The renewable energy source plays a major role in the grid side power production. The stability analysis is very essential in the renewable energy converters. In this paper the bifurcation is analyzed in ZETA converter and Continuous input and output(CIO) power Buck Boost converter. The ZETA converter gives positive step down and step up output voltage and the CIO power converter gives the negative step up and step down output voltage. These converters are used in the DC micro grid with renewable energy as the source. The current mode control technique is applied to analyze the bifurcation behavior and the reference current is taken as the bifurcation parameter. When the reference current is varied, both the converters loses its stability and it enters into chaotic region through period doubling bifurcation. The simulation results are presented to study the performance behavior of both the converters. The stability region of both the converters are determined by deriving the Monodromy matrix approach.

Ocean wave energy conversion as one of the renewable clean energy sources is attracting the research interests of many people. This review introduces different types of power take-off technology of wave energy converters. The main focus is the linear direct drive power take-off devices as they have the advantages for ocean wave energy conversion. The designs and optimizations of power take-off systems of ocean wave energy converters have been studied from reviewing the recently published literature. Also, the simple hydrodynamics of wave energy converters have been reviewed for design optimization of the wave energy converters at specific wave sites. The novel mechanical designs of the power take-off systems have been compared and investigated in order to increase the energy harvesting efficiency.

Cognitive deterioration caused by illness or aging often occurs before symptoms arise, and their timely diagnosis is crucial to reducing its medical, personal, and societal impacts. Brain-Computer Interfaces (BCIs) stimulate and analyze key cerebral rhythms, enabling reliable cognitive assessment that can accelerate diagnosis. The BCI system presented analyzes Steady-State Visually Evoked Potentials (SSVEPs) elicited in subjects of varying age to detect cognitive aging, predict its magnitude, and identify its relationship with SSVEP features (band power and frequency detection accuracy), which were hypothesized to indicate cognitive decline due to aging. The BCI system was tested with subjects of varying age to assess its ability to detect aging-induced cognitive deterioration. Rectangular stimuli flickering at theta, alpha, and beta frequencies were presented to subjects, and frontal and occipital EEG responses were recorded. These were processed to calculate detection accuracy for each subject and calculate SSVEP band power. A neural network was trained using the features to predict cognitive age. The results showed potential cognitive deterioration through age-related variations in SSVEP features. Frequency detection accuracy declined after age group 20–40 and band power, throughout all age groups. SSVEPs generated at theta and alpha frequencies, especially 7.5 Hz, were the best indicators of cognitive deterioration. Here, frequency detection accuracy consistently declined after age group 20-40 from an average of 96.64% to 69.23%. The presented system can be used as an effective diagnosis tool for age related cognitive decline.

Even though the current classic aerospace propulsion methods are greatly improved, some of the most modern methods have already been introduced, among which the propulsion with electric motors. Energy can be obtained from hydrogen burners, honeycomb burners to protect the burning of hydrogen that burns 10 times faster than conventional oil fuels or alcohols. Hydrogen storage is also done in honeycomb cell reservoirs. Getting solar photovoltaic power even during flight is not yet profitable or efficient, but it can be proposed in the future for lighter and/or spacecraft. A great desire is to dismantle water in hydrogen and oxygen directly on the aircraft, so the stored fuel is actually water and the one actually used is the hydrogen removed from the water. In this case, there is no need for hydrogen storage. And other modern methods of propulsion and energy acquisition are briefly presented in the paper.

In this paper, we derive and prove, by means of Binomial theorem and Faulhaber's formula, the following identity between $m$-order polynomials in $T$ $$\sum_{k=1}^{\ell}\sum_{j=0}^m A_{m,j}k^j(T-k)^j=\sum_{k=0}^{m}(-1)^{m-k}U_m(\ell,k)\cdot T^k=T^{2m+1}, \ \ell=T\in\mathbb{N}.$$

This paper reports a new control strategy to improve sharing of unbalanced currents in islanded LV microgrids. This technique provides fast and effective sharing of positive-, negative- and zero-sequence currents, and is the first example of zero-sequence current sharing in the literature. The controllers are designed in the stationary frame. The control structure consists of four loops; 1)~the current controller; 2)~the voltage controller; 3)~the droop controller and the 4)~negative and zero sequence current controllers. The output current is considered unknown for the controller and is added to the control system as a disturbance. The proposed controller features a high gain in fundamental and harmonic frequencies, hence a good voltage quality is obtained in the presence of unbalanced and nonlinear loads. To this aim, a proportional-resonant (PR) controller is adopted as the current controller. By using a multi-resonant controller as current controller, a unified control structure is obtained which is suitable for both grid-connected and islanded modes. The voltage controller is designed using a resonant controller so that the voltage can have low VUF and THD in the presence of unbalanced and nonlinear loads. Furthermore, in this paper droop method is applied to the control structure to share real and reactive powers. Simulation studies show that the conventional droop method cannot share the oscillatory part of the output power that is due to the presence of unbalanced loads in the microgrid. This paper relies on using zero and negative sequence virtual impedance controller to share the oscillatory part of output power. By using zero-sequence virtual impedance controller (ZSVIC) and negative-sequence virtual impedance controller (NSVIC), the zero and negative sequence currents in the microgrid are controlled and shared effectively. By compensating zero- and negative-sequence currents locally, the flow of these currents in the microgrid is minimized, and the overall power quality of the islanded LV microgrid is improved.

Since general relativity (GR) has already established that matter can simultaneously have two different values of mass depending on its context, we argue that the missing mass attributed to non-baryonic dark matter (DM) actually obtains because there are two different values of mass for the baryonic matter involved. The globally obtained "dynamical mass'' of baryonic matter can be understood as a small perturbation to a background spacetime metric even though it's much larger than the locally obtained "proper mass". Having successfully fit the SCP Union2.1 SN Ia data without accelerating expansion or a cosmological constant, we employ the same ansatz to compute dynamical mass from proper mass and explain galactic rotation curves (THINGS data), the mass profiles of X-ray clusters (ROSAT and ASCA data) and the angular power spectrum of the cosmic microwave background (Planck 2015 data) without DM. We compare our fits to modified Newtonian dynamics (MOND), metric skew-tensor gravity (MSTG) and scalar-tensor-vector gravity (STVG) for each data set, respectively, since these modified gravity programs are known to generate good fits to these data. Overall, we find our fits to be comparable to those of MOND, MSTG and STVG. While this favorable comparison does not establish the validity of our proposition, it does provide confidence in using the fits to pursue an underlying action. Indeed, the functional form of our ansatz reveals an interesting structure in these fits.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior.

Background: Systemic-to pulmonary collaterals (SPC) are common in congenital heart disease (CHD). Particularly in single ventricle anatomy and Fontan circulation, SPC can both complicate the postoperative course and lead to clinical deterioration in the long term. Treatment of SPC is controversial. The aim of our study was (1) to analyze retrospectively patients who underwent SPC embolization using Concerto™ Helix nylon-fibred microcoils (CHM) and (2) to describe the interventional technique. Methods: In this a single-center retrospective observational cohort study, we analyzed clinical and imaging data of all patients who underwent transcatheter embolization of SPC using CHM from January 2016 to December 2023. Results: In 38 consecutive patients (65.8 % male, median age 41 months, range 2 – 490), a total number of 141 CHM had been implanted into 64 SPC in 49 procedures. The majority were arterial SPC (n = 59/64) originating from the thoracic aorta or its branches; 5/64 were veno-venous SPC. Primary closure succeeded in all procedures. The CHM diameters ranged from 3 to 8 mm, with 5 mm being the most commonly used diameter. The mean coil / SPC ratio was 2.6 (range 1.3 – 5.3). CHM implantation was performed via 4 French sheaths. Both detachment and stable positioning was simple and safe. Neither non-target embolization nor coil migration occurred. One complication occurred with a minor vascular injury without clinical relevance. Conclusion: CHM are easy to use and appropriate for SPC embolization in all age groups, including infants, with a low complication rate. The coils are particularly suitable for closure of collaterals with small diameter or tortuous course.

Background: The Advanced Lung Cancer Inflammation Index (ALI) is a novel, comprehensive index that integrates inflammation and nutritional status, incorporating parameters such as albumin, body mass index (BMI), and the neutrophil-to-lymphocyte ratio (NLR). Unlike traditional inflammation biomarkers, this study aims to evaluate the prognosis of IPF patients by considering both inflammation and nutritional status. Method: A total of 102 patients with IPF were included in the study. Clinical data were obtained from the patients’ medical records. NLR and ALI score were calculated based on data collected at the initiation of antifibrotic treatment using the following formula: Neut/Lym and albumin × BMI / NLR. Results: IPF subject subgroups in terms of ALI based on gender–age–physiology (GAP) stages (1,2,3), FVC (median split, <70% vs ≥70%), DLCO (<51% vs ≥51%), 6-Minute Walk Test (6MWT) (<350 vs ≥350) and CCI (≤1 vs >1). ALI showed significant difference depending on the categories of GAP stage, FVC, DLCO, and 6MWT but these differences were not observed based on the charlson comorbidity index (CCI) categories (sırasıyla p=0.000, p=0.000, p=0.000, p=0.001, p=0.233). Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the sensitivity and specificity of ALI, albumin, NLR, and BMI in determining the mortality risk in IPF patients. ALI demonstrated a sensitivity of 63.6% and a specificity of 98.9% at a threshold of 11.2 (AUC = 0.945, 95% CI 0.892–0.998, p < 0.000). Conclusion: We determined that ALI levels are significantly associated with disease severity and mortality in patients with IPF.

Recently, we published that the monoclonal antibody (D12 mAb) recognizes gp63 of L. mexicana, it is responsible for COX activity. This D12 mAb exhibited cross-reactivity with Trypanosoma cruzi, Entamoeba histolytica, Acanthamoeba castellanii, and Naegleria fowleri. COX activity assays performed in these parasites suggested the potential presence of such enzymatic activity. In our investigation, we confirmed that wild-type recombinant gp63 exhibits COX-like activity, in contrast to a mutated recombinant gp63 variant. Consequently, our objective was to identify sequences orthologous to gp63 and subsequently analyze the binding of arachidonic acid (AA) to the putative active sites of these proteins. Given the absence of a crystallized structure for this protein in the Protein Data Bank (PDB), it was imperative to first obtain a three-dimensional structure by homology modeling, using leishmanolysin (PDB ID: LML1) as a template in the Swiss model. Database. The results obtained through molecular docking simulations revealed the primary interactions of AA close to the Zinc atom present in the catalytic site of gp63-like molecules of several parasites, predominantly mediated by hydrogen bonds with HIS264, HIS268 and HIS334. Furthermore, COX activity was evaluated in commensal species such as E. dispar and during the encystment process of E. invadens.

Brain-to-brain communication (B2B-C) is rapidly expanding, integrating communication technology and neuroscience to enable direct neural data transfer between people. Nonetheless, because neural data is susceptible to noise, interference, and hostile attacks, guaranteeing the security and resilience of B2B-C systems continues to be difficult. This work aims to use Adversarial Neural Network Training (ANNT) to improve the security of B2B-C systems by using Steady-State Visually Evoked Potentials (SSVEP) EEG data. We use two large SSVEP datasets for a thorough analysis: Lee2019_SSVEP and Nakanishi2015. We use the Fast Gradient Sign Method (FGSM) to create adversarial instances and ANNT to train the model on clean and adversarially perturbed data. The system's accuracy and resilience are significantly improved by ANNT, as seen by the up to 17% increase in adversarial accuracy and the average 0.03 point improvement in the Area Under the Curve (AUC). This work demonstrates how ANNT may strengthen B2B-C systems against advanced cyberattacks, opening the door for dependable and safe neural communication technologies.

Aim: To evaluate the clinical findings of glucose 6 phosphate dehydrogenase(G6PD) and pyruvate kinase(PK) deficiency in prolonged jaundice. To determine whether systemic-immune-inflammation index(SII), neutrophil-to-lymphocyte ratio(NLR) and platelet-to-lymphocyte ratio (PLR) can be used in the diagnosis of neonatal prolonged jaundice. Methods: In full term neonates with hyperbilirubinemia who were admitted to Medicine Hospital between January 2019 and January 2024 with the complaint of jaundice, 167 infants with a serum bilirubin level above 10 mg/dL, whose jaundice persisted after the 10th day, were included in the study. Results: G6PD was negatively correlated with NLR, SII, age, and Hct. There was a negatively poor correlation between G6PD and NLR and a negatively moderate correlation between G6PD and SII when adjusted for age and Hct. PK showed no significant correlation with G6PD, NLR, PLR, SII, age, and Hct. A linear relationship was observed between G6PD and SII and NLR. Conclusions: NLR and SII can be easily calculated in the evaluation of prolonged jaundice in G6PD deficiency has a considerable advantage. NLR and SII levels may contribute by preventing further tests for prolonged jaundice and regulating its treatment. It may be useful to form an opinion in emergencies and in the early period.

