bluuebunny/crossref_metadata_2025 huggingface dataset:
Collecting women in geology: opening the international case of a Scottish ‘cabinétière’, Eliza Gordon Cumming (
c.
1798–1842)
Authors: Orr Mary
Published: June 2020

The double meanings of ‘case’ in the subtitle pinpoint the dual investigations of this chapter. It first puts the case for better understanding of women's contributions to ‘serious’ geology in international, as well as national, contexts by overtly collecting British women collectors in the field who contributed to French geological knowledge. It can then unpack the pivotal importance of women's geology collections and women collectors ‘at home’ in the establishment of new global subfields of geological work in the 1840s, despite more famous names being given national and international recognition for key discoveries. Our examination of the geology case in point – the collection and its expert collector, Lady Eliza Gordon Cumming – discloses her international geological expertise but also longer transnational heritage of women's scientific collecting practice. By proposing the French term ‘cabinétière’ to name its clearer status, this chapter investigates the implications of serious retrospective relabelling for geology when a woman discoverer-collector is restored and reconnected to her world collections.
Female students of geology in Victorian Dublin
Authors: Hegarty Susan
Published: June 2020

The science of geology began to thrive during the middle of the nineteenth century, with the expansion and consolidation of geological mapping of the Geological Survey of Great Britain and Ireland, and the foundation of geological societies across the islands of Britain and Ireland. As the desire for geological knowledge and understanding among the general public grew, so did the provision of lectures and courses open to the public. These public lecture series proved popular with a wide cross-section of men and women of Victorian Britain and Ireland.

This paper explores the provision of geological lectures by officers of the Geological Survey of Ireland through the Museum of Irish Industry in Dublin, and the women who took these courses during the 1850s and 1860s, and completed geological examinations for London's Science and Art Department in Dublin as a result of these lectures. It provides a glimpse into the scientific and, specifically, geological interests and activities of these women at a time when it was not possible for them to become members of the geological societies in the cities in which they lived.
Smart Diagnosis
Authors: Jiang Yizhang , Gu Xiaoqing , Ji Dingcheng , Qian Pengjiang , Xue Jing , Zhang Yuanpeng , Zhu Jiaqi , Xia Kaijian , Wang Shitong
Published: June 2020

To effectively identify electroencephalogram (EEG) signals in multiple-source domains, a multiple-source transfer learning-based Takagi–Sugeno–Kang (TSK) fuzzy system (FS), called MST-TSK, is proposed, which combines multiple-source transfer learning and manifold regularization (MR) learning mechanisms together into the TSK-FS framework. Specifically, the advantages of MST-TSK include the following: (1) by evaluating the significance of each source domain (SD), a flexible domain entropy-weighting index is presented; (2) using the theory of sample transfer learning, a reweighting strategy is presented to weigh the prediction of unknown samples in the target domain (TD) and the output of the source prediction functions; (3) by taking into account the MR term, the manifold structure of the TD is effectively maintained in the proposed system; and (4) by inheriting the interpretability of TSK-FS, MST-TSK displays good interpretability in identifying EEG signals that are understandable by humans (domain experts). The effectiveness of the proposed FS is demonstrated in several EEG multiple-source transfer learning tasks.
Proposal Complementary Action Detection
Authors: Zhu Suguo , Yang Xiaoxian , Yu Jun , Fang Zhenying , Wang Meng , Huang Qingming
Published: June 2020

Temporal action detection not only requires correct classification but also needs to detect the start and end times of each action accurately. However, traditional approaches always employ sliding windows or actionness to predict the actions, and it is different to train to model with sliding windows or actionness by end-to-end means. In this article, we attempt a different idea to detect the actions end-to-end, which can calculate the probabilities of actions directly through one network as one part of the results. We present PCAD, a novel proposal complementary action detector to deal with video streams under continuous, untrimmed conditions. Our approach first uses a simple fully 3D convolutional network to encode the video streams and then generates candidate temporal proposals for activities by using anchor segments. To generate more precise proposals, we also design a boundary proposal network to offer some complementary information for the candidate proposals. Finally, we learn an efficient classifier to classify the generated proposals into different activities and refine their temporal boundaries at the same time. Our model can achieve end-to-end training by jointly optimizing classification loss and regression loss. When evaluating on the THUMOS’14 detection benchmark, PCAD achieves state-of-the-art performance in high-speed models.
A New Transfer Function for Volume Visualization of Aortic Stent and Its Application to Virtual Endoscopy
Authors: Huang Chenxi , Lan Yisha , Zhang Guokai , Xu Gaowei , Jiang Landu , Zeng Nianyin , Tan Jenhong , Ng E. Y. K. , Cheng Yongqiang , Han Ningzhi , Ji Rongrong , Peng Yonghong
Published: June 2020

