bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scabies surrepticius: An uncommon presentation of a common dermatosis
Authors: Kouki Chaima , Korbi Mouna , Manaa Linda , Njim Laila , Mohamed Mariem , Belhadjali Hichem , Zili Jameleddine 
Published: July 2022

AbstractWe report an atypical presentation of a common disease to highlight the importance of making a correct diagnosis of scabies surrepticius in front of any itchy dermatosis especially in elderly patients. The misdiagnosis of this disease results in extensive infestation, especially with the use of corticosteroids.
Atrial septal defect device closure and concurrent atrio‐fascicular Mahaim ablation in adult patient with Ebstein's anomaly
Authors: Khajali Zahra , Firouzi Atta , Kabir Masoud Farzad , Harirforoosh Iman , Aliramezany Maryam 
Published: July 2022

AbstractEbstein's anomaly is an uncommon congenital malformation which might be associated with atrial septal defect and atrio‐fascicular Mahaim. Here, we report a known case of Ebstein's anomaly with atrial septal defect and concomitant atrio‐fascicular Mahaim pathway who underwent atrial septal defect device closure and concurrent ablation of accessory pathway.
High Sugar Production from Hydrolysate of Pineapple Residues via Integrated Enzyme‐Membrane System
Authors: Ayanasamy Kohmalam , Baharudin Aishah , Jamek Shariza , Saufi Syed M. , Hairom Nur Hanis Hayati , Mohd Sueb Mohd Shafiq 
Published: July 2022

AbstractThe enzyme‐membrane integrated system has become an attractive method for the depolymerization of lignocellulosic biomass. The effects of pH, temperature, enzyme loading, and reaction time were evaluated in order to maximize the sugar production. Hydrolysate extracted from pineapple leaves was used as a substrate. The feed substrate was hydrolyzed by β‐xylosidase under different working conditions using the one‐factor‐at‐a‐time (OFAT) method. The best working conditions obtained via enzymatic hydrolysis were applied in the enzyme‐membrane integrated system. The sugar yield obtained by simultaneous reaction and filtration was much higher (293.94 %) than by the reaction alone (32.23 %).
Tracking of Dissolved Oxygen Distribution and Consumption Pattern in a Bespoke Bacterial Growth System
Authors: Mulakhudair Ali R. , Al-Mashhadani Mahmood K. H. , Kokoo Rungrote 
Published: July 2022

AbstractMicrobial cells are used to produce valuable bioproducts. Dense cultures, however, have a high demand for dissolved oxygen which is challenging, considering the low solubility of oxygen in liquid. This study of design and simulation of a gaslift bioreactor highlights a vital limitation of growth, which is the oxygen limitation and sustain aerobic cultures. The aerobic growth has the effect of greatest resource efficiency in that the highest fraction of dosing is done with the largest concentration driving force near critical dissolved oxygen levels and the lowest fraction occurs with near saturated dissolved oxygen values. The results indicate that oxygen homogeneously distributed with limited dead zones at the bottom. The developed system produces 40.5 % more biomass compared with conventional systems, which suffer from oxygen depletion.
Tuning the Electrode Activity to Expose Transformational and Electrocatalytic Characteristics of Individual Nanoparticles by Nanoimpact Electrochemistry
Authors: Kostopoulos Nikolaos , Vieira Mathias Miranda , Godeffroy Louis , Médard Jérôme , Combellas Catherine , Lemineur Jean‐Francois , Kanoufi Frédéric , Noël Jean‐Marc 
Published: July 2022

AbstractNanoimpact electrochemistry (NIE) is a straightforward analytical technique to study at high throughput the reactivity of single nanoparticles (NPs) colliding with a biased ultramicroelectrode (UME). As NIE can reveal both NP size and catalytic activity, this strategy can be employed to establish relationships between these two NP descriptors. Herein, it is shown that the electrode material is crucial for visualizing simultaneously electrocatalytic processes and NP transformation, which can size the NPs. UMEs made of gold (Au) or glassy carbon (GC), were employed to study the reduction of AgBr NPs and the electrocatalytic activity of the resulting Ag NPs for the oxygen reduction reaction (ORR). With Au UME, only the transformation process is probed, allowing a quantitative analysis of the overpotential effect on the reduction dynamics of the AgBr NPs. When a GC UME is employed, the AgBr NPs reduction and subsequent ORR activity can be quantified for the very same NPs.
A Chemically Fuelled Molecular Automaton Displaying Programmed Migration of Zn2+ Between Alternative Binding Sites
Authors: Wootten Matthew M. , Tshepelevitsh Sofja , Leito Ivo , Clayden Jonathan 
Published: July 2022

