bluuebunny/crossref_metadata_2025_split huggingface dataset:
VEGA is an interpretable generative model for inferring biological network activity in single-cell transcriptomics
Authors: Seninge Lucas , Anastopoulos Ioannis , Ding Hongxu , Stuart Joshua 
Published: September 2021

AbstractDeep learning architectures such as variational autoencoders have revolutionized the analysis of transcriptomics data. However, the latent space of these variational autoencoders offers little to no interpretability. To provide further biological insights, we introduce a novel sparse Variational Autoencoder architecture, VEGA (VAE Enhanced by Gene Annotations), whose decoder wiring mirrors user-provided gene modules, providing direct interpretability to the latent variables. We demonstrate the performance of VEGA in diverse biological contexts using pathways, gene regulatory networks and cell type identities as the gene modules that define its latent space. VEGA successfully recapitulates the mechanism of cellular-specific response to treatments, the status of master regulators as well as jointly revealing the cell type and cellular state identity in developing cells. We envision the approach could serve as an explanatory biological model for development and drug treatment experiments.
Restructuring highly electron-deficient metal-metal oxides for boosting stability in acidic oxygen evolution reaction
Authors: Liu Xinghui , Xi Shibo , Kim Hyunwoo , Kumar Ashwani , Lee Jinsun , Wang Jian , Tran Ngoc Quang , Yang Taehun , Shao Xiaodong , Liang Mengfang , Kim Min Gyu , Lee Hyoyoung 
Published: September 2021

AbstractThe poor catalyst stability in acidic oxidation evolution reaction (OER) has been a long-time issue. Herein, we introduce electron-deficient metal on semiconducting metal oxides-consisting of Ir (Rh, Au, Ru)-MoO3 embedded by graphitic carbon layers (IMO) using an electrospinning method. We systematically investigate IMO’s structure, electron transfer behaviors, and OER catalytic performance by combining experimental and theoretical studies. Remarkably, IMO with an electron-deficient metal surface (Irx+; x > 4) exhibit a low overpotential of only ~156 mV at 10 mA cm−2 and excellent durability in acidic media due to the high oxidation state of metal on MoO3. Furthermore, the proton dissociation pathway is suggested via surface oxygen serving as proton acceptors. This study suggests high stability with high catalytic performance in these materials by creating electron-deficient surfaces and provides a general, unique strategy for guiding the design of other metal-semiconductor nanocatalysts.
Eight-hours conventional versus adaptive deep brain stimulation of the subthalamic nucleus in Parkinson’s disease
Authors: Bocci Tommaso , Prenassi Marco , Arlotti Mattia , Cogiamanian Filippo Maria , Borellini Linda , Moro Elena , Lozano Andres M. , Volkmann Jens , Barbieri Sergio , Priori Alberto , Marceglia Sara 
Published: September 2021

AbstractThis study compares the effects on motor symptoms between conventional deep brain stimulation (cDBS) and closed-loop adaptive deep brain stimulation (aDBS) in patients with Parkinson’s Disease. The aDBS stimulation is controlled by the power in the beta band (12–35 Hz) of local field potentials recorded directly by subthalamic nucleus electrodes. Eight subjects were assessed in two 8-h stimulation sessions (first day, cDBS; second day, aDBS) with regular levodopa intake and during normal daily activities. The Unified Parkinson’s Disease Rating Scale (UPDRS) part III scores, the Rush scale for dyskinesias, and the total electrical energy delivered to the tissues per second (TEEDs) were significantly lower in the aDBS session (relative UPDRS mean, cDBS: 0.46 ± 0.05, aDBS: 0.33 ± 0.04, p = 0.015; UPDRS part III rigidity subset mean, cDBS: 2.9143 ± 0.6551 and aDBS: 2.1429 ± 0.5010, p = 0.034; UPDRS part III standard deviation cDBS: 2.95, aDBS: 2.68; p = 0.047; Rush scale, cDBS 2.79 ± 0.39 versus aDBS 1.57 ± 0.23, p = 0.037; cDBS TEEDs mean: 28.75 ± 3.36 µj s−1, aDBS TEEDs mean: 16.47 ± 3.33, p = 0.032 Wilcoxon’s sign rank test). This work further supports the safety and effectiveness of aDBS stimulation compared to cDBS in a daily session, both in terms of motor performance and TEED to the patient.
Application of dielectric barrier discharge for improving food shelf life and reducing spoilage
Authors: Roy Subrata , Choudhury Bhaswati , Johnson Judith , Schindler-Tyka Alexander 
Published: September 2021