Aortic stent has been widely used in restoring vascular stenosis and assisting patients with cardiovascular disease. The effective visualization of aortic stent is considered to be critical to ensure the effectiveness and functions of the aortic stent in clinical practice. Volume rendering with ray casting has been used as an effective approach to enable the effective visualization of aortic stent. The volume rendering relies on the transfer function that converts the medical images into optical attributes including color and transparency. This article proposes a new transfer function, namely, the multi-dimensional transfer function, to provide additional transparency value of a voxel. The proposed approach using the additional transparency value effectively assists the distinguishing of tissues that have the same CT value. The transparency values are simultaneously determined by gray threshold and gray change threshold, which can recognize the unnecessary structures such as bones transparent. A series of experimental results demonstrate that the situation of aorta stent of a patient can be directly observed, and the angle of view can be switched arbitrarily. The proposed method provides a new way for the operation of a virtual endoscopy to reach the place of blood vessels that a traditional endoscopy fails to reach.
Augmenting DL with Adversarial Training for Robust Prediction of Epilepsy Seizures
Authors: Hussein Amir , Djandji Marc , Mahmoud Reem A. , Dhaybi Mohamad , Hajj Hazem
Published: June 2020

Epilepsy is a chronic medical condition that involves abnormal brain activity causing patients to lose control of awareness or motor activity. As a result, detection of pre-ictal states, before the onset of a seizure, can be lifesaving. The problem is challenging because it is difficult to discern between electroencephalogram signals in pre-ictal states versus signals in normal inter-ictal states. There are three key challenges that have not been addressed previously: (1) the inconsistent performance of prediction models across patients, (2) the lack of perfect prediction to protect patients from any episode, and (3) the limited amount of pre-ictal labeled data for advancing machine learning methods. This article addresses these limitations through a novel approach that uses adversarial examples with optimized tuning of a combined convolutional neural network and gated recurrent unit. Compared to the state of the art, the results showed an improvement of 3x in model robustness as measured in reduced variations and superior accuracy of the area under the curve, with an average increase of 6.7%. The proposed method also exhibited superior performance with other advances in the field of machine learning and customized for epilepsy prediction including data augmentation with Gaussian noise and multitask learning.
Network-level Design Space Exploration of Resource-constrained Networks-of-Systems
Authors: Zhao Zhuoran , Barijough Kamyar Mirzazad , Gerstlauer Andreas
Published: June 2020

Driven by recent advances in networking and computing technologies, distributed application scenarios are increasingly deployed on resource-constrained processing platforms. This includes networked embedded and cyber-physical systems as well as edge computing in mobile applications and the Internet of Things (IoT). In such resource-constrained Networks-of-Systems (NoS), computation and communication workloads need to be carefully co-optimized yet are tightly coupled. How to optimally partition and schedule application tasks among an appropriately designed NoS architecture requires a simultaneous consideration of design parameters from applications and processing platforms all the way to network configurations. Traditionally, however, systems and networks are designed in isolation and combined in an ad hoc manner, which ignores joint effects and optimization opportunities. To systematically explore and optimize NoS design spaces, a higher level of design abstraction on top of traditional system and network design is required.

In this article, we propose a novel network-level design methodology for resource-constrained NoS optimization and design space exploration. A key component in such a design flow is fast yet accurate network/system co-simulation to rapidly evaluate NoS parameters with high fidelity. We first introduce a novel NoS simulator (NoSSim) that integrates source-level simulation models of applications with a host-compiled system simulation platform and a reconfigurable network simulation backplane to accurately capture system and network interactions. The co-simulation platform is further combined with model generation tools and a multi-objective genetic search algorithm to provide a comprehensive and fully automated NoS design space exploration framework. Finally, we apply our network-level design flow on several state-of-art IoT/mobile design case studies. Results show that NoSSim can achieve more than 86% simulation accuracy on average as compared to a real-world edge device cluster, where sensitivities to various design parameters are faithfully captured with high fidelity. When applying our network-level design space exploration methodology, design decisions are automatically optimized, where non-obvious NoS configurations are discovered outperforming manually designed solutions by more than 45%.
Morphological Segmentation to Improve Crosslingual Word Embeddings for Low Resource Languages
Authors: Chimalamarri Santwana , Sitaram Dinkar , Jain Ashritha
Published: June 2020

Crosslingual word embeddings developed from multiple parallel corpora help in understanding the relationships between languages and improving the prediction quality of machine translation. However, in low resource languages with complex and agglutinative morphologies, inducing good-quality crosslingual embeddings becomes challenging due to the problem of complex morphological forms and rare words. This is true even for languages that share common linguistic structure. In our work, we have shown that performing a simple morphological segmentation upon the corpora prior to the generation of crosslingual word embeddings for both roots and suffixes greatly improves the prediction quality and captures semantic similarities more effectively. To exhibit this, we have chosen two related languages: Telugu and Kannada of the Dravidian language family. We have also tested our method upon a widely spoken North Indian language, Hindi, belonging to the Indo-European language family, and have observed encouraging results.
Towards a Low-cost RSSI-based Crop Monitoring
Authors: Bauer Jan , Aschenbruck Nils
Published: June 2020

