Olfaction plays a crucial role in many important behavioral activities of insects, such as finding sexual partners, locating hosts, and selecting oviposition sites. Ionotropic receptors (IRs) play a central role in detecting chemosensory information from the environment and guiding insect behaviors and are potential target genes for pest control. Empoasca onukii Matsuda is a major pest of the tea plant Camellia sinensis (L.) O. Ktze, and seriously influences tea yields and quality. In this study, the ionotropic receptor gene EnouIR25a in E. onukii was cloned, and the expression pattern of EnouIR25a was detected in various tissues. Behavioral responses of E. onukii to volatile compounds emitted by tea plants were determined by the olfactometer bioassay and field trials. To further explore the function of EnouIR25a in olfactory recognition of compounds, RNAi (RNA interference) of EnouIR25a was carried out by ingestion of in vitro synthesized dsRNAs. The CDS length of EnouIR25a was 1266 bp and it encoded a 48.87 kD protein. EnouIR25a was enriched in the antennae of E. onukii. E. onukii were more significantly attracted by 1-phenylethanol at concentration of 100 µl/ml. Feeding with dsRNA-IR25a significantly downregulated the expression level of EonuIR25a, after 3 h of treatment, which disturbed the behavioral responses of E. onukii to 1-phenylethanol at concentration of 100µl/ml. The response rate of E. onukii to 1-phenylethanol was significantly decreased after dsRNA-IR25a treatment for 12 h. In summary, the ionotropic receptor gene EnouIR25a was highly expressed in the antennae of E. onukii and was involved in olfactory recognition of the tea plant volatile 1-phenylethanol. The present study may help us to use the ionotropic receptor gene as a target for the behavioral manipulation of E. onukii in the future.

In this paper, feasibility of the initial alignment of the gyro-free inertial navigation system (GF-INS) is investigated. Initial roll and initial pitch are obtained as the conventional INS since centripetal acceleration is very small. Relation between initial heading and accelerometers’ outputs of the gyro-free inertial measurement unit (GF-IMU) is derived. It is determined from the relation whether initial heading can be obtained in 15 GF-IMUs which have been presented in research literatures. The relationship between the accelerometer errors of GF-IMU and the initial heading error is derived. When gyros are additionally attached in one axis or two axes of the body frame, it is investigated that initial heading can be obtained. The initial heading error is also calculated from the accelerometer errors and the gyroscope errors. The results show that the initial heading from only accelerometer outputs of the GF-IMU cannot be used in the GF-INS since the error is too large. It can also be seen from the results that the initial heading can be used in the GF-INS if two gyroscopes are additionally attached to the roll and pitch axes of the body frame.

This paper presents an improved SOC estimation method for lithium ion batteries in Electric Vehicles using Bayesian optimized feedforward network. This innovative bayesian optimized neural network method attempts to minimize a scalar objective function by extracting hyperpa-rameters (hidden neurons in both layers) using a surrogate model. Furthemore, the hyperparameters are built and data samples are trained and validated. The performance of the proposed deep learning neural network is evaluated. Two reasonable size data samples are ex-tracted from Panasonic 18650PF Li-ion Mendeley datasets that are used for training and valida-tion. RNN and LSTM neural network algorithms offer the common core property of retaining past information and/or hidden states for better SOC estimation. However, the feature of this pro-posed method is the inclusion of Bayesian optimization that chooses optimal double layer hidden neurons. Analysis of results shows that Bayesian optimized feedforward algorithm with average MAPE (0.20%) is the lowest and is the best selection compared with average MAPE for other five deep learning algorithms. In the last quarter of fuel gauge, where fuel anxiety is severe, feed-forward with Bayesian Optimization algorithm is still the best selection (with MAPE of 0.64%).

Energy storage systems (ESSs) are the key elements to improve the operation of power systems. On the other hand, these elements challenge the power system planners. The difficulties arise as a result of the ESSs' economic and technological features. The cycle life of ESSs is a critical aspect that influences the choices made during expansion planning processes. In this manuscript, we have focused on a new model for the expansion planning of ESSs considering the impacts of technical properties, such as the cycle life and depth of discharge. For this purpose, the proposed model consists of the hourly operation planning of ESSs in the sample days of year. A new indicator is proposed to determine the daily charging/discharging cycles of ESSs. Numerical results show the ability of the proposed model to determine the optimal technology and capacity of ESSs.

The article presents the results of a morpho-physiological assessment of rice samples by the strength of growth, as well as an assessment of the degree of development of the conducting system of the flag leaves of rice plants. The resistance of varieties to flooding is very relevant in the fight against weeds due to the deep layer of water that weeds cannot overcome. Currently, there are no zoned varieties in Russia that would meet these requirements. Therefore, the problem of creating such rice varieties is urgent, as it will reduce production costs, reduce grain losses during harvesting, improve the quality of the products obtained, and also reduce the pesticide load on the ecosystem. As a result of research, a number of studied samples revealed the potential to quickly lengthen the first leaves, overcome a large layer of water and accumulate vegetative mass. As a result of the evaluation of the conducting system of the flag leaf of rice plants, it was found that in plants with the flood resistance gene Sub1A, which stops growth under water, the conductive beams were smaller in comparison with other fast-growing samples with the AG, Sk genes. Consequently, fast-growing samples have bigger sizes of the conducting system as a resistance mechanism.

We investigate the extent to which a two-level quantum system subjected to an external time-dependent drive can be characterized by supervised learning. We apply this approach to the case of bang-bang control and the estimation of the offset and the final distance to a given target state. The estimate is global in the sense that no a priori knowledge is required on the parameters to be determined. Different neural network algorithms are tested on a series of data sets. We point out the limits of the estimation procedure with respect to the properties of the mapping to be interpolated. We discuss the physical relevance of the different results.

Introduction. The outbreak of the COVID pandemic was a period of uncer-tainty and tension for healthcare managers, resulting from the lack of knowledge, i.e. about the transmission of the virus, but also from the lack of uniform organisational and treatment procedures. It was the period where the ability to prepare to a crisis situation, to adapt to the existing conditions and to draw conclusion from the situa-tion were critical to keep ICUs operating. The aim of this study was to show the prep-aration of an ICU in Poland to ensure resilience, and also the methods of reacting dur-ing the COVID-19 pandemic on both central and local level. Methods. Based on the EC and WHO guidelines on resilience a matrix of 6 elements and 13 standards as-signed to them was created, with a series of questions from a survey questionnaire. Results. Good management in resilient systems is free access to any resource. A free and transparent flow of information and also well motivated human resources in an appropriate number. Conclusion. Appropriate preparation, adaptation to the existing situation and effective management of crisis situations is an important element of ICU resilience.

There is increasing interest in the application of near-infrared (NIR) laser light for the treatment of various musculoskeletal disorders. The present study thoroughly examined the physical characteristics of laser beams from two different laser therapy devices that are commercially available for the treatment of musculoskeletal disorders. Then, these laser beams were used to measure the penetration depth in various biological tissues from different animal species. The key result of the present study was the finding that for all investigated tissues, most of the initial light energy was lost in the first one to two millimeters, more than 90% of the light energy was absorbed within the first ten millimeters, and there was hardly any light energy left after 15 – 20 mm of tissue. Furthermore, the investigated laser therapy devices fundamentally differed in several laser beam parameters that can have an influence on how light is transmitted through tissue. Overall, the present study showed that a laser therapy device that is supposed to reach deep layers of tissue for treatments of musculoskeletal disorders should operate with a wavelength between 800 nm and 905 nm, a top-hat beam profile, and it should emit very short pulses with a large peak power.

The cortical motor system can be reorganized following a stroke, with an increasing recruitment of the contralesional hemisphere. However, it is unknown whether a similar hemispheric shift occurs in the somatosensory system to adapt to this motor change, and whether this is related to movement impairments.  This proof-of-concept study assessed somatosensory evoked potentials (SEPs), P50 and N100, in hemiparetic stroke participants and age-matched controls using high-density electroencephalograph (EEG) recordings during tactile finger stimulation. The laterality index was calculated to determine hemispheric dominance of the SEP and re-confirmed with source localization.  The study found that latencies of P50 and N100 were significantly delayed in stroke brains when stimulating the paretic hand. The amplitude of P50 was negatively correlated with Fügl-Meyer Upper Extremity Motor Score in stroke. Bilateral cortical responses were detected in stroke, while only contralateral cortical responses were shown in controls, resulting in a significant difference in the laterality index.  These results suggested that somatosensory reorganization after stroke involves increased recruitment of ipsilateral cortical regions. This reorganization delays the latency of somatosensory processing after a stroke.  This research provided new insights related to the somatosensory reorganization after stroke, which could enrich future hypothesis-driven therapeutic rehabilitation strategies from a sensory or sensory-motor perspective.

When designing rule-based dialogue systems, the need for elaborate design by the designer is a challenge for dialogue systems. One way to reduce the cost of creating content is to generate utterances from data collected in an objective and reproducible manner. This study focuses on rule-based dialogue systems using survey data, and more specifically on opinion dialogue where the system models the user. In opinion dialogue, there has not been much study of topic transition methods for modeling users while maintaining their motivation for dialogue. To model them, we adopted information content. Our contribution includes the design of a rule-based dialogue system that does not require elaborate design. We also reported an appropriate topic transition method based on information content. This is confirmed by the influence of the user's personality characteristics. The content of questions can give the user a sense of the system's intention to understand them. We also reported the possibility that the system's rational intention contributes to the user's motivation for dialogue with the system.

The thermocontextual interpretation (TCI) defines the physical state with respect to a system’s actual surroundings at a positive ambient temperature. The TCI provides a clear distinction between the Second Law of thermodynamics and MaxEnt. The Second Law dictates irreversible dissipation of free energy to ambient heat, and it establishes the thermodynamic arrow of time. MaxEnt describes reversible changes in statistical mechanical entropy in response to changes in the system’s boundary constraints. We introduce new TCI postulates that establish the equality of thermal and statistical entropies and MaxEnt as a fundamental physical principle. We then apply MaxEnt to the double-slit experiment. Impacts of multiple particles symmetrically passing through parallel slits record a wave interference pattern over time. However, a which-slit detector eliminates wave interference. Richard Feynman called the double slit experiment the only mystery, at the heart of quantum mechanics. The TCI and MaxEnt offer a simple explanation. The which-slit detector breaks the system’s symmetry, and MaxEnt selects the higher-entropy asymmetrical state, enabling particles to pass through one slit or the other without wave interference.

Proposal: Pineal region cysts (PCs) may affect the tectum and aqueduct and cause deep central vein congestion and endocrine dysfunction. In addition to headaches, PC often causes a broad range of symptoms, leading to prolonged diagnosis and therapy. The aims of this study are to reveal parameters that might explain the ambiguity of the symptoms and to identify factors association with the respiration driven neurofluid preload system. Methods: This retrospective study included 28 paediatric patients (mean age 11.6 years) who received surgical treatment for pineal region cysts and 18 patients (mean age 11.3 years) who were followed conservatively. Multiple clinical patient characteristics, such as symptoms, time to neuroimaging diagnosis, cyst size, ventricular indices, head circumference and postoperative outcome, were analysed. Four patients were investigated for CSF dynamics with real-time MRI. The mean follow-up time was 1.6 years. Results: The most common early onset symptoms were headaches (92%), blurred vision (42.8%), sleep disturbances (39.3%) and vertigo (32.1%). Tectum contact was observed in 82% of patients, and MRI examinations revealed that imaging flow void signals were absent in 32.1% of patients. The mean cyst diameters were 13.7 mm for the axial axis and 15.6 mm for the longitudinal axis. Together with a postoperative flow void signal, 4 patients recovered their respiration-driven CSF upward flow, which was not detectable before OP. After operation in 92.1% of patients, the leading symptoms improved without any mortality or morbidity. Conclusion: Despite proximity to the tectum and aqueduct with frequently absent aqueductal flow void signals, hydrocephalic ventricular enlargement was never detected. Data from real-time MRI depicted a reduced preoperative filling of the ventricular CSF compartments, indicating a diminished fluid preload, which recovered postoperatively.

