bluuebunny/crossref_metadata_2025 huggingface dataset:
Regulation of developmental hierarchy inDrosophilaneural stem cell tumors by COMPASS and Polycomb complexes
Authors: Gaultier Cassandra , Foppolo Sophie , Maurange Cédric
Published: May 2022

COMPASS and Polycomb complexes are antagonistic chromatin complexes that are frequently inactivated in cancers, but how these events affect the cellular hierarchy, composition, and growth of tumors is unclear. These characteristics can be systematically investigated inDrosophilaneuroblast tumors in which cooption of temporal patterning induces a developmental hierarchy that confers cancer stem cell (CSC) properties to a subset of neuroblasts retaining an early larval temporal identity. Here, using single-cell transcriptomics, we reveal that the trithorax/MLL1/2-COMPASS–like complex guides the developmental trajectory at the top of the tumor hierarchy. Consequently,trithoraxknockdown drives larval-to-embryonic temporal reversion and the marked expansion of CSCs that remain locked in a spectrum of early temporal states. Unexpectedly, this phenotype is amplified by concomitant inactivation of Polycomb repressive complex 2 genes, unleashing tumor growth. This study illustrates how inactivation of specific COMPASS and Polycomb complexes cooperates to impair tumor hierarchies, inducing CSC plasticity, heterogeneity, and expansion.
Theory-guided experimental design in battery materials research
Authors: Eng Alex Yong Sheng , Soni Chhail Bihari , Lum Yanwei , Khoo Edwin , Yao Zhenpeng , Vineeth S. K. , Kumar Vipin , Lu Jun , Johnson Christopher S. , Wolverton Christopher , Seh Zhi Wei
Published: May 2022

A reliable energy storage ecosystem is imperative for a renewable energy future, and continued research is needed to develop promising rechargeable battery chemistries. To this end, better theoretical and experimental understanding of electrochemical mechanisms and structure-property relationships will allow us to accelerate the development of safer batteries with higher energy densities and longer lifetimes. This Review discusses the interplay between theory and experiment in battery materials research, enabling us to not only uncover hitherto unknown mechanisms but also rationally design more promising electrode and electrolyte materials. We examine specific case studies of theory-guided experimental design in lithium-ion, lithium-metal, sodium-metal, and all-solid-state batteries. We also offer insights into how this framework can be extended to multivalent batteries. To close the loop, we outline recent efforts in coupling machine learning with high-throughput computations and experiments. Last, recommendations for effective collaboration between theorists and experimentalists are provided.
Stretchable broadband photo-sensor sheets for nonsampling, source-free, and label-free chemical monitoring by simple deformable wrapping
Authors: Li Kou , Araki Teppei , Utaki Ryogo , Tokumoto Yu , Sun Meiling , Yasui Satsuki , Kurihira Naoko , Kasai Yuko , Suzuki Daichi , Marteijn Ruben , den Toonder Jaap M.J. , Sekitani Tsuyoshi , Kawano Yukio
Published: May 2022

Chemical monitoring communicates diverse environmental information from industrial and biological processes. However, promising and sustainable systems and associated inspection devices that dynamically enable on-site quality monitoring of target chemicals confined inside transformable and opaque channels are yet to be investigated. This paper designs stretchable photo-sensor patch sheets for nonsampling, source-free, and label-free on-site dynamic chemical monitoring of liquids flowing inside soft tubes via simple deformable surface wrapping. The device integrates carbon nanotube–based broadband photo-absorbent thin films with multilayer-laminated stretchable electrodes and substrates. The patterned rigid-soft structure of the proposed device provides durability and optical stability against mechanical deformations with a stretchability range of 70 to 280%, enabling shape-conformable attachments to transformable objects. The effective use of omnidirectional and transparent blackbody radiation from free-form targets themselves allows compact measurement configuration and enhances the functionality and simplicity of this scheme, while the presenting technology monitors concentrations of arbitrary water-soluble chemicals.
An empirical mean-field model of symmetry-breaking in a turbulent wake
Authors: Callaham Jared L. , Rigas Georgios , Loiseau Jean-Christophe , Brunton Steven L.
Published: May 2022

Improved turbulence modeling remains a major open problem in mathematical physics. Turbulence is notoriously challenging, in part due to its multiscale nature and the fact that large-scale coherent structures cannot be disentangled from small-scale fluctuations. This closure problem is emblematic of a greater challenge in complex systems, where coarse-graining and statistical mechanics descriptions break down. This work demonstrates an alternative data-driven modeling approach to learn nonlinear models of the coherent structures, approximating turbulent fluctuations as state-dependent stochastic forcing. We demonstrate this approach on a high–Reynolds number turbulent wake experiment, showing that our model reproduces empirical power spectra and probability distributions. The model is interpretable, providing insights into the physical mechanisms underlying the symmetry-breaking behavior in the wake. This work suggests a path toward low-dimensional models of globally unstable turbulent flows from experimental measurements, with broad implications for other multiscale systems.
Influenza virus replication in cardiomyocytes drives heart dysfunction and fibrosis
Authors: Kenney Adam D. , Aron Stephanie L. , Gilbert Clara , Kumar Naresh , Chen Peng , Eddy Adrian , Zhang Lizhi , Zani Ashley , Vargas-Maldonado Nahara , Speaks Samuel , Kawahara Jeffrey , Denz Parker J. , Dorn Lisa , Accornero Federica , Ma Jianjie , Zhu Hua , Rajaram Murugesan V. S. , Cai Chuanxi , Langlois Ryan A. , Yount Jacob S.
Published: May 2022

