bluuebunny/crossref_metadata_2025 huggingface dataset:
HSSG: Identification of Cancer Subtypes Based on Heterogeneity Score of A Single Gene
Authors: Pang Shanchen , Wu Wenhao , Zhang Yuanyuan , Wang Shudong , Niu Muyuan , Zhang Kuijie , Yin Wenjing
Published: August 2022

Cancer is a highly heterogeneous disease, which leads to the fact that even the same cancer can be further classified into different subtypes according to its pathology. With the multi-omics data widely used in cancer subtypes identification, effective feature selection is essential for accurately identifying cancer subtypes. However, the feature selection in the existing cancer subtypes identification methods has the problem that the most helpful features cannot be selected from a biomolecular perspective, and the relationship between the selected features cannot be reflected. To solve this problem, we propose a method for feature selection to identify cancer subtypes based on the heterogeneity score of a single gene: HSSG. In the proposed method, the sample-similarity network of a single gene is constructed, and pseudo-F statistics calculates the heterogeneity score for cancer subtypes identification of each gene. Finally, we construct gene-gene networks using genes with higher heterogeneity scores and mine essential genes from the networks. From the seven TCGA data sets for three experiments, including cancer subtypes identification in single-omics data, the performance in feature selection of multi-omics data, and the effectiveness and stability of the selected features, HSSG achieves good performance in all. This indicates that HSSG can effectively select features for subtypes identification.
Genome-Wide Association Analysis Reveals Trait-Linked Markers for Grain Nutrient and Agronomic Traits in Diverse Set of Chickpea Germplasm
Authors: Srungarapu Rajasekhar , Mahendrakar Mahesh Damodhar , Mohammad Lal Ahamed , Chand Uttam , Jagarlamudi Venkata Ramana , Kondamudi Kiran Prakash , Kudapa Himabindu , Samineni Srinivasan
Published: August 2022

Chickpea is an inexpensive source of protein, minerals, and vitamins to the poor people living in arid and semi-arid regions of Southern Asia and Sub-Saharan Africa. New chickpea cultivars with enhanced levels of protein, Fe and Zn content are a medium-term strategy for supplying essential nutrients for human health and reducing malnutrition. In the current study, a chickpea reference set of 280 accessions, including landraces, breeding lines, and advanced cultivars, was evaluated for grain protein, Fe, Zn content and agronomic traits over two seasons. Using a mid-density 5k SNP array, 4603 highly informative SNPs distributed across the chickpea genome were used for GWAS analysis. Population structure analysis revealed three subpopulations (K = 3). Linkage disequilibrium (LD) was extensive, and LD decay was relatively low. A total of 20 and 46 marker-trait associations (MTAs) were identified for grain nutrient and agronomic traits, respectively, using FarmCPU and BLINK models. Of which seven SNPs for grain protein, twelve for Fe, and one for Zn content were distributed on chromosomes 1, 4, 6, and 7. The marker S4_4477846 on chr4 was found to be co-associated with grain protein over seasons. The markers S1_11613376 and S1_2772537 co-associated with grain Fe content under NSII and pooled seasons and S7_9379786 marker under NSI and pooled seasons. The markers S4_31996956 co-associated with grain Fe and days to maturity. SNP annotation of associated markers were found to be related to gene functions of metal ion binding, transporters, protein kinases, transcription factors, and many more functions involved in plant metabolism along with Fe and protein homeostasis. The identified significant MTAs has potential use in marker-assisted selection for developing nutrient-rich chickpea cultivars after validation in the breeding populations.
HKUST-1-Doped High-Resolution Volume Holographic Gratings
Authors: Castagna Riccardo , Tombesi Alessia , Riminesi Cristiano , Di Donato Andrea , Francescangeli Oriano , Lucchetta Daniele Eugenio
Published: August 2022

We report on transmission holographic gratings doped with metal organic frameworks (MOFs). As a first attempt, we focused on MOF-199, also known as HKUST-1, which is an efficient adsorbent of VOCs. HKUST-1 is not soluble in the pre-polymerized holographic mixture. For this reason, samples containing HKUST-1 show high light scattering. In this work, the recording of HKUST-1-doped one-dimensional transmission phase gratings is demonstrated. The optical properties of the recorded structures, such as diffraction efficiency and average refractive index changes, are reported by using angular analysis measurements. A first attempt to demonstrate the possibility of using the doped gratings as sensors is also reported.
In Vitro and In Silico Evaluation of Indole-Bearing Squaraine Dyes as Potential Human Serum Albumin Fluorescent Probes
Authors: Sousa Margarida A. , Lima Eurico , Ferreira Octávio , Boto Renato E. , Almeida Paulo , Reis Lucinda V.
Published: August 2022

