The static formation temperature (SFT) is required to determine the thermophysical properties and production parameters in geothermal and oil reservoirs. However, the SFT is not easy to be obtained by both experimental and physical methods. In this paper, a mathematical approach to predicting SFT based on a new model describing the relationship between bottom hole temperature (BHT) and shut-in time was proposed. The unknown coefficients of the model were derived from least squares fit by Particle Swarm Optimization (PSO) algorithm. Besides, the ability to predict SFT based on a few BHT data (such as first 3, 4, or 5 ones of a data set) was evaluated. The accuracy of the proposed method to predict SFT was testified with a deviation percentage less than ±4% and high values of regression coefficient R² (>0.98). The proposed method could be used as a practical tool to predict SFT in both geothermal and oil wells.

The branch prediction units (BPUs) generally have security vulnerabilities, which can be used by attackers to obtain the execution status, jump directions, and jump address of conditional branches, and the existing protection methods cannot defend against these attacks. Therefore, this article proposes a hardware security protection method for conditional branches of embedded systems. This method calculates the number of updates to the branch target buffer (BTB). When it exceeds the threshold, BTB is locked to prevent attackers from analyzing the execution status of branches based on the time difference of whether BTB is updated. Moreover, the hybrid physical unclonable function (PUF) circuit is designed to provide confidentiality protection for the jump directions, jump addresses, and their indexes, preventing attackers from stealing these critical data. If these mechanism fails and attackers successfully tamper with conditional branches, this paper proposes a control flow integrity (CFI) protection mechanism based on branch labels to timely detect tampering with instruction codes, jump addresses, and jump directions. The proposed method is implemented and tested on FPGA. The experimental results show that this method can achieve fine-grained security protection for conditional branches, with about 5.4% resource overhead and less than 5.5% performance overhead.

The study assessed the trapping efficacy of locally-modified 1) Gravid Aedes Trap(GAT) lined with insecticide-treated net (ITN) as a killing agent, 2) Autocidal Gravid Ovitrap(AGO) with sticky board in the semi-field system (SFS) and field setting. Fully-balanced Latin square experiments were conducted to compare GAT lined with ITN vs AGO, both with either yeast or grass infusion. Biogents-Sentinel (BGS) with BG-Lure and no CO2 was used as standard trap for Aedes mosquitoes. In the SFS, GAT outperformed AGO in collecting both nulliparous (65% vs 49%,OR=2.22,[95%CI:1.89-2.60],p

The field dynamics of neutral and charged matter (treated as gauge fields) beyond the event horizon of black holes are investigated. As an extension of the work done in Ganesan (2023) [1], the analysis was done using the combined dynamics of the two-dimensional Yang-Mills and Liouville gravity fields beyond the event horizon. The quantum interactions and symmetry breaking mechanisms of the combined two-dimensional fields are discussed. The second part of this paper explores the quantum dynamics occurring at the event horizon. By considering the structure of the event horizon as a Möbius strip (embedded in three-dimensional space), a formulation for the lower bound of the first energy eigenvalue of a quantum particle (electron) at the event horizon is obtained.

Solidification microstructure is formed under high cooling rates and temperature gradients in powder-based additive manufacturing. In this study, a non-equilibrium multi-phase field method (MPFM), which was based on a finite interface dissipation model proposed by Steinbach et. al., coupled with a CALPHAD database was developed for a multicomponent Ni alloy. A qua-si-equilibrium MPFM was also developed for comparison. Two-dimensional equiaxed micro-structural evolution for the Ni (Bal.)–Al–Co–Cr–Mo–Ta–Ti–W–C alloy was performed at various cooling rates. The temperature–γ fraction profiles obtained under 10^5 K/s using non- and qua-si-equilibrium MPFMs were in good agreement with each other. Over 10^6 K/s, the differences between non- and quasi-equilibrium methods grew as the cooling rate increased. The non-equilibrium solidification was strengthened over a cooling rate of 10^6 K/s. Colum-nar-solidification microstructural evolution was performed under cooling rates from 5×10^5 K/s to 1×10^7 K/s at various temperature gradient values under the constant interface velocity (0.1 m/s). The results showed that as the cooling rate increased, the cell space decreased in both methods, and the non-equilibrium MPFM agreed well with experimental measurements. Our results show that the non-equilibrium MPFM can simulate solidification microstructure in powder bed fusion additive manufacturing.

Count data analysis presents unique challenges due to its discrete nature, often exhibiting excessive zeros and overdispersion. To address these complexities, count models, such as Poisson regression and Negative Binomial regression, have been developed, enabling modeling and prediction of count-based phenomena. Additionally, it’s important to notice that zero inflation, a phenomenon commonly observed in count data, requires specialized techniques for robust analysis. This article provides an overview of count data and count models, explores zero inflation, introduces Likelihood Ratio Tests, and explains how the Vuong Test can be used as a model selection criteria. Furthermore, we created a Vuong Test implementation from scratch using the Python programming language. This implementation enhances the accessibility and applicability of the Vuong Test in real-world scenarios, providing a valuable contribution to the academic community, since Python didn’t have an implementation of this statistical test.

Verticillium dahliae (Vd) and Fusarium oxysporum f. sp. lycopersici (Fol) are two major fungal pathogens that infect tomato plants, causing significant challenges in their control since both pathogens can persist in the soil for several years even in the absence of a host plant and no effective fungicides are available at present. This study investigated the efficacy of two biocontrol formulations, Clonotri and Strepse, against Vd and Fol, and their impact on tomato fruit quality and yield under greenhouse conditions. Pathogenicity experiment demonstrated that the Clonotri formulation, containing Trichoderma and Clonostachys spores, significantly reduced Fusarium wilt disease by 32% compared to the control group. However, in Vd pathogenicity experiment, the formulations did not exhibit disease reduction, although the treatment with Strepse, containing Streptomyces and Pseudomonas microorganisms, resulted in preserved total fruit number when compared to uninfected plants. Analysis of fruit quality attributes revealed no significant differences among the various interventions. Furthermore, Fol infection in the first fruit set significantly increased fruit firmness, while Vd infection resulted in elevated levels of total soluble solids in fruits. These findings demonstrate that the evaluated biocontrol formulations provide a degree of protection against fungal wilt pathogens in tomato plants and can increase yield in greenhouse conditions, while having minimal impact on overall fruit quality attributes.

The Circular Bioeconomy (CBE) combines the concepts of bioeconomy and circular economy. As an alternative concept to the current fossil-based, linear economy, it de-scribes an economy based on the efficient valorization of biomass. It is regional in nature and aims to improve sustainability. An analysis of the transition process, by identifying its success criteria and assessing its impacts through the modelling of technology-specific scenarios is necessary to ensure that CBE concepts are sustainable. However, a compre-hensive consideration of regional influences on both is lacking. Based on extensive literature research and an expert survey, we (i) present a compre-hensive catalog of CBE success criteria and discuss their region-specific character and (ii) develop a methodology based on evaluation matrices that enable to match CBE technolo-gies with regions. The matrices support the evaluation of technological and regional characteristics influencing the successful CBE implementation. The results show that the success criteria "biomass resources", "technological", and "social" are perceived as highly important, and that most of the success criteria are both region- and technology-specific, highlighting the relevance of developing matrices to match them. We describe such matrices indicatively for the two broadest and most im-portant success criteria clusters “social acceptance” and “biomass supply chain”. With this, we substantiate the regional nature of CBE and raise the awareness on the importance of considering regional conditions in CBE transition processes. Furthermore, we provide practical guidance on how regional conditions can be reflected in the selection of technologies, e.g. in regional CBE technology scenarios.

The synchronization of laser and X-ray sources is essential for time-resolved measurements in the study of ultrafast processes, including photo-induced piezo-effect, shock wave generation, and phase transition. On the one hand, the optical diagnostics (by synchronization of two laser sources) provides information about change in vibration frequencies, shock waves dynamics, linear and nonlinear refractive index behavior. On the other hand, the optical pump – X-ray probe diagnostics give opportunity to directly reveal the lattice dynamics. To integrate two approaches into a unified whole one need to create a robust method for synchronization of two systems with different repetition rate up to MHz range. In this paper, we propose a universal approach utilizing a field-programmable gate array (FPGA) to achieve precise synchronization between different MHz sources such as various lasers and synchrotron X-ray sources. This synchronization method offers numerous advantages, such as high flexibility, fast response, and low jitter. Experimental results demonstrate successful synchronization of two different MHz systems with a temporal resolution of 250 ps for these systems. This enables ultrafast measurements with sub-nanosecond resolution, facilitating the uncovering of complex dynamics in ultrafast processes.

Milk MIR spectra have been shown to provide valuable information on a wide range of traits to be used in dairy cattle breeding programs. Selecting the most informative variables from complex data can improve prediction accuracy and model robustness and, consequently, the interpretability of MIR spectra. Thus, we aimed to investigate the prediction performance of feature selection methods based on MIR spectra data, using the milk fatty acid (FA) profile as an example to illustrate the evaluated procedure. Data of MIR spectra, milk test-day records, and reference FA concentrations of 155 first-parity Holstein cows were used in the analyses. Four models comprising different explanatory variables and five feature selection methods were evaluated. The results indicated that the Competitive Adaptive Reweighted Sampling (CARS) method can effectively select the most informative variables from the MIR spectra, resulting in higher prediction accuracies than other variable selection approaches. The model including selected MIR spectra and cow information variables [days in milk at the test day, age at the test day, pregnancy stage (in days), number of days open, number of inseminations, and somatic cell count] yielded the best FA profile predictions based on Partial Least Square regression. In particular, ten FAs (C8:0, C10:0, C14:1, C17:0 isomers, C18:1, C18:1 isomer, medium-chain FA, unsaturation FA, monounsaturated FA, and polyunsaturated FA) presented accuracies based on the determination coefficient (R2cv) ranging from 0.66 to 0.85 in internal validation and from 0.65 to 0.84 in external validation. By running CARS 1,000 times in internal validations, we obtained the frequency of selected milk MIR wavenumber for 35 FAs. The most related wavenumbers to FAs were found within 1,003 to 1,145 cm-1, while other discrete areas were between 1,651 to 1,797 and 2,834 to 2,954 cm-1. These biomarkers may give insights into the relationship between MIR spectra and FA phenotypes. In conclusion, using CARS and cow information improved predictions of FAs based on MIR spectra in Chinese Holstein dairy cows. Additional validation studies should be conducted as larger datasets become available.

The virtually complete loss of intestinal worms, known as helminths, from Western society has resulted in elimination of a range of helminth-induced morbidities. Unfortunately, that loss has also led to inflammation-associated deficiencies in immune function, ultimately contributing to widespread pandemics of allergies, autoimmunity, and neuropsychiatric disorders. Several socio-medical studies have examined the effects of intentional reworming, or self-treatment with helminths, on a variety of inflammation-related disorders. In this study, the latest results from ongoing socio-medical studies are described. The results point toward two important factors that appear to be overlooked in some if not most clinical trials. Specifically, (a) the method of preparation of the helminth can have a profound effect on its therapeutic efficacy, and (b) variation between individuals in the effective therapeutic dosage apparently covers a 10-fold range, regardless of the helminth used. These results highlight current limits in our understanding of the biology of both hosts and helminths, and suggest that information from self-treatment may be critical in moving the field forward into mainstream medicine.

Neuroprotective strategies for stroke remain inadequate. Nanoliposomes comprised of phos-phatidylcholine, cholesterol and monosialogangliosides (NL) induced an antioxidant protective response in endothelial cells exposed to amyloid insults. We tested the hypotheses that NL will preserve SH-SY5Y neuroblastoma cell viability following hypoxic injury and will reduce injury in mice following middle cerebral artery occlusion (MCAO). Neuroblastoma were exposed to 20-hour physoxic (5% oxygen) or hypoxic (1% oxygen) condition without or with NL (100 or 300 µg/mL). Viability was measured using calcein-AM fluorescence and SH-SY5Y gene expression of antioxidant proteins heme oxygenase-1 (HO-1), NAD(P)H quinone dehydrogenase 1 (NQO1) and superoxide dismutase 1 (SOD1) were measured by quantitative polymerase chain reaction. C57BL/6J mice were treated with saline (N=8) or NL (10000 ug/mL, N=7) while undergoing 60-minute MCAO followed by reperfusion. Day 2 post-injury neurologic impairment score and infarction size were compared. Neuroblastoma showed reduced viability following hypoxia that was reversed by NL. NL increased gene expression of HO-1, NQO1 and SOD1 versus controls. NL-treated mice showed reduced neurologic impairment and brain infarct size (18.8±2% versus 27.3±2.3%, p=0.017) versus controls. NL reduced stroke injury in mice subjected to MCAO likely through induction of an antioxidant stress response. NL is a candidate novel agent for stroke.

