bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Plant Growth Promoting Microorganisms on Pepper Plants Infected with Tomato Brown Rugose Fruit Virus
Authors: Ragasová Lucia , Hakalová Eliška , Ferby Vojtěch , Čechová Jana , Klapcová Gabriela , Pokluda Robert
Published: August 2022

Symbiotic interaction between plants and microorganisms in the rhizosphere is an important factor affecting plant growth and fitness. Arbuscular mycorrhiza fungi symbiosis increases resistance of the plants to stress factors, including pathogens. Tomato brown rugose fruit virus (ToBRFV) is an important destructive virus damaging tomatoes and peppers with losses that can reach 100%. It is listed on the list of current quarantine organisms in the Czech Republic. The aim of this study was to evaluate influence of root colonization with Funneliformis mosseae or/and Azospirillum brasilense on ToBRFV symptoms and viral titre reduction. Plants treated with arbuscular mycorhizal fungi (AMF) had lower symptom emergence after 14 dpi, however there was no difference in symptoms emergence after 21 dpi within all treatments. The highest colonization intensity by Funneliformis mosseae was detected in ToBRFV negative plants treated with both AMF and Azospirillum (AZO) and the lowest in ToBRFV positive plants with the same treatment (AMF + AZO). Colonization intensity of Azospirillum brasilense in all treated variants went from 20% to 41%. Results suggest that the combination of those two beneficial microorganisms in ToBRFV-infected plants negatively affected AMF colonization.
Analysis of Factors Affecting Neutralizing Antibody Production after COVID-19 Vaccination Using Newly Developed Rapid Point-of-Care Test
Authors: Shim Hyeon Woo , Shin Jae hang , Shin Shang Cheol , Lee Hwa Jung , So Kyung Soon , Lee So Young , Jun Jae Woo , Seo Jeong Ku , Lee Hwa Seop , Lee Suk Young , Kim Seung Hyun , Kim Sun Jong , Kim Kyoung-Chol , Ryu Gyu Ha
Published: August 2022

(1) Objective: To investigate the factors that affect rates of neutralizing antibody production and duration after vaccination using the newly developed SARS-CoV-2 POCT. (2) Methods: The production of immunoglobulin and neutralizing antibody in clinical subjects who completed various vaccines was analyzed using the POCT, the semi-quantitative was interpreted by measurement application, and the quantified neutralizing antibody titers were using the ELISA. (3) Results: According to the clinical performance analysis of the POCT, the clinical sensitivity and the specificity were 96.8% (90/93) and 97.7% (167/171), respectively, for the S1 RBD IgG antibody. The clinical sensitivity was 92.22% (83/90), and the clinical specificity was 100.00% (174/174) for neutralizing antibodies. Factors influencing antibody production were analyzed using the whole blood of the five types of second-completed vaccinators (N = 736, 20–80 years old). General and neutralizing antibody and showed significant differences in age (p < 0.0001), vaccine type (p < 0.0001), inoculation interval (p < 0.0001), pain score (p < 0.0001), diabetes (p < 0.0001), and hypertension (p = 0.002). The gender (p = 0.021) and chronic fatigue (p = 0.02) did not show the significance. (4) Conclusions: An acquisition of immunoglobulin and neutralizing antibody varies according to vaccine type, age, days after vaccination, pain degree after vaccination, and underlying diseases. The POCT used in this study will be utilized for clinical recommendations such as deciding whether to receive additional vaccines through the immediate rapid determination of neutralizing antibody generation in the clinical site.
Salivary Gland Toxicity of PSMA-Targeted Radioligand Therapy with 177Lu-PSMA and Combined 225Ac- and 177Lu-Labeled PSMA Ligands (TANDEM-PRLT) in Advanced Prostate Cancer: A Single-Center Systematic Investigation
Authors: Langbein Thomas , Kulkarni Harshad R. , Schuchardt Christiane , Mueller Dirk , Volk Gerd Fabian , Baum Richard P.
Published: August 2022

Purpose: PSMA-targeted radioligand therapy (PRLT) is a promising treatment option for patients with metastatic castration-resistant prostate cancer (mCRPC). However, a high uptake of the radiopharmaceutical in the salivary glands (SG) can lead to xerostomia and becomes dose-limiting for 225Ac-PSMA-617. This study investigated the sialotoxicity of 177Lu-PSMA-I&T/-617 monotherapy and co-administered 225Ac-PSMA-617 and 177Lu-PSMA-617 (Tandem-PPRLT). Methods: Three patient cohorts, that had undergone 177Lu-PSMA-I&T/-617 monotherapy or Tandem-PRLT, were retrospectively analyzed. In a short-term cohort (91 patients), a xerostomia assessment (CTCAE v.5.0), a standardized questionnaire (sXI), salivary gland scintigraphy (SGS), and SG SUVmax and the metabolic volume (MV) on 68Ga-PSMA-11-PET/CT were obtained before and after two cycles of 177Lu-PSMA-I&T/-617. In a long-term cohort, 40 patients were similarly examined. In a Tandem cohort, the same protocol was applied to 18 patients after one cycle of Tandem-PRLT. Results: Grade 1 xerostomia in the short-term follow-up was observed in 22 (24.2%) patients with a worsening of sXI from 7 to 8 at (p < 0.05). In the long-term cohort, xerostomia grades 1 to 2 occurred in 16 (40%) patients. SGS showed no significant changes, but there was a decline of the MV of all SGs. After Tandem-PRLT, 12/18 (66.7%) patients reported xerostomia grades 1 to 2, and the sXI significantly worsened from 9.5 to 14.0 (p = 0.005), with a significant reduction in the excretion fraction (EF) and MV of all SGs. Conclusion: 177Lu-PSMA-I&T/-617 causes only minor SG toxicity, while one cycle of Tandem-PRLT results in a significant SG impairment. This standardized protocol may help to objectify and quantify SG dysfunction.
Artificial Intelligence in Eye Disease: Recent Developments, Applications, and Surveys
Authors: Han Jae-Ho
Published: August 2022