The quantitative determination of proteins is an important parameter in biochemistry, biotechnology and immunodiagnostics, and the importance of serum albumin in clinical diagnosis should be highlighted, given that alterations in its concentration are generally associated with certain diseases. As possible probes for this purpose, squaraine dyes have been arousing the interest of many researchers due to their unique properties, such as absorption in the visible spectra, moderate relative fluorescence quantum yields and increased fluorescence intensity after non-covalent binding to specific ligands. In this work, five squaraine dyes, four of which have never been reported in the literature, were characterized and evaluated in vitro and in silico concerning their potential application as fluorescent probes for human serum albumin detection. After interaction with the protein, the fluorescence intensity increased from 12 to 41 times, depending on the dye under study. High sensitivity (1.0 × 105–5.4 × 105 nM), low detection limits (168–352 nM) and moderate quantitation limits (560–1172 nM) were obtained, proving the efficiency of the method. In addition, moderate-to-excellent selectivity was observed compared to γ-globulin proteins. Molecular docking suggests that the dyes interact more effectively with the Sudlow site I, and binding energies have been markedly higher than those of warfarin, a molecule known to bind to this site specifically.
Improving the Density of Functional Fabrics to Protect Radiation Workers in Radiology Departments
Authors: Son Jun Sik , Kim Seon-Chil
Published: August 2022

In medical institutions, the high weight of shielding clothing restrains the activities of medical workers. Although lightweight shielding clothing is being manufactured to solve this problem, the weight can only be reduced by 10%–20%. Flexible shielding fibers are mainly used to minimize activity restrictions; however, it is difficult to maintain the reproducibility of shielding performance. When weaving fibers with a yarn that contains a shielding material, the content of the shielding material in the yarn, tensile strength, and problems encountered during weaving should be considered. Therefore, in this study, a high-density shielding fabric weaving process was developed to weave a functional shielding fabric for actively utilizing it for low-dose shielding. The yarn was manufactured using 5 wt% barium sulfate, and the shielding performance was evaluated using the existing plain weave and two fabrics that underwent the newly developed high-density twill weave process. As a result of the experiment, the density of the fabric woven by the twill method increased by 82 g/m³, documenting a difference of 7.46% in the high-energy region and 11.71% in the low-energy region, thus indicating that the Twill method improves the shielding effect. Therefore, it is possible to mass produce lightweight, high-density shielding fabric that can protect against scattered rays that represent the main source of radiation in medical institutions.
Historic Conservation and Tourism Economy: Challenges Facing Adaptive Reuse of Historic Conservation Areas in Chengdu, China
Authors: He Xiangting , Zang Tongguang , Zhou Tiancheng , Ikebe Konomi
Published: August 2022

With continuous developments in the integration of culture and tourism, adaptive reuse has highlighted the vitality of historic conservation areas while simultaneously causing great challenges to urban life, local economy, and cultural sustainability. Current studies focus on the adaptive reuse of historic buildings, with little focus on historic conservation areas. To expand this understanding further, this study investigated and analyzed the challenges faced by Chengdu historic conservation areas in the context of adapting to the tourism environment, from multiple perspectives, and proposed corresponding protection and development strategies. The results of the study obtained using field investigation and semi-structured interviews contribute to the literature on the adaptive reuse of historic conservation areas; they deepen our understanding of the identified factors and provide in-depth knowledge. These findings provide a reference for future practices and promote the sustainable development of historic conservation areas for improved conservation and economic returns.
Zinc Matrix Composites Reinforced with Partially Unzipped Carbon Nanotubes as Biodegradable Implant Materials
Authors: Fan Mei , Zhao Fei , Liu Yuan , Yin Sheng , Peng Shanshan , Zhang Zongkui
Published: August 2022

The activity of zinc is between that of magnesium and iron, and it has a suitable degradation rate and good biocompatibility. It has been regarded as a very promising biodegradable metal material for biomedicine. However, the insufficient mechanical properties of pure Zn limit its practical application in the field of orthopedic implants. In this paper, partially unzipped carbon nanotubes (PUCNTs) obtained by meridionally cutting multi-walled carbon nanotubes (MWCNTs) were used as reinforcements and combined with spark plasma sintering to prepare partially unzipped carbon nanotube reinforced Zn matrix composites. The effects of PUCNT addition on the microstructure and the mechanical properties of Zn matrix composites were investigated. The microstructure analysis showed the good interface bonding between PUCNTs and the Zn matrix. Additionally, the strength of PUCNTs/Zn composites showed a trend of increasing first and then decreasing with the PUCNT content increases. When the PUCNT content was 0.2 wt%, the tensile strength and yield strength of composites were about 78.4% and 64.4% higher than that of pure Zn, respectively, while maintaining a high elongation (62.6%).
Engaging Patients in the Canadian Real-World Evidence for Value in Cancer Drugs (CanREValue) Initiative: Processes and Lessons Learned
Authors: Evans William K. , Takhar Pam , McDonald Valerie , Elias Martine , Binder Louise , Michaud Stéphanie , Tadrous Mina , Muñoz Caroline , Chan Kelvin K. W.
Published: August 2022