Current sampling methods for detecting the presence of the invasive freshwater hydrozoan Craspedacusta sowerbii rely mainly on visual confirmation of the medusa stage. Confirming the presence of the polyp stage is equally important to observing medusae since typical late summer/early fall occurrences or observations of medusae are sporadic though becoming more frequent. The polyp stage is important as it is the organism’s primary stage and is present throughout the year depending on water temperatures. Therefore, sampling methods for the polyp stage are commonly the collection of substrates such as rocks, plants or pieces of wood in a given body of water and can be cumbersome to examine. Based on preliminary culturing of the polyp stage on glass and plastic microscope slides in the lab, we designed a novel sampling methodology based on submerging 4 substrate types (small glass petri dishes, Hester-Dendy plates, plastic and glass microscope slides) to confirm the presence of C. sowerbii polyps in the field. We tested this method in various lakes in the Illinois-Indiana region (USA). The sampling method we designed was effective in that C. sowerbii polyps (and sometimes colonies) were found on both plastic and glass slides. While this method can be sufficient for detection of the polyp stage, it also shows significant potential for improvement; we highlight water flow and competition and predation from other organisms as significant factors influencing the collection of C. sowerbii polyps for future methodologies.

A novel coronavirus (2019-nCoV) was first identified in Wuhan, Hubei Province, and then spreads to the other Provinces of China. 2019-nCoV was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-CoV. Previous studies have found ACE2 is abundantly present in humans in the epithelia of the lung and small intestines, and they found ACE2 expression in the basal layer of the non-keratinizing squamous epithelium in nasal and oral mucosa and the nasopharynx. Here based on the public single-cell RNA-Seq datasets, we analyzed the ACE2 expression in the nasal, mouth, lung, and colon tissues. We find that the number of ACE2-expressing cells in the nasal tissue and mouth is comparable to the number of ACE2-expressing cells in the lung tissue and colon. We also find that ACE2 tends to be co-expressed with HLA-DRB1, which plays a central role in the immune system by presenting peptides derived from extracellular proteins, in the nasal, mouth, lung, and colon tissues at single-cell resolution. We hope this provides valuable information for virus-prevention strategy and therapeutic strategy development.

During an epidemic outbreak it is useful for planners and responsible authorities to be able to plan ahead to estimate when an outbreak of an epidemic is likely to ease and when the last case can be predicted in their area of responsibility. Theoretically this could be done for a point source epidemic using epidemic curve forecasting. The extensive data now coming out of China makes it possible to test if this can be done using MS Excel a standard spreadsheet program available to most offices. The available data is divided up for whole China and the different provinces. This and the high number of cases makes the analysis possible. Data for new confirmed infections for Hubei, Hubei outside Wuhan, China excluding Hubei as well as Zhejiang and Fujian provinces all follow a log-normal distribution that can be used to make a rough estimate for the date of the last new confirmed cases in respective areas. In the version 2 continuation work, 9 additional days were added for the Chinese data to evaluate the previous predictions. The extra data then available from China follows the previous predicted trend supporting the usefulness of this simple technique. In the version 2 we also tested the feasibility for a non-specialist to make similar predictions using additional data from S Korea now available. In this third continuation the predictions for Version 2 are evaluated for S Korea and fits well the beginning of the decline but it seems to be difficult to bring down numbers of cases per day under about 100 new cases per day, potential reasons for this is discussed. To further evaluate when in a prediction becomes reliable the Chinese data was used to evaluate to make predictions for each day around the peak in number of cases and after2-3 consecutive days of decreasing new cases per day the prediction becomes reliable. In version 3 data for Italy just reaching this point was used to make further predictions for that country. A second new analysis was also added to use the fitted equation to detect when the acceleration of new cases per day stopped increasing exponentially. In the Chinese case this measured point coincides with the date of the complete Hubei lockdown and in the new Italian analysis it coincides with the mandatory Italian lockdown. Predicted dates for the end of the Italian outbreak is also added. In version 4 we expand the analysis to selected European countries, USA and the World as a whole and try to predict the end of the outbreak. We further discuss the apparent success of the used techniques that might work to introduce a “new normal” not very different to the previous to stop secondary outbreaks of COVID19 and future COVIDs that are sure to come.

In this ‘New Normal' post-COVID-19 modern world, people's health is becoming increasingly important to track. An advanced technology that uses sensory instruments to track and record critical parameters and communicates with others is the need of the time. It's difficult to keep track of all of the medical parameters and post-operative data of people with non-communicable diseases like diabetes and heart disease on a continuous basis. The system discussed here to be designed for patients who are confined to their homes, particularly when going out and being exposed to the outer world is prohibited. This paper proposed a groundbreaking health management system based on the Internet of Things (IoT) for accessing patient medical parameters in both local and remote areas. When a person's wellbeing becomes urgent, this initiative seeks to send an emergency alert to family members or loved ones. A cloud server records data from the patient's temperature sensor and pulse sensor; the data is analyzed using support vector machine algorithms to identify irregular conditions, and an emergency message is sent to the rest of the family via a mobile application, as well as a warning message to the nearest hospital.

This work investigates into the enhancement of iris recognition systems through a two-module approach focusing on low level image preprocessing techniques and advanced feature extraction. The first module is dedicated to the preprocessing of iris images, leveraging the Canny algorithm for edge detection followed by the circle-based Hough transform for precise iris extraction. This process, integral to our methodology, ensures the quality and consistency necessary for the subsequent Binary Statistical Image Features (BSIF) analysis. The second module employs the BSIF technique, incorporating domain-specific filters trained on iris-specific data, for robust biometric identification. By combining these advanced image preprocessing techniques, the proposed method addresses key challenges in iris recognition, such as occlusions, varying pigmentation, and textural diversity. Experimental results on the Human-inspired Domain-specific Binarized Image Features (HDBIF) Dataset composed of 1892 iris images demonstrate the effectiveness of the developped approach, with potential future improvements including adaptive algorithms and machine learning integrations for enhanced performance in diverse and unpredictable real-world applications. The novel contributions of this paper lie in the provision of a reproducible research framework, making the iris-domain-specific BSIF filters, training patches, testing database, and source codes publicly available for further application and study.

Off-grid electrification planning increasingly recognizes the importance of productive use of electricity (PUE) to promote community value creation and (financial) project sustainability. To ensure a sustainable and efficient integration in the community and energy system, PUE assets must carefully be evaluated to match both the community needs and the residential electricity demand patterns. We propose a novel methodology interlinking qualitative interviews, statistical analysis, and energy system modelling to optimize decision-making for PUE integration in off-grid energy systems in rural Madagascar by aligning relevant PUE effectively with anticipated residential electricity demand patterns based on socio-economic determinants of the community. We find that a possible contribution of the PUE to reducing the electricity costs depends signifi-cantly on three factors: 1. the residential electricity consumption patterns that are influenced by the socio-economic composition of the community, 2. the degree of flexibility of i) PUE assets and ii) operational preferences of the PUE user, and 3. the capacity of community members to finance and operate PUE assets. Our study demonstrates that significant cost reductions for PUE-integrated off-grid energy systems can be achieved by applying our proposed methodology. When matching PUE and residential consumption patterns, the integration of PUE assets in residential community energy system can reduce the financial risk of operators, provided the PUE enterprise operates reliably and sustainably. We highlight that the consideration of local value chains and co-creation approaches are essential to ensure the energy system is addressing the community’s needs, creates value for the community, enhances the project´s financial sustainability, and is achieving the overall objectives of decentralized energy system planning.

For a number of years heritage resources have suffered the negative effects of tourist pressure. Overtourism has been generating a wide-ranging debate on this issue. This work focuses on the strategies and measures adopted to address overtourism during the last 30 years in heritage attractions, which are much less studied than urban heritage centres. Specifically, it analyses measures relating to the management of site capacities, based on the concept of tourist carrying capacity, using the content analysis as a methodology. We have used the Alhambra in Granada as a case study, as one of the most visited Spanish World Heritage Sites. The results obtained reflect a strong consensus on the need to introduce measures to restrict tourist activity, although these measures imply a great effort in terms of management and tend to be taken advantage of by some stakeholders for their own benefit. The extensive time frame of the measures adopted allows us to reflect on the possibilities and limitations of dealing with overtourism by using capacity management strategies, and to extract useful conclusions for other heritage sites with similar problems.

Chronic exposure to the nephrotoxic metal pollutant, cadmium (Cd), has been associated with hypertension, but the mechanism by which it raises blood pressure is not understood. We hypothesize that exposure to Cd reduces the glomerular filtration rate (GFR), which in turn, causes a rise in blood pressure. Data were collected from 447 Thai subjects with a mean age of 51.1 years, of which 48.8% had hypertension, 15.4% had diabetes and 6.9% had an estimated GFR (eGFR) below 60 mL/min/1.73 m2 (low eGFR). The mean blood and urinary Cd concentrations were 2.75 and 4.23 µg/L, respectively. The prevalence odds ratio (POR) for hypertension rose twofold in those with blood Cd levels of 0.61-1.69 µg/L or urinary Cd excretion levels ≥ 0.98 µg/g creatinine. In the hypertensive group, the eGFR was inversely associated with age (β =−0.517), the Cd excretion rate (β = −0.177), and diabetes (β = −0.175). Mean eGFR in the normotensive group was 7.5 mL/min/1.73 m2 higher than the hypertensive with a similar Cd body burden. Mean systolic blood pressure (SBP) in those with low or medium eGFR plus heavy Cd body burden was 9.5 mmHg higher than those with the same Cd body burden and a normal eGFR. By mediation analysis, a 22.7% increase in SBP and a 5% increase in diastolic blood pressure (DBP) were attributable to the effect of Cd on GFR. Thus, a rise of blood pressure appears to be a consequence of GFR loss due to Cd-induced kidney damage. This finding is consistent with a well-known role of the kidney in long-term blood pressure regulation.

This article raise a topic of critical examination of polypropylene, a key polymeric material, and its extensive application within the automotive industry, particularly focusing on the manufacturing of brake fluid reservoirs. The study aims to enhance the understanding of polypropylene's behavior under mechanical stresses through a series of laboratory destruction tests and numerical simulations, emphasizing the Finite Element Method (FEM). A novel aspect of this research is the introduction of the PEAK parameter, a groundbreaking approach designed to assess the material's resilience against varying states of strain, known as triaxiality. This parameter facilitates the identification of critical areas prone to crack initiation, thereby enabling the optimization of component design with a minimized safety margin, which is crucial for cost-effective production. The methodology involves conducting burst tests to locate crack initiation sites, followed by FEM simulations to determine the PEAK threshold value for the Sabic 83MF10 polypropylene material. The study successfully validates the predictive capability of the PEAK parameter, demonstrating a high correlation between simulated results and actual laboratory tests. This validation underscores the potential of the PEAK parameter as a predictive tool for enhancing the reliability and safety of polypropylene automotive components. The research presented in this article contributes significantly to the field of material science and engineering by providing a deeper insight into the mechanical behavior of polypropylene and introducing an effective tool for predicting crack initiation in automotive components. The findings hold promise for advancing the design and manufacturing processes in the automotive industry, with potential applications extending to other sectors.

The dynamic evolution and variation of electrical loads is now a priority for optimum management and, above all, forecasting. Indeed, these dynamic load variations require computer tools able to implement optimal load forecasting models. Scientific research into automated models for forecasting electrical loads therefore represents a challenge for scientific researchers. Several research studies have therefore been carried out. These include machine learning approaches such as: LSTM (Long Short-Term Memory), Support Vector Machine (SVM) and others. This article proposes a comparison study between a hybrid model based on the wavelet transform coupled with the adaboost method, and LSTM, for forecasting electricity consumption loads. Python 3.10 was used for the studies. The first results obtained consisted in the study of electricity load forecasts over four (04) data sets of the year (January, April, August and December). These results are very satisfactory, showing a good correlation between the real results of the electrical load consumption data, and the results of the implemented model. The electrical load consumption data are collected from a renewable energy production source: photovoltaic solar energy. The model test results (R2) obtained range from 0.919 to 0.958. These results are representative of real data and reflect the model's performance. The second set of results concerns a comparative study between the methods used by Y. Xie et al (CNN, MLP, LSTM-AM and LSTM-AM-MLP), and our approach. The prediction results obtained between the approaches show a prediction gap ranging from 0.15 to 0.78 for RMSE and 0.83 for MAPE. These results show significant differences between the methods. The minimization of errors by our model, therefore, reflects the model's performance in terms of accuracy, which is necessary for the optimal management of consumer electricity load forecasts in order to ensure balance between supply and demand.

