bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating Uncertainties in Concrete Monoblock Railroad Tie Flexural Behavior Through Monte Carlo Simulation
Authors: Chen Yu-Szu , Jones Christopher , Peterman Robert
Published: June 2022

Research is conducted to estimate uncertainty in concrete monoblock tie flexural behavior through Monte Carlo simulation. A parameterized Moment-Curvature based computational program was developed for design and analysis of the prestressed concrete monoblock tie flexural behavior. For Monte Carlo simulation, a parameter sweep was performed to sample the expected range of input quantities. The parameter sweep program generates independent parameter combination input files, and the quantities of interest (QOIs) are computed by the Moment-Curvature based computational program. The QOIs are computed at governing locations, including: 1) moment at first crack, 2) moment at crack propagation to outer layer of reinforcement, 3) deflection at rail-center and 4) crack height at AREMA recommended design force. Several simulation input parameters were randomly varied including 1) concrete compressive strength at 28 days, 2) initial concrete strength, 3) modulus of rupture, 4) prestress level, and 5) wire position. The results of the Monte Carlo simulation allow the estimation of the probabilistic prediction of tie performance. The prediction could be used to check primary tie design before proceeding to experimental tests for design approval. This approach could be used to analyze existing tie behavior, in track, for risk analysis.
Transient Thermal Analysis of a Railroad Bearing Adapter for Optimal Placement of Onboard Sensors
Authors: Arroyo Javier E. , Tarawneh Constantine , Fuentes Arturo , Garcia Roberto A. , Gallegos Jose G.
Published: June 2022

Bearing temperature serves as an important metric used in identifying defective bearings in the rail industry. Current defect detection systems, such as the Hot Box Detectors (HBDs), are used to measure the temperature of freight car roller bearings. The HBD is a wayside device that utilizes a non-contact infrared sensor to determine the operating temperature of a railroad bearing as it passes over the HBD. Railroads analyze the data collected by HBDs to detect and flag defective bearings. If the operating temperature of a bearing surpasses a predetermined threshold, an emergency stop is initiated, and the bearing is removed from service and sent for inspection. One major drawback of HBDs is that they have been associated with many “false positives,” which has resulted in costly train stoppages and delays.

To combat that, researchers have opted to use wireless onboard sensor devices mounted directly on the bearing adapter. One such device is the wireless onboard health monitoring system developed by the University Transportation Center for Railway Safety (UTCRS) that utilizes temperature and vibration sensors to detect the condition of rolling stock. However, because the device is affixed to the bearing adapter and not the bearing itself, the strategic placement of the temperature sensor on the adapter is crucial in minimizing the thermal lag associated with the heat transfer from the bearing to the location where the temperature is measured, as this will directly affect the accuracy of the readings. By conducting a transient heat transfer finite element analysis (FEA), the estimated time-lag and the temperature distribution within the bearing adapter can be determined. To validate the accuracy of the transient FEA model, the results were compared to data acquired from laboratory testing performed on the UTCRS dynamic bearing test rigs. The results obtained in this study can be used to identify optimal anchor points for the temperature sensors on the bearing adapter, and in turn, increase the proficiency of wireless onboard sensor devices in detecting defective components.
Parameters Affecting Lateral Track Strength After Surfacing
Authors: Wilk Stephen
Published: June 2022

Over the past two years, Transportation Technology Center, Inc. (TTCI) has been investigating how tie and ballast parameters affect lateral track strength after surfacing. This investigation included both a literature review of previous work in the United States and single tie push tests (STPTs) performed under a variety of tie and ballast conditions at the Facility for Accelerated Service Testing (FAST) in Pueblo, CO. Knowing which parameters affect lateral tie strength and comparing the influence of the various parameters can help in lateral stability risk-assessments in continuously welded rail (CWR) track.

The results of both the literature review and the STPT testing showed that the parameters of post-surfacing tonnage accumulation (for ballast density), tie type, ballast shoulder width, ballast crib height, tamping lift height, and ballast particle characteristics all have a significant influence on the lateral tie strength of clean ballast. The results both emphasize the importance of considering multiple parameters when assessing track buckling risk and verifies the good practice of having both full ballast shoulders and crib heights for resisting lateral and longitudinal movements. TTCI plans to incorporate these parameters into mathematical models that predict the lateral tie strength based on measurable tie and ballast condition parameters, holistic track buckling prediction models, and risk-based rail neutral temperature (RNT) management recommendations.
Dynamic Model of Resilient Wheel and its Performance Comparison
Authors: Hu Xianting , Xue Zhao , Zhang Jimin
Published: June 2022

In order to further study the improvement effect of resilient wheel on performance of vehicle dynamic, the dynamic models of tram with resilient wheel which has concentrated force element, 4 and 20 uniform circumferential distributed force elements are established respectively. Under three modeling methods, the performance indexes of tram are compared and analyzed. The running stability of the tram with resilient wheel with 4 and 20 distributed force elements is basically consistent. The curve passing simulation results of 4 force elements and concentrated force element are quite different from those of 20 force elements. The influence of whose internal transmission mode is simplified and ignored, so 4 force elements and concentrated force element modeling methods are not suitable in the curve passing performance research.
Visualization Using Google Earth Engine Coupled With Unsupervised Learning, A Practical Approach to Detecting Track Instability
Authors: Hosseini SayedMohammad , Radmehr Ahmad , Ahmadian Mehdi
Published: June 2022