Cardiac dysfunction is a common complication of severe influenza virus infection, but whether this occurs due to direct infection of cardiac tissue or indirectly through systemic lung inflammation remains unclear. To test the etiology of this aspect of influenza disease, we generated a novel recombinant heart-attenuated influenza virus via genome incorporation of target sequences for miRNAs expressed in cardiomyocytes. Compared with control virus, mice infected with miR-targeted virus had significantly reduced heart viral titers, confirming cardiac attenuation of viral replication. However, this virus was fully replicative in the lungs and induced similar systemic inflammation and weight loss compared to control virus. The miR-targeted virus induced fewer cardiac conduction irregularities and significantly less fibrosis in mice lacking interferon-induced transmembrane protein 3 (IFITM3), which serve as a model for influenza-associated cardiac pathology. We conclude that robust virus replication in the heart is required for pathology, even when lung inflammation is severe.
Real-time 3D optoacoustic tracking of cell-sized magnetic microrobots circulating in the mouse brain vasculature
Authors: Wrede Paul , Degtyaruk Oleksiy , Kalva Sandeep Kumar , Deán-Ben Xosé Luis , Bozuyuk Ugur , Aghakhani Amirreza , Akolpoglu Birgul , Sitti Metin , Razansky Daniel
Published: May 2022

Mobile microrobots hold remarkable potential to revolutionize health care by enabling unprecedented active medical interventions and theranostics, such as active cargo delivery and microsurgical manipulations in hard-to-reach body sites. High-resolution imaging and control of cell-sized microrobots in the in vivo vascular system remains an unsolved challenge toward their clinical use. To overcome this limitation, we propose noninvasive real-time detection and tracking of circulating microrobots using optoacoustic imaging. We devised cell-sized nickel-based spherical Janus magnetic microrobots whose near-infrared optoacoustic signature is enhanced via gold conjugation. The 5-, 10-, and 20-μm-diameter microrobots are detected volumetrically both in bloodless ex vivo tissues and under real-life conditions with a strongly light-absorbing blood background. We further demonstrate real-time three-dimensional tracking and magnetic manipulation of the microrobots circulating in murine cerebral vasculature, thus paving the way toward effective and safe operation of cell-sized microrobots in challenging and clinically relevant intravascular environments.
Magnetoelectric dissociation of Alzheimer’s β-amyloid aggregates
Authors: Jang Jinhyeong , Park Chan Beum
Published: May 2022

The abnormal self-assembly of β-amyloid (Aβ) peptides and their deposition in the brain is a major pathological feature of Alzheimer’s disease (AD), the most prevalent chronic neurodegenerative disease affecting nearly 50 million people worldwide. Here, we report a newly discovered function of magnetoelectric nanomaterials for the dissociation of highly stable Aβ aggregates under low-frequency magnetic field. We synthesized magnetoelectric BiFeO
3
-coated CoFe
2
O
4
(BCFO) nanoparticles, which emit excited charge carriers in response to low-frequency magnetic field without generating heat. We demonstrated that the magnetoelectric coupling effect of BCFO nanoparticles successfully dissociates Aβ aggregates via water and dissolved oxygen molecules. Our cytotoxicity evaluation confirmed the alleviating effect of magnetoelectrically excited BCFO nanoparticles on Aβ-associated toxicity. We found high efficacy of BCFO nanoparticles for the clearance of microsized Aβ plaques in ex vivo brain tissues of an AD mouse model. This study shows the potential of magnetoelectric materials for future AD treatment using magnetic field.
In vivo hitchhiking of immune cells by intracellular self-assembly of bacteria-mimetic nanomedicine for targeted therapy of melanoma
Authors: Gao Cheng , Wang Qingfu , Li Junyan , Kwong Cheryl H. T. , Wei Jianwen , Xie Beibei , Lu Siyu , Lee Simon M. Y. , Wang Ruibing
Published: May 2022

Cell-based drug carriers are mostly prepared in vitro, which may negatively affect the physiological functions of cells, and induce possible immune rejections when applied to different individuals. In addition, the immunosuppressive tumor microenvironment limits immune cell–mediated delivery. Here, we report an in vivo strategy to construct cell-based nanomedicine carriers, where bacteria-mimetic gold nanoparticles (GNPs) are intravenously injected, selectively phagocytosed by phagocytic immune cells, and subsequently self-assemble into sizable intracellular aggregates via host-guest interactions. The intracellular aggregates minimize exocytosis of GNPs from immune cells and activate the photothermal property via plasmonic coupling effects. Phagocytic immune cells carry the intracellular GNP aggregates to melanoma tissue via inflammatory tropism. Moreover, an initial photothermal treatment (PTT) of the tumor induces tumor damage that subsequently provides positive feedback to recruit more immune cell–based carriers for enhanced targeting efficiency. The optimized secondary PTT notably improves antitumor immunotherapy, further strengthened by immune checkpoint blockade.
Invasive chameleons released from predation display more conspicuous colors
Authors: Whiting Martin J. , Holland Brenden S. , Keogh J. Scott , Noble Daniel W. A. , Rankin Katrina J. , Stuart-Fox Devi
Published: May 2022