In this study, sodium alginate (SA) was oxidized with potassium periodate to produce an alginate-based tanning agent. Using OSA as a biodegradable tanning agent and a nano-hydroxyapatite (nano-HAp) low concentration suspension to give flame retardancy to leather, eco-design concepts were applied to establish a chrome-, aldehyde-, and phenol-free tanning process. Micro-DSC, 1H NMR, attenuated total reflection mode Fourier transform infrared spectroscopy (FTIR-ATR), and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS) were used to investigate the complex matrix collagen-OSA-nano-HAp. Micro-differential scanning calorimetry (micro-DSC) was used to assess OSA's ability to interact with collagen and stabilize the collagen-OSA matrix, while 1H unilateral nuclear magnetic resonance (NMR) was used to investigate the aqueous environment and limitations around collagen molecules caused by their association with OSA and nano-HAp. Industrial standard tests were used to assess mechanical properties and fire resistance of the new leather prototype. The findings reported here indicate that both OSA and nano-HAp are suitable alternatives for cleaner tanning technologies and more sustainable leather.

“Non-Locality is most naturally incorporated into a theory in which there is a special frame of reference. One possible candidate for this special frame of reference is the one in which the Cosmic Microwave Background (CMB) is isotropic. However, other than the fact that a realistic interpretation of quantum mechanics requires a preferred frame and the CMB provides us with one, there is no readily apparent reason why the two should be linked” (L. Hardy). Starting from this remark we first argue that, given the present view of the vacuum, the basic tenets of Quantum Field Theory cannot guarantee that Einstein Special Relativity, with no preferred frame, is the physically realized version of relativity. Then, to try to understand the nature of the hypothetical preferred Σ−frame, we consider the so called ether-drift experiments, those precise optical measurements that try to detect in laboratory a small angular dependence of the two-way velocity of light and then to correlate this angular dependence with the direct CMB observations with satellites in space. By considering all experiments performed so far, from Michelson-Morley to the present experiments with optical resonators, and analyzing the small observed residuals in a modern theoretical framework, the long sought Σ− frame tight to the CMB naturally emerges. Finally, if quantum non-locality reflects some effect propagating at vastly superluminal speed vQI→∞, its ultimate origin could be hidden somewhere in the infinite speed cs→∞ of vacuum density fluctuations.

The evolution of integrable classical systems leads to conserved quantities and vanishing Poisson brackets. In contrast, such invariants do not exist in the dynamics of non-integrable systems, which include (but are not limited to) deterministic models with long-term chaotic behavior. The object of this review is to briefly survey the mathematical background of nonintegrability and its role in the physics unfolding well-above the Standard Model (SM) scale.

Fractional-time Schrödinger equation (FTSE) describes the evolution of quantum processes endowed with memory effects. FTSE manifestly breaks all consistency requirements of quantum field theory (unitarity, locality and compliance with the clustering theorem), unless the order of fractional differentiation and integration ( ) falls close to the standard index . Working in the context of the minimal fractal manifold (where , ), we confirm here that FTSE approximates the attributes of gravitational metric and provides an unforeseen generation mechanism for massive fields.

In this article the reduction of a $n$-dimensional space to a $k$-dimensional space is considered as a reduction of $N^n$ states to $N^k$ states, where $N$ stands for the number of single-particle states per unit of spatial length. It turns out, this space reduction could be understood as another definition of inflation. It is shown that the introduction of the non-associativity of the algebra of physical fields in a homogeneous space leads to a nonlinear equation, the solutions of which can be considered as two-stage inflation. Using the example of reduction $T\times R^7$ to $T\times R^3$, it is shown that there is a continuous cross-linking of the Friedmann and inflationary stages of algebraic inflation at times $10^{-15}$ with the number of baryons $10^{80}$ in the Universe. In this paper, we construct a new gravitational constant based on a nonassociative octonion algebra.

In this article the reduction of a $n$-dimensional space to a $k$-dimensional space is considered as a reduction of $N^n$ states to $N^k$ states, where $N$ stands for the number of single-particle states per unit of spatial length. It turns out, this space reduction could be understood as another definition of inflation. It is shown that the introduction of the non-associativity of the algebra of physical fields in a homogeneous space leads to a nonlinear equation, the solutions of which can be considered as two-stage inflation. Using the example of reduction $T\times R^7$ to $T\times R^3$, it is shown that there is a continuous cross-linking of the Friedmann and inflationary stages of algebraic inflation at times $10^{-15}$ with the number of baryons $10^{80}$ in the Universe. In this paper, we construct a new gravitational constant based on a nonassociative octonion algebra.

Background: Evaluation of nutrition programs is essential to guarantee the effectiveness of community-based management of acute malnutrition (CMAM). Methods: The Rainbow Project Supplementary Feeding Programs (SFPs) in Zambia were evaluated between years 2015-17, following implementation of new recommendations based on previous evaluations (years 2012-14). Outcomes of the program were compared with International Standards and with those of 2012-14. Cox proportional risk regression analysis was performed to identify predictors of mortality and defaulting. Results: Data for 900 under age 5 years malnourished children (48.8% male; mean age 19.7months ±9.9) were analyzed. Rainbow 2015-17 program outcomes met International Standards, for general malnutrition or stratified moderate acute malnutrition (MAM) and severe acute malnutrition (SAM). When comparing with 2012-14 outcomes, better performance was noted: mortality rates were reduced by half (5.6% vs 3.1%, p = 0.01; for SAM: 12.4% vs 6.7%, p = 0.006), with significant improvement in average weight gain and mean length of stay (p<0.001), and increased awareness of HIV status (+30%; p < 0.001). HIV infection (5.5; 1.9–15.9), WAZ < −3 at baseline (4.6; 1.3–16.1) and kwashiorkor (3.5; 1.2–9.5) remained the major predictors of mortality. Conclusion: The effectiveness of the Rainbow SFPs for child malnutrition treatment and prevention in Zambia has significantly improved after evaluation and implementation activities, with impressive outcomes which resulted in a 50% reduction in mortality.

The integration of Wireless Power Transfer (WPT) technologies with Artificial Intelligence (AI) is poised to revolutionize multiple industries, including consumer electronics and industrial applications. This study delves into the latest advancements in WPT, with a focus on AI-enhanced efficiency, range, and reliability. AI-driven algorithms optimize power transfer, improve device alignment, and predict maintenance needs, leading to smarter and more sustainable power solutions. Machine learning and computer vision are employed to achieve precise alignment, while predictive maintenance minimizes downtime and costs. Additionally, AI-powered power management systems adapt to varying demands, optimizing energy usage. This research highlights the transformative potential of AI in enhancing WPT technologies, with significant implications for next-generation applications. The findings emphasize the importance of ongoing research in this interdisciplinary field to address existing challenges and unlock new opportunities for innovation.

Fever control is essential in patients with severe traumatic brain injury (TBI). The efficacy of therapeutic hypothermia (TH) in severe TBI has been investigated over the last few decades; however, in contrast to experimental studies showing benefits, no evidence of efficacy has been demonstrated in clinical practice. In this review, the mechanisms and history of hypothermia were briefly outlined, while the results of major randomized controlled trials (RCTs) and meta-analyses investigating TH for adult TBI are introduced and discussed. The retrieved meta-analyses showed conflicting results, with a limited number of studies indicating benefits of TH. Some studies have shown benefits of long-term TH compared with short-term TH. Although TH is effective at lowering elevated intracranial pressure (ICP), reduced ICP does not lead to favorable outcomes. Low-quality RCTs overestimated the benefits of TH, while high-quality RCTs showed no difference or worse outcomes with TH. RCTs assessing standardized TH quality demonstrated the benefits of TH. As TBI has heterogeneous and complicated pathologies, applying a uniform treatment may not be ideal. A meta-analysis of young patients who underwent early cooling and hematoma removal showed better TH results. TH should not be abandoned, and its optimal should be advocated on an individual basis.

Source water quality is a key determinant of drinking water quality. The recast European Union 2020/2184 drinking water directive (DWD) introduced the obligation for comprehensive risk assessment in drinking water supplies, including the water source and incorporated new elements of natural origin in the list of parameters to be monitored. The current study is the first comprehensive assessment of 15 natural elements (B, Ba, Be, Ca, Co, K, Li, Mg, Mo, Na, Se, Sr, Ti, U and V) in 1155 (82%) Hungarian drinking water sources, including surface water, bank filtered and groundwater sources. Parameters posing a risk to health (Se, V and U) were typically below the lower limit of quantification (LOQ), but higher concentrations (max. 7.0, 17 and 41 µg/L, respectively) may occur in confined locations, the latter exceeding the DWD parametric value in one water supply. Li in a small geographical area, Mg and Ca in the majority of the water supplies reached the concentration range assumed to be protective to health. Water sources were grouped in 6 clusters based on their element distribution, some of them also showing clear geographical patterns. Water types were not differentiated, with the exception of karstic waters (dominated by Ca and Mg). None of the investigated parameters are expected to be a source of public health concern.

Background:Caregiving for individuals with neurological disease involves providing physical, emotional, and social support, which can be a challenging and stressful experience. This study aims to compare the caregivers' burden, including the impact on mental and physical health, social support, and quality of life, in different neurodegenerative disorders. Methods:Fifty-five primary caregivers (F=41;mean age=53.07±12.29) of patients with Parkinson's Disease (PD=26), Multiple System Atrophy (MSA=16), and Amyotrophic Lateral Sclerosis (ALS=13), took part in the study. Standardized screening scales for the quality of life (EQ-5D/EQ-VAS and PQoL), levels of the caregiving burden (CBI and FSQ), and the assessment of the anxiety-depressive axis (HADS) were administered. Results: The mean CBI score was higher for caregivers of MSA patients (28.81±21.90) and ALS (25.15±16.23) than for caregivers of PD patients (16.08±10.34; p=0.036). Critical burden (cut-off>36) was present in the caregivers of MSA (31.3%), ALS (23.1%), and PD (19.2%) patients. Caregivers of patients with ALS had a worse perception of quality of life (EQ-5D total score) than caregivers of patients with MSA and PD (p

Protection suit is vital for fireman’ safety. Traditional protection suit just physically protects fireman from empyrosis, but can not locate the body injury position from the impact debris. Herein, we present a wearable impact debris positioning system for fireman protection suit alarming based on accelerometer array. The wearable piezoelectric accelerometers with distribute regularly on the suit to detect the vibration on different body parts, which is conducive to positioning injured body parts. In addition, the injured parts can be displayed on the dummy body model on the upper computer with a higher localization accuracy of 4 cm. The positioning alarm system has a rapid response time of 0.11ms attributing to smart signal processing method. This work provides a reliable and smart method for locating and assessing the body injury position from the impact debris, which is significant for fire disaster commander to rescue injured fireman in time.

The increased prevalence of obesity worldwide has been implicated for the alarming rise of the incidence of gestational diabetes and preeclampsia as well, both considered as threatening conditions for both mother and fetus. We studied gene polymorphisms of the proinflammatory cytokine Interleukin 6 (IL-6) and the gene expression levels of VEGF and VEGF-receptor all known to be involved in pregnancy complications aiming to identify possible predisposing risk factors in pregnancies with obesity. G allele of IL-6 was found to correspond with an increased risk for gestational diabetes and preeclampsia occurrence. Furthermore, in obese pregnant mothers with either gestational diabetes or pre-existing type 2 diabetes and to those developed preeclampsia it was confirmed that gene expression levels of VEGF were reduced while they were increased for VEGF receptor. We conclude that the genetic profile of the obese pregnant woman shares a common background with that of a pre-existing type 2 diabetes mellitus and therefore predisposes to complications in pregnancy.

The systematic sampling is used as a method to get the quantitative results from the tissues and the radiological images. Systematic sampling on real line (R) is a very attractive method within which the biomedical imaging is consulted by the practitioners. For the systematic sampling on R, the measurement function (MF) is occurred by slicing the three-dimensional object equidistant systematically. The currently used covariogram model in variance approximation proposed by [28,29] is tested for the different measurement functions in a class to see the performance on the variance estimation of systematically sampled R. This study is an extension of [17], and an exact calculation method is proposed to calculate the constant λ(q,N) of confidence interval in the systematic sampling. The exact value of constant λ(q,N) is examined for the different measurement functions as well. As a result, it is observed from the simulation that the proposed MF should be used to check the performances of the variance approximation and the constant λ(q,N). Synthetic data can support the results of real data.