AbstractA molecular system comprising a cationic zinc complex and an amino acid‐derived ambident ligand having phosphate and carboxylate binding sites undergoes a series of rearrangements in which the metal cation migrates autonomously from one site to another. The location of the metal is identified by the circular dichroism spectrum of a ligated bis(2‐quinolylmethyl)‐(2‐pyridylmethyl)amine (BQPA) chromophore, which takes a characteristic shape at each binding site. Migration is fuelled by the decomposition of trichloroacetic acid to CO2 and CHCl3, which progressively neutralises the acidity of the system as a function of time, revealing in sequence binding sites of increasing basicity. The migration rate responds to control by variation of the temperature, water content and triethylamine concentration, while an excess of fuel controls the duration of an induction period before the migration event.
Synthesis of Cage‐Shaped Borates Bearing Pyrenylmethyl Groups: Efficient Lewis Acid Catalyst for Photoactivated Glycosylations Driven by Intramolecular Excimer Formation
Authors: Tsutsui Yuya , Tanaka Daiki , Manabe Yoshiyuki , Ikinaga Yuka , Yano Kumpei , Fukase Koichi , Konishi Akihito , Yasuda Makoto 
Published: July 2022

AbstractWe describe the synthesis and characterization of a photoactivated boron‐based Lewis acid catalyst based on a cage‐shaped triphenolic ligand with three pyrenylmethyl moieties. The obtained cage‐shaped borate functioned as a photoactivated Lewis acid catalyst thanks to the flexible three pyrenylmethyl moieties. The deformation of the cage‐shaped scaffold driven by intramolecular excimer formations of the pyrenes is a critical factor in realizing the photoactivation. Mannich‐type reactions and glycosylations significantly were accelerated under 370 nm light irradiations. It is noteworthy that various glycosyl fluorides, which are not easily activated in photocatalytic systems due to their high C−F bond stability, are activated by the photoimproved catalytic activity of the catalyst.
A New Discovery towards Novel Skeleton of Benzimidazole‐Conjugated Pyrimidinones as Unique Effective Antibacterial Agents
Authors: Yang Xi , Syed Rasheed , Fang Bo , Zhou Cheng‐He 
Published: July 2022

Comprehensive SummaryA class of new potential antibacterial agents with distinctive pyrimidinone benzimidazole skeleton was developed through nucleophilic substitution and Biginelli reaction starting from urea, ethyl 4‐chloroacetoacetate and various aldehydes. Some target molecules exhibited strong antibacterial activities, especially pyrimidinone benzimidazole hybrid 9e possessed the strongest inhibitory effects on the growth of E. faecalis and P. aeruginosa with a lower MIC value of 1 μg/mL than norfloxacin. Moreover, compound 9e displayed strong antibiofilm capacity, low drug resistance and excellent biosafety toward human red blood cells. Further research revealed that compound 9e could disrupt membrane integrity and cause leakage of cellular components such as proteins and nucleic acids. Meanwhile, compound 9e could decrease lactate dehydrogenase activity, block cell metabolism and interact with DNA in an intercalation manner. ADMET analysis predicated that molecule 9e possessed promising pharmacokinetic properties and good bioavailability profile.
Pentagon‐Containing Doublet Graphene Fragments with Edge‐Dependent Spin/Charge Distribution
Authors: Gong Zongcheng , Xiang Qin , Li Ke , Xu Zhuofan , Hu Jinlian , Ni Yong , Sato Sota , Sun Zhe 
Published: July 2022

