bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of Non‐Aromatic Hydrophobic α‐Amino Acids (α‐AA) and Non‐Amino Acid Derived Synthons: Comparative Studies Towards Total Syntheses of Selected Bioactive Natural Alkaloids
Authors: Kumar Amit , Bhattacherjee Sandeep , Ganesher Asha , Manda Srinivas Lavanya Kumar , Banerjee Arpita , Panda Gautam 
Published: March 2022

AbstractEnantiomerically pure non‐aromatic α‐amino acids having hydrophobic side chains (Isoleucine, Valine, Leucine, Methionine and Alanine) have been acknowledged as an important chiral pool. The wide range of chemical and biological applications associated with these α‐amino acids has encouraged organic chemists to develop new synthetic methodologies for the total synthesis of bioactive molecules. In this review, the synthetic routes of10bioactive natural alkaloids have been covered. The present article is an attempt to discuss various synthetic approaches of therapeutically active natural alkaloids and related diversity from non‐aromatic hydrophobic α‐amino acids and non‐amino acid derived synthetic approaches to present a comparative study between the methods. The synthetic steps and the key strategies involved in the total synthesis of selected natural alkaloids have been compared based on atom economy, overall chemical yield, stereoselectivity and sustainability with cost effective manner by using inexpensive commercially available starting materials but the source of chiral pool mainly α‐amino acids to target natural alkaloids in chiral synthesis will be playing an important role. In selected cases of alkaloids synthesized from non‐amino acid route, an external chiral source of induction like metal and organometallic catalysts to generate chirality in the molecule are used.
Synthesis of Fused pyrazolo[4,3‐c]quinolines through KI‐Promoted Cyclization of Pyrazole‐arylamines and Benzyl Bromide
Authors: Mu Yangxiu , Iqbal Zafar , Jiang Rui , Hou Jing , Yang Zhixiang , Li Hongjun , Tang Dong 
Published: March 2022

AbstractA simple and highly efficient protocol was developed for the formation of pyrazolo[4,3‐c]quinolines starting from 2‐(1H‐pyrazol‐5‐yl)anilines and benzyl bromide in the presence of KI, affording desired products in moderate to good yields. The reaction showed good tolerance for a range of substrates with variable substituents. In this methodolgy, benzyl bromide proved to be an available C1 synthon in organic synthesis. Moreover, benzyl bromide can be replaced with benzyl iodide to synthesize pyrazolo[4,3‐c]quinoline derivatives, and benzyl chloride could not apply in this reaction system.
Aza‐Michael Mono‐ and Bis‐Addition of Primary and Secondary Amines Promoted by Silica‐Supported Polyphosphoric Acid, PPA/SiO2
Authors: Bosica Giovanna , Saliba Ryan 
Published: March 2022

AbstractThe development of new protocols using non‐toxic, low cost, eco‐friendly, recyclable catalyst systems which give high productivity under mild reaction conditions has received much attention in organic synthesis in the last couple of years. A collection of structurally diverse β‐amino carbonyl compounds was successfully synthesized by aza‐Michael mono‐ and double‐additions using silica‐supported polyphosphoric acid as catalyst under solventless conditions. Highlighted advantages of this particular catalyst include ease of preparation and long‐term stability under storage.
Ultrasmall Manganese Ferrites for In Vivo Catalase Mimicking Activity and Multimodal Bioimaging
Authors: Carregal‐Romero Susana , Miguel‐Coello Ana Beatriz , Martínez‐Parra Lydia , Martí‐Mateo Yolanda , Hernansanz‐Agustín Pablo , Fernández‐Afonso Yilian , Plaza‐García Sandra , Gutiérrez Lucía , Muñoz‐Hernández María del Mar , Carrillo‐Romero Juliana , Piñol‐Cancer Marina , Lecante Pierre , Blasco‐Iturri Zuriñe , Fadón Lucía , Almansa‐García Ana C. , Möller Marco , Otaegui Dorleta , Enríquez Jose Antonio , Groult Hugo , Ruíz‐Cabello Jesús 
Published: March 2022

