bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of community engagement interventions to improve child immunisation in low‐ and middle‐income countries: A systematic review and meta‐analysis
Authors: Jain Monica , Shisler Shannon , Lane Charlotte , Bagai Avantika , Brown Elizabeth , Engelbert Mark , Vardy Yoav , Eyers John , Leon Daniela Anda , Parsekar Shradha S. 
Published: July 2022

AbstractImmunisation is one of the most cost‐effective interventions to prevent and control life‐threatening infectious diseases. Nonetheless, rates of routine vaccination of children in low‐ and middle‐income countries (LMICs) are strikingly low or stagnant. In 2019, an estimated 19.7 million infants did not receive routine immunisations. Community engagement interventions are increasingly being emphasised in international and national policy frameworks as a means to improve immunisation coverage and reach marginalised communities. This systematic review examines the effectiveness and cost‐effectiveness of community engagement interventions on outcomes related to childhood immunisation in LMICs and identifies contextual, design and implementation features that may be associated with effectiveness. We identified 61 quantitative and mixed methods impact evaluations and 47 associated qualitative studies related to community engagement interventions for inclusion in the reteview. For cost‐effectiveness analysis 14 of the 61 studies had the needed combination of cost and effectiveness data. The 61 included impact evaluations were concentrated in South Asia and Sub‐Saharan Africa and spread across 19 LMICs. The review found that community engagement interventions had a small but significant, positive effect on all primary immunisation outcomes related to coverage and their timeliness. The findings are robust to exclusion of studies assessed as high risk of bias. Qualitative evidence indicates appropriate intervention design, including building in community engagement features; addressing common contextual barriers of immunisation and leveraging facilitators; and accounting for existing implementation constraints and practicalities on the ground are consistently cited as reasons for intervention success. Among the studies for which we were able to calculate cost‐effectiveness, we find that the median non‐vaccine cost per dose of intervention to increase immunisation coverage by 1% was US $3.68. Given the broad scope of the review in terms of interventions and outcomes, there is significant variation in findings. Among the various types of community engagement interventions, those that involve creation of community buy‐in or development of new cadres of community‐based structures were found to have consistent positive effect on more primary vaccination coverage outcomes than if the engagement is limited to the design or delivery of an intervention or is a combination of the various types. The evidence base for sub‐group analysis for female children was sparse (only two studies) and the effect on coverage of both full immunisation and third dose of diphtheria pertussis tetanus for this group was insignificant.
The Evaluation of l‐Tryptophan Derivatives as Inhibitors of the l‐Type Amino Acid Transporter LAT1 (SLC7A5)
Authors: Graff Julien , Müller Jennifer , Sadurní Anna , Rubin Matthias , Canivete Cuissa Inês André , Keller Claudia , Hartmann Marco , Singer Simon , Gertsch Jürg , Altmann Karl‐Heinz 
Published: July 2022

AbstractA series of derivatives of the substrate amino acid l‐tryptophan have been investigated for inhibition of the L‐type amino acid transporter LAT1 (SLC7A5), which is an emerging target in anticancer drug discovery. Of the four isomeric 4‐, 5‐, 6‐, or 7‐benzyloxy‐l‐tryptophans, the 5‐substituted derivative was the most potent, with an IC50 of 19 μM for inhibition of [3H]‐l‐leucine uptake into HT‐29 human colon carcinoma cells. The replacement of the carboxy group in 5‐benzyloxy‐l‐tryptophan by a bioisosteric tetrazole moiety led to a complete loss in potency. Likewise, the corresponding tetrazolide derived from l‐tryptophan itself was found to be neither a substrate nor an inhibitor of the transporter. Increasing the steric bulk at the 5‐position, while reasonably well tolerated in some cases, did not result in an improvement in potency. At the same time, none of these derivatives was found to be a substrate for LAT1‐mediated transport.
Clickable Selenylation – a Paradigm for Seleno‐Medicinal Chemistry
Authors: Hou Wei , Dong Hewei , Yao Ying , Pan Kangyin , Yang Guang , Ma Peixiang , Xu Hongtao 
Published: July 2022

