Survivors of severe brain injury may require care in a neurointensive care unit (neuro-ICU), where the brain is vulnerable to secondary brain injury. Thus, there is a need for noninvasive, bedside, continuous cerebral blood flow monitoring approaches in the neuro-ICU. Our goal is to address this need through combined measurements of EEG and functional optical spectroscopy (EEG-Optical) instrumentation and analysis to provide a complementary fusion of data about brain activity and function. The present case demonstrates in a patient with traumatic brain injury, noninvasive cerebral blood flow transients can be recorded that correlate with gold-standard invasive measurements and with the frequency content changes in the EEG data during clinical care.

Wearable and mobile technology has advanced in leaps and bounds in the last decade with technological advances creating a role from enhancing healthy living to monitoring and treating disease. However, the discussion about the ethical use of such commercial technology in the community, especially in minors, is lacking behind. In this paper, we first summarize the major ethical concerns that arise from the usage of commercially available wearable technology in children, with a focus on smart watches, highlighting issues around the consent process, mitigation of risk and potential confidentiality and privacy issues, as well as the potential for therapeutic misconceptions when used without medical advice. Then through a relevant thought experiment we move on to outline some further ethical concerns that are connected to the use of wearables by minors, to wit the issue of informed consent in the case of minors, forcing them to live in the spotlight, and compromising their right to an open future. We conclude with the view that mitigating potential pitfalls and enhancing the benefits of wearable technology especially for minors requires brave and comprehensive moral debates.

This study presents a methodology to reveal traces of viral particles, as aerosol with known chemical and molecular structure, in a sample by means of photon and electron interactions. The method is based on Monte Carlo simulations and on the analysis of photon-electron fluxes-spectra through energy channels counts as a function of different aerosol viral concentrations in the air sample and looking at the peculiar photon/electron interactions with the potential abnormal atomic hydrogen (H), oxygen (O), carbon (C), and phosphorus (P) compositions present in the air sample as a function of living and nonliving matter with PO4 group RNA/DNA strands in a cluster configuration.

COVID-19 is characterized by an unprecedented abrupt increase in the viral transmission rate (SARS-CoV-2) relative to its pandemic evolutionary ancestor, SARS-CoV (2003). The complex molecular cascade of events related to the viral pathogenicity is triggered by the Spike protein upon interacting with the ACE2 receptor on human lung cells through its receptor binding domain (RBD_Spike). One potential therapeutic strategy to combat COVID-19 could thus be limiting the infection by blocking this key interaction. In this current study, we adopt a protein design approach to predict and propose non-virulent structural mimics of the RBD_Spike which can potentially serve as its competitive inhibitors in binding to ACE2. The RBD_Spike is an independently foldable protein domain, resilient to conformational changes upon mutations and therefore an attractive target for strategic re-design. Interestingly, in spite of displaying an optimal shape fit between their interacting surfaces (attributed to a consequently high mutual affinity), the RBD_Spike–ACE2 interaction appears to have a quasi-stable character due to a poor electrostatic match at their interface. Structural analyses of homologous protein complexes reveal that the ACE2 binding site of RBD_Spike has an unusually high degree of solvent-exposed hydrophobic residues, attributed to key evolutionary changes, making it inherently ‘reaction-prone’. The designed mimics aimed to block the viral entry by occupying the available binding sites on ACE2, are tested to have signatures of stable high-affinity binding with ACE2 (cross-validated by appropriate free energy estimates), overriding the native quasi-stable feature. The results show the apt of directly adapting natural examples in rational protein design, wherein, homology-based threading coupled with strategic ‘hydrophobic ↔ polar’ mutations serve as a potential breakthrough.

The COVID-19 infections in Pakistan are spreading at an exponential rate and a point may soon be reached where rigorous prevention measures would need to be adopted. Mathematical models can help define the scale of an epidemic and the rate at which an infection can spread in a community. I used ARIMA Model, Diffusion Model, SIRD Model and Prophet Model to forecast the magnitude of the COVID-19 pandemic in Pakistan and compared the numbers with the reported cases on the national database. Results depicts that Pakistan could hit peak number of infectious cases between June 2020 and July, 2020.

