal effect for intensity ratings.ConclusionsThis study was the first to confirm clinical observations that self‐relevant and emotional processing are different between individuals with DID and controls, but consistent over time. Actors were unable to perfectly simulate DID. The finding that ratings of self‐relevant trauma‐related words differ between subgroups as included in the study is in line with clinical observations.
Exploring the Synthetic and Antioxidant Potential of 1,2‐Disubstituted Benzimidazoles Using [Et3NH][HSO4] Ionic Liquid Catalyst
Authors: Sahiba Nusrat , Teli Pankaj , Meena Priyadarshi , Agarwal Shikha 
Published: September 2023

AbstractAn [Et3NH][HSO4] ionic‐liquid catalyzed, intermolecular C−N bond formation for 1,2‐disubstituted benzimidazole synthesis was achieved by the reaction of OPD and substituted aldehydes at ambient reaction conditions. Operational simplicity, use of easily available substrate and reagents, good yields (74–95 %) in short reaction time (4–18 min), simple work‐up, and column chromatographic free synthesis are the remarkable features of this new protocol. The applicability of [Et3NH][HSO4] ionic‐liquid as a green and inexpensive catalyst with good recyclability and compatibility with a broad range of functional group having heteroatom, electron‐withdrawing, and electron‐releasing groups manifested the sustainability, eco‐friendliness, and efficiency of the present methodology. Moreover, the antioxidant studies of the synthesized compounds using DPPH and ABTS assays were appealing and several synthesized compounds showed significant antioxidant activity.
Diastereoselective Pd‐catalyzed Decarboxylative (4+2) Cycloaddition Reactions of 4‐Vinylbenzoxazinanones and 2‐Nitro‐1,3‐enynes
Authors: Tague Andrew J. , Hoang Pham Quoc , Richardson Christopher , Pyne Stephen G. , Hyland Christopher J. T. 
Published: September 2023

AbstractA formal palladium‐catalyzed decarboxylative (4+2) cycloaddition reaction between 4‐vinylbenzoxazinanones and 2‐nitro‐1,3‐enynes has been developed to produce highly valuable, densely functionalized tetrahydroquinolines in moderate to excellent yields with high diastereoselectivity under mild reaction conditions. The optimised protocol tolerates a range of substituted 2‐nitro‐1,3‐enynes, which represent an under‐utilized class of dipolarophile for transition‐metal catalyzed cycloadditions. The employed reaction methodology facilitates efficient cycloaddition with both N‐H‐ and N‐Ts‐4‐vinylbenzoxazinanone dipole precursors. The stereochemistry of the major and minor diastereomeric (4+2) cycloadducts was determined by single crystal X‐ray analyses. A mechanistic rationale for the high intrinsic diastereoselectivity and preliminary enantioselective experiments are also presented. The tetrahydroquinoline cycloadduct products feature numerous pendant functionalities, including a vinyl handle, an internal alkyne motif and a nitro functionality (which functions as a latent C‐3 nitrogen substituent) for further synthetic manipulations.
Control structure selection of increased‐pressure extractive distillation process for DMC‐MeOH azeotropic mixture
Authors: Varyemez H. Selin , Kaymak Devrim B. 
Published: September 2023

AbstractProducing dimethyl carbonate (DMC) as a green chemical with the desired purity is important in the industry. Although studies on the steady‐state design of energy‐efficient extractive distillation processes are important for the purification of DMC‐methanol (DMC‐MeOH) azeotropic mixtures, the dynamic controllability of these processes is also critical in the case of feed condition changes, and it should be investigated carefully. Results of the limited studies in the literature show that changing the operating pressures in extractive distillation processes might have different effects on the dynamic controllability of different systems. Thus, in this study, alternative control strategies are developed for a recently proposed increased‐pressure extractive distillation process to separate DMC‐MeOH mixture. All control structures are designed using inferential temperature controllers, which have a general acceptance in industrial applications. Effects of different ratio controllers are investigated by evaluating the dynamic responses of control structures for disturbances in feed flowrate and composition. Two metrics including integral absolute error and steady‐state deviation of purities are used in the evaluation of alternatives. Results of dynamic simulations show that a control structure including reflux ratio controller is not a suitable strategy for this process. It is demonstrated that a control structure including reflux to feed ratio controller for both distillation columns is necessary for the robust and efficient control of a pressure‐increased extractive distillation process. These efficient dynamic results support the economic advantage of increased‐pressure extractive distillation process separating DMC‐MeOH azeotropic mixtures.
Reasonable Design and Controllable Growth of Instant Boric Acid
Authors: Bi Shengnan , Shi Lei , Ye Junwei , Ning Guiling 
Published: September 2023

