bluuebunny/crossref_metadata_2025 huggingface dataset:
Strain Prediction of Bridge SHM Based on CEEMDAN-ARIMA Model
Authors: Bian Siyu , Zhuo Jingchao , Zhu Liming
Published: September 2020

In this paper, a model based on CEEMDAN-ARIMA is proposed to predict the strain monitoring data for bridge SHM. In view of the problem that the classical time series theory cannot predict the modal overlap-ping data effectively, the CEEMDAN method was used to decompose the strain monitoring data for the bridge SHM. To deal with the large number of components after using CEEMDAN, the PE method (permutation entropy) was used to generate a series of new data sequences according to the degree of randomness. Finally, each new data sequence was predicted and the final prediction is obtained by ARIMA model. The method was used to predict the SHM strain data of a cable-stayed bridge in Shanghai. The results show that the proposed combination method is more accurate than the classical time series theory and is promising for engineering applications.
Research on Wind Resistance and Monitoring Technology for Pole-line Structure in Transmission Lines
Authors: Wang Hua , Wang Longlin , Wu Changxia , Peng Xi , Li Litao
Published: September 2020

The research on wind resistance monitoring technology of typical cement pole-line structure in 10kv transmission line is carried out in view of the fact that the transmission lines in the coastal areas of South China are often threatened by typhoons. Firstly, a wind-resistant monitoring system for pole-line structures is established. Secondly, the method to determine the early warning value in the monitoring system is proposed and the whole finite element model of the pole-line is established. Then, the wind speed is transformed into wind load to determine the early warning value of wind speed according to the wind-pole fluid-solid coupling model. Finally, the correctness of the wind-resistant monitoring technology of the pole-line structure is verified by the results monitored by practical engineering. The research shows that the wind load on the surface of the conductor is non-uniform, which can be accurately calculated through the wind-pole fluid-solid coupling model; The structural response obtained by the whole finite element model of the pole-line structure can accurately reflect the actual stress state, which can be used to determine the early warning value of wind speed; The proposed wind-resistant monitoring system in transmission lines has been verified by practical projects and can be popularized.
Research Method for Dyke Swarms Based on UAV Remote Sensing in Desert Areas: A Case Study in Beishan, Gansu, China
Authors: Dai Junhao , Xue Linfu , Sang Xuejia , Li Zhongtan , Ma Jianxiong , Sun Hairui
Published: September 2020

The Beishan area of Gansu, China, is an arid desert area, and the surface rocks are well-exposed, creating excellent conditions for drone remote sensing geological mapping experiments. The magmatic rocks and metamorphic rocks in the Beishan area are widely exposed, and a large number of basic and acidic dykes have developed. The formation and distribution of gold deposits are closely related to the dykes. In order to explore the development rules of dykes in this area, a 20km2; area in the Changliushui area of Beishan was selected as the target, and a set of methods for studying the dyke swarm using drones was formed and applied: Images were collected and high-resolution orthophotos and three-dimensional models were synthesized, combined with ground work, and finally remote sensing geological interpretation was performed, to obtain high-precision geological maps. Based on this, the dykes were identified in detail and divided into four phases. The strikes and dips information of the dykes was extracted, and it could be concluded that the dominance of the strikes of the dykes in the target area is NEE, and the inclination is nearly upright, while the length and thickness of dykes obey a skewed distribution. The application of the method not only provides more geological information, but also provides clues for the tectonic evolution and formation mechanisms of dyke swarms, indicates the prospecting direction of future gold deposits.
Study on Rheological Constitutive Model of Landslide Loess in Tianshui City under Triaxial Condition with Variable Water Content
Authors: Jia Yajun , Chen Cunli
Published: September 2020

This paper analyses the water content of landslide loess in Tianshui City, Gansu Province. Through triaxial cyclic loading and unloading rheological tests, the creep curves and water content forms of landslide loess under different confining pressures are obtained, and their rheological constitutive model for analysis. The rheological constitutive model test under triaxial conditions shows that under low and high stress conditions, the creep strain rate decreases with time, which is manifested as decelerating creep; only under high stress conditions, creep strain The rate undergoes a process of decreasing first, then stabilizing, and finally increasing, corresponding to the three stages of deceleration creep, constant velocity creep and acceleration creep. The specimen will produce a certain instantaneous elastic deformation under different stresses. The rheology of loess has a nonlinear characteristic. The stress-strain iso-curve gradually shifts toward the strain axis as the stress level increases, and the degree of nonlinearity increases as the stress increases.
Analysis on the Variation Trend of Evaporation and Precipitation in Xiaolangdi Reservoir
Authors: Ma Ziru
Published: September 2020

