bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combination of Asymmetric Organo‐ and Biocatalysis in Flow Processes and Comparison with their Analogous Batch Syntheses
Authors: Schober Lukas , Tonin Fabio , Hanefeld Ulf , Gröger Harald 
Published: January 2022

AbstractA sequential‐type as well as a tandem‐type chemoenzymatic flow cascade combining an organocatalytic aldol reaction and a biocatalytic reduction to form stereoselectively a 1,3‐diol with two stereogenic centers were developed. Initially, a comprehensive screening of 24 alcohol dehydrogenases was carried out and the identified candidates were applied in different multi‐step flow cascades. All four stereoisomers of the desired 1,3‐diol product are accessible via a sequential flow approach with product formation‐related conversions of up to 76 % over two steps, isolated yields of up to 64 % and enantiomeric excess of >99 % in all cases. In addition, a tandem‐type flow process, performing both reaction steps simultaneously, was established leading to 51 % conversion with >99 % ee and 8 : 1 d.r. and representing a combination of the fields of asymmetric chemocatalysis, biocatalysis and flow chemistry.
Ensemble‐based adaptive soft sensor for fault‐tolerant biomass monitoring
Authors: Siegl Manuel , Brunner Vincent , Geier Dominik , Becker Thomas 
Published: January 2022

AbstractThe accuracy and precision of soft sensors depend strongly on the reliability of underlying model inputs. These inputs (particularly readings of hardware sensors) are frequently subject to faults. This study aims to develop an adaptive soft sensor capable of reliable and robust biomass concentration predictions in the presence of faulty model inputs for aPichia pastorisbioprocess. Hence, three soft sensor submodels were developed based on three independent model inputs (base addition, CO2production, and mid‐infrared spectrum). An ensemble‐based algorithm combined the submodels to form an ensemble model, that is, an adaptive soft sensor, to achieve fault‐tolerant prediction. The algorithm's basic steps are as follows: the initial determination of submodel reliability is followed by selecting appropriate submodels to generate a reliable prediction via variance‐based weighting of the submodels. The adaptive soft sensor demonstrated high robustness and accuracy in biomass prediction in the presence of multiple simulated sensor faults (RMSE = 0.43 g L−1) and multiple real sensor faults (RMSE = 0.70 g L−1).
Monitoring and measurement analysis of key indexes for the implementation of mining, dressing, backfilling, and controlling technology in coal resources—A case study of Tangshan Mine
Authors: Qiang Zhang , Yang Kang , Zhang Jixiong , Wei Yin , Liu Xianwei , Wu Zhongya , Song Weijian , Xiling Xu 
Published: January 2022

AbstractBased on the mining, dressing, backfilling, and X technology framework, we proposed the key operation indexes by exploring the principle, system, and integrated process of “mining, dressing, backfilling, and controlling” technology. After that, the index monitoring method was established to further analyze the change law of key indexes and implementation effects of “mining, dressing, backfilling, and controlling” technology. The mining engineering of Tangshan mine showed that the “mining, dressing, backfilling, and controlling” technology solves the problems of gangue discharge, construction protection, and safe mining of compressed coal resources. The vertical feeding capacities and filling capacities are 337,171 and 422,428 t/year, respectively. The stress change in the filling body is consistent with the dynamic roof subsidence, with a compacting ratio of 81.3%. The average filling mass ratio (1.28) is greater than the design value (1.2). The maximum ground subsidence is 49 mm, and the deformation of the structure is controlled within the range of Level I. The research result provides evidence for the deepening of the theoretical and technical researches of “mining, dressing, backfilling, and X.” It also provides a technical reference for mines with similar geological conditions and engineering problems.
Mathematical modeling of impulse island controller to safely store the energy from high‐voltage lightning impulse
Authors: Jana Suman , Biswas Pabitra Kumar , Sain Chiranjit 
Published: January 2022

AbstractExtricating the energy from lightning impulse is very difficult for researchers due to the uncontrollability of hazardous and intermittent parameters. This paper proposed a mathematical method to island the lightning impulse to provide safety for the impulse storage system. The proposed model also can intelligently force the impulse to be extricated for the conversion system of the lightning energy storage device. This islanding controller is designed to increase the efficiency and safety of the storage system. Six essential parameters, that is, breakdown voltage, current dependency, spark channel radius, spark channel conductivity, coil inductance, and coil voltage, are considered to design the mathematical model. These parameters are formulated to record the responses of the proposed controller. All the equations are validated by using state of the art experiments and prototype hardware setup. The proposed method, mathematical model, and analyzed responses may assist lightning researchers in advancing lightning energy harvesting.
Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning
Authors: Balcilar Mehmet , Gabauer David , Gupta Rangan , Pierdzioch Christian 
Published: January 2022