Cholinesterase (ChE) and secretase (BACE) inhibitors, and fibril- and β-amyloid-suppressing medicines are used to treat Alzheimer's disease (AD) symptomatically. The prevalence and complex nature of AD have increased the urgent need for multi-targeted directed ligands (MTDLs). This is because MTDLs can prevent potential drug-drug interactions during poly-therapy and have a better therapeutic profile than single targeted agents. Using piperazine linker or spacer and two primary scaffolds, benzofuran and 8-hydroxyquinoline, a unique class of multi-targeted medicines was recently reported by our group. These compounds showed re-markable effectiveness in inhibiting Aβ1-42 aggregation and acting as iron chelators.The results prompted us to synthesize an additional series of compounds as multimodal anti-AD agents and investigate its inhibitor activities to ChE (AChE/BChE) and BACE1 enzymes. The resulting in-hibitory effects suggested that the compounds under study might be used to improve cognitive function. The docking analysis' findings revealed that the compounds bind to AChE and BChE by forming H-bond interactions with amino acid residues at binding sites and µ-stacking inter-actions with aromatic residues, whereas the binding to BACE1 only revealed H-bond interac-tions with amino acid residues at binding sites.

A large number of bridges are designed and built without considering seismic actions and, differently from buildings, there are currently no comprehensive guidelines to evaluate existing bridges without performing, as in the well known incremental dynamic analysis (IDA), complex non linear dynamic analyses (RHA). Bridges are structurally very different from building but, at the same time, are sensitive to higher modes as well as many multi-storey buildings that inspired innovative pushover procedures such as the well known modal pushover analysis (MPA). In the present study the incremental modal pushover analysis (IMPA), a pushover based approach already proposed and applied on buildings by the same authors, is revised and proposed for bridges (IMPAβ). IMPAβ accounts for the effects of higher modes in order to accurately estimate the seismic response of bridges; the effect of higher modes is considered by introducing a suitable number of modes to ensure the participation of a predefined total effective modal mass. The efficiency of the proposed method is demonstrated by conducting a study on two bridges, one regular and one irregular, and the IDA analysis is employed as reference solution. Numerical results indicate good accuracy of the proposed method in assessing the seismic response and a very good accuracy if compared to other available pushover procedures available in the literature.

The development of non-destructive testing (NDT) methods for infrastructure facilities and residential buildings that may affect human life is urgent to prevent collapse due to aging or damage in the event of earthquakes and other events. In this study, we developed a single-input and multiple-output (SIMO) synthetic aperture radar (SAR) imaging system using a high-sensitivity millimeter-wave (MM-wave) array antenna module with high directivity and absolute gains of 13.5 dB and 14.5 dB for the transmit and receive antennas, respectively. After various performance evaluations, we successfully demonstrated the usefulness of this system in NDT. Specifically, we observed cracks hidden by fiberglass tape and black acrylic paint during measurements on concrete materials. In addition, we demonstrated the transmission performance of the MM-wave against a thin concrete plate and obtained the attenuation distance Λ_exp=6.0 mm. Furthermore, in the experiment using composite materials consisting of ceramic tiles and a refractory board bonded together, and another experiment using composite plywood which is used in ordinary residential construction materials in Japan, we were able to observe defects in the internal structure that are invisible to the human eye through a perspective view.

Long-haul truck drivers are responsible for transporting goods valued at millions of dollars of the world economy and may have their health affected by living and working conditions. This study analyzed and synthesized the scientific findings about risk factors for the development of chronic non-communicable diseases in long-haul truck drivers. An integrative literature review was conducted. We identified 23 studies that met the inclusion criteria and evaluated the health of 7,363 drivers. The biological risks identified were age, gender, race/ethnicity, genetics, comorbidities, and were considered non-modifiable for chronic diseases. The behavioral risks, considered modifiable, were sedentary lifestyle, smoking, alcohol consumption, overweight, diet, stress, anxiety, unfavorable socioeconomic conditions. Environmental risks involved working conditions such as the number of working hours per day, week and month; time away from home, risk of musculoskeletal injury, and opportunities for rest, hours of sleep and access to health services. The results were presented in two categories: 1) biological, behavioral and environmental risks, and 2) general recommendations to promote physical, cognitive and emotional health. Macro-structural changes are needed to reorganize work and rest, improve access to health services to control risk factors, and to support behavioral and environmental changes to reduce chronic non-communicable diseases and deaths.

Lung cancer is one of the leading causes of cancer-related mortality globally. Pulmonary nodules are one of the risk factors and their discovery rate has been increasing. Based on the nodule size and growth rate, their malignancy propensity is determined; however, it is very challenging to distinguish between benign and cancerous nodules. Many tumour-associated antigens (TAA) have been studied as blood biomarkers for lung cancer, most commonly the Cytokeratin 19 fragment (CYFRA 21-1), squamous cell carcinoma antigen (SCC Ag), carbohydrate antigen (CA19-9) and carcinoembryonic antigen (CEA). Due to their low sensitivity, TAAs are not recommended as tools for the early detection of lung cancer. However, cancer testis antigens (CTAs) are highly specific for carcinomas but their expression is more commonly associated with advanced stages of cancer and poor prognosis. Despite the fact that TAAs may provide useful insights for the diagnosis and prognosis of early lung cancer, their potential to do so has yet to be demonstrated.

Mycobacteria can be one of the main contaminants of biological products, and their presence can have serious consequences on patients’ health. Thus, specific testing is necessitated by regulations such as the European Pharmacopoeia. The current pharmacopeial reference i.e., microbial culture method cannot ensure an exhaustive detection of mycobacteria due to their growth characteristics. Additionally, the method is time-consuming and requires a continuous supply of culture media, which could be further challenging. Thus, to overcome these challenges, pharmaceutical industries need to consider alternative non-microbiological techniques to detect these fastidious, slow-growing contaminating agents. This review provides an overview of alternative methods, which could be applied within a quality control environment of biological products, and underlines advantages and limitations of these methods. Nucleic acid amplification techniques or direct measurement of mycobacteria stands out as the most suitable alternatives for mycobacterial testing in biological products.

The human-centric approach is a leading trend for future production processes, and collaborative roboticists are key to its realization. This article addresses the challenge of designing a new cus-tom-made non-conventional machine or robot involving toolpath control (interpolated axes) with collaborative functionalities but by using “general-purpose standard" safety and motion control technologies. This is done on a non-conventional Cable-Driven Parallel Robot (CDPR). Safety is assured by safe commands to individual axes, known as Safe Motion Monitoring Functionalities, which limits the axes speed in the event of human intrusion. At the same time, the robot's Motion Controller applies an override to the toolpath speed to accommodate the robot's path speed to the axis’s limitations. The implementation of a new Pre-Warning Zone, prevent unnecessary stops due to the approach of the human operator. The article also details a real experiment that validates the effectiveness of the proposed strategy.

Autologous micrografting technology (AMT®) involves the use of autologous micrografts to stimulate/enhance the repair of damaged tissue. This study assessed the efficacy and safety of the AMT® procedure in patients with early stages of knee osteoarthritis. Briefly, the AMT® procedure involved extraction of auricular cartilage, disaggregation using the Rigeneracons® SRT in 4.0 mL of saline solution and injection of the disaggregated micrografts into the external femorotibial compartment area of the affected knee. Ten patients (4 men, 6 women; age range: 37─84 years) were included in the study. In all patients, there was a steady improvement in knee instability, pain, swelling, mechanical locking, stair climbing and squatting at 1- and 6-months post-procedure. Improvement in mobility was observed as early as 3 weeks post-procedure in 2 patients. Significant improvements were seen in mean scores of all five subscales of Knee Injury and Osteoarthritis Outcome Score (KOOS [KOOS symptoms, KOOS pain, KOOS ADL, KOOS sport and recreation, and KOOS quality-of-life]) between pre-procedure and 1- and 6-months post-procedure (all p≤0.05). Autologous auricular cartilage micrografts obtained by AMT® procedure (using Rigenera® technology) is an effective and safe protocol in the treatment of early-stage knee osteoarthritis. These encouraging findings need to be validated in a larger patient population.

Diabetes mellitus is a widespread chronic metabolic disorder demanding regular blood glucose level surveillance (BGLs). Current invasive techniques, such as finger-prick tests, often result in discomfort for patients, leading to infrequent monitoring and potential health complications. The primary objective of this study was to design a novel, portable, non-invasive system for diabetes detection using breath samples, named as DiabeticSense, an affordable digital health device for early detection, encouraging immediate intervention. The device employed MOSFET-based electrochemical sensors to assess volatile organic compounds in breath samples, whose concentrations differ between diabetic and non-diabetic individuals. The system merged body vital signs with sensor voltages obtained by processing breath sample data to predict diabetic conditions. Our research used readings from 100 patients at a nationally recognised hospital to form the dataset. Data was then processed 10 using a Gradient Boosting Classifier model, and performance was cross-validated. The proposed system attained a promising accuracy of 86.6%, marking an improvement of 20.72% over an existing regression technique. The developed device introduces a non-invasive, cost-effective, and user-friendly solution for preliminary diabetes detection. It has the potential to increase patient adherence to regular monitoring.

In real-life scenario, there are many mathematical tools to handle the incomplete and imprecise data. One of them is the fuzzy approach. This article aims to contribute to the literature of fuzzy multi-objective dynamic programming issues involving the fuzzy objective functions. The piecewise quadratic fuzzy numbers characterize these fuzzy parameters. Some basic notions in the problem under the α-pareto optimal solution concept is redefined and analyzed to study the stability of the problem. Furthermore, a technique, named as enhancing decomposition approach, is presented for achieving a subset for the parametric space that contains the sameα-pareto optimal solution. For a better understanding and comprehension of the suggested concept, a numerical example is provided.

With a large number of annotated non-coding RNAs (ncRNAs), repetitive sequences are found to constitute functional components (termed as repetitive elements) in ncRNAs that perform specific biological functions. Bioinformatics analysis is a powerful tool for improving our understanding of the role of repetitive elements in ncRNAs. This chapter summarizes recent findings that reveal the role of repetitive elements in ncRNAs. Furthermore, relevant bioinformatics approaches are systematically reviewed, which promises to provide valuable resources for studying the functional impact of repetitive elements on ncRNAs.

In this paper, we introduce a non-invasive approach for monitoring bridge infrastructure with ground-based interferometric radar. This approach is called the mirror mode, since it utilises the flat surface of the bridge underside as a mirror to reflect the signal to a corner reflector on the ground placed opposite of the radar sensor. For proving the feasibility of this approach, a measurement campaign has been carried out at an exemplary bridge in Karlsruhe (Germany) including a radar sensor in mirror mode, a second radar sensor in the default mode and a laser profile scanner. We investigate the potential of this approach to monitor the bridge displacement in vertical direction and compare the results with the two other sensors. The derived results reveal the potential for monitoring bridge infrastructure. Finally, we propose further research aspects of this approach to analyse its capabilities and limitation in the context of non-invasive infrastructure monitoring.

The chicken embryo is a widely used experimental animal-model in many studies such as developmental biology and to study the physiological responses and adaptation to altered environments as well as for cancer and neurobiology research. Embryonic heart rate is an important physiological variable useful as an index reflecting the embryo's natural activity and is considered one of the most difficult parameters to measure. An acceptable measurement technique of embryonic heart rate should provide a reliable cardiac signal quality while maintaining adequate gas exchange through the eggshell along the incubation and embryonic developmental period. In this paper, we presented a detailed design and methodology for a non-invasive PPG-based prototype (Egg-PPG) for real-time and continuous monitoring of embryonic heart rate during incubation. An automatic embryonic cardiac wave detection algorithm, based on normalised spectral entropy, is described. The developed algorithm successfully estimated the embryonic heart rate with 98.7% accuracy. We believe that the developed overall system presented in this paper is showing a promising solution for non-invasion, real-time monitoring of embryonic cardiac signal, which can be used in both experimental studies (e.g., developmental embryology and cardiovascular research) and in industrial incubation applications.