Artificial intelligence (AI) has expanded by finding applications in medical diagnosis for clinical support systems [...]
Reference Interval for the Axis-Shield Clinical Chemistry Heparin-Binding Protein Assay
Authors: Yoon Sumi , Hur Mina , Kim Hanah , Moon Hee-Won , Yun Yeo-Min
Published: August 2022

The newly developed Axis-Shield clinical chemistry heparin-binding protein (HBP) assay (Axis-Shield Diagnostics Ltd., Dundee, Scotland) can be applied to fully automated platforms. We aimed to establish a reference interval (RI) of HBP using the Axis-Shield HBP assay, and to evaluate the analytical performance of this assay. An RI was established in 212 sodium citrated plasma samples using the non-parametric method (2.5th and 97.5th percentiles). Precision, linearity, and carry-over were evaluated according to the Clinical and Laboratory Standards Institute guidelines. The RI of HBP was between 5.3 ng/mL and 171.0 ng/mL, which could be applied regardless of gender and age. Percentage coefficients of variations (%CVs) of repeatability and within-laboratory precision were 4.9% and 6.3%, respectively, for low-concentration control and 1.6% and 3.0%, respectively, for high-concentration control. The linearity was excellent (coefficient of determination (R2) = 0.99), and the carry-over rate was negligible (0.05%). This is the first study to establish an RI of HBP using the newly developed and fully automated Axis-Shield HBP assay. The Axis-Shield HBP assay showed an acceptable level of analytical performance and could be used to measure HBP concentrations effectively in routine clinical practice. Further studies are awaited to evaluate the clinical utility of HBP using this automated assay.
K-Means Clustering for Shock Classification in Pediatric Intensive Care Units
Authors: Rollán-Martínez-Herrera María , Kerexeta-Sarriegi Jon , Gil-Antón Javier , Pilar-Orive Javier , Macía-Oliver Iván
Published: August 2022

Shock is described as an inadequate oxygen supply to the tissues and can be classified in multiple ways. In clinical practice still, old methods are used to discriminate these shock types. This article proposes the application of unsupervised classification methods for the stratification of these patients in order to treat them more appropriately. With a cohort of 90 patients admitted in pediatric intensive care units (PICU), the k-means algorithm was applied in the first 24 h data since admission (physiological and analytical variables and the need for devices), obtaining three main groups. Significant differences were found in variables used (e.g., mean diastolic arterial pressure p < 0.001, age p < 0.001) and not used for training (e.g., EtCO2 min p < 0.001, Troponin max p < 0.01), discharge diagnosis (p < 0.001) and outcomes (p < 0.05). Clustering classification equaled classical classification in its association with LOS (p = 0.01) and surpassed it in its association with mortality (p < 0.04 vs. p = 0.16). We have been able to classify shocked pediatric patients with higher outcome correlation than the clinical traditional method. These results support the utility of unsupervised learning algorithms for patient classification in PICU.
Reversible Tumor Progression Induced by a Dexamethasone Course for Severe COVID-19 during Immune Checkpoint Inhibitor Treatment
Authors: Gougis Paul , Abbar Baptiste , Benzimra Julie , Vozy Aurore , Spano Jean-Philippe , Campedel Luca
Published: August 2022

Immunotherapies and immune checkpoint inhibitors (ICI) represent the latest revolution in oncology. Several studies have reported an association between the use of corticosteroids and poorer outcomes for patients treated with ICIs. However, it has been never established whether corticoid-induced tumor progression under ICI treatment could be reversible. We report herein transient tumor progression induced by dexamethasone for a patient treated with pembrolizumab for metastatic bladder cancer. An 82-year-old man was treated with pembrolizumab as a second-line treatment for metastatic urothelial carcinoma with stable disease for 8 months as the best tumoral response. He experienced severe coronavirus disease 2019 (COVID-19) infection and was treated with high-dose dexamethasone for ten days according to the RECOVERY protocol. Following this episode, radiological CT-scan evaluation showed tumor progression. Pembrolizumab was maintained, and subsequent radiological evaluation showed tumor shrinkage. This case highlights that the antagonistic effect of glucocorticoids with ICI efficacy is transient and can be reverted when corticoids are withdrawn. Clinicians should be aware that tumor progression in the context of the intercurrent use of systemic corticosteroids can be temporary and should be interpreted with caution, and ICI continuation could be considered for some patients. Insights: The antagonistic effect of glucocorticoids with ICI efficacy is transient and can be reverted when corticoids are withdrawn. Tumor progression in the context of the intercurrent use of systemic corticosteroids can be temporary and should be interpreted with caution, and ICI continuation could be considered for some patients.
Testing Drones as a Tool for Surveying Lizards
Authors: Monks Joanne , Wills Harriet , Knox Carey
Published: August 2022