The Canadian Real-world Evidence for Value in Cancer Drugs (CanREValue) Collaboration established the Engagement Working Group (WG) to ensure that all key stakeholders had an opportunity to provide input into the development and implementation of the CanREValue Real-World Evidence (RWE) Framework. Two consultations were held in 2021 to solicit patient perspectives on key policy and data access issues identified in the interim policy and data WG reports. Over 30 individuals, representing patients, caregivers, advocacy leaders, and individuals engaged in patient research were invited to participate. The consultations provided important feedback and valuable lessons in patient engagement. Patient leaders actively shaped the process and content of the consultation. Breakout groups facilitated by patient advocacy leaders gave the opportunity for open and thoughtful contributions from all participants. Important recommendations were made: the RWE framework should not impede access to new drugs; it should be used to support conditional approvals; patient relevant endpoints should be captured in provincial datasets; access to data to conduct RWE should be improved; and privacy issues must be considered. The manuscript documents the CanREValue experience of engaging patients in a consultative process and the useful contributions that can be achieved when the processes to engage are guided by patients themselves.
Localization Detection Based on Quantum Dynamics
Authors: Kudo Kazue
Published: August 2022

Detecting many-body localization (MBL) typically requires the calculation of high-energy eigenstates using numerical approaches. This study investigates methods that assume the use of a quantum device to detect disorder-induced localization. Numerical simulations for small systems demonstrate how the magnetization and twist overlap, which can be easily obtained from the measurement of qubits in a quantum device, changing from the thermal phase to the localized phase. The twist overlap evaluated using the wave function at the end of the time evolution behaves similarly to the one evaluated with eigenstates in the middle of the energy spectrum under a specific condition. The twist overlap evaluated using the wave function after time evolution for many disorder realizations is a promising probe for detecting MBL in quantum computing approaches.
Towards Generalizing the Information Theory for Neural Communication
Authors: Végh János , Berki Ádám József
Published: August 2022

Neuroscience extensively uses the information theory to describe neural communication, among others, to calculate the amount of information transferred in neural communication and to attempt the cracking of its coding. There are fierce debates on how information is represented in the brain and during transmission inside the brain. The neural information theory attempts to use the assumptions of electronic communication; despite the experimental evidence that the neural spikes carry information on non-discrete states, they have shallow communication speed, and the spikes’ timing precision matters. Furthermore, in biology, the communication channel is active, which enforces an additional power bandwidth limitation to the neural information transfer. The paper revises the notions needed to describe information transfer in technical and biological communication systems. It argues that biology uses Shannon’s idea outside of its range of validity and introduces an adequate interpretation of information. In addition, the presented time-aware approach to the information theory reveals pieces of evidence for the role of processes (as opposed to states) in neural operations. The generalized information theory describes both kinds of communication, and the classic theory is the particular case of the generalized theory.
Multiscale Analysis of Runoff Complexity in the Yanhe Watershed
Authors: Liu Xintong , Zhao Hongrui
Published: August 2022

Runoff complexity is an important indicator reflecting the sustainability of a watershed ecosystem. In order to explore the multiscale characteristics of runoff complexity and analyze its variation and influencing factors in the Yanhe watershed in China during the period 1991–2020, we established a new analysis method for watershed runoff complexity based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method for the decomposition of multiscale characteristics and the refined composite multiscale entropy (RCMSE) method for the quantification of the system complexity. The results show that runoff and its components all present multiscale complexity characteristics that are different from random signals, and the intermediate frequency modes contribute the most to runoff complexity. The runoff complexity of the Yanhe watershed has decreased gradually since 1991, and 2010 was a turning point of runoff complexity, when it changed from a decline to an increase, indicating that the ecological sustainability of this basin has improved since 2010, which was mainly related to the ecological restoration measures of the Grain for Green Project. This study expands the research perspective for analyzing the variation characteristics of runoff at the multiscale, and provides a reference for the study of watershed ecological sustainability and ecological management.
Transport Preferences of City Residents in the Context of Urban Mobility and Sustainable Development
Authors: Wolnowska Anna Eliza , Kasyk Lech
Published: August 2022

The article focuses on the transport preferences of the inhabitants of a medium-sized city in the context of changing urban mobility and sustainable development. It fills the gap in the literature researching the changing communication behavior of the inhabitants of a given city. The main purpose of this article is to identify and analyze the preferred means of movement for inhabitants of a medium-sized city in Central and Eastern Europe. The research area was the city of Szczecin, Poland. The research was carried out using the following research methods: literature review, analysis of legal acts and documents, case study. The research material was collected using an anonymous questionnaire based on a proprietary survey made available to the inhabitants of the largest city of north-western Poland, Szczecin, in the GOOGLE browser in the period 17 May 2019–1 April 2021. The multiple-response contingency tables, chi-square test of independence and non-parametric U Mann–Whitney and Kruskal–Wallis tests were used for study development. The conducted scientific research showed that, when determining the relationship between the method and the destination, the respondents most often chose a car or on-foot commuting in all of the surveyed destinations. The research results increase the level of knowledge regarding residents’ needs in terms of urban mobility and the development of Szczecin’s transport system. They can be used in the rational actions of local authorities aiming to improve residents’ the quality of life in the context of the sustainable development of city transport.
Unified Strategy for Fault-Tolerant Operation of MMC with Multiple SMs Failure Based on SMs Grouping Management
Authors: Bai Zhihong , Li Yifei
Published: August 2022

