bluuebunny/crossref_metadata_2025 huggingface dataset:
Synergistic Effect of β-Carotene and Metformin on Antihyperglycemic and Antidyslipidemic Activities in Streptozotocin-Induced Diabetic Rats
Authors: Khanam Khadiza , Rajia Sultana , Yeasmin Mim , Morshed Munira , Haque Rashidul
Published: November 2021

Purpose: Worldwide prevalence of diabetes mellitus (DM) has become an issue of great concern in current decades. To date, a large number of biological properties have been reported from carotenoids, particularly protective effects against cancer, cardiovascular diseases, and DM, including enhancement of insulin sensitivity.In this study, we aimed to evaluate the efficacy of β-carotene as an additive agent with metformin in ameliorating Type2 (T2)DM.

Methods: In this experiment, fasting blood glucose level (BGL), low density lipoprotein (LDL), high density lipoprotein (HDL), total cholesterol (TC) and triglycerides (TG) were measured in serum of Wister albino rats with streptozotocin (STZ)-induced diabetes and after treatment with metformin (850mg/70kg b.w.) and β-carotene (10 mg/70kg b.w.) administered orally once daily for three weeks.

Results: Metformin and β-carotene treatments individually resulted in significant (p<0.001) reversal of the diabetes induced increase in BGL, LDL, TC and TG, whereas significantly increased the STZ-induced decrease in HDL, compared to diabetic control. As compared to the monotherapy, the combination therapy with metformin and β-carotene showed a significant (p<0.001) attenuation of BGL and serum level of LDL, TC, and TG and a slight increase (p<0.05) in serum HDL level, as compared to the treatment with β-carotene, but not with metformin.

Conclusion: The combination therapy of β-carotene and metformin produced a significant antidiabetic and antihyperlipidemic effect than the monotherapy alone and provides a scientific rationale for their use in antidiabetic therapy as a potential antioxidant.
Personality, Group Thinking and Cohesiveness as Predictor of Criminal Behavior among Adolescents
Authors: Kehinde Arowosegbe, Christianah , Temitope Bankole Emmanuel , Olubukola Ajayi
Published: November 2021

The purpose of this study was to examine the influence of Group thinking, cohesiveness and Personality characteristics as predictors of Criminal Behaviour. The population comprises of Three Hundred (300) students through stratified sampling technique from institutions in Ekiti State was used. A questionnaire was designed using a descriptive research design for data collection. The data was collected using questionnaire. Three hypotheses were tested in total and they are: there will be a significant relationship between group thinking, cohesiveness, personality characteristics and criminal behavior; Personality Characteristics will significantly predict criminal behavior; Group thinking and cohesiveness will have main and interaction influence on criminal behaviour; the first hypothesis was tested using regression analysis and found that there is a positive and significant relationship between criminal behaviour and group thinking with r = .194, p<0.05 and there is a negative but significant relationship between personality characteristics and group cohesiveness with r = -.123, p<0.05. the second hypothesid was tested using linear regression analysis and found that that F (299) = .000, p > 0.05 significant level and the hypothesis rejected. The thirds hypothesis was tested using one way ANOVA analysis showed that group thinking has an influence on criminal behaviour among adolescents, F(299) = 5.768, p<0.05, group cohesiveness does not have a significant influence on criminal behaviour of adolescents, F(299) = 2.124, p>0.05. the results were discussed in line with relevant empirical literature, conclusion and recommendation. The study concluded that group thinking is a major predictor of criminal behaviour among adolescents, while group cohesiveness and personality characteristics do not influence criminal behaviour among adolescents. It was recommended that there is need of adequate sensitization of adolescents on the negative consequences criminal behavior and how it can affect their future if not curtailed, Government should organize empowerment for the youth, so that it can reduce criminal act and the government introduces or organize seminar to the adolescents, to teach them how to behave in the society.
Analysing the Potential of Blockchain for the Accounting Field in Indonesia
Authors: Hartoyo Abdulrival , Sukoharsono Eko Ganis , Prihatiningtyas Yeney Widya
Published: November 2021

This research aims to identify and analyze the potential of blockchain technology for the accounting field in Indonesia. This research was conducted at the Indonesian Blockchain Association. This research uses qualitative methods with the case study approach and analysis of making explanation strategies. The result of this study indicates that blockchain is applicable in Indonesia without having to use cryptocurrency as a payment tool. The result finds that blockchain can be used as a technology for Accounting Information System. One of the reasons is that all accounting transactions have the potential to be traceable with the blockchain. The data in this technology can be considered as relevant information due to the nature of blockchain as a technology that records and stores data that cannot be changed and manipulated. Blockchain will be used as a database and data procession will still be carried out by using the Accounting Information System.  Blockchain is unable to automatically process data into information that may be needed in accounting. This research is expected to strengthen the theory related to blockchain as one of the accounting technologies, also to be an initial step in improving the concept of triple-entry accounting that is usable in Indonesia by using Blockchain which is supported by other platforms such as ERP and uses Token as the representative of assets or financial in recording transactions.
STORE ATMOSPHERE MEMODERASI PENGARUH KUALITAS MAKANAN DAN KUALITAS LAYANAN TERHADAP KEPUASAN KONSUMEN (Studi pada Konsumen Moonk Cartil & Cafe Surabaya)
Authors: Binaraesa Ni Nyoman Padang Cakra , Hidayat Imam , Lestariningsih Marsudi
Published: November 2021

