bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electrochemically Enabled One‐Pot Multistep Synthesis of C19 Androgen Steroids
Authors: Sommer Florian , Kappe C. Oliver , Cantillo David 
Published: February 2021

AbstractThe synthesis of many valuable C19 androgens can be accomplished by removal of the C17 side chain from more abundant corticosteroids, followed by further derivatization of the resulting 17‐keto derivative. Conventional chemical reagents pose significant drawbacks for this synthetic strategy, as large amounts of waste are generated, and quenching of the reaction mixture and purification of the 17‐ketosteroid intermediate are typically required. Herein, we present mild, safe, and sustainable electrochemical strategies for the preparation of C19 steroids. A reagent and catalyst free protocol for the removal of the C17 side chain of corticosteroids via anodic oxidation has been developed, enabling several one‐pot, multistep procedures for the synthesis of androgen steroids. In addition, simultaneous anodic C17 side chain cleavage and cathodic catalytic hydrogenation of a steroid has been demonstrated, rendering a convenient and highly atom economic procedure for the synthesis of saturated androgens.
Frischluftzufuhr besser nicht von oben
Authors: Schmitz Kathrin 
Published: February 2021

AbstractIn einer aktuellen Stellungnahme analysiert der Arbeitsausschuss Feinstäube (AAF) den Aerosol‐Transmissionspfad der Corona‐Pandemie genauer. Die Expertinnen und Experten gehen auf Gegenmaßnahmen ein und erläutern, wie sich durch Masken, richtiges Lüften, geeignete Luftreinigung und Überkopfabsaugungen die Aerosollast und damit die Übertragung verhindern lässt. Das Papier steht kostenfrei zum Download zur Verfügung.
Den Kreislauf schließen
Authors: Haubensak Silke , Schober Dennis , Sturm Michael , Schuhen Katrin 
Published: February 2021

AbstractMikroplastik ist in aller Munde und gleichzeitig ein hochkomplexes Thema. Wir essen, trinken und atmen Mikroplastik – jeder von uns, jeden Tag. Diese vielen kleinen Kunststoffpartikel mit einer Größe kleiner als 5 mm befinden sich fein verteilt in Boden
Energieeffizienz kann man herbeisteuern
Authors: Schimmer Oliver , Hauser Jan 
Published: February 2021

AbstractDrehzahlgeregelte Kompressoren gelten oft als Wunderwaffe, wenn es darum geht, Energie zu sparen. Doch falsch betrieben verbrauchen sie mehr Energie als herkömmliche Geräte. Erst eine intelligente Übergeordnete Steuerung schöpft das Potenzial drehzahlgere
Universalwerkzeug bei Feldeinsätzen
Authors: Gampp Stefan , Kraftschik Florian 
Published: February 2021

AbstractDie fortschreitende Digitalisierung von Prozessanlagen führt dazu, dass immer mehr Daten produziert werden. Jedoch werden die daraus erwachsenden Möglichkeiten noch immer wenig genutzt und in den Anlagen schlummern große Produktivitätspotentiale. Dies gil
Si/FeSi2 Nanoparticles Prepared by Thermal Plasma with Stress‐releasing Effect for Li‐ion Storage
Authors: Du Yu , Yang Zongxian , Bai Liuyang , Ding Fei , Jin Huacheng , Yang Yijun , Lam Tran Dai , Hou Guolin , Yuan Fangli 
Published: February 2021

AbstractSilicon (Si) anode materials have been extensively studied due to high capacity and abundant reserves. Herein, inspired by the Li+‐inert components, we design a novel silicon/iron silicide nanoparticles (Si/FeSi2 NPs) prepared by thermal plasma to achieve stress‐releasing effect. The Si/FeSi2 NPs is composed of Si and FeSi2 which exhibits superhigh Initial Coulomb Efficiency (ICE, 89%) with a capacity of 1121 mAh g−1 after 850 cycles. The mechanism of the FeSi2 phase in the Si/FeSi2 NPs is studied by using finite element modelling creatively, demonstrating that the FeSi2 phase can buffer the volume expansion effectively by reducing the stress concentration on the particles surface and releasing internal stress of particles, thus maintaining structural integrity. After combining with carbon coating layer, the Si/FeSi2/carbon/graphite materials (Si/FeSi2/C/G) can achieve superior electrochemical performances. This work provides new insight into the development of the structural stable Si‐alloy anodes towards LIBs applications.
The Gauche Effect in XCH2CH2X Revisited
Authors: Rodrigues Silva Daniela , de Azevedo Santos Lucas , Hamlin Trevor A. , Fonseca Guerra Célia , Freitas Matheus P. , Bickelhaupt F. Matthias 
Published: February 2021