AbstractUtilizing a machine learning technique known as random forests, we study whether regional output growth uncertainty helps to improve the accuracy of forecasts of regional output growth for 12 regions of the UK using monthly data for the period from 1970 to 2020. We use a stochastic volatility model to measure regional output growth uncertainty. We document the importance of interregional stochastic volatility spillovers and the direction of the transmission mechanism. Given this, our empirical results shed light on the contribution to forecast performance of own uncertainty associated with a particular region, output growth uncertainty of other regions, and output growth uncertainty as measured for London as well. We find that output growth uncertainty significantly improves forecast performance in several cases, where we also document cross‐regional heterogeneity in this regard.
Antimicrobial property of Pichia pastoris‐derived natto peptide against foodborne bacteria and its preservative potential to maintain pork quality during refrigerated storage
Authors: Dong Bin , Yu Cailing , Lin Yanjun , Zhou Guowen , Sun Chunlong , Wang Jun , Wu Tao 
Published: January 2022

AbstractPork spoilage caused by foodborne bacteria contamination always leads to substantial economic loss in the meat industry. The toxicity and drug resistance of chemical preservatives have raised public concerns about their safety and stability. In this study, natto peptide from Pichia pastoris was prepared using DNA recombinant technology. It showed an excellent antibacterial effect against Gram‐positive and ‐negative bacteria, with minimum inhibitory concentrations (MICs) ranging from 6 to 30 μg/ml. Of note, natto peptide exhibited low cytotoxicity and hemolytic activity. The application of natto peptide on pork during refrigerated storage dramatically decreased the growth of Staphylococcus spp., Escherichia spp., and Pseudomonas spp. The bactericidal properties remained in force when natto peptide was used in pork models contaminated with artificial bacteria. Moreover, the application of natto peptide (90 μg/ml) inhibited the increase in pH variation and drip loss, decreased the generation of total volatile basic nitrogen (TVB‐N) and thiobarbituric acid reactive substances (TBARS), and maintained a high sensory quality score during pork storage. These results implied that P. pastoris‐derived natto peptide could extend the storage time of pork, and it has the potential to be a promising antiseptic biopreservative to replace chemical preservatives.
High‐definition transcranial direct current stimulation of the occipital cortices induces polarity dependent effects within the brain regions serving attentional reorientation
Authors: Arif Yasra , Embury Christine M. , Spooner Rachel K. , Okelberry Hannah J. , Willett Madelyn P. , Eastman Jacob A. , Wilson Tony W. 
Published: January 2022

AbstractNumerous brain stimulation studies have targeted the posterior parietal cortex, a key hub of the attention network, to manipulate attentional reorientation. However, the impact of stimulating brain regions earlier in the pathway, including early visual regions, is poorly understood. In this study, 28 healthy adults underwent three high‐definition transcranial direct current stimulation (HD‐tDCS) visits (i.e., anodal, cathodal, and sham). During each visit, they completed 20 min of occipital HD‐tDCS and then a modified Posner task during magnetoencephalography (MEG). MEG data were transformed into the time‐frequency domain and significant oscillatory events were imaged using a beamformer. Oscillatory response amplitude values were extracted from peak voxels in the whole‐brain maps and were statistically compared. Behaviorally, we found that the participants responded slowly when attention reallocation was needed (i.e., the validity effect), irrespective of the stimulation condition. Our neural findings indicated that cathodal HD‐tDCS was associated with significantly reduced theta validity effects in the occipital cortices, as well as reduced alpha validity effects in the left occipital and parietal cortices relative to anodal HD‐tDCS. Additionally, anodal occipital stimulation significantly increased gamma amplitude in right occipital regions relative to cathodal and sham stimulation. Finally, we also found a negative correlation between the alpha validity effect and reaction time following anodal stimulation. Our findings suggest that HD‐tDCS of the occipital cortices has a polarity dependent impact on the multispectral neural oscillations serving attentional reorientation in healthy adults, and that such effects may reflect altered local GABA concentrations in the neural circuitry serving attentional reorientation.
TAFRO syndrome with fatigue and abdominal distension as the first symptom: A case report
Authors: Zhou Bai , Tang Chao , Chen Guiyang , Jiang Tiebin , Shi Xiao , Wang Fen 
Published: January 2022

AbstractTAFRO syndrome is a peculiar and rare type of multi‐centric Castleman's disease which contained a series of symptoms such as thrombocytopenia (T), anasarca (A), fever (F), reticulin fibrosis (R), and organomegaly (O). Here we provide a case of TAFRO syndrome with the manifestation of fatigue, abdominal distension, and low fever at primary diagnosis, characterized by multiple lymphadenopathy of superficial mediastinal and retroperitoneal lymph nodes, and it was finally confirmed by lymph node biopsy. The patient recovered speedy after receiving CHOP chemotherapy. In this case report, the patient has a history of dust‐exposure and hepatitis B virus infection, which may be potentially related to the disease. In addition, this case suggests the importance of pathological biopsy of complete lymph nodes in diagnostic process.
Spatial snowdrift modelling for an open natural terrain using a physically‐based linear particle distribution equation
Authors: Ohara Noriaki , He Siwei , Parsekian Andrew D. , Jones Benjamin M. , Rangel Rodrigo C. , Nichols Ian O. , Hinkel Kenneth M. 
Published: January 2022