The continuous monitoring of crop growth is crucial for site-specific and sustainable farm management in the context of precision agriculture. With the help of precise
in situ
information, agricultural practices, such as irrigation, fertilization, and plant protection, can be dynamically adapted to the changing needs of individual sites, thereby supporting yield increases and resource optimization. Nowadays, IoT technology with networked sensors deployed in greenhouses and farmlands already contributes to
in situ
information. In addition to existing soil sensors for moisture or nutrient monitoring, there are also (mainly optical) sensors to assess growth developments and vital conditions of crops. This article presents a novel and complementary approach for a low-cost crop sensing that is based on temporal variations of the signal strength of low-power IoT radio communication. To this end, the relationship between crop growth, represented by the leaf area index (LAI), and the attenuation of signal propagation of low-cost radio transceivers is investigated. Real-world experiments in wheat fields show a significant correlation between LAI and received signal strength indicator (RSSI) time series. Moreover, influencing meteorological factors are identified and their effects are analyzed. Including these factors, a multiple linear model is finally developed that enables an RSSI-based LAI estimation with great potential.
Approval Voting and Incentives in Crowdsourcing
Authors: Shah Nihar B. , Zhou Dengyong
Published: June 2020

The growing need for labeled training data has made crowdsourcing a vital tool for developing machine learning applications. Here, workers on a crowdsourcing platform are typically shown a list of unlabeled items, and for each of these items, are asked to choose a label from one of the provided options. The workers in crowdsourcing platforms are not experts, thereby making it essential to judiciously elicit the information known to the workers. With respect to this goal, there are two key shortcomings of current systems: (i) the incentives of the workers are not aligned with those of the requesters; and (ii) the interface does not allow workers to convey their knowledge accurately by forcing them to make a single choice among a set of options. In this article, we address these issues by introducing approval voting to utilize the expertise of workers who have partial knowledge of the true answer and coupling it with two strictly proper scoring rules. We additionally establish attractive properties of optimality and uniqueness of our scoring rules. We also conduct preliminary empirical studies on Amazon Mechanical Turk, and the results of these experiments validate our approach.
A Practical Learning-based Approach for Viewer Scheduling in the Crowdsourced Live Streaming
Authors: Zhang Rui-Xiao , Ma Ming , Huang Tianchi , Pang Haitian , Yao Xin , Wu Chenglei , Sun Lifeng
Published: June 2020

Scheduling viewers effectively among different Content Delivery Network (CDN) providers is challenging owing to the extreme diversity in the crowdsourced live streaming (CLS) scenarios. Abundant algorithms have been proposed in recent years, which, however, suffer from a critical limitation: Due to their inaccurate feature engineering or naive rules, they cannot optimally schedule viewers. To address this concern, we put forward LTS (Learn to Schedule), a novel scheduling algorithm that can adapt to the dynamics from both viewer traffics and CDN performance. In detail, we first propose LTS-RL, an approach that schedules CLS viewers based on deep reinforcement learning (DRL). Since LTS-RL is trained in an end-to-end way, it can automatically learn scheduling algorithms without any pre-programmed models or assumptions about the environment dynamics. At the same time, to practically deploy LTS-RL, we then use the decision tree and imitation learning to convert LTS-RL into a more light-weighted and interpretable model, which is denoted as Fast-LTS. After the extensive evaluation of the real data from a leading CLS platform in China, we demonstrate that our proposed model (both LTS-RL and Fast-LTS) can improve the average quality of experience (QoE) over state-of-the-art approaches by 8.71--15.63%. At the same time, we also demonstrate that Fast-LTS can faithfully convert the complicated LTS-RL with slight performance degradation (< 2%), while significantly reducing the decision time (×7--10).
Parameterized Hardness of Art Gallery Problems
Authors: Bonnet Édouard , Miltzow Tillmann
Published: June 2020

Given a simple polygon
P
on
n
vertices, two points
x
,
y
in
P
are said to be visible to each other if the line segment between
x
and
y
is contained in
P
. The P
oint
G
uard
A
rt
G
allery
problem asks for a minimum set
S
such that every point in
P
is visible from a point in
S
. The V
ertex
G
uard
A
rt
G
allery
problem asks for such a set
S
subset of the vertices of
P
. A point in the set
S
is referred to as a guard. For both variants, we rule out any
f
(
k
)
n

o
(
k
/ log
k
)

algorithm, where
k
:= |
S
| is the number of guards, for any computable function
f
, unless the exponential time hypothesis fails. These lower bounds almost match the
n

O
(
k
)

algorithms that exist for both problems.
KiWi
Authors: Basin Dmitry , Bortnikov Edward , Braginsky Anastasia , Golan-Gueta Guy , Hillel Eshcar , Keidar Idit , Sulamy Moshe
Published: June 2020

We present KiWi, the first atomic KV-map to efficiently support simultaneous large scans and real-time access. The key to achieving this is treating scans as first class citizens and organizing the data structure around them. KiWi provides wait-free scans, whereas its put operations are lightweight and lock-free. It optimizes memory management jointly with data structure access. We implement KiWi and compare it to state-of-the-art solutions. Compared to other KV-maps providing atomic scans, KiWi performs either long scans or concurrent puts an order of magnitude faster. Its scans are twice as fast as
non-atomic
ones implemented via iterators in the Java skiplist.
Groute
Authors: Ben-Nun Tal , Sutton Michael , Pai Sreepathi , Pingali Keshav
Published: June 2020