Based on the monthly evaporation and precipitation data from 1982 to 2013 of 13 meteorological stations in and around the Xiaolangdi Reservoir, the linear tendency estimation method, cumulative anomaly, M-K mutation detection method and ARIMA model are used to study and predict the changing characteristics of evaporation and precipitation. The results show that the annual evaporation and precipitation in the reservoir area both show a downward trend. The evaporation has an abrupt decline in 2001, and the precipitation decreases suddenly in 2003 and 2011. After impoundment, the annual evaporation volume changed from the upward trend to a weak downward trend, and the downward trend of annual precipitation is weakened. The impact of impoundment on evaporation and precipitation is limited, and the impact intensity decreases with increasing distance from the reservoir. The reservoir area’s evaporation and precipitation have significant seasonal variation characteristics, and the future evaporation will show a slight downward trend, while the precipitation will show a slight upward trend.
The standardization of water use statistics in China
Authors: Zhang Yubo , Du Wei , Yang Jie , Lin Ling , Bai Xue
Published: September 2020

This paper outlines the current situation concerning the standardisation of water use statistics in China. The water classification, statistical subjects, objects, methods and report templates are clarified in part regarding national total water use. Additionally, the standards of water use statistics for enterprises are introduced, which define statistical items, procedures, methods. Suggestions are proposed on issues such as insufficient statistical accuracy and imperfect statistical systems.
pH control in neutral solutions using polymethylacrylic acids as polymer-supported buffer agents
Authors: Gao Zhinan , Li Chen , Liu Xiaorong , Li Yongsheng
Published: September 2020

Polymethylacrylic acid beads were utilized as polymer-supported buffer agents for the pH control of neutral aqueous solutions to reduce phosphorus effluents from phosphate buffers. The agents were used to buffer the pH of ureasecatalyzed reactions in a neutral PH region.
Discussion on Fire Risk Assessment for Irradiation Room
Authors: Yao Xiaolin
Published: September 2020

In order to study fire hazards, the reason that we chose 60Co round irradiation room of stacking is just because it is very typical. Ignition temperatures of several radiation cargo can be sequentially gotten by experiment. Both numerical simulation and experiment were adopted to research the rule of change in smoke temperature under source blockage. The fire scenario was simulated to discuss temperature field by FDS. The results I have seen show that temperatures of fire smoke in round irradiation room rose rapidly at 0.5h in the early stage of source blockage. Temperature field in irradiation room gradually comes to stability as time goes on, and the temperature is rising very slowly. The temperature will reach the ignition temperature of radiation cargo, 3.56 days after source blockage. Some radiation cargo may be ignited and cause a fire.
Thermal Oxidation Mechanism and Test Method of Lubricating Oil
Authors: Wang Yuexing , Sun Yuanyuan , Wang Pujian
Published: September 2020

Thermal Oxidation Process Mechanism of lubricating oil is described, at the same time, the thermal oxidation test methods of lubricating oil-infrared spectrum, rotating oxygen bomb, Cyclic voltammetry and sludge content are introduced and compared. The correlation and difference between them were compared by experiments.
A Humidity Compensation Method for On-line Odor Detection System in the Vehicle
Authors: Cui Chen , Liu Wei , Wang Lei , Liu Xuefeng
Published: September 2020

The paper introduce a humidity compensation method for the on-line detection system of odor in the vehicle. The method is based on theoretical model of dilution and humidity control, and the gas concentration of the sample to be measured under different dilution multiples is measured, and then the original gas concentration is calculated by linear fitting with the gas concentration data under the condition of low humidity, so that the humidity compensation of the measured sample gas can be carried out. After the humidity compensation method, the relative error of VOCs concentration of the sample A is about 15%, which is close to its real value, which significantly improves the accuracy of sample’s VOCs concentration measurement.
Study on the Calculation Method of VOCs Emission Index per Unit Coating Area of Automobile
Authors: Ren Jiabao , Liu Xuefeng , Wang Lei , Liu Wei
Published: September 2020

Volatile organic compounds (VOCs) are the important factors causing complex air pollution. Strengthening the prevention and control of VOCs pollution is the key work of energy saving and emission reduction in the 13th Five-Year Plan period in China. Automobile industry is a typical VOCs emission industry. A series of VOCs emission standards for automobile manufacturing links have been formulated at home and abroad. However, due to the complex production and emission links of automobile products, the VOCs accounting methods are various. In this paper, the method of VOCs emission accounting based on material balance is introduced in detail. The advantages and disadvantages of this method and its application scope are described. The parameters needed in the method are collected and summarized, which can provide reference for total VOCs control in automobile industry.
Overview of Downhole Spray Dust Removal Technology
Authors: Wang Yao
Published: September 2020