The study investigates the determinants of mobile Internet banking adoption among Gen-Y in Malaysia. Align the issue of the study and research objectives, and the study underpinned Technology Acceptance Model (TAM) as the main guideline or a blueprint to analyze the research model. The study applied survey research design and analyzed using Structural Equation Modelling (SEM) under the PLS-SEM technique with SmartPLS 2.0. A total of 358 mobile internet banking users in Malaysia were random proportional selected as respondents and analyzed. Results from the partial least square structural equation modeling (PLS-SEM) revealed that perceived ease of use, perceived usefulness, facilitating condition, and personal innovativeness in IT have significantly influenced the attitude of mobile internet banking adoption in Malaysia. Additionally, perceived ease of use and facilitating conditions found to have a significant influence on the perceived usefulness of Mobile Internet Banking. Lastly, facilitating conditions and personal innovativeness in IT are significantly influence the perceived ease of use of mobile internet banking among Gen-Y in Malaysia

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

We compare Chiral Perturbation Theory (ChPT) and the Linear Sigma Model (LSM) as realizations of low energy QCD for light mesons in a chirally imbalanced medium. The relations between the low-energy constants of the Chiral Lagrangian and the corresponding constants of the Linear Sigma Model are established as well as the expressions for the decay constant of $\pi $-meson in the medium and for the mass of the $a_0$. In the large $N_c$ count taken from QCD the correspondence of ChPT and LSM is remarkably good and give a solid ground for search of chiral imbalance manifestation in pion physics. A possible experimental detection of chiral imbalance (and therefore a phase with Local Parity Breaking) is outlined in the charged pion decays inside the fireball.

Recently, several research groups have reported on anomalous enhancement of the self-field critical currents, Ic(sf,T), at low temperatures in superconductor/Dirac-cone material/superconductor (S/DCM/S) junctions. Some papers attributed the enhancement to the low-energy Andreev bound states arising from winding of the electronic wave function around DCM. In this paper, Ic(sf,T) in S/DCM/S junctions have been analyzed by two approaches: modified Ambegaokar-Baratoff and ballistic Titov-Beenakker models. It is shown that the ballistic model is an inadequate tool to analyze experimental data from S/DCM/S junctions. The primary mechanism for limiting superconducting current in S/DCM/S junctions is different from the conventional view that the latter is the maximum value within the order parameter phase variation. Thus, there is a need to develop a new model for self-field critical currents in S/DCM/S systems.

The research objectives was to determine the plants vegetation profile in forest revegetation and Mount Arjuna springs. The method used was descriptive method. While based on the techniques and tools used to research, the author uses the survey method to obtain facts that occur in the research area, namely in the area around the springs of Arjuna mount, Pasuruan, East Java, Indonesia. Data obtained in the field are then processed and analyzed using GIS, ArcView 3.3 and Google Earth programs. The results of the study explain the profile of plant vegetation, namely plant stratification, bird wealth, taxonomic wealth and plant density have a significant effect on forest revegetation and springs in Arjuna mount. The forest vegetation profile has a positive and significant effect on the preservation of springs. The better the profile of forest vegetation, the preservation of springs will be better, and vice versa.

The theory of the continuous two-dimensional (2D) Fourier Transform in polar coordinates has been recently developed but no discrete counterpart exists to date. In the first part of this two-paper series, we proposed and evaluated the theory of the 2D discrete Fourier Transform (DFT) in polar coordinates. The theory of the actual manipulated quantities was shown, including the standard set of shift, modulation, multiplication, and convolution rules. In this second part of the series, we address the computational aspects of the 2D DFT in polar coordinates. Specifically, we demonstrate how the decomposition of the 2D DFT as a DFT, Discrete Hankel Transform (DHT) and inverse DFT sequence can be exploited for efficient code. We also demonstrate how the proposed 2D DFT can be used to approximate the continuous forward and inverse Fourier transform in polar coordinates in the same manner that the 1D DFT can be used to approximate its continuous counterpart.