Modular multilevel converter (MMC) is distinguished by its modularity. In order to improve its reliability and avoid unscheduled maintenance, it requires the MMC to continue operating even though some of its submodules (SMs) have failed. In this paper, a grouping management method of SMs in MMC is first presented where every six SMs are conceptually grouped into a virtual subunit (SU), and on this basis, a simplified space vector modulation (SVM) implementation is developed. Then, the fault-tolerant solutions are proposed by investigating the post-fault operation of the MMC based on the virtual SU concept. It is analyzed that the SU failures can be categorized into three basic types, according to the phase where the failed SMs are located, and also multiple SM failures can be decomposed into one or multiple basic fault types. In this way, the fault-tolerant solutions are unified regardless of the number of faulty SMs. Further, the sorting capacitor voltage control is combined into the proposed methods to balance all of the SM capacitor voltages. With the proposed fault-tolerant method, the amplitude and THD of the line voltages are almost unchanged under fault conditions when compared with normal operations. The simulation and experiment verify the propositions.
An Improved Extended State Observer-Based Composite Nonlinear Control for Permanent Magnet Synchronous Motor Speed Regulation Systems
Authors: Che Zhiyuan , Yu Haitao , Mobayen Saleh , Ali Murad , Yang Chunyu , Bartoszewicz Andrzej
Published: August 2022

This paper addresses the problems of an improved extended state observer (ESO)-based composite nonlinear control for the permanent magnet synchronous motor (PMSM) speed regulation systems, which is primarily constituted by a linear ESO-based feedforward compensation and nonlinear proportional feedback (NPF) control law. Firstly, by taking the parametric perturbations and external disturbances into account, a novel linear ESO is designed and analyzed to estimate the lumped disturbance, such that the system anti-disturbance performance is preserved. Meanwhile, the estimation of system state is also performed. Then, an optimal control synthesis function-based tracking differentiator (TD) is developed to arrange the transition dynamic for the reference velocity value, while its high quality differential signal is facilitated. Furthermore, an adaptive proportional control law is proposed, resulting in the eventual composite nonlinear strategy by incorporating the estimate values into the designed NPF controller. Finally, a PMSM servo system is studied to demonstrate the advantages and effectiveness of the proposed approaches.
DC Component Suppression of Grid-Connected Z-Source Inverter Based on Disturbance Observer
Authors: He Guofeng , Lin Junfang , Li Guojiao , Dong Yanfei , Zhang Wenjie
Published: August 2022

Regarding the problems of resonance and direct current (DC) components when the Z-source inverter (ZSI) without an isolation transformer is connected to the grid through an LCL filter, this paper proposes a novel DC component suppression strategy for a grid-connected ZSI based on the split capacitor method of disturbance observer (DOB). The split capacitor method is utilized to convert a third-order LCL filter into a first-order one to eliminate the resonance problem. The DC component of the inverter output voltage is regarded as an external disturbance, and the employed DOB is used to observe it, which is fed forward to suppress the DC disturbance component. Various comparison results of the simulation and experiment show that the proposed control strategy can effectively reduce grid-connected DC components injected into the grid at less than 0.5%, which decreases the DC component from 1.8% to 0.1%.
Comparison of AC Losses in the Winding of Electrical Machines with Fixed Strands Positions, Fixed Conductor Shapes and Random Winding
Authors: Bardalai Anuvav , Gerada David , Zou Tianjie , Degano Michele , Zhang Chengming , Gerada Chris
Published: August 2022

In high performance electric machines, the increase of fundamental frequency leads to additional losses in the winding due to parasitic effects such as the associated skin and proximity effects. In the first part, this paper presents an investigation into accurate modelling of AC losses in the winding using numerical methods and their experimental verification. Then, using experimental motorette setups, this research provides a comparative study between fixed strand positioning and fixed conductor shapes on the AC losses in the winding. It is shown that the exact position of strands in the conductor is not a critical factor; however, it is very important to control the conductor shape inside the slot. In the final section of this paper, an investigation into the relationship between AC losses in the winding and copper filling factor is presented. It is shown experimentally that counter-intuitive design choices such as using a lower copper fill factor and thicker strand diameters may be beneficial in achieving the highest overall efficiency.
Investigation into Power Line Supporting Structure Dynamic Properties by Means of Impulse Test
Authors: Iwaniec Joanna , Iwaniec Marek , Kurowski Piotr , Szopa Krystian
Published: August 2022