Nodes with multiple GPUs are becoming the platform of choice for high-performance computing. However, most applications are written using bulk-synchronous programming models, which may not be optimal for irregular algorithms that benefit from low-latency, asynchronous communication. This article proposes constructs for asynchronous multi-GPU programming and describes their implementation in a thin runtime environment called Groute. Groute also implements common collective operations and distributed work-lists, enabling the development of irregular applications without substantial programming effort. We demonstrate that this approach achieves state-of-the-art performance and exhibits strong scaling for a suite of irregular applications on eight-GPU and heterogeneous systems, yielding over 7× speedup for some algorithms.
Where to Next? The Impact of COVID-19 on Human-Robot Interaction Research
Authors: Feil-Seifer David , Haring Kerstin S. , Rossi Silvia , Wagner Alan R. , Williams Tom
Published: June 2020

The COVID-19 pandemic will have a profound and long-lasting impact on the entire scientific endeavor. Scientists already are adapting research programs to adapt to changes in what is prioritized—and what is possible; educators are changing the way that the next generation of researchers are trained, and flagship conferences in many fields are being cancelled, postponed, and fundamentally transformed.

These broad-reaching changes are particularly impactful to human-oriented domains such as human-robot interaction (HRI). Because in-person human-subject experiments can take a year or more to conduct, the research we will see published in the field in the immediate future may appear to be “business as usual,” with accounts of laboratory studies with large numbers of in-person participants. The research currently being performed, however, is of course a different story entirely. Studies that were under way when the current crisis began will be truncated, resulting either in work that cannot be published or in work whose true impact is difficult to accurately assess. Yet HRI research performed in the coming years will be changed in fundamentally different ways; the inability to perform—or expect future performance of—in-person human subjects research, especially research involving tactile or multiparty interaction, will change both the dominant methodological techniques employed by HRI researchers and the very research questions that the field chooses to—and is able to—address.

These challenges demand that HRI researchers identify precisely how the field can maintain research quality and impact while the ability to conduct human-subject studies is severely impaired for an undetermined amount of time. A natural inclination may be simply to wait the crisis out in the hope of a speedy return to normalcy; however, in this article, we argue that the community can also take this opportunity to reevaluate and refocus how research in this field is conducted and how students are mentored in ways that will yield benefits for years to come after the current crisis has ended.
Synthetic Genomes
Authors: Zhang Weimin , Mitchell Leslie A. , Bader Joel S. , Boeke Jef D.
Published: June 2020

DNA synthesis technology has progressed to the point that it is now practical to synthesize entire genomes. Quite a variety of methods have been developed, first to synthesize single genes but ultimately to massively edit or write from scratch entire genomes. Synthetic genomes can essentially be clones of native sequences, but this approach does not teach us much new biology. The ability to endow genomes with novel properties offers special promise for addressing questions not easily approachable with conventional gene-at-a-time methods. These include questions about evolution and about how genomes are fundamentally wired informationally, metabolically, and genetically. The techniques and technologies relating to how to design, build, and deliver big DNA at the genome scale are reviewed here. A fuller understanding of these principles may someday lead to the ability to truly design genomes from scratch.
Single-Molecule Studies of Protein Folding with Optical Tweezers
Authors: Bustamante Carlos , Alexander Lisa , Maciuba Kevin , Kaiser Christian M.
Published: June 2020

Manipulation of individual molecules with optical tweezers provides a powerful means of interrogating the structure and folding of proteins. Mechanical force is not only a relevant quantity in cellular protein folding and function, but also a convenient parameter for biophysical folding studies. Optical tweezers offer precise control in the force range relevant for protein folding and unfolding, from which single-molecule kinetic and thermodynamic information about these processes can be extracted. In this review, we describe both physical principles and practical aspects of optical tweezers measurements and discuss recent advances in the use of this technique for the study of protein folding. In particular, we describe the characterization of folding energy landscapes at high resolution, studies of structurally complex multidomain proteins, folding in the presence of chaperones, and the ability to investigate real-time cotranslational folding of a polypeptide.
Structure and Giant Magnetoresistance of Co-Fe/Cu Multilayer Films Electrodeposited from Various Bath Formulations
Authors: Zalka D. , Péter L. , El-Tahawy M. , Gubicza J. , Molnár G. , Bakonyi I.
Published: June 2020

Detailed new results are reported on the preparation and giant magnetoresistance (GMR) of electrodeposited Co-Fe/Cu multilayer films by using four different baths (sulfamate, sulfate, ammonium chloride and sodium citrate type solutions). Two-pulse plating was applied for Co-Fe(5nm)/Cu(5nm) multilayer preparation by using galvanostatic pulses for the deposition of the magnetic layer. The Cu layer deposition potential was electrochemically optimized for each bath formulation by analyzing the current transients during the deposition of the non-magnetic layers. The optimal Cu deposition potential was found to be dependent both on the bath formulation and the Fe2+/Co2+ ion concentration ratio. The results of X-ray diffraction (XRD) measurements were in agreement with the composition of the samples. At low Fe content (about 10 at.% Fe) in the magnetic layer, an fcc structure was formed (in some cases, even multilayer satellites were observed). In samples with high Fe content (about 33 at.% Fe) in the magnetic layer, both fcc and bcc phases were present. A GMR behavior was observed for all multilayers, with a maximum GMR of about 4% in some cases. For multilayers from the sulfamate, sulfate and chloride baths, the GMR exhibited a multilayer-type behavior whereas the GMR of samples from the citrate bath was rather similar to the behavior of granular magnetic alloys containing also superparamagnetic regions.
Vertical integration of head, neck, and special senses module in undergraduate medical curriculum
Authors: Arain Shoukat Ali , Kumar Santosh , Yaqinuddin Ahmed , Meo Sultan Ayoub
Published: June 2020