AbstractManganese ferrite nanoparticles display interesting features in bioimaging and catalytic therapies. They have been recently used in theranostics as contrast agents in magnetic resonance imaging (MRI), and as catalase‐mimicking nanozymes for hypoxia alleviation. These promising applications encourage the development of novel synthetic procedures to enhance the bioimaging and catalytic properties of these nanomaterials simultaneously. Herein, a cost‐efficient synthetic microwave method is developed to manufacture ultrasmall manganese ferrite nanoparticles as advanced multimodal contrast agents in MRI and positron emission tomography (PET), and improved nanozymes. Such a synthetic method allows doping ferrites with Mn in a wide stoichiometric range (MnxFe3‐xO4, 0.1 ≤ x ≤ 2.4), affording a library of nanoparticles with different magnetic relaxivities and catalytic properties. These tuned magnetic properties give rise to either positive or dual‐mode MRI contrast agents. On the other hand, higher levels of Mn doping enhance the catalytic efficiency of the resulting nanozymes. Finally, through their intracellular catalase‐mimicking activity, these ultrasmall manganese ferrite nanoparticles induce an unprecedented tumor growth inhibition in a breast cancer murine model. All of these results show the robust characteristics of these nanoparticles for nanobiotechnological applications.
History Dependence in a Chemical Reaction Network Enables Dynamic Switching
Authors: Kriukov Dmitrii V. , Koyuncu A. Hazal , Wong Albert S. Y. 
Published: March 2022

AbstractThis work describes an enzymatic autocatalytic network capable of dynamic switching under out‐of‐equilibrium conditions. The network, wherein a molecular fuel (trypsinogen) and an inhibitor (soybean trypsin inhibitor) compete for a catalyst (trypsin), is kept from reaching equilibria using a continuous flow stirred tank reactor. A so‐called ‘linear inhibition sweep’ is developed (i.e., a molecular analogue of linear sweep voltammetry) to intentionally perturb the competition between autocatalysis and inhibition, and used to demonstrate that a simple molecular system, comprising only three components, is already capable of a variety of essential neuromorphic behaviors (hysteresis, synchronization, resonance, and adaptation). This research provides the first steps in the development of a strategy that uses the principles in systems chemistry to transform chemical reaction networks into platforms capable of neural network computing.
Enabling High Loading in Single‐Atom Catalysts on Bare Substrate with Chemical Scissors by Saturating the Anchoring Sites
Authors: Li Ang , Kan Erjun , Chen Shuangming , Du Zhengwei , Liu Xuan , Wang Tongyu , Zhu Wenjin , Huo Hailing , Ma Jingjing , Liu Dong , Song Li , Feng Hao , Antonietti Markus , Gong Jinlong 
Published: March 2022

AbstractAtomically dispersed metal catalysts often exhibit high catalytic performances, but the metal loading density must be kept low to avoid the formation of metal nanoparticles, making it difficult to improve the overall activity. Diverse strategies based on creating more anchoring sites (ASs) have been adopted to elevate the loading density. One problem of such traditional methods is that the single atoms always gather together before the saturation of all ASs. Here, a chemical scissors strategy is developed by selectively removing unwanted metallic materials after excessive loading. Different from traditional ways, the chemical scissors strategy places more emphasis on the accurate matching between the strength of etching agent and the bond energies of metal‐metal/metal‐substrate, thus enabling a higher loading up to 2.02 wt% even on bare substrate without any pre‐treatment (the bare substrate without any pre‐treatment generally only has a few ASs for single atom loading). It can be inferred that by combining with other traditional methods which can create more ASs, the loading could be further increased by saturating ASs. When used for CH3OH generation via photocatalytic CO2 reduction, the as‐made single‐atom catalyst exhibits impressive catalytic activity of 597.8 ± 144.6 µmol h−1 g−1 and selectivity of 81.3 ± 3.8%.
Evaluation of enterprise financial investment environment based on block‐chain and cloud computing
Authors: Li Qiang 
Published: March 2022