This study introduces a data visualization platform coupled to an unsupervised machine learning technique that has been developed using Google Earth Engine and OpenRailwayMap API to serve as a practical application for identifying potentially soft track segments. The goal is to provide maintenance-of-way engineers with a shortlist of locations that are highly likely to be soft, for a closer human inspection. The visualization platform is an interactive map that has been developed using Google Earth Engine by creating additional layers on Google Maps. OpenRailwayMap is also connected to this visualization platform as an independent layer to facilitate identifying rail structures. The results show that the cloud-based hybrid solutions (sensor measurements data, machine learning, and visualization) have the potential to fully automate the identification of track irregularities.
Modeling and Performance Evaluation of an RF Transceiver System at 160 MHz for Railroad Environments
Authors: Ghasemzadeh Pejman , Hempel Michael , Sharif Hamid , Omar Tarek
Published: June 2022

With the continued proliferation of wireless applications across North America’s railroad industry, it is vital to explore performance capabilities and constraints across different wireless frequency bands, including the impact of characteristics of the RF environment. In this study, our efforts are directed towards a traditionally underutilized wireless frequency band available to the railroad industry, at 160 MHz. While this frequency band is currently primarily utilized for limited voice communications, our interest is to explore it for modern data applications. This exploration includes an evaluation of end-to-end performance characteristics. In order to carry out such a study we simulate our 160 MHz communications system utilizing various channel models, e.g., FSPL, Two-Ray Ground-Reflection, Okumura and Winner2. In this communications system, our design of the transmitter and receiver addresses real-world signal impairments, such as carrier frequency and phase offset that may result from the modelled channel. We evaluate the communications system for QAM-modulated signals with different modulation orders ranging from 2 to 256. The parameters of the transmitter and receiver structures are evaluated for maximizing communication throughput while adhering to channelization, spectral mask, and power requirements. We present and discuss practical and theoretical throughput results for different channel models. The various channel models investigated in this study can be utilized to represent different railroad environments such as rural, urban and suburban areas. This study provides the basis for our efforts to fully develop a data communications system for the 160 MHz frequency band in support of vital railroad applications, such as expanding spectrum access for Positive Train Control.
Effect of Prestressing Wire Indent Geometry on Transfer Length and Tie Splitting Propensity
Authors: Beck B. Terry , Robertson Aaron A. , Peterman Robert J.
Published: June 2022

The importance of the indent geometry of prestressing wire used in the manufacture of prestressed concrete railroad ties is well known. In particular, it has been shown to have a major affect on the magnitude of the transfer length. Important parameters affecting transfer length include indent depth, indent volume and indent sidewall angle, with indent volume providing a major influence. Previous experimental evidence has revealed that the larger the indent volume, the shorter the transfer length. Furthermore, for full load bearing capacity, it is critical that the transfer length not exceed the distance to the rail seat. As a result, transfer length represents a key diagnostic parameter for evaluating the load bearing capability of prestressed concrete railroad ties, with potential for use as a quality control parameter.

Adequate transfer length alone, however, is not sufficient to guarantee tie performance. The geometry of the prestressing wire indents also plays a major role in the formation of cracking, which is of particular importance to the manufacture of concrete ties intended for high-speed rail applications. Insufficient consideration of cracking and de-bonding of prestressing wires associated with ties in service can result in severe splitting and complete tie failure. It should also be noted that while the wire specifications in standard ASTM A881 are intended to promote quality prestressed railroad tie behavior, they do not address either the detailed causes of cracking and splitting, or the specific indent features that are responsible.

Although indent geometry was known to influence both transfer length and splitting propensity, specific quantitative relationships between indent features and tie performance had not been identified. Accurate quantitative measurements of indent geometry on a statistically significant basis were simply not yet available. Recently, however, a high-resolution automated non-contact optical wire indent scanning system was developed for rapidly characterizing all relevant indent parameters including indent depth, indent width, indent sidewall angle, indent pitch, and indent volume. This paper presents, for the first time, development of reliable quantitative relationships between the relevant indent parameters and the tie performance indicators with a high degree of correlation. In addition, measurements using the new automated profiling system have revealed a new indent parameter that, on its own, shows direct correlation with transfer length. The physical concept behind this new parameter, referred to as the “Bite Per Length (BPL),” and its measured characteristics, will be presented along with its demonstrated experimental relationship to transfer length.
Feasibility and Roadmap for Applying Model Assisted Probability of Detection to Track Inspection
Authors: Baillargeon Jay , Einbinder Daniel , Bruzek Radim , Tunna John
Published: June 2022

