bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nexus of environmental, social, and governance performance in China‐listed companies: Disclosure and green bond issuance
Authors: Wang Shanshan , Chen Shih‐Chih , Ali Mohd Helmi , Tseng Ming‐Lang 
Published: September 2023

AbstractThis study establishes a connection between existing literature on corporate environmental, social, and governance (ESG) matters, information disclosure, and green bonds by employing the issuance of green bonds to indicate investors' acknowledgment of a company's sustainable activities. Prior research has not adequately addressed the relationship between ESG performance, disclosure, and green bond issuance. A novel dataset has been compiled by merging ESG performance and information disclosure data of Chinese‐listed companies spanning from 2016 to 2020, alongside green bond issuance information from the Wind and Hexun databases. Concurrently, China's pursuit of carbon neutrality necessitates the establishment of a green, low‐carbon, and circular economy framework. ESG has surfaced as an indispensable instrument for appraising a company's sustainability and advocating the enhancement of its information disclosure systems, thereby aiding investors in forming well‐informed judgments. This study scrutinizes the correlation between each facet of ESG performance, disclosure, and green bond issuance, from the perspective of companies listed in emerging markets. The findings corroborate that companies exhibiting commendable ESG practices are more predisposed to issuing green bonds, particularly when such practices are suitably disclosed. The identified evidence will spur the enforcement of obligatory ESG disclosure regulations, further propelling China's advancement in ecological civilization and green finance.
Selective Dehydrogenation of Formic Acid Catalyzed by Air‐Stable Cuboidal PN Molybdenum Sulfide Clusters
Authors: Gutiérrez‐Blanco María , Stein Carolin A. M. , Alfonso Carmina , Guillamón Eva , Safont Vicent S. , Sorribes Iván , Junge Henrik , Beller Matthias , Llusar Rosa 
Published: September 2023

AbstractFormic acid is considered as a promising hydrogen storage material in the context of a green hydrogen economy. In this work, we present a series of aminophosphino and imidazolylamino Mo3S4 cuboidal clusters which are active and selective for formic acid dehydrogenation (FAD). Best results are obtained with the new [Mo3S4Cl3(ediprp)3](BPh4) (4(BPh4)) (ediprp=(2‐(diisopropylphosphino)ethylamine)) cluster, which is prepared through a simple ligand exchange process from the Mo3S4Cl4(PPh3)3(H2O)2 precursor. Under the conditions investigated, complex 4+ showed significantly improved performance (TOF=4048 h−1 and 3743 h−1 at 120 °C in propylene carbonate using N,N‐dimethyloctylamine as base after 10 min and 15 min, respectively) compared to the other reported molybdenum compounds. Mechanistic investigations based on stoichiometric and catalytic experiments show that cluster 4+ reacts with formic acid in the presence of a base to form formate substituted species [Mo3S4Cl3‐x(OCOH)x(ediprp)3]+ (x=1–3) from which the catalytic cycle starts. Subsequently, formate decarboxylation of the partially substituted [Mo3S4Cl3‐x(OCOH)x(ediprp)3]+ (x=1, 2, 3) catalyst through a β‐hydride transfer to the metal generates the trinuclear Mo3S4 cluster hydride. Dehydrogenation takes place through protonation by HCOOH to form Mo−H⋅⋅⋅HCOOH dihydrogen adducts, with regeneration of the Mo3S4 formate cluster. This proposal has been validated by DFT calculations.
Boosting the Oxygen Evolution Activity of FeNi Oxides/Hydroxides by Molecular and Atomic Engineering
Authors: Da Silva Eliana S. , Macili Aureliano , Bofill Roger , García‐Antón Jordi , Sala Xavier , Francàs Laia 
Published: September 2023

AbstractFeNi oxides/hydroxides are the best performing catalysts for oxidizing water at basic pH. Consequently, their improvement is the cornerstone to develop more efficient artificial photosynthetic systems. During the last 5 years different reports have demonstrated an enhancement of their activity by engineering their structures via: (1) modulation of the number of oxygen, iron and nickel vacancies; (2) single atoms (SAs) doping with metals such as Au, Ir, Ru and Pt; and (3) modification of their surface using organic ligands. All these strategies have led to more active and stable electrocatalysts for oxygen evolution rection (OER). In this Concept, we critically analyze these strategies using the most relevant examples.
Pioneering the Power of Twin Bonds in a Revolutionary Double Bond Formation. Unveiling the True Identity of o‐Carboryne as o‐Carborene
Authors: Poater Jordi , Viñas Clara , Escayola Sílvia , Solà Miquel , Teixidor Francesc 
Published: September 2023