Tropical cyclones devastate large areas, take numerous lives and damage extensive property in Bangladesh. Research on landfalling tropical cyclones affecting Bangladesh has primarily focused on events occurring since AD1960 with limited work examining earlier historical records. We rectify this gap by developing a new tornado catalogue that include present and past records of tornados across Bangladesh maximizing use of available sources. Within this new tornado database, 119 records were captured starting from 1838 till 2020 causing 8,735 deaths and 97,868 injuries leaving more than 1,02,776 people affected in total. Moreover, using this new tornado data, we developed an end-to-end system that allows a user to explore and analyze the full range of tornado data on multiple scenarios. The user of this new system can select a date range or search a particular location, and then, all the tornado information along with Artificial Intelligence (AI) based insights within that selected scope would be dynamically presented in a range of devices including iOS, Android, and Windows. Using a set of interactive maps, charts, graphs, and visualizations the user would have a comprehensive understanding of the historical records of Tornados, Cyclones and associated landfalls with detailed data distributions and statistics.

To determine the ethical-attitudinal profile of university students in the education career during the pandemic with a tendency towards a new normality. University students of the education career were surveyed online, in an ethical key (axiological attitude, moral attitude and attitude towards new normality). The research was descriptive of univariate hypothesis, with non-probabilistic snowball sampling, reaching a sample of 480 participants. The Ethical-Attitudinal Profile Scale (EPEA) was designed, whose reliability was 0.93 in Lawshe's formula and 0.89 in Cronbach's Alpha. In the axiological attitude, values were obtained more frequently: respect with 79%, sincerity with 73%, prudence with 72%. In the moral attitude, a polar result is contrasted between laxity (67%) and kindness (45%); while, in the attitude towards new normality, there was no spike in frequencies, being distributed more homogeneously between indicators, with a low resilience index. There is an adequate evaluative profile of the university students of the education career despite the context of the pandemic and the trend towards a new normality; having a moral attitude of laxity inferred by the circumstances of uncertainty that are experienced in adverse contexts.

The ridge line of the western Pacific subtropical high (WPSHRL) plays an important role in determining the shift of the summer rain belt in eastern China. In this study, we developed a forecast system for the June WPSHRL index based on the latest autumn and winter sea surface temperature (SST). Considering the adverse condition of the small observed sample size, a very simple neural network (NN) model was selected to extract the non-linear relationship between input predictors (SST) and target predictands (WPSHRL) in the forecast system. In addition, some techniques are used to deal with the adverse condition, enhance the stabilization of forecast skills, and analyze the interpretability of the forecast system. The forecast experiments show that the linear correlation coefficient between the predictions from the forecast system and their corresponding observations is around 0.6, and about three-fifths of the observed abnormal years (the years with an obviously high or low WPSHRL index) are successfully predicted. Furthermore, sensitivity experiments show that the forecast system is relatively stable in terms of forecast skill. The above evaluations suggest that the forecast system is valuable in a real application sense.

The Failure Mode and Effect Analysis (FMEA) is often used to improve a system's reli-ability. This paper proposes a new approach that aims to overcome the most critical defects of the traditional FMEA. This new methodology combines the Entropy and Best Worst Method (BWM) methodology with the EDas and System Dynamics, FMECA: The EN-B-ED Dynamic FMECA. The main innovation’s point of the proposed work is the presence of an unknown factor (Cost), that allows to obtain an objective weighted factor, a risk index when a machine failure occurs. The criticality analysis has been carried out using software (Vensim PLE x64) to simulate System Dynamics models to identify corrective actions and evaluating the possible implementation of these ac-tions. The methodology proposed is applied to a case study in a relevant Italian com-pany in the agri-food sector.

Offshore grids can have a key role in the transition of the energy system to sustainability. Although they require extensive infrastructure investments, they open up for the exploitation of additional resources and may be important to provide for part of the increasing electricity demand driven by sector coupling. This paper quantifies the socio-economic value of offshore grids and identifies their major drivers, performing energy system optimization in a model application of the Northern-central European energy system and the North Sea offshore grid towards 2050. The increasing wake loss with the size of hub-connected wind farms is integrated in the modelling. We find that without sector coupling no offshore grid may develop, and that the higher the level of sector coupling, the higher the value of offshore grids. Therefore, it can be strongly stated that offshore grid infrastructure development should not be discussed as a separate political topic, but seen in connection to sector coupling.

We studied the prognostic impact of tumor immunoglobulin kappa C (IGKC) mRNA expression as a marker of the humoral immune system in the FinHer trial patient population, where 1,010 patients with early breast cancer were randomly allocated to either docetaxel-containing or vinorelbine-containing adjuvant chemotherapy. HER2-positive patients were additionally allocated to either trastuzumab or no trastuzumab. Hormone receptor-positive patients received tamoxifen. IGKC was evaluated in 909 tumors using quantitative real-time polymerase chain reaction, and the influence on distant disease-free survival (DDFS) was examined using univariable and multivariable Cox regression and Kaplan-Meier estimates. Interactions were analyzed using Cox regression. IGKC expression, included as continuous variable, was independently associated with DDFS in a multivariable analysis including also age, molecular subtype, grade, and pT and pN stage (HR 0.930, 95% CI 0.870 – 0.995, P = 0.034). An independent association with DDFS was also found in a subset analysis of triple-negative breast cancers (TNBC) (HR 0.843, 95% CI 0.724 – 0.983, P = 0.029), but not in luminal (HR 0.957, 95% CI 0.867 – 1.056, P = 0.383) or HER2-positive (HR 0.933, 95% CI 0.826 – 1.055, P = 0.271) cancers. No significant interaction between IGKC and chemotherapy or trastuzumab administration was detected (Pinteraction = 0.855 and 0.684, respectively). These results show that humoral immunity beneficially influences the DDFS of patients with early TNBC.

Monitoring of the surface operations using movement and surveying radar (MSR) can prevent loss of life, equipment, production and loss of the mine. Slope monitoring using MSR is an important aspect of open-pit mining as it provides real-time movement of deformation data for the slope. It is therefore important that the radar is accurately geo-referenced in order to provide accurate real-time movement data. Geo-referencing is defined as the process of determining an instrument’s position (in the form of Easting, Northing, Height) as well as the orientation with respect to the mine’s local coordinate system. This helps in getting geo-referenced data points from the radar that are identified by a unique set of coordinates in relation to the mine’s coordinate system which allows the radar to track movement for a specific set of coordinates. In this research, we assess the performance of geo-referencing a radar using the total station method and compare it with the integration of Advance Navigation – Spatial Dual GPS system connected via RS422 on the MSR. This includes usage of the Spatial Dual navigation coordinates output to calculate the radar’s position relative to the mine local coordinates and mapping the radar’s azimuth, elevation and Range (Az, El and Rl) values to the measured pit-slope data points. Furthermore, a comparison of key attributes of both methods of geo-referencing is performed using a matrix system and giving an overall performance appraisal of both systems. Integrating a navigation system allows the radar to have an auto geo-referencing functionality that will reduce the time spent in completing this process. The findings reveal that the GPS obtained a higher score than the total station with prism method on the weighted matrix system. The total station was found to be more accurate than the GPS however, the deployment time for the GPS is quicker than that of the total station. This is important for different operation such as strip and open-pit mining to choose the preferred method of geo-referencing depending on the level of accuracy required.

The entropy of a system gives a powerful insight into its microscopic degrees of freedom, however standard experimental ways of measuring entropy through heat capacity are hard to apply to nanoscale systems, as they require the measurement of increasingly small amounts of heat. Two alternative entropy measurement methods have been recently proposed for nanodevices: through charge balance measurements and transport properties. We describe a self-consistent thermodynamic framework for treating few-electron nanodevices which incorporates both existing entropy measurement methods, whilst highlighting several ongoing misconceptions. We show that both methods can be described as special cases of a more general relation and prove its applicability in systems with complex microscopic dynamics – those with many excited states of various degeneracies.

The purpose of this work is to determine the possibility of using an automated SkyWatcher Virtuoso system to analyze distribution of sky luminance. The article presents the procedure for measuring the sky luminance distribution defined according to CIE using a manual luminance meter cooperating with the SkyWatcher system. The use of matrix luminance meter was also analyzed.

Accruing evidence on the influence of β-carotene regarding the prevention of several chronic diseases - in addition to its well-acknowledged role in vision has been a strong driver for developing alternative delivery systems. Though oral delivery is accepted as the most fitting, mild and safe path for delivering bioactive agents, β-carotene delivery via food items poses challenges due to its lipophilic nature, poor water-solubility, high chemical/photochemical instability and poor oral bioavailability. Nanotechnology has opened new windows for delivering bioactive agents. Their physiochemical characteristics, i.e. small size, high surface area, unique composition, biocompatibility and biodegradability make these nanomaterials an attractive tool for β-carotene delivery. Delivering β-carotene through nanoparticles does not only improve its bioavailability/bioaccumulation in target tissues, but also lessens its sensitivity against environmental factors during processing. Regardless of these benefits, nanocarriers inherit some limitations, such as variations in sensory quality, modification of the food matrix, increasing costs, as well as limited consumer acceptance and regulatory challenges. This research area has been rapidly evolved, with a plethora of innovative nano-engineered materials, including micelles, nano/microemulsion, liposomes, niosomes, solid-lipid nanoparticles and nanostructured lipid carriers. These nano-delivery systems make conventional delivery systems appear archaic and promise better solubilization, protection during processing, improved shelf-life, higher bioavailability as well as controlled and targeted release. This review provides information on the state of knowledge on β-carotene nano-delivery systems adopted for developing functional foods: depicting their classification, composition, preparation methods, challenges, release-and absorption of β-carotene in the GIT and possible risks and future prospects.

this review summarizes current knowledge of the hydrogen sulfide role in cardiovascular system, the proposed mechanisms of its action and the prospects for its applicability in the treatment of cardiovascular diseases. Hydrogen sulfide was recently recognized as gasotransmitter – simple signaling molecule which freely penetrates the cell membrane and regulates a number of biological functions. In humans endogenous H2S is generated via enzymatic and non-enzymatic pathways and its content varies in different tissues and is strictly regulated. In cardiovascular system H2S is produced by myocardial, vascular and blood cells and regulates a number of vital functions. Numerous experimental data prove that endogenously generated as well as exogenously administered H2S exerts a wide range of actions in cardiovascular system, including vasodilator/vasoconstrictor effects, regulation of blood pressure, pro-apoptotic and anti-proliferative effects in the vascular smooth muscle cells, influence on angiogenesis and erythropoiesis, myocardial cytoprotection in ischemia-reperfusion injury, oxygen sensing, inhibition of platelet aggregation and blood coagulation, modification of erythrocyte microrheological properties (aggregability and deformability). Understanding of molecular mechanisms of H2S action and molecular crosstalk between H2S, NO, and CO is essential for the development of its diagnostic and therapeutic potential.

Recently, the application of deep reinforcement learning in recommender system is flourishing and stands out by overcoming drawbacks of traditional methods and achieving high recommendation quality. The dynamics, long-term returns and sparse data issues in recommender system have been effectively solved. But the application of deep reinforcement learning brings problems of interpretability, overfitting, complex reward function design, and user cold start. This paper proposed a tag-aware recommender system based on deep reinforcement learning without complex function design, taking advantage of tags to make up for the interpretability problems existing in recommender system. Our experiment is carried out on MovieLens dataset. The result shows that, DRL based recommender system is superior than traditional algorithms in minimum error and the application of tags has little effect on accuracy when making up for interpretability. In addition, DRL based recommender system has excellent performance on user cold start problems.