AbstractImproving and strengthening the various factors of the financial investment system to improve the entire investment system has become an important part of modern economic development. This research is based on block‐chain and cloud computing on the evaluation of corporate financial investment environment. It aims to fully apply the advantages of block‐chain and computing technology to conduct a thorough analysis of corporate financial investment environment and increase the stability of corporate financial investment decisions. Provide economic benefits to a certain extent. The article mainly analyzes the status quo, influencing factors, and evaluation principles of the financial investment environment, and combines the advantages of cloud computing and block‐chain in data acquisition and processing applications to conduct experiments; this research constructs a structural correlation model between the enterprise and the external environment, and investment business data process and cloud computing and financial investment information organization structure model, which can visually present specific investment operation details, and so on; formulate comprehensive evaluation indicators for regional investment, and focus on the role of the institutional environment based on the analysis of the role of regional factors on the regional development of the enterprise. The research results show that cloud computing technology and block‐chain technology have greatly improved the construction of financial investment data whether it is intertemporal, predictive or follow‐up. From the data inspection results, the maximum value of this performance has been expanded from the original 5.98 to 9.27; from the perspective of computational performance, it has been increased from 5.98 to 9.27.
Blind watermarking algorithm combiningNSCT,DWT,SVD, andHVS
Authors: Zeng Fanfeng , Bai Haoyin , Xiao Ke 
Published: March 2022

AbstractIn order to solve the contradiction between watermark transparency and robustness, this paper combines Non‐subsampled Contourlet Transformation (NSCT), Discrete Wavelet Transformation (DWT), Singular Value Decomposition (SVD), and Human Visual System (HVS) to improve a watermarking algorithm. Firstly, this algorithm performs a first‐level NSCT decomposition on the carrier image to obtain its low‐frequency part, and then performs a second‐level DWT on the low‐frequency part, extracts its second‐level low‐frequency sub bands and block these sub bands to sub‐blocks according to their size. Secondly, SVD is performed for each sub‐block and the best embedding position of the watermark according to the sensitivity of HVS for the average brightness and the modified cosine similarity measurement method is calculated. Finally, the watermark scrambled and encrypted by Arnold is embedded into the selected singular value. This algorithm can realize the blind extraction of watermark. Experimental results show that the algorithm can not only satisfy the transparency but the robustness of the watermark at the same time as well.
RVprio: A tool for prioritizing runtime verification violations
Authors: Cabral Lucas , Miranda Breno , Lima Igor , d'Amorim Marcelo 
Published: March 2022

SummaryRuntime verification (RV) helps to find software bugs by monitoring formally specified properties during testing. A key problem in using RV during testing is how to reduce the manual inspection effort for checking whether property violations are true bugs. To date, there was no automated approach for determining the likelihood that property violations were true bugs to reduce tedious and time‐consuming manual inspection. We present RVprio, the first automated approach for prioritizing RV violations in order of likelihood of being true bugs. RVprio uses machine learning classifiers to prioritize violations. For training, we used a labelled dataset of 1170 violations from 110 projects. On that dataset, (1) RVprio reached 90% of the effectiveness of a theoretically optimal prioritizer that ranks all true bugs at the top of the ranked list, and (2) 88.1% of true bugs were in the top 25% of RVprio‐ranked violations; 32.7% of true bugs were in the top 10%. RVprio was also effective when we applied it to new unlabelled violations, from which we found previously unknown bugs—54 bugs in 8 open‐source projects. Our dataset is publicly available online.
Effective reinforcement ratio of RC beams: Validation of modelling assumptions with high‐resolution strain data
Authors: Galkovski Tena , Mata‐Falcón Jaime , Kaufmann Walter 
Published: March 2022