AbstractDielectric Barrier Discharge (DBD) based ozone therapy is an attractive non-thermal, additive-free and environment-friendly alternative to traditional food processing technologies. Its practical application is dependent on economical ozone generation and optimum ozone dosage. This study investigates the one-time and periodic application of a compact (48 cu. cm), lightweight (55 g), low power, low temperature, DBD ozone generator for treatment of spoilage inocula prepared from combinations of spoiled green beans, grape tomatoes, lettuce and strawberries. A one-time exposure of 126–136 ppm of average ozone concentration produced by the DBD generator over 3 min and 15 min resulted in at least 1 and 4 log reduction, respectively, in microbial colonies present in the spoilage inocula. Daily exposure of 128.7 ppm average ozone concentration over 3 min under similar conditions showed that inhibition through periodic exposure can successfully inhibit the growth of both bacteria and mold species with at least 5 log reduction of microbial colonies. Visual inspection of whole fruits and vegetables with similar 3-min daily exposure showed the potential of ozone therapy to at least double the shelf-life of food products. For the daily exposures, energy required by the DBD ozone generator was calculated as 0.39 $$\pm $$
±
0.06 kJ/day.
Assessment of the structural and functional characteristics of human mesenchymal stem cells associated with a prolonged exposure of morphine
Authors: Carano Francesco , Teti Gabriella , Ruggeri Alessandra , Chiarini Francesca , Giorgetti Arianna , Mazzotti Maria C. , Fais Paolo , Falconi Mirella 
Published: September 2021

AbstractThe discovery of the expression of opioid receptors in the skin and their role in orchestrating the process of tissue repair gave rise to questions regarding the potential effects of clinical morphine treatment in wound healing. Although short term treatment was reported to improve tissue regeneration, in vivo chronic administration was associated to an impairment of the physiological healing process and systemic fibrosis. Human mesenchymal stem cells (hMSCs) play a fundamental role in tissue regeneration. In this regard, acute morphine exposition was recently reported to impact negatively on the functional characteristics of hMSCs, but little is currently known about its long-term effects. To determine how a prolonged treatment could impair their functional characteristics, we exposed hMSCs to increasing morphine concentrations respectively for nine and eighteen days, evaluating in particular the fibrogenic potential exerted by the long-term exposition. Our results showed a time dependent cell viability decline, and conditions compatible with a cellular senescent state. Ultrastructural and protein expression analysis were indicative of increased autophagy, suggesting a relation to a detoxification activity. In addition, the enhanced transcription observed for the genes involved in the synthesis and regulation of type I collagen suggested the possibility that a prolonged morphine treatment might exert its fibrotic potential risk, even involving the hMSCs.
Audible acoustics from low-magnitude fluid-induced earthquakes in Finland
Authors: Lamb Oliver D. , Lees Jonathan M. , Malin Peter E. , Saarno Tero 
Published: September 2021

AbstractEarthquakes are frequently accompanied by public reports of audible low-frequency noises. In 2018, public reports of booms or thunder-like noises were linked to induced earthquakes during an Engineered Geothermal System project in the Helsinki Metropolitan area. In response, two microphone arrays were deployed to record and study these acoustic signals while stimulation at the drill site continued. During the 11 day deployment, we find 39 earthquakes accompanied by possible atmospheric acoustic signals. Moment magnitudes of these events ranged from $$-0.07$$