AbstractWe have quantum chemically investigated the rotational isomerism of 1,2‐dihaloethanes XCH2CH2X (X = F, Cl, Br, I) at ZORA‐BP86‐D3(BJ)/QZ4P. Our Kohn‐Sham molecular orbital (KS‐MO) analyses reveal that hyperconjugative orbital interactions favor the gauche conformation in all cases (X = F−I), not only for X = F as in the current model of this so‐called gauche effect. We show that, instead, it is the interplay of hyperconjugation with Pauli repulsion between lone‐pair‐type orbitals on the halogen substituents that constitutes the causal mechanism for the gauche effect. Thus, only in the case of the relatively small fluorine atoms, steric Pauli repulsion is too weak to overrule the gauche preference of the hyperconjugative orbital interactions. For the larger halogens, X⋅⋅⋅X steric Pauli repulsion becomes sufficiently destabilizing to shift the energetic preference from gauche to anti, despite the opposite preference of hyperconjugation.
Sharp Turns and Fluorescent Repeats: Modular Construction and Shape‐Dependent Electronic Properties of π‐Conjugated Chain Molecules
Authors: Lee Milim , Kang Suk‐il , Song Sungmin , Kim Hongsik , Lee Dongwhan 
Published: February 2021

AbstractIn search of the design rules for structural ordering of open‐chain molecules, we have built a series of zig‐zag shaped π‐conjugated structures with ring‐fused heteroaromatics as sharp turns and tolane‐based linear fragments as light‐emitting units. Using only a finite number of common building blocks, an efficient “double‐elongation” strategy was implemented to construct a series of π‐conjugated oligomers with precise length control (55–89 % yields). Our approach takes advantage of the modular nature of the bis(triazolo)benzene synthesis and the masked reactivity of the nitro group. A combination of photophysical and DFT computational studies revealed that the bis(triazolo)benzene–tolane repeat units behave as electronically decoupled light‐absorbing/emitting units (λmax,em = 408–422 nm; ΦF = 20–25 % in THF). Such context‐independent photophysical properties promise their potential applications in chemical sensing and switching.
An improved control strategy of grid‐tied solar photovoltaic system using active current detection method
Authors: Jalan Subham Kumar , Babu B. Chitti , Sridharan K. , Gupta Nitin 
Published: February 2021

SummaryThis paper presents an active current detection method (ACDM) for three‐phase grid‐tied solar photovoltaic (PV) system. The proposed control utilizes the character triangular function (CTF) for fundamental component extraction and minimizes the computational burden. This shows the effectiveness of proposed ACDM under variety of operating conditions. Moreover, the design of control algorithm allows superior voltage regulation in outer voltage control loop, which reduces the peak overshoot during transients. This will also help in regulating grid current quickly, and it accurately follows the reference current. Further, the proposed control algorithm effectively deals with several power quality (PQ) issues and maintains the continuous power flow to satisfy the load demand. Finally, the withstand capability of the proposed ACDM controller is verified by simulation studies under MATLAB®/Simulink environment and experimentally validated by dSPACE‐1104 based downscaled laboratory prototype.
Understanding cell‐cell communication and signaling in the colorectal cancer microenvironment
Authors: AlMusawi Shaikha , Ahmed Mehreen , Nateri Abdolrahman S. 
Published: February 2021

AbstractCarcinomas are complex heterocellular systems containing epithelial cancer cells, stromal fibroblasts, and multiple immune cell‐types. Cell‐cell communication between these tumor microenvironments (TME) and cells drives cancer progression and influences response to existing therapies. In order to provide better treatments for patients, we must understand how various cell‐types collaborate within the TME to drive cancer and consider the multiple signals present between and within different cancer types. To investigate how tissues function, we need a model to measure both how signals are transferred between cells and how that information is processed within cells. The interplay of collaboration between different cell‐types requires cell‐cell communication. This article aims to review the current in vitro and in vivo mono‐cellular and multi‐cellular cultures models of colorectal cancer (CRC), and to explore how they can be used for single‐cell multi‐omics approaches for isolating multiple types of molecules from a single‐cell required for cell‐cell communication to distinguish cancer cells from normal cells. Integrating the existing single‐cell signaling measurements and models, and through understanding the cell identity and how different cell types communicate, will help predict drug sensitivities in tumor cells and between‐ and within‐patients responses.
Deep learning‐enabled imaging flow cytometry for high‐speedCryptosporidium and Giardia detection
Authors: Luo Shaobo , Nguyen Kim Truc , Nguyen Binh T. T. , Feng Shilun , Shi Yuzhi , Elsayed Ahmed , Zhang Yi , Zhou Xiaohong , Wen Bihan , Chierchia Giovanni , Talbot Hugues , Bourouina Tarik , Jiang Xudong , Liu Ai Qun 
Published: February 2021