Conspicuous social and sexual signals are predicted to experience pronounced character release when natural selection via predation is relaxed. However, we have few good examples of this phenomenon in the wild and none in species with dynamic color change. Here, we show that Jackson’s chameleons inadvertently introduced from Kenya to Hawaii (Oahu), where there are no coevolved, native lizard predators, experienced pronounced character release of color signals. Hawaiian chameleons displayed more conspicuous social color signals than Kenyan chameleons during male contests and courtship, were less cryptic in response to bird and snake predators, and showed greater change between display and antipredator color states. Hawaiian chameleon display colors were also more conspicuous in their local than ancestral habitats, consistent with local adaptation of social signals. These results demonstrate that relaxed predation pressure can result in character release of dynamic social signals in introduced species experiencing strong sexual selection.
A bioinspired revolving-wing drone with passive attitude stability and efficient hovering flight
Authors: Bai Songnan , He Qingning , Chirarattananon Pakpong
Published: May 2022

Among small rotorcraft, the use of multiple compact rotors in a mechanically simple design leads to impressive agility and maneuverability but inevitably results in high energetic demand and acutely restricted endurance. Small spinning propellers used in these vehicles contrast with large lifting surfaces of winged seeds, which spontaneously gyrate into stable autorotation upon falling. The pronounced aerodynamic surfaces and delayed stalls are believed key to efficient unpowered flight. Here, the bioinspired principles are adopted to notably reduce the power consumption of small aerial vehicles by means of a samara-inspired robot. We report a dual-wing 35.1-gram aircraft capable of hovering flight via powered gyration. Equipped with two rotors, the underactuated robot with oversized revolving wings, designed to leverage unsteady aerodynamics, was optimized for boosted flight efficiency. Through the analysis of flight dynamics and stability, the vehicle was designed for passive attitude stability, eliminating the need for fast feedback to stay upright. To this end, the drone demonstrates flight with a twofold decrease in power consumption when compared with benchmark multirotor robots. Exhibiting the power loading of 8.0 grams per watt, the vehicle recorded a flight time of 14.9 minutes and up to 24.5 minutes when equipped with a larger battery. Taking advantage of the fast revolving motion to overcome the severe underactuation, we also realized position-controlled flight and illustrated examples of mapping and surveillance applications with a 21.5-gram payload.
In Vitro
Activity of Nitroxoline in Antifungal-Resistant
Candida
Species Isolated from the Urinary Tract
Authors: Fuchs Frieder , Aldejohann Alexander Maximilian , Hoffmann Ada Marie , Walther Grit , Kurzai Oliver , Hamprecht Axel G.
Published: May 2022

Infections by drug-resistant fungi are increasingly reported worldwide; however, only few novel antifungals are being developed. The old antimicrobial nitroxoline is currently repurposed for oral treatment of bacterial urinary tract infections (UTI).
Utility of Cytomegalovirus Cell-Mediated Immunity Assays in Solid Organ Transplantation
Authors: Hall Victoria G. , Humar Atul , Kumar Deepali
Published: May 2022

Cytomegalovirus (CMV) is one of the most important viral complications after solid organ transplantation (SOT). Current preventive and management strategies rely primarily on serologic and viral load testing and remain suboptimal.
SARS-CoV-2 Variants of Concern Hijack IFITM2 for Efficient Replication in Human Lung Cells
Authors: Nchioua Rayhane , Schundner Annika , Kmiec Dorota , Prelli Bozzo Caterina , Zech Fabian , Koepke Lennart , Graf Alexander , Krebs Stefan , Blum Helmut , Frick Manfred , Sparrer Konstantin M. J. , Kirchhoff Frank
Published: May 2022

Recent data indicate that SARS-CoV-2 requires endogenously expressed IFITM proteins for efficient infection. However, the results were obtained with an early SARS-CoV-2 isolate.
A Case Series of Rifabutin Use in Staphylococcal Prosthetic Infections
Authors: Monk Miranda , Elshaboury Ramy , Tatara Alexander , Nelson Sandra , Bidell Monique R.
Published: May 2022

This work evaluates real-world data and clinical outcomes when rifabutin is used in place of rifampin for adjunctive management of staphylococcal hardware-associated infections. This is the second case study looking at this specific use of rifabutin, signifying the current lack of clinical data in this area. Assessing use of rifabutin in this capacity is clinically important given its lower propensity for drug interactions compared to rifampin.
Emergence of SARS-CoV-2 Spike Mutations during Prolonged Infection in Immunocompromised Hosts
Authors: Ko Karrie K. K. , Yingtaweesittikul Hatairat , Tan Thuan Tong , Wijaya Limin , Cao Delphine Yanhong , Goh Sui Sin , Abdul Rahman Nurdyana Binte , Chan Kenneth X. L. , Tay Hui Ming , Sim James Heng Chiak , Chan Kian Sing , Oon Lynette L. E. , Nagarajan Niranjan , Suphavilai Chayaporn
Published: May 2022

The emergence of clinically important mutations described in this report highlights the need for sustained vigilance and containment measures when managing immunocompromised patients with persistent COVID-19. Even as jurisdictions across the globe start lifting pandemic control measures, immunocompromised patients with persistent COVID-19 constitute a unique group that requires close genomic monitoring and enhanced infection control measures, to ensure early detection and containment of mutations and variants of therapeutic and public health importance.
Familial risk of epithelial ovarian cancer after accounting for gynaecological surgery: a population-based study
Authors: Barnard Mollie E , Meeks Huong , Jarboe Elke A , Albro James , Camp Nicola J , Doherty Jennifer A
Published: May 2022

Background

Uptake of risk-reducing surgery has increased among women at high risk of epithelial ovarian cancer. We sought to characterise familial risk of epithelial ovarian cancer histotypes in a population-based study after accounting for gynaecological surgeries, including bilateral oophorectomy.