Extracorporeal shock wave therapy (ESWT) is a well investigated and widely used treatment modality for a number of musculoskeletal disorders. A limitation of ESWT is its potential painfulness at higher, clinically relevant energy flux density (EFD), which may limit its applicability and, thus, effectiveness. Various studies in the literature demonstrated that neither application of a higher number of extracorporeal shock waves with lower EFD nor use of local anesthesia may solve this problem. Based on the results of several other studies in the literature it is hypothesized here that in patients suffering from musculoskeletal disorders that can be treated with ESWT, pretreatment with a pulsed, high power laser with a wavelength of 904 or 905 nanometers (hereafter: "laser pretreatment") does not only allow to apply higher EFDs in subsequent ESWT but actually results in faster and/or better treatment outcome than ESWT without laser pretreatment. Accordingly, it is hypothesized here that combining ESWT with laser pretreatment leads to synergistic effects and, thus, is superior to either treatment modality alone. Confirming this hypothesis in preclinical and clinical research may raise significance and increase the use of ESWT in physical and rehabilitation medicine, with immediate benefit for patients.

Early prediction of thermal loads plays an essential role in analyzing energy-efficient buildings' energy performance. On the other hand, stochastic algorithms have recently shown high proficiency in dealing with this issue. These are the reasons that this work is dedicated to evaluating an innovative hybrid method for predicting the cooling load (CL) in buildings with residential usage. The proposed model is a combination of artificial neural networks and stochastic fractal search (SFS-ANN). Two benchmark algorithms, namely the grasshopper optimization algorithm (GOA) and firefly algorithm (FA), are also considered to be compared with the SFS. The non-linear effect of eight independent factors on the CL is analyzed using each model's optimal structure. Evaluation of the results outlined that all three metaheuristic algorithms (with more than 90 % correlation) can adequately optimize the ANN. In this regard, this tool's prediction error declined by nearly 23, 18, and 36 % by applying the GOA, FA, and SFS techniques. Also, all used accuracy criteria indicated the superiority of the SFS over the benchmark schemes. Therefore, it is inferred that utilizing the SFS along with ANN provides a reliable hybrid model for the early prediction of CL.

Capacity Expansion Models (CEMs) are optimization models used for long-term energy planning on national to continental scale. They are typically computationally demanding, thus in need of simplification, where one such simplification is to reduce the temporal representation. This paper investigates how using representative periods to reduce the temporal representation in CEMs distorts results compared to a benchmark model of a full chronological year. The test model is a generic CEM applied to Europe, equipped with a novel formulation for storage in model versions with reduced temporal representation. We test the performance of reduced models at penetration levels of wind and solar of 90%. Three measures for accuracy are used: (i) system cost, (ii) total capacity mix and (iii) regional capacity. We find that: (i) the system cost is well represented (~5% deviation from benchmark) with as few as ten representative days, (ii) the capacity mix is in general fairly well (~20% deviation) represented with 50 or more representative days, and (iii) the regional capacity mix displays large deviations (>50%) from benchmark for as many as 250 representative days. We conclude that modelers should be aware of the error margins when presenting results on these three aspects.

Female infertility is a global medical condition that can be caused by various disorders of the reproductive system, including premature ovarian failure (POF), polycystic ovary syndrome (PCOS), endometriosis, Asherman syndrome, and preeclampsia. It affects the quality of life of both patients and couples. Mesenchymal stem cells (MSCs) have received increasing attention as a potential cell-based therapy with several advantages over other cell sources, including greater abundance, fewer ethical considerations, and high capacity for self-renewal and differentiation. Clinical researchers have examined the therapeutic use of MSCs in female infertility. In this review, we discuss recent studies on the use of MSCs in various reproductive disorders that lead to infertility. We also describe the role of microRNAs (miRNAs) and exosomal miRNAs in controlling MSC gene expression and driving MSC therapeutic outcomes. The clinical application of MSCs holds great promise for the treatment of infertility or ovarian insufficiency and to improve reproductive health for a significant number of women worldwide.

In Electronic Nicotine Delivery System (ENDS), coil resistance is an important factor in the generation of heat energy used to change e-liquid into vapor. An accurate and unbiased method for testing coil resistance is vital for understanding its effect on emissions and reporting results that are comparable across different types and brands of ENDS and measured in different laboratories. This study proposes a robust, accurate and unbiased method for measuring coil resistance. An apparatus is used which mimics the geometric configuration and assembly of ENDS pods and power control units. The method is demonstrated on two commonly used ENDS devices, the ALTO by Vuse and JUUL. Analysis shows that the proposed method is stable and reliable. The two-wire configuration introduced a positive measurement bias of 0.086 [ohm], which is a significant error for sub-ohm coil designs. The four-wire configuration is far less prone to bias error. We observed a significant difference in coil resistance of 0.593 [ohm] (p<0.001) between the two products tested. The mean resistance and standard deviation of the pod coil assemblies was shown to be 1.031 (0.067) [ohm] for ALTO and 1.624 (0.033) [ohm] for JUUL. The variation in coil resistance between products and within products can have significant impacts on aerosol emissions.

Taking into account the increase in the emission of greenhouse gases produced by ships, during navigation and maneuvering in the port, a direct consequence of the increase in maritime traffic, the international community has developed a broad set of regulations to limit such emissions. The installation in commercial ports of automatic mooring systems by means of vacuum suction cups (AMS), thus reducing considerably the time required to carry out the mooring and unmooring maneuvers of ships, is a factor that is considerably influencing the decrease in Emissions of polluting gases in commercial ports with high traffic. The objective of the present work is to verify the influence of the use of the AMS on the emissions of polluting gases produced in the facilities destined to the traffic of container ships. It examines the CO2 emissions of container ships that call in the only three container ports equipped with AMS: Salalah (Oman), Beirut (Lebanon) and Ngqura (South Africa). Between them, these three ports supported the transit of 6 million TEUS in 2017. The calculation of emissions is made taking into account the time saved when performing the mooring maneuvers using the new AMS system compared with when it is not used. To do this, two different calculation methods are used: EPA and ENTEC to then compare the results of the two and thus obtain the reduction in emissions per TEU in these terminals during the mooring maneuvers. The paper concludes with a discussion on the values of the reductions in emissions obtained and the advantages of the installation of AMS in commercial ports located near population centres.

The aim of the instant study was to evaluate relative inline progesterone dynamic changes according to parity and status of reproduction and to estimate the relationship with productivity in dairy cows by inline milk analysis system (IMAS) Herd Navigator. According to a progesterone assay, cows were divided into three periods: postpartum, after insemination, and pregnancy. In the first stage of the postpartum period (0-29 days), the progesterone level in milk was monitored every 6 days. The second stage of the postpartum period (30-65 days) lasted until cows were inseminated. In the third period (0-45 days) after cows were inseminated, progesterone scores were distributed according to whether or not cows became pregnant. The stability of progesterone dynamics was monitored in the last study period (45-90 days). For milk progesterone detection, the fully automated real-time progesterone analyzer Herd Navigator (Lattec I/S. Hillerød. Denmark) was used in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). The highest progesterone concentration in multiparous cows ranged from 1.08% (11-17 days postpartum) to 34.89% higher than that in cows of the first parity. The lowest progesterone concentrations in the milk of all cows were estimated during the first 5 postpartum days and between 18 and 23 days after calving. Peak milk progesterone concentrations were evaluated in the first stage of the experiment on days 24-29 after calving. In the 30-65-day period after calving, the level of milk progesterone was 2.02-2.08 times higher than that in the 24-29-day postpartum period. After insemination, the level of progesterone in milk increased by 10.77-22.54% compared with the level from cows on days 30-65 after calving. A higher (12.88%) concentration of progesterone in milk was evaluated in multiparous cows compared with that from cows of the first parity. In pregnant cows, milk progesterone within 0-45 days after insemination was 23.88% (in multiparous cows) and 32.54% (in primiparous cows) higher than that in non-pregnant cows. On days 31–35 after insemination, pregnant cows had higher milk progesterone levels, which can predict pregnancy success. According to our study results, we can suggest that an inline progesterone concentration determined by inline milk analysis system Herd Navigator and changes in its dynamics correlate with different reproductive statuses and milk yield of cows. Pregnant cows 11–15 days after insemination have higher milk progesterone levels, what positively, associated with a successful pregnancy.

Purpose: At a time of a pandemic SARS-CoV2 infection, and in the context of the multiorgan crosstalk widely accepted as a mechanism participating in the pathophysiology of all organs and systems, a correlation between adipose tissue, muscle and the immune system has been investigated. Physical Activity (PA) represents the first line of defence against metabolic diseases and infections, like SARS-CoV2, modulating several crucial functions such as inflammation and immune response. Conversely, obesity, type 2 diabetes and cardiovascular disorders – all correlated with PA - negatively impact on general health status, including susceptibility to infections. Here we review the complex interplay between type 2 diabetes, obesity, immune response, inflammation and viral infections, such as the current SARS-CoV2, focusing on the molecular mechanisms modulated by exercise. Methods: A comprehensive literature search was completed to identify joint biomarkers previously used to investigate acute and chronic exercise training. Results: we show that PA may counteract/mitigate viral adverse effects. We also describe data suggesting that vitamin D supplementation, frequently observed in practitioners of sport and regular exercise, could represent an additional positive factor in supporting COVID-19 with fighting against the virus. Conclusion: Altogether this evidence confirms that an active lifestyle and PA not only counteract dysmetabolic diseases but could also be effective for counteracting SARS-CoV2 infection. It is therefore essential to persuade people to keep active.

This case study investigates the heart rate (HR) and heart rate variability (HRV) in a patient with coronavirus disease 2019 (COVID-19). We report the case of a 58-year old male who contracted COVID-19. During his disease, 24-hour Holter electrocardiography (ECG) was performed continuously. For comparison, his 24-hour Holter ECGs from the previous 10 years were available. In this patient, COVID-19 was associated with a decrease in HR and a paradoxical decline in HRV. An abrupt decline in HRV and a decrease in HR may signal the onset of COVID-19 before common symptoms such as dry cough or fever appear. In addition, HRV and HR measurements may help to evaluate the course of the disease.

A novel and highly pathogenic coronavirus (2019-nCoV)-induced pneumonia spread worldwide in a short time. However, studies on the effects of 2019-nCoV on the male reproductive system are limited. The aim of this study is to describe the clinical characteristics of the male reproductive system of COVID-19 patients and to explore the presence of 2019-nCoV in semen. Retrospective, single-center case series of 112 male patients with confirmed COVID-19 who were admitted to Renmin Hospital of Wuhan University from January 2 to March 7, 2020. Demographic data, symptoms and signs related to the male reproductive system, throat swabs and semen samples were collected and analyzed. 2019-nCoV RNA measured in throat swab and semen samples. The organ distribution of ACE2 mRNA and protein in human tissue on The Human Protein Atlas portal and investigated immunohistochemistry (IHC) images of the testis. The HPA dataset revealed relatively high levels of ACE2 protein and RNA expression in the testis. A total of 3 severe COVID-19 patients (2.7%) presented with orchidoptosis, while no patients experienced other symptoms or signs related to the male reproductive system. The analysis of 2019-nCoV RNA in semen included 17 patients with fertility needs. Among these patients, 9 (52.9%) remained positive for 2019-nCoV according to throat swab analysis, and 8 (47.1%) became negative. In the semen 2019-nCoV analysis, all 17 patients were negative for the N gene and ORF1ab gene. In view of the potential impairment, long-term follow-up for male COVID-19 patients with fertility needs is of great significance.

An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred in China towards the end of 2019, and has spread rapidly ever since. Previous studies showed that some virus could affect the reproductive system and cause long-term complications. Recent studies exploring the source of SARS-CoV-2 using genomic sequencing have revealed that SARS-CoV-2 enters the host cells via the angiotensin-converting enzyme II (ACE2), the receptor that recognizes SARS-CoV. To investigate the expression of ACE2 and to explore the potential risk of infection in the reproductive system, we performed a thorough bioinformatic analysis on data from public databases involving RNA expression, protein expression, and single-cell RNA expression studies. The analyzed data showed high levels of ACE2 mRNA and protein expression in the testis and spermatids and equal levels of ACE2 expression in the uterus and lung. Comprehensive single-cell analysis identified ACE2 expression in the lung, testis, spermatids, and uterus. In conclusion, this study revealed the potential risk associated with the SARS-CoV-2 infection in the reproductive system and predicted that long-term complications might have a significant impact on the prevention and management of COVID-19, the disease caused upon infection with SARS-CoV-2.