One of the challenges facing the railway community is deciding when new inspection technologies are both accurate and reliable enough for regular use in safety assurance. New sensors and data processing techniques recently introduced in the industry have resulted in a spate of new inspection-related technologies. Track inspection technologies play an increasingly critical role in ensuring the safe and reliable operations. Therefore, railways must be sure these new inspection technologies are effective. Also, objective characterization of inspection technology effectiveness helps to establish confidence in new technology, thereby facilitating its adoption. Railways have typically relied on field confirmation of known defects or used repeatability tests to prove consistency when evaluating track inspection technologies. The Federal Railroad Administration (FRA) sponsored ENSCO to develop a formal procedure for the design and execution of performance evaluation tests. As part of this effort ENSCO explored how to apply model-assisted probability of detection (MAPOD) in the railroad industry. MAPOD combines the results from a small number of physical tests with more extensive results from computer simulation to increase confidence in the performance evaluation results. This paper presents the results of a feasibility analysis for applying MAPOD to various inspection technologies and describes a MAPOD implementation roadmap for a handheld ultrasonic rail flaw detection system.
Bringing inanimate matter to life
Transformer: The Deep Chemistry of Life and Death
Nick Lane
Norton, 2022. 400 pp.
Authors: Moran Joseph
Published: June 2022

A biochemist probes the origins and vital nature of the Krebs cycle
Can the Miocene climate inform the future?
Authors: von der Heydt Anna S.
Published: June 2022

Another climate reconstruction shows a correlation between temperature and CO
2
Elucidating the causes of neurodegeneration
Authors: Petsko Gregory A. , Small Scott A.
Published: June 2022

Investigating phase separation in neurodegeneration highlights evidence needed for causation
In Science Journals
Authors: Treisman Jessica , Zahn Laura M. , Jiang Di , Nusinovich Yevgeniya , Lavine Marc S. , VanHook Annalisa M. , Smith H. Jesse , Stern Peter , Ash Caroline , Hines Pamela J. , Grocholski Brent , Norton Melissa , Alderton Gemma , Vinson Valda , Purnell Beverly A. , Hurtley Stella M. , Isles Hannah M. , Cherezov Vadim
Published: June 2022

Highlights from the
Science
family of journals
Crocosphaeraas a Major Consumer of Fixed Nitrogen
Authors: Masuda Takako , Inomura Keisuke , Kodama Taketoshi , Shiozaki Takuhei , Kitajima Satoshi , Armin Gabrielle , Matsui Takato , Suzuki Koji , Takeda Shigenobu , Sato Mitsuhide , Prášil Ondřej , Furuya Ken
Published: June 2022

Crocosphaera watsoniiis as a key nitrogen (N) supplier in marine ecosystems, and it has been estimated to contribute up to half of oceanic N2fixation. Conversely, a recent study reported thatCrocosphaeracan assimilate combined N and proposed that unicellular diazotrophs can be competitors with non-N2fixing phytoplankton for combined N.
Effectiveness of theActivateinjury prevention exercise programme to prevent injury in schoolboy rugby union
Authors: Barden Craig , Hancock Matthew V , Stokes Keith A , Roberts Simon P , McKay Carly D
Published: June 2022

Objective

The efficaciousActivateinjury prevention exercise programme has been shown to prevent injuries in English schoolboy rugby union. There is now a need to assess the implementation and effectiveness ofActivatein the applie setting.

Methods

This quasi-experimental study used a 24-hour time-loss injury definition to calculate incidence (/1000 hours) and burden (days lost/1000 hours) for individuals whose teams adoptedActivate(usedActivateduring season) versus non-adopters. The dose-response relationship of varying levels ofActivateadherence (medianActivatesessions per week) was also assessed. Player-level rugby exposure, sessionalActivateadoption and injury reports were recorded by school gatekeepers. Rate ratios (RR), adjusted by cluster (team), were calculated using backwards stepwise Poisson regression to compare rates between adoption and adherence groups.

Results

Individuals in teams adoptingActivatehad a 23% lower match injury incidence (RR 0.77, 95% CI 0.55 to 1.07), 59% lower training injury incidence (RR 0.41, 95% CI 0.17 to 0.97) and 26% lower match injury burden (95% CI 0.46 to 1.20) than individuals on non-adopting teams. Individuals with highActivateadherence (≥3 sessions per week) had a 67% lower training injury incidence (RR 0.33, 95% CI 0.12 to 0.91) and a 32% lower match injury incidence (RR 0.68, 95% CI 0.50 to 0.92) than individuals with low adherence (<1 session per week). While 65% of teams adoptedActivateduring the season, only one team usedActivatethree times per week, using whole phases and programme progressions.

Conclusion

Activateis effective at preventing injury in English schoolboy rugby. Attention should focus on factors influencing programme uptake and implementation, ensuringActivatecan have maximal benefit.
A 132 bp deletion affecting theKCNQ1OT1gene associated with Silver-Russell syndrome clinical phenotype
Authors: Gaudet Marie Véronique , Allain Eric Pierre , Gallant Lynne M , Arts Heleen H , Ben Amor Mouna
Published: June 2022

Background

Imprinting centre 2 (IC2) in the chromosomal region 11p15.5 regulates the monoallelic expression of imprinted genes by differential methylation of paternal and maternal chromosomes. Copy number variants in IC2 are associated with Beckwith-Wiedemann syndrome and Silver-Russell syndrome (SRS). Clinical outcome of IC2 deletions seems to depend on the parental origin of the chromosome, deletion size and inclusion or exclusion of enhancer and promoter regions.