Spray dust technology is one of the main methods of the coal mine dust prevention, comprehensive dust spray technology are summarized, the principle of the spray nozzle, water quality, spray dust system automation affect efficiency: common pressure type nozzle when the nozzle pressure and aperture around 8 MPa and 1.5 mm respectively when the dust efficiency is higher, magnetized water and the addition of wetting agents to further improve the efficiency of dust, spray dust system automation and intelligent development promoted the improvement of the downhole working conditions and improve work efficiency, and through the comparison of different nozzle type, compare the advantages and disadvantages, puts forward the future development direction of the nozzle.
Multi-formation track initiation method based on Density clustering
Authors: Zhang Yang , Gu Xiangqi
Published: September 2020

Aiming at the problem that the existing track initiation algorithm has a poor effect when starting multiple formation tracks under strong clutter, based on the Hough transform method and its derivative algorithm, a multi-formation Hough transform route based on density clustering is proposed. Trace start algorithm. The algorithm first combines the motion information of the target and the timing parameters of the detection points to filter the detection data set to exclude as many points as possible from non-targets. Then it uses the Hough transform to process the obtained detection point set to obtain a preliminary threshold with a lower threshold Formation track; Finally, according to the characteristics of formation goals, the overall formation track is obtained by density clustering method, which solves the problems of track crossing and chaos. Simulation results show that, compared with the standard Hough transform method and its derivative algorithm, the algorithm can start the track of formation targets under strong clutter, and has good performance.
The Application analysis of electrochemical energy storage technology in new energy power generation side
Authors: Kang Haifeng
Published: September 2020

With the continuous increase of the installed capacity of renewable energy power generation in China, and the formulation of policies about allocating certain scale energy storage system for new energy power generation. The development of the electrochemical energy storage exhibits an explosive growth trend. In this paper. The current situation and characteristics of electrochemical energy storage technology are described from three aspects: The electrochemical energy storage ‘technology, Integration technology of the energy storage system and the operation control strategy of energy storage system. Based on the typical demonstration projects of new energy equipping energy storage system. That have been implemented, the application direction. Implementation function and technical characteristics of energy storage in the field of new energy power generation side are analyzed. Furthermore. The main application functions and technology research trend of energy storage in new energy generation side are proposed. Finally, the prospect and development trend of energy storage technology in the new energy generation side in the future are prospected, four directions are given.
Research on Reliability of Chemical Power Supply for Lead-Acid Batteries Based on Wide Ambient Temperature Range
Authors: Fan Xinxin , She Shizhou , Chen Xiuguo , Wang Jianbin
Published: September 2020

This article describes the principles of the use and maintenance of lead-acid battery chemical power supplies for power systems based on a wide range of ambient temperature range, combined with the actual requirements of power systems for the monitoring and maintenance of lead-acid battery chemical power supplies Power supply reliability detection system. The system uses sensor technology and photoelectric coupling technology to collect lead-acid battery data, and determines the operating state of the battery pack by monitoring the battery pack’s single voltage, total voltage, charge and discharge current, and temperature, and innovates to achieve online balance The voltage between the battery and the battery is used to effectively maintain the operation of the battery pack, so that the operating state of the battery pack is easy to observe to minimize the possibility of accidents in the system, and the battery pack is well maintained, thereby increasing the service life of the battery pack, To achieve the purpose of saving resources and environmental protection.
The Role of Mathematical Model of Energy Storage by Power Systems Computer Aided Design / Electromagnetic Transients including DC in Power Energy Security Control
Authors: Yang Haoning
Published: September 2020

In order to discuss the application of energy storage system in power energy control, in this study, the energy storage system in small wind power generation system is taken as the research object, and the converter mathematical model in the energy storage system is built. Meanwhile, in the control state of grid-connected operation, the energy storage system is analyzed and a Power Systems Computer Aided Design / Electromagnetic Transients including Direct Current (PSCAD/EMTDC) simulation model based on Power Quality (PQ) control and Space Vector Pulse Width Modulation (SVPWM) mode is built. And when Insulated Gate Bipolar Transistor (IGBT) fails on the upper bridge arm of A-phase Alternating Current (AC) converter in the energy storage system, the changes of AC voltage, AC current, active power, and reactive power in the system and simulated. The results show that the simulation model of energy storage system established by PSCAD/EMTDC is feasible under the PQ control of grid-connected operation. In addition, fault analysis shows that the current conduction of A phase is delayed in the negative half wave, and there is a positive Direct Current (DC) bias, but the distortion of current of B phase and C phase is not significant. And the active power and reactive power remain within the set reference range. Therefore, it is possible to determine the failure of the converter IGBT of the energy storage system by whether or not the three-phase current on the AC side of the energy storage system has a DC offset. This study aims to provide theoretical basis for the follow-up fault diagnosis and system protection of the energy storage system.
Design Application and Research of Substation Comprehensive Automation System Based on Smart Grid
Authors: Bian Rui , Liu Xinying
Published: September 2020