AbstractThe homolytic elimination of two H atoms from two adjacent carbons in benzene results in the aromatic product o‐benzyne. In a similar way, the homolytic elimination of two H atoms from the two adjacent carbons in 1,2‐C2B10H12 results in the aromatic product o‐carboryne. In this work, we provide experimental and computational evidences that despite the similarity of o‐carboryne and o‐benzyne, the nature of the C−C bond generated between two adjacent carbons that lose H atoms is different. While in o‐benzyne the C−C bond behaves as a triple bond, in o‐carboryne the C−C bond is a double bond. Therefore, we must stop naming 1,2‐dehydro‐o‐carboryne as o‐carboryne but instead call it o‐carborene.
Deep chemometrics using one‐dimensional convolutional neural networks for predicting crude oil properties from FTIR spectral data
Authors: Ta Souvik , Alizadeh Shahla , Samavedham Lakshminarayanan , Ray Ajay K. 
Published: September 2023

AbstractThe determination of physicochemical properties of crude oils is a very important and time‐intensive process that needs elaborate laboratory procedures. Over the last few decades, several correlations have been developed to estimate these properties, but they have been very limited in their scope and range. In recent years, methods based on spectral data analysis have been shown to be very promising in characterizing petroleum crude. In this work, the physicochemical properties of crude oils using Fourier transform infrared (FTIR) spectrums are predicted. A total of 107 samples of FTIR spectral data consisting of 6840 wavenumbers is used. One dimensional convolutional neural networks (CNNs) were used employing FTIR spectral data as the one‐dimensional input and Keras and TensorFlow were used for model building. The Root Mean Square Error decreased from 160 to around 60 for viscosity when compared to previous machine learning methods like partial least squares (PLS), principal component regression (PCR), and partial least squares regression with genetic algorithm (PLS‐GA) on the same data. The important hyper‐parameters of the CNN were optimized. In addition, a comparison of results obtained with different neural network architectures is presented. Some common preprocessing techniques were also tested on the spectral data to determine their impact on model performance. To increase interpretability, the intermediate neural network layers were analyzed to reveal what the convolutions represented, and sensitivity analysis was done to gather key insights about the wavenumbers that were the most important for prediction of the crude oil properties using the neural network.
Synthesis of hydrogels from fractionated proteins of Moringa oleifera Lam. seeds for the treatment of water contaminated with black reactive dye 5
Authors: Freitas Resende Jayana , Reck Paulino Isabela Maria , dos Reis Oliveira Marina , Ferri Bruna Bruguer , Bergamasco Rosângela , Guilherme Marcos R. , Rinaldi Andrelson W. , Vieira Angélica Marquetotti Salcedo 
Published: September 2023

AbstractAs has been portrayed in the literature, the main proteins extracted from the seeds of Moringa oleifera Lam. have coagulant and clarifying potential in water treatment. However, when using them as coagulant agents, sludge formation occurs, which is an environmental problem. Thus, it was proposed to synthesize hydrogels from the main Moringa seeds proteins and use them as adsorbents. This work aimed to synthesize albumin hydrogels and globulin hydrogels and evaluate their efficiency as adsorbents to remove the reactive black 5 dye. Through FTIR spectrum it was possible to confirm that the synthesis of hydrogels occurred successfully. The kinetic data fit the pseudo‐second order model for both hydrogels. The equilibrium isotherms showed that adsorption occurs in multilayers, due to Freundlich fitting. The maximum adsorption capacity occurred at 298 K and was 1.19 mg g−1 for the albumin hydrogel and 10.06 mg g−1 for the globulin hydrogel. Through the results it is possible to state that globulin hydrogel was more favourable for adsorption since it has a more porous morphology and requires less mass compared to albumin hydrogel.
Early Organic Chemistry in Kyiv: Serhii Mykolayovych Reformatskyi (1860–1934) and his Name Reaction*
Authors: Lewis David E. 
Published: September 2023