Kualitas Makanan, Kualitas Layanan dan Store Atmosphere memiliki kontribusi penting untuk mencapai Kepuasan Konsumen restoran. Tujuan penelitian untuk menguji dan menganalisis pengaruh Kualitas Makanan dan Kualitas Layanan terhadap Kepuasan Konsumen secara langsung maupun dengan Store Atmosphere sebagai variabel moderasi. Populasi yang digunakan adalah konsumen yang mengunjungi Moonk Cartil & Cafe. Teknik pengambilan sampel menggunakan purposive sampling dengan jumlah sampel 100 responden. Penelitian ini menggunakan teknik analisis data Moderated Regression Analysis (MRA). Hasil penelitian menunjukkan Kualitas Makanan dan Kualitas Layanan berpengaruh positif dan signifikan terhadap Kepuasan Konsumen, Store Atmosphere tidak memoderasi pengaruh Kualitas Makanan dan Kualitas Layanan terhadap Kepuasan Konsumen.
The S‐adenosylmethionine analog sinefungin inhibits the trimethylguanosine synthase TGS1 to promote telomerase activity and telomere lengthening
Authors: Galati Alessandra , Scatolini Livia , Micheli Emanuela , Bavasso Francesca , Cicconi Alessandro , Maccallini Paolo , Chen Lu , Roake Caitlin M. , Schoeftner Stefan , Artandi Steven E. , Gatti Maurizio , Cacchione Stefano , Raffa Grazia D.
Published: November 2021

Mutations in many genes that control the expression, the function, or the stability of telomerase cause telomere biology disorders (TBDs), such as dyskeratosis congenita, pulmonary fibrosis, and aplastic anemia. Mutations in a subset of the genes associated with TBDs cause reductions of the telomerase RNA moiety hTR, thus limiting telomerase activity. We have recently found that loss of the trimethylguanosine synthase TGS1 increases both hTR abundance and telomerase activity and leads to telomere elongation. Here, we show that treatment with the S‐adenosylmethionine analog sinefungin inhibits TGS1 activity, increases the hTR levels, and promotes telomere lengthening in different cell types. Our results hold promise for restoring telomere length in stem and progenitor cells from TBD patients with reduced hTR levels.
4DCT and VMAT for lung patients with irregular breathing
Authors: Caines Rhydian , Sisson Naomi K. , Rowbottom Carl G.
Published: November 2021

Purpose

Irregular breathing in lung cancer patients is a common contra‐indication to 4D computerized tomography (4DCT), which may then limit radiotherapy treatment options. For irregular breathers, we investigated whether 3DCT or 4DCT (1) better represents tumor motion, (2) better represents average tumor densities, and (3) better allows for volumetric modulated arc threarpy (VMAT) plans delivered with acceptable dosimetric accuracy.

Methods

Ten clinical breathing traces were identified with irregularities in phase and amplitude, and fed to a programmable moving platform incorporating an anthropomorphic lung tumor phantom. 3DCT and 4DCT data resorted by phase (4DCT‐P) and amplitude (4DCT‐A) were acquired for each trace. Tumors were delineated by Hounsfield unit (HU) thresholding and apparent motion range assessed. HU profiles were extracted from each image and agreement with calculated expected profiles quantified using area‐under‐curve (AUC) scoring. Clinically representative VMAT plans were created for each image, delivered to the irregularly moving phantom, and measured with a small‐volume ion chamber at the tumor center.

Results

Median difference from expected tumor motion range for 3DCT, 4DCT‐P, and 4DCT‐A was 2.5 [1.6–3.6] cm, 1.1 [0.1–1.9] cm, and 1.3 [0.4–1.9] cm, respectively (p = 0.005, 4DCT‐P vs. 3DCT). Median AUC scores (ideal = 0) for 3DCT, 4DCT‐P, and 4DCT‐A were 0.25 [0.14–0.49], 0.12 [0.05–0.42], and 0.13 [0.09–0.44], respectively (p = 0.005, 4DCT‐P vs. 3DCT). Nine of ten 4DCT‐P plans and all 4DCT‐A plans measured within 2.5% of expected dose in the treatment planning system (TPS), compared with seven 3DCT plans.

Conclusion

For the cases studied tumor motion range and average density was better represented with 4DCT compared with 3DCT, even in the presence of irregular breathing. 4DCT images allowed for delivery of VMAT plans with acceptable dosimetric accuracy. No significant differences were detected between phase and amplitude resorting. In combination with 4D cone beam imaging at treatment, our findings have given us confidence to introduce 4DCT and VMAT for lung radiotherapy patients with irregular breathing.
Generalized predictive control of spacecraft attitude with adaptive predictive period
Authors: Sun Guang , Chen Jialei , Yong Yingqiong , Li Yongyuan
Published: November 2021