AbstractConcrete tensile stresses influence the cracking behaviour and the stiffness of reinforced concrete (RC) members. Most design codes account for this tension stiffening effect using an effective reinforcement ratio. Although this ratio has a significant influence on the design of RC structures, its quantification is controversial in many cases, and typically relies on empirical geometry‐based expressions. One main reason for this knowledge gap is that the area of concrete in tension can only be verified indirectly, for example, through crack widths and spacings and using a suitable mechanical model. This indirect validation is subject to considerable uncertainty as it depends on parameters that scatter (e.g., bond stresses and the concrete tensile strength), and further assumptions relating internal stresses to the applied loads are required. This article outlines how refined measurements of the reinforcing steel strains and the concrete deformations in the compression zone, combining distributed fibre optic sensing (DFOS) and digital image correlation (DIC), can be used in order to obtain a more reliable quantification of the parameters affecting tension stiffening and hence, the effective reinforcement ratio. Selected models are validated against experimental data of an RC beam tested under four‐point bending, underlining the potential of DFOS and DIC as valuable tools for a better understanding of RC structures and the enhancement of mechanical models.
First evidence of Crimean‐Congo haemorrhagic fever virus circulation in Bosnia and Herzegovina
Authors: Satrovic Lejla , Softic Adis , Zuko Almedina , Kustura Aida , Koro Amira , Goletic Sejla , Satrovic Edin , Llorente Francisco , Pérez‐Ramírez Elisa , Omeragic Jasmin , Salkic Jasna , Alic Amer , Jiménez‐Clavero Miguel Angel , Goletic Teufik 
Published: March 2022

AbstractBackgroundCrimean–Congo haemorrhagic fever (CCHF) is a widespread tick‐borne zoonosis with reported detection of virus and/or virus‐specific antibodies from over 57 countries across Africa, Asia, Europe and the Middle East and is endemic in the Balkans. Detection of Crimean–Congo Haemorrhagic Fever Virus (CCHFV) antibodies in domestic ruminants has been important in providing initial evidence of virus circulation and in localising CCHFV high‐risk spots for human infection.ObjectivesThe present study investigated the possible exposure of sheep to CCHFV in Bosnia and Herzegovina (B&H).MethodsTo investigate the presence of anti‐CCHFV antibodies in sheep, all sera (n = 176) were tested using multi‐species double antigen enzyme‐linked immunosorbent assay (ELISA). Reactive sera were further complementary tested by adapted commercial indirect immunofluorescence assay (IFA) using FITC‐conjugated protein G instead of anti‐human immunoglobulins.ResultsCCHFV specific antibodies were detected in 17 (9.66%) animals using ELISA test. All negative sera were determined as negative by both tests, while 13 out of 17 ELISA‐positive reactors were also determined as unambiguously positive by IFA test. The age group with the highest proportion of seropositive rectors were the oldest animals.ConclusionsThis is the first report of anti‐CCHFV antibodies in sheep from B&H providing the evidence of CCHFV circulation in the country's sheep population. So far, these findings indicate the circulation of the virus in the westernmost region of the Balkans and point to the potential CCHFV spread further out of this endemic area.
Fracture rate and time to fracture in dogs with appendicular osteosarcoma receiving finely fractionated compared to coarsely fractionated radiation therapy: A single institution study
Authors: Norquest Carissa J. , Maitz Charles A. , Keys Deborah A. , Moore Melanie , Bryan Jeffrey N. , Ehling Tara J. , Lattimer Jimmy C. , Flesner Brian K. 
Published: March 2022

AbstractBackgroundRadiation therapy (RT) is used for local pain alleviation in dogs with appendicular osteosarcoma (OS), especially among dogs that are poor surgical candidates for amputation. However, many historical reports of fractionated protocols lack time to fracture and fracture rates.ObjectivesThe primary objectives of this retrospective study were to determine fracture rate and time to fracture of dogs receiving RT (coarse or fine fractionated) for appendicular OS. Secondary objectives were to evaluate tolerability and disease outcome measures.MethodsFifty‐one dogs that received RT as part of treatment for appendicular OS were available for evaluation. Forty‐five received coarse fractionation (C‐RT, 8 or 6 Gy per fraction protocols [C‐RT8 or C‐RT6]) while the remaining six received fine fractionation (F‐RT).ResultsThe overall pathologic fracture rate was 37%. Pathologic fracture rate was significantly higher for dogs that received F‐RT (5/6, 83%) compared to dogs that received C‐RT (12/40, 30%, p = 0.021). In the 17 dogs that fractured, the overall median time to fracture was 57 days. For all dogs, the median progression free interval (PFI) and median overall survival time (OST) were 90 and 140 days, respectively. In a very small cohort of dogs (n = 7) treated with zoledronate and RT, fracture rate was 0% and extended survival times were noted.ConclusionsIn conclusion, C‐RT is recommended over F‐RT due to lower risk of pathologic fracture and similar PFI. Prospective evaluation of combined C‐RT and zoledronate, especially for dogs with poor surgical candidacy, is warranted for the treatment of canine appendicular osteosarcoma.
Antioxidant activity of mango seed wax additive on the properties of poly(lactic acid) transparent films for food packaging application
Authors: Thomas Tesi , Olongal Manaf , Athiyanathil Sujith 
Published: March 2022