Vertical integration is believed to increase motivation by providing context for the learning. In this quasi-experimental study, cohort I took two horizontally integrated modules: structure and function of head, neck, and special senses in the second year, and pathophysiology and clinical sciences in the third year. Cohort II took a combined, vertically integrated module in the second year. Data from the questionnaire and examination scores were compared. Response rate was 80.1% (125/156) for cohort I and 57.6% (98/170) for cohort II. Response to the statement that vertical integration provides context to basic sciences was mixed with a higher agreement in cohort II (51.5 vs. 37.2%; P = 0.04). Cohort II was least satisfied with the appropriateness of self-study time (52.0 vs. 34.7%; P = 0.01). However, cohort II felt that the basic sciences lectures (90.8 vs. 69.4%; P < 0.01) and the clinical skills sessions (85.7 vs. 62.1%; P < 0.01) were more effective. Cohort II was less satisfied with clinical lectures (80.6 vs. 56.1%; P < 0.01) and was less confident in achieving clinical learning objectives (72.8 vs. 40.8%; P < 0.01). Mean multiple-choice questions and problem-based learning scores were similar. However, the short-answer question score was higher for cohort I [82.48 (SD 14.9) vs. 70.74 (SD 17.9); P < 0.01]. Overall, the idea of early vertical integration had a mixed response. It improved the effectiveness of basic sciences lectures and clinical skills sessions. Achievement of clinical learning outcomes was compromised. A disparity in the module’s duration and curricular content, and students' ability to grasp clinical concepts and faculty’s expectations are the possible reasons. Increased duration and better communication with clinical faculty may improve early introduction of vertical integration.
Parallel intermediate conductance K+ and Cl− channel activity mediates electroneutral K+ exit across basolateral membranes in rat distal colon
Authors: Rehman Shabina , Narayanan Karthikeyan , Nickerson Andrew J. , Coon Steven D. , Hoque Kazi Mirajul , Sandle Geoffrey I. , Rajendran Vazhaikkurichi M.
Published: June 2020

This study demonstrates that during active electroneutral K+ absorption in rat distal colon, K+ exit across the basolateral membrane mainly reflects intermediate conductance K+ channels operating in conjunction with chloride channel 2, with a smaller but significant contribution from K+-Cl− cotransporter-1 activity.
Sex differences in renal ischemia-reperfusion injury
Authors: Hosszu Adam , Fekete Andrea , Szabo Attila J.
Published: June 2020

Ischemia-reperfusion injury of the kidney is caused by the sudden and temporary obstruction of blood flow to the organ. Renal ischemia-reperfusion injury is associated with high morbidity and mortality, but effective therapies are lacking. Sexual dimorphism in renal injury has been acknowledged since the 1940s, and the possible role of sex hormones has been intensively investigated in the past decades. Clinical and experimental data demonstrate sexual differences in renal anatomy, physiology, and susceptibility to renal diseases including but not limited to ischemia-reperfusion injury. Some data suggest the protective role of female sex hormones, whereas others highlight the detrimental effect of male hormones in renal ischemia-reperfusion injury. Although the important role of sex hormones is evident, the exact underlying mechanisms remain to be elucidated. This review focuses on collecting the current knowledge about sexual dimorphism of renal ischemia-reperfusion injury, with emphasis on molecular mechanisms and potential novel therapeutic strategies.
Silencing of MYH7 ameliorates disease phenotypes in human iPSC-cardiomyocytes
Authors: Dainis Alexandra , Zaleta-Rivera Kathia , Ribeiro Alexandre , Chang Andrew Chia Hao , Shang Ching , Lan Feng , Burridge Paul W. , Liu W. Robert , Wu Joseph C. , Chang Alex Chia Yu , Pruitt Beth L. , Wheeler Matthew , Ashley Euan
Published: June 2020

Allele-specific RNA silencing has been shown to be an effective therapeutic treatment in a number of diseases, including neurodegenerative disorders. Studies of allele-specific silencing in hypertrophic cardiomyopathy (HCM) to date have focused on mouse models of disease. We here examine allele-specific silencing in a human-cell model of HCM. We investigate two methods of silencing, short hairpin RNA (shRNA) and antisense oligonucleotide (ASO) silencing, using a human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) model. We used cellular micropatterning devices with traction force microscopy and automated video analysis to examine each strategy’s effects on contractile defects underlying disease. We find that shRNA silencing ameliorates contractile phenotypes of disease, reducing disease-associated increases in cardiomyocyte velocity, force, and power. We find that ASO silencing, while better able to target and knockdown a specific disease-associated allele, showed more modest improvements in contractile phenotypes. These findings are the first exploration of allele-specific silencing in a human HCM model and provide a foundation for further exploration of silencing as a therapeutic treatment for MYH7-mutation-associated cardiomyopathy.
Role of Oxidation‐Dependent CaMKII Activation in the Genesis of Abnormal Action Potentials in Atrial Cardiomyocytes: A Simulation Study
Authors: Zhao Na , Li Qince , Sui Haibo , Zhang Henggui
Published: June 2020