AbstractSelenium (Se) is an emerging versatile player in medicinal chemistry. The incorporation of Se into small molecules and natural products could have multiple benefits. However, the lack of efficient methods for the synthesis of Se‐containing chemical library has greatly hindered the development of seleno‐medicinal chemistry. With the aim to address this issue, we proposed the development of “clickable selenylation” reactions, which can be used in the synthesis of Se‐containing in situ library and DNA‐encoded library (SeDEL), thereby quickly producing ultra‐large collections of Se‐containing compounds and boosting the development of seleno‐medicinal chemistry. This research paradigm can be concluded as “clickable selenylation chemistry development→in situ library construction/SeDEL synthesis→phenotype‐ or target‐based screening→seleno‐hit compound”.
NSGA‐II‐XGB: Meta‐heuristic feature selection with XGBoost framework for diabetes prediction
Authors: Gupta Aditya , Rajput Ishwari Singh , Gunjan  , Jain Vibha , Chaurasia Soni 
Published: July 2022

SummaryDiabetes is one of the most prevalent causes of casualties in the modern world. Early diagnosis of diabetes is the most promising way for increasing the chances of patients' survival. The ever‐growing technology of the current era, machine learning‐based algorithms pave the door in the healthcare industry by delivering efficient decision support services in real‐time. However, high‐dimensionality of the data obtained using multiple sources increases the computation time and significantly impacts the models' efficiency in classifying the results. Feature selection improves learning performance and reduces the computational cost by selecting subsets of features and eliminating unnecessary and irrelevant features. In this article, an attempt has been made to develop a hybrid machine learning model based on non‐dominated sorting genetic algorithm (NSGA‐II) and ensemble learning for the efficient categorization of diabetes. The proposed work uses various data preprocessing techniques, such as missing data handling and normalization, prior to model training. The most prominent and salient features are selected by exploiting the potential of the NSGA‐II in the diabetes dataset. Finally, an ensemble learning‐based extreme gradient boosting (XGBoost) model is modeled using features selected by NSGA‐II to classify patients as diabetic or non‐diabetic. The proposed methodology is experimentally validated using a hybridized dataset comprising 23 features, with 1288 instances of both male and female patients between the ages of 21 and 65. In addition, for performance evaluation, the results of statistical parameters are compared with several state‐of‐the‐art decision‐making models in the current domain. Experiment findings exemplify that the proposed NSGA‐II‐XGB approach gives better classification results with an average accuracy of 98.86%. Furthermore, the statistical results of specificity (88.6%), sensitivity (96.36%), and F‐score (97.84%) also support the utility of the proposed methodology in the early diagnosis of diabetes.
Molecular Electrides: An In Silico Perspective
Authors: Saha Ranajit , Das Prasenjit , Chattaraj Pratim Kumar 
Published: July 2022

AbstractElectrides are defined as the ionic compounds where the electron(s) serves as an anion. These electron(s) is (are) not bound to any atoms, bonds, or molecules but are rather localized into the space, crystal voids, or interlayer between two molecular slabs. There are three major categories of electrides, known as organic electrides, inorganic electrides, and molecular electrides. The computational techniques have proven as a great tool to provide emphasis on the electride materials. In this review, we have focused on the computational methodologies and criteria that help to characterize molecular electrides. A detailed account of the computational methods and basis sets applicable for molecular electrides have been discussed along with their limitations in this field. The main criterion for the identification of the electrides has also been discussed thoroughly with proper examples. The molecular electrides presented here have been justified with all the required criteria that support and proved their electride characteristics. We have also presented few systems which have similar properties but are not considered as molecular electrides. Moreover, the applicability of the electrides in catalytic processes have also been presented.
Structural, Photophysical, and Water Sensing Properties of Pyrazolo[1,5‐a]pyrimidine‐Triphenylamine Hybrid Systems
Authors: Tigreros Alexis , Macías Mario , Portilla Jaime 
Published: July 2022