Methods

We compared risk of epithelial ovarian cancer in relatives of 3536 epithelial ovarian cancer cases diagnosed in 1966–2016 and relatives of 35 326 matched controls. We used Cox competing risk models, incorporating bilateral oophorectomy as a competing risk, to estimate the relative risk of ovarian cancer in first-degree (FDR), second-degree (SDR) and third-degree (TDR) relatives from 1966 to 2016. We also estimated relative risks in time periods before (1966–1994, 1995–2004) and after (2005–2016) formal recommendations were made for prophylactic oophorectomy among women with pathogenic variants inBRCA1/2.

Results

The relative risks of epithelial ovarian cancer in FDRs, SDRs and TDRs of cases versus controls were 1.68 (95% CI 1.39 to 2.04), 1.51 (95% CI 1.30 to 1.75) and 1.34 (95% CI 1.20 to 1.48), respectively. Relative risks were greatest for high-grade serous, mucinous and ‘other epithelial’ histotypes. Relative risks were attenuated for case FDRs, but not for SDRs or TDRs, from 2005 onwards, consistent with the timing of recommendations for prophylactic surgery.

Conclusion

Familial risk of epithelial ovarian cancer extends to TDRs, especially for high-grade serous and mucinous histotypes. Distant relatives share genes but minimal environment, highlighting the importance of germline inherited genetics in ovarian cancer aetiology. Increased ovarian cancer risk in distant relatives has implications for counselling and recommendations for prophylactic surgeries that, from our data, appear only to reach FDRs.
Effect of hydraulic conductivity and impeded drainage on the liquefaction potential of gravelly soils
Authors: Roy Jashod , Rollins Kyle M.
Published: May 2022

Investigating the role of sand and fines content and in situ drainage conditions in governing the hydraulic conductivity of gravelly deposits is highly important to characterize the liquefaction potential of gravelly soil. In this study, a variation of hydraulic conductivity with sand content has been empirically obtained based on the existing gravel liquefaction case histories. It is found that the hydraulic conductivity of a soil matrix having more than about 20%–30% sand content by mass is low enough to cause liquefaction without the presence of any impervious confining layer. In addition, a numerical study has been performed using the commercial software FEQDrain to study pore pressure generation in gravelly soil at a variety of relative densities and hydraulic conductivities with and without an impermeable cap layer when subjected to a variety of earthquake loadings. For both unconfined and confined condition, excess pore pressure ratios consistently increase with a decrease in hydraulic conductivity ( k) and relative density ( Dr). Excess pore pressure ratio is correlated with hydraulic conductivity, soil compressibility, and cyclic stress ratio (CSR). For the confined condition, pore pressure in the gravel layer is primarily governed by the overlying cap layer and even a sandy cap layer instead of highly impervious clay layer can cause liquefaction.
Causal structure of singularity in non-spherical gravitational collapse
Authors: Dey Dipanjan , Joshi Pankaj S. , Mosani Karim , Vertogradov Vitalii
Published: May 2022

We investigate here the final state of gravitational collapse of a non-spherical and non-marginally bound dust cloud as modeled by the Szekeres spacetime. We show that a directionally globally naked singularity can be formed in this case near the collapsing cloud boundary and not at its geometric center, as is typically the case for a spherical gravitational collapse. This singularity is a strong curvature naked singularity in the sense of Tipler criterion on gravitational strength. The null geodesics escaping from the singularity would be less scattered in this case in certain directions since the singularity is close to the boundary of the cloud, as is the case in the current scenario. The physical implications are pointed out.
EH-DPD: a dissipative particle dynamics approach to electrohydrodynamics
Authors: Gubbiotti Alberto , Chinappi Mauro , Casciola Carlo Massimo
Published: May 2022

Electrohydrodynamics is crucial in many nanofluidic and biotechnological applications. In such small scales, the complexity due to the coupling of fluid dynamics with the dynamics of ions is increased by the relevance of thermal fluctuations. Here, we present a mesoscale method based on the Dissipative Particle Dynamics (DPD) model of the fluid. Two scalar quantities, corresponding to the number of positive and negative ions carried by each DPD particle, are added to the standard DPD formulation. We introduced a general framework that, given the definition of the free-energy of the DPD particle, allows to derive a fluctuation-dissipation relation and the expression for ionic fluxes between the DPD particles. This provides a link between the dynamics of the system and its equilibrium properties. The model is then validated simulating a planar electroosmotic flow for the cases of overlapping and non overlapping electric double layers. It is shown that using a Van der Waals equation of state the effect of ionic finite size can be accounted, leading to significant effects on the concentration and velocity profiles with respect to the ideal solution case.