AbstractTo improve the tensile properties of poly(lactic acid) (PLA) biodegradable packaging film, mango seed wax (MSW), an agro‐industrial waste from the mango fruit processing industry has been used as a plasticizing additive. Four different weight ratios of MSW (3, 5, 7, and 9 wt%) in pristine PLA were considered for optimization. The mechanical properties comprising tensile strength, elongation at break, and Young's modulus were studied. Characterizations such as Fourier transform infra‐red (FTIR) spectroscopy, and differential scanning calorimetry were studied. Oxidation induction time (OIT) analysis of samples was also conducted. Other studies such as thermal, barrier, and optical properties were also evaluated. The differential scanning calorimetry (DSC) analysis revealed better compatibility between MSW and PLA matrices. A small decrease in glass transition temperature (10%), and melting point (3%) was observed when increasing the percentage of MSW in PLA. Moreover, the visual transparency of MSW/PLA systems was intact when increasing the loading. The addition of 9% MSW results in a 700% enhancement in elongation at break than that of pristine PLA. The optimized sample (PLA with 5% MSW) showed a 26% improvement in the hydrophobicity of the PLA matrix. The barrier properties (55.6% in WVTR and 10% in oxygen transmission rate (OTR) were also improved by the presence of MSW. These are promising systems as a suitable material for biodegradable food packaging thermoplastic material.
Removal of an intracardiac sewing needle without inflow occlusion or cardiopulmonary bypass in a dog
Authors: Maggiar Adrien , Testault Isabelle , Billet Jean‐Philippe 
Published: March 2022

AbstractA 3.5‐year‐old Australian shepherd dog referred for the exploration and management of an intrathoracic sewing needle. The animal had a history of cardiovascular collapse the previous day. On presentation, the dog was asymptomatic, bright, alert and responsive. Computed tomography scan and echocardiography confirmed the presence of a sewing needle in the heart, with moderate pericardial and bilateral pleural effusions. Using careful blind palpation of the heart after sternotomy, the sewing needle was pushed through the myocardium and retrieved without haemorrhage. Recovery was uneventful and the dog returned to full exercise. This case report describes the migration of a sewing needle into the heart from an unspecified origin, an atypical removal, and a good postoperative outcome in a 3.5‐year‐old Australian shepherd dog.
Machine intelligence for chemical reaction space
Authors: Schwaller Philippe , Vaucher Alain C. , Laplaza Ruben , Bunne Charlotte , Krause Andreas , Corminboeuf Clemence , Laino Teodoro 
Published: March 2022

AbstractDiscovering new reactions, optimizing their performance, and extending the synthetically accessible chemical space are critical drivers for major technological advances and more sustainable processes. The current wave of machine intelligence is revolutionizing all data‐rich disciplines. Machine intelligence has emerged as a potential game‐changer for chemical reaction space exploration and the synthesis of novel molecules and materials. Herein, we will address the recent development of data‐driven technologies for chemical reaction tasks, including forward reaction prediction, retrosynthesis, reaction optimization, catalysts design, inference of experimental procedures, and reaction classification. Accurate predictions of chemical reactivity are changing the R&D processes and, at the same time, promoting an accelerated discovery scheme both in academia and across chemical and pharmaceutical industries. This work will help to clarify the key contributions in the fields and the open challenges that remain to be addressed.This article is categorized under:
Data Science > Artificial Intelligence/Machine Learning
Data Science > Computer Algorithms and Programming
Data Science > Chemoinformatics