Results

A paternally inherited 132 bp deletion within theKCNQ1OT1gene was found in a proband with an SRS clinical phenotype. The patient’s father and paternal grandmother, who both carry the deletion on their maternal chromosome, are unaffected. Review of other IC2 deletions and their associated clinical presentation was useful in understanding the genetic–phenotypic correlation.

Conclusion

Only six cases have been reported with deletions involving exclusively IC2, one being identical to our proband’s 132 bp deletion. Our study, which is based on more extensive segregation data than the previous 132 bp deletion report, confirms the association of this deletion with growth restriction when paternally inherited. Remarkably, even though our patient has the same deletion, he has more pronounced phenotypic features; our findings thus suggest that some degree of clinical variability may be associated with this loss.
Cardiodiabetology: newer pharmacologic strategies for reducing cardiovascular disease risks
Authors: Wong Nathan D.
Published: June 2022

Globally, nearly 500 million adults currently have diabetes, which is expected to increase to approximately 700 million by 2040. Cardiovascular diseases (CVD), including coronary heart disease, stroke, heart failure, and peripheral arterial disease, are the principal causes of death in persons with diabetes. Key to the prevention of CVD is optimization of associated risk factors. However, few persons with diabetes are at recommended targets for key CVD risk factors including low-density lipoprotein-cholesterol (LDL-C), blood pressure, glycated hemoglobin, nonsmoking status, and body mass index. While lifestyle management forms the basis for the prevention and control of these risk factors, newer and existing pharmacologic approaches are available to optimize the potential for CVD risk reduction, particularly for the management of lipids, blood pressure, and blood glucose. For higher-risk patients, antiplatelet therapy is recommended. Medication for blood pressure, statins, and most recently, icosapent ethyl, have evidence for reducing CVD events in persons with diabetes. Newer medications for diabetes, including sodium glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide-1 receptor agonists, also reduce CVD and SGLT2 inhibitors in particular also reduce progression of kidney disease and reduce heart failure hospitalizations (HFHs). Most importantly, a multidisciplinary team is required to address the polypharmaceutical options to best reduce CVD risks persons with diabetes.
Improving CP measurement with THEIA and muon decay at rest
Authors: Ge Shao-Feng , Kong Chui-Fan , Pasquini Pedro
Published: June 2022

We explore the possibility of using the recently proposed THEIA detector to measure the $${\bar{\nu }}_\mu \rightarrow {\bar{\nu }}_e$$

ν

¯

μ

→

ν

¯

e

oscillation with neutrinos from a muon decay at rest ($$\mu $$
μ
DAR) source to improve the leptonic CP phase measurement. Due to its intrinsic low-energy beam, this $$\mu $$
μ
THEIA configuration ($$\mu $$
μ
DAR neutrinos at THEIA) is only sensitive to the genuine leptonic CP phase $$\delta _D$$

δ
D

and not contaminated by the matter effect. With detailed study of neutrino energy reconstruction and backgrounds at the THEIA detector, we find that the combination with the high-energy DUNE can significantly reduce the CP uncertainty, especially around the maximal CP violation cases $$\delta _D = \pm 90^\circ $$

δ
D

=
±

90
∘

. Both the $$\mu $$
μ
THEIA-25 with 17 kt and $$\mu $$
μ
THEIA-100 with 70 kt fiducial volumes are considered. For DUNE + $$\mu $$
μ
THEIA-100, the CP uncertainty can be better than $$8^\circ $$

8
∘

.
Complicated Dynamics of a Delayed Photonic Reservoir Computing System
Authors: Pei Lijun , Zhang Mengyu
Published: June 2022

In this paper, we consider the complicated dynamics of a delay-based photonic reservoir computing system. Since conventional computer architectures are approaching their limit, it is imperative to find new, efficient and fast ways of data processing. Photonic reservoir computing (RC) is a promising way which combines the computational capabilities of recurrent neural networks with high processing speed and energy efficiency of photonics. As the RC system is very promising, we analyze its dynamics so that we can make better use of it. In this paper, we mainly focus on its double Hopf bifurcation. We first analyze the existence of double Hopf bifurcation points. Then we use DDE-BIFTOOL to draw the bifurcation diagrams with respect to two bifurcation parameters, i.e. feedback strength [Formula: see text] and delay [Formula: see text], and give a clear picture of the double Hopf bifurcation points of the system. These figures show stability switches and the existence of double Hopf bifurcation points. Finally, we employ the method of multiple scales to obtain their normal forms, use the method of normal form to unfold and classify their local dynamics. The classification and unfolding of these double Hopf bifurcation points are obtained. Three types of double Hopf bifurcations are found. We verify the results by numerical simulations and find its complicated behavioral dynamics. For example, there exist stable equilibrium, stable periodic and quasi-periodic solutions in distinct regions. The discovered rich dynamical phenomena can help us to choose suitable values of parameters to achieve excellent performance of RC.
Research Performance and Hierarchical Staff-Mix by Rank in a Research-Oriented System: A Case Study
Authors: Ekhosuehi Virtue U.
Published: June 2022