The motivation of this work is to investigate experimentally the influence of non-thermal plasma (NTP) application on the reaction kinetics of atmospheric pressure steam gasification of charcoal using a thermostatically controlled drop tube reactor. A gliding-arc generator provides about 1 kW electrical power NTP. For comparison thermal gasification is investigated under comparable flow and specific energy input conditions providing additional heat to the steam. Optical temperature measurement 20 cm flow down of the NTP zone is utilized to characterize the specific enthalpy of the reactive flow. The composition of produced syngas is measured by a gas analyzer and used for the calculation of gas flow rates. The results show a NTP-enhancement on the production of individual syngas components (H2, CO, CH4), especially on hydrogen production by around 39%. The syngas-based carbon conversion and hydrogen release are calculated from the carbon and hydrogen balance between the correspondent content in syngas and in the feedstock. The NTP promoted the carbon conversion and hydrogen release by 25% and 31%, respectively. The first-order reaction kinetics are determined by data-fitting in an Arrhenius diagram. The plasma enhanced the reaction rate coefficients by 27%. Based on experimental results and other literature, possible plasma-induced reactions are proposed.

The Dutch Konik is valued from a genetic conservation perspective and also for its role in preservation of natural landscapes. The primary management objective for the captive breeding of this primitive horse is to maintain its genetic purity, whilst also maintaining the nature reserves on which they graze. Breeding selection has traditionally been based on phenotypic characteristics consistent with the breed description, and the selection of animals for removal from the breeding program is problematic at times due to high uniformity within the breed. With the objective of identifying an additional non-invasive selection criterion with potential uniqueness to the Dutch Konik, this study investigates the anatomic parameters of the distal equine limb, with a specific focus on the relative lengths of the individual splint bones. Post-mortem dissections performed on distal limbs of Dutch Konik (n = 47) and modern domesticated horses (n = 120) revealed significant differences in relation to the length and symmetry of the 2nd and 4th Metacarpals and Metatarsals. Distal limb characteristics with apparent uniqueness to the Dutch Konik are described which could be an important tool in the selection and preservation of the breed.

Seeing atomic configuration of single organic nanoparticles at sub-Å spatial resolution by transmission electron microscopy has been so far prevented by the high sensitivity of soft matter to radiation damage. The difficulty is related to the need to irradiate the particle with a total dose of few electrons/Å2, not compatible with the electron beam density necessary to search the low-contrast nanoparticle, to control its drift, to finely adjust the electro-optical conditions and particle orientation, and to finally acquire an effective atomic resolution image. On the other hand, the capability to study individual pristine nanoparticles, such as proteins, active pharmaceutical ingredients, and polymers, with peculiar sensitivity to the variation of the local structure, defects, and strain, would provide advancements in many fields, including materials science, medicine, biology, and pharmacology. Here we report direct sub-ångström resolution imaging at room temperature of pristine unstained crystalline polymer-based nanoparticles. This result is obtained by combining low-dose in-line electron holography and phase-contrast imaging on state-of-the-art equipment, providing an effective tool for the quantitative sub-angstrom imaging of soft matter.

The research showsThis paperstudy presents a theoretical model of sustainable tourism in protected areas based on the experiences obtained in fromthrough field work carried out in the Machalilla national park. The units of analysis that compose it and their theoretical–-methodological foundation, and as well as the indications for their practical implementation in the face of the changes imposed by future tourism are exposed. Using the deductive method, the an analysis of the problem and the general theories linked to sustainable tourism in protected areas was carried out., the This involved establishingment of the premises and the developingment of the objectives to reach conclusions on the topic studied. A qualitative investigation is presented that allowed for the integration of contributions from the analyszes carried out for the treatment and processing of information. Among the results, the systematization of theoretical models linked to tourism in protected areas and, from a practical point of view, the application of a sustainable tourism model was were achieved. The results show the relevance of the proposed theoretical model that is proposed as a contribution to the scientific development of tourism. This model highlights, the systemic nature of its components from a new perspective of analysis, which considerings the need for changes as a development factor.

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.

Neurological disorders are the leading cause of cognitive and physical disability worldwide, affecting 15% of the global population. Due to the demographics of aging, the prevalence of neurological disorders, including neurodegenerative diseases, will double over the next two decades. Unfortunately, while available therapies provide symptomatic relief for cognitive and motor impairment, there is an urgent unmet need to develop disease-modifying therapies that slow the rate of pathological progression. In that context, biomarkers could identify at-risk and prodromal patients, monitor disease progression, track response to therapy, and parse causality of molecular events to identify novel targets for further clinical investigation. Thus, identifying biomarkers that discriminate between diseases and reflect specific stages of pathology would catalyze the discovery and development of therapeutic targets. This review will describe the prevalence, known mechanisms, ongoing or recently concluded therapeutic clinical trials, and biomarkers of three of the most prevalent neurodegenerative diseases, including Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson’s disease (PD).

The main purpose of our research is the evaluation of the efficacity of solvent polarity on phenolic composition, as well as the antibacterial, and antioxidant activities of extract of Moroccan Mentha aquatica L., leaves. To attempt these objectives, the HPLC-DAD was used to identify the biomolecules. The total amount of phenolic and flavonoid content was determined using the Folin-Ciocalteu and aluminum trichloride processes as well as the DPPH, RP, and TAC tests were used to evaluate the antioxidant capabilities. In addition, by employing both in vitro and in silico analysis through the microdilution method, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extracts were assessed against multidrug-resistant bacteria. Furthermore, the High-Performance Liquid Chromatography (HPLC) analysis indicated that all extracts of M. aquatica were abundant in noteworthy phytochemical compounds, especially gallic acid, vanillic acid, chlorobenzoic acid, quercetin, and kaempferol. Furthermore, the results indicated that the total phenolic content was higher in hydroethanolic extract (62.19 ± 1.19 mg GAE/g DW) in contrast to the acetonic and aqueous extracts (22.22 ± 0.64, and 22.44± 0.57 mg GAE/g DW) respectively. Similarly, the aqueous ethanol extract contained the greatest flavonoid concentration, with values of 29.15± 0.09 mg QE/g DW when compared with the other extracts. The seam extract poses excellent antioxidant power with an IC50 of 0.06 ± 0.00 mg/mL for the DPPH test, and lower RP with EC50 of 80± 0.00 µg/ml when compared with acetonic and aqueous extract (370± 0.00 and 460± 0.01 µg/mL) respectively. Moreover, the hydroethanolic extract has a high level of TAC 75.09± 2.00 mg EAA/g DW, followed by aqueous extract carrying a value of 28.53 ± 1.36 mg EAA/g DW. The antibacterial capacity is ranged between 0.78 ± 0.05 mg/mL and 12.60 ± 0.00 mg/L. The results of the in-silico study demonstrated that quercetin, vanillic acid, and naringenin components contribute to the antioxidant capability. While gallic acid, kaempferol, and quercetin components are attributed to the antibacterial capacity.

Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits - grain protein content (GPC) and thousand kernel weight (TKW) - across 179 Bulgarian contemporary and historic varieties, and landraces in three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, genotypic data from the 25K Infinium iSelect array, and a Bonferroni-adjusted p-value. As a result, 776 significant quantitative trait nucleotides (QTNs) organized into quantitative trait loci were discovered, including 25 loci associated with GPC, and 35 loci linked to TKW. Additionally, 14 environmentally stable QTNs were identified for TKW. Certain loci on chromosomes 2A, 3A, and 6B favorably in-fluenced GPC, while the locus on chromosome 6D impacted TKW positively. These loci may reflect novel associations to the two traits. Annotations for proteins involved in the remobilization of carbon and nitrogen from vegetative tissues to developing grain during senescence, as well as in the following buildup of resources required for seed germination, have been found for selected pu-tative candidate genes. These include genes coding for 11S globulin seed storage protein, glutamine synthetase, metalloendopeptidase, components of the ubiquitin/proteasome system, sucrose transporter, alpha-amylase, NAC and bZIP transcription factors. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content.

The approach based on molecular modeling was developed to study dNTP derivatives characterized by new polymerase-specific properties. For this purpose, the relative efficiency of PCR amplification with modified dUTPs was studied using Taq, Tth, Pfu, Vent, Deep Vent, Vent (exo-), and Deep Vent (exo-) DNA polymerases. The efficiency of PCR amplification with modified dUTPs was compared with the results of molecular modeling using the known 3D structures of KlenTaq polymerase–DNA–dNTP complexes. The dUTPs were C5-modified with bulky functional groups (the Cy5 dye analogs) or lighter aromatic groups. Comparing the experimental data and the results of molecular modeling revealed the decrease of PCR efficiency in the presence of modified dUTPs with an increase in the number of non-covalent bonds between the substituents and the DNA polymerase (about 15% decrease per one extra non-covalent bond). Generalization of the revealed patterns to all the studied polymerases of the A and B families is discussed herein. The number of non-covalent bonds between the substituents and polymerase amino acid residues is proposed to be a potentially variable parameter for regulating enzyme activity.

Under suitable continuity and uniqueness conditions, solutions of an α order Caputo fractional boundary value problem are differentiated with respect to boundary values and boundary points. This extends well-known results for nth order boundary value problems. The approach used is a standard technique and makes heavy use of recent results for differentiation of solutions of Caputo fractional intial value problems with respect to initial conditions and continuous dependence for Caputo fractional boundary value problems.

Highly transparent, conductive nanosheets are extremely attractive for advanced optoelectronic applications. Previously, we have demonstrated that transparent, conductive Au nanosheets can be prepared by UV irradiation of Au nanoparticle (AuNP) monolayers spread on water, which serves as the subphase. In this study, we show that this UV irradiation technique can easily be extended as a nanosheet modification method by using subphases containing metal ions. That is, aqueous solutions containing Au and Ag ions are effective in modifying Au nanosheets. HAuCl4 solutions increased Au nanosheet thickness, which improved conductivity, but reduced transparency. On the other hand, use of aqueous AgNO3 and CH3COOAg solutions yielded Au-Ag hybrid nanosheets; however, their morphologies depended on the electrolytes used. Homogeneous Au-Ag nanosheets from AgNO3 and AuNPs covered with an Ag nanosheet from CH3COOAg were also produced. Further, these Au-Ag hybrid nanosheets had high conductivity without reduced transparency. Therefore, this UV irradiation method, modified by adding metal ions is quite effective at improving and diversifying properties of Au nanosheets.

The mechanism of vapor-gas deposition of vinyltrimethoxysilane (VS) and ethylene glycol (EG) from azeotropic solutions is investigated, which allows to reduce the evaporation temperature of the components of working mixtures. The need for such studies is associated with the development of a new direction in the technology of vapor-gas deposition of polymer coatings. Methods have been developed for monitoring the chemical composition of working solutions in evaporators using optical spectroscopy, which allow calculating the partial pressures of vapor phase components. Based on these studies, compositions of working solutions are proposed that allow to equalize the partial pressures of the components of working mixtures with a large difference in boiling point. A new method of vapor-gas deposition of non-volatile powder inhibitors on metals is proposed. Chemical compositions of siloxane coatings were determined using XPS and mechanisms of interaction of VS with polymerization promoters ethylene glycol and 1-hydroxy ethylidene-1,1-diphosphonic acid (HEDP) were proposed.

For a linear ordinary differential equation (ODE in short) of the third order, results are presented that supplement the theory of conjugate points and extremal solutions by W. Leighton, Z. Nehari, M. Hanan. It is especially noted the sensitivity of solutions to the initial data, which makes their numerical study difficult. Similar results were obtained for the third-order nonlinear equations of the Emden-Fowler type.

The exact similarity solutions of two dimensional laminar boundary layer were obtained by Blasius in 1908, however, for two dimensional turbulent boundary layers, no similarity solutions (special exact solutions) have ever been found. In the light of Blasius' pioneer works, we extend Blasius similarity transformation to the two dimensional turbulent boundary layers, and successfully transform the two dimensional turbulent boundary layers partial differential equations into a single ordinary differential equation. By author's Maple code, we numerically solve the ordinary differential equation and produce some useful quantities.

This article has two objectives. Firstly, we will use the vector variational-like inequalities problems to achieve local approximate (weakly) efficient solutions of Vector Optimization Problem within the novel field of the Hadamard manifolds. Previously, we will introduce the concepts of generalized approximate geodesic convex functions and illustrate them with examples. We will see the minimum requirements under which critical points, solutions of Stampacchia and Minty weak variational-like inequalities and local approximate weakly efficient solutions can be identified, extending previous results from the literature for linear Euclidean spaces. Secondly, we will show an economical application, using again solutions of the variational problems to identify with Stackelberg equilibrium points on Hadamard manifolds and under geodesic convexity assumptions.