Photonic integrated circuits (PIC) devices are impacted by fabrication tolerances and therefore, prior knowledge of such variation could improve the PIC fabrication process and overall yield. This paper presents a method for predicting the fabrication impacts on a telecommunication optical digital to analog converter (oDAC) based pulse amplitude modulator level four (PAM-4) transmitter. Our findings allow us to estimate the production yield in fabrication scenario using symbol error rate (SER) benchmark.

Fast Field-Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry is a powerful non-destructive magnetic resonance technique that enables, among other things, the investigation of slow molecular dynamics at low magnetic field intensities. FFC-NMR relaxometry measurements provide insight into molecular motion across various timescales within a single experiment. This study focuses on a \textit{model-free} approach, representing the NMRD profile $R_1$ as a linear combination of Lorentzian functions, thereby addressing the challenges of fitting data within an ill-conditioned linear least-squares framework. Tackling this problem, we present a comprehensive review and experimental validation of three regularization approaches to implement the model-free approach to analysing NMRD profiles. These include: (1) \nameUpe, utilizing locally adapted $L_2$ regularization; (2) \nameL, based on $L_1$ penalties; and (3) a hybrid approach combining locally adapted $L_2$ and global $L_1$ penalties. Each method's regularization parameters are determined automatically, according to the Balancing and Uniform Penalty principles. % Our contributions include the implementation and experimental validation of the \nameUpe{} and \nameUp{} algorithms, and the development of a "dispersion analysis" technique to assess the existence range of the estimated parameters. The objective of this work is to delineate the variance in fit quality and correlation time distribution yielded by each algorithm, thus broadening the set of software tools for the analysis of sample structures in FFC-NMR studies. The findings underline the efficacy and applicability of these algorithms in the analysis of NMRD profiles from samples representing different potential scenarios. 1

Background: After the increasingly common anterior cruciate ligament reconstruction (ACLR) procedure in competitive athletes, rehabilitation is crucial for facilitating a timely return to sports (RTS) and preventing re-injury. This pilot study investigates the biomechanical and psychological outcomes of postoperative rehabilitation in competitive athletes, comparing supervised rehabilita-tion (SVR) and home-based rehabilitation (HBR). Methods: After ACLR, 60 (out of 74 screened) athletes were recruited and equally divided into 2 groups using non-probability convenience sam-pling: 30 HBR and 30 SVR (each group comprising 15 males and 15 females). Rehabilitation out-comes in respective groups were evaluated at 8 months using measures (Tegner-Activity-Scale [TAS], International Knee Documentation Committee subjective knee form [IKDC-SKF], ACL Return to Sport after Injury [ACL-RSI]) and objective parameters (isometric muscle strength, hamstring/quadriceps asymmetry). RTS was evaluated at 9 months; with ACL re-injury rates rec-orded approximately 6 months post-RTS. Results: Both groups exhibited decreased TAS scores (HBR: 8 to 6, SVR: 8 to 7), with the SVR group demonstrating superior post-operative IKDC-SKF scores (81.82 vs. 68.43) and lower ACL-RSI scores (49.46 vs. 55.25). Isometric and isokinetic mus-cle strength, along with asymmetry values, favored the SVR group 8 months post-ACLR (p

To satisfy the interests of multiple agents and those of comprehensive indicators such as peak-to-valley differences and load fluctuations occurring on the network side, this paper presents a flexible load demand-side response optimization method that considers the benefits of peak-to-valley smoothing. First, load aggregation modelling of air conditioning and electric vehicles was conducted, and the complementarity of the power consumption behaviour of different types of flexible loads was used to improve the responsiveness of the load aggregator. Second, considering demand-side responses and taking into account the interests of both supply and demand, the load fluctuation and peak-to-valley difference on the network side are reduced, and a flexible load double-layer optimization model incorporating the peak-to-valley smoothing benefit is established. Finally, the effectiveness of the proposed optimization model is verified by using the KKT condition and the big M method to evaluate this two-layer optimization problem as a single-layer optimization problem. Comparative examples demonstrate that the proposed two-layer optimization method can improve the revenue of the distribution network operators and the load aggregators by using the complementary nature of the load response characteristics of electric vehicles and air conditioners. Moreover, the proposed method can effectively reduce the load peak-to-valley difference and load fluctuation of the distribution network by introducing the peak-to-valley smoothing benefit model.

Commuting is a vital travel channel for college students throughout their higher education career; nevertheless, excessive commute time negatively impacts students’ school satisfaction, academic achievement, health, and quality of life. Meanwhile, few studies have explored students’ commute time, covering a large population and scope. Therefore, this study analyzes the dwelling type that influences college and graduate students’ school commute times in the Seoul Metropolitan Area, using data from the 2016 Household Travel Diary Survey. This study uses spatial data on housing development to classify five dwelling types (i.e., new town, housing site development, Seoul, Incheon, and Gyeonggi-do). A multiple linear regression model empirically analyses students’ household and personal characteristics. The results reveal that dwelling type significantly affects students’ commute time. Specifically, Students living in Seoul have a shorter commute to school than those living in new towns. Socioeconomic characteristics have less effect on college and graduate students' school commute time. This study discusses the problem of excessive commuting of college and graduate students in new towns.

Speech recognition, or automatic speech recognition (ASR), is a technology designed to convert spoken language into text using software. However, conventional ASR methods involve several distinct components, including language, acoustic, and pronunciation models with dictionaries. This modular approach can be time-consuming and may influence performance. In this study, we propose a method that streamlines the speech recognition process by incorporating a unified recurrent neural network (RNN) architecture. Our architecture integrates a convolutional neural network (CNN) with an RNN and employs a connectionist temporal classification (CTC) loss function. Key experiments were carried out using a dataset comprising 576,656 valid sentences, using erosion techniques. Evaluation of the model performance, measured by the word error rate (WER) metric, demonstrated remarkable results, achieving a WER of 2%. This approach has significant implications for the realm of speech recognition, as it alleviates the need for labor-intensive dictionary creation, enhancing the efficiency and accuracy of ASR systems, and making them more applicable to real-world scenarios. For future enhancements, we recommend the inclusion of dialectal and spontaneous data in the dataset to broaden the model's adaptability. Additionally, fine-tuning the model for specific tasks can optimize its performance for targeted objectives or domains, further enhancing its effectiveness in those areas.

Transformer models have emerged as frontrunners in the field of natural language processing, primarily due to their adept use of self-attention mechanisms to grasp the semantic linkages between words in sequences. Despite their strengths, these models often face challenges in single-task learning scenarios, particularly when it comes to delivering top-notch performance and crafting strong latent feature representations. This challenge is more pronounced in the context of smaller datasets and is particularly acute for under-resourced languages such as Arabic. In light of these challenges, this study introduces a novel methodology for text classification of Arabic texts. This method harnesses the newly developed Reverse Positional Encoding (RPE) technique. It adopts inductive-transfer learning (ITL) framework combined with a switching self-attention shared encoder, thereby increasing the model's adaptability and improving its sentence representation accuracy. The integration of Mixture of Experts (MoE) and Reverse Positional Encoding (RPE) techniques empowers the model to process longer sequences more effectively. This enhancement is notably beneficial for Arabic text classification, adeptly supporting both the intricate five-point and the simpler ternary classification tasks. The empirical evidence points to its outstanding performance, achieving accuracy rates of 87.20% for the HARD dataset, 72.17% for the BRAD dataset, and 86.89% for the LABR dataset, as evidenced by the assessments conducted on these datasets.

This research examines how rainfall and mining affect the slope damage resulting from the transition from open-pit mining to underground mining. Using unmanned aerial vehicle (UAV), the Huangniu slope of Dexing Copper Mine was fully characterized, and experiments were conducted on rock samples from appropriate sites. First, the mechanical properties of the samples were measured. Then, the parameters of the similarity simulation experiments were derived based on the similarity theory. Subsequently, the rainfall, rock slope, data acquisition and monitoring systems were designed. Finally, the rock mass failure with different slope angles was analyzed, and the deformation and damage patterns under the coupling effect were obtained. The results show that rainfall increases pore water pressure and moisture content. Rainfall and slope-slip water have more impact on the open-pit platform. The pore water pressure values on the upper rock mass rise faster than inside. In the open-pit mining stage, the rock mass shifts slightly to the upper left. In the room mining stage, vertical fractures and goaf sinking occur. The fractures above the mine room form a semi-ellipse. In the pillar mining stage, the overlying rock displacement is evident, and fractures persist. In the continuous pillar mining stage, the overlying rock collapses massively. The 65° slope model is the most damaged, while the 55° slope model is the least damaged. The results also suggest that the UAV guides sample selection.

This study investigates the specific factors affecting the usage intention of distributed ledger technology (DLT), such as availability, diversity and economic value from the perspective of a unified theory of technology acceptance. Users of DLT in public and private sectors were surveyed. Availability and economic value affect performance expectancy, while availability, diversity, and profitability have an influence on effort expectancy. Performance expectancy and transparency have a positive effect on the intention to use DLT which in turn exerts a positive effect on usage behavior. This study provides implications for researchers in that it attempts to investigate the factors affecting the usage intention of DLT based on the extended unified theory of acceptance and encompassing diverse industries that adopt DLT, such as the public, financial, medial, and logistics sectors.

The Reactive Spark Plasma Sintering (R-SPS) method is compared in this work with the two-steps SHS-SPS route, based on combination of the Self-propagating High-temperature Synthesis (SHS) with the SPS process, for the fabrication of dense (Hf0.2Mo0.2Ti0.2Ta0.2Nb0.2)B2-SiC and (Hf0.2Mo0.2Ti0.2Ta0.2Zr0.2)B2-SiC ceramics. A multiphasic and inhomogeneous product, containing various borides, is obtained at 2000°C/20min by R-SPS, from transition metals, B4C and Si. In contrast, if the same precursors are first reacted by SHS, and then processed by SPS under the optimized condition of 1800°C/20min, the desired ceramics are successfully attained. Both High-Entropy-Boride/SiC products display densities > 97%, uniform microstructures and contained only small amounts of residual oxides (<2.4 wt.%). The presence of SiC makes the sintering temperature milder, i.e. 150°C below to that needed by the corresponding additive-free system. Fracture toughness is also markedly improved, particularly when considering the Nb-containing system processed at 1800°C/20min, whereas KIC progressively decreases (from 7.35 to 5.36 MPa m1/2) as the SPS conditions become more severe. SiC addition is found to inhibit the volatilization of metal oxides like MoO3 formed during oxidation experiments, thus avoiding mass loss in the ceramics. The benefits above also likely take advantage of the fact that the two composite constituents are synthesized in parallel, according to the SHS-SPS approach, rather than being produced separately and combined subsequently, so that strong interfaces between them are formed.

Transitions from seed to seedling represent a critical developmental step in the life cycle of higher plants, dramatically affecting plant ontogenesis and stress tolerance. The release from dormancy to acquiring the germination ability is defined by a balance of phytohormones, with a substantial contribution of abscisic acid (ABA), which inhibits germination. We studied the embryonic axes of Pisum sativum L. before and after radicle protrusion. Our previous work compared RNA sequencing-based transcriptomics in the embryonic axes isolated before and after radicle protrusion. The current study aims to analyze ABA-dependent gene regulation during the transition of embryonic axes from germination to post-germination stage. First, we determined the levels of abscisates (ABA, phaseic acid, dihydrophaseic acid, and neo-phaseic acid) using the ultra-high-performance liquid chromatography-tandem mass spectrometry. Second, we made a detailed annotation of ABA-associated genes using RNA sequencing-based transcriptome profiling. Finally, we analyzed the DNA methylation pattern in the promoters of the PsABI3, PsABI4, and PsABI5 genes. We showed that changes in the abscisate profile are characterized by the accumulation of ABA catabolites, and the ABA-related gene profile is accompanied by the upregulation of genes controlling the seedling development and the downregulation of genes controlling the water deprivation. The expression of ABI3, ABI4 and ABI5, which encode the crucial transcription factors during late maturation, was downregulated by more than 20-fold, and their promoters exhibited a high level of methylation already at the late germination stage. Thus, although ABA remains important, other regulators seems to be involved in the transition from seed to seedling.