Atrial fibrillation is a common cardiac arrhythmia with an increasing incidence rate. Particularly for the aging population, understanding the underlying mechanisms of atrial arrhythmia is important in designing clinical treatment. Recently, experiments have shown that atrial arrhythmia is associated with oxidative stress. In this study, an atrial cell model including oxidative‐dependent Ca2+/calmodulin‐ (CaM‐) dependent protein kinase II (CaMKII) activation was developed to explore the intrinsic mechanisms of atrial arrhythmia induced by oxidative stress. The simulation results showed that oxidative stress caused early afterdepolarizations (EADs) of action potentials by altering the dynamics of transmembrane currents and intracellular calcium cycling. Oxidative stress gradually elevated the concentration of calcium ions in the cytoplasm by enhancing the L‐type Ca2+ current and sarcoplasmic reticulum (SR) calcium release. Owing to increased intracellular calcium concentration, the inward Na+/Ca2+ exchange current was elevated which slowed down the repolarization of the action potential. Thus, the action potential was prolonged and the L‐type Ca2+ current was reactivated, resulting in the genesis of EAD. Furthermore, based on the atrial single‐cell model, a two‐dimensional (2D) ideal tissue model was developed to explore the effect of oxidative stress on the electrical excitation wave conduction in 2D tissue. Simulation results demonstrated that, under oxidative stress conditions, EAD hindered the conduction of electrical excitation and caused an unstable spiral wave, which could disrupt normal cardiac rhythm and cause atrial arrhythmia. This study showed the effects of excess reactive oxygen species on calcium cycling and action potential in atrial myocytes and provided insights regarding atrial arrhythmia induced by oxidative stress.
Effect of the High-FODMAP Diet on Bowel Preparation for Colonoscopy: A Multicenter, Prospective Cohort Study
Authors: Cheng Peng , Ma Ruijun , Wang Shuling , Fang Jun , Zhong Zhengrong , Bai Yu , Meng Xiangjun , Li Zhaoshen
Published: June 2020

Background. Optimal bowel preparation for colonoscopy is fundamental to a successful examination. The FODMAP diet can increase the content of intestinal water and gas, but its impact on bowel cleanliness and bubbles has not been reported. This study was therefore aimed at evaluating the effect of the FODMAP diet on the quality of bowel preparation and the adenoma detection rate (ADR). Methods. This was a multicenter, prospective cohort study involving consecutive patients who underwent colonoscopy in two centers in China. Patients were assigned to one of two groups: high-FODMAP or nonhigh-FODMAP diet. ODMP Software was used for the identification of FODMAP diet types. The primary outcome was ADR; secondary outcomes were the quality of bowel preparation, measured by the Boston bowel preparation scale and bubble scores. Results. There were 365 patients included. Patients in the high-FODMAP-diet group showed poor bowel cleansing efficacy: BBPS≥6 in 76.8% vs. 90.3% (P<0.01) and bubble scores of 2.42±1.69 vs. 1.32±1.63 (P<0.001). The intubation time was significantly longer in the high-FODMAP-diet group (7.07±5.18 vs. 5.46±3.05 min; P=0.002). The High-FODMAP diet was an independent risk predictor for inadequate bowel preparation. There were no statistically significant differences in ADR between the two dietary groups. Conclusion. The high-FODMAP diet significantly reduced the quality of bowel preparation. We recommend the consumption of nonhigh-FODMAP diet in bowel preparation as a reference standard for dietary regimen. This method was effective, flexible, referable, and well tolerated, which could help to provide patients a valuable dietary guidance in bowel preparation.
Symbiotic Organism Search Algorithm for Power Loss Minimization in Radial Distribution Systems by Network Reconfiguration and Distributed Generation Placement
Authors: The Tung Tran , Quoc Sy Nguyen , Ngoc Dieu Vo
Published: June 2020

This paper proposes the Symbiotic Organism Search (SOS) algorithm to find the optimal network configuration and the placement of distributed generation (DG) units that minimize the real power loss in radial distribution networks. The proposed algorithm simulates symbiotic relationships such as mutualism, commensalism, and parasitism for solving the optimization problems. In the optimization process, the reconfiguration problem produces a large number of infeasible network configurations. To reduce these infeasible individuals and ensure the radial topology of the network, the graph theory was applied during the power flow. The implementation of the proposed SOS algorithm was carried out on 33-bus, 69-bus, 84-bus, and 119-bus distribution networks considering seven different scenarios. Simulation results and performance comparison with other optimization methods showed that the SOS-based approach was very effective in solving the network reconfiguration and DG placement problems, especially for complex and large-scale distribution networks.
Altered Temporal Dynamic Intrinsic Brain Activity in Late Blindness
Authors: Huang Xin , Wen Zhi , Qi Chen-Xing , Tong Yan , Dan Han-Dong , Xie Bao-Jun , Shen Yin
Published: June 2020