AbstractBoric acid is widely used in human life and industrial production. However, few methods for solving the slow dissolution behavior of boric acid are reported. Based on the Density Functional Theory (DFT) analysis, a reasonable modulation strategy is proposed and an effective regulation method is obtained for preparing instant boric acid in this work. The DFT theoretical calculations and various characterizations explain the relation between the exposed surface of crystalline boric acid and its dissolution rate. The experiment results prove that the slow dissolution behavior of boric acid can be dramatically improved by regulating its exposed surface of crystalline particles. This work may fill the lack in the controllable regulation of boric acid crystalline structure and provide new perspectives for improving the dissolution rate of other crystalline products.
Is my model fit for purpose? Validating a population model for predicting freshwater fish responses to flow management
Authors: Hale Robin , Yen Jian D. L. , Todd Charles R. , Stuart Ivor G. , Wootton Henry F. , Thiem Jason D. , Koehn John D. , Tonkin Zeb , Lyon Jarod P. , McCarthy Michael A. , Bird Tomas J. , Fanson Ben G. 
Published: September 2023

AbstractModels based on ecological processes (process‐explicit models) are often used to predict ecosystem responses to environmental changes or management scenarios. However, models are imperfect and need to be validated, ideally by testing their assumptions and outputs against independent empirical data sets. Examples of validation of process‐explicit models are rare. Recently, stochastic population models have been developed to predict the likely responses (over 10–120 years) of a riverine fish (golden perch, Macquaria ambigua) to flow management in the Murray–Darling Basin (MDB) in eastern Australia, one of the world's most regulated river basins. Declines in golden perch (and other species) are a direct consequence of altered hydrology, and managers require information to predict how fish will respond to possible future hydrological conditions to guide substantial investments in flow management. Here, we use two independent field data sets to validate our population model. We compared model predictions to observed trends to ask: (1) How do predicted population sizes and growth rates compare with observed data? (2) Does the correlation between predicted and observed population sizes and growth rates vary among populations? (3) Does the correlation between predicted and observed population sizes and growth rates vary across observed hydrological conditions? (4) How do modeled and observed fish movement rates compare? We found reasonable correlations between fish population sizes and growth rates as predicted by the model and observed in independent data sets for several populations (Aim 1), but the strength of these correlations varied among populations (Aim 2) and hydrological conditions (Aim 3). Predicted and observed fish movement rates were strongly correlated (Aim 4). Population models are frequently used in conservation decision‐making but are rarely validated. We demonstrate that: (1) validation can identify model strengths and weaknesses; (2) observed data sets often have inherent limitations that can preclude robust validations; (3) validation is likely to be more common if appropriate observed data sets are available; and (4) validation should consider the purpose of modeling. Wider consideration of these messages would contribute to more critical examinations of models, so they can be most appropriately used in conservation decision‐making.
Curcumin‐loaded nanomedicines as therapeutic strategy in malaria management
Authors: Amin Ruhul , Melody Devi Chanam , Sarkar Dona , Sharifi‐Rad Javad , Sönmez Gürer Eda , Oana Docea Anca , Calina Daniela 
Published: September 2023

AbstractMalaria, a parasitic protozoan disease widespread in tropical climates, is transmitted by Plasmodium spp. Many people are affected by this significant public health disease, which has a high incidence of illness and mortality worldwide. Because drug‐resistant parasites are on the rise, there are not enough controls on mosquitoes, and there are not any malaria vaccinations. Malaria is particularly challenging in developing countries. Antimalarial drugs approved by Food and Drug Administration are the main options for combating and preventing malaria; also the control of transmission at the level of mosquitoes is important. Current antimalarial chemotherapeutic therapies have significant clinical flaws such as Plasmodium resistance, the drugs that call for the development of novel drug candidates. To combat malaria, nanotechnology may give a viable alternative that is both more effective and safer than current treatment options. Nanotechnology‐based curcumin formulations have proved to overcome the limitations of current therapies in terms of optimum therapeutic benefits, safety, and cost‐efficiency, which increases a patient's capacity to adhere to prescribed medicine. The limits of current malaria therapies and the need to employ nanotechnological curcumin to treat malaria were addressed and discussed in this paper.
PBP and PSP promote β' form crystallization of palm oil, palm stearin, and a cocoa butter replacer
Authors: Zhang Qing , Qi Ang , Li Hong , Li Xuehong , Zhang Hong , Wei Tao , Zhang Lu 
Published: September 2023

