bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examining lung microstructure using 19F MR diffusion imaging in COPD patients
Authors: Obert Arnd Jonathan , Gutberlet Marcel , Kern Agilo Luitger , Kaireit Till Frederik , Glandorf Julian , Moher Alsady Tawfik , Wacker Frank , Hohlfeld Jens Michael , Vogel‐Claussen Jens 
Published: March 2022

PurposeTo examine the time‐dependent diffusion of fluorinated (19F) gas in human lungs for determination of surface‐to‐volume ratio in comparison to results from hyperpolarized 129Xe and lung function testing in healthy volunteers and patients with chronic obstructive pulmonary disease.MethodsDiffusion of fluorinated gas in the short‐time regime was measured using multiple gradient‐echo sequences with a single pair of trapezoidal gradient pulses. Pulmonary surface‐to‐volume ratio was calculated using a first‐order approximation of the time‐dependent diffusion in a study with 20 healthy volunteers and 22 patients with chronic obstructive pulmonary disease. The repeatability after 7 days as well as the correlation with hyperpolarized 129Xe diffusion MRI and lung function testing was analyzed.ResultsUsing 19F diffusion MRI, the median surface‐to‐volume ratio is significantly decreased in chronic obstructive pulmonary disease patients (S/V = 126 cm−1 [87–144 cm−1]) compared with healthy volunteers (S/V = 164 cm−1 [160–84 cm−1], p < 0.0001). No significant difference was found between measurements within 7 days for healthy (p = 0.88, median coefficient of variation = 4.3%) and diseased subjects (p = 0.58, median coefficient of variation= 6.7%). Linear correlations were found with S/V from 129Xe diffusion MRI (r = 0.85, p = 0.001) and the forced expiratory volume in 1 second (r = 0.68, p < 0.0001).ConclusionExamination of lung microstructure using time‐dependent diffusion measurement of inhaled 19F is feasible, repeatable, and correlates with established measurements.
A column generation algorithm for the demand‐responsive feeder service with mandatory and optional, clustered bus‐stops
Authors: Galarza Montenegro Bryan David , Sörensen Kenneth , Vansteenwegen Pieter 
Published: March 2022

AbstractWith the rise of smart cities, relevant passenger data can be collected to improve the quality of transport services. In this article, a demand‐responsive feeder service is presented. A feeder service transports passengers from a low‐demand area, like a suburban area, to a transportation hub, like a city center. The feeder service modeled in this article considers two sets of bus stops: mandatory stops and optional stops. Mandatory stops are always visited by a bus, while optional stops are only visited when a client nearby makes a request for transportation. This gives the service both flexibility and some predictability. To optimize the performance of the service, mathematical modeling techniques to improve the model's runtime are developed. It is concluded that a combination of column generation and the separation of sub‐tour elimination constraints decreases the computing time of small and midsize instances significantly.
Z‐pin effect on interlaminar mechanical and ablation performance of quartz‐phenolic composites
Authors: Li Lisha , Li Yong , Huan Dajun , Chen Xiaodong , Liu Hongquan , Wang Wuqiang , Li Yanrui , Jin Yue , Li Wenying 
Published: March 2022

AbstractWhen a spacecraft flies at a high speed through a high‐heat flow, the ablative composites suffer from severe delamination and bulging due to their weak interlaminar performance. This will interfere normal operations of spacecraft. To improve the interlaminar performance of ablative composites is of great significance to the ablative structures. This study investigated Z‐pin reinforced quartz‐phenolic composites and reinforcement mechanism. First, a thermogravimetry (TG) test was used to analyze the thermal decomposition process of the phenolic. Second, a series of tests, including a single Z‐pin pull‐out, a single‐lap joint tensile and an oxyacetylene ablation test, were conducted to investigate composites' ablation performance. We also deployed a 3D morphometer and an infrared thermography to reveal the function of Z‐pins. The results demonstrated that Z‐pins can improve composites' ablation performance in both structure and function. In the structure, Z‐pins suppress the interlaminar delamination of composites by enhancing the interlaminar strength. As the ablation time increases, interface bridging between the Z‐pin and laminates contributes increasingly to the interlaminar shear strength of laminates. After 60 s of ablation in a flame of 920°C, the interlaminar shear strength of Z‐pin specimens is 84.66% stronger than that of the normal composites. In the function, the Z‐pins suppress large areas of bulges by providing escape channels for pyrolysis gas, and reduce bulging areas by 60%. Z‐pin technology can effectively suppress mechanical erosion of the ablative surface due to the delamination and bulging. It is an important way to improve ablation performance of ablative structures.
Anomaly detection in IR images of PV modules using supervised contrastive learning
Authors: Bommes Lukas , Hoffmann Mathis , Buerhop‐Lutz Claudia , Pickel Tobias , Hauch Jens , Brabec Christoph , Maier Andreas , Marius Peters Ian 
Published: March 2022