Taking capital, manpower, and natural resources as inputs, regional GDP as expected output, and industrial pollution as undesired output, this study measures the ecological efficiency of various regions in China through the Global-Malmquist model. The results show a trend of an initial sharp decline in ecological efficiency followed by a gradual increase in the time dimension, but there is no significant correlation in the spatial dimension. Using the gravity model to quantify the attractiveness of the regions’ capital and human resources for collaborative innovation, it estimates the impact of collaborative innovation on eco-efficiency through the system-Generalized Method of Moments (GMM) model. The results show that technological innovation capital in other regions has a negative “U” relationship with local ecological efficiency, while scientific and technological innovation human resources have a positive “U” relationship. In addition, government financial support in science and technology and the ecological efficiency of the previous period serve as promoting factors of the current local ecological efficiency, while the introduction of foreign technological innovation is likely to inhibit improvements in ecological efficiency. Based on these findings, this study puts forward corresponding policy recommendations for local governments to advance their development agendas alongside their environmental priorities in line with their specific circumstances.

Health information and communication are key elements that allow patients and family members to make decisions about end-of-life process and guarantee a death with dignity. Objective: To understand carers’ experiences regarding health information and communication during the illness and death of family members. Methods: This qualitative study was conducted in Andalusia based on the paradigm of hermeneutic phenomenology. Participants were carers who had accompanied a family member at the end of life for over 2 months and less than 2 years. Five nominal groups and 5 discussion groups were established, and 41 in-depth interviews with 123 participants were conducted. Atlas.ti 7.0 software was used to analyse the discourses. Results: Four dimensions of the dying process emerged: differences in carers’ perceptions of information and communication, a conspiracy of silence, consequences of the absence or presence of information, and the need for a culture change. Conclusions: Poor management of health information and communication at the end of life suffering and discomfort patients and their families. The culture of denying and avoiding death is still present today. A change in education about death would better enable health professionals to care for patients at the end of life.

The paper is devoted to fundamental issues concerning to the ideology of the future sustainable development. Its implementation has available in the first place basing on the recognized framework concept of sustainable development (SD). At the same time, this concept requires serious improvement. As follows from the argumentation, a realistic design of institutional changes in connection with resource and organizational/behavioral changes needed for SD is called for to realize in the line of overall social system transformation. Its adequate understanding presupposes an exhaustive study of interconnected transformations in the main social fields as system processes taking into account the influence of relatively exogenous factors (technological, demographic and climate changes).According to the author, the transition to global sustainable social transformation is achievable. Main attention focuses on a number of possible fundamental shifts, the synergetic implementation of which will make such a transition possible.Proceeding from the arguments, the sustainable reproduction of the economy of a mature post-industrial type, including the green sectors, implies its stable and quiet growth, although the rapid growth of individual markets, especially innovative ones, may take place. The main findings also include the substantiation in favor of the choice of the national middle way model as the most appropriate for the corresponding sustainable system transformation of society.

Recently, the phase-sensitive OTDR (Φ-OTDR) based vibration sensor system has gained the focus of many researchers and some efforts have been undertaken to push further the limitations imposed on the performance of the Φ-OTDR sensor system. Then, progress in the different areas of its performance evaluation factors such as: improvement of the signal-to-noise ratio (SNR), spatial resolution (SR) in the sub-meter range, enlargement of the sensing range, frequency response bandwidth over the conventional limit and phase signal demodulation for quantitative measurement have been realized. This paper presents an overview of the recent progress in the Φ-OTDR based vibration sensing system in the different areas mentioned above.

Bacterial pathogens have been attributed to poultry housing structure, financial strength, and incessant use of antibiotics, variable seasons and management systems practiced. Variant forms of bacterial pathogens can be detected by recognizing the molecular pattern of the pathogens through an innate immune mechanism such as mannose-binding lectin. Mannose-binding lectin (MBL) possesses an innate pattern recognition molecule that easily sequestered to region of infections and inflammations. This works by attaching itself to antigen surface thus hinders proliferation and disease activity in the host organism. Baker’s method, nephelometric assays technique, Enzyme-Linked Immunosurbent Assay technique, Polymerase Chain Reaction, Deoxyribonucleic Acid typing and other biotechnology related methods are techniques used in detecting and quantifying MBL. Mannose-binding lectin levels in serum can be influenced by age, management systems, feed formulation strategies and seasons. Therefore, knowledge of MBL should be encouraged in all aspect of poultry production, in order to discourage incessant use of drugs at a slight exposure to prevailing bacterial which can help in maximizing cost.

This study describes the design and implementation of an electronic nose, which was applied to classify and identify hazardous gases generated in underground coal mines. For this purpose, an electrochemical sensor array was used to detect a set of toxic gases. This work illustrates the electronic components of a wireless multisensory system for the toxic gases detection on indoor environments (i.e., underground mines), which was performed with reduced size, low cost and low electrical consumption, in order to detect different compounds using the basic principle of operation of each component to be applied to the target gas. Furthermore, the sample collection, data communication and data processing in real time obtained an excellent performance for gas sensing and even to measure the concentration level of the chemical volatile compounds transmitted from different points of the detection zone. The results demonstrated that using a wireless electronic nose for toxic gases detection was possible to reach a success rate of discrimination of 97%, using principal components analysis (PCA) and Linear Discriminant Analysis (LDA).

In this paper, we propose a new covering-based set in which the lower and the upper approximation operations are defined by neighborhood systems. We discuss this new type of covering-based set systematically in two steps. First, we study the basic properties of this covering-based set, such as the properties of normality, contraction, and monotone. Second, we discuss the relationship between the new type of covering-based set and the other ten sets proposed.

In this paper, we propose a new covering-based set in which the lower and the upper approximation operation are defined by neighborhood systems. We discuss this new type of covering-based set systematically in two steps. First, we study the basic properties of this covering-based set, such as the properties of normality, contraction, and monotone. Second, we discuss the relationship between the new type of covering-based set and the other ten sets proposed.

The mining wastes generated during the last decades in the mining region of Pachuca-Real del Monte in Mexico, still contains silver values of interest. For this reason, the present work is a preliminary study of the leaching kinetics of silver contained in these residues, using as a leaching reagent the thiosemicarbazide-oxygen system, with the aim of proposing this leaching system as a less toxic alternative than cyaniding process. Previous the leaching process, representative samples were wholly characterized, finding 56 g of Ag and 0.6 g of Au per ton. For the kinetic study in the mentioned system, were evaluated the reagent concentration, temperature, partial pressure of oxygen, pH and stirring rate. According the experimental results found, it was observed that [CH5N3S] concentration showed a significant effect on the leaching rate, obtaining a reaction order of n = 0.93, in the range of 20 - 40 mol CH5N3S ⋅ m-3, getting so a silver recovery up to 76.9%. The effect of temperature gave an activation energy of Ea = 45.55 KJ mol-1, which was indicative of a chemical reaction control. Finally, partial pressure of oxygen has a notable effect on leaching rate, but pH and stirring rate have not apparent effect.

The present article is dealing with the state of question about building-energy monitoring systems used for data collection to estimate the Heat Lost Coefficient (HLC) with existing methods and so determinate buildings’ Envelope Energy Performance (EEP). In addition, the data requirements of HLC estimation methods are related with commonly used methods for fault detection, calibration and supervision of energy monitoring systems in buildings. Based on an extended review of experimental tests since 1978, a qualitative and quantitative analysis of Monitoring and Controlling System (MCS) specifications has been carried out. Although most actual Buildings Automation Systems (BAS) may measure the required parameters, further research is still needed to ensure that these data are accurate enough to rigorously apply the HLC estimation methods.

This paper presents a study on the thermal efficiency improvement of the user equipment room in the district heating system based on reinforcement learning [1], and suggests a general method of constructing a learning network(DQN)[2] using deep Q learning[3], which is a reinforcement learning algorithm that does not specify a model. In addition, we introduce the big data platform system and the integrated heat management system for the energy field in the massive data processing from the IoT sensor installed in large number of thermal energy control facilities.

We propose a new Mamdani fuzzy rule-based system in which the fuzzy sets in the antecedents and consequents are assigned in a discrete set of points and approximated by using the extended inverse fuzzy transforms, whose components are calculated by verifying that the dataset is sufficiently dense with respect to the uniform fuzzy partition. We test our system in the problem of spatial analysis consisting in the evaluation of the liveability of residential housings in all the municipalities of the district of Naples (Italy). Comparisons are done with the results obtained by using trapezoidal fuzzy numbers in the fuzzy rules.

Noni juice is a globally popular health beverage that originates from the tropics. Traditional Tahitian healers believe the noni plant to be useful for a wide range of maladies, and noni juice consumers throughout the world have similar perceptions. Nevertheless, human clinical trials are necessary for an understanding of what the health benefits of noni juice truly are. A review of published human intervention studies suggest that noni juice may provide protection against tobacco smoke-induced DNA damage, blood lipid and homocysteine elevation, and systemic inflammation. Human interventions studies also suggest that noni juice may improve joint health, increase physical endurance, increase immune activity, inhibit glycation of proteins, aid weight management, help maintain bone health in women, help maintain normal blood pressure, and improve gum health. Further, these studies point to noni juice possessing notable antioxidant activity, more so than the other fruit juices that served as placebos. It is this antioxidant effect, and its interaction with the immune system and inflammation pathways, that may account for many of the observed health benefits of noni juice. However, the existing evidence does have some limitations in its application to noni juice products in general as all the peer-reviewed human interventions studies to-date have involved only one source of French Polynesian noni juice. Geographical factors and variations in processing methods are known to produce commercial noni juice products with divergent phytochemical and nutrient compositions. Therefore, other sources of noni products may have different toxicological and pharmacological profiles.

Presence and identity of secondary metabolites are two of the main components of lichen taxonomy. Aromatic compounds formed via the acetyl-polymalonate pathway are the most studied lichen substances. In addition, compounds derived from the mevalonic acid pathway (e.g., terpenes and steroids) are sometimes detected in the medulla. However, their identity and value as diagnostic characters in the genus Usnea are yet poorly understood despite the fact that they were mentioned in several taxonomical papers. We conclude that i) aside from the previously recognized polyphenolic compounds, carbohydrates and steroids are also detected in the medulla of some Usnea species; ii) the use of sulfuric anisaldehyde reagent greatly improves the detection of terpenes, carbohydrates and steroids compared with the sulfuric acid reagent routinely used in thin layer chromatography; iii) among carbohydrates, we detected arabitol and sucrose in the medulla; iv) steroids and terpenes remain unidentified and deserve further investigations.

The anti-money laundering (AML) process has failed both in identifying suspicious cases in due time as in assisting the AML analysts in decision making. Starting from a new generic anti-fraud approach, this article presents the main aspects related to the development of a multi-agent system that goes beyond the capture of suspicious transactions, seeking to assist the human expert in the analysis of suspicious behaviour. First, a transactional behavioural profile of clients is obtained in a data mining process. A set of rules, obtained through data mining over a real database, in conjunction with specific rules based on legal aspects and in the expertise of the AML analysts make up the agents' knowledge base. The cases for which the system was unable to suggest a decision are flagged as requiring more detailed analysis. The system analysed 6 months of real transactions and indicated several suspicious profiles, a set of these suspects was investigated by the AML analysts who proved the suspicion of several cases, including some that had not been identified by the systems in execution.

Recently, design of electric scooters (ESs) has commonly adopted brushless DC motors (BLDCMs) in place of brushed DC motors. This invention develops a new anti-lock braking system (ABS), based on a slip-ratio estimator, for ES utilizing the braking force generated by the BLDCM when electrical energy releases to the load yielding an analogous effect of ABS control in gas-engine vehicles. Comparing to mechanical ABS, the design possesses the advantages of rapid torque responses due to fast actuating response. The electrical ABS is realized by associating with kinematic and Short-circuit braking. A current controller is used to adjust the braking force, while the sliding mode control strategy is adopted to regulate the slip ratio for best road adhesion while braking. Real-world experiments have been conducted for functional and performance verification.