AbstractImaging flow cytometry has become a popular technology for bioparticle image analysis because of its capability of capturing thousands of images per second. Nevertheless, the vast number of images generated by imaging flow cytometry imposes great challenges for data analysis especially when the species have similar morphologies. In this work, we report a deep learning‐enabled high‐throughput system for predicting Cryptosporidium and Giardia in drinking water. This system combines imaging flow cytometry and an efficient artificial neural network called MCellNet, which achieves a classification accuracy >99.6%. The system can detect Cryptosporidium and Giardia with a sensitivity of 97.37% and a specificity of 99.95%. The high‐speed analysis reaches 346 frames per second, outperforming the state‐of‐the‐art deep learning algorithm MobileNetV2 in speed (251 frames per second) with a comparable classification accuracy. The reported system empowers rapid, accurate, and high throughput bioparticle detection in clinical diagnostics, environmental monitoring and other potential biosensing applications.
On the unified error performance of PSK modulation schemes over mm‐wave wireless channels affected by carrier phase synchronization errors
Authors: Khanna Himanshu 
Published: February 2021

SummaryThe performance of radio‐frequency (RF) networks where channels are modeled by an extended‐generalized‐K(EGK) distribution and consider significant phase errors during coherent detection at the receiver due to carrier‐phase‐synchronization‐mismatch is investigated in this work. The performance is evaluated for a single‐hop link and two‐hop amplify‐and‐forward (AF) and decode‐and‐forward (DF) relay‐assisted RF links. The EGK is a generalized distribution, which can model various fading conditions in millimeter (mm)‐wave wireless channels where transmission frequency is 60 GHz and above and takes into account non‐homogeneous propagation, interference effects in a multiuser transmission environment, multipath fading and shadowing effects. The average symbol error probability (ASEP) performance is evaluated for a single‐hop link when carrier is modulated using multilevel PSK modulation scheme. Based on the analytical results obtained for a single‐hop link, the mathematical analysis for the error performance in widely employed AF and DF relay‐assisted RF two‐hop networks is developed and ASEP is derived. To quantify the degradation in system performance introduced by phase errors, the reference‐carrier phase estimation loss for a single‐hop RF link is also evaluated. The obtained analytical results are also verified by numerical plots and depict the effects of various channel conditions existing over the RF link and phase synchronization errors.
Architecture and sequence stratigraphy of the Upper Coralline Limestone formation, Malta—Implications for Eastern Mediterranean restriction prior to the Messinian Salinity Crisis
Authors: Bialik Or M. , Zammit Raymond , Micallef Aaron 
Published: February 2021

AbstractThe Eastern and Western Mediterranean are separated by an elevated plateau that regulates water exchange between these two basins. The Maltese archipelago, situated atop this topographic high, offers a unique window into the evolution of this plateau in the lead up to the Messinian Salinity Crisis. The Upper Coralline Limestone Formation was deposited between the late Tortonian and the early Messinian and was probably terminated by palaeoceanographic events related to the Messinian Salinity Crisis. It represents the youngest Miocene sedimentary deposits outcropping in the Maltese archipelago. This shallow‐water carbonate unit can be used to trace palaeoenvironmental changes atop the sill between the Eastern and Western Mediterranean and to explain the possible water flow restrictions to the Eastern Mediterranean that could have preceded the Messinian Salinity Crisis. Here field surveys, and analysis of the depositional environment within the Upper Coralline Limestone in Malta, are combined with recently acquired multichannel seismic reflection profiles between Malta and Gozo, to reconstruct the depositional sequence in the Malta Plateau during the late Miocene. The Upper Coralline Limestone consists of multiple coralline and larger benthic foraminifera dominated facies, extending from subtidal to intertidal environments. These accumulated in two depositional cycles observed in both outcrop and seismic reflection data. Each cycle exhibits an early aggradation–progradation phase followed by a progradation phase and a final aggradation phase. These manifest themselves in the outcrops as shallowing and deepening upwards phases. These were deposited above a deep water unit and are indicative of a preceding uplift phase followed by filling of the accommodation space through the deposition of the Upper Coralline Limestone Formation in shallow marine depths. The presence of this highly elevated sill during the late Miocene could have restricted circulation to the eastern basin.
Grazing affects vegetation diversity and heterogeneity in California vernal pools
Authors: Michaels Julia , Batzer Evan , Harrison Susan , Eviner Valerie T. 
Published: February 2021