This study examines the relationship between the research performance and the hierarchical staff-mix by rank (or staff-mix categories) for academics in a research-oriented system. A supervised learning approach is employed to classify academics on the basis of their research performance and the association between this classification and the staff-mix categories is measured using the Somer’s [Formula: see text] coefficient. Although there have been other studies on research performance for such a system based on the volume-based indicators of research performance, this is the first study that assesses the researchers’ position in the academic reward structure on the basis of research performance. The Scopus database is used as a collection of individual productivity in research. A case-study is presented on a cross-section of academics in the mathematics discipline from different federal universities in Nigeria. The results show that there is a dearth of outstanding scientists in the system and that there is a weak association between research performance and the staff-mix categories. The need for scientific collaboration by way of a continuous collegial interaction between the outstanding scientists and the emerging scholars in the system is suggested.
OntoBa: Ontology of Biomedical Analysis
Authors: Moussaoui Nabil , Dennai Abdeslem , Benali Khaled
Published: June 2022

In the medical field, ontologies are mainly used to standardise the coding of knowledge, either during the drafting phase of documents or during subsequent processing intended to give them a format which makes them usable for automatic processing. In this sense, they have a normative role analogous to the classical medical terminologies (in particular thesauri): to set up a common vocabulary and to make use of shared representations and concepts, in order to allow the interoperability of documents and medicals information systems. Medical and biomedical data play a very important role in the medical field. They solve many of the problems encountered during the diagnosis of diseases and in the prescription medical treatments. The objective of this paper is to develop ontology for the field of medical analyses in an attempt to facilitate the tasks of the various actors in the medical field, namely: doctors, laboratory assistants and patients. It also endeavours to improve the care of patients and facilitate the various acts of health professionals, the purpose of which is to aid in decision-making in the treatment of a disease. To this end, we followed the so-called METHONTOLOGY based on the phases ranging from the needs specification to the evaluation and documentation of this ontology of medical analysis.
Workings of science
Authors: Johnson Jeffrey , Odlyzko Andrew
Published: June 2022

Concerns about the trustworthiness of science are not confined to fringe groups that reject science entirely. There is substantial unease even among researchers about the reliability of peer review and the reproducibility crisis---where scientific results are not or cannot be tested by replication. Here the authors point out that such worries even apply to mathematics---for many the language of science. This is largely caused by the growing complexity of our knowledge base, where results are more complicated and investigators sometimes have to rely on the results of others that they do not fully understand. This means, as with the sciences, mathematical discoveries increasingly have to be treated as not absolutely reliable, but as part of a process of searching for the truth, and even what it means for something to true.
Workings of science
Authors: Tichy Walter
Published: June 2022

Falsifiability is a cornerstone of science. It states that scientific claims---propositions, hypotheses, theories---must be testable by experiment. A scientific claim is falsified if an empirical test contradicts it; if a claim withstands repeated attempts at falsification, it is accepted as fact. This article discusses three examples of falsified theories about software. They address the reliability of multi-version programs, the prediction of program bugs by means of software metrics, and the advantages of software models (UML). These examples demonstrate how falsifiability can eliminate incorrect theories and help reorient research and practice.
A Cost-Effective Optoelectronic Cycler for the Durability Testing of Dynamic Windows: Case Studies with Reversible Metal Electrodeposition Devices
Authors: Arvisu Lorenzo S. , Palma Alexis A. , Islam Shakirul M. , Barile Christopher J.
Published: June 2022

The implementation of dynamic windows that possess electronically tunable transparency is a promising method to increase the energy efficiency of buildings. Long-term dynamic window cyclability is a key issue that has prevented the widespread adoption of many different device architectures. In this manuscript, we have developed an inexpensive (less than $1,000) optoelectronic cycler to improve dynamic window durability testing. The cycler is programmed to process transmission data to dynamically adjust the voltage profile used for window switching throughout the course of long-term cycling experiments. We demonstrate that this optoelectronic cycler results in significantly improved cycle lives for three different dynamic window chemistries that facilitate reversible metal electrodeposition. Taken together, these results showcase a new tool for the dynamic window research community to improve device cyclability in the laboratory setting.
Urinary Podocyte Excretion Predicts Urinary Protein Selectivity and Renal Prognosis
Authors: Abe Makoto , Kaiga Akiko , Ohira Takehiro , Ishimitsu Toshihiko , Tojo Akihiro
Published: June 2022