AbstractTo precisely regulate the crystallization of lipids, an in‐depth understanding of the correlation between the structures of the crystallization promoters and their functionalities is crucial. The effects of the crystallization promoters 1,3‐dipalmitoyl‐2‐behenoyl‐glycerol (PBP) and 1,3‐dipalmitoyl‐2‐stearoyl‐glycerol (PSP) on the crystallization behavior of palm oil, palm stearin, and a cocoa butter replacer were investigated by differential scanning calorimetry, polarized light microscopy, and X‐ray diffraction. The chain‐length difference between PSP and PBP resulted in different thermally stable polymorphs. PBP was stabilized in the β‐3L form, but PSP was stabilized in the β′‐2L form. The addition of PBP and PSP significantly promoted nucleation and led to an earlier onset of crystallization during cooling. After isothermal and nonisothermal crystallization, the PSP and PBP increased the melting temperatures of the palm oil and the cocoa butter replacer but decreased the melting temperature of the palm stearin, since PBP and PSP effectively promoted β′ formation but retarded the β' to β transformation. Due to the differences in chain length and subcell matching, palm stearin crystallizes on PSP and PBP via different modes.Practical Applications: PBP and PSP have potential as β'‐form crystallization promoters for plastic fats. This research indicated the possibility of regulating the nanostructures of fats by structural design of the crystallization promoters.
Design and implementation of optimal algorithm for shelves handling based on the change of return position of movable shelves
Authors: Yao Wenbin , Gong Gaiyun 
Published: September 2023

AbstractA shelf‐to‐person picking system based on automatic guided vehicles (AGVs) is developed in the mobile shelf warehouse, which can meet the needs of multi batches, small volume and multi variety picking. In this system, the efficiency of picking is affected by Storage location allocation, optimal combination of picking orders, optimization of handling shelves and AGVs scheduling. This article establishes a mathematical model according to the shortest walking distance of AGV in view of the situation that the return position of the shelf can be changed. In this article, a hybrid intelligent algorithm is designed, and its effectiveness is verified by numerical examples. At the same time, the heuristic algorithm and intelligent algorithm were compared in two cases, and the range of intelligent algorithm parameters was analyzed to verify the stability and effectiveness of the algorithm.
Joint modeling on serum creatinine and time to end stage of renal disease for chronic kidney disease patients under treatment at the University of Gondar Referral Hospital
Authors: Belay Samson , Melese Dessie , Muhammed Kasim 
Published: September 2023

AbstractBackground and AimsChronic kidney disease (CKD) is a major health problem worldwide. The general objective of this study is to identify the joint factors of serum creatinine (SCr) and time to end stage of renal disease (ESRD) for CKD patients under treatment at University of Gondar Referral Hospital (UOGRH).MethodsA retrospective cohort study was conducted. The collected information was secondary data type obtained from 311 CKD patient's medical charts in the UOGRH from September 2019 to January 2022 G.C. Joint modeling analysis contained a linear mixed model for SCr and the Cox‐PH model for time to ESRD of CKD patients under treatment was used.ResultFrom the total of 311 patients, 104 (33.4%) patients were developed the ESRD, while the other 207 (66.6%) were censored patients. In the longitudinal submodel, the variable sex, age, electrolyte, visit time, anemia, diabetes mellitus, chronic heart disease, hypertension, and hepatitis have a significant effect on the variable SCr. In survival process, anemia (HR = 2.53, p = < 0.001), diabetes mellitus (HR = 2.206, p = < 0.0047), chronic heart disease (HR = 2.83, p = < 0.0011), HIV (HR = 2.778, p = < 0.0045), hypertension (HR = 2.616, p = < 0.001), and hepatitis (HR = 4.4, p = < 0.0074) have a significant effect on the variable ESRD. On the basis of the result of the joint model, the variable anemia, diabetes mellitus, chronic heart disease, hypertension, and hepatitis were common significant factors.ConclusionThe majority of patients 207 (66.6%) of CKD patients were censored. On the basis of the smaller information criteria value and the significance association value, the joint model better fits the data. In the joint model, the variable anemia, diabetes mellitus, chronic heart disease, hypertension, and hepatitis were common factors of two responses, and also concluded that the rate of progression of longitudinal measure SCr decreased over time.
21‐gene expression assay and clinical outcomes of premenopausal patients with hormone receptor‐positive breast cancer
Authors: Hyung Jaewon , Lee Sae Byul , Kim Jisun , Kim Hee Jeong , Ko BeomSeok , Lee Jong Won , Son Byung‐Ho , Lee Hee Jin , Gong Gyungyub , Jeong Hyehyun , Jeong Jae Ho , Kim Jeong Eun , Ahn Jin‐Hee , Jung Kyung Hae , Kim Sung‐Bae 
Published: September 2023