Dynamic analysis of a large, full-scale construction requires proper excitation in order to induce vibrations that can be measured and further processed. The amount of delivered energy over the frequency band must be sufficient to excite all the mode shapes in the studied range. The paper concerns the pseudo-impulse pull-and-release method that allows to determine frequency response functions of a large, lightly damped structure and estimate its modal parameters. The main advantage of the developed method is the great independence of the repetitiveness of the experiment’s operational parameters. The output time histories from subsequent partial experiments are accurately synchronised and normalised without measuring the signal of input excitation. The research conducted for the full-scale transmission tower results in modal parameters, estimated by classical and pseudo-impulse methods. The applied pseudo-impulse improves the conditioning of the excitation and results in the better readability of stabilisation diagrams as well as in a better stabilisation of the poles that are not clearly represented in the input data. The proposed method allows for the visualisation of poles which are non-detectable in cases of classical analysis.
Constrained Optimization of a Hydraulic Actuation System
Authors: Fox Michael T. , Chong Edwin K. P.
Published: August 2022

Operators of mobile platforms that employ hydraulic actuation, such as excavators, seek more efficient power transfer from source to load. Pump-controlled architectures achieve greater efficiency than valve-controlled architectures but exhibit poor tracking performance. We present a system-design optimization technique that ensures compliance with design requirements and minimizes peak input power, which correlates inversely with efficiency. We utilize the optimization technique to size a valve-controlled hydraulically actuated stabilized mount on a mobile platform. Our optimization framework accounts for the disturbance spectrum, a stabilization performance measure, the system dynamics, and control system design. Our technique features automated requirement derivation in the form of a parameter estimation, which supports design decisions under constraints. Our results show that one of four inequality constraints is active. This constraint represents a common design rule and results in limiting efficiency. We show that relaxing this constraint is practically feasible and leads to higher efficiency in achieving the required performance. We propose adding an inerter to justify the relaxed constraint and present the resulting open-loop servo transfer function.
Biogas Production from Microalgal Biomass Produced in the Tertiary Treatment of Urban Wastewater: Assessment of Seasonal Variations
Authors: Barros Raúl , Raposo Sara , Morais Etiele G. , Rodrigues Brígida , Afonso Valdemira , Gonçalves Pedro , Marques José , Cerqueira Paulo Ricardo , Varela João , Teixeira Margarida Ribau , Barreira Luísa
Published: August 2022

The valorization of microalgal biomass produced during wastewater treatment has the potential to mitigate treatment costs. As contaminated biomass (e.g., with pharmaceuticals, toxic metals, etc.) is often generated, biogas production is considered an effective valorization option. The biomass was obtained from a pilot facility of photobioreactors for tertiary wastewater treatment. The pilots were run for one year with naturally formed microalgal consortia. The biogas was generated in 70 mL crimp-top vials at 35 °C, quantified with a manometer and the methane yield measured by gas chromatography. A maximum biogas production of 311 mL/g volatile solids (VS) with a methane yield of 252 mL/g VS was obtained with the spring samples. These rather low values were not improved using previous thermo-acidic hydrolysis, suggesting that the low intrinsic biodegradable organic matter content of the consortia might be the cause for low yield. Considering the total volume of wastewater treated by this plant and the average amount of methane produced in this study, the substitution of the current tertiary treatment with the one here proposed would reduce the energy consumption of the plant by 20% and create an energy surplus of 2.8%. The implementation of this system would therefore contribute towards meeting the ambitious decarbonization targets established by the EU.
Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review
Authors: Onen Patrick Sunday , Mokryani Geev , Zubo Rana H. A.
Published: August 2022

The increasing use of high shares of renewable energy sources (RESs) in the current electricity network introduces challenges to the design and management of the electricity network due to the variation and uncertainty nature of the RESs. Some existing energy infrastructures, such as heat, gas, and transport, all have some level of inbuilt storage capacity and demand response (DR) potentials that can be exploited in an energy system integration to give the electricity network some level of flexibility and promote an efficient transition to a low-carbon, resilient, and robust energy system. The process of integrating different energy infrastructure is known as multi-vector energy systems (MESs). This paper reviews different studies on the planning of MESs using the energy hubs (EHs) approach. The EHs model used in this paper links different energy vectors such as gas, electricity, and heat energy vectors in its planning model, as opposed to planning each energy vector independently, in order to provide more flexibility in the system, minimise total planning cost, and encourage high penetration of renewable energy source for future energy demands. In addition, different uncertainty modelling and optimization methods that have been used in past studies in planning of EH are classified and reviewed to ascertain the appropriate techniques for addressing RESs uncertainty when planning future EH. Numerical results show 12% reduction in the planning cost in the case of integrated planning with other energy vectors compared to independent planning.
Addressing Challenges of Low-Carbon Energy Transition
Authors: Kyriakopoulos Grigorios L. , Streimikiene Dalia , Baležentis Tomas
Published: August 2022

Currently, national bodies and international congregations, such as that of the Stockholm, Rio, and Johannesburg conferences, jointly identified that sustainable energy development has proven to be a very challenging factor in global development [...]
Controlled Islanding under Complete and Partial False Data Injection Attack Uncertainties against Phasor Measurement Units
Authors: Basumallik Sagnik , Eftekharnejad Sara , Fardad Makan
Published: August 2022