In this article, a dynamic nonlinear generalized predictive control method based on exponential function to adjust predictive period is proposed for the problem of spacecraft attitude tracking with model uncertainties and unknown disturbances. First, a virtual generalized predictive control law is designed on the basis of invariable predictive period for attitude subsystem. Subsequently, introducing predictive period into attitude, a closed‐loop error equation for fusion of attitude and predictive period is established. Meanwhile, a dynamic adaptive law of predictive period and a disturbance estimator are built in the light of Lyapunov theory. Second, through a similar approach, an actual control input is designed for the attitude angular velocity subsystem. In order to simplify the calculation, the derivatives of virtual control and unknown disturbances in the actual control are dealt with adaptive estimators by considering them as uncertainties. Finally, it is proved that the spacecraft attitude can converge to the desired attitude of bounded small neighborhood. The simulation results of comparative analysis demonstrate that the predictive period can be adjusted to improve the control performance and speed up the attitude convergence.
Thermally Decomposed Binary Fe–Cr Alloys: Toward a Quantitative Relationship Between Strength and Structure
Authors: Küchler Severin , Vojtech Vladimir , Gerstl Stephan S.A. , Schäublin Robin E. , Löffler Jörg F.
Published: November 2021

Binary Fe–Cr alloys are model alloys for ferritic steels proposed as structural materials for future fusion reactors. They are used to investigate the fundamental mechanisms of their degradation induced by heat and irradiation. Fe–Cr presents a miscibility gap, which induces Cr‐rich (α′) regions in an Fe‐rich (α) matrix. As this causes embrittlement, it is crucial to understand this phase decomposition and its role, starting with the heat impact. Fe–Cr alloys with 5−40 wt% Cr were annealed at 500 °C for up to 1008 h. The microstructure was probed by chemical mapping using scanning transmission electron microscopy with energy‐dispersive X‐ray spectroscopy (EDS) and atom probe tomography, and hardness was assessed by Vickers testing. Increasing Cr content increases hardness, and beyond 15 wt% Cr it further increases upon annealing. At 20 wt% Cr, nanoscale globular α′ precipitates appear, while at 40 wt% Cr an α′‐percolating structure develops. In both cases, the α′ core composition reaches slightly more than 80 at% Cr, and hardness doubles. A unified relationship is found between the alloy strength and the α′ structure and it is shown that this type of hardening is a general mechanism for mature systems, independent of the nominal alloy composition.
Evolution of the Nature of Excitons and Electronic Couplings in Hybrid 2D Perovskites as a Function of Organic Cation π‐Conjugation
Authors: Dai Qingqing , Li Hong , Sini Gjergji , Bredas Jean‐Luc
Published: November 2021

2D perovskites have attracted much attention, due to their organic–inorganic hybrid nature and layered configuration. Multi‐quantum‐well structures then generally form since the inorganic frameworks and organic spacers have typically well‐separated frontier energy levels. Here, it is focused on the opposite picture where wavefunction hybridization occurs between the frontier orbitals of the two components. Such a hybridization emerges upon tuning the strength of electronic coupling between the inorganic and organic layers. A series of model diammonium organic spacers is theoretically designed with varying extent of π‐conjugation along their backbones. Wavefunction hybridization is realized in a Dion‐Jacobson 2D perovskite combining PbI4 inorganic layers with anthracene‐bis(ethan‐1‐ammonium) organic spacers. An analysis of the electronic band structures points to electronic couplings as high as 30–40 meV between the organic and inorganic components. Such couplings can lead to the formation of interfacial hybrid excitons or to the appearance of Dexter‐type energy transfer conducive to phosphorescence in the organic layers. Overall, the results highlight that a variety of excitonic behaviors could be observed by tuning the degree of conjugation of the organic cations and the structural proximity and electronic couplings between the organic and inorganic constituents.
Charge Carrier Doping As Mechanism of Self‐Assembled Monolayers Functionalized Electrodes in Organic Field Effect Transistors
Authors: Patrikar Kalyani , Bothra Urvashi , Rao Valipe Ramgopal , Kabra Dinesh
Published: November 2021

Coating electrodes with self‐assembled monolayer (SAM) of polar molecules is known to reduce contact resistance (RC) in organic field effect transistors (OFETs). It is shown that the behavior of SAM in OFETs can be explained by considering a mechanism of interfacial doping in organic semiconductor by electrodes due to charge transfer during interface formation. The enhancement is analyzed in performance of pentacene OFETs with Cu electrodes, by coating Cu with SAM of pentafluorobenzenethiol or perfluorodecanethiol. It is found that application of either SAM leads to an increase in work function of Cu surface. However, work function shift due to SAM does not correlate with trends inRCand OFET drain current. Further, first principle calculations reveal a notable difference in delocalization of frontal orbitals with either SAM, an indicator of the difference in ease of charge transfer across interface. Based on the mechanism of interfacial doping, a semiconductor physics model is developed for estimating interface doping and injection barrier, and for predicting the consequent device characteristics. It is believed that the model and methodology developed in this study can be utilized beyond the SAM and semiconductor system used here.
Amphiphilic Perforated Honeycomb Films for Gravimetric Liquid Separation
Authors: Chen Bihai , Wada Takehiko , Yabu Hiroshi
Published: November 2021