A lack of effective methods for sampling lizards in terrain that is inaccessible to human observers limits our knowledge of their ecology and conservation needs. Drones are increasingly being used in wildlife monitoring, but their potential use for surveying lizards has not been evaluated. We investigated: (1) the detectability of model lizards using a drone relative to a human observer, and (2) the response of four lizard species to an approaching drone in three habitat types. Model lizards placed in potential basking positions within a defined search area were detected by both the drone operator and human observer, but the probability of detection was lower with the drone. Jewelled geckos (Naultinus gemmeus) in shrubland and grand skinks (Oligosoma grande) in rocky habitats showed surprisingly little reaction to the approaching drone, enabling close approaches (means of 59 cm and 107 cm, respectively) and accurate species identification with photos taken by the drone camera. For highly patterned jewelled geckos, identification was also possible to individual level. However, the drone was unsuccessful at detecting two alpine skink species in a near-vertical cliff habitat. Collectively, our results suggest that drones have potential as a tool for detecting small-bodied lizards in habitats inaccessible to human observers.
Pseudoclassical Dynamics of the Kicked Top
Authors: Zou Zhixing , Wang Jiao
Published: August 2022

The kicked rotor and the kicked top are two paradigms of quantum chaos. The notions of quantum resonance and the pseudoclassical limit, developed in the study of the kicked rotor, have revealed an intriguing and unconventional aspect of classical–quantum correspondence. Here, we show that, by extending these notions to the kicked top, its rich dynamical behavior can be appreciated more thoroughly; of special interest is the entanglement entropy. In particular, the periodic synchronization between systems subject to different kicking strength can be conveniently understood and elaborated from the pseudoclassical perspective. The applicability of the suggested general pseudoclassical theory to the kicked rotor is also discussed.
Directed Brain Network Analysis for Fatigue Driving Based on EEG Source Signals
Authors: Qin Yingmei , Hu Ziyu , Chen Yi , Liu Jing , Jiang Lijie , Che Yanqiu , Han Chunxiao
Published: August 2022

Fatigue driving is one of the major factors that leads to traffic accidents. Long-term monotonous driving can easily cause a decrease in the driver’s attention and vigilance, manifesting a fatigue effect. This paper proposes a means of revealing the effects of driving fatigue on the brain’s information processing abilities, from the aspect of a directed brain network based on electroencephalogram (EEG) source signals. Based on current source density (CSD) data derived from EEG signals using source analysis, a directed brain network for fatigue driving was constructed by using a directed transfer function. As driving time increased, the average clustering coefficient as well as the average path length gradually increased; meanwhile, global efficiency gradually decreased for most rhythms, suggesting that deep driving fatigue enhances the brain’s local information integration abilities while weakening its global abilities. Furthermore, causal flow analysis showed electrodes with significant differences between the awake state and the driving fatigue state, which were mainly distributed in several areas of the anterior and posterior regions, especially under the theta rhythm. It was also found that the ability of the anterior regions to receive information from the posterior regions became significantly worse in the driving fatigue state. These findings may provide a theoretical basis for revealing the underlying neural mechanisms of driving fatigue.
A Pattern Dictionary Method for Anomaly Detection
Authors: Sabeti Elyas , Oh Sehong , Song Peter X. K. , Hero Alfred O.
Published: August 2022

In this paper, we propose a compression-based anomaly detection method for time series and sequence data using a pattern dictionary. The proposed method is capable of learning complex patterns in a training data sequence, using these learned patterns to detect potentially anomalous patterns in a test data sequence. The proposed pattern dictionary method uses a measure of complexity of the test sequence as an anomaly score that can be used to perform stand-alone anomaly detection. We also show that when combined with a universal source coder, the proposed pattern dictionary yields a powerful atypicality detector that is equally applicable to anomaly detection. The pattern dictionary-based atypicality detector uses an anomaly score defined as the difference between the complexity of the test sequence data encoded by the trained pattern dictionary (typical) encoder and the universal (atypical) encoder, respectively. We consider two complexity measures: the number of parsed phrases in the sequence, and the length of the encoded sequence (codelength). Specializing to a particular type of universal encoder, the Tree-Structured Lempel–Ziv (LZ78), we obtain a novel non-asymptotic upper bound, in terms of the Lambert W function, on the number of distinct phrases resulting from the LZ78 parser. This non-asymptotic bound determines the range of anomaly score. As a concrete application, we illustrate the pattern dictionary framework for constructing a baseline of health against which anomalous deviations can be detected.
Learning PDE to Model Self-Organization of Matter
Authors: Brandao Eduardo , Colombier Jean-Philippe , Duffner Stefan , Emonet Rémi , Garrelie Florence , Habrard Amaury , Jacquenet François , Nakhoul Anthony , Sebban Marc
Published: August 2022