This paper analyses the needs of smart grids for smart substation automation systems, studies and proposes a new scheme for smart substation automation systems, which applies vertical integration of intervals to reduce the implementation of protection and monitoring functions, improve system reliability and ease of maintenance; Adopting network parallel redundancy protocol to improve the reliability and standardization of information transmission in the station; applying service-oriented monitoring function to improve the level of information sharing and coordination and interaction between substations and control centres. The key technology of the system is expounded, and its application prospect is prospected. Finally, the discussion and analysis of some problems that may exist when the system is popularized and applied.
Energy efficiency of microgrid and the application of blockchain in microgrid
Authors: Mei Huawei , Li Gen
Published: September 2020

Blockchain has the characteristics of reliability, encryption, non-tampering and traceability, which can effectively solve many problems such as data isolation and uneven distribution and energy waste in China’s microgrid. Both have the characteristics of decentralization, security, transparency and intelligence, which provide a basis for the combination of the two. The exploration of the integration of the blockchain’s own characteristics with the technology of the microgrid illustrates the advantages and feasibility of the blockchain in current transactions.
Power load forecasting based on Bayesian neural network and particle swarm optimization
Authors: Gao Zhengping , Shi Jing , Li Hu , Chen Chen , Tan Jian , Liu Lixin
Published: September 2020

Accurate demand forecasting is very important for power system operation and planning. In order to forecast energy demand more accurately, a short-term power load forecasting model based on Bayesian neural network is proposed. Firstly, Pearson coefficient is used to analyze the influence of distributed energy on the load of the distribution network, and Bayesian neural network (BNN) is used to make predictions. Then, particle swarm optimization (PSO) is used to optimize the weights and thresholds of the neural network in order to obtain the best prediction effect. The experimental results show that the Pearson coefficient can quantitatively analyze the impact of distributed energy. The prediction accuracy of BNN-PSO based prediction model is significantly higher than that of other conventional methods, and the proposed prediction model has higher prediction accuracy.
Research and Application of Power Information Risk Early Warning System Based on Big Data
Authors: Tang Zhenying , An Yeteng , Li Ziqian , Xu Liyang , Li Fan , Wang He
Published: September 2020

With the increase of power equipment and business systems and the increasing complexity of IT system architecture and operation scale, the existing manual operation and maintenance mode can no longer meet the needs of business. This paper proposes an electric power information risk early warning system based on big data, which analyzes operation and maintenance data from five angles of transaction analysis, trend analysis, comparative analysis, composition analysis and comprehensive analysis. The system consists of three parts: data collection, data management, data analysis and risk early warning. By improving the operation and maintenance automation level, the system security level and operation efficiency are greatly improved.
Research on the Combination Technology of Smart Meter Status Evaluation and Acquisition Function Based on Big Data Technology
Authors: Xie Guorong , Zheng Xiaohui , Zhuang Dahai , Zheng Hong , Chen Yuanting , Gao Qiangqiang , Zhen Weishan
Published: September 2020

In order to study the key technologies suitable for large-scale intelligent electric energy meter automatic verification, the discrete verification mode is discussed from three aspects of data interaction, scheduling control, and intelligent diagnosis. First, build an application architecture for automated verification data from the perspective of multi-dimensional perception, use WCF and MQ communication modes to build a data interaction architecture, and propose a feedforward feedback integrated control mechanism; second, based on the automated verification control architecture, establish a space-time vertical and horizontal scheduling control strategy; finally. According to the category of automatic verification equipment, classify abnormal / fault categories and establish a fault knowledge base. Based on the intelligent diagnosis process of “alarm-discovery-diagnosis-processing-learning” mechanism, build an intelligent diagnosis application framework. The proposed method effectively guarantees the accuracy and reliability of the interactive data, realizes the automatic verification of space-time cooperative operation, and can effectively improve the daily operation and maintenance efficiency of large-scale automated verification.
Study on thermodynamics and kinetics of chemical vapor deposition of silicon nitride
Authors: Wang Fuyuan , Cheng Laifei , Liang Shuhua
Published: September 2020

The thermodynamics and kinetics methods had been applied to study the effects of the deposition temperature, the reaction gas ratio and the dilution gas on Si3N4 formation in the SiCl4-NH3-H2 system. The studies revealed that raising the deposition temperature would accelerate the chemical reaction and increase Si3N4 yield below 1400 K, higher temperature prompted the side reactions. With the increase of NH3 concentration, the content of Si3N4 in the reaction products also increased. As the diluent gas, H2 could accelerate the reaction and the deposition of Si3N4. However, the excess dilution gas would carry away the reaction gas and inhibit the reaction. The comprehensive effect of temperature and gas ratio on Si3N4 deposition were also analyzed by the three-dimensional figures. Finally, the optimal conditions for Si3N4 preparation were suggested.
Effect of nano-WC content on microstructures and wear resistance of laser cladding Fe-based alloy coatings
Authors: Gao Zhongtang , Ren Haibo , Yu Yuan , Guo Wei , Zhang Chuanwei , Gao Zhiming
Published: September 2020