AbstractThe prognostic role of the recurrence score (RS) based on the 21‐gene expression assay in premenopausal women is not well delineated, and we investigated the association of outcomes and the RS in premenopausal patients who had 21‐gene expression assay at Asan Medical Center, Seoul, Korea, between June 2005 and July 2018. Invasive breast cancer‐free survival (IBCFS) by STEEP version 2.0 was compared according to the RS and clinical risk factors. A total of 554 patients were included in our study and 116 patients (20.9%) had age <40 years, 238 patients (43.0%) had luminal B subtype (Ki67 ≥ 20%), and 83 patients (15.0%) had RS >25. All patients received adjuvant tamoxifen ± chemotherapy. Overall, patients with RS >25 showed trend toward worse IBCFS from multivariable analysis (adjusted HR 1.89 [95% CI: 0.95‐3.73], P = .069). When comparing outcomes according to age and luminal subtypes, patients with luminal B subtype and age <40 years (n = 60) showed significantly worse outcomes compared to the others (luminal A or luminal B + age ≥40 years, n = 494; adjusted HR 2.95 [95% CI: 1.49‐5.82], log‐rank P < .001). Among patients with luminal B subtype and age <40 years, there was no significant association observed between IBCFS and the RS (log‐rank P = .51). In conclusion, while RS >25 showed association with poor outcomes in premenopausal women, it may have less prognostic significance among those with luminal B subtype and age <40 years.
Shell‐Net: A robust deep neural network for the joint segmentation of retinal fragments
Authors: Pappu Geetha Pavani , Uppudi Prashanth Gowri Shankar , Biswal Birendra , Kandula Srinivasa Rao , Dhavala Meher Savedasa , Potturi Giri Madhav , Sharat Paila Sai , Polapragada Sridevi , Datti Nagadhara Harini 
Published: September 2023

AbstractSegmentation of retinal fragments like blood vessels, optic disc (OD), and optic cup (OC) enables the early detection of different retinal pathologies like diabetic retinopathy (DR), glaucoma, etc. This article proposed a novel deep learning architecture termed as Shell‐Net for the accurate segmentation of the retinal fragments. The main novelty of the architecture relies on the intellectual fusion of two different styled networks for attaining better segmentation results. The lower part of the Shell‐Net (feature condenser) follows the down‐sampling and up‐sampling style, whereas the upper part of the network (feature amplifier) follows the up‐sampling and down‐sampling style of architecture. In addition to this, an additional residual module (feature stabilizer) is integrated with the network to achieve more spatial information from lower levels. The lower part of the network reduces the data through summarization, enabling much scope for precise extraction of heavy details such as thick vessels, OD, and OC. On the contrary, the upper part of the network augments the data using duplication, assisting in the enlargement of minuscule details such as the tiny vessels and boundaries. Experiments were performed on publicly available datasets like Digital Retinal Images for Vessel Extraction (DRIVE), Child Heart and Health Study in England (CHASE_DB1), Structured Analysis of the Retina (STARE), Online Retinal Fundus Image Dataset for Glaucoma Analysis and Research (ORIGA), DRISHTI‐GS1, and Retinal Image database for Optic Nerve Evaluation (RIMONE r1). The network accomplished an average accuracy (ACC) and specificity (SPE) of 0.96 and 0.98 when tested on DRIVE, CHASE_DB1, and STARE datasets respectively for vessel segmentation. Furthermore, it outperformed previously existing models in OD and OC segmentation by achieving an average accuracy of 0.98 with a specificity of 0.99 on the DRISHTI_GS1 dataset.
Predicting coronary artery disease using learning rate based snow leopard optimization with soft swish scaling based bidirectional long short‐term memory
Authors: Kowsalyadevi J. , Geetha P. 
Published: September 2023

AbstractThe most common kind of heart disease is coronary artery disease (CAD), which impacts millions globally. For CAD detection, the computed tomography (CT) image is very helpful. CT aids in the quick visualization of the heart and coronary arteries with a higher spatial resolution. So, this research methodology uses the CT image for CAD detection with the risk assessment by the proposed SS‐B‐LSTM (Soft Swish Scaling based Bidirectional Long Short‐Term Memory) algorithm. Moreover, the proposed methodology considers the vital features from different regions of the heart encompassing calcium tissue, leaflet tissue, and blood pool. Thus, CAD can be detected efficiently, and the risk assessment is done precisely. The proposed research mainly consists of seven steps: preprocessing, heart segmentation, clustering, feature extraction, feature selection, disease detection, and risk assessment. The proposed technique detects CAD with an accuracy of 96.66%. Furthermore, the computational time of the proposed framework is 0.3948 s. After experimental evaluation, the proposed technique is found to be more efficient in detecting and classifying CAD. Moreover, the complexity is low compared to the existing works.