This research presents a novel approach to film analysis, leveraging word vectors to objectively evaluate movie critiques. Focusing on Director Chanwook Park’s award-winning film, ’Decision to Leave’, the study employs word vectors derived from the movie’s script of Korean text. Traditional critiques often emphasize contrasting elements and themes, but their subjective nature poses challenges in objective validation. To address this, we trained a language model using LSTM on the film’s script, obtaining word vectors that capture the essence of the narrative. These vectors were then used to perform various text analyses, including similarity and analogy operation for the keywords suggested by the critiques. By comparing the semantic relationships in the critiques with those derived from the word vectors, we could objectively validate the critiques’ assertions. Furthermore, we visualized the word vectors in a two-dimensional space, confirming the spatial relationships of key terms highlighted in critiques. The study underscores the potential of word vectors in providing a more objective lens for film analysis, bridging the gap between traditional film criticism and data-driven insights.

The model internal year-to-year variability (hereafter, internal variability) is a significant source of uncertainty when estimating anthropogenic aerosol effective radiative forcing (ERF). In this study, we investigate the impact of internal variability using large ensemble simulations (600 years in total) with the same climate model under prescribed anthropogenic aerosol forcings. A comparison of the magnitudes (i.e., standard deviation, Std) of these influences confirms that internal variability has negligible impacts on the instantaneous radiative forcing (RF) diagnosed by double radiation calls but has considerable impacts on estimating ERF through rapid adjustments (ADJ). Approximately half of the model grids exhibit strong internal variability influence on ERF (Std &gt; 5 W m−2). These strong internal variabilities lead to a 50% probability that 30-year linear change can reach 2 W m−2, and 10-year linear change can reach 4 W m−2. A 50-year simulation can provide a relatively stable annual mean map of ERF (ERF = ADJ + RF), but it fails for ADJ. The statistically significant areas in the annual mean maps of both ERF and ADJ from a 10-year simulation exhibit instability with evident chaotic features. These analyses contribute to the setup of comparative experiments and a more comprehensive understanding of the modeled anthropogenic aerosol ERF.

Abstract: A two-year study of pearl millet-groundnut cropping systems across two fertilizer levels was conducted at the INRAN/TARNA research station in Maradi, Niger in the Sahelian zone of West Africa. The objective of this study was to identify the best cropping system with and without fertilizer application to optimize pearl millet and groundnut yields, land use efficiency, and economics as measured by value-to-cost ratio. The experiment was conducted with three replications, and ten treatments combination of five pearl millet and groundnut cropping systems (pearl millet and groundnut sole crops, and three pearl millet – groundnut intercrops), and two fertilizer levels. Sole cropping produced the highest pearl millet grain by over 300 kg ha-1 and groundnut pod yields by over 500 kg ha-1, but all the intercropping systems had a LER above 1.0 with land use efficiency increased by 19 to 41%, also intercropping increased diversity, and reduced risk. Fertilizer application increased yields in all cropping systems by 200 to 600 kg ha-1. Government subsidy increased the value-to-cost ratio by 0.5 to 2, 5 units, and was required for economic response for pearl millet sole and intercrops in 2022. The groundnut sole cropping system had the greatest economic response to fertilizer application. Based on the risky environment and multiple end uses needed by producers, the intercrop system M-G: 1:3:1 with fertilizer application is usually the best option to optimize pearl millet and groundnut production.

This study evaluates the accessibility of primary care physicians (PCPs) in Eastern Quebec using an enhanced two-step floating catchment area (E2SFCA) methodology. The E2SFCA methodology considers both the population supply of PCPs and the travel time between PCPs and dissemination areas, and was found to be effective in identifying possibly underserved areas. The availability of primary care services is contingent upon the presence of adequate road infrastructure, and populations residing in areas with limited access to main road networks may experience compromised access to primary care. The study concludes that the E2SFCA methodology can facilitate the identification of areas experiencing a shortage of PCPs, and this information can be used to inform the development of regional medical workforce programs and support the establishment of rural residency initiatives.

Current trends in industrial development strive for maximum digitalization. The digital industrial revolution has been going on for more than a dozen years, Industry 4.0 and the idea of digital twins (DT) is becoming the focus of virtually all industrial sectors. Some sectors are more predisposed to digitalization, for others the process is much more difficult. This depends mainly on the specific characteristics and susceptibility of a given industry, including the current degree of digitalization of enterprises, as well as the knowledge and mental readiness of employees. The individual characteristics of an industry are important. Shipyards belong to the industry with a traditional approach, where the degree of digitalization remains low. As a result, the efficiency of shipbuilding processes and the quality of ships built are not sufficiently controlled. The article addresses this problem, reviews work in the field of digitalization of shipbuilding processes and points out the needs and challenges in this area. The article proposes the concept of a DT system for the entire ship design and production process. Key areas of digitalization of actual processes were defined, and a division was made into planning, monitoring and process analysis activities. Special attention was paid to the area of dimensional quality control and the Dimensional Quality Management Metasystem (DQMM) was featured in the comprehensive DT system. The requirements were defined and the limitations of the proposed solution were identified, taking into account a number of external factors including the degree of readiness of the manufacturer – the shipyard. The developed DT system concept was tested on the example of the construction process of a simplified ship. Practical aspects of the implementation of the proposed solution, in particular DQMM, were indicated.

Human motion analysis using inertial measurement units (IMUs) has recently been shown to provide accuracy similar to the gold standard, marker-based optical motion capture, but at much lower costs and while being less restrictive and time-consuming. However, IMU-based motion analysis requires precise knowledge of the orientation in which the sensor is attached to the body segments. This knowledge is commonly obtained via an anatomical calibration procedure based on precisely defined poses or motions, which is time-consuming and error-prone. In the present work, we propose a self-calibrating approach for magnetometer-free joint angle tracking that is suitable for joints with two degrees of freedom (DoF), such as the elbow, ankle, and metacarpophalangeal finger joints. The proposed methods exploit kinematic constraints to simultaneously identify the joint axes and the heading offset. The experimental evaluation shows that the proposed methods are able to estimate plausible and consistent joint axes from just ten seconds of arbitrary elbow joint motion. Comparison with optical motion capture shows that the proposed methods yield joint angles with similar accuracy as a conventional IMU-based method while being much less restrictive. Therefore, the proposed methods improve the practical usability of IMU-based motion tracking in many clinical and biomedical applications.

This study aims to explore the link between public investment and private investment in South Africa, using time series data spanning 40 years (1980–2020). Private investment is subdivided into credit to private sector (CPS) and foreign direct investment (FDI). Several econometric methodologies were used in the study, including the unit root test, cointegration test, and Error Correction Method (ECM). The Phillips-Perron (PP) test results point out that all the variables are stationary at levels with the exception of public investment (PI) which is stationary at first difference. The co-integration test reveals that the variables have a long-run equilibrium relationship. According to the findings of the ECM, public investment has a negative relationship with private investment (as measured by credit to private sector and foreign direct investment). The conclusion implies that in South Africa, public investment crowds out private investment. Other results revealed that, RGDP crowds in credit to private sector while crowding out foreign direct investment. Finally, the ECM findings show that government consumption expenditure crowds out credit to private sector and foreign direct investment. The residuals are homoskedastic and show no serial correlation, indicating that the model is adequate, according to the test for adequacy.

We follow the PRISMA extension for scoping reviews to review the emerging international body of empirical evidence on consumers’ attitudes and willingness to pay (WTP) for novel foods produced with New Plant Engineering Techniques (NPETs). NPETs include genome/gene editing, cisgenesis, intragenesis, RNA interference and others. These novel foods are often beneficial for the environment and human health and more sustainable under increasingly prevalent climate extremes. These techniques can also improve animal welfare and disease resistance when applied to animals. Despite these promising attributes, evidence suggests that many, but not all, consumers discount these novel foods relative to conventional ones. Our review sorts out findings to identify conditioning factors that can increase the acceptance of and WTP for these novel foods in a significant segment of consumers. International patterns of acceptance are identified. We also analyze how information and knowledge interact with consumer acceptance of these novel foods and technologies. Heterogeneity of consumers—across cultures and borders and in attitudes towards science and innovation—emerges as a key determinant of acceptance and WTP. Acceptance and WTP tend to increase when socially beneficial attributes—as opposed to producer-oriented cost-saving attributes—are generated by NPETs. NPET-improved foods are systematically less discounted than transgenic foods. Most of the valuation estimates are based on hypothetical experiments and surveys and await validation through revealed preferences in actual purchases in food retailing environments.

Ensuring a protection scheme in DC distribution is more difficult to achieve against pole-to-ground fault than in AC distribution system because of the absence of zero crossing points and low line impedance. To complement the major obstacle of limiting the fault current, several compositions have been proposed related to mechanical switching and solid-state switching. Among them, solid-state circuit breakers(SSCBs) are considered a possible solution to limit fast fault current. However, they may cause problems in circuit complexity, reliability and cost-related troubles due to the use of multiple power semiconductor devices and additional circuit configuration to commutate current. This paper proposes the SSCB with a coupled inductor(SSCB-CI) which has symmetrical configuration. The circuit is comprised of passive components like commutation capacitors, a CI and damping resistors. Thus, proposed SSCB-CI offers the advantages of simple circuit configuration and fewer utilized power semiconductor devices than another typical SSCBs in LVDC microgrid. For analysis, six operation states are described for the voltage across main switches and fault current. The effectiveness of the SSCB-CI against a short-circuit fault is proved via simulation and experimental results in a lab-scale prototype.

Ascorbate; Pars Plana Vitrectomy; Open Angle Glaucoma; Oxidative Stress; Vitreous Me-tabolism 0. How to Use This Template

Chronic rhinosinusitis is a common inflammatory disease of paranasal sinuses, which causes rhinorrhea, nasal congestion and hyposmia. The genetic predisposition or the exposure to irritants can sustain the inflammatory response and the development of nasal polyposis. Nasal polyps are benign and teardrop-shaped growths that project in the nasal cavities and originate from the ethmoid sinuses. This inflammatory process is associated with high expression of IL-5 cytokine and infiltration of eosinophils. Humanized monoclonal antibodies targeting IL-5 or its receptor, represent a therapeutic strategy in the treatment of nasal polyposis in combination with corticosteroids. The molecular pathogenesis of nasal polyps in CRS patients is associated to the epithelial-mesenchymal transition (EMT), a process in which epithelial cells lose their typical phenotype acquiring a mesenchymal phenotype. TGFβ/SMAD, ERK, and Wnt/β-catenin pathways are altered in EMT during the nasal tissue remodeling. miRNA and inhibitor molecules targeting these altered signaling pathways are able to interfere with EMT; which could lead to alternative therapies. Nasal polyps are an alternative source of mesenchymal stem cells which can be easily isolated from surgical biopsies. A molecular understanding of the biology of PO-MSCs will contribute to delineating inflammatory process underlying the development of nasal polyps.

Glacial relicts, especially those with very narrow habitat requirements, are particularly affected by global warming and thus good models for studying the future biodiversity patterns of the Alps. We have used as a model taxon Papaver occidentale, a glacial relict endemic to the Western Prealps, belonging to the alpine poppy complex (P. alpinum aggr.). All known localities were visited, each population was georeferenced and the number of individuals was estimated. Species Distribution Modelling (SDM) was used to evaluate the present and future potential distribution range and habitat suitability, taking into account the specificity of its habitat (calcareous screes). According to our study, there are globally 19 natural populations of P. occidentale. The total number of individuals was estimated at 30756 (with 72% of all individuals in canton of Bern). The taxon is a highly specialized alpine plant growing preferentially between 1900 and 2100 m a.s.l. on north facing screes. Predictions for the end of the 21st century indicate that suitable area will significantly decrease, for both the entire studied area (0-30% remaining) and sites nearby current P. occidentale populations (0-17% remaining). Under the most severe scenario, the species risks complete extinction. The long-term in situ conservation of P. occidentale, and all other taxa of the P. alpinum complex, is unlikely to be achieved without slowing global climate change. More generally, our fine-scale study shows that local environmental buffering of large-scale climate change in high-mountain flora may be very limited in specialised taxa of such patchy environments as screes.

Endometrial Cancer (EC) is the sixth most commonly occurring cancer in women with 380 000 cases in 2018. Sadly, EC morbidity and mortality are continuously increasing, therefore the medical society have a substantial need for an accurate and inexpensive diagnostic test for EC early detection and a prognostic tool for treatment planning and evaluation. Considering experience with different types of cancers C-reactive protein (CRP) appears to be a promising diagnostic and prognostic factor. Aiming to investigate its potential and in view of EC authors, this paper reviewed the following databases for metanalysis, randomized controlled trials and review articles published up to June 2020: Pubmed, Scopus, Google scholar and ClinicalKey. Studies indicate CRP >3.33 mg/l correlate with EC incidence with HR = 2.29 (p<0.05). Moreover, High-sensitivity CRP assay allows to detect CRP in very low concentrations and distinguish patients with endometriosis, soft tissue sarcomas and possibly EC. Preoperational and postoperational CRP, as well as its dynamic change are independent prognostic factors for EC and are more reliable if analyzed together. However, CRP-to-albumin ratio as well as Glasgow Prognostic Scale have greater prognostic value that CRP alone. Additionally, CRP is possibly a mediator of carcinogenesis and cancer progression through activation of inter alia FcgRs/MAPK/ERK, FcgRs/IL-6/AKT/STAT3 and FcgRs/NF-κB/NLRP3 pathways.