-
0.07

to 1.87 with located depths of 4.8–6.5 km. Analysis of the largest event revealed a broadband frequency content, including in the audible range, and high apparent velocities across the arrays. We conclude that the audible noises were generated by local ground reverberation during the arrival of seismic body waves. The inclusion of acoustic monitoring at future geothermal development projects will be beneficial for studying seismic-to-acoustic coupling during sequences of induced earthquakes.
Enhancing esophageal repair with bioactive bilayer mesh containing FGF
Authors: Cesur Ozkan , Tanir Tugba Endogan , Celepli Pinar , Ozarslan Fatma , Hucumenoglu Sema , Karaibrahimoglu Adnan , Hasirci Nesrin 
Published: September 2021

AbstractWe aimed to prepare a bioactive and biodegradable bilayer mesh formed by fibroblast growth factor (FGF) loaded gelatin film layer, and poly ε-caprolactone (PCL) film layer, and to investigate its treatment efficacy on esophageal anastomosis. It is envisaged that the bioactive mesh in in vivo model would improve tissue healing in rats. The full thickness semicircular defects of 0.5 × 0.5 cm2 were created in anterior walls of abdominal esophagus. The control group had abdominal esophagus isolated with distal esophageal blunt dissection, and sham group had primary anastomosis. In the test groups, the defects were covered with bilayer polymeric meshes containing FGF (5 μg/2 cm2), or not. All rats were sacrificed for histopathology investigation after 7 or 28 days of operation. The groups are coded as FGF(−)-7th day, FGF(+)-7th day, and FGF(+)-28th day, based on their content and operation day. Highest burst pressures were obtained for FGF(+)-7th day, and FGF(+)-28th day groups (p < 0.005) and decreased inflammation grades were observed. Submucosal and muscular collagen deposition scores were markedly increased in these groups compared to sham and FGF(−)-7th day groups having no FGF (p = 0.002, p = 0.001, respectively). It was proved that FGF loaded bioactive bilayer mesh provided effective repair, reinforcement and tissue healing of esophageal defects.
An elastic fiber based on phononic crystals
Authors: Motaei Farzaneh , Bahrami Ali 
Published: September 2021

AbstractIn this study, a novel elastic phononic crystal fiber has been presented for the first time. This proposed structure can expand the sonic communications field, significantly. In order to realize the elastic fiber performance, solid–solid phononic crystal has been utilized. The phononic crystal structure operates as cladding in surroundings and central region acts as core of fiber by elimination of rods. Incident acoustic waves with transverse polarization have confined and propagated in the core region of the phononic crystal fiber. Two types of phononic crystal fiber with different core radii have been investigated. Incident elastic waves can confine in the core region with confinement factor higher than 500. Also, longitudinal losses have been achieved low and equal to 0.35 dB/km.
Linking the enhanced deep NO oxidation of a ferroelectric K0.5Bi0.5TiO3 nanowire photocatalyst to its spontaneous polarization and oxygen vacancies
Authors: Liang Qingrong , Li Guian , Rao Fei , Zheng Guozhong , Ma Haoxuan , Li Shiping , Hojamberdiev Mirabbos , Wang Qizhao , Zhu Gangqiang 
Published: September 2021

The mechanism of NOx photo-oxidation and the pathway of photogenerated charge carries mechanism over K0.5Bi0.5TiO3 photocatalyst.
Halogenated sodium/lithium monocarba-closo-decaborates: syntheses, characterization, and solid-state ionic conductivity
Authors: Li Shouhu , Qiu Pengtao , Kang Jia-Xin , Shi Zhenpu , Zhang Yichun , Ma Yiming , Chen Xuenian 
Published: September 2021

A series of halogenated monocarba-closo-decaborates, M[closo-1-CHB9H8-6-X] (M = Na, Li; X = Br, I) and M[closo-1-CHB9H4-6,7,8,9,10-I5] (M = Na, Li) have been synthesized for investigating the influence of halogenation on the thermal stability, phase transition and ionic conductivity.
A two‐layer attack‐robust protocol for IoT healthcare security
Authors: Afsaneh Sharafi , Sepideh Adabi , Ali Movaghar , Salah Al‐Majeed 
Published: September 2021