This paper focuses on the problem of finite-time stabilization of homogeneous, non-Lipschitz systems with dilations. A key contribution of this paper is the design of a virtual recursive Hölder, non-Lipschitz state feedback which renders the non-Lipschitz systems in the special case dominated by a lower-triangular nonlinear system, finite-time stable. The proof is based on a recursive design algorithm developed recently, to construct the virtual Hölder continuous, finite-time stabilizer as well as a C¹ positive definite and proper Lyapunov function that guarantees finite-time stability of the non-Lipschitz non-linear systems.

Diabetes mellitus (DM) is the most common metabolic disease in humans, and its prevalence is increasing worldwide in parallel with the obesity pandemic. A lack of insulin or insulin resistance, and consequently hyperglycemia, leads to many systemic disorders, among which diabetic encephalopathy (DE) is a long-term complication of the central nervous system (CNS), characterized by cognitive impairment and motor dysfunctions. The role of oxidative stress and neuroinflammation in the pathomechanism of DE has been proven. Fractalkine (CX3CL1) has unique properties as an adhesion molecule and chemoattractant, and by acting on its only receptor, CX3CR1, it regulates the activity of microglia in physiological states and neuroinflammation. Depending on the clinical context, CX3CL1-CX3CR1 signaling may have neuroprotective effects by inhibiting the inflammatory process in microglia or, conversely, maintaining/intensifying inflammation and neurotoxicity. This review discusses the evidence supporting that the CX3CL1-CX3CR1 pair is neuroprotective and other evidence that it is neurotoxic. Interrupting the vicious cycle within neuron-microglia interactions may be a therapeutic goal in DE by limiting the inflammatory response.

Navigation systems are considered as a fast and efficient source of road information to drivers. However, they can distract drivers with more potential accidents on the road. This study examined the effect of navigation systems on driver distraction and visual search while driving in different driving conditions. An eye-tracking system was used to collect visual search data from twenty young drivers while using a driving simulator. Several factors were investigated, including the driving environment (urban and rural), the illumination level (day and night), and the display of the navigation system (large and small) as well as their interactions. Several measures related to eye movements were used in this experiment, including percentage of total Global Positioning System (GPS) fixation duration, average duration of GPS fixation, GPS fixation frequency, the percentage of total dwell duration for the road ahead, the frequency of dwelling on the mirrors and driver’s right and left side windows, and the percentage of dwellings on the mirrors and driver’s right and left side windows. Statistical analysis of the collected data was performed with repeated measures analysis of variance (ANOVA). The experiment revealed that the small GPS display creates more distraction in terms of average gaze duration and total gaze duration. Moreover, daytime driving conditions increase distraction. Regarding the driver’s visual search, the study showed that the visual search area is wider and more spread out during the day, which leads to better driving performance. This study will compare small and large navigation displays to determine which one is more effective in reducing driver distractions, and contribute to understanding driver distraction and visual search while using the navigation system display.

The proposed research methodology aims to design a generally implementable framework for providing a house owner/member with the immediate notification of an on-going theft (unauthorized access to their premises). For this purpose, a rigorous analysis of existing systems was undertaken to identify research gaps. The problems found with existing systems were that they can only identify the intruder after the theft, or cannot distinguish between human and non-human objects. Wireless Sensors Networks (WSNs) combined with the use of Internet of Things (IoT), Cognitive Internet of Things, Internet of Medical Things, and Cloud Computing are expanding smart home concepts and solutions, and their applications. The primary objective of the present research work was to design and develop IoT and cloud computing based smart home solutions. In addition, we also propose a novel smart home anti-theft system that can detect an intruder, even if they have partially/fully hidden their face using clothing, leather, fiber, or plastic materials. The proposed system can also detect an intruder in the dark using a CCTV camera without night vision facility. The fundamental idea was to design a cost-effective and efficient system for an individual to be able to detect any kind of theft in real-time and provide instant notification of the theft to the house owner. The system also promises to implement home security with large video data handling in real-time.

Four discrete models using the exact spectral derivative discretization finite difference (ESDDFD) method are proposed for a chaotic five-dimensional, conformable fractional derivative financial system incorporating ethics and market confidence. Since the system considered was recently studied using the conformable Euler finite difference (CEFD) method and found to be hyperchaotic, and the CEFD method was recently shown to be valid only at fractional index , the source of the hyperchaos is in question. Through numerical experiments, illustration is presented that the hyperchaos previously detected is in part an artifact of the CEFD method as it is absent from the ESDDFD models.

System-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a High Level Architecture (HLA) simulation of 3 networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.

As people grow a custom to effortless outdoor navigation there is a rising demand for similar possibility indoors as well. Unfortunately, indoor localization, being one of the necessary requirements for navigation, continues to be problem without a clear solution. In this article we are proposing a method for an indoor positioning system using a single image. This is made possible using small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with SIFT algorithm we can look through the database and find image which is the most similar to the image taken by user. Pair of images is then used to find coordinates of database image using PnP problem. Furthermore, projection and essential matrices are determined allowing for the user image localization ~ determining the position of the user in indoor environment. Benefits of this approach lies in the single image being the only input from user and no requirements for new onsite infrastructure and thus enables a simpler realization for the building management.

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

This study aims to examine the safety profile of antiepileptic drugs (AEDs) using real-world data, with a focus on neurological, skin, and sexual/reproductive disorders. Data were collected from AED-caused reports in the Korea Adverse Event Reporting System Database (KAERS-DB) from 2012 to 2022. Totally, 46,963 adverse drug reaction (ADR)-drug pairs were analyzed. At the system organ class level, the most frequently reported classes for sodium channel blockers (SCBs) were skin (37.9%), neurological (16.7%), and psychiatric disorders (9.7%). However, for non-SCBs, these were neurological (31.2%), gastrointestinal (22.0%), and psychiatric disorders (18.2%). The most common ADRs induced by SCBs were rash (17.8%), pruritus (8.2%), and dizziness (6.7%). In contrast, non-SCBs induced dizziness (23.7%), somnolence (13.0%), and nausea (6.3%). Among the most commonly reported ADRs, rash, pruritus, and urticaria occurred on average two days later with SCBs compared to non-SCBs. Sexual/reproductive disorders were reported at a frequency of 0.23%. SCBs were reported as the cause more frequently than non-SCBs (59.8% vs. 40.2%, Fisher’s exact test, p&lt;0.0001). Based on real-world data, we identified the safety profiles of AEDs. AED-induced ADRs exhibited different patterns depending on the mechanism. Therefore, it is important to establish different pharmacovigilance strategies to ensure proper monitoring.

Laryngeal squamous cell carcinoma (SCC) is a head and neck cancer (about 5% of all cancers, and up to 95% of laryngeal cancers; more frequent in males than in females, ratio of 3.9/1) with characteristics depending on its location, with glottis, supraglottis, and subglottis being the most frequent. In African Americans, it appears at younger ages and has lower survival rates than in Caucasians, Hispanics, and Asians. Primary risk factors are tobacco and alcohol consumption. Treatments vary based on the site and stage of the tumor and include radiotherapy, transoral laser microsurgery, and surgery, including partial or total laryngectomy. This study aimed to map by immunohistochemistry four members of the Chaperone System (CS), namely Hsp10, Hsp27, Hsp60, and Hsp90, in laryngeal tissue during the progression from healthy stage to full malignancy, passing through dysplasia. The four chaperones increased in the tissues and changed distribution with the progression of carcinogenesis. The findings provide a histopathological platform for launching in-depth analyses of the mechanisms underpinning the role of the four chaperones in the development of squamous cell carcinoma of the larynx. Also, the data indicate that the four chaperones have potential as biomarkers for diagnosis, prognostication, and patient follow-up.

Rice provides ~20% of human dietary energy and, for many people, a similar share of their protein. Rice cultivation, however, produces significant greenhouse gas (GHG) emissions, comparable to those from the aviation sector. The main GHG from rice production is methane, mostly a result of conventional rice cultivation (CRC) keeping rice fields continuously flooded during the crop cycle. There is extensive evidence that alternate wetting and drying (AWD) of rice fields substantially reduces methane emissions. AWD is one component of the System of Rice Intensification (SRI), an agroecological approach to the management of plants, water, soil and nutrients practiced by millions of farmers in both lowland irrigated rice and upland rainfed cultivation. Thirteen countries have included SRI in their Nationally Determined Contributions to GHG reduction or climate change mitigation. This article reviews 16 field studies of the net reduction in GHG emissions from the adoption of AWD, eight from the adoption of SRI, and two that compared SRI and AWD. Where available, the review includes data on yield and therefore on carbon dioxide-equivalent GHG emissions per kilogram of rice produced. The evidence indicates that AWD and SRI offer a similar and substantial reduction (~35–41%) in GHG emissions per hectare compared with conventional rice cultivation. However, SRI offers ~66% greater yield than CRC, and therefore greater reduction in emissions per kilogram of rice, ~54% more than AWD. The limited data directly comparing SRI and AWD support this finding. SRI also appears to have greater potential to sequester carbon in the soil. SRI lowers rice farmers’ costs of production, adds to their income and can make climate-friendly methods more attractive. Both AWD and SRI are greatly preferable to current conventional practices, but SRI offers opportunities to contribute to food security while directly addressing the drivers of climate change.

Malignant melanoma (MM) is the most fatal form of skin cancer, accounting for 90% of all skin cancer deaths. Multiple dysregulated cellular pathways are involved in MM, including the MAPK/ERK and PI3K/PTEN/AKT pathways, which can be targeted with novel targeted inhibitors. However, these blockades can be overcome through the activation of alternative pathways, leading to treatment resistance. The high immunogenicity of MM has been exploited using checkpoint inhibitors resulting in improved survival outcomes of patients with advanced MM. However, their side effect profile and prohibitive cost remain a challenge and the survival outcomes for patients with metastatic MM remain poor. Treatment resistance has been attributed to the presence of cancer stem cells (CSCs), a small subpopulation of pluripotent, highly tumorigenic cells proposed to drive cancer progression, metastasis, and treatment resistance. CSCs reside within the MM tumor microenvironment (TME) regulated by the immune system, and the paracrine renin-angiotensin system (RAS), expressed in many cancer types, including MM. This article reviews the current treatment of advanced MM with targeted therapy and immune checkpoint blockers, highlights the emergence of mRNA vaccine. It also discusses the MM TME and its relationship with CSCs, and the local immune system and the paracrine RAS. It highlights the regulation of the MAPK/ERK and PI3K/AKT/mTOR pathways by the RAS via prorenin receptor and angiotensin II receptor 1, and how this relates to the CSCs and treatment resistance. This underscores the potential multi-modal therapeutic strategy by concurrent targeting of multiple components of the TME.

The smart management of water resources is an increasingly important topic in today's society. In this context, the paradigm of Smart Water Grids (SWGs) aims at a constant monitoring through a network of smart nodes deployed over the water distribution infrastructure. In such a way, a continuous assessment of water quality and state of health of the pipeline infrastructure can be achieved, allowing an early detection of leaks and water contamination. Acoustic wave-based technology has arisen as a viable communication technique among the nodes of the network. Such technology can be suitable to replace traditional wireless networks in SWGs, as the acoustic channel is intrinsically embedded in the water supply network. However, the fluid-filled pipe is one of the most challenging media to be employed for data communication. This paper aims at reviewing those works dealing with acoustic-based communication networks in real large-scale urban water supply networks. An overview on the characteristics, trends and design challenges of existing works is provided as a guideline for future research.

Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of its nodules. Radiologists need support from automated tools for precise opinion. Automated detection of the affected lungs nodule is difficult because of the shape similarity among healthy tissues. Over the years, several expert systems have been developed that help radiologists to diagnose lung cancer. In this article, we propose a framework to precisely detect lungs cancer by classifying it between benign and malignant nodules. The framework is tested using the subset of the publicly available at the Lung Image Database Consortium image collection (LIDC-IDRI). Multiple techniques including filtering and noise removing are applied for pre-processing. Subsequently, the OTSU and the semantic segmentation are used to accurately detect the unhealthy lungs nodules. In total, 13 nodules features were extracted using Principal Components Analysis (PCA) algorithm. Four optimal features are selected based on the classification performance. In the classification phase, 9 different classifiers are used along with two types of validation schemes i.e. train test holdout validation with 70-30 data split and 10 fold cross-validation. Our experiments show that the proposed system provides 99.23\% accuracy using logic boost classifier.