A self-organization hydrodynamic process has recently been proposed to partially explain the formation of femtosecond laser-induced nanopatterns on Nickel, which have important applications in optics, microbiology, medicine, etc. Exploring laser pattern space is difficult, however, which simultaneously (i) motivates using machine learning (ML) to search for novel patterns and (ii) hinders it, because of the few data available from costly and time-consuming experiments. In this paper, we use ML to predict novel patterns by integrating partial physical knowledge in the form of the Swift-Hohenberg (SH) partial differential equation (PDE). To do so, we propose a framework to learn with few data, in the absence of initial conditions, by benefiting from background knowledge in the form of a PDE solver. We show that in the case of a self-organization process, a feature mapping exists in which initial conditions can safely be ignored and patterns can be described in terms of PDE parameters alone, which drastically simplifies the problem. In order to apply this framework, we develop a second-order pseudospectral solver of the SH equation which offers a good compromise between accuracy and speed. Our method allows us to predict new nanopatterns in good agreement with experimental data. Moreover, we show that pattern features are related, which imposes constraints on novel pattern design, and suggest an efficient procedure of acquiring experimental data iteratively to improve the generalization of the learned model. It also allows us to identify the limitations of the SH equation as a partial model and suggests an improvement to the physical model itself.
Stochastic Control for Bayesian Neural Network Training
Authors: Winkler Ludwig , Ojeda César , Opper Manfred
Published: August 2022

In this paper, we propose to leverage the Bayesian uncertainty information encoded in parameter distributions to inform the learning procedure for Bayesian models. We derive a first principle stochastic differential equation for the training dynamics of the mean and uncertainty parameter in the variational distributions. On the basis of the derived Bayesian stochastic differential equation, we apply the methodology of stochastic optimal control on the variational parameters to obtain individually controlled learning rates. We show that the resulting optimizer, StochControlSGD, is significantly more robust to large learning rates and can adaptively and individually control the learning rates of the variational parameters. The evolution of the control suggests separate and distinct dynamical behaviours in the training regimes for the mean and uncertainty parameters in Bayesian neural networks.
A Useful Criterion on Studying Consistent Estimation in Community Detection
Authors: Qing Huan
Published: August 2022

In network analysis, developing a unified theoretical framework that can compare methods under different models is an interesting problem. This paper proposes a partial solution to this problem. We summarize the idea of using a separation condition for a standard network and sharp threshold of the Erdös–Rényi random graph to study consistent estimation, and compare theoretical error rates and requirements on the network sparsity of spectral methods under models that can degenerate to a stochastic block model as a four-step criterion SCSTC. Using SCSTC, we find some inconsistent phenomena on separation condition and sharp threshold in community detection. In particular, we find that the original theoretical results of the SPACL algorithm introduced to estimate network memberships under the mixed membership stochastic blockmodel are sub-optimal. To find the formation mechanism of inconsistencies, we re-establish the theoretical convergence rate of this algorithm by applying recent techniques on row-wise eigenvector deviation. The results are further extended to the degree-corrected mixed membership model. By comparison, our results enjoy smaller error rates, lesser dependence on the number of communities, weaker requirements on network sparsity, and so forth. The separation condition and sharp threshold obtained from our theoretical results match the classical results, so the usefulness of this criterion on studying consistent estimation is guaranteed. Numerical results for computer-generated networks support our finding that spectral methods considered in this paper achieve the threshold of separation condition.
Entropy Generation Analysis in Turbulent Reacting Flows and Near Wall: A Review
Authors: Sadiki Amsini , Agrebi Senda , Ries Florian
Published: August 2022

This paper provides a review of different contributions dedicated thus far to entropy generation analysis (EGA) in turbulent combustion systems. We account for various parametric studies that include wall boundedness, flow operating conditions, combustion regimes, fuels/alternative fuels and application geometries. Special attention is paid to experimental and numerical modeling works along with selected applications. First, the difficulties of performing comprehensive experiments that may support the understanding of entropy generation phenomena are outlined. Together with practical applications, the lumped approach to calculate the total entropy generation rate is presented. Apart from direct numerical simulation, numerical modeling approaches are described within the continuum formulation in the framework of non-equilibrium thermodynamics. Considering the entropy transport equations in both Reynolds-averaged Navier–Stokes and large eddy simulation modeling, different modeling degrees of the entropy production terms are presented and discussed. Finally, exemplary investigations and validation cases going from generic or/and canonical configurations to practical configurations, such as internal combustion engines, gas turbines and power plants, are reported. Thereby, the areas for future research in the development of EGA for enabling efficient combustion systems are highlighted. Since EGA is known as a promising tool for optimization of combustion systems, this aspect is highlighted in this work.
Temperature Dependence of Structural Relaxation in Glass-Forming Liquids and Polymers
Authors: Novikov Vladimir N. , Sokolov Alexei P.
Published: August 2022

Understanding the microscopic mechanism of the transition of glass remains one of the most challenging topics in Condensed Matter Physics. What controls the sharp slowing down of molecular motion upon approaching the glass transition temperature Tg, whether there is an underlying thermodynamic transition at some finite temperature below Tg, what the role of cooperativity and heterogeneity are, and many other questions continue to be topics of active discussions. This review focuses on the mechanisms that control the steepness of the temperature dependence of structural relaxation (fragility) in glass-forming liquids. We present a brief overview of the basic theoretical models and their experimental tests, analyzing their predictions for fragility and emphasizing the successes and failures of the models. Special attention is focused on the connection of fast dynamics on picosecond time scales to the behavior of structural relaxation on much longer time scales. A separate section discusses the specific case of polymeric glass-forming liquids, which usually have extremely high fragility. We emphasize the apparent difference between the glass transitions in polymers and small molecules. We also discuss the possible role of quantum effects in the glass transition of light molecules and highlight the recent discovery of the unusually low fragility of water. At the end, we formulate the major challenges and questions remaining in this field.
Dynamics of Information Flow between the Chinese A-Share Market and the U.S. Stock Market: From the 2008 Crisis to the COVID-19 Pandemic Period
Authors: Nie Chun-Xiao , Xiao Jing
Published: August 2022