AbstractSerhiy Mykolayovych Reformatskyi, [Ukrainian: Рeφopмaтcьκий, Cepгiй Mиκoлaйoвич; Russian: Sergei Nikolaevich Reformatskii, РeΦopмaтcκий, Cepгeй Hиκoлaeвич (1860‐1934)] was a product of Zaitsev's laboratory in Kazan Imperial University in Russia and one of the founding fathers of organic chemistry in Ukraine. He discovered his eponymous reaction while a graduate student in Kazan under Zaitsev, studying the synthesis of homoallylic alcohols. He modified this reaction by replacing the olefinic π bond of an allyl halide with a carbonyl group. In the prototype reaction, he treated ethyl haloacetates with zinc and aldehydes or ketones. The reaction gave the corresponding β‐hydroxyesters and remains an important synthetic method. Work on the reaction over the ensuing century and a quarter has led to the discovery of analogous reactions using a wide range of metals, and even permitting the use of water as a solvent.
Anger treatment via CBAT delivered remotely: Outcomes on psychometric and self‐monitored measures of anger
Authors: Fernandez Ephrem , Perez Brandon , Sun Renhao , Kolaparthi Krishna , Pham Tuan , Iwuala Emmanuel , Garza Rudy , Shattuck Eric C. , Wu Wenbo 
Published: September 2023

AbstractStudies of anger treatment have often reported on reappraisal and relaxation techniques delivered in person to forensic and psychiatric samples. The present study evaluated an integrative programme of cognitive–behavioural affective therapy (CBAT) delivered remotely to chronic pain sufferers with comorbid anger. Volunteers (N = 54) were randomly assigned to either CBAT or an Emotional Education (EE) group, both receiving hour‐long videorecorded sessions twice a week for 4 weeks plus weekly calls by telephone. At 1‐month post‐treatment, follow‐up was conducted. Outcomes were measured using the Anger Parameters Scale (APS) and its five subscales (frequency, duration, intensity, latency and threshold) as well as daily self‐monitored anger logs. As hypothesized, pre‐ to post‐treatment decline in APS total scores was significant for CBAT, Hedges' g = 0.65, 95% CI [0.14, 1.16] but nonsignificant and small for EE, g = 0.17, CI [−0.41, 0.75]. At the primary endpoint (post‐treatment), APS total scores were significantly lower for CBAT than for EE. Treatment gains were maintained till follow‐up. On all five APS subscales, pre‐post effect sizes were medium‐sized for CBAT and generally small for EE. This picture was mirrored in the self‐monitored frequency, duration and intensity of anger. Findings support the efficacy of CBAT over time, its comparative efficacy over EE and its ecological generalizability. Future research could expand sample size, reduce sample imbalance, extend follow‐up and strengthen treatment potency with more sessions. The present study renews enthusiasm for teletherapy and is the first to demonstrate CBAT efficacy in treating maladaptive anger in the chronic pain population.
A Comparison of the Reactivity of the Lattice Nitrogen in Tungsten Substituted Co3Mo3N and Ni2Mo3N
Authors: Al Sobhi Samia , AlShibane Ihfaf , Catlow C. Richard A. , Daisley Angela , Hargreaves Justin S. J. , Hector Andrew L. , Higham Michael D. , Zeinalipour‐Yazdi Constantinos D. 
Published: September 2023

AbstractThe effect of the partial substitution of Mo with W in Co3Mo3N and Ni2Mo3N on ammonia synthesis activity and lattice nitrogen reactivity has been investigated. This is of interest as the coordination environment of lattice N is changed by this process. When tungsten was introduced into the metal nitrides by substitution of Mo atoms, the catalytic performance was observed to have decreased. As expected, Co3Mo3N was reduced to Co6Mo6N under a 3 : 1 ratio of H2/Ar. Co3Mo2.6W0.4N was also shown to lose a large percentage of lattice nitrogen under these conditions. The bulk lattice nitrogen in Ni2Mo3N and Ni2Mo2.8W0.2N was unreactive, demonstrating that substitution with tungsten does not have a significant effect on lattice N reactivity. Computational calculations reveal that the vacancy formation energy for Ni2Mo3N is more endothermic than Co3Mo3N. Furthermore, calculations suggest that the inclusion of W does not have a substantial impact on the surface N vacancy formation energy or the N2 adsorption and activation at the vacancy site.
Nitrogen Reduction Reaction to Ammonia on Transition Metal Carbide Catalysts
Authors: Ellingsson Viktor , Iqbal Atef , Skúlason Egill , Abghoui Younes 
Published: September 2023