Graphic abstract
Measuring the stability of fundamental constants with a network of clocks
Authors: Barontini G. , Blackburn L. , Boyer V. , Butuc-Mayer F. , Calmet X. , Crespo López-Urrutia J. R. , Curtis E. A. , Darquié B. , Dunningham J. , Fitch N. J. , Forgan E. M. , Georgiou K. , Gill P. , Godun R. M. , Goldwin J. , Guarrera V. , Harwood A. C. , Hill I. R. , Hendricks R. J. , Jeong M. , Johnson M. Y. H. , Keller M. , Kozhiparambil Sajith L. P. , Kuipers F. , Margolis H. S. , Mayo C. , Newman P. , Parsons A. O. , Prokhorov L. , Robertson B. I. , Rodewald J. , Safronova M. S. , Sauer B. E. , Schioppo M. , Sherrill N. , Stadnik Y. V. , Szymaniec K. , Tarbutt M. R. , Thompson R. C. , Tofful A. , Tunesi J. , Vecchio A. , Wang Y. , Worm S.
Published: May 2022

The detection of variations of fundamental constants of the Standard Model would provide us with compelling evidence of new physics, and could lift the veil on the nature of dark matter and dark energy. In this work, we discuss how a network of atomic and molecular clocks can be used to look for such variations with unprecedented sensitivity over a wide range of time scales. This is precisely the goal of the recently launched QSNET project: A network of clocks for measuring the stability of fundamental constants. QSNET will include state-of-the-art atomic clocks, but will also develop next-generation molecular and highly charged ion clocks with enhanced sensitivity to variations of fundamental constants. We describe the technological and scientific aims of QSNET and evaluate its expected performance. We show that in the range of parameters probed by QSNET, either we will discover new physics, or we will impose new constraints on violations of fundamental symmetries and a range of theories beyond the Standard Model, including dark matter and dark energy models.
DOES ACCOUNTING COMPARABILITY MATTER TO THE EFFICIENCY OF A FIRM’S INVESTMENT? EVIDENCE FROM CHINA’S A-SHARE MARKET
Authors: LIN ZHENXING , WANG JINGRAN , HUANG CHINTAN , CHEN LIN , LI PEIGONG
Published: May 2022

This study aims to investigate the role of accounting comparability in firm investment efficiency of firms in China. Using a sample of listed firms in China’s A-share market from 2005 to 2016, this study empirically categorizes the firms into two groups based on overinvestment and underinvestment. After implementing several tests including those for collinearity and heteroskedasticity, the primary results of the empirical models show that accounting comparability can only improve the efficiency of a company’s investment in terms of reducing the overinvestment and increasing the underinvestment through the impact of a financing constraint on the overinvestment and underinvestment. This study thus suggests that the Chinese authorities should take steps to ensure that firms increase the extent of their accounting comparability with other firms, thereby making their accounting statements more comparable not only in the same industry, but also in different industries in accordance with the official accounting regulations and by adopting the same definitions for accounting indicators.
PROMOTING COOPERATION IN A PUBLIC GOOD EXPERIMENT THROUGH OSTRACISM AS A PUNISHMENT MECHANISM
Authors: JARUNGRATTANAPONG RAWADEE
Published: May 2022

Ostracism is one form of real-life punishment mechanism to penalize uncooperative individuals in many societies. This paper aims to test whether ostracism enhances cooperation in the public good experiment by allowing group members to expel others based on the majority voting rule. The study also employed the modified public good experiment to categorize the contributors. The results showed that introducing ostracism increases contribution level by about 45 percentage points on average. However, some participants punished other members, even they contributed less than others or so-called anti-social punishment, suggesting that a third-party punishment may be another solution to sustain cooperation.
SPILLOVERS OF GLOBAL LIQUIDITY AND MONETARY POLICY DIVERGENCE FROM ADVANCED ECONOMIES TO VIETNAM
Authors: LE CHAU , VO XUAN VINH , MULLINEUX ANDY , NGUYEN HUYEN
Published: May 2022

This paper studies the spillovers of global liquidity and monetary policy divergence from advanced economies to Vietnam. Applying the structural Bayesian Vector Auto-Regressive model with Sims–Zha prior distribution, we find that unconventional monetary policy shocks of major central banks led to a reduction in inflation and short-term interest rate as well as an appreciation of local currency in Vietnam. However, market liquidity provided by surge in the cross-border credit flow led to a temporary upward pressure on inflation, interest and foreign exchange rates. Both types of global liquidity caused an insignificant effect on stock price which evidence the dominance of traditional interest rate and bank-lending over asset price channels in Vietnam. When disintegrating the effects among the monetary shocks from the US, European Union and Japan, the empirical result reveals some evidence of contradictory effects. Accordingly, GDP decreased after Fed’s asset purchase while it slightly increased following the same action from European Central Bank. Quantitative easing shocks also caused a depreciation in USD and Euro, resulting in a decrease in foreign exchange rate but large-scale asset purchase from the Bank of Japan is translated into an upward trend in the exchange rate.
Low Complexity Multiplierless Welch Estimator Based on Memory-Based FFT
Authors: Sadaghiani AbdolVahab Khalili , Sheikhaei Samad , Forouzandeh Behjat
Published: May 2022