The relationship between the Chinese market and the US market is widely concerned by researchers and investors. This paper uses transfer entropy and local random permutation (LRP) surrogates to detect the information flow dynamics between two markets. We provide a detailed analysis of the relationship between the two markets using long-term daily and weekly data. Calculations show that there is an asymmetric information flow between the two markets, in which the US market significantly affects the Chinese market. Dynamic analysis based on weekly data shows that the information flow evolves, and includes three significant periods between 2004 and 2021. We also used daily data to analyze the dynamics of information flow in detail over the three periods and found that changes in the intensity of information flow were accompanied by major events affecting the market, such as the 2008 financial crisis and the COVID-19 pandemic period. In particular, we analyzed the impact of the S&P500 index on different industry indices in the Chinese market and found that the dynamics of information flow exhibit multiple patterns. This study reveals the complex information flow between two markets from the perspective of nonlinear dynamics, thereby helping to analyze the impact of major events and providing quantitative analysis tools for investment practice.
How and under Which Conditions Can We Best Combine Research on School Effectiveness with Research on School Improvement? Establishing Connections Using the Dynamic Approach to School Improvement
Authors: Antoniou Panayiotis , Kyriakides Leonidas , Charalambous Evi
Published: August 2022

This paper aims to discuss how and under which conditions can we best combine research on School Effectiveness with research on School Improvement by utilizing the Dynamic Approach (DA) to School Improvement. We firstly elaborate on the difficulties that exist in trying to merge results from research on School Effectiveness with research on School Improvement. Then, we discuss the need and potential benefit from merging the two research strands, and finally we propose a fruitful merging with reference to the DA framework. Studies that have utilized the DA are also presented and their implications for research, policy and practice are discussed. The last section summarizes the results of the studies that have utilized the DA to highlight conditions that could facilitate a productive merging of the School Effectiveness and School Improvement research.
Gamification in Physical Education: A Systematic Review
Authors: Arufe-Giráldez Víctor , Sanmiguel-Rodríguez Alberto , Ramos-Álvarez Oliver , Navarro-Patón Rubén
Published: August 2022

Background: In the last 10 years, gamification has entered the educational field incrementally. The subject of Physical Education has been one of the scenarios where multiple gamified learning environments were carried out. The objective of this work was to evaluate and analyze the scientific evidence of the pedagogical proposals and didactic experiences that have used gamification in the Physical Education classroom in Kindergarten, Elementary School and Middle, Junior and High School. Methods: A systematic review has been carried out following the recommendations set by the PRISMA Declaration. A total of five international databases were used: Web of Science (WoS), Scopus, Sport Discus, ERIC and Psycinfo. The descriptors “gamification”, “gamify” and “Physical Education” were used, limiting the search to December 2021. Several inclusion and exclusion criteria have been established, selecting only empirical research articles. Results: The search yielded a total of 177 eligible articles, and finally, 17 scientific articles that addressed the effects of gamification in Physical Education were selected. No gamified didactic experiences have been found in Early Childhood Education, but they have been found in Elementary School (7 experiences) and Middle, Junior and High School Education (10 experiences). Most of the studies have confirmed an improvement in motivation and commitment toward physical exercise in students; only one study has confirmed improvements in academic performance. The diversity of the applied protocols and the different evaluation instruments used by the researchers prevent a meta-analysis of the data. Some studies that have used a hybrid pedagogical model are recorded, combining gamification with other pedagogical models, and confirmed positive effects on different variables such as intrinsic motivation or autonomy in learning. Conclusion: The results of this review suggest the need to continue evaluating the effects of applying gamification, as an active methodology, in the Physical Education classroom.
Phase-Based Low Power Management Combining CPU and GPU for Android Smartphones
Authors: Ohk Seung-Ryeol , Kim YongSin , Kim Young-Jin
Published: August 2022

Smartphones have limited battery capacity, so efficient power management is required for high-performance applications and to increase usage time. In recent years, efficient power management of smartphones has become very important as the demand for power use of smartphones has grown due to deep learning, games, virtual reality, and augmented reality applications. Existing low-power techniques of smartphones focus only on lowering power consumption without considering actual power consumption based on utilization of the central processing unit (CPU) and graphics processing unit (GPU), which are major components of smartphones. In addition, they do not take into consideration the strict use of resources within the component and what instructions are being processed to operate them. In this paper, we propose a low-power technique that manages power by calculating the actual power consumption of smartphones at execution time and classifying the detailed resource operating states of CPUs and GPUs. The proposed technique was implemented by linking the kernel and native app on a Galaxy S7 smartphone equipped with Android. In experiments with 15 workloads, the proposed technique achieves an energy reduction of 18.11% compared to the low-power technique of the interactive governor built into the Galaxy S7 with a small FPS reduction of 3.12%.
A 112 Gb/s DAC-Based Duo-Binary PAM4 Transmitter in 28 nm CMOS
Authors: Tang Zixiang , Lv Fangxu , Shi Jianjun , Zhang Jinwang , Wei Jiahang , Wang Xinjie
Published: August 2022