AbstractIncreasing deployment of photovoltaic (PV) plants requires methods for automatic detection of faulty PV modules in modalities, such as infrared (IR) images. Recently, deep learning has become popular for this. However, related works typically sample train and test data from the same distribution ignoring the presence of domain shift between data of different PV plants. Instead, we frame fault detection as more realistic unsupervised domain adaptation problem where we train on labeled data of one source PV plant and make predictions on another target plant. We train a ResNet‐34 convolutional neural network with a supervised contrastive loss, on top of which we employ ak‐nearest neighbor classifier to detect anomalies. Our method achieves a satisfactory area under the receiver operating characteristic (AUROC) of 73.3% to 96.6% on nine combinations of four source and target datasets with 2.92 million IR images of which 8.5% are anomalous. It even outperforms a binary cross‐entropy classifier in some cases. With a fixed decision threshold, this results in 79.4% and 77.1% correctly classified normal and anomalous images, respectively. Most misclassified anomalies are of low severity, such as hot diodes and small hot spots. Our method is insensitive to hyperparameter settings, converges quickly, and reliably detects unknown types of anomalies making it well suited for practice. Possible uses are in automatic PV plant inspection systems or to streamline manual labeling of IR datasets by filtering out normal images. Furthermore, our work serves the community with a more realistic view on PV module fault detection using unsupervised domain adaptation to develop more performant methods with favorable generalization capabilities.
Effectiveness of dextrose prolotherapy for the treatment of chronic plantar fasciitis: A systematic review and meta‐analysis of randomized controlled trials
Authors: Chutumstid Tunchanok , Susantitaphong Paweena , Koonalinthip Nantawan 
Published: March 2022

AbstractObjectiveTo systematically investigate the efficacy and safety of dextrose prolotherapy for treating chronic plantar fasciitis.Literature surveyEMBASE, PubMed, Scopus, and Google Scholar (from inception to December 9, 2021).MethodologyComprehensive review of randomized controlled trials investigating dextrose prolotherapy for chronic plantar fasciitis was done. Two investigators independently screened the titles, abstracts, and full texts and extracted data from eligible studies. The changes in visual analog scale (VAS) pain score, foot function index (FFI), American Orthopaedic Foot and Ankle Society (AOFAS) score, and plantar fascia thickness were analyzed. Reports of complications of the procedure were collected.SynthesisEight randomized controlled trials (RCTs) were included in the meta‐analysis, analyzing 444 patients in total. The subgroup analysis showed that at short‐term follow‐up (<6 months) dextrose prolotherapy was more effective in reducing VAS pain score compared to the non‐active treatment control group including exercise and normal saline solution (NSS) injection. However, there was no difference in the change of VAS pain score between dextrose prolotherapy and active treatment control group, which included extracorporeal shock wave therapy (ESWT), steroid injection, and platelet‐rich plasma (PRP) injection. Dextrose prolotherapy was more effective in reducing FFI, increasing AOFAS score, and reducing plantar fascia thickness at short‐term (<6 months) follow‐up compared to other comparators. For long‐term (≥6 months) follow‐up, there was no significant difference in the change in VAS pain score and FFI between the dextrose prolotherapy group and other comparators. No serious complication was reported.ConclusionsDextrose prolotherapy is an effective treatment of chronic plantar fasciitis to reduce pain, improve foot functional score, and decrease plantar fascia thickness at short‐term follow‐up. Further studies in larger populations are needed to identify the optimal treatment regimen including dextrose concentration, volume, injection site, injection technique, and the number of injections required. The long‐term effects of these treatments also require further examination.
Can van der Waals constants be used in the chemical reactivity analysis? A new approach as a support to minimum magnetizability principle
Authors: Kaya Savaş , Şimşek Selçuk 
Published: March 2022