AbstractThe development of a low‐cost, energy‐efficient, and environmentally friendly alternative to the currently utilized Haber‐Bosch process to produce ammonia is of great importance. Ammonia is an essential chemical used in fertilizers and a promising high‐density fuel source. The nitrogen reduction reaction (NRR) has been explored intensively as a potential avenue for ammonia production using water as proton source, but to this day a catalyst capable of producing this chemical at high Faradaic efficiency (FE) and commercial yield and rates has not been reported. Here, we investigate the activity of transition metal carbide (TMC) surfaces in the (100) facets of the rocksalt (RS) structure as potential catalysts for the NRR. In this study, we use density functional theory (DFT) to model reaction pathways, estimate stability, assess kinetic barriers, and compare adsorbate energies to determine the overall performance of each TMC surface. For pristine TMC surfaces (with no defects) we find that none of the studied TMCs possess both exergonic adsorption of nitrogen and the capability to selectively protonate nitrogen to form ammonia in the desired aqueous solution. ZrC, however, is shown to be a potential catalyst if used in a non‐aqueous electrolyte. To circumvent the endergonic adsorption of nitrogen onto the surface, a carbon vacancy was introduced. This provides a well‐defined high coordination active site on the surface. In the presence of a vacancy VC, NbC, and WC showed efficient nitrogen adsorption, selectivity towards ammonia, and a low overpotential (OP). NbC did, however, display an unfeasible kinetic barrier to nitrogen dissociation for ambient‐condition purposes, and thus it is suggested for high tempearture/pressure ammonia synthesis. Both WC and VC in their RS (100) structure are promising materials for experimental investigations in aqueous electrolytes, and ZrC could potentially be interesting for non‐aqueous electrolytic systems.
Challenges of clinical translation from single‐cell sequencing to measures in clinical biochemistry of haematology: Definition of immune cell identities
Authors: Liu Xuanqi , Wang Xiangdong , Powell Charles A. , Wang Diane C. 
Published: September 2023

AbstractPeripheral immune cells play important roles in the maintenance of systemic and microenvironmental hemostasis. Measurements of circulating blood cells by single‐cell RNA sequencing (scRNA‐seq) were proposed as one of the routine measures in the clinical biochemistry of haematology. Out of translational challenges, defining precise identities of cell subsets and states is more difficult, due to the complexity of immune cell development, location, regulation, function, and metabolism. It is also a challenge to precisely interpret the clinical significance and impact of each cell identity marker gene panel (ciMGPs). ciMGPs have the potential to advance the understanding of systemic responses to the disease, identify disease‐specific biomarkers and define cell heterogeneity. Recently, a large number of peripheral cell subsets and expanding/activating states have been identified and validated for use in the fast developments in clinical single‐cell biomedicine. Defining the specificity, measurability and repeatability of cell subsets/states is important for the translation of peripheral scRNA‐seq in clinical haematology and biochemistry. The development of standard operating procedures and the performance of clinical trials in large populations of various ages, diseases, and therapies will promote the clinical translation of ciMGPs to measures. Thus, defining cell subset/state identities will provide the multi‐dimensional and comprehensive readouts of systemic immune cells, the precision monitoring of immune dynamics, and a deeper understanding of the disease and response to therapy.
Deubiquitinase USP19 modulates apoptotic calcium release and endoplasmic reticulum stress by deubiquitinating BAG6 in triple negative breast cancer
Authors: Zhang Xiaoqiang , Chen Xuyu , Qian Fangze , Zhu Yanhui , He Gao , Yang Junzhe , Wu Xian , Zhang Hongfei , Yu Xiafei , Liu Xiaoan 
Published: September 2023

AbstractBackgroundTriple‐negative breast cancer (TNBC), a heterogeneous subtype of breast cancer (BC), had poor prognosis. Endoplasmic reticulum (ER) stress was responsible for cellular processes and played a crucial role in the cell function. ER stress is a complex and dynamic process that can induce abnormal apoptosis and death. However, the underlying mechanism of ER stress involved in TNBC is not well defined.MethodsWe identified ubiquitin‐specific protease 19 (USP19) as a TNBC negative regulator for further investigation. The effects of USP19 on BC proliferation were assessed in vitro using proliferation test and cell‐cycle assays, while the effects in vivo were examined using a mouse tumorigenicity model. Through in vitro flow cytometric analyses and in vivo TUNEL assays, cell apoptosis was assessed. Proteomics was used to examine the proteins that interact with USP19.ResultsMultiple in vitro and in vivo tests showed that USP19 decreases TNBC cell growth while increasing apoptosis. Then, we demonstrated that USP19 interacts with deubiquitinates and subsequently stabilises family molecular chaperone regulator 6 (BAG6). BAG6 can boost B‐cell lymphoma 2 (BCL2) ubiquitination and degradation, thereby raising ER calcium (Ca2+) levels and causing ER stress. We also found that the N6‐methyladenosine (m6A) “writer” methyltransferase‐like 14 (METTL14) increased global m6A modification.ConclusionsOur study reveals that USP19 elevates the intracellular Ca2+ concentration to alter ER stress via regulation of BAG6 and BCL2 stability and may be a viable therapeutic target for TNBC therapy.
Speciation and repeated origins of hypertrophied lips in parallel adaptive radiations of cyprinid fish from East Africa
Authors: Levin Boris , Komarova Aleksandra , Simonov Evgeniy , Tiunov Alexei , Levina Marina , Golubtsov Alexander , Kondrashov Fyodor , Meyer Axel 
Published: September 2023