AbstractThermal, structural, and photophysical properties of five pyrazolo[1,5‐a]pyrimidine‐triphenylamine hybrid systems substituted at position 3 of the fused ring were studied (probe/R: D1/H, D2/I, D3/CCSiMe3, D4/CHO, D5/CN). The solvatofluorochromism of D4 and D5 showed that the solvent dipolarity (SdP) is mainly responsible for their spectral changes, which arose from an internal charge transfer (ICT) from the triphenylamine (TPA) group to the acceptor substituent at position 3. As a result, D5 was applied for the detection of water in organic solvents (i. e., AcOEt and THF); this probe also exhibited an intense light emission in the solid‐state at 530 nm (ϕ=0.60). The five compound structures were solved and analyzed by X‐ray crystallography (XRC), with a link found between their structural characteristics and their physicochemical properties. For example, although all the probes exhibited good thermostabilities, this property decreased in D3 and was explained by frontier molecular orbital calculations based on the XRC results. Crystallographic studies were also used to interpret the differences in solid‐phase emission intensities in D1–D4 versus D5.
Computer‐Assisted Design of Sustainable Syntheses of Pharmaceuticals and Agrochemicals from Industrial Wastes
Authors: Le Pogam Pierre , Papon Nicolas , Beniddir Mehdi A. , Courdavault Vincent 
Published: July 2022

AbstractComputer‐based strategies vastly enhanced the field of analytical chemistry. The impact of data‐driven technologies in shaping organic chemistry strategies long remained comparatively elusive but various tools recently emerged to computationally plan multistep organic syntheses. A recent study elegantly takes benefit of an in‐house library of chemical reactions enriched with various metadata to provide numerous, reliable and realistic organic chemistry workflows to structurally‐varied drugs of interest, from locally available industrial by‐products. The retrieval of the different synthetic pathways and a scoring based on different features, especially comprising sustainability considerations, are also proposed.
Analysis and implementation of an isolated high step‐down converter with interleaved output for low voltage applications
Authors: Sani Sajad Ghabeli , Banaei Mohamad Reza , Hosseini Seyed Hossein 
Published: July 2022

AbstractThis paper proposes a new isolated high step‐down dc‐dc converter with a more extensive output range and high efficiency. The interleaved output and ZVS‐ZCS switching for all semiconductors have made the converter appropriate for high output current applications. An auxiliary inductor is used to achieve the ZVS (zero‐voltage switching) and ZVZCS (zero‐voltage zero‐current switching) condition, which charges and discharges the parallel snubber capacitors of the power switches at different modes of operation. Therefore, the switching losses of semiconductor components are reduced significantly, which results in enhanced efficiency. Moreover, the connection of an auxiliary capacitor in series with the transformer has prevented the probability of DC‐current saturation. The proposed converter could be controlled with duty‐cycle or switching frequency variations. However, the output voltage control with the switching frequency variations gives an extended range of output voltage compared with the other presented converters. Moreover, a coupled inductor is used to relate the output gain with the turn ratios, which causes a more extensive range for output voltage gain. Finally, the theoretical analysis is given and is compared with a 140 W experimental prototype, which converts a higher input voltage 300v to 7.5 V of the output voltage.
Oscillating droplet tribometer for sensitive and reliable wetting characterization of superhydrophobic surfaces
Authors: Junaid Muhammad , Nurmi Heikki A. , Latikka Mika , Vuckovac Maja , Ras Robin H. A. 
Published: July 2022

AbstractAccurate wetting characterization is crucial for the development of next‐generation superhydrophobic surfaces. Traditionally, wetting properties are measured with a contact angle goniometer (CAG) suitable for a broad range of surfaces. However, due to optical errors and challenges in baseline positioning, the CAG method suffers from inaccuracies on superhydrophobic surfaces. Here we present an improved version of the oscillating droplet tribometer (ODT), which can reliably assess wetting properties on superhydrophobic surfaces by measuring the frictional forces of a water‐based ferrofluid droplet oscillating in a magnetic field. We demonstrate that ODT has superior accuracy compared to CAG by measuring the wetting properties of four different superhydrophobic surfaces (commercial Glaco and Hydrobead coatings, black silicon coated with fluoropolymer, and nanostructured copper modified with lauric acid). We show that ODT can detect the small but significant changes in wetting properties caused by the thermal restructuring of surfaces that are undetectable by CAG. Even more, unlike any other wetting characterization technique, ODT features an inverse sensitivity: the more repellent the surface, the lower the error of measurement, which was demonstrated by experiments and simulations.
Increasing tree density accelerates stand‐level nitrogen cycling at the taiga–tundra ecotone in northeastern Siberia
Authors: Hewitt Rebecca E. , Alexander Heather D. , Izbicki Brian , Loranty Michael M. , Natali Susan M. , Walker Xanthe J. , Mack Michelle C. 
Published: July 2022