To reduce the high bit error rate of serial transceivers under strong channel attenuation, a low-power 112 Gb/s SerDes transmitter was designed using a duo-binary PAM4 modulation technology. By adopting duo-binary PAM4 modulation technology, the problem of the low bandwidth utilization of a high-speed PAM4 (pulse amplitude modulation 4) signal was improved. The problem of high jitter caused by charge sharing and the limited bandwidth of a 4:1 high-speed MUX was improved by using precharging auxiliary transistors. The system power consumption of the transmitter was reduced by using a 7-bit weighted voltage-driven digital-to-analog converter (DAC). The transmitter was designed with a 28 nm CMOS process and powered by a voltage of 0.9 V. The simulation results showed that when the channel attenuation was 20.9 dB, the transmitter could work at 112 Gb/s, the power consumption was 2.02 pJ/bit, and the linearity was 96.7%.
Design and Construction of Foundations for Industrial Facilities in the Areas of Former Post-Mining Waste Dumps
Authors: Łupieżowiec Marian , Rybak Jarosław , Różański Zenon , Dobrzycki Przemysław , Jędrzejczyk Witold
Published: August 2022

This article presents the characteristics of the heaps resulting from coal exploitation in terms of the possibility of their development for industrial facilities. The chances of soil improvement and the existing threats were indicated, emphasising the risk of self-ignition. The most effective technologies are dynamic or impulse compaction, which allows deep soil improvement and the obtaining of an appropriately rigid and load-bearing subsoil. The homogeneity of the soil’s mechanical properties that form the subsoil is also essential, which guarantees compliance with the serviceability limit state. A very important aspect of the investment process in the post-mining waste dumps is the risk of auto-ignition of the accumulated material. Considerations and analyses are presented on the example of the implementation of Panatonni service, warehouse, and production halls in Ruda Śląska. The performance of impulse compaction allowed for the safe construction of industrial halls. In particular, the tests carried out on the thermal state of the dumps confirmed the lack of an unacceptable risk of endogenous fire in the dump mass.
Fault Identification and Fault Impact Analysis of The Vapor Compression Refrigeration Systems in Buildings: A System Reliability Approach
Authors: Fadaeefath Abadi Mostafa , Hosseini Rahdar Mohammad , Nasiri Fuzhan , Haghighat Fariborz
Published: August 2022

The Vapor Compression Refrigeration System (VCRS) is one of the most critical systems in buildings typically used in Heating, Ventilation, and Air Conditioning (HVAC) systems in residential and industrial sections. Therefore, identifying their faults and evaluating their reliability are essential to ensure the required operations and performance in these systems. Various components and subsystems are included in the VCRS, which need to be analyzed for system reliability. This research’s objective is conducting a comprehensive system reliability analysis on the VCRS by focusing on fault identification and determining the fault impacts on these systems. A typical VCRS in an office building is selected for this research regarding this objective. The corresponding reliability data, including the probability distributions and parameters, are collected from references to perform the reliability evaluation on the components and subsystems of the VCRS. Then the optimum distribution parameters have been obtained in the next step as the main findings. Additionally, by applying optimization techniques, efforts have been taken to maximize the system’s reliability. Finally, a comparison between the primary and the optimized systems (with new distribution parameters) has been performed over their lifetime to illustrate the system’s improvement percentage.
Management Perspectives towards the Data-Driven Organization in the Energy Sector
Authors: Pugna Irina , Boldeanu Dana , Gheorghe Mirela , Cozgarea Gabriel , Cozgarea Adrian
Published: August 2022

This paper explores the current attitudes of managers and executives working in the energy sector towards the Data-Driven Organizational Model implied by Big Data. The aim is to explore and understand the current mindset of senior decision makers, since their success depends as much on cognitive and behavioral processes as on their technical competences. We adopt a grounded-theory approach, developing models of understanding and belief abductively, driven by the data obtained from participants through a reflection guide. We find that managers differ significantly in their understanding and engagement with their challenges; they display interest but differ in their commitment and enthusiasm; they identify a lack of strategy and skills as current barriers; and they are currently unwilling to trust data, treating evidence according to their own prior commitments. This is a significant barrier to establishing the Data-Driven Organizational Model. These findings raise concerns, and the paper concludes that by considering initiatives for implementing more agile and forward-looking approaches, establishing a data-driven organizational culture, and managing such changes effectively.
Viscous Fingering Dynamics and Flow Regimes of Miscible Displacements in a Sealed Hele-Shaw Cell
Authors: An Baizheng , Solorzano Daniel , Yuan Qingwang
Published: August 2022