Background. Urinary podocyte excretion is related to a reduction in glomerular podocyte numbers, glomerulosclerosis, and urinary protein selectivity. To elucidate the role of urinary podocytes in proteinuria and renal prognosis and to identify the factors that cause podocyte detachment, we examined urinary podocytes in 120 renal biopsy patients. Methods. Podocytes were identified in urinary sediments stained with fluorescent-labeled anti-podocalyxin antibodies in ten high power fields. The amounts of protein bands, separated by SDS-polyacrylamide gel electrophoresis, were calculated using an image software program and the correlation with urinary podocytes was analyzed. Podocyte surface pores were observed using a low-vacuum scanning electron microscope. The renal prognosis, including induction of hemodialysis or 30% reduction in eGFR, was investigated. Results. Urinary podocyte excretion showed a higher positive correlation with albumin excretion compared to IgG, prealbumin, and transferrin. There were no significant correlations between urinary podocyte count and low molecular weight proteins, including β2-microglobulin and α1-microglobulin. The number of podocyte surface pores was positively correlated with proteinuria, suggesting enhanced albumin transcytosis. The hemodynamic pressure on the glomerular capillary wall, including products of pulse pressure and pulse rate (water hammer pressure), was positively correlated with urinary podocyte excretion. Urinary podocyte excretion and Tamm–Horsfall protein (THP) were independent risk factors for renal prognosis but were not related to response to treatment. Conclusion. Urinary podocyte excretion was correlated with urinary albumin excretion, indicating specific albumin transport by podocytes. Podocytes were detached from the glomerular capillaries by water hammer pressure and THP was involved in the renal prognosis.
Investigation of Error Probability for Grid and Random Uniform Topologies in a Variable Noise Environment
Authors: Iskandarani Mahmoud Zaki
Published: June 2022

Investigation of the effect of topology on the communication efficiency of WSN nodes is carried out through simulation of 9 nodes in a 12 by 12 meters area. The obtained data and plots indicate that the grid topology is a more efficient and stable topology to use in comparison to the random uniform topology. The deduction is supported by probability of error as a function of error distribution values. Five different noise levels are used in the simulation (0dBm, −20 dBm, −40 dBm, −60 dBm, −80 dBm, and −100 dBm) with an output power of −10 dBm. The work shows that at −60 dBm redistribution of probability of error as a function of error values started to occur with higher level error values associated with the random uniform topology compared with the grid topology occurring at −60 dBm noise. The work also shows the relationship between received signal strength indicator (RSSI) and probability of error which decreases as RSSI increase in a similar manner as signal to noise ratio (SNR). Both RSSI and SNR are related through the mathematical model presented in the paper which is based on the path loss model. Common features between the error probability model and Gaussian interpolation function are also presented. A simplified 1-D design model is also presented to enable initial topology considerations. Criteria are also established to enable relating SNR, RSSI, topology, and WSN incremental position.
Vietnamese Sentiment Analysis under Limited Training Data Based on Deep Neural Networks
Authors: Duong Huu-Thanh , Nguyen-Thi Tram-Anh , Hoang Vinh Truong
Published: June 2022

The annotated dataset is an essential requirement to develop an artificial intelligence (AI) system effectively and expect the generalization of the predictive models and to avoid overfitting. Lack of the training data is a big barrier so that AI systems can broaden in several domains which have no or missing training data. Building these datasets is a tedious and expensive task and depends on the domains and languages. This is especially a big challenge for low‐resource languages. In this paper, we experiment and evaluate many various approaches on sentiment analysis problems so that they can still obtain high performances under limited training data. This paper uses the preprocessing techniques to clean and normalize the data and generate the new samples from the limited training dataset based on many text augmentation techniques such as lexicon substitution, sentence shuffling, back translation, syntax‐tree transformation, and embedding mixup. Several experiments have been performed for both well‐known machine learning‐based classifiers and deep learning models. We compare, analyze, and evaluate the results to indicate the advantage and disadvantage points of the techniques for each approach. The experimental results show that the data augmentation techniques enhance the accuracy of the predictive models; this promises that smart systems can be applied widely in several domains under limited training data.
Design of Enterprise Economic Management Intelligent Terminal for Big Data Application
Authors: Fang Ying , Ouyang Shaojuan
Published: June 2022

With the rapid development of world economic informatization, the research and application of intelligent terminals are more and more extensive. Through the comprehensive application of big data in modern enterprise economic management, enterprises can more accurately grasp all kinds of information and mine the deep value of data information. In the era of big data, to realize the stable growth of the enterprise economy, relevant personnel need to gradually explore the enterprise economic management mode, take the enterprise financial management as the core development project, speed up the exchange of internal and external data, improve the brand awareness of the enterprise, and let the enterprise occupy a leading position in the market. Traditional enterprise economic management methods cannot run through big data combined with intelligent terminals. Therefore, this article solves the problem of enterprise economic management under the background of big data through the design of intelligent terminals. The design of an intelligent terminal for enterprise economic management under the background of big data can provide complete information for management positions. It is not only a new attempt for enterprises to explore economic management mode but also a major innovation based on an enterprise scale.
Particles Detection System with CR-39 Based on Deep Learning
Authors: Amit Gal , Mosseri Idan , Even-Hen Ofir , Schneider Nadav , Fisher Elad , Datz Hanan , Cohen Eliahu , Nissim Noaz , Batani Dimitri
Published: June 2022