AbstractAs climate warms, tree density at the taiga–tundra ecotone (TTE) is expected to increase, which may intensify competition for belowground resources in this nitrogen (N)‐limited environment. To determine the impacts of increased tree density on N cycling and productivity, we examined edaphic properties indicative of soil N availability along with aboveground and belowground tree‐level traits and stand characteristics related to carbon (C) and N cycling across a tree density gradient of monodominant larch (Larix cajanderi) at the TTE in far northeastern Siberia. We found no consistent evidence from soil, tree, or stand‐level N cycling characteristics of lower N availability or greater intraspecific competition for N with increased density. Active layer thickness declined, but resin‐sorbed N and soil organic layer thickness did not covary with increased tree density. There was, however, greater allocation belowground to stand‐level coarse and fine roots with increased tree density, an allocation pattern suggestive of limited soil resources. Foliar traits related to C (%C, δ13C, and resorption) were responsive to density indicating the importance of non‐nutrient resources, like light, to foliar stoichiometry. As tree density increased and individual trees had lower productivity, tree‐level N and biomass pools aboveground and belowground declined tracking decreases in N uptake, N resorption, N use efficiency, and allocation to slow cycling tissues like wood. At the stand level, our findings show high N turnover with increased N acquisition, allocation to short‐lived tissues with relatively high N content and reduced N residence time, and greater stand productivity as tree density increased. Yet, these positive relationships were curtailed at the highest tree densities. Our observations of shifts in biomass, C and N allocation, and loss aboveground, along with greater root density with increased tree density, could have strong impacts on C and N cycling and should be represented in models of TTE dynamics and feedbacks to climate.
Implications of habitat‐driven survival and dispersal on recruitment in a spatially structured piping plover population
Authors: Swift Rose J. , Anteau Michael J. , Ellis Kristen S. , Ring Megan M. , Sherfy Mark H. , Toy Dustin L. , Koons David N. 
Published: July 2022

AbstractNatal survival and dispersal have important consequences for populations through the movement of genes and individuals. Metapopulation theory predicts either balanced natal dispersal among regions or source–sink dynamics, which can dramatically change population structure. For species reliant on dynamic, early‐successional habitats, availability and location of habitat will shift from year to year, requiring primiparous individuals to locate an appropriate breeding habitat. We estimated hatch‐year survival to adulthood and natal dispersal rates between two breeding groups of Northern Great Plains piping plovers (Charadrius melodus) from four cohorts (n = 2669 total individuals; 2014–2017). Hatch‐year survival to adulthood was slightly higher for individuals hatched on the Missouri River than on the US Alkali Wetlands but declined over time. Individuals hatched on the US Alkali Wetlands were more likely to disperse to breed on the Missouri River (0.33 [0.20, 0.48]) than vice versa (0.17 [0.11, 0.24]). When more habitat was available at the natal site than in the prior year, natal dispersal rates increased. However, despite higher recruitment rates as a result of higher natal fidelity, the Missouri River showed lower total recruitment with a declining trend in the number of recruits, largely due to differences in abundance between breeding groups. Overall, unbalanced, high natal dispersal rates within the Northern Great Plains indicate high connectivity among distinct regions with different water regimes on the Missouri River and on the US Alkali Wetlands driven by fluctuating availability of habitat. Our results suggest that plovers in the Northern Great Plains take advantage of dynamic habitats where they are available in a broad geographic area, which is consistent with a spatially structured panmictic population rather than a true metapopulation, but further research on adult breeding dispersal is needed to clarify population structure.
Copper‐Catalyzed Synthesis of O/N‐Alkyl S‐Phenyl Phenylcarbamothioates: An Odorless and Chemo‐selective Chan–Lam Reaction to Construct C−S Bond
Authors: Wu Yu−Xi , Wang Xi , Li Jing‐Hang , Xiao Hua‐Qing , Dong Zhi‐Bing 
Published: July 2022