AbstractOne of the most important purposes of theoretical chemists is to derive new, useful, and reliable equations to compute the well‐known parameters like hardness, polarizability, magnetizability, and electrophilicity providing enough hints for the reactivity analysis of the chemical systems. In the derivation of such equations, our research team widely considers the popular electronic structure rules like electronegativity equalization, maximum hardness, minimum polarizability, minimum magnetizability, and minimum electrophilicity principles. Recently, in the light of maximum entropy and minimum magnetizability principles, Kaya and Chattaraj (2021) presented a simple way to calculate their standard absolute entropies (S0298) based on molar diamagnetic susceptibilities (χm) of inorganic ionic systems. In the present paper, a new and useful molar diamagnetic susceptibility calculation method including the use of van der Waals constants (a and b) is introduced. Here, we named this method as Kaya–Şimşek approach. Through the relations between molar diamagnetic susceptibility and van der Waals constants, we can easily predict the magnetic susceptibility of molecules that their magnetic susceptibilities are unknown. The results of the equations derived are quite close to experimentally reported data. The analyses made proved that van der Waals constants can be considered as chemical reactivity descriptors. We propose that in stable states, van der Waals constants are minimized. The validity of minimum magnetizability principle is supported with solid evidences.
RNA meets toxicology: efficacy indicators from the experimental design of RNAi studies for insect pest management
Authors: List Fabian , Tarone Aaron M , Zhu‐Salzman Keyan , Vargo Edward L 
Published: March 2022

AbstractRNA interference (RNAi) selectively targets genes and silences their expression in vivo, causing developmental defects, mortality and altered behavior. Consequently, RNAi has emerged as a promising research area for insect pest management. However, it is not yet a viable alternative over conventional pesticides despite several theoretical advantages in safety and specificity. As a first step toward a more standardized approach, a machine learning algorithm was used to identify factors that predict trial efficacy. Current research on RNAi for pest management is highly variable and relatively unstandardized. The applied random forest model was able to reliably predict mortality ranges based on bioassay parameters with 72.6% accuracy. Response time and target gene were the most important variables in the model, followed by applied dose, double‐stranded RNA (dsRNA) construct size and target species, further supported by generalized linear mixed effect modeling. Our results identified informative trends, supporting the idea that basic principles of toxicology apply to RNAi bioassays and provide initial guidelines standardizing future research similar to studies of traditional insecticides. We advocate for training that integrates genetic, organismal, and toxicological approaches to accelerate the development of RNAi as an effective tool for pest management. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
The impact of the COVID‐19 pandemic on internal migration in Germany: A descriptive analysis
Authors: Stawarz Nico , Rosenbaum‐Feldbrügge Matthias , Sander Nikola , Sulak Harun , Knobloch Vanessa 
Published: March 2022

AbstractThe COVID‐19 pandemic has affected economies, labor markets, health care, education and tourism around the globe in unprecedented ways. However, little research has yet been devoted to the impact that the pandemic might have had on internal migration. This study aims to address this gap by determining how the intensity and spatial patterns of internal migration changed between 2019 and 2020 in Germany. We draw on data from the population register on annual flows between 401 counties. We find that the COVID‐19 pandemic was associated with a 5% drop in the intensity of inter‐county migration in 2020 compared to the previous year, with significant variation across age. The pandemic was also associated with an upsurge in net migration losses for the largest cities, driven by fewer inflows of young adults and continuing outflows of families.
Sustainability of local renewable energy projects: A comprehensive framework and an empirical analysis on two islands
Authors: Tsagkari Marula , Roca Jordi , Stephanides Phedeas 
Published: March 2022