The interest on the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this aim, self--tuning control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Some of the considered methods were already verified on wind turbine systems, and important advantages may thus derive from the appropriate implementation of the same control schemes for hydroelectric plants. This represents the key point of the work, which provides some guidelines on the design and the application of these control strategies to these energy conversion systems. In fact, it seems that investigations related with both wind and hydraulic energies present a reduced number of common aspects, thus leading to little exchange and share of possible common points. This consideration is particularly valid with reference to the more established wind area when compared to hydroelectric systems. In this way, this work recalls the models of wind turbine and hydroelectric system, and investigates the application of different control solutions. The scope is to analyse common points in the control objectives and the achievable results from the application of different solutions. Another important point of this investigation regards the analysis of the exploited benchmark models, their control objectives, and the development of the control solutions. The working conditions of these energy conversion systems will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many installations.

Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications intelligent and more effective. In this paper, we present a comprehensive view on mobile data science and intelligent apps in terms of concepts and AI-based modeling that can be used to design and develop intelligent mobile applications for the betterment of human life in their diverse day-to-day situation. This study also includes the concepts and insights of various AI-powered intelligent apps in several application domains, ranging from personalized recommendation to healthcare services, including COVID-19 pandemic management in recent days. Finally, we highlight several research issues and future directions relevant to our analysis in the area of mobile data science and intelligent apps. Overall, this paper aims to serve as a reference point and guidelines for the mobile application developers as well as the researchers in this domain, particularly from the technical point of view.

In crystal structure prediction, Newton's second law can always be applied to particles (atoms or ions) in a cell to determine their positions. However the values of the period vectors (crystal cell edge vectors) should be determined as well. Here we applied the dynamical equations of period vectors derived recently based on Newton's laws (doi:/10.1139/cjp-2014-0518) for that purpose, where the period vectors are driven by the imbalance between the internal and external pressures/stresses. For equilibrium states, they became equations of state, which essentially turn out the equilibrium conditions of crystals from mechanical point of view. For external pressure, by ignoring some effects, they reduced to the Mie-Gruneisen equation. Since the internal stress has both a full kinetic energy term and a full interaction term, the influences of both external temperature and stress/pressure on crystal structures can be calculated, then thermodynamical properties and processes were presented. Contrary to usual ideas, the equations show that pure harmonic vibrating phonons can result in thermal expansion in crystals when the external temperature is changed. Finally, crystal system collapse due to temperature and/or stress/pressure change was discussed.

This paper bases on panel data from 30 provinces and municipalities in China spanning the period of 2010 to 2021 to examine the evolving mechanisms and influencing factors of agricultural product circulation efficiency in the provinces along the Belt and Road Initiative (BRI) within the context of green total factor productivity (TFP). The study research employs various methodologies including the SBM-DDF model, GML index, system GMM, and global Moran's I index. The findings are as follows: Initially, the provinces along the BRI exhibit an overall negative growth trend in the green TFP of agricultural product circulation, with a noticeable decline observed particularly after the initiation of the BRI in 2014. Secondly, foreign investment levels significantly contribute to the positive enhancement of green TFP in agricultural product circulation among the provinces along the BRI. Eventually, environmental regulations, government support, and the level of international trade in agricultural products exert significant negative impacts. Thirdly, the results of spatial effect tests reveal substantial spatial spillover effects in the green TFP of agricultural product circulation among the provinces along the BRI, as demonstrated through examinations utilizing three distinct spatial matrices.

Background: Mitigating climate change requires fundamentally redesigned energy systems in which renewable energy sources ultimately replace fossil fuels such as natural gas. In this context, the question how and to which extent the gas sector can contribute to an increasingly climate-neutral future EU energy system is heavily debated among scholars, energy industry experts and policy makers. Methods: We take a two-step approach: We begin with a review of studies from energy industry and academia to discuss potential gas sector contributions from a holistic energy system design point of view; this is followed by a comprehensive discussion of technical potentials, micro-economic conditions and societal implications of renewable gas. We then enrich our findings with the results of an empirical focus group process. Results: The gas sector can not only contribute to balancing volatile renewable energy production but also enable the supply of renewable energy to end-users in gaseous form; based on existing infrastructure. This could reduce costs for society, increase public acceptance and ultimately speed up the energy system transformation. There is the theoretical technical potential to substitute major parts of natural gas with renewable gas of biogenic and synthetic nature. This, however, crucially requires a supportive policy framework like the one established for renewable electricity. Conclusion: Given the societal benefits and the competitiveness of renewable gas as compared to renewable alternatives, energy policy makers should incorporate renewable gas and the existing gas infrastructure in the future energy system framework. The objective should be an optimized interplay of various energy vectors and their infrastructure along the entire energy supply chain. This requires a level playing field for different renewable technologies across different policy areas and a form of public support that strikes the balance between facilitating the gradual substitution of natural gas by renewable gas while maintaining public acceptance for this transformation despite higher costs for end-users.: Given the societal benefits and the competitiveness of renewable gas as compared to renewable alternatives, energy policy makers should incorporate renewable gas and the existing gas infrastructure in the future energy system framework. The objective should be an optimized interplay of various energy vectors and their infrastructure along the entire energy supply chain. This requires a level playing field for different renewable technologies across different policy areas and a form of public support that strikes the balance between facilitating the gradual substitution of natural gas by renewable gas while maintaining public acceptance for this transformation despite higher costs for end-users.

Under the action of cement hydration heat, construction environment, thermal insulation measures, and pipe cooling system, the mass concrete pile cap produces a complex temperature field inside the structure, which makes it difficult to control the internal surface temperature difference, the maximum adiabatic temperature rise and the surface temperature of the structure. In this paper, the mass concrete pile cap of a super large bridge (the length, width, and height are 26.40m，20.90m, and 5.00m, respectively, and the central pier pile cap is constructed with concrete with a strength of C40) is taken as the research support project. The controlling factors affecting the temperature field of the mass concrete pile cap are found by comparing the temperature monitoring of the pile cap with the calculated value of finite element software simulation analysis. Through the finite element software Midas Civil and Midas FEA, the control factors affecting the temperature field of the main pier cap (concrete mold temperature, concrete surface convection coefficient, ambient temperature, and pipe cooling system parameters, etc.) are numerically analyzed, and the influence law and influence degree of the control factors are found out.

Individuals diagnosed with systemic arterial hypertension (SAH) are considered risk groups for COVID-19 severity. This study assessed differences in cardiac autonomic function (CAF) and functional capacity (CF) in SAH individuals without COVID-19 infection compared to SAH individuals post-COVID-19. Participants comprised 40 SAH individuals aged 31 to 80 years old, grouped as SAH with COVID-19 (G1; n=21) and SAH without COVID-19 (G2; n=19). CAF was assessed via heart rate variability (HRV), measuring R-R intervals during a 10-minute supine period. Four HRV indices were analyzed through symbolic analysis: 0V%, 1V%, 2LV%, and 2UV%. FC assessment was performed by a 6-minute walk test (6MWT). G1 and G2 showed no difference between significant age, anthropometric, clinical and medication. G2 exhibited superior 6MWT performance, covering more distance (522±78 vs. 465±59 meters, p&lt;0.05). Specifically, G2 demonstrated a moderate, positive correlation between 6MWT and the 2LV% index (r=0.58; p&lt;0.05). Shorter walking distances were observed during 6MWT in SAH individuals post-COVID-19. However, the study did not find impaired cardiac autonomic function in SAH individuals post-COVID-19 compared to those without. This suggests that while COVID-19 impacted FC, CAF remained relatively stable in this population.

Objective: To evaluate the existing meta-analytic evidence of associations between exposure to ultra-processed foods, as defined by the Nova food classification system, and adverse health outcomes. Design: Systematic umbrella review of existing meta-analyses. Data Sources: MEDLINE, PsycINFO, Embase, and the Cochrane Database of Systematic Reviews, as well as manually searching reference lists from 2009 to June 2023. Inclusion Criteria: Systematic reviews and meta-analyses of cohort, case-control, and/or cross-sectional study designs that evaluated the associations between exposure to ultra-processed foods and adverse health outcomes in humans across the lifespan. Results: The search identified 45 unique pooled analyses, including 13 dose-response and 32 non-dose-response associations (n=9,888,373). Overall, direct associations were found between exposure to ultra-processed foods and 32 (71%) health outcome domains spanning cardiometabolic, gastrointestinal, and respiratory conditions, cancer, mental health, and mortality. Based on a pre-specified evidence classification criteria, convincing evidence (Class I) supported direct associations between greater ultra-processed food exposure and higher risks of incident cardiovascular disease-related mortality (RR: 1.50; 95%CIs: 1.37 to 1.63), type two diabetes (dose-response RR: 1.12; 95%CIs: 1.11 to 1.13), and depressive outcomes (HR: 1.21; 95%CIs: 1.16 to 1.28), as well as higher risks of prevalent anxiety outcomes (OR: 1.48; 95%CIs: 1.37 to 1.59) and combined common mental disorder outcomes (OR: 1.53; 95%CIs: 1.43 to 1.63). Highly suggestive (Class II) evidence indicated that greater exposure to ultra-processed foods was directly associated with higher risks of incident all-cause mortality (RR: 1.21; 95%CIs: 1.15 to 1.27), heart disease-related mortality (dose-response HR: 1.66; 95%CIs: 1.51 to 1.84), and type two diabetes (OR: 1.40; 95%CIs: 1.23 to 1.59), together with higher risks of prevalent obesity (OR: 1.55; 95%CIs: 1.36 to 1.77), adverse sleep-related outcomes (OR: 1.41; 95%CIs: 1.24 to 1.60), and wheezing (RR: 1.40; 95%CIs: 1.27 to 1.55). Out of the remaining 34 pooled analyses, 21 were graded as suggestive or weak strength (Class III-IV) and 13 were graded as no evidence (Class V). Using the GRADE framework, 22 pooled analyses were rated as "Low" quality, with 19 rated as "Very Low” and four rated as "Moderate" quality. Conclusions: Higher exposure to ultra-processed food was associated with a greater risk of adverse health outcomes, especially cardiometabolic, common mental disorder, and mortality outcomes. These findings provide a rationale to evaluate the effectiveness of using population-based measures to target and reduce dietary exposure to ultra-processed foods for improved human health. Systematic Review Registration: PROSPERO CRD42023412732.

Current research on smart cities is primarily focused on the area of applicability of information and communication technologies. However, in the context of a multidisciplinary approach, it is also necessary to pay attention to the resilience and converged security of individual infrastructures. Converged security represents a particular security type based on a selected spectrum of certain convergent security types of, assuming the creation of a complementary whole. Considering the outputs of the analysis of security breaches manifestations, this kind of security makes it possible to detect emerging security breaches earlier (still in the symptom stage), thus providing a more efficient and targeted solution suitable for building smart city infrastructure. In its essence, the article refers the practical application of the theoretical principles of converged security presented in the publication to a functional sample, deployed and tested in practical conditions of selected smart city infrastructure protection and resilience. Considering the nature of the practical application, the convergence of a wider spectrum of smart security alarm systems in the context of resilience assessment is defined. In the beginning, the general principles of security/ safety and the need for their convergence are presented. In this context, the mathematical model called Converged Resilience Assessment method is presented for better understanding. Subsequently, PSIM and SIEM systems are described as a technological concept that can be used for resilience assessment. The most beneficial part is the structural, process and functional description of the Converged Security and Information Management System (CSIM) using the concept of smart security alarm systems converged security.

This study examines the effect of a corporate citizenship-oriented high performance work system (CC-oriented HPWS) and the interactive influence of CC-oriented HPWS and person-organization fit (PO fit) on creativity at the individual level. Our analysis of field data collected from 303 employees in two branch companies with a two-phase collection method provides empirical support for our theoretical model. The results indicate that high performance work system (HPWS) reflecting corporate citizenship (CC) correlates positively with individual creativity. In addition, the moderating effect of PO fit is significant in the relationship between CC-oriented HPWS and creativity at the individual level. On this basis, this paper discusses the theoretical and practical implications of these findings for future research.