We present a novel method that we call FAINE, fast artificial
intelligence neutron detection system. FAINE automatically classifies tracks
of fast neutrons on CR-39 detectors using a deep learning model. This method
was demonstrated using a LANDAUER Neutrak® fast neutron dosimetry system,
which is installed in the External Dosimetry Laboratory (EDL) at Soreq
Nuclear Research Center (SNRC). In modern fast neutron dosimetry systems,
after the preliminary stages of etching and imaging of the CR-39 detectors,
the third stage uses various types of computer vision systems combined with
a manual revision to count the CR-39 tracks and then convert them to a dose
in mSv units. Our method enhances these modern systems by introducing an
innovative algorithm, which uses deep learning to classify all CR-39 tracks
as either real neutron tracks or any other sign such as dirt, scratches, or
even cleaning remainders. This new algorithm makes the third stage of manual
CR-39 tracks revision superfluous and provides a completely repeatable and
accurate way of measuring either neutrons flux or dose. The experimental
results show a total accuracy rate of 96.7% for the true positive tracks and
true negative tracks detected by our new algorithm against the current
method, which uses computer vision followed by manual revision. This
algorithm is now in the process of calibration for both alpha-particles
detection and fast neutron spectrometry classification and is expected to be
very useful in analyzing results of proton-boron11 fusion experiments. Being
fully automatic, the new algorithm will enhance the quality assurance and
effectiveness of external dosimetry, will lower the uncertainty for the
reported dose measurements, and might also enable lowering the system’s
detection threshold.
Physicochemical Properties and Floral Sources of Honey Produced in Marsabit Forest Reserve, Northern Kenya
Authors: Muhati Godwin Leslie , Warui Mary Wanjiru
Published: June 2022

This study assessed the physicochemical properties and floral sources (botanical origin) of sixteen honey samples collected from beekeepers in five clusters surrounding the Marsabit Forest Reserve (MFR) in northern Kenya. Analysis of Variance (ANOVA) was used to determine the differences in physicochemical properties of honey, while relative frequencies of pollen types in each honey sample were calculated and expressed as percentages. The mean physicochemical parameter values were moisture, 18.09 ± 0.86%; total reducing sugars, 73.03 ± 1.00%; apparent sucrose, 2.43 ± 0.66%; acidity, 20.25 ± 0.86 meq/kg; hydroxymethylfurfural (HMF), 11.01 ± 5.39 mg/kg. All parameter values were within limits set in the East African Standard, Codex Alimentarius, and the European Union directive standards for honey. Pollen analysis showed a total of 108 pollen types representing 55 families and 97 genera. The highest represented family in the honey samples was Euphorbiaceae. The study recommends the further uptake of apiculture and the training and facilitation of honey producers, processors, and traders on quality assurance and certification of honey to make them competitive in the markets beyond the local level.
Combined Effect of Zinc Oxide Nanoparticles and Bacteria on Osmolytes and Antioxidative Parameters of Rice (Oryza sativa L.) Plant Grown in Heavy Metal-Contaminated Water
Authors: Akhtar Nazneen , Khan Sehresh , Rehman Shafiq Ur , Rha Eui Shik , Jamil Muhammad
Published: June 2022

With the advancement in nanotechnology, the use of nanoparticles has been enhanced dramatically in biomedical, agriculture, and industrial processes. However, the combined effect of nanoparticles and bacteria on plant growth in heavy metal (Cd, Cr, Cu, and Pb)-contaminated wastewater is greatly limited. Therefore, the recent work was designed to determine the synergistic impact of green synthesized zinc oxide nanoparticles (ZnO-NPs) (5-10 mg/L) and Bacillus spp. ( Bacillus cereus and Lysinibacillus macroides) on the physiological and biochemical activities of rice seedlings under heavy metal- (HM-) contaminated water. The results revealed that germination percentage (36%), root-shoot length (5.11 and 3.41 cm), fresh shoot-root weight (0.05 and 0.011 g), dry shoot-root weight (0.008 and 0.009 g), Chl a, Chl b, and carotenoid (5.4, 3.2 mg/g, and 4.3  μg/g), total soluble sugar (TSS) (26.44 mg/g), and total soluble protein (TSP) (21.99 mg/g) content considerably reduced in the plant tissues while combined impact of bacteria and ZnO NPs alleviates HM stress in contaminated water and improved seed germination (70%), root-shoot length (9.93 and 11.82 cm), fresh shoot-root weight (0.125 and 0.131 g), dry shoot-root weight (0.0532 and 0.042 g), Chl a, Chl b, and carotenoid (18.8, 13.9 mg/g, and 17.1  μg/g), TSS (57.651 mg/g), and TSP (47.990 mg/g) content. Lipid peroxidation induced by HM stress increased the amount of thiobarbituric acid reactive substances (TBRAS) (17.321 nM/mg) and hydrogen peroxide (H2O2) content (14.5  μM/g), stress markers such as glycine betaine (GB) (40.731 mg/g) and proline (Pro) (38.812  μmol/g) and antioxidant enzymes (SOD, POD, CAT, and APX) (180.87 U/mg, 450.677, 0.1066, and 0.631  μm/min/mg) under HM stress while the combined effect of ZnO NPs and bacteria reduced TBRAS (5.431 nM/mg), H2O2 content (2.25  μM/g), stress markers such as GB (24.731 mg/g) and Pro (18.811  μmol/g), and SOD, POD, CAT, and APX (187.53, 194.88, 0.061, and 0.271  μm/min/mg) contents. The present study suggested a potential role of combined impact of nanoparticles and bacteria in remediation of heavy metals from wastewater by improving plant growth.
Predictive Maintenance Model Based on Multisensor Data Fusion of Hybrid Fuzzy Rough Set Theory Feature Selection and Stacked Ensemble for Fault Classification
Authors: Buabeng Albert , Simons Anthony , Frempong Nana Kena , Ziggah Yao Yevenyo
Published: June 2022