Previous neuroimaging studies demonstrated that visual deprivation triggers significant crossmodal plasticity in the functional and structural architecture of the brain. However, prior neuroimaging studies focused on the static brain activity in blindness. It remains unknown whether alterations of dynamic intrinsic brain activity occur in late blindness (LB). This study investigated dynamic intrinsic brain activity changes in individuals with late blindness by assessing the dynamic amplitude of low‐frequency fluctuations (dALFFs) using sliding‐window analyses. Forty‐one cases of late blindness (LB) (29 males and 12 females, mean age: 39.70 ± 12.66 years) and 48 sighted controls (SCs) (17 males and 31 females, mean age: 43.23 ± 13.40 years) closely matched in age, sex, and education level were enrolled in this study. The dALFF with sliding‐window analyses was used to compare the difference in dynamic intrinsic brain activity between the two groups. Compared with SCs, individuals with LB exhibited significantly lower dALFF values in the bilateral lingual gyrus (LING)/calcarine (CAL) and left thalamus (THA). LB cases also showed considerably decreased dFC values between the bilateral LING/CAL and the left middle frontal gyrus (MFG) and between the left THA and the right LING/cerebelum_6 (CER) (two‐tailed, voxel‐level P < 0.01, Gaussian random field (GRF) correction, cluster‐level P < 0.05). Our study demonstrated that LB individuals showed lower‐temporal variability of dALFF in the visual cortices and thalamus, suggesting lower flexibility of visual thalamocortical activity, which might reflect impaired visual processing in LB individuals. These findings indicate that abnormal dynamic intrinsic brain activity might be involved in the neurophysiological mechanisms of LB.
Co-Supplementation of Flos Sophorae Extract with Tremella fuciformis Polysaccharides Improves Physicochemical, Textural, Rheological, and Antioxidant Properties of Low-Fat Yogurts
Authors: Tang Renyong , Lu Yurong , Hou Caiyun , Peng Jiaxuan , Wang Wei , Guo Xiulan
Published: June 2020

Flos Sophorae extract (FSE) with abundant rutin and Tremella fuciformis polysaccharides (TP) could act as novel natural improvers of low-fat yogurt due to their health benefits and properties of interacting with proteins. This study attempted to understand how FSE or its combination with TP influences physicochemical, textural, and antioxidant properties of low-fat yogurts. The results indicated that the low concentrations of FSE (1.2 or 2.4%) increased the antioxidant activity, prompted the S. thermophilus growth, water holding capacity (WHC), and textural and sensory properties, and shortened the fermentation time, but reduced the rheological properties of yogurts compared with the control. Co-supplementing appropriate TP with the optimum FSE concentration (2.4%) improved the rheological properties, and further enhanced the S. thermophilus growth, WHC, textural and antioxidant properties, and sensory scores of yogurts compared with the 2.4% FSE group, with the best effects at 0.4 mg/mL TP. Taken together, co-supplementation of polyphenols extract FSE with Tremella fuciformis polysaccharides may be an available strategy to optimize health-promoting properties and overcome defects of low-fat yogurts.
Laboratory Experiment and Numerical Analysis on the Precursory Hydraulic Process of Rainfall‐Induced Slope Failure
Authors: Park Joon-Young , Song Young-Suk
Published: June 2020

A combined analysis involving a laboratory test and numerical modeling was performed to investigate the hydraulic processes leading to slope failure during rainfall. Through a laboratory landslide test in which artificial rainfall was applied to a homogeneous sandy slope, the timing and configurations of multiple slides were identified. In addition, volumetric water content was measured in real time through the use of monitoring sensors. The measured volumetric water content data were then used to validate the relevance of the numerical modeling results. The validated numerical modeling of the laboratory‐scale slope failures provided insight into the hydraulic conditions that trigger landslides. According to the numerical modeling results, the miniaturized slope in the laboratory test was saturated in a manner so that the wetting front initially progresses downward and then the accumulated rainwater at the toe of the slope creates a water table that advances toward the crest. Furthermore, each of the five sequential failures that occurred during this experiment created slip surfaces where the pore‐water pressure had achieved full saturation and an excessive pore‐water pressure state. The findings of this study are expected to help understand the hydraulic prerequisites of landslide phenomena.
A Dual Fractal Poroelastic Model for Characterizing Fluid Flow in Fractured Coal Masses
Authors: Liu Guannan , Ye Dayu , Gao Feng , Liu Jishan
Published: June 2020

In the process of coalbed methane exploitation, the fracture and pore structure is the key problem that affects the permeability of coalbed. At present, the coupling effect of fracture and pore structure and in situ stress is seldom considered in the study of coal seam permeability. In this paper, the fractal seepage model is coupled with coal deformation, and the adsorption expansion effect is considered. A multifield coupling model considering the influence of matrix and fracture structure is established. Then, the influence of pore structure parameters of main fracture on macropermeability is analyzed, including (1) fractal dimension of fracture length, (2) maximum fracture length, (3) fractal dimension of throat diameter, and (4) fractal dimension of throat bending. At the same time, the simulation results are compared with the results of Darcy’s uniform permeability model. The results show that the permeability calculated by the proposed model is significantly different from that calculated by the traditional cubic model. Under the action of in situ stress, when the porosity and other parameters remain unchanged, the macropermeability of coal is in direct proportion to the fractal dimension of coal fracture length, the fractal dimension of throat diameter, and the maximum fracture length and in inverse proportion to the fractal dimension of coal throat curvature.
Ameliorative Effects of Bredemolic Acid on Markers Associated with Renal Dysfunction in a Diet-Induced Prediabetic Rat Model
Authors: Akinnuga Akinjide Moses , Siboto Angezwa , Khumalo Bongiwe , Sibiya Ntethelelo Hopewell , Ngubane Phikelelani , Khathi Andile
Published: June 2020