Abstracts

Three kinds of Fe-based power with different content of nano-WC were successfully prepared on 35CrMoV steel using laser cladding technique. The influence of nano-WC on the macro-morphology, microstructure and wear resistance of Fe-based coatings under different wear conditions was investigated by scanning electron microscopy and three-dimensional non-contact surface mapping. It has been found that a lot of fine grains and equiaxed grains synthesized with the addition of nano-WC. Both the volume fraction of eutectics and wear resistance of Fe-based coatings are greatly increased with a moderate addition of nano-WC, which is attributed to the exist of the partial dissolution of hard and high temperature WC phase in the composite coating. The wear rates increase more than 2–3 times with the addition of nano-WC range from 5 wt% WC to 10 wt%WC. Hence the addition of nano-WC strengthening phase is an effective and feasible way to improve the mechanical properties, especial for the tribological properties.
Ising model with variable spin/agent strengths
Authors: Krasnytska M , Berche B , Holovatch Yu , Kenna R
Published: September 2020

We introduce varying spin strengths to the Ising model, a central pillar of statistical physics. With inhomogeneous physical systems in mind, but also anticipating interdisciplinary applications, we present the model on network structures of varying degrees of complexity. This allows us explore the interplay of two types of randomness: individual strengths of spins or agents and collective connectivity between them. We solve the model for the generic case of power-law spin strength and find that, with a self-averaging free energy, it has a rich phase diagram with new universality classes. Indeed, the degree of complexity added by quenched variable spins is on a par to that added by endowing simple networks with increasingly realistic geometries. The model is suitable for investigating emergent phenomena in many-body systems in contexts where non-identicality of spins or agents plays an essential role and for exporting statistical physics concepts beyond physics.
Laboratory Workup of Lymphoma in Adults
Authors: Kroft Steven H , Sever Cordelia E , Bagg Adam , Billman Brooke , Diefenbach Catherine , Dorfman David M , Finn William G , Gratzinger Dita A , Gregg Patricia A , Leonard John P , Smith Sonali , Souter Lesley , Weiss Ronald L , Ventura Christina B , Cheung Matthew C
Published: September 2020

Objectives

The diagnostic workup of lymphoma continues to evolve rapidly as experience and discovery lead to the addition of new clinicopathologic entities and techniques to differentiate them. The optimal clinically effective, efficient, and cost-effective approach to diagnosis that is safe for patients can be elusive, in both community-based and academic practice. Studies suggest that there is variation in practice in both settings.

The aim of this review is to

develop an evidence-based guideline for the preanalytic phase of testing, focusing on specimen requirements for the diagnostic evaluation of lymphoma.

Methods

The American Society for Clinical Pathology, the College of American Pathologists, and the American Society of Hematology convened a panel of experts in the laboratory workup of lymphoma to develop evidence-based recommendations. The panel conducted a systematic review of the literature to address key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, recommendations were derived based on the available evidence, the strength of that evidence, and key judgments as defined in the GRADE Evidence to Decision framework.

Results

Thirteen guideline statements were established to optimize specimen selection, ancillary diagnostic testing, and appropriate follow-up for safe and accurate diagnosis of indolent and aggressive lymphoma.

Conclusions

Primary diagnosis and classification of lymphoma can be achieved with a variety of specimens. Application of the recommendations can guide decisions about specimen suitability, diagnostic capabilities, and correct utilization of ancillary testing. Disease prevalence in patient populations, availability of ancillary testing, and diagnostic goals should be incorporated into algorithms tailored to each practice environment.
The role of individual variation in flowering and pollination in the reproductive success of a crepuscular buzz-pollinated plant
Authors: Soares Natalia Costa , Maruyama Pietro Kiyoshi , Staggemeier Vanessa Graziele , Morellato Leonor Patrícia Cerdeira , Araújo Márcio Silva
Published: September 2020

Background and Aims

Plant individuals within a population differ in their phenology and interactions with pollinators. However, it is still unknown how individual differences affect the reproductive success of plants that have functionally specialized pollination systems. Here, we evaluated whether plant individual specialization in phenology (temporal specialization) and in pollination (pollinator specialization) affect the reproductive success of the crepuscular-bee-pollinated plant Trembleya laniflora (Melastomataceae).

Methods

We quantified flowering activity (amplitude, duration and overlap), plant–pollinator interactions (number of flowers visited by pollinators) and reproductive success (fruit set) of T. laniflora individuals from three distinct locations in rupestrian grasslands of southeastern Brazil. We estimated the degree of individual temporal specialization in flowering phenology and of individual specialization in plant–pollinator interactions, and tested their relationship with plant reproductive success.