The widespread application of phasor measurement units has improved grid operational reliability. However, this has increased the risk of cyber threats such as false data injection attack that mislead time-critical measurements, which may lead to incorrect operator actions. While a single incorrect operator action might not result in a cascading failure, a series of actions impacting critical lines and transformers, combined with pre-existing faults or scheduled maintenance, might lead to widespread outages. To prevent cascading failures, controlled islanding strategies are traditionally implemented. However, islanding is effective only when the received data are trustworthy. This paper investigates two multi-objective controlled islanding strategies to accommodate data uncertainties under scenarios of lack of or partial knowledge of false data injection attacks. When attack information is not available, the optimization problem maximizes island observability using a minimum number of phasor measurement units for a more accurate state estimation. When partial attack information is available, vulnerable phasor measurement units are isolated to a smaller island to minimize the impacts of attacks. Additional objectives ensure steady-state and transient-state stability of the islands. Simulations are performed on 200-bus, 500-bus, and 2000-bus systems.
Production and Characterization of Bacterial Cellulose Separators for Nickel-Zinc Batteries
Authors: Heydorn Raymond Leopold , Niebusch Jana , Lammers David , Görke Marion , Garnweitner Georg , Dohnt Katrin , Krull Rainer
Published: August 2022

The need for energy-storing technologies with lower environmental impact than Li-ion batteries but similar power metrics has revived research in Zn-based battery chemistries. The application of bio-based materials as a replacement for current components can additionally contribute to an improved sustainability of Zn battery systems. For that reason, bacterial cellulose (BC) was investigated as separator material in Ni-Zn batteries. Following the biotechnological production of BC, the biopolymer was purified, and differently shaped separators were generated while surveying the alterations of its crystalline structure via X-ray diffraction measurements during the whole manufacturing process. A decrease in crystallinity and a partial change of the BC crystal allomorph type Iα to II was determined upon soaking in electrolyte. Electrolyte uptake was found to be accompanied by dimensional shrinkage and swelling, which was associated with partial decrystallization and hydration of the amorphous content. The separator selectivity for hydroxide and zincate ions was higher for BC-based separators compared to commercial glass-fiber (GF) or polyolefin separators as estimated from the obtained diffusion coefficients. Electrochemical cycling showed good C-rate capability of cells based on BC and GF separators, whereas cell aging was pronounced in both cases due to Zn migration and anode passivation. Lower electrolyte retention was concluded as major reason for faster capacity fading due to zincate supersaturation within the BC separator. However, combining a dense BC separator with low zincate permeability with a porous one as electrolyte reservoir reduced ZnO accumulation within the separator and improved cycling stability, hence showing potentials for separator adjustment.
An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms
Authors: Akhtar Shamim , Sujod Muhamad Zahim Bin , Rizvi Syed Sajjad Hussain
Published: August 2022

Data-driven electrical energy efficiency management is the emerging trend in electrical energy forecasting and management. This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. The Smart Energy Informatics Lab (SEIL) of the Indian Institute of Technology (IIT) conducted an experimental study in 2019 to collect massive data on university campus energy consumption. The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. The simulation results established the findings that Bagged Trees, Fine Trees, and Medium Trees are, respectively, the best-, second-best-, and third-best-performing algorithms in terms of efficacy. On the contrary, a reverse ranking is observed in terms of efficiency. This is grounded in the fact that Bagged Trees is most effective algorithm for the said application and Medium Trees is the most efficient one. Likewise, Fine Trees has the optimum tradeoff between efficacy and efficiency.
Does Uncertainty Forecast Crude Oil Volatility before and during the COVID-19 Outbreak? Fresh Evidence Using Machine Learning Models
Authors: Tissaoui Kais , Zaghdoudi Taha , Hakimi Abdelaziz , Ben-Salha Ousama , Ben Amor Lamia
Published: August 2022

This paper uses two competing machine learning models, namely the Support Vector Regression (SVR) and the eXtreme Gradient Boosting (XGBoost) against the Autoregressive Integrated Moving Average ARIMAX (p,d,q) model to identify their predictive performance of the crude oil volatility index before and during COVID-19. In terms of accuracy, forecasting results reveal that the SVR model dominates the XGBoost and ARIMAX models in predicting the crude oil volatility index before COVID-19. However, the XGBoost model provides more accurate predictions of the crude oil volatility index than the SVR and ARIMAX models during the pandemic. The inverse cumulative distribution of residuals suggests that both ML models produce good results in terms of convergence. Findings also indicate that there is a fast convergence to the optimal solution when using the XGBoost model. When analyzing the feature importance, the Shapley Additive Explanation Method reveals that the SVR performs significantly better than the XGBoost in terms of feature importance. During the pandemic, the predictive power of the CBOE Volatility Index and Economic Policy Uncertainty index for forecasting the crude oil volatility index is improved compared to the pre-COVID-19 period. These findings imply that investor fear-induced uncertainty in the financial market and economic policy uncertainty are the most significant features and hence represent substantial sources of uncertainty in the oil market.
Experimental Study on the Sweep Law of CO2 Miscible Flooding in Heterogeneous Reservoir in Jilin
Authors: Li Wen , Yu Hongwei , Yang Zhengming , Li Jinlong , Chen Xinliang , Ma Longfei
Published: August 2022