The theory of the continuous two-dimensional (2D) Fourier Transform in polar coordinates has been recently developed but no discrete counterpart exists to date. In this paper, we propose and evaluate the theory of the 2D discrete Fourier Transform (DFT) in polar coordinates. This discrete theory is shown to arise from discretization schemes that have been previously employed with the 1D DFT and the discrete Hankel Transform (DHT). The proposed transform possesses orthogonality properties, which leads to invertibility of the transform. In the first part of this two-part paper, the theory of the actual manipulated quantities is shown, including the standard set of shift, modulation, multiplication, and convolution rules. Parseval and modified Parseval relationships are shown, depending on which choice of kernel is used. Similar to its continuous counterpart, the 2D DFT in polar coordinates is shown to consist of a 1D DFT, DHT and 1D inverse DFT.

Recently, Kayyalha et al. (Phys. Rev. Lett., 2019, 122, 047003) reported on anomalous enhancement of the self-field critical currents, I_c (sf,T), at low temperatures in Nb/BiSbTeSe₂-nanoribbon/Nb Josephson junctions. The enhancement was attributed to the low-energy Andreev bound states arising from winding of the electronic wave function around the circumference of the topological insulator BiSbTeSe₂ nanoribbon. In this paper, we show that identical enhancement in I_c(sf,T) and in the upper critical field, B_c2(T), at approximately same reduced temperatures, were reported by several research groups in atomically thin junctions based on a variety of Dirac-cone materials (DCM) earlier. Our analysis shows that in all these S/DCM/S systems the enhancement is due to a new superconducting band opening. Taking in account that several intrinsic superconductors also exhibit the effect of new superconducting band(s) opening when sample thickness becomes thinner than the out-of-plane coherence length, we strength our previous proposal that there is a new phenomenon of additional superconducting band(s) opening in atomically thin films.

In this paper, we present a comprehensive 4D study of the early stage of plastic deformation in a polycrystalline binary AlLi alloy. The entire microstructure is mapped with X-ray diffraction contrast tomography and a set of bulk grains is further studied via X-ray topotomography during mechanical loading. The observed contrast is analyzed with respect to the slip system activation and the evolution of the orientation spread is measured as a function of applied strain. The experimental observations are augmented by the mechanical response predicted by crystal plasticity finite element simulations to analyze the onset of plasticity in details. Simulation results show a general agreement of the individual slip system activation during loading and that comparison with experiments at the length scale of the grains may be used to fine tune the constitutive model parameters.

This work communicates a review on Balmer series hydrogen beta line measurements and applications for analysis of white dwarf stars. Laser-induced plasma investigations explore electron density and temperature ranges comparable to white dwarf star signatures such as Sirius B, the companion to the brightest star observable from the earth. Spectral line shape characteristics of the hydrogen beta line include width, peak separation, and central dip-shift, thereby providing three indicators for electron density measurements. The hydrogen alpha line shows two primary line-profile parameters for electron density determination, namely, width and shift. Both Boltzmann plot and line-to-continuum ratios yield temperature. The line-shifts recorded with temporally- and spatially- resolved optical emission spectroscopy of hydrogen plasma in laboratory settings can be larger than gravitational redshifts that occur in absorption spectra from radiating white dwarfs. Published astrophysical spectra display significantly diminished Stark or pressure broadening contributions to red-shifted atomic lines. Gravitational redshifts allow one to assess the ratio of mass and radius of these stars, and subsequently, the mass from cooling models.