Apathy in patients with Parkinson's disease (PD) is one of the least studied manifestations of a wide range of neuropsychiatric disorders (PND). The frequency of apathy in PD, according to various researchers, is 17–80%. Structural and neurochemical changes associated with PD are considered as the leading pathophysiological factors of apathy. Possible general pathophysiological mechanisms of apathy and hypokinesia, depression, executive (frontal) cognitive functions, sleep disorders in PD are discussed. The basis of the pathophysiological commonality of apathy, hypokinesia, and executive functions is probably bilateral disturbances in the functional connections of the stratum and dorsolateral, medial parts of the prefrontal cortex. The combination of apathy and depression in PD may be due to dysfunction of the structures of the limbic system and the medial orbital prefrontal cortex responsible for motivational determined behavior. The variability of the relationship between apathy and hypokinesia, depression, cognitive impairments, sleep disorders at different stages of PD may be associated with the phenomenological heterogeneity of apathy.Apathy worsens the quality of life, makes a significant contribution to disorders of both household and social adaptation of PD patients. It is promising to study the possibility of correcting apathy using dopaminergic therapy. Against the background of the appointment of pramipexole (1.5-3.0 mg / day) to 20 patients with PD (middle stage, according to Hen-Yar-2.5) to correct movement disorders after 4-6 weeks of therapy, a statistically significant positive dynamics of apathy were noted. According to the total assessment of the scale of apathy SE Starkstein (AS). As a result of the study, no statistically significant correlation was found between the dynamics of the total apathy indicator and the dynamics of motor symptoms of PD according to the unified rating scale for assessing PD (“Motor functions”), which, we believe, indicates an independent effect of pramipexole therapy in relation to motivational disorders.

The real-time Railway Traffic Management Problem (rtRTMP) is discussed in the field of railway transportation. In this paper, rtRTMP is considered for planning shunting routes based on the use of routing methods on a spatial-temporal graph. An approach and algorithm of Spatial-Temporal Graph formation for rail yard transportation network is proposed. The idea is to construct an undirected loop-free Double Vertex Graph for determining optimal shunting routes consisting of several half-runs for several trains shunting under draw-out tracks capacity constraints. Experimental results on the rail yard simulation model are presented.

This paper develops mathematical models examining possible roles of oxytocin and oxytocin receptors in the development of autism. This is done by demonstrating that mathematical operations on normalized data from the Stanford study (K.J. Parker, 2016), which establishes a correspondence between severity of autism in children and their oxytocin blood levels, generates a graph that is the same as the graph of mathematical operations on a normalized theoretical model for the severity of autism. This procedure establishes the validity of the theoretical model and the significance of oxytocin receptors in autism. A steady-state model follows, explaining the constant baseline concentrations of oxytocin observed in the cerebral spinal fluid and blood in terms of the neuromodulation by oxytocin of oxytocin receptors on the magnocellular neurons that produce oxytocin in nuclei in the hypothalamus. The implications of these models for possible roles of oxytocin and oxytocin receptors in autism is considered for several unrelated conditions that may be associated with autism. These are: oxytocin receptor desensitization and down-regulation as factors during labor in offspring autism development; reductions in the oxytocin receptor numbers in the fixed oxytocin receptor expression that occurs before birth; MAST Immune System disease; and the excess number of dendritic spines from lack of pruning observed in brains of autistic people. Research into the feasibility of generating magnocellular neurons and other neurons from adult stem cells is suggested as a way of doing invitro studies of oxytocin and oxytocin receptors to assess the validity of theories presented in this paper.

Low-complexity ultrasound systems are increasingly desired for wearable point-of-care ultra-sound and massive-channel ultrasound for 3-D matrix imaging. However, the system complexity is closely associated with the imaging capabilities, remaining as a challenge. To resolve this limitation, this study revisits the general structures of analog and digital beamformers and in-troduces a hybrid approach to implement efficient ultrasound systems. The suggested hybrid beamforming takes two stages, where the first analog stage partially beamforms M-channel RF signals to N sum-out data (M-to-N beamforming), and the second digital stage beamforms N partial sums to single final beamformed data (N-to-1 beamforming). Our approach was systematically designed and implemented, which was demonstrated with a customized 64-channel 1-D phased array using a tissue mimicking phantom. The demonstrated results indicate that the analog-digital hybrid beamforming can be applied to any kind of arrays for sophisticated 3-D imaging and tiny wearable ultrasound applications.

The rapid advancements in gene therapy have opened up new possibilities for the treatment of genetic disorders, including Duchenne muscular dystrophy, Thalassemia, cystic fibrosis, Hemophilia, and Familial hypercholesterolemia. The utilization of the clustered regularly interspaced short palindromic repeats (CRISPR) - CRISPR-associated protein (Cas) system has revolutionized the field of gene therapy by enabling precise targeting of genes. In recent years, CRISPR/Cas9 has demonstrated remarkable efficacy in treating cancer and genetic diseases. However, the susceptibility of nucleic acid drugs to degradation by nucleic acid endonucleases, necessitates the development of functional vectors capable of protecting the nucleic acids from enzymatic degradation, while ensuring safety and effectiveness. This review aims to explore the biomedical potential of non-viral vector-explore CRISPR/Cas9 systems for the treatment of genetic diseases. Furthermore, it provides a comprehensive overview of recent research advances in viral and non-viral vector-based gene therapy for genetic disorders, including insights from preclinical and clinical studies. Additionally, the review analyzes the current limitations of these delivery systems and proposes avenues for the development of novel nano-delivery platforms.

Adult neural stem and progenitor cells (NSPCs) contribute to learning, memory, maintenance of homeostasis, energy metabolism and many other essential processes. They are highly heterogeneous populations that require input from a regionally distinct microenvironment including a mix of neurons, oligodendrocytes, astrocytes, ependymal cells, NG2+ glia, vasculature, cerebrospinal fluid (CSF), and others. The diversity of NSPCs is present in all three major parts of the CNS, i.e., the brain, spinal cord, and retina. Intrinsic and extrinsic signals, e.g., neurotrophic and growth factors, master transcription factors, and mechanical properties of the extracellular matrix (ECM), collectively regulate activities and characteristics of NSPCs: quiescence/survival, proliferation, migration, differentiation, and integration. This review discusses the heterogeneous NSPC populations in the normal physiology and highlights their potentials and roles in injured/diseased states for regenerative medicine.

Objectives: Stress urinary incontinence (SUI) negatively affects the quality of life and sexual function in women. This study aimed to evaluate the efficacy of radiofrequency (RF) therapy in reducing SUI symptoms and its impact on sexual function. Methods: Thirty-four women with SUI were enrolled and underwent a single RF treatment session using the Viveve® System (Viveve Medical Inc., USA) with parameters of 90 J/cm² and 220 pulses per hour. Assessments at baseline and 6 months post-treatment included perineal ultrasound and personal interviews to evaluate lower urinary tract symptoms and sexual function. Urodynamic studies, voiding diaries, and questionnaires such as the Female Sexual Function Index (FSFI), Overactive Bladder Symp-tom Score (OABSS), Urogenital Distress Inventory-6 (UDI-6), Incontinence Impact Question-naire-7 (IIQ-7), and International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) measured outcomes. Results: RF therapy significantly improved sexual function, with higher FSFI scores in all domains except pain at 6 months. SUI symptoms were significantly re-duced, as indicated by improved scores on OABSS, UDI-6, IIQ-7, and ICIQ-SF, alongside better voiding diary results. Anatomical changes included reduced bladder neck mobility, decreased vaginal width, and a reduced rotation angle of the proximal urethra. Conclusions: RF therapy is effective and safe for treating mild to moderate SUI and enhances sexual function, potentially due to changes in vaginal topography. These results suggest RF therapy as a viable non-surgical op-tion for managing SUI and improving sexual health.

Integrated landscape approaches (ILA) aim to reconcile multiple, often competing, interests across agriculture, nature conservation, and other land uses. Recognized ILA design principles provide guidance for their implementation, yet application remains challenging, and a strong performance evidence-base is yet to be formed. A comprehensive literature review and focus group discussions with practitioners identified considerable diversity of ILA in actors, temporal, and spatial scales, inter alia. This diversity hampers learning from and steering these integrated planning approaches because of its intractable nature. Therefore, we developed a tool—an ‘ILA mixing board’—to structure the complexity of ILA into selectable and scalable attributes in a replicable way to allow planning, diagnostics, and comparative assessment of ILA. The ILA mixing board tool presents seven qualifiers, each representing a key attribute of ILA design and performance such as project flexibility, inclusiveness of the dialogue, and the centrality of the power distribution. Each qualifier has five (non-normative) outcome indicators that can be registered as present or absent. This process in turn guides planners, evaluators and other participating stakeholders involved in landscape management to diagnose the ILA type, and or its performance. We apply the ILA mixing board as a diagnostic tool to three ILA cases in Nicaragua, Madagascar, and the Congo Basin to show some of the many possible configurations of qualifiers on the mixing board. Overall, the tool allows comparative analyses of the complexity of ILA in a structured and manageable way.

Parkinson-like events are side effects that may persist for an extended period even after drug administration is discontinued. Although these events can be triggered by various drugs, the mechanisms underlying their diverse symptoms remain largely unclear. To investigate this, we used the Japanese Adverse Drug Event Reporting Database, which is maintained by the Phar-maceuticals and Medical Devices Agency, to analyze the risk factors associated with Parkinson-like events along with associated drug trends and characteristics. Our findings indicate that similar to　Parkinson’s disease, age-related differences affect the onset of these events, with older individuals being more susceptible. Hierarchical clustering and principal component analysis revealed that the mechanisms triggering these Parkinson-like events are consistent across reports, suggesting a common underlying cause. However, even with a consistent mechanism, side effects can vary depending on the site of action. These insights underline the importance of swift identification of the drugs suspected of causing these events and implementation of measures to reduce their side effects.

Agriculture is the backbone of Kenya’s economy, supporting up to 80% of the rural livelihoods. Kenya’s export horticulture is currently the leading Agriculture subsector in Kenya has evolved from small-holder farming to agro-industrial large-scale export farming dominated by multinational companies. It is regarded as an agro-industrial food system based on the economies of scale producing for mass markets outside of the production area. Much of the food consumed from this food system has undergone multiple transformations and been subject to a host of formal and informal insitutions (rules, regulations, standards, norms and values). An Anthropological study of export horticulture in Northwest Mount Kenya was carried out utilizing qualitative data collection methods in Northwest Mount Kenya region. Data was coded and analysed thematically based on grounded theory approach. The study described the institutional settings of export horticulture from an emic perspective as changing and defining the operations of the food system access and management of common pool resources, namely water and land. With the agro-industrial food system competing for these scarce resources in a semi-arid zone, there is potential for conflict and also reduced production and overall benefits to the different actors in the study area.

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol stands as a cornerstone in modern aviation surveillance and Aircraft Traffic Control systems, integral to the NextGen project initiated by the US Department of Federal Aviation Administration (FAA) in 2005. ADS-B utilizes data links to autonomously broadcast Aircraft navigational and identification information to augment air transportation system capacity and safety. However, concerns regarding the protocol's security persist, particularly as its adoption expands. The unencrypted nature of transmitted aircraft data and the absence of robust authentication mechanisms render the protocol susceptible to exploitation by malicious actors. In this study, we comprehensively reviewed existing research in the field, identifying a crucial gap necessitating a holistic survey. Prior surveys have predominantly focused on specific aspects, such as vulnerabilities, attacks, or critiques of existing solutions. Our survey addresses this gap by thoroughly exploring the aviation system, providing readers with a nuanced understanding of ADS-B security. Utilizing a detailed SWOT analysis diagram, our paper delves into the vulnerabilities inherent in the ADS-B protocol outlines potential threats and scrutinizes various attack scenarios. We systematically categorize and analyze existing security solutions, considering cost-effectiveness, scalability, implementation complexity, and coverage against diverse attack vectors. Furthermore, we critically evaluate these solutions, elucidate ADS-B security requirements, discuss current challenges, and propose future research directions. This survey serves as a comprehensive resource for researchers and practitioners alike, shedding light on the multifaceted landscape of ADS-B security and paving the way for enhanced aviation system resilience in the face of evolving cybersecurity threats.