Comprehensive SummaryThe synthesis of stable open‐shell hydrocarbon system comprising of pentagon defects and zigzag edges remains unexplored, which can be considered as model compounds for unraveling the spin‐localized states in graphene edges. With concise synthetic approaches, two π‐extended fluorenyl radicals were synthesized and isolated in their crystalline state. X‐ray crystallographic analysis and studies on the magnetic, optical and electrochemical properties of neutral and charged species have revealed an interesting edge‐dependence of the spin/charge distribution, that is, the spin and charge distribution shifted from the pentagon defects to the zigzag edges with the elongation of conjugation. Such phenomenon was unprecedented for hydrocarbon radicals and can be rationalized by the recovery of Clar Sextets in the dominant resonance structures. Remarkably, one of the radicals exhibited exceptional stability in air‐saturated solutions with the half‐life time up to 260 d, thus providing opportunities for the applications as electronic materials.
CXCL8 expression is associated with advanced stage, right sidedness, and distinct histological features of colorectal cancer
Authors: Pennel Kathryn AF , Quinn Jean A , Nixon Colin , Inthagard Jitwadee , van Wyk Hester C , Chang David , Rebus Selma ,   GPOL Group, Hay Jennifer , Maka Noori N , Roxburgh Campbell SD , Horgan Paul G , McMillan Donald C , Park James H , Roseweir Antonia K , Steele Colin W , Edwards Joanne 
Published: July 2022

AbstractCXCL8 is an inflammatory chemokine elevated in the colorectal cancer (CRC) tumour microenvironment. CXCR2, the major receptor for CXCL8, is predominantly expressed by neutrophils. In the cancer setting, CXCL8 plays important roles in neutrophil chemotaxis, facilitating angiogenesis, invasion, and metastasis. This study aimed to assess the spatial distribution of CXCL8 mRNA expression in CRC specimens, explore associations with clinical characteristics, and investigate the underlying biology of aberrant CXCL8 levels. CXCR2 expression was also assessed in a second cohort of unique CRC primary tumours and synchronously resected matched liver metastases. A previously constructed tissue microarray consisting of a cohort of stage I–IV CRC patients undergoing surgical resection with curative intent (n = 438) was probed for CXCL8 via RNAscope®. Analysis was performed using HALO® digital pathology software to quantify expression in the tumour and stromal compartments. Scores were assessed for association with clinical characteristics. Mutational analyses were performed on a subset of these patients to determine genomic differences in patients with high CXCL8 expression. A second cohort of stage IV CRC patients with primary and matched metastatic liver tumours was stained via immunohistochemistry for CXCR2, and scores were assessed for clinical significance. CXCL8 expression within the stromal compartment was associated with reduced cancer‐specific survival in the first cohort (p = 0.035), and this relationship was potentiated in right‐sided colon cancer cases (p = 0.009). High CXCL8 within the stroma was associated with driving a more stromal‐rich phenotype and the presence of metastases. When stromal CXCL8 scores were combined with tumour‐infiltrating macrophage counts or systemic neutrophil counts, patients classified as high for both markers had significantly poorer prognosis. CXCR2+ immune cell infiltration was associated with increased stromal invasion in liver metastases (p = 0.037). These data indicate a role for CXCL8 in driving unfavourable tumour histological features and promoting metastases. This study suggests that inhibiting CXCL8/CXCR2 should be investigated in patients with right‐sided colonic disease and stroma‐rich tumours.
Machine Learning Guided Discovery of Non‐Hemolytic Membrane Disruptive Anticancer Peptides
Authors: Zakharova Elena , Orsi Markus , Capecchi Alice , Reymond Jean‐Louis 
Published: July 2022

AbstractMost antimicrobial peptides (AMPs) and anticancer peptides (ACPs) fold into membrane disruptive cationic amphiphilic α‐helices, many of which are however also unpredictably hemolytic and toxic. Here we exploited the ability of recurrent neural networks (RNN) to distinguish active from inactive and non‐hemolytic from hemolytic AMPs and ACPs to discover new non‐hemolytic ACPs. Our discovery pipeline involved: 1) sequence generation using either a generative RNN or a genetic algorithm, 2) RNN classification for activity and hemolysis, 3) selection for sequence novelty, helicity and amphiphilicity, and 4) synthesis and testing. Experimental evaluation of thirty‐three peptides resulted in eleven active ACPs, four of which were non‐hemolytic, with properties resembling those of the natural ACP lasioglossin III. These experiments show the first example of direct machine learning guided discovery of non‐hemolytic ACPs.
Localization of chemical synapses and modulatory release sites in the cardiac ganglion of the crab, Cancer borealis
Authors: Rue Mara C. P. , Baas‐Thomas Natasha , Iyengar Priya S. , Scaria Lara K. , Marder Eve 
Published: July 2022