Ecosystems are not merely vulnerable to climate change but, if sustainably restored and protected, are a major source of human resilience. Not only is the evidence-base for the importance of these “Nature-based Solutions” (NbS) growing rapidly, but NbS are featuring with increasing prominence in global climate change policy. Here we report on the prominence of NbS in the 141 adaptation components of the 167 Nationally Determined Contributions (NDCs) that were submitted to UNFCCC by all signatories of the Paris Agreement. In total, 103 nations include NbS in the adaptation component of their NDC, 76 nations include them in both their adaptation and mitigation component, and an additional 27 include them as part of their mitigation plans only. In other words, 130 nations—or 66% of all signatories to the Paris Agreement—have articulated intentions of working with ecosystems, in one form or another, to address the causes and consequences of climate change. However, commitments rarely translate into robust science-based targets. As climate pledges are revised in 2020, we urge the ecosystem science community to work closely with policymakers to identify meaningful adaptation targets that benefit both people and the ecosystems on which they depend.

In this paper Brinkman type fluid over an infinite plate between side walls is being investigated. The flow is generated by oscillating shear stress of the bottom plate and the solutions are obtained by using Fourier integral transformation. The obtained results are presented in steady and transient states for both sin and cos shear stresses. The general solutions are reduced to some special cases corresponding, namely to the Brinkman type fluid over an infinite plate and flow of a Newtonian viscous fluid. Graphical illustrations are carried out to have in depth analysis of the involved physical parameters

Deuterium is a heavy nonradioactive isotope of hydrogen, having a neutron as well as a proton, making it twice as heavy. It is a natural element, present at 156 parts per million in seawater. The ATPase pumps in the mitochondria utilize proton motive force to drive ATP synthesis, and deuterons damage the pumps, producing a stutter that can cause reactive oxygen release and inefficiencies in ATP synthesis. Cellular metabolism incorporates several novel mechanisms to assure low deuterium content in the mitochondria and other organelles. Nicotinamide adenine dinucleotide (NAD) is a major carrier of deuterium depleted (deupleted) protons to supply the mitochondria. Many enzymes, especially flavoproteins, are able to use proton tunneling to fractionate out deuterium. In this paper, we argue that the amino acid proline is able to trap and sequester deuterium, and that peptidyl prolyl isomerases (PPIases) play a central role in facilitating deuterium trapping in proline-rich proteins, most notably collagen. The endothelial glycocalyx also sequesters deuterium in gelled water lining the blood vessels, creating a battery and promoting low deuterium in the circulation. Excess deuterium promotes cancer growth, and cancer cells release large quantities of lactate via aerobic glycolysis to help reverse deuterium overload, systemically.

In this paper, we explore the hypothesis that topological defects formed in the quark-gluon plasma (QGP) of the early universe, specifically flux tubes and domain walls, could serve as stable dark matter candidates. Theoretical analysis of the QCD vacuum structure reveals that these defects can form due to nontrivial topological configurations, with the Lagrangian density incorporating topological terms. We model the formation and stability of flux tubes and domain walls, estimating their energy densities and dynamics within the QGP. Flux tubes, with energy per unit length approximately given by $\mu \approx \frac{\sigma}{g_s^2}$, and domain walls, characterized by a surface energy density $\sigma_{\text{DW}} \sim \Lambda_{\text{QCD}}^3$, exhibit unique gravitational signatures. These signatures include distinct gravitational lensing patterns due to their linear and planar mass distributions, making them detectable through astrophysical surveys. Furthermore, their minimal interaction with conventional matter aligns well with observational constraints on dark matter properties. We discuss potential experimental approaches for detecting these defects, including high-energy collider experiments and detailed analysis of gravitational lensing data. Our findings suggest that topological defects in the QGP provide a compelling and novel solution to the dark matter problem, offering a new direction for both theoretical investigation and experimental verification.

. Gut microbiome reflects healthy and predicts possible disease in hosts. A holistic view of this community is needed, focused on identification species, and on the dissection of how species interact with their host and with each other, regardless of whether their presence is beneficial, inconsequential, or detrimental. Distribution of gut-associated eukaryotes within and across NHPs is likely driven by host behavior and ecology. To ascertain the existence of free-living amoebae (FLA) in the gut of wild and captive non-human primates (NHPs), 01 sample stools were collected and submitted to culture-dependent and microscopy examination and DNA sequencing. FLAs were detected in 45.4% (46/101) of fecal samples analysed and their morphological characteristics matching those of Acanthamoeba spp, Vermamoeba spp, and fan-shaped amoebae of the family Vannellidae. Sequence analysis of the PCR- products revealed that the suspected amoebae are highly homologous (99% identity and 100% query coverage) with Acanthamoeba genotype T4 and Vermamoeba vermiformis amoebae. The results showed a great diversity of FLAs in the NHP microbiome, which may pose a potential risk to the health of NHPs. To the best of our knowledge, this is the first report the presence of FLAs in NHPs naturally infected. However, it is not known whether gut-borne FLA are exploiting a viable ecological niche, or whether they are simply transient residents in the gut.

The mites that infest laying hens and broiler chickens in poultry farms have caused great inconvenience to the industry due to the difficulty of controlling or eliminating their populations within the production systems. Dermanyssus gallinae and Ornithonyssus spp. are the mites that mainly interfere with the well-being of the poultry, harming the animals’ health and damaging the production and quality of the end product, with special emphasis on Ornithonyssus sylviarum and Ornithonyssus bursa. The objective of this article is to analyze the impact of hematophagous mites that infest commercial egg and meat production systems, the consequences of this form of parasitism, and discuss the methods of control it, including chemical and non-chemical means with the use of plants, entomopathogenic fungi, diatomaceious earth-based products and synthetic silica, and new lines of study aimed at developing vaccines as a new way of effectively controlling these pests.

Long non-coding RNAs (LncRNAs) are mRNA-like molecules that do not encode for proteins and that are longer than 200 nucleotides. LncRNAs play important biological roles in normal cell physiology and organism development. Therefore, deregulation of their activities is involved in disease processes such as cancer. Lung cancer is the leading cause of cancer-related deaths due to late stage at diagnosis, distant metastasis, and high rates of therapeutic failure. LncRNAs are emerging as important molecules in lung cancer for their oncogenic or tumor suppressive functions. LncRNAs are highly stable in circulation, presenting an opportunity for use as non-invasive and early-stage cancer diagnostic tools. Here, we summarize latest works providing in vivo evidence available for LncRNAs role in cancer development, therapy-induced resistance, and their potential as biomarkers for diagnosis and prognosis, with a focus on lung cancer. Additionally, we discuss current therapeutic approaches to target LncRNAs. The evidence discussed here strongly suggests that investigation of LncRNAs in lung cancer in addition to protein-coding genes will provide a holistic view of molecular mechanisms of cancer initiation, development, and progression, and could open a new avenue for cancer treatment.

As Solar Photovoltaics in buildings reaches maturity, grid integration and economic yield are topics of greater interest. The traditional design of photovoltaic installations has considered the optimal orientation of photovoltaic modules to be that which yields the maximum annual energy production. The influence of the consumption patterns and the hourly-variable electricity prices implies that this traditional optimal design might not be the most profitable. Using a full-year dataset for a residential installation, alternative installations using canopies and modules attached to the façades are simulated. Simulating the energy balances for different annual consumptions, it is found that the canopy and façade installations offer better self-consumption of the PV produced energy, reflected in a 9% higher self-consumption degree using modules on façades and a 5% using canopies. The economic evaluation under the new electricity tariffs in Spain shows a better profit for PV self-consumption, reducing by more than 2 years the time of return on investment. The analysis of different alternatives for an industrial PV has allowed us to identify several benefits for these orientations, such as an increase in annual energy production of up to 59% over the optimal-producing orientation, that are confirmed after several months of operation.

Although cancers account for over 16% of all global deaths annually, at present, no reliable therapies exist for most types of the disease. As protein folding facilitators, heat shock proteins (Hsps) play an important role in cancer development. Not surprisingly, Hsps are among leading anticancer drug targets. Generally, Hsp70s are divided into two main subtypes: canonical Hsp70 (E. coli Hsp70/DnaK homologues) and the non-canonical (Hsp110 and Grp170) members. These two main Hsp70 groups are delineated from each other by distinct structural and functional specifications. Non-canonical Hsp70s are considered as holdase chaperones, while canonical Hsp70s are refoldases. This distinct characteristic feature is mirrored by the distinct structural features of these two groups of chaperones. Hsp110/Grp170 members are larger as they possess an extended acidic insertion in their substrate binding domains. While the role of canonical Hsp70s in cancer has received a fair share of attention, the roles of non-canonical Hsp70s in cancer development has received less attention in comparison. In the current review, we discuss the structure-function features of non-canonical Hsp70s members and how these features impact on their role in cancer development. We further mapped out their interactome and discussed the prospects of targeting these proteins in cancer therapy.

Complex blade responses such as a rotating stall or simultaneous resonances are common in modern engines and their observation can be a challenge even for state-of-the-art tip-timing systems and trained operators. This paper analyses forced vibrations of axial compressor blades, measured during the bench tests of the SO-3 turbojet. In relation to earlier studies conducted in ITWL with a small number of sensors, a multichannel tip-timing system let us observe simultaneous responses or higher-order modes. To find possible symptoms of a failure, blade responses in a healthy and unhealthy engine configuration with an inlet blocker were studied. The used analysis methods covered all-blade spectrum and the circumferential fitting of blade deflections to the harmonic oscillator model. The proposed modal solver can track the vibration frequency and adjust the engine order on the fly. That way, synchronous and asynchronous vibrations are observed and analysed together with an extended variant of least squares. The proposed approach helps to avoid common mistakes and saves a lot of work related to configuring the conventional solver.

Corporate Diagnosis is now recognized as an important tool by decision makers to predict and correct burgeoning problems that a corporation may face. Methods based on this model stem from the use of mathematics and are increasingly being applied in the analysis of production processes. The goal of this paper is to use a logistic regression to design a scoring model for non-financial corporations in industry. Based on the data obtained from the Registry of the Slovak Republic for 738 non-financial corporations, according to SK NACE 26, SK NACE 27, the proportional financial metrics, using the logistic regression method, were calculated. By applying these methods, two logistic regression models were found to reliably estimate the probability of bankruptcy for a firm.

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles has been discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we have compared the key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For the energy storage systems employing ultra capacitors, we have presented the characteristics such as cell voltage, cycle life, power density and energy density. Furthermore, we have discussed and evaluated the interconnection topologies for the existing energy storage systems. We have also discussed the hybrid battery-flywheel energy storage system as well as the mathematical modeling of the battery-ultracapacitor energy storage system. Toward the end, we have discussed energy efficient powertrain for hybrid electric vehicles.

This article briefly shows how particle’s moving at escape velocity can be described in a quantum mechanical frameworks, this is achieved by deriving quantum mechanical equations that puts escape velocity into consideration. The equations are derived from Hamiltonians and Hamiltonian operators formulated from classical kinetic and potential terms which are then quantized. Equations were also presented for specific situations of the particle at escape velocity. Situations such as free-particles at escape velocity, Self-gravitating situations of a charged or neutral particle even while free of the gravitational influence of the large massive body due to its escape velocity, leaving only the self-gravitation as the only gravitational influence on the particle which in the case of a massless, charge less particle reduces back to the equation of free-particle at escape velocity. Other very brief expositions on trajectories and more are also present in this brief article.

We investigate the shear quasinormal modes (QNMs) in the context of electron stars, focusing on the Lifshitz geometry and exploring the behavior in the small star limit. The study begins by analyzing the shear sector modes in the infrared (IR) Lifshitz limit, where the geometry approaches that of a pure Lifshitz space. We derive and solve the differential equations governing the shear modes, revealing the asymptotic behavior in terms of the Lifshitz exponent. In the special case of integer values of the exponent, we obtain analytic corrections to the solutions to extract hydrodynamical QNMs. We then explore the cases with a Lifshitz exponent equal to or greater than three, providing analytical corrections to the Lifshitz IR solutions. A special case with an exponent of two is also considered, leading to modified solutions. The study extends to finding hydrodynamical QNMs, emphasizing the role of the Lifshitz geometry. Further investigations involve the flux with real and complex frequencies, considering the off-shell Lagrangian and deriving conserved flux expressions. Our analysis focuses on the exterior of the star, modeled by the Reissner-Nordström-AdS geometry. The small star limit is examined, revealing interesting features in the behavior of fermionic excitations. In summary, we provide a detailed exploration of shear quasinormal modes in electron stars, shedding light on their behavior in Lifshitz geometry, small star limits, and the interplay between real and complex frequencies. Our findings contribute to our understanding of the dynamics of electron stars and their gravitational properties.