AbstractSnowdrift, which results from deposition of wind transported snow, has been primarily estimated empirically rather than using physically‐based modelling since the snow redistribution process is extremely complex. This study demonstrates a practical predictive model for snow redistribution based on the Linear Particle Distribution equation, which consists of snow surface diffusion, snow surface advection, and snow surface erosion components. Here, we focus on numerical model development and implementation for two‐dimensional natural terrains at meter‐scale resolutions with and without perforated snow fences, which has been difficult to model in a two‐dimensional field. First, a selected numerical scheme was implemented in the Snow Movement Over Open Terrain for Hydrology model platform and tested by the exact solutions under a few well‐defined boundary conditions. Then, to simulate snowdrifts around the snow detention structures in the middle of the computational domain, an equivalent solid snow fence concept was introduced and tested. The model was applied to several terrains in the Laramie Range, Wyoming, and at two sites on the North Slope of Alaska, where wind‐induced snow redistribution plays a major role. Data from Airborne Light Detection and Ranging, Ground Penetrating Radar, and Unmanned Aerial Vehicle photogrammetry were used to calibrate and validate the model. The numerical snow redistribution model effectively reproduces the observed snowdrift distributions when snow densification and snowmelt effects were minimal. The model applications illustrated that the diffusion effect generally dominated snow redistribution with limited contributions of advection and erosion effects for abrupt terrain transition and perforated object, respectively.
Multiple instance learning for classifying histopathological images of the breast cancer using residual neural network
Authors: Abdelli Adel , Saouli Rachida , Djemal Khalifa , Youkana Imane 
Published: January 2022

AbstractDigital histopathological images have complex textures and high variability. Thus, classifying histopathological images requires an accurate classification and recognition of the tissue components in these images. In this article, we propose a novel classification layer based on multiple instances learning (MIL). In regular convolutional neural network (CNN) a flatten or a global pooling layer is used before the fully connected layers. However, in our proposed layer, we consider each last feature map in the network as an instance that will be classified by the output layer. Then, an aggregation function will be applied to get the class of the image (bag). This mapping helps the model to classify each feature independently to catch the micro‐objects of the complex tissue images. Also, our method succeeded in achieving high accuracy without the preprocessing of the images with color normalization, stain normalization, or any other techniques. Additionally, we trained our models in two different strategies. The first one is by combining the images from all the magnification factors, and the second is by training a model for each magnification factor. We show in this work that our model outperforms several previous works on breast cancer classification.
Transitioning to virtual interaction during the COVID‐19 pandemic: Impact on the Family Connects postpartum home visiting program activity
Authors: Rybińska Anna , Best Debra L. , Goodman W. Benjamin , Bai Yu , Dodge Kenneth A. 
Published: January 2022

AbstractIn this paper, we analyze program activity for Family Connects (FC), an evidence‐based postpartum home‐visiting intervention, during the COVID‐19 pandemic. When the pandemic began, FC transitioned to a virtual protocol which maintains key psychosocial components of the in‐person protocol and adjusts health assessments to address the lack of in‐person contact. Program performance is contrasted for periods before the pandemic onset (April 2019–March 2020) and after the onset (April 2020–March 2021), involving 10,280 scheduled visits and 6696 visited families (46% non‐Hispanic white; 20% non‐Hispanic Black; 23% Hispanic; and 10% other race). Post‐pandemic onset, FC program participation rates were at 89.8% of pre‐pandemic levels. Home visitors observed post‐onset increases in families’ concerns about home safety but declines in families’ needs related to infant care. Community connections were facilitated for 42.9% of visited families post‐pandemic onset compared to 51.1% pre‐pandemic onset. We conclude that post‐pandemic onset virtual delivery rates of FC declined but are high enough to merit continued implementation during a period when some families will decline in‐person visits. When in‐person visits are deemed safe per public health guidelines, the findings suggest a hybrid approach that could maximize program outreach by prioritizing in‐person contact and offering virtual delivery as a second choice.
Adaptation of infant mental health services to preterm infants and their families receiving neonatal intensive care unit services during the COVID‐19 pandemic
Authors: Kelleher Jessalyn , Dempsey Jack , Takamatsu Stephanie , Paul Jennifer J. , Kent Evamaria , Dempsey Allison G. 
Published: January 2022