It is very important to effectively describe the sweep characteristics of CO2 miscible flooding based on physical models for actual reservoir development. In this study, based on the geological characteristics of the Jilin ultra-low permeability reservoir, which has significant vertical heterogeneity, a two-dimensional double-layer heterogeneous visualization model with a permeability contrast of 10 and thickness contrast of 2 was designed to perform experimental research on the sweep law of CO2 miscible flooding with an injection-production mode of “united injection and single production”. With the goal of determining the obvious differences in the gas absorption capacity and displacement power of the two layers, the CO2 dynamic miscible flooding characteristics were comprehensively analyzed, and the sweep law of CO2 miscible flooding, including the oil and gas flow trend, migration direction of the oil–gas interface, and distribution characteristics of the miscible zone, was further studied in combination with the oil displacement effect. In this experiment, the gas absorption capacity was the key factor affecting the sweep efficiency of the CO2 miscible flooding. Under the combined influence of the internal and external control factors of the reservoir thickness, permeability, and injection-production mode, the gas absorption capacity of the high-permeability layer was much greater than that of the low-permeability layer, resulting in the retention of a large amount of remaining oil in the low-permeability layer, which effectively displaced and swept the oil in the high-permeability layer. The gas absorption capacity of the reservoir, gravitational differentiation, and miscible mass transfer were key factors affecting the migration of the oil–gas interface and distribution of the miscible zone. The entire displacement process could be divided into three stages: ① The gas-free rapid oil production stage, which was dominated by the displacement; ② the low gas–oil ratio stable oil production stage, which was jointly affected by the displacement and miscible mass transfer; and ③ the high gas–oil ratio slow oil production stage, which was dominated by the effect of CO2 carrying.
Medium-Voltage Distribution Network Parameter Optimization Using a Thyristor Voltage Regulator
Authors: Sosnina Elena , Kralin Aleksey , Asabin Anatoly , Kryukov Evgeny
Published: August 2022

The article is devoted to the study of steady-state conditions of a distribution network containing a thyristor voltage regulator. The thyristor voltage regulator (TVR) is a new controlled semiconductor device developed at Nizhny Novgorod State Technical University n.a. R.E. Alekseev (NNSTU). The TVR allows the optimization of the parameters of 6–20 kV distribution networks (currents and voltages) by voltage regulation. An analytical calculation of electromagnetic processes of a distribution network with the TVR has been carried out. The verification of the obtained results has been made using a computer simulation. The dependences of the current and power on additional voltage introduced by the TVR under different voltage regulation modes have been obtained. It has been shown that the use of the TVR enables optimal flow distribution to be ensured over the power transmission lines in proportion to their transfer capability when changing load power and its power factor.
MILP-Based Profit Maximization of Electric Vehicle Charging Station Based on Solar and EV Arrival Forecasts
Authors: Dukpa Andu , Butrylo Boguslaw
Published: August 2022

Electric vehicles (EVs) will be dominating the modes of transport in the future. Current limitations discouraging the use of EVs are mainly due to the characteristics of the EV battery and lack of easy access to charging stations. Charging schedules of EVs are usually uncoordinated, whereas coordinated charging offers several advantages, including grid stability. For a solar photovoltaic (PV)-based charging station (CS), optimal utilization of solar power results in an increased revenue and efficient utilization of related equipment. The solar PV and the arrival of EVs for charging are both highly stochastic. This work considers the solar PV forecast and the probability of EV arrival to optimize the operation of an off-grid, solar PV-based commercial CS with a battery energy storage system (BESS) to realize maximum profit. BESS supports the sale of power when the solar PV generation is low and subsequently captures energy from the solar PV when the generation is high. Due to contrasting characteristics of the solar PV and EV charging pattern, strategies to maximize the profit are proposed. One such strategy is to optimally size the BESS to gain maximum profit. A mixed integer linear programming (MILP) method is used to determine the optimal solution.
A Comparative Method for Assessment of Sustainable Energy Development across Regions: An Analysis of 30 Provinces in China
Authors: Chen Jiayang , Kong Ying , Yin Shunyong , Xia Jianjun
Published: August 2022

Sustainable energy development (SED) has attracted the attention of the whole world. It has a wide range of concepts and rich connotations, which is difficult to be described with a single indicator. Therefore, scholars usually use multiple indicators to evaluate SED in multiple dimensions. Existing studies mostly took countries as the research objects, and there were fewer studies on sub-regions (provincial-level regions). In fact, due to factors such as resource endowment and industrial structure, there would be obvious differences in the energy system of different regions even within a country, such as China. This study took 30 provinces in China from 2010 to 2019 as the research object, and constructed a provincial-level SED evaluation system. Analytical methods of indicator contribution were also proposed to evaluate the improvement of specific indicators and their contribution to SED on both spatial and temporal scales. The findings could help identify where provinces are doing well or poorly in SED, thereby clarifying priorities for future improvements.
Response of Larix chinensis Radial Growth to Climatic Factors Using the Process-Based Vaganov–Shashkin-Lite Model at Mt. Taibai, China
Authors: Li Shuheng , Guo Wei , Wang Jiachuan , Gao Na , Yang Qi , Bai Hongying
Published: August 2022