AbstractThe majority of studies in the field of developing identification and authentication protocols for Internet of Things (IoT) used cryptographic algorithms. Using brain signals is also a relatively new approach in this field. EEG signal‐based authentication algorithms typically use feature extraction algorithms that require high processing time. On the other hand, the dynamic nature of the EEG signal makes its use for identification/authentication difficult without relying on feature extraction. This paper presents an EEG‐and fingerprint‐based two‐stage identification‐authentication protocol for remote healthcare, which is fast, robust, and multilayer‐based. A modified Euclidean distance pattern matching method is proposed to match the EEG signal in the identification stage due to its dynamic nature. The authentication stage is also an optimized method with the Genetic Algorithm (GA), which utilizes a modified Diffie–Hellman algorithm. Due to the vulnerability of the Diffie–Hellman algorithm to different types of attacks, the parameters used for this algorithm are extracted from the fingerprint and the EEG signal of the patient to provide a fast and robust authentication method. The proposed method is evaluated using data from patients with spinal cord injuries. Simulating results demonstrated high identification and authentication accuracy of the proposed method. Furthermore, it is extremely fast and efficient.
A stochastic framework for secure reconfiguration of active distribution networks
Authors: Ahmadi Seyed‐Alireza , Vahidinasab Vahid , Ghazizadeh Mohammad Sadegh , Giaouris Damian 
Published: September 2021

AbstractAutomatic reconfiguration is one of the key actions in self‐healing distribution networks. In these networks, after detecting and isolating the faulted portion, an automatic reconfiguration procedure is performed to restore the maximum possible affected loads without further interruptions during repair operations. This procedure becomes more complicated in the networks with integrated distributed generation units as they can bring security challenges for the reconfigured network after a fault event. To overcome these challenges, a stochastic framework is proposed here. In this framework, the reconfiguration procedure is conducted with a fast and reliable method which is based on the graph theory. Besides, the security challenges of utilizing distributed generations after an event are highlighted. Then, since a faulted network is more prone to subsequent faults, different actions of changing the distribution generations output power, preventing the insecure increment of short circuit capacity, and also considering the loadability improvement are proposed in the reconfiguration framework. Then in the final stage, the vulnerability of the distribution system to the uncertainties of load demand is resolved through a chance‐constrained programming‐based approach. To see the performance of the proposed stochastic framework, it is tested on a standard test system and the results prove its goodness and applicability for real distribution networks.
A comprehensive survey: Image deraining and stereo‐matching task‐driven performance analysis
Authors: Du Shuangli , Liu Yiguang , Zhao Minghua , Shi Zhenghao , You Zhenzhen , Li Jie 
Published: September 2021

AbstractDeraining has been attracting a lot of attention from researchers, and various methods have been proposed, especially deep‐networks are widely adopted in recent years. Their structures and learning become more and more complicated and diverse, making it difficult to analyze the contributions and improvements. In this paper, a comprehensive review for current rain removal methods is first provided to show their contributions. Specifically, they are reviewed in terms of handing rain streaks and rain mist. Second, besides evaluating their rain removal ability, they are also evaluated in terms of their impact on subsequent stereo‐matching task. To this end, a new deraining dataset is first prepared, called Rain‐Kitti2012 and Rain‐Kitti2015. They are created by adding rain part to clean image‐pairs in Kitti2012 and Kitti2015. By then, nine state‐of‐the‐art deraining methods are evaluated with full‐reference and no‐reference image quality assessment metrics. Furthermore, the blurriness and distortion types introduced during deraining are measured. Finally, three learning‐based stereo matching methods are compared, and they take the outputs of deraining methods as inputs. It is further discussed how derained images influence the accuracy of stereo matching, which can provide some insight for jointly handling rain removal and stereo matching.1: A comprehensive review for the current rain removal methods is provided. They are categorized into rain‐streak‐oriented and rain‐mist‐oriented approaches in terms of degradation type, and are categorized into model‐driven and data‐driven approaches in terms of methodology. 2: A new image deraining dataset is introduced, which is the first dataset that can be used to perform stereo‐matching‐driven evaluation for deraining methods. The dataset is created by adding rain part to clean images in KITTI2012 and KITTI2015. 3: We evaluate 9 deep learning based deraining methods with full‐reference and no‐ reference metrics. In addition, the types of distortions produced by these methods are discussed and measured quantitatively. And, the impact of 9 deraining methods on the subsequent stereo matching task is evaluated, which can provide some insight on how to design stereo matching task‐driven deraining methods.
Data gap decomposed by auxiliary modality for NIR‐VIS heterogeneous face recognition
Authors: Sun Rui , Shan Xiaoquan , Zhang Han , Gao Jun 
Published: September 2021