Peer-to-peer (P2P) content distribution or file sharing system aims to facilitate the dissemination of large files over unreliable networks. Network coding is a new transmission technique that has captured the interest of researchers because of its ability to increase throughput and robustness of the network, and decrease the download time. In this survey paper, we extensively summarize, assess, compare, and classify the most recently used techniques to improve P2P content distribution systems performance using network coding. To the best of our knowledge, this survey is the first comprehensive survey that specifically focuses on the performance of network coding based P2P file sharing systems.

Recently L-shaped tunneling field-effect-transistor (LTFET) has been introduced to overcome the thermal subthreshold limit of conventional metal-oxide-semiconductor field-effect-transistors (MOSFET). In this work, shortcoming of LTFET was investigated. It was found that corner effect present in LTFET effectively degrades its subthreshold slope. To get rid of corner effect a new type of device with dual material gates is presented. The new device termed as DG-LTFET gets rid of the corner effect and results in a significantly improved subthreshold slope of less than 10 mV/dec, and an improved ON/OFF current ratio over LTFET. In this work DG-LTFET was evaluated for different device parameters, and bench-marked against LTFET. This work presents an optimum configuration of DG-LTFET in terms of device dimensions and doping levels, to get the best subthreshold, ON current and ambipolar performance from the DG-LTFET.

Recent pollinator declines have focused efforts on their conservation which require clear estimates of pollination value to agriculture. Our socio-economic producer surveys and agronomic field research data were used to present a new way of estimating ecosystem service value of native pollinators. Using two regionally important U.S.A. crops, Maine wild blueberry and Massachusetts cranberry as models, we present perceived values of native bee pollinators from both consumer and producers. Wild blueberry’s Replacement Cost (RC) was greater than Attributable Net Income (ANI), since greater rented honey bee stocking densities are required. Attributable Net Income for native bees were similar for wild blueberry ($613/ha) and cranberry ($689/ha). Marginal Net Farm Income (MNFI) from incrementally adding more hives per ha was greater from stocking a third/fourth hive per ha for cranberry ($6,206) than stocking a ninth/tenth hive per ha for wild blueberry ($556), given greater responsiveness of yield, revenue, and profit to using rented honey bee hives in cranberry compared to wild blueberry. Both crops’ producers were only willing to annually invest $140–188/ha in native pollination enhancements on their farms, justifying government support. Consumers are willing to pay ~6.7 times more to support native bees than producers, supporting market-based support for invertebrate conservation.

We introduce the Transformation Flower Approach (TFA), a Theory of Change that attends to multiple value creation and institutional change as a dual design challenge. We highlight how the TFA integrates social scientific theories and models relevant for transformative change (in particular focusing on pathways, leverage points, governance, power, and values) and demonstrate its practical value by an application to the ongoing transformation of the Dutch food system. By providing a holistic, transdisciplinary and practically relevant approach that aims to support new social contract formation, the TFA goes beyond other transformative change approaches. Based on the notion of pathways, it offers a toolbox that aids in working towards desired futures, involving both incumbents and challengers in an effort to harness untapped yet proximal potentials in a forward-looking way. By embracing an innovation approach, it not only promises to circumvent resistance to change, but also serves as a step-by-step approach to identify options for multiple value creation and effective cooperation. We demonstrate the analytical and practical value of the TFA by discussing action perspectives at various levels and scales in the context of the Dutch food system transition, including (1) area-oriented approaches, (2) acceleration agendas for specific transformation pathways, and (3) actor-specific transformation flowers. In developing these, we emphasize the importance of interdependencies between leverage points. Our approach helps to identify opportunities to link transformative options (the what), actors (the who) and levers (the how) in dynamic interaction to embark on transformative pathways.

There is a global demand for alternative energy sources away from unsustainable fossil fuels. COP26 agreed that fossil fuels should be phased down; at COP27, anxiety about the cost and availability of energy was raised, and COP28 reiterated the phasedown of coal power. Solar technology in the form of Perovskite solar cells is one such alternative energy source. This article considers the fabrication of the Perovskite layer in a solar cell and postulates the extent to which Material Flow Cost Accounting (MFCA) could be used as a feasible costing method, among other things, to address byproduct and waste generation. Through MFCA, the monetary and physical flows of materials are identified and can be applied throughout the supply chain to facilitate affordability, from the extraction of the ore, transportation, fabrication of the chemicals, manufacturing and distribution of the solar cell and panels, and finally, the recycling of the panel. Informed by these observations, a conceptual framework for applying MFCA in fabricating the Perovskite layer in the supply chain is developed based on sets of qualitative propositions. Future work will be researching the processes of manufacturing solar cells, costing raw materials, energy flows, and solar cell manufacturing emissions.

In this work, we analyzed non-Darcy two-component single-phase isothermal flow in naturally fractured tight gas reservoirs for enhanced gas recovery (EGR) and carbon dioxide storage as a possible application. We used the Peng-Robinson equation of state to evaluate the thermodynamic properties of the components, and we performed the discretization of the governing partial differential equations using the Finite Volume Method. This process leads to two subsystems of algebraic equations, which, after linearization and use of an operator splitting method, are solved by the Conjugate Gradient (CG) and Biconjugate Gradient Stabilized (BiCGSTAB) methods for determining the pressure and fraction molar, respectively. We include inertial effects using the Barree and Conway model, gas slippage via a more recent model than Klinkenberg’s and we use a simplified model for the effects of effective stress. We also utilize a mesh refinement technique to represent the discrete fractures. Finally, we implemented simulations to show the influence of inertial, slippage and stress effects on production in fractured tight gas reservoirs.

Global attention to climate change has surged since the advent of the Paris Agreement, intensifying the importance of measuring and managing carbon productivity indicators on a national level. Nevertheless, concerns persist regarding the reliability of such measurements because of inherent discrepancies in implementing and operating national-level carbon productivity indicators, coupled with their inherent uncertainty. This study proposes a multiple regression model to address these issues aimed at refining national-level carbon productivity indicators metrics, accounting for factors such as the gross domestic product and total greenhouse gas emissions by sectors. The objective was to offer insights into enhancing and effectively utilizing current indicators, enabling a more nuanced interpretation of the variation in the carbon productivity indicators across diverse industrial landscapes. This study showed that adjustments of the carbon productivity metrics reflect disparities in emissions across industrial structures, with countries characterized by high emissions from non-service industries showing improving trends. In addition, this paper proposes an auxiliary indicator estimating method for carbon productivity, emphasizing its utility in interpreting productivity indicators within the context of varying industrial compositions across OECD countries. This study underscores the inadequacies of the current national productivity estimating method, pinpointing areas requiring refinement. Specifically, the method for estimating the auxiliary indicator for carbon productivity guarantees enhanced rationality when integrated with current methodologies. Moreover, by elucidating the nuances of industrial structures, this study advocates for more sophisticated approaches to interpreting and managing the productivity indicators tailored to each unique economic landscape of each country. Nevertheless, the limitations stemming from data availability underscore the need for further research, particularly in refining the national-level carbon resource productivity indicators analyses and exploring the thematic productivity variations in greater depth. By addressing these gaps, future studies will contribute to a more comprehensive understanding of national-level carbon resource productivity indicators dynamics and reveal targeted strategies for sustainable development.

Gas-water relative permeability curve is the foundation of gas reservoir dynamic analysis and numerical simulation. It is generally obtained through gas displacing water experiment. Referring to the existing national standards, gas-water relative permeability test is carried out for low-permeability and tight sandstone. The flow is discontinuous and the curve smoothness is poor, which affects the application of gas-water relative permeability curve. Based on the comparative analysis of a large number of mercury injection and NMR experimental results of low-permeability and tight sandstone, a method to characterize the throat radius distribution of low-permeability tight sandstone based on NMR T2 spectrum is explored. Combined with high-speed centrifugal experiment, the calculation formulas of core water saturation, phase relative permeability of gas-water under different centrifugal force are established. A new method of "nuclear magnetic resonance + high-speed centrifugation" for gas-water relative permeability curve test of low-permeability and tight sandstone is formed, and the test is carried out on Sulige low-permeability tight sandstone core. The results show that: (1) The shape of cumulative distribution curve of throat radius by mercury injection method is basically consistent with that of T2 relaxation time by NMR, and there is a good corresponding relationship between them. (2) The centrifugation process is similar to the gas displacing water process. With the decrease of water saturation, water centrifugation in rock core becomes more and more difficult until it become irreducible. (3) The test process of the new method is unified and standard and up to 6 cores can be tested at the same time. The calculation results of water saturation and relative permeability curve are reliable and the integral curve is smooth, which greatly improves the test efficiency of gas-water relative permeability curve in low-permeability and tight sandstone. The new method can be widely used to study the gas-water two-phase seepage law in low-permeability and tight sandstone gas reservoir.

This work presents the results regarding the synthesis of tungsten nanoparticles (W NPs) by magnetron sputtering combined with gas aggregation (MSGA) when H2 mixed with Ar is used as working gas, the amount of H2 being increased up to 82%. The results show that up to 40% H2 in discharge the synthesis rate increases over 60 times, rapidly decreasing for over 50% H2 in discharge. The W dust is still produced in H2 dominated discharge (82%), the deposition rate being small but not negligible (20 mg/hour). The obtained WNPs are isolated, with the diameter decreasing from 50 nm to 15 nm when the amount of H2 in discharge is smaller than 41%. Over this value, the particles tend to agglomerate, forming structures similar to film-like deposits. Also, the diameter of the deposited spots on substrates is dependent on the H2 content in discharge. This allows the efficient coating of substrates with dimensions up to 26 mm by translating them in front of the MSGA cluster source exit aperture. Supplementary, for 41% H2 in discharge, the influence of synthetic air leaks (0-5%) in discharge was investigated. The deposition rate decreases rapidly (ceasing for around 4% air in discharge) and the obtained nanoparticles tend to agglomerate (at 2% air content, the dust deposit has the aspect of a near continuous film). Chemical composition investigations show a pronounced tendency of oxidation, nitridation and oxynitride formation in the presence of air leaks.

The effect of Localized Surface Plasmon (LSP) of 5 nm mean size Au particles deposited on TiO2 P25 was investigated during the photo-thermal water gas shift reaction (WGSR). The effects of CO concentration, excitation light flux and energy, and molecular oxygen addition during the reaction were investigated. The photocatalytic WGSR rate under light excitation with wavelengths extending from 320 to 1100 nm was found to be higher than the thermal reaction alone at the same temperature (85 oC). A ratio H2/CO2 of near unity was found at high concentrations of CO. Addition of molecular oxygen during the reaction resulted in a slight decrease of molecular hydrogen production while the rates of CO2 formation and that of CO consumption changed by one order of magnitude. More important, it was found that the WGSR rates were still high under only visible light excitation (600 - 700 nm). The results prove that Au LSP alone triggers this chemical reaction without the need to excite the semiconductor on which they are deposited.

We evaluated the closure of idiopathic full-thickness macular holes (MHs) the day after surgery in minimizing the burden and maximizing patient outcomes. Herein, 25-gauge pars plana vitrectomy, internal limiting membrane peeling, and fluid-gas (20% sulfur hexafluoride) were performed for the treatment. Patients were instructed to remain in the facedown position until the confirmation of MH closure, and the position was discontinued in cases where the closure was confirmed. In total, 43 eyes of 43 patients, whose average age was 69.7±8.6 years, were enrolled in this study. We used swept-source (SS)-optical coherence tomography (OCT) for the confirmation of MH closure for gas-filled eyes and used spectral domain (SD)-OCT for the reconfirmation of MH closure after the gas volume was reduced to less than half of the vitreous cavity. MH closure was confirmed in 40 eyes (93%, the closure group) on the next day after surgery. The time from surgery to SS-OCT imaging was 24.7 hours. Although facedown positioning was terminated in cases where MH closure was confirmed, there were no cases in which the MH was re-opened afterward. The basal and minimum MH size was significantly larger in the non-closure group than that in the closure group (p = 0.027, p = 0.043, respectively). Therefore, checking with SS-OCT the day after surgery and terminating facedown positioning in cases where MH closure was confirmed would be a useful method, removing great burden for the elderly without sacrificing the MH closure rate.