AbstractA simple and efficient synthetic method to C−S bonds was established based on the Chan–Lam reaction. A series of O/N‐alkyl S‐phenyl phenylcarbamothioates were obtained in good yields by using odorless O/N‐alkyl phenylthiocarbamates as sulfur sources and commercially available phenylboronic acids as substrates catalyzed by Cu(OAc)2. This methodology features simple performance, odorless sulfur source, easily available starting material, good functional group tolerance, and high chemo‐selectivity to construct C−S bonds, thereby providing an alternative way to the synthesis of potentially bioactive compounds.
Performance of a fuel cell‐based proton battery with varied designs of micro‐flow channel for enhanced hydrogen storage
Authors: Singh Gurwinder , Oberoi Amandeep Singh , Kansal Harmesh K. , Singh Amrinder Pal 
Published: July 2022

AbstractWe present an experimental investigation on a proton battery, that could run both as electrolyser and fuel cell, using six different flow channel orientations viz. pin‐type, parallel, interdigitated, spiral, serpentine, and parallel serpentine. The battery stores energy in the form of hydrogen ions and its performance is determined in terms of hydrogen wt. % stored in an integrated carbon‐based electrode. In this paper, the fabrication of electrode, development of an experimental proton battery and its testing are disclosed. The characterization of the employed activated carbon electrode is done using scanning electron microscopy, X‐ray diffraction analysis, energy dispersive spectroscopy, and fourier transform infrared spectroscopy. The fabricated proton battery is tested by charging (E‐mode operation) and discharging (FC‐mode operation) subsequently at normal temperature and pressure conditions. In the E‐mode operation, electrochemical hydrogen storage of the battery with six different flow channels is found to be in the range of 1.36–1.97 wt. %. The corresponding desorption of hydrogen in the FC‐mode operation is found to be in the range of 1.047–1.479 wt. %, respectively, for six different flow channels. The comparative result analysis revealed that parallel serpentine flow channel outperformed, with energy storage capacity of 1.97 wt. %; and pin type channel design showed comparatively low performance with energy storage capacity of 1.36 wt. %. The presented research work is an effort towards meeting the set targets of hydrogen storage set by the U.S. Department of Energy to make the hydrogen technology commercially viable.Statement of Industrial RelevanceThe presented research work has relevance with the power industry as it reveals the optimum design of flow channels for enhanced hydrogen adsorption. It is a way forward towards developing a fuel‐cell based proton battery that does not emit harmful fumes like lithium batteries and therefore, is environmentally friendly.Novelty or SignificanceThe presented research work is a maiden attempt of testing different designs of micro‐flow channels in an experimental proton battery that is a single unit capable of performing dual tasks i.e., electrolyser and fuel cell to store energy and give out power when required.
Facile synthesis of Fe3O4@TMU‐12 (Co‐based magnetic MOF) for extraction of diazinon and chlorpyrifos from the environmental water samples
Authors: Bahiraee Zeinab , Fathi Sohrab , Safari Meysam 
Published: July 2022

AbstractIn this study, magnetic metal‐organic framework composite (Fe3O4@ TMU‐12) was fabricated and used as an efficient sorbent for magnetic solid‐phase extraction of the diazinon and chlorpyrifos from environmental water samples. By simultaneous use of magnetic solid‐phase extraction and high‐performance liquid chromatography, a simple, quick, exact, and affordable method for the determination of diazinon and chlorpyrifos was achieved. The extraction conditions and efficiency of the magnetic framework composite for diazinon and chlorpyrifos were investigated. Under optimal conditions, the relative recoveries and preconcentration factors of the studied compounds were obtained in the range of 92.0%–99.3% and 201–210, respectively. The calibration curves were obtained in the range of 2–250 μg L−1 and 4–250 μg L−1 for diazinon and chlorpyrifos in water samples, respectively. The LODs were 0.5 and 0.8 μg L−1 for diazinon and chlorpyrifos, respectively (based on S/N = 3). The precision evaluated in terms of the relative standard deviations of intra‐ and inter‐day tests ranged from 3.4% to 3.8% and from 3.9% to 4.1%, respectively. The results show that the Fe3O4@TMU‐12 combine advantages of magnetic nanoparticles and metal‐organic frameworks, and are the promising sorbents in the magnetic solid‐phase extraction of diazinon and chlorpyrifos from environmental water samples.