AbstractLocal energy projects have been associated with several benefits for the local community like social cohesion, economic gains, new skills, and environmental awareness. Yet, there is limited research on whether the projects fulfill their sustainability promises, and how the local community perceive the benefits. This research introduces a novel framework to assess the success of a local renewable energy project based on the perceptions of the local population and the initial ambitions of the projects. Using this framework two innovative local renewable energy projects are assessed; one in Tilos island in Greece and the other in El Hierro in Spain. An online questionnaire was used to assess the impact of the project on people's lives, their overall assessment of the project and their willingness to support similar future initiatives. The data show that the economic benefits are not significant when people assess the project, while on the contrary other factors like the environmental benefits, sense of pride, technical parameters institutional seem to have a greater effect. The environmental and institutional factors are also among the ones that influence people's willingness to support and participate in future projects. Overall, we reveal that the two projects are quite successful in the eyes of the local population and offer good case studies with several implications for policymakers and future initiatives.
Multiply robust subgroup analysis based on a single‐index threshold linear marginal model for longitudinal data with dropouts
Authors: Wei Kecheng , Zhu Huichen , Qin Guoyou , Zhu Zhongyi , Tu Dongsheng 
Published: March 2022

AbstractIdentifying subpopulations that may be sensitive to the specific treatment is an important step toward precision medicine. On the other hand, longitudinal data with dropouts is common in medical research, and subgroup analysis for this data type is still limited. In this paper, we consider a single‐index threshold linear marginal model, which can be used simultaneously to identify subgroups with differential treatment effects based on linear combination of the selected biomarkers, estimate the treatment effects in different subgroups based on regression coefficients, and test the significance of the difference in treatment effects based on treatment‐subgroup interaction. The regression parameters are estimated by solving a penalized smoothed generalized estimating equation and the selection bias caused by missingness is corrected by a multiply robust weighting matrix, which allows multiple missingness models to be taken account into estimation. The proposed estimator remains consistent when any model for missingness is correctly specified. Under regularity conditions, the asymptotic normality of the estimator is established. Simulation studies confirm the desirable finite‐sample performance of the proposed method. As an application, we analyze the data from a clinical trial on pancreatic cancer.
Identification of Catalytic Active Sites for Durable Proton Exchange Membrane Fuel Cell: Catalytic Degradation and Poisoning Perspectives
Authors: Shah Syed Shoaib Ahmad , Najam Tayyaba , Bashir Muhammad Sohail , Javed Muhammad Sufyan , Rahman Aziz‐ur , Luque Rafael , Bao Shu‐Juan 
Published: March 2022

AbstractRecent progress in synthetic strategies, analysis techniques, and computational modeling assist researchers to develop more active catalysts including metallic clusters to single‐atom active sites (SACs). Metal coordinated N‐doped carbons (M‐N‐C) are the most auspicious, with a large number of atomic sites, markedly performing for a series of electrochemical reactions. This perspective sums up the latest innovative and computational comprehension, while giving credit to earlier/pioneering work in carbonaceous assembly materials towards robust electrocatalytic activity for proton exchange membrane fuel cells via inclusive performance assessment of the oxygen reduction reaction (ORR). M‐Nx‐Cy are exclusively defined active sites for ORR, so there is a unique possibility to intellectually design the relatively new catalysts with much improved activity, selectivity, and durability. Moreover, some SACs structures provide better performance in fuel cells testing with long‐term durability. The efforts to understand the connection in SACs based M‐Nx‐Cy moieties and how these relate to catalytic ORR performance are also conveyed. Owing to comprehensive practical application in the field, this study has covered very encouraging aspects to the current durability status of M‐N‐C based catalysts for fuel cells followed by degradation mechanisms such as macro‐, microdegradation, catalytic poisoning, and future challenges.
One stone, many birds: Recent advances in functional nanogels for cancer nanotheranostics
Authors: Wang Huiyi , Picchio Matias L. , Calderón Marcelo 
Published: March 2022