AbstractDisturbance often increases local‐scale (α) diversity by suppressing dominant competitors. However, widespread disturbances may also reduce biotic heterogeneity (β diversity) by making the identities and abundances of species more similar among patches. Landscape‐scale (γ) diversity may also decline if disturbance‐sensitive species are lost. California’s vernal pool plant communities are species rich, in part because of two scales of β diversity: (1) within pools, as species composition changes with depth (referred to here asvertical β diversity), and (2) between pools, in response to dispersal limitation and variation in pool attributes (referred to here ashorizontal β diversity). We asked how grazing by livestock, a common management practice, affects vernal pool plant diversity at multiple hierarchical spatial scales. In terms of abundance‐weighted diversity, grazing increased α both within local pool habitat zones and at the whole‐pool scale, as well as γ at the pasture scale without influencing horizontal or vertical β diversity. In terms of species richness, increases in α diversity within habitat zones and within whole pools led to small decreases in horizontal β diversity as species occupancy increased. This had a dampened effect on species richness at the γ (pasture) scale without any loss of disturbance‐sensitive species. We conclude that grazing increases species richness and evenness (α) by reducing competitive dominance, without large disruptions to the critical spatial heterogeneity (β) that generates high landscape‐level diversity (γ).
Lysosome Specific Platinum(II) Catecholates with Photoactive BODIPY for Imaging and Photodynamic Therapy in Near‐IR Light
Authors: Ramu Vanitha , Kundu Paramita , Upadhyay Aarti , Kondaiah Paturu , Chakravarty Akhil R. 
Published: February 2021

AbstractPlatinum(II)‐BODIPY (boron‐dipyrromethene) complexes of 1,2‐diaminocyclohexane (dach), [Pt(dach)(ML)] (MP) and [Pt(dach)(IML)] (IMP), where H2ML is morpholine‐appended O,O‐donor mono‐styryl BODIPY‐appended catecholate and H2IML is di‐iodinated morpholine‐conjugated O,O‐donor mono‐styryl BODIPY linked catecholate, were prepared for photodynamic therapy in near‐IR light (600–720 nm) by targeting lysosomes. Complex MP exhibited a band at 596 nm (ϵ=2.9×104 M−1 cm−1) and IMP at 710 nm (ϵ=2.6×104 M−1 cm−1) within PDT window in dimethyl sulfoxide (10 %)/Dulbecco's Modified Eagle's Medium (DMSO/DMEM, pH 7.2). Complexes MP and IMP showed red emission (λem) at 615 nm (λex=580 nm, ΦF=0.04) and 718 nm (λex=685 nm) (ΦF, fluorescence quantum yield) in DMSO (10 %)‐DMEM (pH 7.2). Emissive complex MP showed lysosome‐specific localization in cellular imaging study. Complex IMP showed photocytotoxicity in near‐IR light of 600–720 nm (IC50: 0.86–1.2 μM) with apoptotic cell death forming singlet oxygen in a type‐II pathway.
Effects of diethyl aminoethyl hexanoate (DA‐6) on the growth and cadmium accumulation of tomato seedlings
Authors: Dong Yiping , Liang Le , Lin Lijin , Li Huanxiu , Liao Ming'An , Sun Guochao , Liang Dong , Xia Hui , Wang Jin , Wang Xun , Tu Lihua , Tang Yi 
Published: February 2021