Ultra-short 230 fs laser pulses of 515 nm wavelength were tightly focused into 700 nm focal spots and utilised in opening ~ 400 nm nano-holes in a Cr etch mask that was tens-of-nm thick. Nano-holes ablated at slightly above the threshold of ablation irradiance became nano-disks and nano-rings at slightly lower pulse energies. Subtle sub-1 nJ pulse energy control was harnessed to pattern large surface areas with controlled nano-alloying of Si and Cr. This technique is extendable to vacuum-free large area patterning of nanolayers by alloying them at distinct locations with sub-diffraction resolution. Such metal masks with nano-hole opening can be used for formation of random patterns of nano-needles with sub-100 nm separation when applied to dry etching of Si.

Evolutionary ecology may be described as explaining ecology through evolution and vice versa, but one may also view it as an integration of the two fields, where one takes the view that ecology and evolution are inseparable, and one can only begin to understand the biology of organisms by synthesizing the two fields. An example of such a synthesis is the biology of high fecundity and the associated concept of sweepstakes reproduction, or skewed individual recruitment success. As an illustration we consider selection at linked sites under various dominance and epistasis mechanisms in a diploid population evolving according to random sweepstakes and experiencing recurrent bottlenecks. Using simulations we give a few examples of the impact of the stated elements on selection. We show that depending on the dominance mechanisms random sweepstakes can shorten the time to fixation (conditional on fixation) of the fit type at all sites. Bottlenecks tend to increase the fixation time, with random sweepstakes counteracting the effects of bottlenecks on the fixation time. Understanding the effect of random sweepstakes, recurrent bottlenecks, dominance mechanisms and epistasis on the fate of selectively advantageous mutations may help with explaining genetic diversity in natural highly fecund populations possibly evolving under sweepstakes reproduction.

Abstract. Daily vitamin D supplementation using higher than normal dosing (up to the upper limit, UL) and intermittent (once or twice per week) dosing were studied in patients with increased risk of vitamin D deficiency. Using a PubMed database an adequate search for published randomized control trials and other studies was done and results were analyzed. This review provides overview of use of 7000 IU daily, 30,000 IU per week or twice weekly and 50,000 IU weekly of vitamin D on rapid restore of 25(OH)D concentrations to at least 30 ng/mL in different groups of patients at high risk of vitamin D deficiency. The above mention dosing should be considered in adults with obesity or multi-diseased patients on requiring multi-treatment with the use of several drugs, including drugs affecting vitamin D metabolism. The simple schedule for 7000 IU/day, 30,000 IU/week or twice weekly or 50,000 IU/week, all for 6-8 weeks of use by patients representing the increased risk of vitamin D deficiency were provided for consideration. It appeared that higher daily doses or intermittent doses suggested above are effective, safe and responsive for patient’s preferences.

As technology advances, people are increasingly adopting IoT (Internet of Things) devices in smart cities. These devices are equipped with sensors that are connected everywhere, from energy infrastructure and transportation to telecommunications, health and human services, waste management, public safety, and more. People want to access sensor data anytime and everywhere to make better decisions and improve their lives. To achieve this, a sensor integration model has been developed where multiple sensors are integrated under one gateway to manage and share sensor data. However, effective sharing of sensor data requires data security, privacy, confidentiality, fairness, effective architectural design, and low communication and computation costs. These issues need to be addressed in the sensor integration model in smart cities. Existing storage models face challenges in managing sensor data effectively. To overcome these issues and hurdles, a data storage framework leveraging blockchain technology has been proposed within the sensor integration model. This framework ensures data security, privacy, confidentiality, and a fair and transparent financial model, all while minimizing communication and computation costs.

This study explores novel techniques to improve the detection accuracy of skarn iron deposits using advanced image processing methodologies. Leveraging the capabilities of Aster image, Band Ratio (BR) images, and Principal Component Analysis (PCA), alongside the power of 3D Convolutional Neural Networks (3D-CNN), the research aims to enhance the precision and efficiency of ore detection in complex geological environments. The proposed method employs a specific 3D-CNN architecture, accepting input as a 7×7×C image patch, where C represents the combined number of selected Aster image bands, Principal Component (PC) bands, and computed BR images. To evaluate the accuracy of the proposed method, five distinct image bands combinations, including the proposed bands combination, were tested and evaluated based on the overall accuracy (OA), average accuracy (AA), and kappa coefficient. The results demonstrated that while the incorporation of BR images alongside Aster bands initially seemed promising, it introduced significant confusion in certain classifications, leading to unexpected mis-classification rates. Surprisingly, utilizing solely Aster bands as input parameters yielded higher accuracy rates (OA= 93.13%, AA = 91.96%, Kappa = 90.91%) compared to scenarios involving the integration with band ratios (OA = 87.02%, AA = 79.15, and Kappa = 82.60%) or the integration of BR images to PC bands (OA= 87.78%, AA = 82.39%, Kappa = 83.81%). However, the amalgamation of Aster bands with selected PC bands showed slight improvements in accuracy (OA= 94.65%, AA = 92.93%, Kappa = 93.45%), although challenges in accurately classifying certain features persisted. Ultimately, the proposed combination of Aster bands, PC bands, and BR images (proposed bands combination) presented the most visually appealing and statistically accurate results (OA = 96.95%, AA= 94.87%, and Kappa = 95.93%), effectively addressing misclassifications observed in the other combinations. These findings underscore the synergistic contributions of each of the Aster bands, PC bands, and BR images, with Aster bands proving pivotal for optimal skarn classification, PC bands enhancing intrusions classification accuracy, and BR images strengthening wall rock classification accuracy. In conclusion, the proposed combination of input image bands emerges as a robust and comprehensive methodology, demonstrating unparalleled accuracy in the remote sensing detection of skarn iron minerals.

Undernutrition and micronutrient deficiencies such as anemia are considered significant public health challenges in Bangladesh, which enhancing fish consumption is a well-established food-based intervention to address these. This paper documents the establishment of community-based fish chutney production and reports the impact of its consumption on mid-upper arm circumference (MUAC) and hemoglobin (Hb) levels among targeted 150 pregnant and lactating women (PLW) in rural Bangladesh. A fish chutney was developed using locally available ingredients followed by a series of laboratory tests, including nutrient composition, shelf-life and food safety. A community-based fish chutney production process was designed to: 1) supply locally available ingredients for processing; 2) establish two fish drying sites; 3) initiate a community-based production site, and 4) distribute fish chutney to PLW by six women nutrition field facilitators for one year. Then a pre- and post-intervention study was designed for a selected 150 PLW to receive 30g of fish chutney daily for 12 months. Differences in mean mid-upper arm circumference (MUAC) and hemoglobin (Hb) levels pre- and post-consumption were analyzed using one-way analysis of variance. Consumption of 30g of fish-chutney resulted in significant increases of the mean values of Hb levels and MUAC among the targeted PLW.

Fire detection from satellite sensors relies on an accurate estimation of the unperturbed state of a target pixel, from which an anomaly can be isolated. Methods for estimating the radiation budget of a pixel without fire depend upon training data derived from the location's recent history of brightness temperature variation over the diurnal cycle, which can be vulnerable to cloud contamination and the effects of weather. This study proposes a new method that utilises the common solar budget found at a given latitude in conjunction with an area's local solar time to aggregate a broad-area training dataset, which can be used to model the expected diurnal temperature cycle of a location. This training data is then used in a temperature fitting process with the measured brightness temperatures in a pixel, and compared to pixel-derived training data and contextual methods of background temperature determination. Results of this study show similar accuracy between clear-sky medium wave infrared upwelling radiation and the diurnal temperature cycle estimation compared to previous methods, with demonstrable improvements in processing time and training data availability. This method can be used in conjunction with brightness temperature thresholds to provide a baseline for upwelling radiation, from which positive thermal anomalies such as fire can be isolated.

The reduction of PV prices and interest in energy independence accelerate the adoption of residential battery storage. This storage can support various functions of an energy system undergoing decarbonization. In this work, operative benefits of the storage from the system perspective, namely, generation cost reduction and congestion mitigation, are investigated. Germany is chosen as a case study due to its strong reliance on variable renewable energy. For the analysis, an economic dispatch model with a high spatial resolution is coupled with a Pan-European transmission grid model. It is shown that the system's generation costs are highest when the assets are used only to maximize the PV self-consumption, and the costs are lowest when the storage also reacts to the market dynamics. This amounts to 6% cost reduction. Both operation strategies result in an equal level of grid congestion and infrastructure loading. This is improved with a strategy that accounts regional peak reduction as a secondary objective. The high congestion level emphasizes the grid expansion need to keep pace with the generation and electrification expansion necessary to decarbonize other sectors. Lastly, policymakers should enable multipurpose utilization, e.g., via the introduction of market-oriented retail electricity prices with intervention options for grid operators.

It has been proven that in standard Einstein gravity, exotic matter (i.e. matter violating the point-wise and averaged weak and null energy conditions) is required to stabilize traversable wormholes. Quantum field theory permits these violations due to the quantum coherent effects found in any quantum field . Even reasonable classical scalar fields violate the energy conditions. In the case of the Casimir effect and squeezed vacuum states, these violations have been experimentally proven. It is advantageous to investigate methods of minimizing the use of exotic matter. One such area of interest is extended theories of Einstein gravity. It has been claimed that in some extended theories, stable traversable wormholes solutions can be found without the use of exotic matter. There are many extended theories of gravity and in this review paper we first explore f(R) theories and then explore some wormhole solutions in f(R) theories including Lovelock gravity.

This study addresses the pressing need for flood extent and exposure information in data-scarce and vulnerable regions, with a specific focus on West Africa, particularly Senegal. Leveraging the Google Earth Engine (GEE) platform and integrating data from Sentinel-1 SAR, Global Surface Water, HydroSHEDS, Global Human Layer Settlement, and MODIS Land Cover, our primary ob-jective is to delineate flood extents and compare them with centennial flood-prone areas, offering a comprehensive assessment of exposure during the period from July to October 2022 across Sen-egal's 14 regions. The findings underscore a total inundation area of 2 951 square kilometers, impacting 297 142 people, 175 square kilometers of urban and 16 square kilometers of crops. Notably, August wit-nessed the largest flooded areas, reaching 780 square kilometers, constituting 0.40% of the coun-try's surface. Subsequent regions, including Saint-Louis, Ziguinchor, Fatick, and Matam, experi-enced varying extents of flooding, with August data showing a 1.34% overall overlap compared to centennial flood-prone areas derived from hydrological and hydraulic modeling. This low per-centage reveals the distinct purposes and natures of the two approaches (remote sensing and modeling), as well as their complementarity. Turning to flood exposure, August emerges as the most critical month, affecting 76 595 people (0.43% of the total population). Dakar, Diourbel, Thiès, and Saint-Louis regions bore substantial impacts, affecting 100 707, 57 648, 31 579, and 26 581 people, respectively. These findings emphasize the imperative for comprehensive disaster preparedness and mitigation efforts. The study provides a crucial national-scale perspective to guide Senegal's authorities in formulating effective flood management, intervention, and adaptation strategies.

Background: Cardiovascular (CV) morbidity and mortality are many times higher in chronic kidney disease (CKD), as well as IgA nephropathy (IgAN), than in the general population. The occurrence of metabolic syndrome (MetS) and metabolic risk factors are independent risk factors for CV disease and renal progression. The study aimed to determine the prognostic role of metabolic profiles in a homogenous group of CKD patients. Methods: One hundred and forty-five IgA nephropathy patients (92 male, 53 female, age 54.7 ± 13 years) with CKD stage 1-4 were investigated and followed for a median of 190 months. The composite (CV and renal) endpoints included all-cause mortality and any CV event such as stroke, myocardial infarction, revascularization (CV), end-stage renal disease, and renal replacement therapy (renal). Results: Patients with MetS had significantly more endpoint events (16/27 patients vs. 15/98 patients, p = 0.001) compared to the nonMetS group. Of the secondary endpoints (CV or renal separately), the rate of the renal and CV endpoints was significantly higher in the MetS group (p = 0.001 and p = 0.029). The primary endpoint independent predictors of survival were dyslipidemia, eGFR, hemoglobin, urine albuminuria, and diabetes mellitus, as determined by Cox regression analysis. Independent predictors of secondary renal endpoint were dyslipidemia, hemoglobin, urine albumin, and eGFR. Predictors of secondary cardiovascular endpoints were gender, BMI, and diabetes. Kaplan-Meier curves showed significant differences in MetS and non-MetS when examined at the combined endpoints (CV and renal) or at each endpoint separately. The primary endpoint rate increased significantly with the increased number of MetS components (MetS comp. 0 vs. MetS comp. 2+, primary endpoints, p = 0.012). Conclusion: Our results showed that the metabolic profile has a prognostic role not only for renal endpoints but also for CV endpoints in IgAN. BMI, hyperuricemia, hypertension, and diabetes have a predictive value for the prognosis of IgA nephropathy.