Cement manufacturing is one of the most energy-intensive industries in the world. Most of the cost of producing cement is accounted by fuel consumption and power expenditures. Thermal power plants are the major source of electricity in Pakistan. But they are not efficient and environmentally friendly. This study simulates four different models for five cement plants of Pakistan on Homer Pro software and compares the optimal solutions based on the net present cost (NPC), levelized cost of electricity (LCOE) and greenhouse gas (GHG) emissions. Model-1 consists of solar panels, electrolyzer, hydrogen tank, hydrogen generator and converter. Model-2 has only a diesel generator and acts as a base case in this study. Model-3 has solar panels and a battery-converter system. In Model-4, diesel generators, solar panels and converters are considered. Based on NPC, the most optimal model is Model-4, having a 0.249 $/KWh LCOE in islanded systems. The NPC and operating costs are US$540 million and US$ 32.5 million per year, respectively, with a 29.80% reduction in CO2 emissions when compared to the base case. Based on GHG emissions, Model-1 and Model-3 are the best models with 0% GHG emissions. Sensitivity analyses is also performed using the parameters of load, inflation rate and discounted rate. The results prove that the proposed hybrid micropower systems (HMS) can sustainably provide electricity for 24 hours a day to the sites under consideration with minimum objectives.

Gas bubbles present in liquids underpin many natural phenomena and human-developed technologies that improve the quality of life. Since all living organisms are predominantly made of water, they may also contain gas bubbles—introduced both naturally and artificially—that can serve as biomechanical sensors operating in hard-to-reach places inside a living body and emitting signals that can be detected by common equipment used in ultrasound and photoacoustic imaging procedures. This kind of biosensors is the focus of the present article, where we critically review the emergent sensing technologies based on acoustically driven oscillations of gas bubbles in liquids and bodily fluids. This review is intended for a broad biosensing community and transdisciplinary researchers translating novel ideas from theory to experiment and then to practice. To this end, all discussions in this review are written in a language that is accessible to non-experts in specific fields of acoustics, fluid dynamics and acousto-optics.

In this paper, we present the extension of the pressure-based solver designed for the simulation of compressible and/or incompressible two-phase flows of viscous fluids. The core of the numerical scheme is based on the hybrid Kurganov— Noele — Petrova/PIMPLE algorithm. The governing equations are discretized in the conservative form and solved for velocity and pressure, with the density evaluated by an equation of state. The acoustic-conservative interface discretization technique helps to prevent the unphysical instabilities on the interface. The solver was validated on various cases in wide range of Mach number, both for single-phase and two-phase flows. The numerical algorithm was implemented on the basis of the well-known open-source Computational Fluid Dynamics library OpenFOAM in the solver called interTwoPhaseCentralFoam. The source code and the pack of test cases are available on GitHub: https://github.com/unicfdlab/hybridCentralSolvers

Primary energy consumption is one of the key drivers of global CO₂ emissions that, in turn, heavily depend on the efficiency of involved technologies. Either the improvement in technology efficiency or the expansion of non-fossil fuel consumption require large investments. The planning and financing of such investments, by policy makers or global energy firms, require, in turn, reliable measures of associated global spreads and their evolution in time. In this paper, our main contribution is the introduction of index measures for accessing global spreads (that is, measures of inequality or inhomogeneity in the statistical distribution of a related quantity of interest) of technology efficiency and CO₂ emission in primary energy consumption. These indexes are based on the Gini index, as used in economical sciences, and generalised entropy measures. Regarding primary energy sources, we consider petroleum, coal, natural gas and non-fossil fuels. Between our findings, we attest some stable relations in the evolution of global spreads of technology efficiency and CO₂ emission, and a positive relation between changes in global spreads of technology efficiency and use of non-fossil fuel.

High-power output and high conversion efficiency are crucial in the study of microfluidic microbial fuel cells (MFCs). In our previous work, we attempted various methods to increase the power density of the MFCs, but nutrient consumption was limited to the bottom (electrode) layer of the microfluidic channel due to the diffusion limitations. In this work, long-term experiments were conducted on a new 4-electrode microfluidic MFC design, which grew Geobacter sulfurreducens biofilms on upward- and downward-facing electrodes in the microchannel. It was discovered that inoculation and growth of the electroactive biofilm did not proceed as fast as the downward facing anode, which we hypothesize is due to gravity effects that negatively impacted bacterial settling on that surface. Rotating the device during the growth phase resulted in uniform and strong outputs from both sides, yielding individual power densities of 4.03 and 4.13 W m-2, which was increased to nearly double when the top- and bottom-side electrodes were operated in parallel as a single 4-electrode MFC. Similarly, acetate consumption could be doubled with the 4-electrodes operated in parallel.

To support the integration of renewable energy sources and preserve grid stability, this study examines several approaches for controlling the temperature of Battery Energy Storage Systems (BESS) in modern energy settings. Specifically, the usage of BESS in Virtual Power Plants (VPPs) is the focus of this study. The effectiveness, safety features, dependability, affordability, and suitability for VPP applications of these systems are examined. Among the various hybrid cooling alternatives, two particularly promising combinations emerge. Firstly, the integration of heat pipes and phase change materials leverages their ability to conduct heat efficiently away from heat sources with minimal temperature differences, making them excellent for rapid heat transfer. Secondly, an approach employing heat pipes and liquid passive cooling a combination that capitalizes on the efficient heat transfer capabilities of heat pipes and the consistent cooling offered by liquid passive systems. The study underscores the importance of improving BESS performance and sustainability within VPPs by providing useful recommendations for choosing the best thermal management system depending on climate conditions and geographic location.

The sustainable development of an area is highly dependable on reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for the active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller's performance is evaluated in MATLAB environment and simulation results show the proposed scheme's superiority under different operating conditions.

The main aim of this work is to present a step-by-step procedure to model and analyze the power loss distribution of three-level Gallium Nitride (GaN) inverters. It has been applied to three distinct three-phase three-levels voltage source inverters utilized in electric traction drives: Active Neutral Point Clamped, Neutral Point Clamped and T-Type Neutral Point Clamped. The proposed analytical power loss modelling, combined to an equivalent representation of the electrical machine demonstrated to be a viable solution to achieve a time-saving and low computational burden simulation platform, leading to satisfying accuracy results. This has been confirmed by comparing the results carried out from the simulations of a 110kW permanent magnet synchronous motor drive and those determined by considering a simplified circuital representation based on the proposed analytical power loss modelling.

This article introduces the design and analysis of a slope detection circuit tailored for on-chip sensing of the load current in DC-DC converters. The novel indirect sensing approach is grounded in measuring the output voltage slope across the filtering capacitor during discharge phases. Consequently, this slope data can be effectively harnessed to control the converter switches. The slope detector circuit was designed in standard 65 nm CMOS technology using the nominal supply voltage of 1.2 V and can be used for current sensing within the range from one to hundreds of mA. Since the proposed circuit has mainly digital character, the robustness to process, temperature and supply voltage variations can be ensured rather conveniently.

Smart grids are seeing an increase in renewable energy and an enormous introduction of advanced power electronics, increasing the number of disturbance sources. This requires improving the accuracy of measurement systems capable of acquiring data for use in power system monitoring applications. Rogowski Coils (RCs) and Merging Units (MUs) are being widely deployed in controlling, metering, and monitoring of digital power systems. Because the performance of digital measurement devices has a direct influence on power measurement accuracy, it is critical to perform a laboratory calibration of these measurement instruments before they are installed in any project. To determine the magnitude and phase displacement errors of the RC+MU under normal and abnormal operating conditions, this article presents a comprehensive laboratory digital calibration system constructed from precise, readily available commercial products such as a fluxgate current transducer and a National Instrument. In addition, the analysis of measurement chain is affected by sources of uncertainty is discussed. The tests yield findings that are consistent with the relevant standards.

Thailand has formulated her climate change policy and updated relevant plans and policies to align with the goal of achieving carbon neutrality and net zero GHG emissions. This study investigates the optimal level of GHG mitigation in Thailand, taking into account the marginal abatement cost (MAC) and social cost of carbon (SCC). It evaluates how energy efficiency and renewable energy technologies influence GHG reduction in the power and industrial sector and illustrates policy recommendations that align with the 2020 to 2050 policy and plan period. The findings indicate that there may be instances where GHG mitigation potential is insufficient to reach the national mile-stone. In such cases, it becomes imperative to leverage all technologies within the marginal abatement cost curve (MACC) and also utilization of the social cost of carbon for policy decision making and meeting the desired goals. In certain scenarios, the adoption of additional technologies or measures may be necessary, such as flexible power generation and deploying carbon capture and storage or hydrogen which are high-cost technologies. Furthermore, preparations should be made for multiple levels of climate change policies and plans beyond 2030.

The paper proposes an innovative solution for managing and ensuring high energy efficiency of power supply systems at high non-linear loads. This is realized by maintaining optimal value of reliability indicators and high quality of power supply. The validation is carried out using analyzes and tests of quality of electromagnetic compatibility (EMC) for increased number of powered frequency converters. It has been proven that the effective use and reduction of energy consumption can be achieved thanks to the unique technological features of the employed electrical devices. This enables a normal operation of the system with decreased power and adequate control of energy processes. The problem of predicting power losses under changing conditions in a decentralized electrical network has been solved based on the theory of electromagnetic compatibility. The influence of the mains mode parameters and the indices of instantaneous distortion of current and voltage waveforms caused by the operation of converters on the resonance phenomena in power supply systems were investigated. Recommendations were developed for the selection of proper parameters of compensators for 6-10 kV and 0.4-0.66 kV circuits based on the analysis of the optimization problem when minimizing active power losses. Results of our findings may aid parties involved in designing and maintaining power networks in various applications, such as mines, etc.

Growing population, industrialization, and power requirements are adversely affecting the environment by increased greenhouse gases, resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led the nations to promote clean and self-renewable sources of energy to address the environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting offshore wind power resources assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above means sea level (AMSL) and temperature and pressure data near surface is used. The data is obtained from ERA5 (fifth generation reanalysis for the global climate weather) at chosen six (L1-L6) offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL while temperature and pressure are available near water surface level. At L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m2, 6.37 m/s and 225 W/m2, 6.91 m/s and 281 W/m2, 5.48 m/s and 142 W/m2, 4.30 m/s and 77 W/m2, and 5.03 and 115 W/m2 and at 100 m AMSL; respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at L1 and L3 sites and generally lower values of wind variability indices are indicative of favourable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy, for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at L5 and L1 sites corresponding to wind turbines WT1 and WT4. Based on the analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifiers indices introduced, will help decision-makers in deciding the potential windy sites with more confidence.

Over the past few years, there has been an increasing fascination with electric unmanned aerial vehicles (UAVs) because of their capacity to undertake demanding and perilous missions, while also delivering advantages in terms of flexibility, safety, and expenses. These UAVs are revolutionizing various public services, encompassing real-time surveillance, search and rescue operations, wildlife assessments, delivery services, wireless connectivity, and precise farming. To enhance their efficiency and duration, UAVs typically employ a hybrid power system. This system integrates diverse energy sources, such as fuel cells, batteries, solar cells, and supercapacitors. The selection of an appropriate hybrid power arrangement and the implementation of an effective energy management system are crucial for the successful functioning of advanced UAVs. This article specifically concentrates on UAV platforms powered by batteries, incorporating innovative technologies like in-flight recharging via laser beams and tethering. It provides an all-encompassing and evaluative examination of the current cutting-edge power supply configurations, with the objective of identifying deficiencies, presenting perspectives, and offering recommendations for future consideration in this domain.

Yaw misalignment can make a wake steer, which is an effective method to increase the power of wind farms, but it also increases the fatigue load of the turbines. In this paper, the method of combining yaw misalignment and pitch control (CYMP) is proposed to investigate the potential to mitigate wake interference, the wind velocity distribution and turbulence distribution in the wake, as well as the power and load changes of the wind turbine are studied, focusing on power in-crement and fatigue damage reduction. Although some studies have found that the method of CYMP are beneficial to increase power generation and reduce fatigue loads, there are no papers that have made a detailed analysis of the effects of wake turbulence, wind speed distribution, power, especially fatigue damage under this control. Simulation tool FAST.Farm is used to model and analyze wind farms, obtain the variation details of wake and provide simulation data for calculating power and fatigue load. The pitch control brings bias to the CYMP optimization results was neglected, the case studies show that the method of CYMP can reduce the fatigue load by 10.29% and increase the total power by 1.7% compared with only wake steering. The Model Predictive Control collaborative method based on CYMP is proposed, which can increase power by more than 2% and reduce thrust by more than 4% under 10m/s turbulent wind.