Recently, studies have shown that renal dysfunction is associated not only with overt diabetes but also with the preceding stage known as prediabetes. Diet and pharmacological interventions are the therapeutic approaches to managing prediabetes, but the compliance in combining the two interventions is low. Hence, the efficacy of pharmacological intervention is reduced without diet modification. In our previous study, we established that bredemolic acid (BA) ameliorated glucose homeostasis via increased GLUT 4 expression in the skeletal muscle of prediabetic rats in the absence of diet intervention. However, the effects of bredemolic acid on renal function in prediabetic condition are unknown. Therefore, this study was aimed at investigating the ameliorative effects of bredemolic acid on renal dysfunction in a diet-induced prediabetic rat model. Thirty-six Sprague-Dawley male rats (150–180 g) were divided into two groups: the nonprediabetic (n=6) and prediabetic (n=30) groups which were fed normal diet (ND) and high-fat high-carbohydrate (HFHC) diet, respectively, for 20 weeks. After the 20th week, the prediabetic groups were subdivided into prediabetic control (PD) and 4 other prediabetic groups which were treated with either BA (80 mg/kg) or metformin (MET, 500 mg/kg) for further 12 weeks (21st to 32nd). Plasma, urine, and kidney samples were collected for biochemical analysis. The untreated prediabetic (PD) rats presented increased fluid intake and urine output; increased creatinine, urea, and uric acid plasma concentrations; albuminuria; proteinuria; sodium retention; potassium loss; increased aldosterone and kidney injury molecule (KIM-1) concentration; and increased urinary podocin mRNA expression. However, BA administration attenuated the renal markers and oxidative stress and decreased the urinary podocin mRNA expression. In conclusion, BA administration, regardless of diet modification, attenuates renal dysfunction in an experimentally induced prediabetic state.
Bisphenol A Removal through Low-Cost Kaolin-Based Ag@TiO2 Photocatalytic Hollow Fiber Membrane from the Liquid Media under Visible Light Irradiation
Authors: Shareef Usman , Waqas Muhammad
Published: June 2020

Removal of bisphenol A (BPA) from water has presented a major challenge for the water industry. In this work, we report the BPA separation properties of truly low-cost kaolin-based visible light-activated photocatalytic hollow fiber membranes. The ceramic hollow fiber support was successfully fabricated by phase inversion and sintering method, whereas Ag@TiO2 photocatalyst was prepared by liquid impregnation method. Different factors that affected the BPA removal were thoroughly investigated, including Ag loading in TiO2 catalyst and immersion time during dip coating method. A reference BPA (10 mgl-1) was used to check the photocatalytic performance of Ag@TiO2 photocatalysts and prepared membranes. Comprehensive characterization including X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy-dispersive X-ray (EDX/S), Brunner-Emmer-Teller (BET), and UV-Vis spectroscopy revealed altered morphological and physicochemical properties of the photocatalytic membrane. UV-Vis results exhibited that the extended absorption edge of Ag@TiO2 photocatalyst was observed into the visible region that led to its maximum BPA removal of 93.22% within 180 min under visible light irradiation. The FESEM images of the prepared membranes evinced a significant change in the structural morphologies, and UV-Vis showed the absorption edge in the visible region owing to the coating of the Ag@TiO2 photocatalyst on the surface of the membrane. The resultant membrane showed a significant photocatalytic performance in the degradation of BPA (90.51% within 180 min) in an aqueous solution under visible light irradiation. At inference, the prepared membrane can be considered a promising candidate for efficient removal of BPA.
Current Progression: Application of High‐Throughput Sequencing Technique in Space Microbiology
Authors: Chen Yanwu , Wu Bin , Zhang Cheng , Fan Zhiqi , Chen Ying , Xin Bingmu , Xie Qiong
Published: June 2020

During a spaceflight, astronauts need to live in a spacecraft on orbit for a long time, and the relationship between humans and microorganisms in the closed environment of space is not the same as on the ground. The dynamic study of microorganisms in confined space shows that with the extension of the isolation time, harmful bacteria gradually accumulate. Monitoring and controlling microbial pollution in a confined environment system are very important for crew health and the sustainable operation of a space life support system. Culture‐based assays have been used traditionally to assess the microbial loads in a spacecraft, and uncultured‐based techniques are already under way according to the NASA global exploration roadmap. High‐throughput sequencing technology has been used generally to study the communities of the environment and human on the ground and shows its broad prospects applied onboard. We here review the recent application of high‐throughput sequencing on space microbiology and analyze its feasibility and potential as an on‐orbit detection technology.