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

The sustainable development of our world has gain particular attention of a wide range of decisional factors, civil society, business sector, and scientific community, seeing that the prosperity of people and society is possible with the aid of sustained and inclusive economic growth of all countries and regions. Educational environment has a decisive impact on changes in the way that societies are coping with national, regional, and global challenges and opportunities brought by sustainable development. Looking at the implications of HE on the progress of society, the paper addressed the lack of HE institutional capacity to integrate the principles and practices of sustainable development into all aspects of education and learning. The scope of research problem was bounded on the capability of HEI as organization and school to act as entrepreneurial university by combining the scope of its responsibility within the value chain through a practical and effective mechanism needed to align the strategy with sustainable development goals (SDGs). Embarking on the path of SDGs requires HEI to design, launch, implement, and customize specific processes architectures to govern the advance of sustainability approach. The authors applied the process scoping diagram to capture and conceptualize the educational model needed to guide the HEI through the process of change to embrace sustainability into organizational culture and daily operations. It has been used the SIPOC method (Supplier, Input, Process, Output, Customer) with Visio software tool to articulate processes relationships embedded in the educational model of HEI. The benefits relied on the organized view of the work processes needed to be performed to incorporate SDGs into the strategy of any entrepreneurial HEI. Finally, the authors shared their views on the scalability of the model which may be customized and harmonized in accordance with different HE circumstances and priorities. Implementing the proposed educational model requires long-term institutional commitment, transparency, continuous performance improvement, and communicating the strategy for SDGs and its achievements to wider stakeholders.

In this paper the authors describe the architecture of a multidisciplinary data acquisition and visualization platform devoted to the management of coastal environments. The platform integrates heterogeneous data acquisition sub-systems that can be roughly divided in two main categories: remote sensing systems and in-situ sensing systems. Remote sensing solutions include aerial and underwater remote data acquisition while in-situ sensing solutions include the use of RFID tracers, Wireless Sensor Networks and imaging techniques. All the data collected by these subsystems are stored, integrated and fused on a single platform that is also in charge of data visualization. This last task is carried out according to the paradigm of Augmented Virtuality which foresees the augmentation of a virtually reconstructed environment with data collected in the real world. The described solution proposes a novel holistic approach where different disciplines concur, with different data acquisition techniques, to a large scale definition of coastal dynamics, in order to better describe and face the coastal erosion phenomenon. The overall framework has been conceived by the so-called Team COSTE, a joint research team between the Universities of Pisa, Siena and Florence.

In this paper we present the measurement of charged pion two-particle femtoscopic correlation functions in $\sqrt{S_{NN}}$= 200 GeV Au+Au collisions, in 31 average transverse mass bins, separately for positive and negative pion pairs. Lévy-shaped source distributions yield a statistically acceptable description of the measured correlation functions, with three physical parameters: correlation strength parameter λ , Lévy index α and Lévy scale parameter R. The transverse mass dependence of these Lévy parameters is then investigated. Their physical interpretation is also discussed, and the appearance of a new scaling variable is observed.

In this paper, an in-wheel vibration absorber for In-wheel-motor electric vehicle (IWM EV) is designed, and a comprehensive control strategy of in-wheel absorber and vehicle suspension is proposed to improve vehicle ride comfort. The proposed in-wheel vibration absorber, designed for suppressing the motor vibration, is composed of a spring and a controllable damper. The values of in-wheel spring stiffness and damper initial coefficient are determined by using the improved particle swarm optimization (IPSO) algorithm, which is carried on the typical driving condition. To deal with the negative interaction effects between vehicle suspension and in-wheel absorber, the linear quadratic regulator (LQR) algorithm is utilized to control suspension damper, and the fuzzy PID method is utilized to control in-wheel damper. Based on the four evaluation indexes including vehicle body vertical acceleration, suspension dynamic deflection, wheel dynamic load and motor wallop, the simulation results show that, the proposed LQR control of suspension effectively improves vehicle ride comfort, and the fuzzy PID control of in-wheel damper exhibits superior performance of motor vibration suppressing in comparison to conventional electric wheel.