AbstractInspired by the development of nanomedicine and nanotechnology, more and more possibilities in cancer theranostic have been provided in the last few years. Emerging therapeutic modalities like starvation therapy, chemodynamic therapy, and tumor oxygenation have been integrated with diagnosis, giving a plethora of theranostic nanoagents. Among all of them, nanogels (NGs) show superiority benefiting from their unique attributes: high stability, high water‐absorption, large specific surface area, mechanical strength, controlled responsiveness, and high encapsulation capacity. There have been a vast number of investigations supporting various NGs combining drug delivery and multiple bioimaging techniques, encompassing photothermal imaging, photoacoustic imaging, fluorescent imaging, ultrasound imaging, magnetic resonance imaging, and computed tomography. This review summarizes recent advances in functional NGs for theranostic nanomedicine and discusses the challenges and future perspectives of this fast‐growing field.This article is categorized under:
Therapeutic Approaches and Drug Discovery > Emerging Technologies
Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Nanotechnology Approaches to Biology > Nanoscale Systems in Biology
Diagnostic Tools > In Vivo Nanodiagnostics and Imaging
Enhanced n‐butanol permselective vapor permeation by incorporating ZIF‐8 into a polydimethylsiloxane composite membrane: Effect of filler loading contents
Authors: Su Xing , Zheng Tucai , Zhu Youliang , Tao Xiaohong , Yu Kuangli , Zhao Zhiqing , Wu Zhenghong , Lu Jiale , Gao Chuanhua , Zhao Dian 
Published: March 2022

AbstractFabricating high‐performance mixed matrix composite membranes (MMMs) based on the integration of metal‐organic frameworks (MOFs) and hydrophobic polymer matrix are highly sought for the industrial development of vapor permeation (VP) technology. In this work, ZIF‐8@polydimethylsiloxane/polyvinylidene fluoride (ZIF‐8@PDMS/PVDF) MMMs with various ZIF‐8 nanofiller loading contents were prepared via a simple “prime” blending method. The dispersion and agglomeration of ZIF‐8 nanoparticles on both surface and cross‐section of these membranes were characterized by scanning electron microscopy (SEM) and energy‐dispersive X‐ray spectroscopy (EDS), respectively. The hydrophobicity of as‐obtained MMMs was investigated by water contact angle and swelling degree tests. Furthermore, VP experiments were carried out to evaluate the perm‐selection performance of the ZIF‐8@PDMS/PVDF MMMs for the butanol/water mixture separation. Compared to the conventional PDMS membrane, the separation factor and total flux of MMM with ZIF‐8 loading content of 20 wt% increased by 70 % and 23 %, respectively. The mechanism of mass transfer of butanol and water molecules inside the MMMs was also discussed.
The Effects of Lanthanide Ions Doping and Chromophore Anchoring on the Photocurrent Response and Photocatalytic Behaviours of Titanium‐Oxo‐Clusters
Authors: Luo W. , Wu X.‐H. , Cai B. , Zhang H.‐L. , Liu M.‐D. , Huang Y. , Ge G.‐W. , Hu B. 
Published: March 2022

AbstractLanthanide‐titanium‐oxo‐clusters (LnTOCs) have been attractive as a rapidly growing class of molecular materials due to their use as molecular models and precursors of nano titanium oxide. Although various applications of LnTOCs with alkoxide/carboxylate ligands have been documented, phenol dyes coordination LnTOCs applications in antibiotics fields have not been reported yet. Herein three LnTOCs formulated as [Ti2Ln2O(OiPr)6(NO3)4(2,3‐DN)2]2 ⋅ 3.5Et3N ⋅ 2HOiPr (Ln=Tb (1), Eu (2) and Yb (3)) were designed and synthesized. Their structures consisted of a Ti2Tb2O subunit and two 2, 3‐DN ligands. Using cluster 1, Ti2(2, 3‐DN)2 and Ti2Tb2, photocurrent response and photocatalytic dye degeneration were examined. The improvements in photocurrent intensity and photocatalytic activity of dye‐degradation could be attributed to the cooperative effect of the Ln3+ doping and 2, 3‐DN coordination. Furthermore, using cluster 1 as a precursor, F1 exhibited high photoactivity for tetracycline. The antibiotics application of LnTOCs was evaluated firstly. The results indicate that clusters 1–3 have potential applications as a molecule based photodegeneration catalyst.