AbstractIn the dark scene at night, the face images captured by ordinary visible light (VIS) are generally poor quality and very dim, while the near‐infrared (NIR) can capture high definition and recognizable face images at night. The NIR‐VIS Heterogeneous face recognition has become a hot research field, which helps to build an all‐weather face recognition system. NIR‐VIS HFR is sophisticated because of the large visual difference between NIR images and VIS images. In order to reduce the difficulty of such cross‐modality invariant feature learning, this paper proposes a cross‐modality data gap decomposed by auxiliary modality method (DGD) for NIR‐VIS HFR. First, the brightness component (Y component) of VIS image YCbCr space is used as the auxiliary modality to decompose the cross‐modality data gap. The lightness component retained the structural information of VIS image and was similar to the colour information of NIR modality; in this way, the huge gap between the NIR data and the VIS data is decomposed into two smaller gaps, thus reducing the difficulty of network learning. Second, the data of the three modalities are input into the weight sharing network and training under the combined guidance of cross‐modality gap decomposition loss and intra‐modality gap loss; in this way, the modality invariant features can be learned faster and better. Extensive experiments were conducted on two commonly used datasets CASIA NIR‐VIS 2.0 and Oulu‐CASIA NIR‐VIS to evaluate DGD method. Experimental results indicate DGD method has competitive performance compared with the latest methods.
Identification of photovoltaic‐generation‐characteristic at real‐time conditions by improved single‐diode model
Authors: Nguyen Tuyen Duc , Le Thinh Viet , Fujita Goro 
Published: September 2021

AbstractThe dramatic penetration of sustainable energy systems, including photovoltaic (PV) systems, has profoundly affected the stability and the reliability of the power system. Hence, determining the generation characteristics of PV systems has been becoming a crucial task in planning and dispatching the power system. However, since the generation of PV systems is profoundly impacted by the weather conditions, especially the irradiance and the temperature, producing a PV model, which performs well at various conditions, has been a challenging task for years. In this paper, we present a model to determine the PV generation characteristics by obtaining the current‐voltage (I–V) curves of the single‐diode model. First, the three key points, including the open‐circuit point, the short‐circuit point, and the maximum power point, are estimated from the historical data based on an improved regression model. After that, a new algorithm is proposed, which ensures the model always converges at any temperature and irradiance conditions. The proposed model is validated by comparing with recently published models and the measured data from the National Renewable Energy Laboratory, USA. Compared to previous numerical models, the proposed model is capable of determining the generation characteristics of PV systems at anomaly conditions (anomalously low irradiance and anomalously high irradiance) with high accuracy and fast speed. The validated results demonstrate the accuracy and the reliability of the proposed model in determining the generation characteristics of PV modules at real‐time conditions.
Considerations on prediction horizon and dissipative losses for wave energy converters
Authors: Shahroozi Zahra , Göteman Malin , Engström Jens , Todalshaug Jørgen Hals 
Published: September 2021

AbstractThe non‐causal optimal control law for wave energy converters leads to a requirement of predicting waves and wave forces over a future horizon. Using examples of generic body shapes and oscillation modes, the authors show through computations of the velocity reference trajectory how the length of prediction horizon required to reach the maximum power output depends on the level of dissipative losses in the conversion chain . The sensitivity to noise is discussed, and so is the use of filtering to improve performance when the available prediction horizon is short or predictions are inaccurate . Considerations are also made for amplitude constraints and other effects encountered in a real system. With realistic assumptions for the level of dissipative losses, results indicate that the prediction horizon needed to approach the maximum achievable power output for real systems ranges from only a few seconds up to about half a wave period, which is shorter than that has generally been assumed earlier.