With the rising demand for integrated and autonomous systems in the field of engineering, efficient frameworks for instant detection of performance anomalies are imperative for improved productivity and cost-effectiveness. This study proposes a systematic predictive maintenance framework based on the hybrid multisensor fusion technique of fuzzy rough set feature selection and stacked ensemble for the efficient classification of fault conditions characterised by uncertainties. First, a feature vector of time-domain features was extracted from 17 multiple sensor signals. Then, a comparative study of six different Fuzzy Rough Set Feature Selection (FRFS) methods was employed to select the various combinations of optimal feature subsets for various faults classification tasks. The determined optimal feature subsets then served as inputs for training the stacked ensemble (ESB(STK)). In the ESB(STK), Support Vector Machine (SVM), Multilayer Perceptron (MLP),

k

-Nearest Neighbour (

k

-NN), C4.5 Decision Tree (C4.5 DT), Logistic Regression (LR), and Linear Discriminant Analysis (LDA) served as the base classifiers while the LR was selected to be the metaclassifier. The proposed hybrid framework (FRFS-ESB(STK)) improved the classification accuracy with the selected combinations of optimal feature subset size whiles reducing the computational cost, overfitting, training runtime, and uncertainty in modelling. Overall analyses showed that the FRFS-ESB(STK) proved to be generalisable and versatile in the classification of all conditions of four monitored hydraulic components (i.e., cooler, valve, accumulator, and internal pump leakage) when compared with the six base classifiers (standalone) and three existing ensemble classifiers (Stochastic Gradient Boosting (SGB), Ada Boost (ADB), and Bagging (BAG)). The proposed FRFS-ESB(STK) showed an average improvement of 11.28% and 0.88% test accuracies when classifying accumulator and pump conditions, respectively, whiles 100% classification rates were obtained for both cooler and valve.
Analysis of PETCT Imaging Diagnosis of Heart Failure Improved by Intelligent Sensor in Exercise
Authors: Li Jingzhe
Published: June 2022

The incidence of cardiovascular disease is closely related to the heart, and the quality of the heart function directly affects the health of the cardiovascular system. At present, the prevention and treatment of diseases no longer rely solely on drug treatment, and people are increasingly aware of the importance of exercise. Therefore, it is very important to find an economical and effective way to improve cardiovascular function in patients with heart failure. The purpose of this paper is to analyze and discuss the PETCT imaging diagnosis of heart failure improved by Tai Chi exercise based on intelligent sensors. First, it summarizes the origin, characteristics, and exercise rules of simplified Taijiquan, introduces the basic etiology and pathophysiology of cardiac insufficiency, studies the pathogenesis of chronic cardiac insufficiency, and understands the influence of exercise therapy on chronic cardiac insufficiency, combining information fusion and smart sensors to observe the effect of Taijiquan’s short-term intervention on mild to moderate chronic cardiac insufficiency and the diagnosis of nuclear medicine PET and CT. The results of the experiment showed that there were 317 cases of Taijiquan group III patients before treatment and 413 cases after treatment. Tai Chi can not only improve the health-related quality of life of CHF patients but also can effectively improve the restricted activities of CHF patients. Exercise endurance is significantly improved. According to the clinical treatment principles and rules of CHF, it is an excellent auxiliary treatment method. The significance of auxiliary Taijiquan therapy is not only to improve heart function and quality of life but also to have a positive impact on the patient’s mental state, which meets the needs of the bio-psycho-social medical model, and also inspires and assists the research progress of other diseases.
The Improved Precoding Method in the VLC-Based Intelligent Transportation System
Authors: li Shilin , Cheng Y. , Zhou T.Y. , Liang P.Y.
Published: June 2022

Visible light communication (VLC) transmission system, combined with lighting and communication, has a great application value in the field of intelligent transportation. To efficiently improve the performance of VLC-based intelligent transportation system, an improved precoding scheme is proposed and experimentally verified. Partial data-carrying subcarrier (PDS)-precoding scheme can balance the signal-to-noise ratio (SNR) and combat frequency selective fading (FSF) in the VLC-based intelligent transportation system. For ∼3.52 Gb/s DMT-VLC system with 1.9-m free space transmission, the OCT-based PDS-precoding signal shows almost the same BER performance as full data-carrying subcarriers precoding ones. Compared with the conventional scheme, the BER is reduced from 2e-3 to 8.14e-5 by using the proposed PDS-precoding. PDS-precoding is a nice choice to degrade the unbalanced damage for data-carrying subcarriers (SCs) in the bandwidth-limited VLC-based intelligent transportation system.