The Qinling Mountains are located on the dividing line between the north and the south of China. Mt. Taibai, the study site, is the highest peak in the Qinling Mountains and also the highest peak in eastern mainland China. At Mt. Taibai, several dendroecological studies have been conducted on the relationship between tree-ring indices and climatic factors using traditional statistical methods. In this study, the response of Larix chinensis Beissn radial growth to climatic factors was explored in the treeline area of Mt. Taibai using the process-based Vaganov–Shashkin-Lite (VSL) model for the first time. The conclusions were obtained according to the analysis of the L. chinensis tree-ring samples collected from both the northern and southern slopes of Mt. Taibai. The VSL model showed that temperature limits L. chinensis growth during the entire growing season, while the model did not indicate precipitation as a limiting factor. The model showed significant positive correlations between the simulated and observed tree-ring chronologies for 1959–2013, excluding the uppermost sample site on the northern slope. However, the model performance deteriorated with increasing altitude, which may be due to the decreased sensitivity of radial growth to climatic factors above the treeline.
Bacterial Cellulose/Tomato Puree Edible Films as Moisture Barrier Structures in Multicomponent Foods
Authors: Freitas John , Mendonça Giovana , Santos Leticia , Alonso Jovan , Mendes Juliana , Barud Hernane , Azeredo Henriette
Published: August 2022

Edible films have been studied mainly as primary packaging materials, but they may be used as barrier layers between food components, e.g., by reducing the moisture migration between components with contrasting water activities. Since edible films are part of the food itself, components adding sensory appeal (e.g., fruit purees) are usually desirable. The objective of this study was to develop a film to be applied as a moisture barrier between nachos and guacamole. Ten film formulations were prepared according to a simplex centroid design with three components—a polysaccharide matrix (consisting of a 5:1 mixture of bacterial cellulose—BC—and carboxymethyl cellulose), tomato puree (for sensory appeal), and palm olein (to reduce hydrophilicity)—and produced by bench casting. The film with the highest palm olein content (20%) presented the lowest water vapor permeability, and its formulation was used to produce a film by continuous casting. The film was applied as a layer between nachos and guacamole, and presented to 80 panelists. The film-containing snack was preferred and considered as crispier when compared to the snack without the film, suggesting that the film was effective in reducing the moisture migration from the moist guacamole to the crispy nachos.
Maternal Microbiota Modulate a Fragile X-like Syndrome in Offspring Mice
Authors: Varian Bernard J. , Weber Katherine T. , Kim Lily J. , Chavarria Tony E. , Carrasco Sebastian E. , Muthupalani Sureshkumar , Poutahidis Theofilos , Zafarullah Marwa , Al Olaby Reem R. , Barboza Mariana , Solakyildirim Kemal , Lebrilla Carlito , Tassone Flora , Wu Fuqing , Alm Eric J. , Erdman Susan E.
Published: August 2022

Maternal microbial dysbiosis has been implicated in adverse postnatal health conditions in offspring, such as obesity, cancer, and neurological disorders. We observed that the progeny of mice fed a Westernized diet (WD) with low fiber and extra fat exhibited higher frequencies of stereotypy, hyperactivity, cranial features and lower FMRP protein expression, similar to what is typically observed in Fragile X Syndrome (FXS) in humans. We hypothesized that gut dysbiosis and inflammation during pregnancy influenced the prenatal uterine environment, leading to abnormal phenotypes in offspring. We found that oral in utero supplementation with a beneficial anti-inflammatory probiotic microbe, Lactobacillus reuteri, was sufficient to inhibit FXS-like phenotypes in offspring mice. Cytokine profiles in the pregnant WD females showed that their circulating levels of pro-inflammatory cytokine interleukin (Il)-17 were increased relative to matched gravid mice and to those given supplementary L. reuteri probiotic. To test our hypothesis of prenatal contributions to this neurodevelopmental phenotype, we performed Caesarian (C-section) births using dissimilar foster mothers to eliminate effects of maternal microbiota transferred during vaginal delivery or nursing after birth. We found that foster-reared offspring still displayed a high frequency of these FXS-like features, indicating significant in utero contributions. In contrast, matched foster-reared progeny of L. reuteri-treated mothers did not exhibit the FXS-like typical features, supporting a key role for microbiota during pregnancy. Our findings suggest that diet-induced dysbiosis in the prenatal uterine environment is strongly associated with the incidence of this neurological phenotype in progeny but can be alleviated by addressing gut dysbiosis through probiotic supplementation.