The separation of oil and water is an important technology for solving a wide range of water‐related problems such as purification of industrial wastewater. Herein, the fabrication of an extremely thin oil–water separation membrane is reported by precisely controlling the wettability of a honeycomb (HC) porous membrane. The developed membrane can easily separate water and oil by gravity and capillary force. The method of wettability control by UV–O3 treatment and the resultant change in the separated liquid are discussed. Amphiphilic perforated HC films with controlled wettability can be used in membranes that can separate different liquids according to their densities when the initial liquid added to the surface of the HC film is changed.
Visible Achromatic Metalens Design Based on Artificial Neural Network
Authors: Wang Feilou , Geng Guangzhou , Wang Xueqian , Li Junjie , Bai Yang , Li Jianqiang , Wen Yongzheng , Li Bo , Sun Jingbo , Zhou Ji
Published: November 2021

Metasurfaces, known as ultra‐thin and planar structures, are widely used in optical components with their excellent ability to manipulate the wavefront of the light. The key function of the metasurfaces is the spatial phase modulation, originated from the meta‐atoms. Thus, to find the relation between the phase modulation and the parameters of an individual meta‐atom, including the sizes, shapes, and material's optical properties, is the most important but also time‐consuming part in the metasurface design. Here by developing a backpropagation neural network based machine learning tool, the design process of a high performance achromatic metalens can be greatly simplified and accelerated. A library of the phase modulation data from 15 753 meta‐atoms can be generated in less than 1 s by our backpropagation neural network. In the experiment, it is demonstrated that the designed metalens shows an excellent achromatic focusing and imaging ability in the visible wavelengths from 420 to 640 nm without the polarization dependence.
When Do We Need Massive Computations to Perform Detailed COVID‐19 Simulations?
Authors: Lutz Christopher B. , Giabbanelli Philippe J.
Published: November 2021

The COVID‐19 pandemic has infected over 250 million people worldwide and killed more than 5 million as of November 2021. Many intervention strategies are utilized (e.g., masks, social distancing, vaccinations), but officials making decisions have a limited time to act. Computer simulations can aid them by predicting future disease outcomes, but they also require significant processing power or time. It is examined whether a machine learning model can be trained on a small subset of simulation runs to inexpensively predict future disease trajectories resembling the original simulation results. Using four previously published agent‐based models (ABMs) for COVID‐19, a decision tree regression for each ABM is built and its predictions are compared to the corresponding ABM. Accurate machine learning meta‐models are generated from ABMs without strong interventions (e.g., vaccines, lockdowns) using small amounts of simulation data: the root‐mean‐square error (RMSE) with 25% of the data is close to the RMSE for the full dataset (0.15 vs 0.14 in one model; 0.07 vs 0.06 in another). However, meta‐models for ABMs employing strong interventions require much more training data (at least 60%) to achieve a similar accuracy. In conclusion, machine learning meta‐models can be used in some scenarios to assist in faster decision‐making.
Boosting Output Performance of Triboelectric Nanogenerator via Mutual Coupling Effects Enabled Photon‐Carriers and Plasmon
Authors: Chen Xin , Zhao Yanjun , Wang Fayang , Tong Daqiao , Gao Lingxiao , Li Dongxiao , Wu Liangke , Mu Xiaojing , Yang Ya
Published: November 2021

Boosting the output performance of triboelectric nanogenerators via some unique methods is always a meaningful way to speed up their commercialization. However, the available approach to boost performance is mainly restricted to one physics effect based and the basic research of boosting performance via mutual coupling effects is little research. Herein, a new strategy is creatively proposed based on charge traps from mutual coupling effects, generated from g‐C3N4/MXene‐Au composites, to further promote the output performance of triboelectric nanogenerator. It is found that photon‐generated carriers coupling surface plasmon effect enables composites filled into tribo‐material with visible light is an excellent value in boosting performance. The charge traps from mutual coupling effects for boosting performance are analyzed theoretically and verified by experiments. The output power of boosting‐triboelectric nanogenerator (TENG) achieves a sixfold enhancement (20 mW) of normal TENG with polydimethylsiloxane (PDMS) in ambient conditions. This work provides a profound understanding of the working mechanism of mutual coupling effects boosting the performance of TENG and an effective way for promoting TENG output.
Going Beyond the d‐Band Center to Describe CO2 Activation on Single‐Atom Alloys
Authors: Sun Zhongti , Song Zhilong , Yin Wan-Jian
Published: November 2021

The computational screening of single‐atom alloys (SAAs) is challenging owing to their complicated electronic structure compared with traditional metal or alloy catalysts and the consequent lack of an accurate and low‐cost activity descriptor to replace expensive adsorption energy calculations. Herein, a data‐driven approach involving consecutive classification and regression is explored to identify the descriptor in the form of algebraic operators representing atomic information for predicting the adsorption energies of CO2 molecules on SAAs. The best descriptor significantly outperforms the d‐band center model in terms of accuracy and computational overhead. This study provides a fundamental understanding of the bonding strength on SAA surfaces and also an effective approach for the high‐throughput screening of promising catalysts.
Flexible sensors based on assembled carbon nanotubes
Authors: He Sisi , Hong Yang , Liao Meng , Li Yingchun , Qiu Longbin , Peng Huisheng
Published: November 2021