Key Results

Trembleya laniflora presented overlapping flowering, a temporal generalization and specialized pollinator interactions. Flowering overlap among individuals and populations was higher than expected by chance but did not affect the individual interactions with pollinators and nor their reproductive success. In contrast, higher individual generalization in the interactions with pollinators was related to higher individual reproductive success.

Conclusions

Our findings suggest that individual generalization in plant–pollinator interaction reduces the potential costs of specialization at the species level, ensuring reproductive success. Altogether, our results highlight the complexity of specialization/generalization of plant–pollinator interactions at distinct levels of organization, from individuals to populations, to species.
Difference between emergent aquatic and terrestrial monocotyledonous herbs in relation to the coordination of leaf stomata with vein traits
Authors: Zhao Wanli , Fu Peili , Liu Guolan , Zhao Ping
Published: September 2020

Emergent aquatic plants mostly occur in shallow waters and root in bottom substrates, but their leaves emerge from the water surface and are thus exposed to air, similar to the leaves of terrestrial plants. Previous studies have found coordination between leaf water supply and demand in terrestrial plants; however, whether such a coordination exists in emergent aquatic plants remains unknown. In this study, we analysed leaf veins and stomatal characteristics of 14 emergent aquatic and 13 terrestrial monocotyledonous herb species (EMH and TMH), with 5 EMH and 8 TMH belonging to Poaceae. We found that EMH had significantly higher mean leaf area, leaf thickness, stomatal density, stomatal number per vein length and major vein diameter, but lower mean major vein length per area (VLA) and total VLA than TMH. There was no significant difference in stomatal length, minor VLA and minor vein diameter between the two groups. Stomatal density and total VLA were positively correlated among the EMH, TMH, as well as the 8 Poaceae TMH species, but this correlation became non-significant when data from both the groups were pooled. Our results showed that the differences in water supply between emergent aquatic and terrestrial plants modify the coordination of their leaf veins and stomatal traits.
Contrasting growth responses to aluminium addition among populations of the aluminium accumulator Melastoma malabathricum
Authors: Mahmud Khairil , Burslem David F R P
Published: September 2020

Aluminium (Al) hyper-accumulation is a common trait expressed by tropical woody plants growing on acidic soils. Studies on Al accumulators have suggested that Al addition may enhance plant growth rates, but the functional significance of this trait and the mechanistic basis of the growth response are uncertain. This study aimed to test the hypothesis that differential growth responses to Al among populations of an Al accumulator species are associated with variation in biomass allocation and nutrient uptake. We conducted two experiments to test differential responses to the presence of Al in the growth medium for seedlings of the Al accumulator shrub Melastoma malabathricum collected from 18 populations across Peninsular Malaysia. Total dry mass and relative growth rate of dry mass were significantly greater for seedlings that had received Al in the growth medium than for control plants that did not receive Al, but growth declined in response to 5.0 mM Al addition. The increase in growth rate in response to Al addition was greater for a fast-growing than a slow-growing population. The increase in growth rate in response to Al addition occurred despite a reduction in dry mass allocation to leaves, at the expense of higher allocation to roots and stems, for plants grown with Al. Foliar concentrations of P, K, Mg and Ca increased in response to Al addition and the first axis of a PCA summarizing foliar nutrient concentrations among populations was correlated positively with seedling relative growth rates. Some populations of the Al hyper-accumulator M. malabathricum express a physiological response to Al addition which leads to a stimulation of growth up to an optimum value of Al in the growth medium, beyond which growth declines. This was associated with enhanced nutrient concentrations in leaves, which suggests that Al accumulation functions to optimize elemental stoichiometry and growth rate.
RBANS Validity Measures and the TOMM in Veterans Undergoing Seizure Monitoring
Authors: Binder Laurence , Salinsky Martin C , Storzbach Daniel , Tadrous-Furnanz Sandy K
Published: September 2020

Objective

To assess the validity of embedded measures of performance validity, the effort index (EI) and effort scale (ES) of the repeatable battery for the assessment of neuropsychological status (RBANS), in Veterans with seizures; to compare the frequency of failure on the test of memory malingering (TOMM) in patients with epileptic versus psychogenic nonepileptic seizures (PNES).

Methods

Seizure diagnosis was established for 309 participants in epilepsy monitoring units using conventional diagnostic criteria who completed both the TOMM and RBANS. The criterion for performance invalidity was failure on any trial of the TOMM. We examined multiple EI and ES cutoffs to establish optimal sensitivity and specificity.

Results

An RBANS EI cutoff score of greater than three was optimal with specificity of .98, sensitivity of.19, and positive Likelihood Ratio of 10 but was not useful when below this cutoff. Confidence intervals indicate the need for confirmation of a failed EI with another performance validity test (PVT). No ES cutoff had sufficient specificity for clinical use. Invalid TOMM performance but not invalid RBANS performance was significantly more common in persons with PNES than in persons with epileptic seizures.