Accurately predicting the power of solar power generation can greatly reduce the impact of the randomness and volatility of power generation on the stability of the power grid system, which is beneficial for the balanced operation and optimized dispatch of the power grid system, and reduces operating costs. Solar PV power generation depends on weather conditions, which are prone to large fluctuations under different weather conditions. Its power generation is characterized by randomness, volatility and intermittency. Recently, the demand for further investigation and effective use on the uncertainty of short-term solar PV power generation prediction has been getting increasing attention in many application of renewable energy sources. In order to improve the predictive accuracy of output power of solar PV power generation and develop a precise predictive model, the authors worked predictive algorithms for the output power of a solar PV power generation system. Moreover, since short-term solar PV power forecasting is one of the important aspects for optimizing the operation and control of renewable energy systems and electricity markets, this review focuses on the predictive models of solar PV power generation, which can be verified in the daily planning and operation of a smart grid system. In addition, the predictive methods in the reviewed literature are classified according to the input data source used for accurate predictive models, and the case studies and examples proposed are analyzed in detail. The contributions, advantages and disadvantages of the predictive probabilistic methods are compared. Finally, the future studies of short-term solar PV power forecasting is proposed.

Electrical power quality is one of the main elements in power generation systems. At the same time, it is one of the most significant challenges regarding stability and reliability. Due to different switching devices in this type of architecture, different kinds of power generators, and non-linear loads are used for different industrial processes. As a result of this, the need to classify and analyze Power quality disturbance (PQD) to prevent and analyze the degradation of the system reliability affected by the non-linear and non-stationary oscillatory nature. This paper presents A Novel Mul-titasking Deep Neural Network (MDL) for the Classification and Analysis of Multiple Electrical Disturbances. The characteristics are extracted with a specialized and adaptive methodology for non-stationary signals, Empirical Mode Decomposition (EMD). The methodology’s design, devel-opment, and various performance tests are carried out with 28 different difficulty levels, such as severity, disturbance duration time, and noise in the 20 dB to 60 dB signal range. MDL was devel-oped with a diverse data set in difficulty and noise, with a quantity of 4500 records of different samples of multiple electrical disturbances. The analysis and classification methodology has an average accuracy percentage of 95% with multiple disturbances. In addition, an average accuracy percentage of 90% in analyzing important signal aspects for studying electrical power quality such as crest factor, Per Unit voltage analysis, Short Term Flicker Perceptibility (Pst), and Total Harmonic Distortion (THD), among others.

Lead-based ternary chalcogenide thin films of the (PbTe)1-x(PbS)x system were obtained by plasma-enhanced chemical vapor deposition technique (PECVD) under conditions of a nonequilibrium low-temperature argon plasma of an RF discharge (40.68 MHz) at a reduced pressure (0.01 Torr). High-purity elements were directly used as starting materials – Pb, S and Te. Plasma-chemical synthesis was carried out on the surface of of c-sapphire and silicon substrate. The physicochemical properties of the films were studied by various analytical methods. The dependence of the Seebeck coefficient, resistivity, and power factor on the structural properties and composition has been studied. The thermoelectric characteristics were found to be dependent on the film composition. Upon the selection of optimal sulfur concentration one can increase the power factor as compared to single phase PbS ot PbTe films.

The growing integration of renewable energy sources (RES) into the power system causes congestion to occur more frequently. In order to reduce congestion in the short term and to make the utilization of the power system more efficient in the long term, power flow control (PFC) in the transmission system has been proposed. However, exemplary studies show that congestion will increase also in the distribution system if the transmission system is expanded. For this reason, the potential of PFC to reduce congestion in a model of a real 110 kV distribution system is investigated. Several Unified Power Flow Controller (UPFC) devices are optimized in terms of their number and placement in the power system, their size, control parameters, and costs, by using a Parallel Tempering approach as well as a greedy algorithm. Two optimization variants are considered, one reducing the number of degrees of freedom by integrating system knowledge while the other is not. We find that near a critical grid state and disregarding costs, PFC can reduce congestion significantly (99.13 %). When costs of the UPFCs are taken into account, PFC can reduce congestion by 73.2 %. A basic economic analysis of the costs reveals that the usage of UPFCs is profitable. Furthermore, it is found that the reduction of the solution space of the optimization problem leads to better results faster and that, contrary to expectations, the optimization problem is simple to solve. The developed methods allow not only for the determination of the optimal use of UPFCs to minimize congestion, but also to estimate their profitability.

We investigate a family of nonlinear partial differential equations which are singularly perturbed in a complex parameter and singular in a complex time variable at the origin. These equations combine differential operators of Fuchsian type in time and space derivatives on horizontal strips in the complex plane with a nonlocal operator acting on the complex parameter known as the formal monodromy around 0. Their coefficients and forcing terms comprise polynomial and logarithmic type functions in time and are bounded holomorphic in space. A set of logarithmic type solutions are shaped by means of Laplace transforms relatively to time and parameter and Fourier integrals in space. Furthermore, a formal logarithmic type solution is modeled which represents the common asymptotic expansion of Gevrey type of the genuine solutions with respect to the complex parameter on bounded sectors at the origin.

Purpose – Extend the Blade Element Momentum Theory (BEMT) such that rotors with pronounced cone and axis angle (tilt or yaw) can be calculated. Derive an equation for the speed ratio (lambda) as a function of Tip Speed Ratio (TSR), radius, blade, cone and axis angle. This converts the BEMT into an Unsteady BEMT or UBEMT. Present the Wagner rotor as one such rotor geometry. --- Methodology – Literature review and calculations. --- Findings – The UBEMT can be used to calculate highly unconventional rotor geometries. --- Research Limitations – Although the aerodynamic coefficients used in the UBEMT are from measurements in steady flow conditions, they can be used with success. --- Practical Implications – Also conventional Horizontal Axis Wind Turbines (HAWT) with noticeable cone and axis angle should be calculated with the UBEMT. The accuracy of power calculations of these HAWTs can be slightly improved. --- Originality – Analytic equations for rotors with cone and axis angle have barely been discussed.

Integrating large-scale wind energy in modern power systems is demanding more efficient mathematical models to properly address classical assumptions in power system problems. In particular, there are two main assumptions in power system problems with wind integration that have not been adequately studied yet; First, non-linear AC power flow equations have been linearized in most of the literature. Such simplifications can lead to inaccurate power flow calculations that may result in other technical issues. Second, wind power uncertainties are inevitable and have been mostly modelled using the traditional uncertainty modelling approaches, that may not be suitable for large-scale wind power integration. In this paper, we address both challenges: we present a tight second-order conic relaxation (SOCR) for optimal power flow (OPF) problem, and simultaneously, implement the new effective budget of uncertainty approach for uncertainty modelling that determines the maximum wind power admissibility first and then addresses the uncertainty in the model. To the best of our knowledge, this is the first study that proposes an effective robust second-order conic programming (ERSOCP) model that simultaneously addresses the issues of power flow linearization and wind power uncertainty with the new paradigm on the budget of uncertainty approach. Our numerical results show the merit of the proposed model against traditional linearized power flow equations as well as traditional uncertainty modelling approaches.

Wireless power transfer promises to revolutionize the way we use and power mobile devices. However, low transfer efficiencies prevent this technology from seeing wide scale real-world adoption. The aim of this work is to use quasioptics to develop a system composed of a dielectric lens fed by a phased array to reduce spillover losses, increasing the beam efficiency, while working on the antenna system’s Fresnel zone. The DC-RF electronics, digital beamforming and beam-steering by an FPGA, and radiating 4x4 microstrip patch phased array have been developed and experimented upon, while the lens has been designed and simulated. This paper details these preliminary results, where the phased array radiation pattern was measured, showing that the beam is being generated and steered as expected, prompting the lens construction for the complete system experimentation.

Motivated for improving the efficiency and reliability of wind turbine energy conversion, this paper presents an advanced control design that enhances the power regulation efficiency and re-liability. The constrained behaviour of the wind turbine is taken into account, by using the barrier Lyapunov function in the analysis of the Lyapunov direct method. This, consequently, guarantees that the generated power remains within the desired bounds to satisfy the grid power demand. Moreover, a Nussbaum-type function is utilized in the control scheme, to cope with the unpre-dictable wind speed. This eliminates the need for accurate wind speed measurement or estimation. Furthermore, via properly designed adaptive laws, a robust actuator fault-tolerant capability is integrated into the scheme, handling the model uncertainty. Numerical simulations are performed on a high-fidelity wind turbine benchmark model, under different fault scenarios, to verify the effectiveness of the developed design. Also, a Monte-Carlo analysis is exploited for the evaluation of the reliability and robustness characteristics against the model-reality mismatch, measurement errors and disturbance effects.

The power-generation capacity of grid-connected photovoltaic (PV) power systems is increasing. As output power forecasting is required by electricity market participants and utility operators for the stable operation of power systems, several methods have been proposed using physical and statistical approaches for various time ranges. A short-term (30 min ahead) forecasting method has been previously proposed by our laboratory for geographically distributed PV systems using motion estimation. This study focuses on an important parameter for estimating the proposed motion and optimizing the parameter. This parameter is important because it is associated with the smoothness of the vector field, which is the result of motion estimation and influences the forecasting accuracy. In the periods with drastic power output changes, the evaluation was conducted on 101 PV systems located within a circle of 15-km radius in the Kanto region of Japan. The results indicate that the absolute mean error of the proposed method with the optimized parameter is 10.3%, whereas that of the persistent prediction method is 23.7%. Therefore, the proposed method is effective in forecasting for periods when PV output changes drastically in a short time.

The paper deals with the Compound Inverse Rayleigh distribution, shown to constitute a proper model for the characterization of the probability distribution of extreme values of wind-speed, a topic which is gaining growing interest in the field of renewable generation assessment, both in view of wind power production evaluation and the wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model - already proven to be a valid model for extreme wind-speeds - by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity to interpret different field data is illustrated, also by means of numerous numerical examples based upon real wind speed measurements. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. In practice, the method allows to express one’s prior beliefs both in terms of parameters, as customary, and/or in terms of probabilities. The results of a large set of numerical simulations – using typical values of wind-speed parameters - are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information.

We study the efficient computation of power indices for weighted voting games with precoalitions amongst subsets of players (reflecting, e.g., ideological proximity) using the paradigm of dynamic programming. Starting from the state-of-the-art algorithms for computing the Banzhaf and Shapley-Shubik indices for weighted voting games we present a framework for fast algorithms for the three most common power indices with precoalitions, i.e. the Owen index, the Banzhaf-Owen index and the Symmetric Coalitional Banzhaf index, and point out why our new algorithms are applicable for large numbers of players. We discuss implementations of our algorithms for the three power indices with precoalitions in C++ and review computing times as well as storage requirements.

The recent advancements in the field of communication have led data sharing to become an integral part of today's smart cities with the evolution of concepts such as the internet of vehicles (IoV) paradigm. As a part of IoV, Electric Vehicles (EVs) have recently gained momentum as authorities have started expanding their Low Emission Zones (LEZ) in an effort to build green cities with low carbon footprints. Energy is one of the key requirements of EVs not only to support the smooth and sustainable operation of EV itself but to also ensure connectivity between the vehicles and infrastructure with controlling devices like sensors and actuators installed within an EV. In this context, renewable energy sources (such as wind energy) dramatically play their parts in the automobile sector towards designing the energy harvesting electric vehicles (EH-EV) to pare the energy reliance on the national grid. In this article, a novel approach is presented to achieve electric generation due to vehicle mobility to support the communication primitives in electric vehicles which enables plenty of IoV use cases in the presence of surplus energy at hand. A small-scale wind turbine is designed to harness wind power for converting it into mechanical power. This power is then fed to the onboard DC generator to produce electrical energy. Furthermore, the acquired power is processed through a regulation circuitry to consequently achieve the desired power supply for the end load, i.e. the batteries installed. The suitable orientation for efficient power generation is proposed on ANSYS-based aerodynamics analysis. The voltages induced by DC generator at No-Load condition are 35V while at Full-Load 25V are generated at rated current of 6.9A, along with the generation of power at around 100W (at constant voltage) at the rated speed of 90 mph for nominal battery charging. Moreover, the acquired data can be monitored via an android application interface by using a Bluetooth module.

We analyzed the peak spring tidal current speeds, annual mean tidal power densities (TPD) and annual energy production (AEP) obtained from experiment 06.1, referred as the "HYCOM model" throughout, of the three dimensional (3D), global model HYCOM in an area covering the Baja California Pacific and the Gulf of California. The HYCOM model is forced with astronomical tides and surface winds alone, and therefore is particularly suitable to assess the tidal current and wind-driven current contribution to in-stream energy resources. We find two areas within the Gulf of California, one in the Great Island Region and one in the Upper Gulf of California, where peak spring tidal flows reach speeds of 1.1 meters per second. Second to fifth-generation tidal stream devices would be suitable for deployment in these two areas, which are very similar in terms of tidal in-stream energy resources. However, they are also very different in terms of sediment type and range in water depth, posing different challenges for in-stream technologies. The highest mean TPD value when excluding TPDs equal or less than 50 W/m² (corresponding to the minimum velocity threshold for energy production) is of 172.8 W/m², and is found near the town of San Felipe, at (lat lon) = (31.006 -114.64); here energy would be produced during 39.00% of the time. Finally, wind-driven currents contribute very little to the mean TPD and the total AEP. Therefore, the device, the grid, and any energy storage plans need to take into account the periodic tidal current fluctuations, for optimal exploitation of the resources.