Flexible sensors have attracted significant attention as they could be directly attached to/implanted into the body or incorporated into textiles to monitor human activities and give feedbacks for healthcare. A typical fabrication method is the direct use of intrinsically flexible active materials such as carbon nanotubes (CNTs). CNTs are generally assembled into aligned structures to extend their remarkable chemical, mechanical, and electrical properties to macroscopic scale to afford high sensing performances. In this review, we present the recent advance of CNT assemblies as electrodes or functional materials for flexible sensors. The realizations of aligned CNTs are firstly investigated. A variety of flexible sensors based on the aligned CNTs are then carefully explored, with an emphasis on understanding the working mechanism for their high sensing properties. The main attention is later paid to comparing two main categories of flexible sensors with fiber and film shapes. The remaining challenges are finally highlighted to offer some insights for future study.
Objective criteria for explanations of machine learning models
Authors: Yeh Chih‐Kuan , Ravikumar Pradeep
Published: November 2021

Objective criteria to evaluate the performance of machine learning (ML) model explanations are a critical ingredient in bringing greater rigor to the field of explainable artificial intelligence. In this article, we survey three of our proposed criteria that each target different classes of explanations. In the first, targeted at real‐valued feature importance explanations, we define a class of “infidelity” measures that capture how well the explanations match the ML models. We show that instances of such infidelity minimizing explanations correspond to many popular recently proposed explanations and, moreover, can be shown to satisfy well‐known game‐theoretic axiomatic properties. In the second, targeted to feature set explanations, we define a robustness analysis‐based criterion and show that deriving explainable feature sets based on the robustness criterion yields more qualitatively impressive explanations. Lastly, for sample explanations, we provide a decomposition‐based criterion that allows us to provide very scalable and compelling classes of sample‐based explanations.
The Biophysics of Cancer: Emerging Insights from Micro‐ and Nanoscale Tools
Authors: Beshay Peter E. , Cortes-Medina Marcos G. , Menyhert Miles M. , Song Jonathan W.
Published: November 2021

Cancer is a complex and dynamic disease that is aberrant both biologically and physically. There is growing appreciation that physical abnormalities with both cancer cells and their microenvironment that span multiple length scales are important drivers for cancer growth and metastasis. The scope of this review is to highlight the key advancements in micro‐ and nanoscale tools for delineating the cause and consequences of the aberrant physical properties of tumors. Herein, the following three important physical aspects of cancer are focused: 1) solid mechanical properties, 2) fluid mechanical properties, and 3) mechanical alterations to cancer cells. Beyond posing physical barriers to the delivery of cancer therapeutics, these properties are also known to influence numerous biological processes, including cancer cell invasion and migration leading to metastasis, and response and resistance to therapy. There is a comment on how micro‐ and nanoscale tools have transformed the fundamental understanding of the physical dynamics of cancer progression and their potential for bridging toward future applications at the interface of oncology and physical sciences.
Acid catalyzedepoxy–methylolphenolthermosets: Astructure–propertystudy
Authors: Roy Choudhury Shreya , Houston Katelyn R. , Mason Dawn C. , Dingemans Theo J.
Published: November 2021

We have explored the structure–property relationships of a series epoxy–methylolphenol based thermoset films. Ortho‐, meta‐, and para‐isomers of methylolphenol, that is, ortho‐methylolphenol, meta‐methylolphenol and para‐methylolphenol, respectively, were reacted with the diglycidyl ether of bisphenol A (DGEBA) in the presence of an acid catalyst (CYCAT® XK 406 N). Thermogravimetric analyses showed that irrespective of the methylolphenol structure used, all crosslinked films exhibit 5% weight loss at 343–360°C under nitrogen. The glass transition temperature (Tg) decreases in the order of ortho‐ (Tg = 117°C) > para‐(Tg = 102°C) > meta‐methylolphenol (Tg = 82°C) as measured by differential scanning calorimetry. Uniaxial tensile testing of thin films shows good stress–strain behavior, with ultimate tensile strength values of 75 MPa and 6% strain‐at‐break. Homo‐crosslinking of methylolphenol moieties can occur under the reaction conditions used but in the presence of DGEBA, the methylolphenols prefer to undergo epoxy ring‐opening reactions. This was confirmed by the uniform networks that were formed, that is, no block‐formation was observed. The results of this study confirm that simple methylolphenol hardeners can be used to prepare crosslinked epoxy‐based films with excellent thermomechanical properties.
Asymmetric Direct/Stepwise Dearomatization Reactions Involving Hypervalent Iodine Reagents
Authors: Kumar Ravi , Singh Fateh V. , Takenaga Naoko , Dohi Toshifumi
Published: November 2021

A remarkable growth in hypervalent iodine‐mediated oxidative transformations as stoichiometric reagents as well as catalysts has been well‐documented due to their excellent properties, such as mildness, easy handling, high selectivity, environmentally friendly nature, and high stability. This review aims at highlighting the asymmetric oxidative dearomatization reactions involving hypervalent iodine compounds. The present article summarizes asymmetric intra‐ and intermolecular dearomatization reactions using chiral hypervalent iodine reagents/catalysts as well as hypervalent iodine‐mediated dearomatization reactions followed by desymmetrization.
Current Comment: The Illiberal Academic Authority. An Oxymoron?
Authors: Pető Andrea
Published: November 2021