Conclusions

In Veterans undergoing seizure monitoring, the RBANS EI was useful as a screen when positive that requires confirmation with another PVT. The RBANS ES was not useful. Invalid performance on the TOMM was more common in persons with PNES than in persons with epileptic seizures.
Filler Migration to the Orbit
Authors: Hamed-Azzam Shirin , Burkat Cat , Mukari Abed , Briscoe Daniel , Joshi Narish , Scawn Richard , Alon Eran , Hartstein Morris
Published: September 2020

Background

Dermal filler injections continue to grow in popularity as a method of facial rejuvenation. This increase in the number of injections performed has resulted in an increasing number of types of filler-related complications.

Objectives

We report a series of cases where dermal filler injected in the face migrated to the orbit. Treatment methods and possible mechanisms of this newly reported complication are discussed.

Methods

A retrospective, multicenter analysis was performed on patients with dermal filler migration to the orbit after facial filler injections.

Results

Seven patients (6 females, 1 male; age range, 42-67 years) presented with orbital symptoms after filler injection and were subsequently found to have dermal filler in the orbit. Four out of 7 patients underwent orbitotomy surgery, 1 patient underwent lacrimal surgery, 1 patient had strabismus surgery, and 1 patient was treated with hyalurodinase injections. All patients have remained stable postoperatively.

Conclusions

Orbital complications secondary to migrated filler may occur long after the initial procedure. Because the site of the complication is distant from the injection site, patients and physicians may not immediately make the connection. Furthermore, this may lead to unnecessary examinations and a delay in diagnosis while looking for standard orbital masses. Dermal fillers should therefore be considered in the differential diagnosis of patients presenting with new-onset orbital masses.

Level of Evidence: 4
New mixture models for decoy-free false discovery rate estimation in mass spectrometry proteomics
Authors: Peng Yisu , Jain Shantanu , Li Yong Fuga , Greguš Michal , Ivanov Alexander R. , Vitek Olga , Radivojac Predrag
Published: September 2020

Motivation

Accurate estimation of false discovery rate (FDR) of spectral identification is a central problem in mass spectrometry-based proteomics. Over the past two decades, target-decoy approaches (TDAs) and decoy-free approaches (DFAs) have been widely used to estimate FDR. TDAs use a database of decoy species to faithfully model score distributions of incorrect peptide-spectrum matches (PSMs). DFAs, on the other hand, fit two-component mixture models to learn the parameters of correct and incorrect PSM score distributions. While conceptually straightforward, both approaches lead to problems in practice, particularly in experiments that push instrumentation to the limit and generate low fragmentation-efficiency and low signal-to-noise-ratio spectra.

Results

We introduce a new decoy-free framework for FDR estimation that generalizes present DFAs while exploiting more search data in a manner similar to TDAs. Our approach relies on multi-component mixtures, in which score distributions corresponding to the correct PSMs, best incorrect PSMs and second-best incorrect PSMs are modeled by the skew normal family. We derive EM algorithms to estimate parameters of these distributions from the scores of best and second-best PSMs associated with each experimental spectrum. We evaluate our models on multiple proteomics datasets and a HeLa cell digest case study consisting of more than a million spectra in total. We provide evidence of improved performance over existing DFAs and improved stability and speed over TDAs without any performance degradation. We propose that the new strategy has the potential to extend beyond peptide identification and reduce the need for TDA on all analytical platforms.

Availabilityand implementation

https://github.com/shawn-peng/FDR-estimation.

Supplementary information

Supplementary data are available at Bioinformatics online.
A novel sequence alignment algorithm based on deep learning of the protein folding code
Authors: Gao Mu , Skolnick Jeffrey
Published: September 2020

Motivation

From evolutionary interference, function annotation to structural prediction, protein sequence comparison has provided crucial biological insights. While many sequence alignment algorithms have been developed, existing approaches often cannot detect hidden structural relationships in the ‘twilight zone’ of low sequence identity. To address this critical problem, we introduce a computational algorithm that performs protein Sequence Alignments from deep-Learning of Structural Alignments (SAdLSA, silent ‘d’). The key idea is to implicitly learn the protein folding code from many thousands of structural alignments using experimentally determined protein structures.

Results

To demonstrate that the folding code was learned, we first show that SAdLSA trained on pure α-helical proteins successfully recognizes pairs of structurally related pure β-sheet protein domains. Subsequent training and benchmarking on larger, highly challenging datasets show significant improvement over established approaches. For challenging cases, SAdLSA is ∼150% better than HHsearch for generating pairwise alignments and ∼50% better for identifying the proteins with the best alignments in a sequence library. The time complexity of SAdLSA is O(N) thanks to GPU acceleration.

Availability and implementation

Datasets and source codes of SAdLSA are available free of charge for academic users at http://sites.gatech.edu/cssb/sadlsa/.