This paper proposes a novel hardware efficient low power Welch power spectral density (PSD) estimator. The presented multiplier-less hardware uses a combined coefficient selection and shift-and-add implementation (CCSSI) unit in order to prevent multiplications in FFT computation. Two filtering operations, which are implemented in folded architecture, are utilized. The micro-rotation resources of the CCSSI unit can be shared with estimator’s modules simultaneously. The proposed architecture is a nonparametric estimator that operates based on a modified, memory-based, 128-point scalable radix-22 FFT processor. It uses bidirectional fractional delay filter to estimate half delay sample in merging two FFTs. Using modified safe-scaling, the final output would be valid, without any averaging operation. Another important feature of the proposed method is its capability of operating in short word lengths (WL). Artix-7, as an ideal option for DSP applications, is the utilized FPGA in this research. As results demonstrate, the hardware has a high capability in operating in short WLs which results in high performance in low-power applications.
Leaf Disease Classification in Smart Agriculture Using Deep Neural Network Architecture and IoT
Authors: Ramana Kadiyala , Aluvala Rajanikanth , Kumar Madapuri Rudra , Nagaraja G. , Krishna Akula Vijaya , Nagendra Pidugu
Published: May 2022

The Internet of Things (IoT) is bringing a new dimension to the smart farming market. This helps the user to collect the data from the agricultural fields in real time and move it to remote areas for processing. With the available sensor data and the image taken from the fields, automated disease prediction is possible. Deep neural network is used for classification of disease using the leaf images. Agriculture is the backbone of our country, but our output is poor when compared to the global standards due to lack of using technologies in the fields. In this work, various sensors like humidity sensor, pH level monitoring sensor, Temperature sensor, and Soil moisture sensor are used in the agricultural fields for collecting the real-time data. Multiple Sensors are installed in various locations of farms with one common controller Raspberry PI 3 module (RPI3), which was used to control all these sensors. Camera interfacing with RPI can be observed on leaf disease. Convolutional neural network architecture is used for leaf disease detection and classification. The accuracy of the disease classification system using convolutional neural network is 96% when the system is iterated for 50 epochs.
Investigation and Analysis of Power Performance Area (PPA) Cards of Digital Multiplier Architectures
Authors: Janwadkar Sudhanshu , Dhavse Rasika
Published: May 2022

The crucial role played by digital multipliers in VLSI system design makes it indispensable to study the PPA cards of digital multiplier architectures before tailoring multiplier architecture into such systems. Therefore, in this work, we present a detailed investigation and analysis of PPA cards of popular digital multiplier architectures, for various wordlengths. Each multiplier has been implemented on Artix-7 FPGA xc7a200tfbg676-2 and analyzed using Xilinx Vivado Design Suite 2019.2. A major contribution in this paper is the study of energy profiles of the architectures, not focused on in the earlier literature. This study compares their device utilization, timing parameters, power consumption, and energy profiles. Results indicate that Dadda Tree Multiplier and Wallace Tree Multiplier (460 slices and 557 slices, respectively, for [Formula: see text] bits) are undoubtedly the least slices consuming fast multipliers, but their power consumption and energy density are high as well. For 32-bit implementation, Vedic Multiplier consumes 48.9% lower power than Dadda Tree Multiplier, while the latter occupies 30.42% lesser slices. The speed of the Vedic Multiplier is in close proximity with the tree multipliers. The energy density of Vedic Multiplier (0.3[Formula: see text]nJ/slice) is much lower than that of Dadda Tree Multiplier (0.77[Formula: see text]nJ/slice).
Event-Triggered Neural Network Control for Uncertain Nonlinear Systems Without State Observer
Authors: Hu Hui , Wang Yuebiao , Yi Wei , Li Yang , Yan Jiande , Xiao Wei , Yuan Junqi
Published: May 2022

A robust approximation-based event-triggered control method is presented for single input single output (SISO) nonlinear continuous-time systems with unmeasurable states and external disturbance. In the whole system, just one neural network (NN) is designed to approximate the unknown part in the controller, and output errors are directly used to construct the system controller and event-triggered mechanism to relieve the burden of system communication. The controller with a simple structure is easier to be realized in practical engineering. The system control signals and adaptive parameters are updated only if the event trigger condition is met, and this way further reduces the waste of network resources caused by frequent system sampling. The application of stability theory of Lyapunov proves that the weight estimation of the NN and tracking errors are ultimate and uniform boundedness, and the efficacy of the proposed scheme is verified with numerical results on a robot.
Concordance maps in HFK−
Authors: Tovstopyat-Nelip Lev
Published: May 2022

We show that a decorated knot concordance [Formula: see text] from [Formula: see text] to [Formula: see text] induces an [Formula: see text]-module homomorphism [Formula: see text] which preserves the Alexander and absolute [Formula: see text]-Maslov gradings. Our construction generalizes the concordance maps induced on [Formula: see text] studied by Juhász and Marengon [Concordance maps in knot Floer homology, Geom. Topol. 20 (2016) 3623–3673], but uses the description of [Formula: see text] as a direct limit of maps between sutured Floer homology groups discovered by Etnyre et al. [Sutured Floer homology and invariants of Legendrian and transverse knots, Geom. Topol. 21 (2017) 1469–1582].
Targeting the SARS-CoV-2 Main Protease: In Silico Study Contributed to Exploring Potential Natural Compounds as Candidate Inhibitors
Authors: Ounissi Mourad , Rachedi Fatma Zohra
Published: May 2022