AbstractMultiple changes and stressors at the family, hospital, and societal levels have resulted from the COVID‐19 pandemic that impact the early social environment of infants in Neonatal Intensive Care Unit (NICU) settings. This manuscript reviews these pandemic‐related adversities, including hospital‐wide visitor restrictions, mask requirements that interfere with caregiver facial expressions, parental anxiety about virus transmission, and reduced support services. We will further describe adaptations to mental health service delivery and approaches to care in the NICU to mitigate increased risk associated with pandemic‐related adversities. Adaptations include integration of technology, staff education and support, and delivery of activity kits to encourage parent–infant bonding. Data was collected as part of routine program evaluation of infant mental health services from one 50‐bed NICU setting and describes family concerns, barriers to visitation, and utilization of mental health services during the pandemic. Concerns related to COVID‐19 rarely emerged as the primary presenting issue by the families referred for infant mental health services from April through December of 2020. However, a number of families indicated that infection concerns and visitation restrictions posed significant challenges to their parenting and/or coping. There were significant discrepancies noted between the visitation patterns of families with public and private insurance. Several adaptations were developed in response to the multiple challenges and threats to infant mental health present during the COVID‐19 pandemic.
Research and scholarly methods: Propensity scores
Authors: Medaglio Dominique , Stephens‐Shields Alisa J. , Leonard Charles E. 
Published: January 2022

AbstractPropensity score methods are increasingly used as a tool to control for confounding bias in pharmacoepidemiologic studies. The propensity score is a dimension reducing balancing score, creating treatment, and reference groups that have comparable distributions of measured covariates. The purpose of this methods review is to provide an overview of the use of propensity score methods, including a summary of important data assumptions, various applications of the propensity score, and how to evaluate covariate balance. This article is intended for pharmacists and researchers who wish to receive an introduction to propensity score methods and be able to engage in high‐level discussions on application and reporting.
Pharmacist role in addressing health disparities—Part 2: Strategies to move toward health equity
Authors: Osae Sharmon P. , Chastain Daniel B. , Young Henry N. 
Published: January 2022

AbstractHealth disparities or extreme gaps of health across different groups of people result in poor outcomes for many Americans today. Pharmacists have an important role in addressing health disparities across many populations. Contextualizing root causes of gaps in health care and outcomes and identifying potential solutions to address those root causes are important initial steps clinical pharmacists can take to combat health disparities. PubMed and Web of Science were searched to identify articles published from inception until May 9, 2021. Articles in English were screened by title and abstract for relevance to clinical pharmacists' involvement in addressing health disparities. References from identified journal articles were also screened to identify further relevant articles. Utilizing the five domains of social determinants of health (SDOH) (economic stability, neighborhood and built environment, social and community context, education access and quality, and health care access and quality), actionable interventions to pursue health equity are presented. Pharmacists are in a unique position to make positive impacts on health disparities. By remaining intentional about decreasing unconscious biases and seeing past medications to the individual to identify potential barriers, pharmacists can bolster the movement toward health equity.
In vitro cytotoxicity, macromolecular interaction and antioxidant potential of dual coated selenium nanoparticles
Authors: Shinde Vrundali , Desai Krutika 
Published: January 2022

AbstractThe present research focuses on synthesizing selenium nanoparticles (Se NPs) coated with Methionine and Folic acid. selenium‐methionine‐folate nanoparticles (Se‐Met‐Fa NPs) were prepared by the chemical precipitation method. These were characterized by UV–Vis spectroscopy, FTIR, X‐ray diffraction, Zeta potential, ICP‐AES, TEM, and Raman spectroscopy. The average diameter of nanoparticles was determined by TEM was 50 nm. In Vitro viability of cells exposed to Se‐Met‐Fa NPs were studied using MTT and AO/EB assay. Approximately 80% of cells were viable at 100 μg/ml concentration after 24 h of incubation, suggestive of the safety of nanoparticles. Macromolecular interaction studies were carried out with plasmid DNA and Bovine serum albumin (BSA) protein. UV–Vis Spectroscopy showed ground state complex formation of Se‐Met‐Fa NPs with BSA. Intrinsic fluorescence of BSA was quenched by Se‐met‐Fa NPs via Static quenching and was observed under Spectro‐fluorimetry. Conformational structural change in α‐Helices of BSA was observed to be 4.4% after the interaction with Se‐Met‐Fa NPs, and it was studied using CD spectroscopy. At 250 μg/ml Se‐Met‐Fa NPs prevented oxidative damage of Plasmid DNA. The total antioxidant property of Se‐Met‐Fa NPs expressed in terms of scavenging of free DPPH radicals. Ten micrograms per milliliter could inhibit 41% of DPPH, proving its scavenger role at the lowest concentration. Nanoparticles comprising antioxidant semi‐conducting cores and encapsulated by biomaterials that are highly bioavailable can be promising therapeutic agents for inflammation and oxidative stress disorders studies.