Although different assessments and evaluations of Dual-Miller cycle performed, specified output power and thermal performance associated with engine determined. Besides, multi objective optimization of thermal efficiency, Ecological Coefficient of performance ( ) and Ecological function ( ) by the mean of NSGA-II technique and thermodynamic analysis performed. The Pareto optimal frontier obtaining the best optimum solution is chosen by fuzzy Bellman-Zadeh, LINMAP, and TOPSIS decision-making techniques. Based on the results, performances of dual-Miller cycles and their optimization are improved.

The Doubly-Fed Induction Generator (DFIG) has significant features in comparison with Fixed Speed Wind Turbine (FSWT), which has popularized its application in power system. Due to partial rated back-to-back converters in the DFIG, Fault Ride-Through (FRT) capability improvement is one of the great subjects regarding new grid code requirements. To enhance the FRT capability of the DFIG, many studies have been carried out. Fault current limiting devices as one of the techniques are utilized to limit the current level and protect switches of the back-to-back converter from over-current damage. In this paper, a review is done based on fault current limiting characteristic of the proposed fault current limiting devices Therefore, Fault Current Limiters (FCLs) and Series Dynamic Braking Resistors (SDBRs) are mainly taken into account. Operation of all configurations including their advantages and disadvantages is explained. Impedance type and the fault current limiting devices’ location are two important factors, which significantly affect the DFIG behaviour in the fault condition. These two factors are basically studied by the simulation and their effects on the key parameters of the DFIG are investigated. Finally, future works in respect to the FCL application in the FRT improvement of the DFIG have also been discussed.

In this paper we discuss a problem of generalization of binomial distributed triangle, that is sequence A287326 in OEIS. The main property of A287326 that it returns a perfect cube n as sum of n-th row terms over k; 0 ≤ k ≤ n−1 or 1 ≤ k ≤ n, by means of its symmetry. In this paper we have derived a similar triangles in order to receive powers m = 5; 7 as row items sum and generalized obtained results in order to receive every odd-powered monomial n^2m+1; m ≥ 0 as sum of row terms of corresponding triangle. In other words, in this manuscript are found and discussed the polynomials D_m(n,k) and U_m(n,k), such that, when being summed up over k in some range with respect to m and n returns the monomial n^2m+1.

This paper proposes the impact of plug-in electric vehicles integrated into power distribution system based on voltage dependent control. The plug-in electric vehicles was modeled as the static load model in power distribution systems under balanced load condition. The power flow analysis is determined by using the basic parameters of the electrical network. The main point of this study are compare with voltage magnitude profiles, load voltage deviation, and total power losses of the electrical power system. There are investigating the affected from constant power load, constant current load, constant impedance load and plug-in electric vehicles load, respectively. The IEEE 33 bus test system is used to test the proposed method by assigning each load type to a balanced load in steady state and applied the solving methodology based on the bus injection to branch injection matric, branch current to bus voltage matrix, and current injection matrix to solve the power flow problem. The simulation results showed that the plug-in electric vehicles load had the lowest impact compared to other loads. The lowest plug-in values for the electric vehicle loads were 0.062, 119.67 kW and 79.31 kVar for the load voltage deviation, total active power loss and total reactive power loss, respectively. Therefore, this study can be verified that the plug-in electric vehicles load were affected to the lowest of the electrical power system in condition to same sizing and position. So that, in condition to the plug-in electric vehicles load added into the electrical power system with the conventional load type or complex load type could be considered that the affected from the plug-in electric vehicles load in next study.

To implement renewable energy resources, microgrid systems have been adopted and developed into the technology of choice to assure mass electrification in the next decade. Microgrid systems have a number of advantages over the conventional utility grid systems, however, it faces severe instability issues due to continually increasing constant power loads. To improve the stability of the entire system, load side compensation technique is chosen because of its robustness and cost effectiveness. In this particular occasion, a sliding mode controller is developed for microgrid system in the presence of CPL to assure certain control objective of keeping the output voltage constant at 480V. After that, the robustness analysis of the sliding mode controller against parametric uncertainties is presented. The sliding mode controller robustness against parametric uncertainties, frequency variations, and additive white Gaussian noise (AWGN) are illustrated in this paper. Later, the performance of the PID and sliding Mode controller is compared in case of nonlinearity, parameter uncertainties, and noise rejection to justify the selection of Sliding Mode controller over PID controller. All the necessary calculations are reckoned mathematically and results are verified in the virtual platform such as MATLAB/Simulink with the appreciable outcome.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus 13 voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ 14 constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources 15 on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar 16 PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed 17 using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of 18 simulation and statistical results of EO with other optimization techniques showed that EO is more effective 19 and superior.

The aim of this research work consisted of assessing the effects of the COVID-19 pandemic on the interurban public transport system in a rural region with a sparse population density, considering the number of tickets sold and passengers in each locality, as well as the different connecting lines. From a methodological point of view and with the intention of identifying patterns to explain the behaviour of both routes and passengers, a series of variables were selected, becoming determining factors that sought to offer a solution to the search for a common trend. Additionally, data processing by means of statistical analysis and the application of Geographic Information Systems (GIS) tools complemented the procedure. The results obtained in the investigation were provided both by municipality and by interurban route. An interesting finding of the research was the uneven recovery of the municipalities. The localities closest to the attractor nucleus have recovered more quickly to pre-pandemic mobility levels due to their geographical proximity, larger population, higher income per household and the need to access certain public services. In terms of routes, all lines showed significant decreases in ticket sales, although with variations. Although passenger numbers have shown a gradual recovery, the initial loss was considerable, and pre-pandemic normality has not been completely achieved. The authors consider that future research should include other alternative means of transport in these interurban areas, incorporating variables to characterise passengers, such as age, gender...etc.

A “watch and wait” strategy, delaying treatment until active disease manifests, is adopted for most CLL cases; however prognostic models incorporating biomarkers have shown to be useful to predict treatment requirement. In our prospective O-CLL1 study including 224 patients, we investigated the predictive role of 513 microRNAs (miRNAs) on time to first treatment (TTFT). In the context of this study six well-established variables (i.e., Rai stage, beta-2-microglobulin levels, IGVH mutational status, del11q, del17p, and NOTCH1 mutations) maintained significant associations with TTFT in a basic multivariable model, collectively yielding a Harrell's C-index of 75% and explaining 45.4% of the variance in the prediction of TTFT. Concerning miRNAs, 73 out of 513 were significantly associated with TTFT in a univariable model; of these, 16 retained an in-dependent relationship with the outcome in a multivariable analysis. For 8 of these (i.e., miR-582-3p, miR-33a-3p, miR-516a-5p, miR-99a-5p, and miR-296-3p, miR-502-5p, miR-625-5p, and miR-29c-3p) a lower expression correlated with a shorter TTFT, whereas in the remaining eight (i.e., miR-150-5p, miR-148a-3p, miR-28-5p, miR-144-5p, miR-671-5p, miR-1-3p, miR-193a-3p, and miR-124-3p) the higher expression was associated with shorter TTFT. Integrating these miRNAs into the basic model significantly enhanced predictive accuracy, raising the Harrell’C index to 81.1% and the explained variation in TTFT to 63.3%. Moreover, the inclusion of the miRNA scores enhanced the Integrated Discrimination Improvement (IDI) and the Net Reclassification Index (NRI), underscoring the potential of miRNAs to refine CLL prognostic models and providing insights for clinical decision-making. In silico analyses on the differently expressed miRNAs revealed their potential regulatory functions of several pathways, including those involved in the therapeutic responses. To add a bio-logical context to the clinical evidence, a miRNA-mRNA correlation analysis revealed at least one significant negative correlation between 15 of the identified miRNAs and a set of 50 Artificial Intelligence (AI) selected genes, previously identified by us as relevant for TTFT prediction in the same cohort of CLL patients. In conclusion, the identification of specific miRNAs as predictors of TTFT holds promise for enhancing risk stratification in CLL to predict therapeutic needs. However, further validation studies and in-depth functional analyses are required to confirm the robustness of these observations and to facilitate their translation into meaningful clinical utility.

Concurrent Optical and Magnetic Stimulation (COMS) combines extremely low frequency electromagnetic and light stimulation modalities for enhanced wound healing. In this report, we investigated the potential mechanistic synergism between magnetic and light components by comparing their individual and combined cellular responses. Although each individual stimulation mode was capable of stimulating cell proliferation, magnetic fields exposure alone produced greater proliferation enhancement than light alone, yet their combined effects of were supra-additive of the individual responses. Reactive oxygen species were incrementally reduced by exposure to light, magnetics fields and their combination, where statistical significance was ultimately achieved. On the other hand, ATP production was significantly enhanced in response to magnetic exposure alone or in combination with light. These results suggest that mitochondrial respiratory efficiency was preferentially improved by the combination of the two stimuli. Protein expression related to cell proliferation was preferentially enhanced by the combinatory COMS modality as were the protein levels of the TRPC1 cation channel previously implicated as part of a calcium-mitochondrial signaling axis invoked by electromagnetic exposure and involved in proliferation. These results corroborate that light facilitates functional synergism with magnetic fields that ultimately impinge on mitochondria-dependent developmental responses. The aminoglycoside antibiotics (AGAs) have been previously shown to antagonize TRPC1-mediated magnetotransduction. Streptomycin applied during the exposure to any of the stimulation modes reduced proliferation enhancement, whereas streptomycin added after the exposure did not. Notably, the COMS modality and magnetic field exposure were capable of partially overcoming streptomycin antagonism of proliferation, whereas light alone was not. Transductional antagonism of combinatorial photon-electromagnetic effects by streptomycin thus aligns with previous studies showing that the AGAs block TRPC1-mediated magnetotransduction when applied during exposure. The prophylactic usage of the AGAs (neomycin) should be avoided during COMS therapy to maintain clinical efficacy and would be a common concern with most other electromagnetic regenerative paradigms.

Breast cancer is the most common cause of mortality due to cancer for woman both in Lithuania and worldwide. Chances of survival after diagnosis differ significantly depending on the stage of disease at the time of diagnosis and other factors. One way to estimate survival is to construct a Kaplan-Meier estimate for each factor value separately. However, in cases when it is impossible to observe a large number of patients (for example, in case of countries with lower numbers of inhabitants) dividing data into subsets, say, by stage at diagnosis may lead to results where some subsets contain too little data so that results of Kaplan Meier (or any other) method will become statistically incredible. The problem may become even more acute if the researcher would like to use more risk factors, such as stage at diagnosis, sex, place of living, treatment method, etc. Alternatively, Cox models are used to analyse survival data with covariates, and they don’t require dividing the data into subsets according to chosen risks factors (hazards).

Sums of M consecutive squared integers (a+i)^2 equaling squared integers (for a<=1, 0<= i<= M-1) yield remarkable regular linear features when plotting values of M in function of a. These features correspond to groupings of pairs of a values for successive same values of M around straight lines of equation mu*M = 2a and are characterized in this paper for rational values of mu.

The main channel for disseminating information is now the Internet. Users have different expectations for the calibre of websites regarding the posted and presented content. The WEB site's quality is influenced by up to 120 factors, each represented by two to fifteen attributes. A major challenge is quantifying the features and evaluating the quality of a website based on the feature counts. One of the aspects that determines a website's quality is its completeness, which focuses on the existence of all the objects and their connections with one another. It isn’t easy to build an expert model based on feature counts to evaluate website quality, so this paper has focused on that challenge. Both a methodology for calculating a website's quality and a parser-based approach for measuring feature counts are offered. We provide a multi-layer perceptron model that is an expert model for forecasting website quality from the "Completeness" perspective. The accuracy of the predictions is 98%, whilst the accuracy of the nearest model is 87%.

Low-sodium salt substitute (LSSS) has the potential in regulating sodium and potassium intake and has been available in China market for years. However, its real-world use and impact to sodium\potassium intake is unclear. Baseline data of 4000 adult participants who participated in three similar-designed randomized controlled trails were pooled together for this study. Self-reported awareness and use of LSSS were collected using the uniform questionnaire, and the 24-h urinary sodium and potassium excretion was used to estimate their dietary intake. Mixed-effects models were developed to assess the relationship between LSSS and 24-h urinary sodium and potassium excretion. 32.0% of the participants reported awareness of LSSS and 11.7% reported its current use. After adjusting location, sex, age, and education, compared with the group of participants unaware of LSSS, participants who were aware but not using LSSS and those who were using LSSS had a lower 24-h urinary sodium excretion by –356.1(95% CI: –503.9, –205.9) mg/d and –490.6(95% CI: –679.2, –293.7), respectively (p&lt;0.001). No significant difference was found for 24-h urinary potassium excretion and sodium-to-potassium ratio among the three groups (p&gt;0.05). In conclusion, although associated with lower sodium intake, the awareness and real-world use of LSSS are still very low in China.