The SARS-CoV-2 main protease (Mpro) is one of the essential therapeutic keys of the COVID-19, which ensures the replication of the virus in the host cells, causing tissue damage, for this reason, we accelerate the research of potential natural compounds that could inhibit this enzyme or used as a scaffold to generate a series of optimized and potent inhibitors. In silico study was performed. This study was started with the generation and validation of a structure-based pharmacophore hypothesis that is used to screen a chemical library containing 99,049 natural compounds extracted, filtered, and cleaned from the Chinese universal natural products database (UNPD), the screening process using the pharmacophore hypothesis and the molecular docking yielded 15 hits. These hits were ranked depending on their binding [Formula: see text], as a result, the two compounds UNPD90246 and UNPD221225 exhibited higher binding affinity to the catalytic cavity of the Mpro interacting with important amino acids which play a crucial role in the enzyme catalysis, on the other hand, the two complexes UNPD90246/5R82 and UNPD221225/5R82 subjected to the molecular dynamic simulation show very good stability along the trajectory of the simulation as revealed by the calculated RMSD, RMSF, rGyr, SASA as well as the RMSF of the protein and the potential energy. In addition, the in silico evaluation of some drug-like and pharmacokinetic (ADMET) properties, revealed in general satisfactory prediction results for almost all compounds, however, some compounds require optimization steps to improve their weakness, regarding pharmacokinetic properties such as metabolism and toxicity.
Exploration of Binding Interaction of β-1,3-D-Glucan and Patulin by Molecular Dynamics Simulation Study
Authors: Wang Yaxue , Yue Tianli , Yuan Yahong
Published: May 2022

Patulin (PAT) contaminant in apple juice has attracted extensive attention. As a biosorbent, [Formula: see text]-1,3-D-glucan shows great advantages in removing toxic contaminants. The aim of this study was to reveal the adsorption mechanisms of PAT by [Formula: see text]-1,3-D-glucan. Four [Formula: see text]-1,3-D-glucans with different number of side chains: curdlan, a hypothetical glucan, schizophyllan (SPG) and lentinan were simulated. Performance of molecular docking was observed to predict the binding mode and affinity. The most potential compounds were performed molecular dynamics (MD) simulation. The results show that the interaction between [Formula: see text]-1,3-D-glucan and PAT is driven by steric complementarity, intermolecular H-bond and Pi–Sigma interaction. SPG has a large internal helical space to facilitate the insertion of PAT into the helix, and has relatively strong interaction with PAT. The side and main chains form a cavity to wrap PAT inside the helix. Furthermore, the binding free energy calculation was carried out using Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) approach. SPG showed high negative [Formula: see text] value. Structural and energetic analyses demonstrated the adsorption characteristics of the four [Formula: see text]-1,3-D-glucans. SPG is the most promising adsorbent for PAT. The side chain plays a major role in the adsorption process of the [Formula: see text]-1,3-D-glucans. It provides a basis for the development of [Formula: see text]-1,3-D-glucan as PAT adsorbent.
Utility-aware and Privacy-preserving Trajectory Synthesis Model that Resists Social Relationship Privacy Attacks
Authors: Zheng Zhirun , Li Zhetao , Li Jie , Jiang Hongbo , Li Tong , Guo Bin
Published: May 2022

For academic research and business intelligence, trajectory data has been widely collected and analyzed. Releasing trajectory data to a third party may lead to serious privacy leakage, which has spawned considerable researches on trajectory privacy protection technology. However, existing work suffers from several shortcomings. They either focus on point-based location privacy, ignoring the spatio-temporal correlations among locations within a trajectory, or they protect the privacy of each user separately without considering privacy leakage of the social relationship between trajectories of different users. Besides, they fail to balance privacy protection and data utility. Motivated by these limitations, in this article, we propose
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-Trajectory, which is a utility-aware and privacy-preserving trajectory synthesis model that Resists social relationship privacy attacks. Specifically, we first develop a time-dependent Markov chain based on an adaptive spatio-temporal discrete grid to efficiently and accurately capture human mobility behavior. Then, we propose three mobility feature metrics from spatio-temporal, semantic, and social dimensions. On the basis of the metrics, we construct a bi-level optimization problem to accomplish the utility-aware and privacy-preserving trajectory synthesizing. The upper-level objective guarantees data utility and the lower-level optimization problems (or upper-level constraints) provides two-layer privacy protection for
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-Trajectory, i.e., resisting location inference attacks and social relationship privacy attacks. We conduct extensive experiments on large-scale real-world datasets loc-Gowalla and loc-Brightkite. The experimental results demonstrate the effectiveness and robustness of
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Trajectory. Compared with the baseline models,
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Trajectory achieves between 7.8% and 23.8% performance improvement in resisting social relationship privacy attacks and achieves at least 5.19% improvement regarding data utility.
On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests–A Mixed-Methods Study of 10 Large Open-Source Projects
Authors: Khatoonabadi Sayedhassan , Costa Diego Elias , Abdalkareem Rabe , Shihab Emad
Published: May 2022