AbstractThe evolution of convergent phenotypes is one of the most interesting phenomena of repeated adaptive radiations. Here, we examined the repeated patterns of thick‐lipped or “rubberlip” phenotype of cyprinid fish of the genus Labeobarbus discovered in riverine environments of the Ethiopian Highlands, East Africa. To test the adaptive value of thickened lips, identify the ecological niche of the thick‐lipped ecomorphs, and test whether these ecomorphs are the products of adaptive divergence, we studied six sympatric pairs of ecomorphs with hypertrophied lips and the normal lip structure from different riverine basins. Trophic morphology, diet, stable isotope (δ15N and δ13C) signatures, as well as mtDNA markers and genome‐wide SNP variation, were analyzed. Our results show that thick‐lipped ecomorphs partition trophic resources with generalized ecomorphs in only one‐half of the examined sympatric pairs despite the pronounced divergence in lip structure. In these thick‐lipped ecomorphs that were trophically diverged, the data on their diet along with the elevated 15N values suggest an invertivorous specialization different from the basal omnivorous–detritivouros feeding mode of the generalized ecomorphs. Genetic data confirmed an independent and parallel origin of all six lipped ecomorphs. Yet, only one of those six thick‐lipped ecomorphs had a notable genetic divergence with sympatric non‐lipped ecomorphs based on nuclear SNPs data (FST = 0.21). Sympatric pairs can be sorted by combinations of phenotypic, ecological, and genetic divergence from an ecologically non‐functional mouth polymorphism via ecologically functional polymorphism to a matured speciation stage via divergent evolution.
Identification of driving factors for chlorophyll‐a in multi‐stable shallow lakes of China employing machine learning methods
Authors: Qu Shan , Wang Jian‐jian , Kumar Amit , Yu Zhi‐Guo , Zhao Wan‐Qi 
Published: September 2023

AbstractDue to the rapid increase in urbanization and anthropogenic activity in the lake catchment, nutrients like phosphorus and nitrogen are abundant in urban sewage, leading to lake eutrophication and promoting algal blooms. Chlorophyll‐a (Chl‐a) is an important indicator of algal blooms; thus, predicting concentration is vital for lake restoration and management. Literature reveals that most of the previous studies of Chl‐a prediction required multiple variables and considerable computation. Thus, it is crucial to scientifically identify the key drivers of Chl‐a in Taihu Lake for the formulation of effective environmental management measures. In this study, a long‐term dataset (1991–2015) and Daniel trend test method were employed to analyse the trend of meteorological and water quality indicators in Taihu Lake in China. The redundancy of variables was eliminated by using the rank correlation method, combined with prior knowledge that provides a solid foundation for the analysis of the driving factors of Chl‐a. Four machine learning models, named Extreme Gradient Boosting (XGBoost), random forest (RF), support vector regression (SVR) and gradient boosting decision tree (GBDT), were employed to predict the concentration of Chl‐a in different regions of Taihu Lake. The result shows that the XGBoost model outperformed the other three models in terms of R2 (>0.90) and root mean square error (RMSE) (3.69–8.40). Finally, based on the predictions of the concentration of Chl‐a using the XGBoost model, the SHapley Additive exPlanation (SHAP) framework was utilized to analyse the key factors influencing Chl‐a concentration. Finding of this study suggests that the XGBoost model performed best and could be applied to the overall stretches of Taihu Lake and other lakes in China; model prediction will be helpful in providing a zoning decision‐making approach for the rational protection of the lake environment and the prevention of algal bloom hazards.