As in every workplace, human sustainability in dental enterprises is connected to air and water quality, eco-friendly and naturally designed working spaces and 4R’s culture. Purpose of this study is to access the preferences and knowledge on circular economy and green building construction in a sample of students and dentists in Greece. Students (N1=93) and dentists (N2= 126) filled in e-questionnaires from April to December 2022. The response rate was 17,88% for N1 and 1.94% for N2. Data revealed that both students and dentists lack knowledge on circular economy (N1=67.7%, N2=68,25%), EU regulations on amalgam disposal (N1=64.5%, N2=58.73%) and plastic recycling (N1=76.34%, N2=76,98) while they do recycle at home (N1= 80.6%, N2=82.54%) and have participated in voluntary environmental actions (N1=58.1%, N2=66.67%). Gender influences the importance of factors related to green dental practices, with women students being more prone to answer positively as important for increase costs for network changes (p=0.02), lack of environmental awareness of manufacturers (p=0.057), and poor wastewater management (p=0.01). Students from urban areas are more prone to answer positively for lack of state financial support (p=0.02), low level of green design in the building (p=0.03), low direct financial benefit of a green dental office (p=0.04), low benefit to the reputation of the green dental office (p=0.02), lack of continuing education training seminars on green dentistry (p=0.05). For dentists, no significant relationships were observed except of a weak positive relationship in increase in costs for changes related to utility networks (p=0.08) while increased wasteful energy (p=0.12) and waste of dental materials (p=0.19) seemed important only for dentists in urban areas. Women dentists were more prone to answer positively on wasting energy (p=0.024) and use of unapproved disinfection products (p=0.036). The findings contribute ideas and solutions on green dental office buildings and sustainable behaviors through educational activities and social perspective of factors such as age, experience in dentistry, gender, and urbanism. It also inspires future multi-disciplinary research on dental quality assurance, psychology of environmentalism, economics, and behavioral science in dentistry.

Invasive weeds cause significant crop yield and economic losses in agriculture. The highest in-direct impact may be attributed to the role of invasive weeds as virus reservoirs especially within the commercial growing areas. The new tobamovirus tomato brown rugose fruit virus (ToBRFV), recently identified in the Middle-East, overcomes the Tm-22 resistance allele in the cultivated tomato varieties grown in greenhouses. In this study, we determined the role of invasive weed species as potential hosts for ToBRFV and pepino mosaic virus (PepMV). Out of all tested weed species, the invasive species So-lanum elaeagnifolium and S. rostratum, mechanically inoculated with ToBRFV, were positive for To-BRFV in both enzyme linked immunosorbent assay (ELISA) and RT-PCR tests. S. rostratum was also positive for PepMV. No conspicuous phenotype was observed on ToBRFV infected S. elaeagnifolium plants suggesting a hostplant associated defense response. S. rostratum plants inoculated with either ToBRFV alone or a mixture of ToBRFV and PepMV-IL, contained high ToBRFV levels. In addition, when inoculated with ToBRFV or PepMV-IL disease symptom manifestations were observed in S. rostratum plants and the symptoms were exacerbated upon mixed infections with both viruses. The distribution and abundance of both Solanaceae species increase the risks of virus transmission between species.

Immune escape is observed with SARS-CoV-2 Omicron (Pango lineage B.1.1.529), the predominant circulating strain worldwide. Booster dose was shown to restore immunity against Omicron infection, however, real world data comparing mRNA (BNT162b2; Comirnaty) and inactivated vaccine (CoronaVac; Sinovac) homologous and heterologous boosting is lacking. A retrospective study was performed to compare the rate and outcome of COVID-19 in healthcare workers (HCWs) with various vaccination regime during a territory-wide Omicron outbreak in Hong Kong. During the study period 1 Feb – 31 Mar 2022, 3167 HCWs were recruited, 871 HCWs reported 746 and 183 episodes of significant household and non-household close contact. 737 HCWs acquired COVID-19 which were all clinically mild. Time dependent Cox regression showed that, comparing with 2-dose vaccination, 3-dose vaccination reduced infection risk by 31.7% and 89.3% in household contact and non-household close contact respectively. Using 2-dose BNT162b2 as reference, 2-dose CoronaVac recipient had significantly higher risk of being infected (HR 1.69 P<0.0001). Three-dose BNT162b2 (HR 0.4778 P<0.0001) and 2-dose CoronaVac + BNT162b2 booster (HR 0.4862 P=0.0157) were associated with lower risk of infection. Three-dose CoronaVac and 2-dose BNT162b2 + CoronaVac booster were not significantly different from 2-dose BNT162b2. The mean time to achieve negative RT-PCR or E gene cycle threshold 31 or above was not affected by age, number of vaccine dose taken, vaccine type and timing of the last dose. In summary, we have demonstrated lower risk of breakthrough SARS-CoV-2 infection in HCWs given BNT162b2 as booster after 2 doses of BNT162b2 or CoronaVac.

The option of decarbonizing urban freight transport using Battery Electric Vehicle (BEV) seems promising.However, there is currently a strong debate whether Fuel Cell Electric Vehicle (FCEV) might be the bettersolution. The question arises as to how a fleet of FCEV influences the operating cost, the Greenhouse Gas(GHG) emissions and primary energy demand in comparison to BEVs and to Internal Combustion EngineVehicle (ICEV). To investigate this, we simulate the urban food retailing as a representative share of urbanfreight transport using a multi-agent transport simulation software. Synthetic routes as well as fleet size andcomposition are determined by solving a Vehicle Routing Problem (VRP). We compute the operating costsusing a total cost of ownership (Total Cost of Ownership (TCO)) analysis and the use phase emissions as wellas primary energy demand using the Well To Wheel (WTW) approach. While a change to BEV results in 17 -23% higher costs compared to ICEV, using FCEVs leads to 22 - 57% higher costs. Assuming today’s electricitymix, we show a GHG emission reduction of 25% compared to the ICEV base case when using BEV. Currenthydrogen production leads to a GHG reduction of 33% when using FCEV which however cannot be scaled tolarger fleets. Using current electricity in electrolysis will increase GHG emission by 60% compared to the basecase. Assuming 100% renewable electricity for charging and hydrogen production, the reduction from FCEVsrises to 73% and from BEV to 92%. The primary energy requirement for BEV is in all cases lower and forhigher compared to the base case. We conclude that while FCEV have a slightly higher GHG savings potentialwith current hydrogen, BEV are the favored technology for urban freight transport from an economic andecological point of view, considering the increasing shares of renewable energies in the grid mix.

The importance of this study may be defined by using the smart techniques to earned value indicators of residential buildings projects in Republic of Iraq, only one development intelligent forecasting model was presented to predict Schedule Performance Index (SPI), Cost Performance Index (CPI), and To Complete Cost Performance Indicator (TCPI) are defined as the dependent. The approach is principally influenced by the determining numerous factors which effect on the earned value management, that involves Iraqi historical data. In addition, six independent variables (F1: BAC, Budget at Completion., F2: AC, Actual Cost., F3, A%, Actual Percentage., F4: EV, Earned Value. F5: P%, Planning Percentage., and F6: PV, Planning Value) were arbitrarily designated and satisfactorily described for per construction project. It was found that ANN has the capability to envisage the dust storm with a great accuracy. The correlation coefficient (R) has been 90.00%, and typical accuracy percentage has been 89.00%.

This paper presents an overview of the smart electro-clothing systems (SeCSs) targeted at health monitoring, sports benefits, fitness tracking, and social activities. Technical features of the available SeCSs, covering both textile and electronic components, are thoroughly discussed and their applications in the industry and research purposes have been highlighted. In addition, it also presents the developments in the associated areas of wearable sensor systems and textile-based dry sensors. As it became evident during the literature research, such a review on SeCSs covering all relevant issues has not been presented before. This paper will be particularly helpful for new generation researchers investigating the design, development, function and comforts of the sensor integrated clothing materials.

Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. The results show that the strategies derived from the general heuristic are very interesting, all of them deploying roadside units in a circle pattern around the traffic epicenter.

Increased nutrient withdrawal by rapidly expanding intensive cropping systems, in combination with imbalanced fertilization, is leading to potassium (K) depletion from agricultural soils in Asia. There is an urgent need to better understand the soil K-supplying capacity and K-use efficiency of crops to address this issue. Maize is increasingly being grown in rice-based systems in South Asia, particularly in Bangladesh and North East India. The high nutrient extraction, especially K, however, causes concerns for the sustainability of maize production systems in the region. The present study was designed to estimate, through a plant-based method, the magnitude, and variation in K-supplying capacity of a range of soils from the maize-growing areas and the K-use efficiency of maize in Bangladesh. Eighteen diverse soils were collected from several upazillas (or sub-districts) under 11 agro-ecological zones to examine their K-supplying capacity from the soil reserves and from K fertilization (@ 100 mg K kg-1 soil) for successive seven maize crops grown up to V10-V12 in pots inside a net house. A validation field experiment was conducted with five levels of K (0, 40, 80, 120 and 160 kg ha-1) and two fertilizer recommendations based on “Nutrient Expert for Maize-NEM” and “Maize Crop Manager-MCM” decision support tools (DSSs) in 12 farmers’ fields in Rangpur, Rajshahi and Comilla districts in Bangladesh. Grain yield and yield attributes of maize responded significantly (P < 0.001) to K fertilizer, with grain yield increase from 18 to 79% over control in all locations. Total K uptake by plants not receiving K fertilizer, considered as potential K-supplying capacity of the soil in the pot experiment, followed the order: Modhukhali >Mithapukur >Rangpur Sadar >Dinajpur Sadar >Jhinaidah Sadar >Gangachara >Binerpota >Tarash >Gopalpur >Daudkandi >Paba >Modhupur >Nawabganj Sadar >Shibganj >Birganj >Godagari >Barura >Durgapur. Likewise in the validation field experiment, the K-supplying capacity of soils was 83.5, 60.5 and 57.2 kg ha-1 in Rangpur, Rajshahi, and Comilla, respectively. Further, the order of K-supplying capacity for three sites was similar to the results from pot study confirming the applicability of results to other soils and maize-growing areas in Bangladesh and similar soils and areas across South Asia. Based on the results from pot and field experiments, we conclude that the site-specific K management using the fertilizer DSSs can be the better and more efficient K management strategy for maize.

This paper deals with the environmental characterization of a large and densely populated area, with a poor reputation for contamination, considering the contribution of environmental features (air, soil, soil hydraulic and groundwater) and the potential effects on human health. The use of Geographic Information System (GIS) has made possible a georeferenced inventory and, by overlaying environmental information, an operational synthesis of comprehensive environmental conditions. The cumulative effects on environmental features were evaluated, taking into account superposition effects, by means of the spatial multicriteria decision analysis (S-MCDA). The application of the S-MCDA for converging the combination of heterogeneous factors, related to soil, land and water, deeply studied by heterogeneous groups of experts, constitutes the novelty of the paper. The results confirmed an overall higher potential of exposure to contaminants in the environment and higher mortality rates in the study area for some tumours, but hospital admissions for tumours were generally similar to the regional trend. Besides, mortality data may be strictly dependent on the poor socioeconomic conditions, quality of therapy and a lack of welfare in the area relative to the rest of Italy. Finally, as regards the possible relationship between presence of contaminants in the environment and health conditions of the population no definite conclusions can be drawn, although the present study encourages the use of the new proposed methods, that increase the possibilities for studying the combined effect of more environmental factors.

Intracellular aggregates of the alpha-synuclein protein result in cell loss and dysfunction in Parkinson’s disease and atypical parkinsonism, such as multiple system atrophy and dementia with Lewy bodies. Each of these neurodegenerative conditions, known collectively as alpha-synucleinopathies, may be characterized by a different suite of molecular triggers that initiate pathogenesis. The mechanisms whereby alpha-synuclein aggregates in turn mediate cytotoxicity also remain to be fully elucidated. However, recent studies have implicated the cell-to-cell spread of alpha-synuclein as the major mode of disease propagation between brain regions during disease progression. Here, we review the current evidence for different modes of alpha-synuclein cellular release, movement and uptake, including exocytosis, exosomes, tunnelling nanotubes, glymphatic flow and endocytosis. A more detailed understanding of the major modes by which alpha-synuclein pathology spreads throughout the brain may provide new targets for therapies that halt the progression of disease.