Pull-based development has enabled numerous volunteers to contribute to open-source projects with fewer barriers. Nevertheless, a considerable amount of pull requests (PRs) with valid contributions are abandoned by their
contributors
, wasting the effort and time put in by both the contributors and maintainers. To better understand the underlying dynamics of contributor-abandoned PRs, we conduct a mixed-methods study using both quantitative and qualitative methods. We curate a dataset consisting of 265,325 PRs including 4,450 abandoned ones from ten popular and mature GitHub projects and measure 16 features characterizing PRs, contributors, review processes, and projects. Using statistical and machine learning techniques, we find that complex PRs, novice contributors, and lengthy reviews have a higher probability of abandonment and the rate of PR abandonment fluctuates alongside the projects’ maturity or workload. To identify why contributors abandon their PRs, we also manually examine a random sample of 354 abandoned PRs. We observe that the most frequent abandonment reasons are related to the obstacles faced by contributors, followed by the hurdles imposed by maintainers during the review process. Finally, we survey the top core maintainers of the studied projects to understand their perspectives on dealing with PR abandonment and on our findings.
ForSense: Accelerating Online Research Through Sensemaking Integration and Machine Research Support
Authors: Ramos Gonzalo , Rachatasumrit Napol , Suh Jina , Ng Rachel , Meek Christopher
Published: May 2022

Online research is a frequent and important activity people perform on the Internet, yet current support for this task is basic, fragmented and not well integrated into web browser experiences. Guided by sensemaking theory, we present ForSense, a browser extension for accelerating people’s online research experience. The two primary sources of novelty of ForSense  are the integration of multiple stages of online research and providing machine assistance to the user by leveraging recent advances in neural-driven machine reading. We use ForSense  as a design probe to explore (1) the benefits of integrating multiple stages of online research, (2) the opportunities to accelerate online research using current advances in machine reading, (3) the opportunities to support online research tasks in the presence of imprecise machine suggestions, and (4) insights about the behaviors people exhibit when performing online research, the pages they visit, and the artifacts they create. Through our design probe, we observe people performing online research tasks, and see that they benefit from ForSense’s integration and machine support for online research. From the information and insights we collected, we derive and share key recommendations for designing and supporting imprecise machine assistance for research tasks.
Fairness in Ranking, Part I: Score-Based Ranking
Authors: Zehlike Meike , Yang Ke , Stoyanovich Julia
Published: May 2022

In the past few years, there has been much work on incorporating fairness requirements into algorithmic rankers, with contributions coming from the data management, algorithms, information retrieval, and recommender systems communities. In this survey, we give a systematic overview of this work, offering a broad perspective that connects formalizations and algorithmic approaches across sub-fields. An important contribution of our work is in developing a common narrative around the value frameworks that motivate specific fairness-enhancing interventions in ranking. This allows us to unify the presentation of mitigation objectives and of algorithmic techniques to help meet those objectives or identify trade-offs.

In this first part of this survey, we describe four classification frameworks for fairness-enhancing interventions, along which we relate the technical methods surveyed in this article, discuss evaluation datasets, and present technical work on fairness in score-based ranking. In the second part of this survey, we present methods that incorporate fairness in supervised learning, and also give representative examples of recent work on fairness in recommendation and matchmaking systems. We also discuss evaluation frameworks for fair score-based ranking and fair learning-to-rank, and draw a set of recommendations for the evaluation of fair ranking methods.
Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems
Authors: Zehlike Meike , Yang Ke , Stoyanovich Julia
Published: May 2022

In the past few years, there has been much work on incorporating fairness requirements into algorithmic rankers, with contributions coming from the data management, algorithms, information retrieval, and recommender systems communities. In this survey, we give a systematic overview of this work, offering a broad perspective that connects formalizations and algorithmic approaches across subfields. An important contribution of our work is in developing a common narrative around the value frameworks that motivate specific fairness-enhancing interventions in ranking. This allows us to unify the presentation of mitigation objectives and of algorithmic techniques to help meet those objectives or identify trade-offs.

In the first part of this survey, we describe four classification frameworks for fairness-enhancing interventions, along which we relate the technical methods surveyed in this article, discuss evaluation datasets, and present technical work on fairness in score-based ranking. In the second part of this survey, we present methods that incorporate fairness in supervised learning, and also give representative examples of recent work on fairness in recommendation and matchmaking systems. We also discuss evaluation frameworks for fair score-based ranking and fair learning-to-rank, and draw a set of recommendations for the evaluation of fair ranking methods.
Preparation of Porous Fe–N–C Composite from Cotton Straw and Its Supercapacitor Performance
Authors: Song Yanfang , Wu Jinxiong , Zheng Jiliang , Sun Yiwei , Ivanets Andrei , Du Guangming , Su Xintai
Published: May 2022

The doping of multiple heteroatoms can improve the electrochemical properties of carbon substrates. However, in existing studies, carbon, iron and nitrogen sources are generally mixed directly and then pyrolyzed for secondary activation. This tends to form aggregates of metal particles or metal oxides and requires the consumption of large amounts of alkali and energy. Therefore, there is an urgent need to develop an environmentally friendly technology capable of uniformly doping iron and nitrogen into carbon materials. In this work, porous Fe–N–C composites were prepared at 600 °C using potassium humate (HA-K) obtained from cotton straw by low-temperature pyrolysis as the carbon source, and urea-iron complexes formed by the pre-coordination of urea and Fe as the iron and nitrogen sources. In the absence of secondary activation, the best sample Fe-NHPC-2 had a good mesoporous structure with high specific surface area (889. 01 m2 g−1). It had a high specific capacitance of 256.8 F g−1 at a current density of 0.5 A g−1. The capacitance retention was 92.6% after 10,000 cycles at a current density of 10 A g−1. In the symmetric supercapacitor application, the energy density reached 33.16 Wh kg−1 when the power density was 600.2 W kg−1.