Nano-drugs and nano-delivery systems are rapidly evolving, with new strategies emerging in the current practices. The evolution of these technologies began with modifying the chemical structure, progressing to supramolecular ionic complexes, and culminating in elegant ad hoc delivery systems. Nanoparticles have numerous benefits as a carrier system for delivering therapeutic agents to intra-arterial sites. These benefits include their subcellular size, targeted surfaces, good suspensibility, and uniform dispersity, making them an ideal choice for catheter-based delivery. Despite the advancements made in the field of nano-drugs and nano-delivery systems, there are still some hurdles to overcome in terms of their commercial availability.The current review presents an updated summary of recent advancements in nano-drugs and nano-delivery systems, including their commercial availability. We aim to discuss the present challenges and prospects of commercially available nano-drugs and nano-delivery systems. Here, we provide a precise and informative overview of the current state of these technologies and underscore the potential they hold for future developments. Further, we have categorized commercially available modifications, name, parent company and their main applications in nano-drugs.

Hydro generator sets serve as the peak and frequency regulation of the power system,and play a very important role in maintaining system stability and improving power quality.Based on the internal characteristics model of a specific type of hydro generator,this paper constructs a hydroelectric coupling model for hydropower units,studies the influence of the regulation system of hydropower units on low-frequency oscillations under different load conditions,and adopts variable speed reaching law and fuzzy sliding mode control strategy to improve the regulation quality of the system and ensure the stable operation of the units.Results of simulation and water turbine set under different load conditions show that varible speed reaching law can effectively improve the power-angle oscillation behavior of the hydropower set and suppress the occurrence of low-frequency oscillations of the system when the system is subject to power disturbance,which provide a new theoretical basis and solution for the vibration analysis and control optimization of hydraulic turbine units.

Color can direct visual attention to specific locations through bottom-up and top-down mechanisms. Using Continuous Flash Suppression (CFS) as way to investigate the factors that gate access to consciousness, the current study investigated whether color also directly affected the timing of conscious perception. Low or high spatial frequency (SF) gratings with different orientations were shown as targets to the non-dominant eye of human participants. CFS patterns were presented at a rate of 10Hz to the dominant eye to delay conscious perception of the targets, and participants had the task to report the target’s orientation as soon as they could see it. With low-SF targets, two types of color-based effects became evident. First, when the targets and the CFS patterns had different colors, the targets entered consciousness faster than in trials where the targets and CFS patterns had the same color. Second, when participants searched for a specific target color, targets that matched these search settings entered consciousness faster compared to conditions where the target color was irrelevant and could vary from trial to trial. Thus, the current study demonstrates that color is a central feature of human perception and leads to faster conscious perception of visual stimuli through bottom-up and top-down attentional mechanisms.

The interest on the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this aim, data--driven control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Some of the considered methods, such as fuzzy and adaptive self--tuning controllers, were already verified on wind turbine systems, and similar advantages may thus derive from their appropriate implementation and application to hydroelectric plants. These issues represent the key features of the work, which provides some guidelines on the design and the application of these control strategies to these energy conversion systems. The working conditions of these systems will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many installations.

Cyber-physical Systems involve the creation, continuous updating and monitoring of virtual replicas that closely mirror their physical counterparts. These virtual representations are fed by real-time data from sensors, Internet of Things (IoT) devices and other sources, enabling a dynamic and accurate reflection of the state of the physical system. This emphasizes the importance of data synchronization, visualization and interaction within virtual environments as a means to improve decision-making, training, maintenance and overall operational efficiency. This paper presents a novel approach to a cyber-physical system to harness the power of Industry 4.0, Digital Twin technology, Virtual Reality (VR) and 3D SCADA in the context of monitoring and optimizing an olive mill. In conclusion, this paper presents a methodology that leverages digital twins and virtual reality to create an immersive, data-driven simulation and monitoring system for an olive mill. The proposed CPS takes data from the physical environment through the existing sensors and measurement elements in the olive mill, concentrates them and exposes them to the virtual environment through the Open Platform Communication United Architecture (OPC-UA) protocol, thus establishing a bidirectional and real-time communication. Furthermore, in the proposed virtual environment, the digital twin is interfaced with the 3D SCADA system, allowing it to create virtual models of the process. This innovative approach has the potential to revolutionize the olive oil industry by improving operational efficiency, product quality and sustainability, while optimizing maintenance practices.

The Food Boost Challenge (FBC) was developed using a participatory action research approach to enhance healthy eating behaviors, here vegetable and fruit products (V&amp;F-products) among adolescents, particularly those with lower education levels. FBC is a quadruple helix innovation process, involving adolescents, (peer)researchers, and food system partners of non-governmental and commercial organizations. In 2021-2022, 34 partners provided both cash and in-kind contributions to join the FBC-community. Phase 1 involved 200 students identifying barriers and drivers for consumption of F&amp;V-products among 1000 pre-vocational adolescents, aged 12-20 years. In phase 2, student teams submitted innovative ideas, resulting in 25 concepts fitting into ≥1 of 4 routes: I) innovative technology for a healthy diet, II) new food products/concepts for adolescents, III) hotspots improving F&amp;V-product experience, and IV) new routes to market. In phase 3 consortia of adolescents, students and partners were formed to develop 10 selected concepts into prototypes, and phase 4 offered teams a national platform. Results show FBC resonates with all stakeholders, generating valuable insights to increase F&amp;V-intake. Prototypes in all 4 routes have been developed, with some already in the implementation stage. Additionally, other regions in the Netherlands have adopted the FBC approach. Overall, FBC is an approach that transforms ideas into actionable measures and shows potential to be adapted to promote various healthy eating behaviors among school students.

Manufacturing environments, characterized by rapid, unpredictable changes, uncertainties, risks, and uncontrollable fluctuations, pose significant challenges to minimizing disruptions in processes. This study introduces an innovative approach that prioritizes curbing risk propagation among processes to enhance robustness. It emphasizes the integration of engineering management principles and modular design within manufacturing. Adopting a system engineering perspective, all manufacturing process activities are viewed as interrelated components within a unified system. By employing Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, manufacturing process architecture is modularized, yielding heightened robustness. The proposed mathematical model equips engineering and manufacturing managers with a potent tool for designing robust processes while adeptly managing system complexity. The study's outcomes underscore a substantial enhancement in modularization, leading to elevated overall robustness in manufacturing processes. To validate the methodology, the architectural design of manufacturing processes is examined in a real-case scenario, specifically the Barez Industrial Group in Iran. This verification substantiates the 'manufacturing processes' of the case, presenting an optimally modularized architecture. The results affirm the proposed approach's efficacy, demonstrating improved modularization that contributes to bolstered robustness in manufacturing processes.

Foundational and state-of-the-art anomaly detection methods through power system state estimation are reviewed. The traditional components for bad data detection such as chi-square testing, residual-based methods, and hypothesis testing are discussed to explain the motivations for recent anomaly detection methods given the increasing complexity of power grids, energy management systems, and cyber-threats. In particular, state estimation anomaly detection based on data-driven quickest change detection and artificial intelligence are discussed and directions for research are suggested with particular emphasis on considerations of the future smart grid.

Structural Units (SU) is a novel unit system, proposed as compatible to the International System of Units (SI), rooted in Spacetime Structure. Unlike SI, which evolved over history without a fixed reference frame, SU defines one Structural Unit as the space and time between two vertices in the Spacetime Structure. This perspective offers a unique viewpoint, where space and time units are proportionate. This correlation results in Natural constants being expressible through algebraic relationships involving the pure numbers π, φ (the Golden ratio), and α (the Fine Structure constant), not only simplifying Fundamental constants but also introducing a harmonious integration of geometric concepts. In contrast, SI currently relies on fixed values for seven constants derived from CODATA. It's crucial for Structural Units to seamlessly integrate with the existing International System of Units, proposing a theoretical framework, hitherto nonexistent, for the values of the various Fundamental Constants that have been experimentally obtained in our scientific endeavor. To ensure compatibility, the four Planck Units, (length, mass, time, and temperature), introduced by Max Planck in 1899, will be recalculated in SU and then converted back to SI using dimensional analysis. Additionally, to further validate this compatibility, we will examine the Schwarzschild radius from Relativity, the photon energy from Quantum Mechanics, and propose a new interpretation of the Uncertainty Principle under the SU framework. This potential harmonization of geometry and Natural constants in SU could offer a deeper understanding of the inherent order in the fabric of the Universe.

Many systems in the manufacturing industry have spatial distribution characteristics, which correlate with both time and space. Such systems are known as distributed parameter systems (DPS). Due to the spatiotemporal coupling characteristics, the modeling of such systems is quite complex. The paper presents a new approach for three-dimensional fuzzy modeling using Simultaneous Perturbation Stochastic Approximation (SPSA) for nonlinear DPS. The Affinity Propagation clustering approach is utilized to dynamically determine the optimal number of fuzzy rules and construct a collection of preceding components for three-dimensional fuzzy models. Fourier space base functions are used in the resulting components of three-dimensional fuzzy models, and their parameters are learned by the SPSA algorithm. The proposed three-dimensional fuzzy modeling technique was utilized on a conventional DPS within the semiconductor manufacturing industry, with the simulation experiments confirming its efficacy.

The Klaten Regency, Central Java Province, Indonesia is an leptospirosis endemic area. This study’s purpose is to spatially describe the abiotic and biotic environmental factors with the Leptospirosis incidence in the Klaten Regency in 2018. This was a descriptive observational with cross-sectional approach conducted in the Klaten Regency, Central Java, in 2019 with 59 respondents. The results revealed that the percentage of abiotic environment factors such as poor waste disposal facilities, poor gutter conditions, river <200 meters, and flooding history, namely 35.6%; 41.2%; 54.2%; and 6.8%, respectively. The highest leptospirosis cases occurred in April 2018 with 325 mm of rainfall, average temperature of 270C, average humidity of 82.3%, and altitude of 100-200 MASL (79.7%). Meanwhile, biotic factors included rat nest existence (100%), having pets at risk (32.2%), and ≥3 types of vegetation (79.7%). In conclusion, most respondents' dominant environmental factors were presence of rat nests, ≥3 vegetation types, and river availability <200 meters.

Good Boussinesq equations will be considered in this work. First we apply three combined compact schemes to approximate spatial derivatives of good Boussinesq equations. Then three fully discrete schemes are developed based on symplectic scheme in time direction, which are sympletic-structure preserving.Meanwhile, the convergence and conservation of the fully discrete schemes are analyzed. Finally, we present numerical experiments to confirm our theoretical analysis. Both our analysis and numerical test indicate that the fully discrete schemes are efficient in solving the spatial derivative mixed equation.

A processual texture lies at the core of phenomena that undergo change. Philosophers have observed the incessant becoming of our world from antiquity to the present day, but an explanation must still be found in terms of contemporary metaphysics. This article strives to bring the focus on the domain of possibles, an under-theorised philosophical issue that dwells in the ontological realm between the possibility and its actual realization. Sketching a more comprehensive concept of the possible unravelling the thread of its main meanings, the process of change will be not simply clarified from inside, but also understood as an activator of reality. Finally, the discussion will argue for a principle of prudence and responsibility derived from an ontological basis.

Integrated energy systems (IES) seek to minimize power generating costs in future power grids through the dynamic coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, i.e., even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear of components. If a unit is flexibly operated without respecting limits on materials and components, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the limits on power variations (explicit constraints), the solution of the unit dispatch problem needs to meet the limits on temperature, pressure and flow rate variations (implicit constraints). The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher-validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., Balance of Plant, Gas Turbine, High-Temperature Steam Electrolysis. Finally, FARM module provides dedicated tools for visualizing the response of the process variables of interest during operation transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an Ecological Interface Design (EID) for IES units.