The emergence of illiberal science policy also raises serious questions about the European scientific authorization process as the rapid spread of illiberal science policies, such as closing accredited study programs and research institutions, privatizing higher education, appointing university leaders based on their loyalty to the government, ignoring quality assurance, etc. demand not only a reaction but also critical analysis. The article applies the theoretical framework of the polypore state (Grzebalska, Pető) to tackle the difficulty lies in understanding the rise of illiberal science policy in Hungary, as it is a twofold case study in both polypore government control/state capture, and neoliberal marketization of higher education.
Cancer prevention, screening, and survivorship ECHO: A pilot experience with an educational telehealth program
Authors: Severance Tyler S. , Milgrom Zheng , Carson Anyé , Scanlon Caitlin M. , Chauhan O’Brien Rishika , Anderson Brent , Robertson Mary , Janota Andrea , Coven Scott L. , Mendonca Eneida A. , Duwve Joan , Vik Terry A.
Published: November 2021

Introduction

The American Cancer Society, Inc. (ACS) estimates that 37,940 Indiana residents were diagnosed with cancer in 2020, which remains the leading cause of death in the state. Across the cancer continuum, national goals have been established targeting recommended benchmarks for states in prevention, screening, treatment, and survivorship. Indiana consistently falls below most goals for each of these targeted categories.

Methods

To address these disparities, we implemented Project ECHO (Extension for Community Healthcare Outcomes) as a virtual telehealth educational platform targeted at local healthcare providers. ECHO programs utilize a novel tele‐mentoring approach to the education of clinicians in a hub/spoke design. Sessions occurred twice monthly from September 2019 to September 2020 and consisted of a traditional didactic lecture and a case‐based discussion led by participating providers.

Results

During the pilot year there were a total of 22 ECHO sessions with 140 different participants. On average, 15.5 spokes attended each session with increasing participation at the end of the year. Post‐session surveys suggested generally favorable perception with 72% of respondents finding the quality “excellent.”

Discussion

Given the increasing rate of recurrent participation toward the end of the pilot year in conjunction with the favorable survey responses following each session, it was felt that the program was overall successful and warranted continued implementation.

Conclusion

The Project ECHO platform is a validated telehealth education platform that has the potential to impact cancer care at multiple points along the cancer continuum at the regional level.
Optimum cycle length models using atom search optimization and grasshopper optimization algorithms
Authors: Korkmaz Ersin , Akgüngör Ali Payıdar
Published: November 2021

A fixed‐time traffic control system is widely used to manage the traffic flow at intersections. Cycle length has an important effect on the performance of the fixed‐time control system and the Webster model is widely used in the literature to determine the cycle length. However, when the traffic flow ratio (Y) approaches 1, the Webster model loses its effectiveness and cannot determine the cycle length when Y is above 1. In the scope of this study, it is aimed to develop models that can predict cycle length for all traffic conditions in which are Y ≤ 1 and Y ≥ 1. Two different heuristic algorithms, atom search optimization (ASO) and grasshopper optimization algorithm (GOA) were used in the development of models and the performances of these algorithms were demonstrated. The efficiency of the developed models has been demonstrated by comparing them with both Webster's model and VISTRO optimization program. Models developed in exponential, power, and quadratic forms have been able to predict cycle lengths with lower delay values by showing better performance than Webster and VISTRO. In addition, statistical results show that the ASO approach is more successful than the GOA approach.
Population‐specific responses of an insect herbivore to variation in host‐plant quality
Authors: Kuczyk Josephine , Raharivololoniaina Ange , Fischer Klaus
Published: November 2021

Anthropogenic climate change poses a substantial challenge to many organisms, to which they need to respond to avoid fitness reductions. Investigating responses to environmental change is particularly interesting in herbivores, as they are potentially affected by indirect effects mediated via variation in host‐plant quality. We here use the herbivorous insectPieris napito investigate geographic variation in the response to variation in food quality. We performed a common garden experiment using replicated populations from Germany and Italy, and manipulated host quality by growing host plants at different temperature and water regimes. We found that feeding on plants grown at a higher temperature generally diminished the performance ofP.napi, evidenced by a prolonged development time and reduced larval growth rate, body mass, fat content, and phenoloxidase activity. Genotype by environment interactions (G × E) were present in several performance traits, indicating that Italian populations (1) respond more strongly to variation in host‐plant quality and (2) are more sensitive to poor food quality than German ones. This may reflect a cost of the rapid lifestyle found in Italian populations. Consequently, German populations may be more resilient against environmental perturbations and may perhaps even benefit from warmer temperatures, while Italian populations will likely suffer from the concomitantly reduced host‐plant quality. Our study thus exemplifies how investigating G × E may help to better understand the vulnerability of populations to climate change.
Strong trait correlation and phylogenetic signal in North American ground beetle (Carabidae) morphology
Authors: Stachewicz Jacob D. , Fountain‐Jones Nicholas M. , Koontz Austin , Woolf Hillary , Pearse William D. , Gallinat Amanda S.
Published: November 2021