Miscible viscous fingering occurs when a less viscous fluid displaces a more viscous one in porous media or a Hele–Shaw cell. Such flow instabilities are of particular interest in a variety of applications in flows and displacements in subsurface energy and environment systems. In this study, we investigate the miscible viscous fingering dynamics experimentally using water to displace glycerol in a sealed Hele–Shaw cell with two wells located in it instead of at the boundary or corners. We comprehensively examine the spatial and temporal variations of fingering dynamics, different flow regimes, and how they are affected by the water injection rate and control of pressure or rate at the outlet. Alongside the widely recognized diffusion-dominated and convection-dominated flow regimes, we identify three new regimes: a slow expansion regime prior to breakthrough, a rapid shrinkage regime immediately after breakthrough, and a uniform, slow expansion regime without fingering instability. Each regime is characterized by interesting flow dynamics, which has not been reported previously. The duration of each regime depends on the water injection rate and whether constant pressure or a constant production rate is applied at the outlet. The variations of swept area, interfacial length, and count of fingers are also quantitatively examined. This study provides new insights into the fundamental mechanisms for miscible fluid displacements in a variety of applications such as CO2 sequestration, hydrogen storage, enhanced oil recovery, and groundwater contaminate remediation.
Geological Controlling Factors of Low Resistivity Shale and Their Implications on Reservoir Quality: A Case Study in the Southern Sichuan Basin, China
Authors: Ma Xinhua , Wang Hongyan , Zhou Tianqi , Zhao Qun , Shi Zhensheng , Sun Shasha , Cheng Feng
Published: August 2022

At the Changning block and at the Luzhou block, the genetic mechanism of low-resistivity shale and its impact on reservoir quality are currently a hot topic on a world-wide scale. Shale with resistivity lower than 20 Ω·m is widely developed at the Wufeng-Longmaxi Formation in the Southern Sichuan Basin, bringing a considerable challenge for reservoir prediction using the electromagnetic method. This paper discusses the genetic mechanisms and reservoir qualities of three low-resistivity shale reservoir types in the Southern Sichuan Basin (the Changning block and Luzhou block). Three primary elements controlling low-resistivity shale distribution in the Southern Sichuan Basin have been deduced: widely distributed gravity flow deposits, poor structural preservation conditions and shale graphitization caused by Emeishan basalt. Specifically, (1) the shale reservoir with a resistivity <12 Ω·m was uniformly distributed with gravity flow deposits in the Southern Sichuan Basin. High clay mineral contents (especially illite) in gravity flow deposits increased cation exchange capacity and irreducible water saturation at shale reservoir, decreasing electrical resistivity. (2) The resistivity of the shale reservoir close to a complex fault-fracture zone was generally lower than 20 Ω·m, indicating that poor structural preservation conditions played an important role in the wide distribution of low-resistivity shale. The resistivity of the shale reservoir near NE-trending faults at the Changning block was significantly lower than that in other areas. (3) Emeishan basalt caused extensive shale graphitization at the west of the Changning block, which was limited at the Luzhou block. The shale resistivity at the Luzhou block was not affected by graphitization. Among three types of low-resistivity shale, type III was characterized by high quartz content, high TOC, high porosity, high gas content and low graphitization. Although the resistivity of type III is generally lower that 20 Ω·m, it is still a favorable exploration target in the Southern Sichuan Basin.
Power Management for Distributed Generators Integrated System
Authors: Alam Md Shafiul
Published: August 2022

The integration of distributed generation systems, including intermittent solar photovoltaic (PV) and wind, has a significant impact on the power system [...]
The Unabated Atmospheric Carbon Losses in a Drowning Wetland Forest of North Carolina: A Point of No Return?
Authors: Aguilos Maricar , Warr Ian , Irving Madison , Gregg Olivia , Grady Stanton , Peele Toby , Noormets Asko , Sun Ge , Liu Ning , McNulty Steve , Pettay Forrest , Bhattacharya Shamik , Penney Skylar , Kerrigan Maccoy , Yang Linqing , Mitra Bhaskar , Prajapati Prajaya , Minick Kevan , King John
Published: August 2022

Coastal wetlands provide the unique biogeochemical functions of storing a large fraction of the terrestrial carbon (C) pool and being among the most productive ecosystems in the world. However, coastal wetlands face numerous natural and anthropogenic disturbances that threaten their ecological integrity and C storage potential. To monitor the C balance of a coastal forested wetland, we established an eddy covariance flux tower in a natural undrained bottomland hardwood forest in eastern North Carolina, USA. We examined the long-term trends (2009–2019) in gross primary productivity (GPP), ecosystem respiration (RE), and the net ecosystem C exchange (NEE) seasonally and inter-annually. We analyzed the response of C fluxes and balance to climatic and hydrologic forcings and examined the possible effects of rising sea levels on the inland groundwater dynamics. Our results show that in 2009, a higher annual GPP (1922 g C m−2 yr−1) was observed than annual RE (1554 g C m−2 yr−1), resulting in a net C sink (NEE = −368 g C m−2 yr−1). However, the annual C balance switched to a net C source in 2010 and onwards, varying from 87 g C m−2 yr−1 to 759 g C m−2 yr−1. The multiple effects of air temperature (Tair), net radiation (Rn), groundwater table (GWT) depth, and precipitation (p) explained 66%, 71%, and 29% of the variation in GPP, RE, and NEE, respectively (p < 0.0001). The lowering of GWT (−0.01 cm to −14.26 cm) enhanced GPP and RE by 35% and 28%, respectively. We also observed a significant positive correlation between mean sea level and GWT (R2 = 0.11), but not between GWT and p (R2 = 0.02). Cumulative fluxes from 2009 to 2019 showed continuing C losses owing to a higher rate of increase of RE than GPP. This study contributes to carbon balance accounting to improve ecosystem models, relating C dynamics to temporal trends in under-represented coastal forested wetlands.
Spectroscopic Data for the Rapid Assessment of Microbiological Quality of Chicken Burgers
Authors: Fengou Lemonia-Christina , Liu Yunge , Roumani Danai , Tsakanikas Panagiotis , Nychas George-John E.
Published: August 2022