Background Olfactory perception is an important physiological function for the human well-being and health. Loss of olfaction, or anosmia, caused by viral infections such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) received a considerable attention especially in the persistent cases that take long time to recover. Objectives This review discusses the integration of different components of the olfactory epithelium to serve as a structural and functional unit, and explores how they are affected during viral infections, leading to the development of olfactory dysfunction. Methods The review mainly focused on the role of receptors mediating the disruption of olfactory signal transduction pathways such as ACE2, TMPRSS2 protease, neuropilin 1 (NRP1), basigin (CD147), olfactory, TRPV1, purinergic, and interferon gamma receptors. Furthermore, the compromised function of the epithelial sodium channel (ENaC) induced by SARS-CoV-2 infection and its contribution in olfactory dysfunction is also discussed. Results Collectively, this review provides fundamental information about the many types of receptors that may modulate olfaction and participate in olfactory dysfunction. It will help to understand the underlying pathophysiology of virus-induced anosmia which may help in finding and designing effective therapies targeting molecules involved in viral invasion and in olfaction. Conclusion This wide and complex spectrum of receptors that mediates the pathophysiology of olfactory dysfunction reflects the many ways by which anosmia can be therapeutically managed.

Androgenetic alopecia is a genetic disorder caused by an excessive response to androgens. This alopecia is the most common cause of progressive hair loss in men and causes low self-esteem in patients. In this study we used various methods, including quantitative PCR, flow cytometry, ELISA, and immunocytochemistry, to evaluate the biological effects of germinated hemp seeds extract and exosomes derived from calli of germinated hemp seeds. This research reveals pre-ventive functions of two biomaterials (GE2000: 2000 ug/mL germinated hemp seeds extract; E40: 40 ng/mL exosomes derived from calli of germinated hemp seeds) for androgenetic alopecia through three biochemical categories: genetic modulation in hair follicle dermal papilla stem cells (HFDPSCs), cellular differentiation, and modulation of immune systems. Despite exposure to dihydrotestosterone (DT), two materials upregulated alopecia preventing genes including Wnt, β-catenin, and TCF in HFDPSCs. Conversely, alopecia activating genes (STAT1, 5α-reductase type 1, and IL-15R) were suppressed. Moreover, two materials suppressed alopecia genes (NKG2DL, IL2-Rβ, JAK1, and STAT1) in CD8+ T cells. Notably, E40 was effected more in-tensely in these biochemical categories than those of GE2000. Consequently, E40 and GE2000 ef-fectively prevented DT stress. Additionally, two materials activated mechanisms for hair for-mation through the biological activities of three categories.

Weather-related risks in aviation are one of the main causes of accidents worldwide. This article aims to analyze aviation risks resulting from adverse weather conditions, using the case study of the Pucallpa accident that occurred on August 23, 2005, in eastern Peru. In this analysis, we have determined the relationship between meteorological information and aviation risks, presented a matrix of risks associated with the most predominant meteorological variables at Pucallpa airport, and drawn up three maps of meteorological risks indicating the month of the year in which their incidence is most relevant. Finally, we conclude that it is essential to emphasize the importance of considering the prevailing weather conditions at Pucallpa airport to help mitigate the potential risks that may occur during different phases of the flight.

The progress in markerless technologies is bringing clinicians tools to rapidly evaluate tests such as Timed Up and Go (TUG) without compromising the time of the assessment, yet it raises questions about the potential trade-off in accuracy compared to traditional marker-based systems, suggesting that the precision of these evaluations is not yet conclusively established. The OpenCap system is an easy tool to process 3D kinematics with two iPhone cameras placed in front of the subject. Previous research has primarily focused on walking and movement towards the cameras with the subject facing the cameras (WF) and thus has been unable to disentangle the differences in the movement directions. We have compared the OpenCap system with a standard marker-based system for both walking directions. In OpenCap, we found significantly worse results capturing walking facing away from the cameras (RW). Compared to the marker-based system, our findings indicate troubles measuring kinematic parameters but provide good accuracy in measuring spatial-temporal parameters. These insights pave the way for refining markerless assessment technologies, potentially enhancing their utility in clinical settings.

In this work, an analog front-end (AFE) circuit for Electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter- all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the $g_m/I_D$ methodology. Both the pre-layout and post-layout simulation were carried out. The layout consumes an area of 0.0058 mm$^2$ without the resistors and capacitors. Analysis of various simulation results were carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz with a variable gain between 44 to 58 dB, a notch depth of -56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of -59.65 dB (less than 1\%), an input referred noise spectral density of $

The delivery of Cytochrome c (Cyt c) to the cytosol stimulates apoptosis in cells were its release from mitochondria and apoptosis induction is inhibited. We developed a drug delivery system consisting of Cyt c nanoparticles decorated with folate-poly(ethylene glycol)-poly(lactic-co-glycolic acid)-thiol (FA-PEG-PLGA-SH) to deliver Cyt c into cancer cells and test their targeting in the Lewis Lung Carcinoma (LLC) mouse model. Cyt c-PLGA-PEG-FA nanoparticles (NPs) of 253 ± 55 and 354 ± 11 nm were obtained by Cyt c nanoprecipitation, followed by surface decoration with the co-polymer SH-PLGA-PEG-FA, and compared to a nanoparticle-free formulation. Overexpression of FA in LLC cells and internalization of Cyt c-PLGA-PEG-FA nanoparticles (NPs) was confirmed by confocal microscopy. Caspase activation assays show NPs retain 88-96% Cyt c activity. The NP formulations were more efficient in decreasing LLC cell viability than the NP-free formulation, with IC50: 49.2 to 70.1 μg/ml versus 129.5 μg/ml, respectively. Our NP system is thrice as selective towards cancerous than normal cells. In-vivo studies using tagged nanoparticles show accumulation in mouse LLC tumor 5 min post-injection. In conclusion, our NP delivery system for Cyt c shows superiority over the NP-free formulation and reaches a folic acid-overexpressing tumor in an immune-competent animal model.

Background: Both of cognitive decline and unhealthy lifestyle have been associated with an increased risk of mortality in older people. We aimed to investigate whether lifestyle behaviors might modify the association between cognitive function and the risk of all-cause mortality in Chinese older populations. Methods: The study included 5,124 individuals free of dementia in the Chinese Longitudinal Healthy Longevity Survey from 2011 to 2018. Cognitive function was measured using the Mini-Mental State Examination in 2011. A lifestyle score was calculated on the basis of five lifestyle factors including smoking, alcohol consumption, physical activity, diet and body mass index. Cox proportional hazards models were performed to examine the association between baseline cognitive function and all-cause mortality, with an interaction term of cognitive function and lifestyle score being added to the models Results: During a median follow-up of 6.4 years, we documented 1,461 deaths. Both higher cognitive function (HR: 0.96; 95% CI: 0.96–0.97) and healthier lifestyle (HR: 0.92; 95% CI: 0.87–0.97) were significantly associated with a lower risk of mortality. We found that lifestyle significantly modified the association of cognitive function with mortality (P for interaction = 0.004). The inverse association between high cognitive function and mortality was more prominent among participants with healthier lifestyle. Of note, among the lifestyle scores component, diet showed a significant interaction with mortality (P for interaction = 0.003), with the protective HR of the all-cause mortality associated with higher MMSE scores was stronger among participants with healthy diets compared with unhealthy diets. Conclusion: Our study indicates that cognitive decline is associated with an increased risk of mortality, and such relations are modified by overall lifestyle, with healthy diet being the major contributor.

In this article we estimate the value of “Non-R&D Innovation Expenditures” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission from the period 2010-2019. We test data with the following econometric models i.e.: Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. We found that “Non-R&D Innovation Expenditures” is positively associated among others to “Innovation Index” and “Firm Investments” and negatively associated among others to “Human Resources” and “Government Procurement of Advanced Technology Products”. We use the k-Means algorithm with either the Silhouette Coefficient and the Elbow Method in a confrontation with the network analysis optimized with the Distance of Manhattan and we find that the optimal number of clusters is four. Furthermore, we propose a confrontation among eight machine learning algorithms to predict the level of “Non-R&D Innovation Expenditures” either with Original Data-OD either with Augmented Data-AD. We found that Gradient Boost Trees Regression is the best predictor for OD while Tree Ensemble Regression is the best Predictor for AD. Finally, we verify that the prediction with AD is more efficient of that with OD with a reduction in the average value of statistical errors equal to 40,50%.

Despite the acknowledged relevance of renewable energy sources, biofuel production supported by food-related agriculture has faced severe criticism. One way to minimize the considered negative impacts is the use of sources of non-food biomass or wastes. Synthetic biology (SB) embraces a promising complex of technologies for biofuel production from non-edible and sustainable raw materials. Therefore, it is pertinent to identify the global evolution of investments, concepts, and techniques underlying the field in support of policy formulations for sustainable bioenergy production. We mapped the SB scientific knowledge related to biofuels using software that combines information visualization methods, bibliometrics, and data mining algorithms. The United States and China have been the leading countries in developing SB technologies. Technical University of Denmark and Tsinghua University are the institutions with higher centrality and have played prominent roles besides UC-Los Angeles and Delft University Technology. We identified six knowledge clusters under the terms: versatile sugar dehydrogenase, redox balance principle, sesquiterpene production, Saccharomyces cerevisiae, recombinant xylose-fermenting strain, and Clostridium saccharoperbutylacetonicum N1-4. The emerging trends refer to specific microorganisms, processes, and products. Yarrowia lipolytica, Oleaginous yeast, E. coli, Klebsiella pneumoniae, Phaeodactylum tricornutum, and Microalgae are the most prominent microorganisms, mainly from the year 2016 onwards. Anaerobic digestion, synthetic promoters, and genetic analysis appear as the most relevant platforms of new processes. Improved biofuels, bioethanol, and N-butanol are at the frontier of the development of SB-derived products. Synthetic biology is a dynamic interdisciplinary field in environmentally friendly bioenergy production pushed by growing social concerns and the emergent bioeconomy.

Unlike fowl pox, pigeon pox virus (PPV) has not been described in Ghana. This is the first report of the disease and virus in Ghana based on gross necropsy, histopathological analysis and molecular techniques. This index case was presented as the occurrence of both cutaneous (dry) and diphtheritic (wet) forms of the pigeon pox disease in a 5-month-old female pigeon. Although the observation of Bollinger bodies during histology is confirmatory of pox viruses, the amplification of the p4b gene using polymerase chain reaction and its visualisation by gel electrophoresis confirmed the presence of an avian pox virus. Sequencing and phylogenetic analysis of the isolates from this case showed 100% relatedness to the reference PPV isolate FeP2. Thus, confirming the presence of PPV. The discovery of this virus in the Ghana raises the need for surveillance of both wild and domestic avian populations in preparation for any future outbreak, protection of the production birds and decision on the need for other pox viruses in the country.

The real systems are often complex, nonlinear, and noisy in various areas including mathematics, natural science, and social science. We present the symplectic entropy (SymEn) measure as well as an analysis method based on SymEn to estimate the nonlinearity of the complex system by analyzing the given time series. The SymEn estimation is a kind of entropy based on symplectic principal component analysis (SPCA) which represent organized but unpredictable behaviors of systems. The key to SPCA is to preserve the global submanifold geometrical properties of the systems through symplectic transform in the phase space, which is a kind of the measure-preserving transforms. The capability of preserving the global geometrical characteristics makes the SymEn a test statistic to detect the nonlinear characteristics in several typical chaotic time series and the stochastic characteristic in the Gaussian white noise. The results are in agreement with findings in the approximate entropy (ApEn), the sample entropy (SampEn) and the fuzzy entropy (FuzzyEn). Moreover, the SymEn method is also used to analyze the nonlinearities of the real signals (including the EEG signals for ASD and healthy subjects, and the sound and vibration signals for the mechanical systems). The results indicate that the SymEn estimation can be taken as a measure for describing the nonlinear characteristics in the data collected from the natural complex systems.