Functional traits mediate species' responses to, and roles within, their environment and are constrained by evolutionary history. While we have a strong understanding of trait evolution for macro‐taxa such as birds and mammals, our understanding of invertebrates is comparatively limited. Here, we address this gap in North American beetles with a sample of ground beetles (Carabidae), leveraging a large‐scale collection and digitization effort by the National Ecological Observatory Network (NEON). For 154 ground beetle species, we measured seven morphological traits, which we placed into a recently developed effect–response framework that characterizes traits by how they predict species' effects on their ecosystems or responses to environmental stressors. We then used cytochrome oxidase 1 sequences from the same specimens to generate a phylogeny and tested the evolutionary tempo and mode of the traits. We found strong phylogenetic signal in, and correlations among, ground beetle morphological traits. These results indicate that, for these species, beetle body shape trait evolution is constrained, and phylogenetic inertia is a stronger driver of beetle traits than (recent) environmental responses. Strong correlations among effect and response traits suggest that future environmental drivers are likely to affect both ecological composition and functioning in these beetles.
Decreased bee emergence along an elevation gradient: Implications for climate change revealed by a transplant experiment
Authors: McCabe Lindsie M. , Aslan Clare E. , Cobb Neil S.
Published: November 2021

Bees experience differences in thermal tolerance based on their geographical range; however, there are virtually no studies that examine how overwintering temperatures may influence immature survival rates. Here, we conducted a transplant experiment along an elevation gradient to test for climate‐change effects on immature overwinter survival using movement along elevational gradient for a community of 26 cavity‐nesting bee species in the family Megachilidae along the San Francisco Peaks, Arizona elevational gradient. In each of three years, we placed nest blocks at three elevations, to be colonized by native Megachilidae. Colonized blocks were then (1) moved to lower (warmer) elevations; (2) moved to higher (cooler) elevations; or (3) left in their natal habitat (no change in temperature). Because Megachilidae occupy high elevations with colder temperatures more than any other family of bees, we predicted that emergence would decrease in nest blocks moved to lower elevations, but that we would find no differences in emergence when nest blocks were moved to higher elevations. We found three major results: (1) Bee species moved to lower (warmer) habitats exhibited a 30% decrease in emergence compared with species moved within their natal habitat. (2) Habitat generalists were more likely than habitat specialists to emerge when moved up or down in elevation regardless of their natal life zones. (3) At our highest elevation treatment, emergence increased when blocks were moved to higher elevations, indicating that at least some Megachilidae species can survive at colder temperatures. Our results suggest that direct effects of warming temperatures will have negative impacts on the overall survival of Megachilidae. Additionally, above the tree line, low availability of wood‐nesting resources is a probable limiting factor on bees moving up in elevation.
Machine learning optimization of an electronic health record audit for heart failure in primary care
Authors: Raat Willem , Smeets Miek , Henrard Severine , Aertgeerts Bert , Penders Joris , Droogne Walter , Mullens Wilfried , Janssens Stefan , Vaes Bert
Published: November 2021

Aims

The diagnosis of heart failure (HF) is an important problem in primary care. We previously demonstrated a 74% increase in registered HF diagnoses in primary care electronic health records (EHRs) following an extended audit procedure. What remains unclear is the accuracy of registered HF pre‐audit and which EHR variables are most important in the extended audit strategy. This study aims to describe the diagnostic HF classification sequence at different stages, assess general practitioner (GP) HF misclassification, and test the predictive performance of an optimized audit.

Methods and results

This is a secondary analysis of the OSCAR‐HF study, a prospective observational trial including 51 participating GPs. OSCAR used an extended audit based on typical HF risk factors, signs, symptoms, and medications in GPs' EHR. This resulted in a list of possible HF patients, which participating GPs had to classify as HF or non‐HF. We compared registered HF diagnoses before and after GPs' assessment. For our analysis of audit performance, we used GPs' assessment of HF as primary outcome and audit queries as dichotomous predictor variables for a gradient boosted machine (GBM) decision tree algorithm and logistic regression model. Of the 18 011 patients eligible for the audit intervention, 4678 (26.0%) were identified as possible HF patients and submitted for GPs' assessment in the audit stage. There were 310 patients with registered HF before GP assessment, of whom 146 (47.1%) were judged not to have HF by their GP (over‐registration). There were 538 patients with registered HF after GP assessment, of whom 374 (69.5%) did not have registered HF before GP assessment (under‐registration). The GBM and logistic regression model had a comparable predictive performance (area under the curve of 0.70 [95% confidence interval 0.65–0.77] and 0.69 [95% confidence interval 0.64–0.75], respectively). This was not significantly impacted by reducing the set of predictor variables to the 10 most important variables identified in the GBM model (free‐text and coded cardiomyopathy, ischaemic heart disease and atrial fibrillation, digoxin, mineralocorticoid receptor antagonists, and combinations of renin‐angiotensin system inhibitors and beta‐blockers with diuretics). This optimized query set was enough to identify 86% (n = 461/538) of GPs' self‐assessed HF population with a 33% reduction (n = 1537/4678) in screening caseload.