AbstractThe crustacean cardiac ganglion (CG) comprises nine neurons that provide rhythmic drive to the heart. The CG is the direct target of multiple modulators. Synapsin‐like immunoreactivity was found clustered around the somata of the large cells (LC) and in a neuropil at the anterior branch of the CG trunk of Cancer borealis. This implicates the soma as a key site of synaptic integration, an unusual configuration in invertebrates. Proctolin is an excitatory neuromodulator of the CG, and proctolin‐like immunoreactivity exhibited partial overlap with putative chemical synapses near the LCs and at the neuropil. A proctolin‐like projection was also found in a pair of excitatory nerves entering the CG. GABA‐like immunoreactivity was nearly completely colocalized with chemical synapses near the LCs but absent at the anterior branch neuropil. GABA‐like projections were found in a pair of inhibitory nerves entering the CG. C. borealis Allatostatin B1 (CbASTB), red pigment concentrating hormone, and FLRFamide‐like immunoreactivity each had a unique pattern of staining and co‐localization with putative chemical synapses. These results provide morphological evidence that synaptic input is integrated at LC somata in the CG. Our findings provide a topographical organization for some of the multiple inhibitory and excitatory modulators that alter the rhythmic output of this semi‐autonomous motor circuit.
Literature review of vision‐based dynamic gesture recognition using deep learning techniques
Authors: Jain Rahul , Karsh Ram Kumar , Barbhuiya Abul Abbas 
Published: July 2022

SummaryGesture recognition is the foremost need in building intelligent human‐computer interaction systems to solve many day‐to‐day problems and simplify human life in this digital world. The traditional machine learning (ML) algorithm tried to capture specific handcrafted features, failed miserably in some real‐world environments. Deep learning (DL) techniques have become a sensation among researchers in recent years, making the traditional ML approaches quite obsolete. However, existing reviews consider only a few datasets on which DL algorithm has been applied, and the categorization of the DL algorithms is vague in their review. This study provides the precise categorization of DL algorithms and considers around 15 gesture datasets on which these techniques have been applied. This study also provides a brief overview of the numerous challenging dataset available among the research community and insight into various challenges and limitations of a DL algorithm in vision‐based dynamic gesture recognition.
MobEdge: Mobile blockchain‐based privacy‐edge scheme for healthcare Internet of Things‐based ecosystems
Authors: Deshmukh Varun , Pathak Sunil , Bothe Santosh 
Published: July 2022

SummaryCentralized healthcare Internet of Things (HIoT)‐based ecosystems are challenged by high latency, single‐point failures, and privacy‐based attacks due to data exchange over open channels. To address the challenges, the shift has progressed toward decentralized HIoT setups that infuse computation closer to a patient node via edge services. As HIoT data are critical and sensitive, trust among stakeholders is a prime concern. To address the challenges, researchers integrated blockchain (BCH) into edge‐based HIoT models. However, the integration of lightweight BCH is required with an edge for proper interplay and leverage effective, scalable, and energy‐efficient computational processes for constrained HIoT applications. Owing to the existing gap, this article proposes a schemeMobEdge, that fuses lightweight BCH, and edge computing to secure HIoT. A local BCH client model is set up that forwards data to edge sensor gateways. The shared data are secured through an access tree control lock scheme that preserves the privacy of health records. For security and signing purposes, we have considered signcryption, and the validated records meta‐information are stored in an on‐chain structure. The scheme is compared on two grounds, security and simulation grounds. On the security front, we do cost evaluation and present a formal analysis model using the Automated Validation of Internet Security Protocols and Applications tool. An edge‐based BCH setup use‐case is presented, and parameters like mining cost, storage cost, edge servicing latency, energy consumption, BCH network usage, and transaction signing costs are considered. In the simulation, the mining cost is 0.6675 USD, and improvement of storage costs are improved by 18.34%, edge‐servicing latency is 384 ms, and signcryption improves the signing cost by 36.78% against similar schemes, that indicates the scheme viability in HIoT setups.
Automatic classification and diagnosis of heart valve diseases using heart sounds with MFCC and proposed deep model
Authors: Yildirim Muhammed 
Published: July 2022