The rapid assessment of the microbiological quality of highly perishable food commodities is of great importance. Spectroscopic data coupled with machine learning methods have been investigated intensively in recent years, because of their rapid, non-destructive, eco-friendly qualities and their potential to be used on-, in- or at-line. In the present study, the microbiological quality of chicken burgers was evaluated using Fourier transform infrared (FTIR) spectroscopy and multispectral imaging (MSI) in tandem with machine learning algorithms. Six independent batches were purchased from a food industry and stored at 0, 4, and 8 °C. At regular time intervals (specifically every 24 h), duplicate samples were subjected to microbiological analysis, FTIR measurements, and MSI sampling. The samples (n = 274) acquired during the data collection were classified into three microbiological quality groups: “satisfactory”: 4–7 log CFU/g, “acceptable”: 7–8 log CFU/g, and “unacceptable”: >8 logCFU/g. Subsequently, classification models were trained and tested (external validation) with several machine learning approaches, namely partial least squares discriminant analysis (PLSDA), support vector machine (SVM), random forest (RF), logistic regression (LR), and ordinal logistic regression (OLR). Accuracy scores were attained for the external validation, exhibiting FTIR data values in the range of 79.41–89.71%, and, for the MSI data, in the range of 74.63–85.07%. The performance of the models showed merit in terms of the microbiological quality assessment of chicken burgers.
Longitudinal Trends, Determinants, and Cardiometabolic Impact of Adherence to the Mediterranean Diet among Greek Adults
Authors: Georgoulis Michael , Georgousopoulou Ekavi N. , Chrysohoou Christina , Pitsavos Christos , Panagiotakos Demosthenes B.
Published: August 2022

Despite the well-established health benefits of the Mediterranean diet, there are signs that Mediterranean populations are deviating from this traditional pattern. We aimed to evaluate longitudinal changes in adherence to the Mediterranean diet, its determinants and health effects in a representative sample of the adult Greek population. This was a secondary analysis of the ATTICA epidemiological cohort study conducted in 2001/2002 and 2011/2012. The study sample consisted of 3042 men and women free of cardiovascular diseases living in Attica, Greece; of them, 2583 were followed-up for 10 years. Participants were evaluated in terms of sociodemographic, lifestyle and clinical parameters at baseline, and incidence of cardiometabolic diseases was recorded at follow-up. Dietary habits were assessed both at baseline and 10 years through a validated food frequency questionnaire and adherence to the Mediterranean diet was evaluated through the MedDietScore, based on which four trajectories were identified, i.e., low–low, low–high, high–low and high–high. During the study period, 45.6% of participants moved away from the Mediterranean diet (high–low), 9.0% moved closer (low–high), while 18.7% sustained a high adherence (high–high). Participants in the high–high trajectory were younger, mostly women, more physically active, had a higher socioeconomic status, and a more favorable body composition and cardiometabolic profile at baseline, and exhibited lower 10-year incidence rates of hyperlipidemia, hypertension, diabetes mellitus and cardiovascular disease compared to other trajectories (all p-values < 0.050). Adherence to the Mediterranean diet is declining among Greek adults. Staying close to the Mediterranean diet is associated with significant health benefits and should be a major target of public health strategies.
Enhancing the Emulsification and Photostability Properties of Pectin from Different Sources Using Genipin Crosslinking Technique
Authors: Lin Jiawei , Meng Hecheng , Guo Xiaobing , Yu Shujuan
Published: August 2022

Pectin is a potential polysaccharide-based emulsifier, but the stabilized emulsions suffer from insufficient emulsion stability. Therefore, modification is needed to enhance its emulsification performance to cater to practical applications. The genipin-crosslinking strategy was used in this work to modify pectin with different sources and extraction conditions. Chemical composition analysis, molecular weight (Mw), and radius of gyration (Rg) measurement revealed that sugar beet pectin (SBP) has a more compact and flexible conformation than commercial citrus pectin (CP) and apple pectin (AP), indicated by the significantly (p < 0.05) larger Mw/Rg of SBP (18.1–11.3 kg/mol/nm) than CP (8.3 kg/mol/nm) and AP (8.0 kg/mol/nm). Crosslinking modification significantly increased the Mw, radius of gyration, and viscosity. This significantly (p < 0.05) improved the emulsifying stability (a smaller increase in droplets size) by the contribution of both thicker adsorbed hydrated layers at the oil-water interface with a stronger steric-hindrance effect and larger viscosity effect to slow down droplet collision. The formation of a blue-black substance from crosslinking reaction was able to block the UV radiation, which significantly improved the photostability of β-carotene-loaded emulsions. Altogether, genipin-crosslinking is feasible to modify pectin of different sources to enhance the emulsion stability and for use as a vehicle for delivering bioactive compounds.