AbstractDiethyl aminoethyl hexanoate (DA‐6) can lessen the effects of cadmium (Cd) toxicity on some plants. A pot experiment was conducted to examine the impact of different DA‐6 concentrations (0, 10, 20, 30, and 40 mg/L) on growth and Cd accumulation of tomato seedlings. A DA‐6 concentration of 10 mg/L increased the biomass of roots, stems, leaves, and shoots, while the other concentrations either had no significant effects or inhibited the growth of tomato seedlings. Concentrations 10 and 20 mg/L of DA‐6 increased the chlorophyll b and total chlorophyll contents, and the activities of superoxide dismutase and peroxidase. All the four tested concentrations of DA‐6 reduced catalase activity and increased the soluble protein content. Importantly, all tested DA‐6 concentrations decreased the Cd content of tomato seedling roots, and increased in the Cd contents of stems, leaves, and shoots. While 10 mg/L DA‐6 did not significantly affect the translocation factor of tomato seedlings, the other tested DA‐6 concentrations enhanced the translocation factor. Therefore, 10 mg/L DA‐6 could significantly promote the growth of tomato, but all the tested concentrations of DA‐6 could also promote the uptake of Cd in tomato shoots, which could impede the safe production of tomatoes in Cd‐contaminated soils.
Adaptive modem and interference suppression based on deep learning
Authors: Wei Peng , Wang Shilian , Luo Junshan 
Published: February 2021

AbstractWith the increasingly fierce competition of electromagnetic spectrum, developing intelligent communication systems that can reconfigure its waveform can effectively improve the communication system's ability to adapt to the complex electromagnetic environment. In this paper, an adaptive modem based on a deep autoencoder network (DAN) is designed, and the demodulation performance that is close to, consistent with, or better than traditional MPSK or QAM is achieved. This DAN can be trained by a unified loss function and a unified optimization algorithm to implement a variety of modems. For high‐order modems, the constellation diagrams generated by the DAN are radically different from the traditional modulation and very difficult to distinguish linearly, which is beneficial to improve the anti‐interception ability of the communication systems. Additionally, based on the trained DAN, a convolutional neural network (CNN) with a single convolutional layer is incorporated to suppress a variety of interferences. By using transfer learning, the new deep learning (DL) model with the CNN converges fast with a few epochs of training. Training and test results verify that the new DL model can improve the anti‐interference ability of the communication systems by learning and suppressing the interferences in both frequency and power domains.
An intrusion detection system using optimized deep neural network architecture
Authors: Ramaiah Mangayarkarasi , Chandrasekaran Vanmathi , Ravi Vinayakumar , Kumar Neeraj 
Published: February 2021

AbstractInternet usage became increasingly ubiquitous. The concern regarding security and privacy has become essential for Internet users. As the usage of the Internet increases the number of cyber‐attacks also increases substantially. Intrusion detection is one of the challenging aspects of network security. Efficient intrusion detection is crucial for every organization to mitigate the vulnerability. This paper presents a novel intrusion detection system to detect malicious attacks targeted at a smart environment. The proposed Intrusion detection method uses a correlation tool and a random forest method to detect the predominant independent variables for improvising neural‐based attack classifier. To detect a malicious attack, a shallow neural network and an optimized neural‐based classifier are presented. The designed intrusion detection system has experimented on the KDDCUP99 dataset. The experimental results reveal that the performance of the proposed intrusion detection system is superior in terms of quantitative metrics. Thus, the proposed system can be deployed in the IoT and wireless networks to detect cyber‐attacks.
Human resources and corporate failure prediction modeling: Evidence from Belgium
Authors: Brédart Xavier , Séverin Eric , Veganzones David 
Published: February 2021

AbstractThis paper analyzes the prediction performance of human resources (HR) variables in corporate failure modeling. We define corporate failure as a two‐phase process from financial distress to bankruptcy, so that we can determine the prediction power of HR variables along a firm's phase in the financial deterioration process. We demonstrate the use of HR variables and their application to a two‐phase corporate failure model, providing first evidence for the predictive power of HR variables. The experimental results, based on real‐world datasets from Belgium, show that HR variables used in conjugation with accounting‐based information improve the accuracy of prediction modeling. However, the predictive power of HR variables varies in different phases of corporate failure with better prediction accuracy during the initial symptoms of corporate failure (i.e., financial distress). Findings show that our proposed model predicted financial distress with 84.1%, whereas the accuracy decreased to 83.3% when predicting bankruptcy. Besides, they also show that, on average, the inclusion of HR variables improves the global accuracy of the prediction models of 3.8% and allows to decrease Type I error of 5%.