SummaryHeart sounds have been widely used for years to monitor and classify heart diseases. Experts manually examine these sounds, which is arduous and time‐consuming. In addition, since interpreting these sounds requires experience, experts who do not have enough experience may misinterpret these sounds. For this reason, a new deep one‐dimensional Convolutional Neural Network (1D‐CNN) architecture has been proposed to increase the detection accuracy and alleviate the workload of experts in the classification of sound signals used in the diagnosis of heart valve diseases. In the developed model, first, feature maps were obtained from heart sounds by using the MFCC method. High performance was achieved when the feature maps obtained later were classified in the developed deep architecture. Furthermore, the feature maps generated by the MFCC approach were classified using traditional machine learning classifiers. When the obtained results were compared, it was observed that the suggested deep model was more successful. In the developed architecture, an accuracy rate of 99.5% was obtained. The accuracy rate obtained shows that the developed architecture can be used to classify heart sounds and diagnose heart valve diseases.
Does board capital enhance corporate social responsibility disclosure quality? The role of CEO power
Authors: Maswadi Laila , Amran Azlan 
Published: July 2022

AbstractThis paper examines the relationship between board capital attributes and corporate social responsibility disclosure (CSRD) quality and how CEO power moderates the association between board capital attributes and CSRD quality. Using a cross‐sectional sample of 114 firms, we find that directors' experience and directors' interlocking have positive impacts on CSRD quality while directors' political ties have a significant negative impact on CSRD quality in Saudi firms. Contrary to our hypotheses, we find no support for the impacts of directors' education, directors' expertise, and board nationality on CSRD quality. Moreover, we find partial support for the moderation effects of CEO power. Overall, we theoretically highlight the roles of resource dependence theory and agency theory in enhancing CSRD quality.
A Survey of Catalytic Materials for Ammonia Electrooxidation to Nitrite and Nitrate
Authors: Johnston Sam , Cohen Sam , Nguyen Cuong K. , Dinh Khang N. , Nguyen Tam D. , Giddey Sarbjit , Munnings Christopher , Simonov Alexandr N. , MacFarlane Douglas R. 
Published: July 2022

AbstractStudies of the ammonia oxidation reaction (AOR) for the synthesis of nitrite and nitrate (NO2/3−) have been limited to a small number of catalytic materials, majorly Pt based. As the demand for nitrate‐based products such as fertilisers continues to grow, exploration of alternative catalysts is needed. Herein, 19 metals immobilised as particles on carbon fibre electrodes were tested for their catalytic activity for the ammonia electrooxidation to NO2/3− under alkaline conditions (0.1 m KOH). Nickel‐based electrodes showed the highest overall NO2/3− yield with a rate of 5.0±1.0 nmol s−1 cm−2, to which nitrate contributed 62±8 %. Cu was the only catalyst that enabled formation of nitrate, at a rate of 1.0±0.4 nmol s−1 cm−2, with undetectable amounts of nitrite produced. Previously unexplored in this context, Fe and Ag also showed promise and provided new insights into the mechanisms of the process. Ag‐based electrodes showed strong indications of activity towards NH3 oxidation in electrochemical measurements but produced relatively low NO2/3− yields, suggesting the formation of alternate oxidation products. NO2/3− production over Fe‐based electrodes required the presence of dissolved O2 and was more efficient than with Ni on longer timescales. These results highlight the complexity of the AOR mechanism and provide a broad set of catalytic activity and nitrate versus nitrite yield data, which might guide future development of a practical process for the distributed sustainable production of nitrates and nitrites at low and medium scales.
A simple rotor current estimation method for predictive control of multi‐phase drives
Authors: Satué Manuel G. , Arahal Manuel R. , Ortega Manuel G. , Ramírez Daniel R. 
Published: July 2022

SummaryPredictive control of stator currents is a model‐based technique needing an estimation of rotor currents, which are normally not measured. These currents affect the evolution of the stator currents and, therefore, also affect the predictions used by the controller. The usual procedure consists in correcting their effect by a simple feedback technique. In this article, the estimation of rotor currents is tackled based in the induction machine equivalent circuit. The proposed estimation procedure aims at improving the predictions with respect to the usual procedure. Simulation and experimental results are provided for the particularly demanding case of a multi‐phase induction machine, showing the superiority of the proposal.