Conclusions

Diagnostic coding of HF in primary care health records is inaccurate with a high degree of under‐registration and over‐registration. An optimized query set enabled identification of more than 80% of GPs' self‐assessed HF population.
Addressing planar solid oxide cell degradation mechanisms: A critical review of selected components
Authors: McPhail Stephen J. , Frangini Stefano , Laurencin Jérôme , Effori Elisa , Abaza Amira , Padinjarethil Aiswarya Krishnakumar , Hagen Anke , Léon Aline , Brisse Annabelle , Vladikova Daria , Burdin Blagoy , Bianchi Fiammetta Rita , Bosio Barbara , Piccardo Paolo , Spotorno Roberto , Uchida Hiroyuki , Polverino Pierpaolo , Adinolfi Ennio Andrea , Postiglione Fabio , Lee Jong‐Ho , Moussaoui Hamza , Van herle Jan
Published: November 2021

In this review paper, a critical assessment of the main degradation processes in three key components of solid oxide fuel cells and electrolysers (negative and positive electrodes and the interconnect) is undertaken, attempting prioritization of respective degradation effects and recommendation of the best approaches in their experimental ascertainment and numerical modeling. Besides different approaches to quantifying the degradation rate of an operating solid oxide cell (SOC), the latest advancements in microstructural representation (3D imaging and reconstruction) of SOC electrodes are reviewed, applied to the quantification of triple‐phase boundary (TPB) lengths and morphology evolution over time. The intrinsic degradation processes in the negative (fuel) electrode and the positive (oxygen) electrode are discussed, covering first the composition and governing mechanisms of the respective electrodes, followed by a comprehensive evaluation of the most important factors of degradation during operation. By this systematic identification of dominant degradation processes, measurement techniques, and modeling approaches, the foundations are laid for the definition of meaningful accelerated stress testing of SOC cells and stacks, which will help the technology achieve the constantly more demanding durability targets in market applications.
Defect identification of wind turbine blade based on multi‐feature fusion residual network and transfer learning
Authors: Zhu Jiawei , Wen Chuanbo , Liu Jihui
Published: November 2021

As a key part of the wind turbines (WTs), the blade has a direct influence on the efficiency of WT. Because the defect detection technology of WT blade is not widely used, and the robustness of traditional detection methods is poor, this paper proposes a multi‐feature fusion residual network combined with transfer learning. In this paper, the WT blade image dataset is enhanced and constructed to train the convolutional network. Two residual structures of multi‐feature fusion (two feature fusion and three feature fusion) are proposed and compared. At the same time, transfer learning is used to improve training process and accelerate convergence. Compared with several convolutional neural networks based on indices include training loss and testing accuracy, f1‐score and confusion matrix, the method proposed greatly reduces the time while achieving accurate detection.
Astrocytes as essential time‐keepers of the central pacemaker
Authors: Astiz Mariana , Delgado‐García Lina Maria , López‐Mascaraque Laura
Published: November 2021

Since the early observations made by Santiago Ramon y Cajal more than a century ago till now, astrocytes have gradually gained protagonism as essential partners of neurons in building brain circuits that regulate complex behavior. In mammals, processes such as sleep–wake cycle, locomotor activity, cognition and memory consolidation, homeostatic and hedonic appetite and stress response (among others), are synchronized in 24‐h rhythms by the circadian system. In such a way, physiology efficiently anticipates and adapts to daily recurring changes in the environment. The hypothalamic suprachiasmatic nucleus (SCN) is considered the central pacemaker, it has been traditionally described as a nucleus of around 10,000 neurons nearly all GABAergic able to be entrained by light and to convey time information through multiple neuronal and hormonal pathways. Only recently, this neuro‐centered view was challenged by breakthrough discoveries implicating astrocytes as essential time‐keepers. In the present review, we will describe the current view on the SCN circuit and discuss whether astrocytic functions described in other brain regions and state‐of‐the‐art experimental approaches, could help explaining better those well‐ and not so well‐known features of the central pacemaker.
Increased functional connectivity between presupplementary motor area and inferior frontal gyrus associated with the ability of motor response inhibition in obsessive–compulsive disorder
Authors: Tomiyama Hirofumi , Murayama Keitaro , Nemoto Kiyotaka , Tomita Mayumi , Hasuzawa Suguru , Mizobe Taro , Kato Kenta , Ohno Aikana , Tsuruta Sae , Togao Osamu , Hiwatashi Akio , Nakao Tomohiro
Published: November 2021

Recent evidence suggests that presupplementary motor area (pre‐SMA) and inferior frontal gyrus (IFG) play an important role in response inhibition. However, no study has investigated the relationship between these brain networks at resting‐state and response inhibition in obsessive–compulsive disorder (OCD). We performed resting‐state functional magnetic resonance imaging scans and then measured the response inhibition of 41 medication‐free OCD patients and 49 healthy control (HC) participants by using the stop‐signal task outside the scanner. We explored the differences between OCD and HC groups in the functional connectivity of pre‐SMA and IFG associated with the ability of motor response inhibition. OCD patients showed a longer stop‐signal reaction time (SSRT). Compared to HC, OCD patients exhibit different associations between the ability of motor response inhibition and the functional connectivity between pre‐SMA and IFG, inferior parietal lobule, dorsal anterior cingulate cortex, insula, and anterior prefrontal cortex. Additional analysis to investigate the functional connectivity difference from the seed ROIs to the whole brain voxels revealed that, compared to HC, OCD exhibited greater functional connectivity between pre‐SMA and IFG. Also, this functional connectivity was positively correlated with the SSRT score. These results provide additional insight into the characteristics of the resting‐state functional connectivity of the regions belonging to the cortico‐striato‐thalamo‐cortical circuit and the cingulo‐opercular salience network, underlying the impaired motor response inhibition of OCD. In particular, we emphasize the importance of altered functional connectivity between pre‐SMA and IFG for the pathophysiology of motor response inhibition in OCD.