Supplementary information

Supplementary data are available at Bioinformatics online.
Probabilistic graphlets capture biological function in probabilistic molecular networks
Authors: Doria-Belenguer Sergio , Youssef Markus K. , Böttcher René , Malod-Dognin Noël , Pržulj Nataša
Published: September 2020

Motivation

Molecular interactions have been successfully modeled and analyzed as networks, where nodes represent molecules and edges represent the interactions between them. These networks revealed that molecules with similar local network structure also have similar biological functions. The most sensitive measures of network structure are based on graphlets. However, graphlet-based methods thus far are only applicable to unweighted networks, whereas real-world molecular networks may have weighted edges that can represent the probability of an interaction occurring in the cell. This information is commonly discarded when applying thresholds to generate unweighted networks, which may lead to information loss.

Results

We introduce probabilistic graphlets as a tool for analyzing the local wiring patterns of probabilistic networks. To assess their performance compared to unweighted graphlets, we generate synthetic networks based on different well-known random network models and edge probability distributions and demonstrate that probabilistic graphlets outperform their unweighted counterparts in distinguishing network structures. Then we model different real-world molecular interaction networks as weighted graphs with probabilities as weights on edges and we analyze them with our new weighted graphlets-based methods. We show that due to their probabilistic nature, probabilistic graphlet-based methods more robustly capture biological information in these data, while simultaneously showing a higher sensitivity to identify condition-specific functions compared to their unweighted graphlet-based method counterparts.

Availabilityand implementation

Our implementation of probabilistic graphlets is available at https://github.com/Serdobe/Probabilistic_Graphlets.

Supplementary information

Supplementary data are available at Bioinformatics online.
Dementia key gene identification with multi-layered SNP-gene-disease network
Authors: Lee Dong-gi , Kim Myungjun , Son Sang Joon , Hong Chang Hyung , Shin Hyunjung
Published: September 2020

Motivation

Recently, various approaches for diagnosing and treating dementia have received significant attention, especially in identifying key genes that are crucial for dementia. If the mutations of such key genes could be tracked, it would be possible to predict the time of onset of dementia and significantly aid in developing drugs to treat dementia. However, gene finding involves tremendous cost, time and effort. To alleviate these problems, research on utilizing computational biology to decrease the search space of candidate genes is actively conducted.

In this study, we propose a framework in which diseases, genes and single-nucleotide polymorphisms are represented by a layered network, and key genes are predicted by a machine learning algorithm. The algorithm utilizes a network-based semi-supervised learning model that can be applied to layered data structures.

Results

The proposed method was applied to a dataset extracted from public databases related to diseases and genes with data collected from 186 patients. A portion of key genes obtained using the proposed method was verified in silico through PubMed literature, and the remaining genes were left as possible candidate genes.

Availability and implementation

The code for the framework will be available at http://www.alphaminers.net/.

Supplementary information

Supplementary data are available at Bioinformatics online.
Batch equalization with a generative adversarial network
Authors: Qian Wesley Wei , Xia Cassandra , Venugopalan Subhashini , Narayanaswamy Arunachalam , Dimon Michelle , Ashdown George W , Baum Jake , Peng Jian , Ando D Michael
Published: September 2020

Motivation

Advances in automation and imaging have made it possible to capture a large image dataset that spans multiple experimental batches of data. However, accurate biological comparison across the batches is challenged by batch-to-batch variation (i.e. batch effect) due to uncontrollable experimental noise (e.g. varying stain intensity or cell density). Previous approaches to minimize the batch effect have commonly focused on normalizing the low-dimensional image measurements such as an embedding generated by a neural network. However, normalization of the embedding could suffer from over-correction and alter true biological features (e.g. cell size) due to our limited ability to interpret the effect of the normalization on the embedding space. Although techniques like flat-field correction can be applied to normalize the image values directly, they are limited transformations that handle only simple artifacts due to batch effect.

Results

We present a neural network-based batch equalization method that can transfer images from one batch to another while preserving the biological phenotype. The equalization method is trained as a generative adversarial network (GAN), using the StarGAN architecture that has shown considerable ability in style transfer. After incorporating new objectives that disentangle batch effect from biological features, we show that the equalized images have less batch information and preserve the biological information. We also demonstrate that the same model training parameters can generalize to two dramatically different types of cells, indicating this approach could be broadly applicable.

Availability and implementation

https://github.com/tensorflow/gan/tree/master/tensorflow_gan/examples/stargan

Supplementary information

Supplementary data are available at Bioinformatics online.
Mitochondria and Parkinson’s disease: a complex (III) liaison
Authors: Cerri Silvia , Valente Enza Maria
Published: September 2020

This scientific commentary refers to ‘Mitochondrial UQCRC1 mutations cause autosomal dominant parkinsonism with polyneuropathy’, by Lin et al. (doi:10.1093/brain/awaa279).