This paper presents a methodology for determining the sensitivity of the main air flow directions in ventilation subnetworks to changes of aerodynamic resistance and of air density in mine workings. Formulae for determination of the sensitivity of the main subnetwork air flows by establishing the degree of dependency of the air volume stream in a given working on the variations in resistance or air density of other workings of the network have been developed. They have been implemented in the VentGraph mine ventilation network simulator. This software, widely used in Polish collieries provides an extended possibility to predict the process of ventilation, air distribution and, in the case of underground fire, also the spread of combustion gasses. The new method facilitates assessment by mine ventilation services of the stability of ventilation systems in exploitation areas and determine of the sensitivity of the main subnetwork air flow directions to changes of aerodynamic resistance and air density. Recently in some Polish collieries new longwalls are developed in seams located deeper then the bottom of the intake shaft. Such solution is called “exploitation below the level of access” or “sublevel”. The new approach may be applied to such developments to assess the potential of changes of direction and air flow rates. In addition, interpretation of the developed sensitivity indicator is presented. While analyzing air distributions for sublevel exploitation, application of current numerical models for calculations of the distribution results in tangible benefits, such as the evaluation of the safety or risk levels for such exploitation. Application of the VentGraph computer program, and particularly the module POŻAR (fire) with the newly developed options, enables an additional approach to the sensitivity indicator in evaluating air flow safety levels for the risks present during exploitation below the level of the intake shaft. The analyses performed and examples presented enabled useful conclusions in mining practice to be drawn.

The understanding of various health-oriented vital sign data generated from body sensor networks (BSN) and discovery of the association between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where the occupants’ health status is continuously monitored remotely, it is essential to provide required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach to mine the incomplete (partial) periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce the productive-associated partial periodic frequent patterns as the set of correlated partial periodical frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients for quality of diagnosis, and also for better treatment and smart care, especially for the elderly people at smart home. We developed an efficient algorithm named PPFP-Growth (Productive Periodic Frequent Pattern growth) to discover all productive associated partial periodic patterns using these measures. PPFP-Growth is efficient, and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-Growth algorithm, and can filter a huge number of partial periodic patterns to reveal only the correlated ones.

Early in the middle of the 1800s. Up until about 1900, the automotive land speed record 1 was held by an electrical vehicle. Unfortunately, internal combustion engine vehicles did not do 2 well in the market due to their high cost, limited speed, and short range in the 20th century, which 3 resulted in a global fall in their use as private motor vehicles. Since there are no fuel emissions into 4 the environment, there are important uses for electrical vehicles, Electric cars, or EVs, have a closed 5 circuit, cheap operating costs, no maintenance requirements, and excellent performance. The goal 6 of this project is to assess the current state of electric vehicles and the issues surrounding the global 7 advancement of electric vehicle technology. Because of the changing climate.8

The war to technology and economic power have been the driver for industrialization in most developed countries. The first industrial revolution (industry 1.0) earned millions for textile mill owners while the second industrial revolution (industry 2.0) opened the way for tycoons and captains of industry like John D. Rockefeller, J.P. Morgan and Henry Ford. The third industrial revolution (industry 3.0) engendered technology giants like Apple and Microsoft, and made magnates of men like Steve Jobs and Bill Gates. Now, the race for the fourth industrial revolution (industry 4.0) is on and there is no option, every country whether developed or developing must participate. Many countries have positively responded to industry 4.0 by developing strategic initiatives to strengthen industry 4.0 implementation. Unlocking the country’s potential to industry 4.0 has been of interest to researchers in the recent past. However, the extent to which industry 4.0 initiatives being launched globally has never been revealed. Therefore, the present study aimed at exploring industry 4.0 initiatives through comprehensive electronic survey of literature to estimate the extend of its launching in different regions. Inferences were drawn from industry 4.0 initiatives in developed nations to be used as the recommendations for East Africa Community. Results of the survey revealed that 117 industry 4.0 initiatives have been launched in 56 countries worldwide consisting of five regions. The country’s percent of industry 4.0 initiatives as per region were: Latin America and the Caribbean (15%), North America (40%), Europe (53%), Asia and Oceania (25%), Middle East and Africa (11%). While the worldwide percent was estimated as 25%. This revealed that the big gap is existing between countries towards the race for industry 4.0.

The enormous diversity of hair fibers found in human population is striking, while the basic structure of human fibers is often the same! But why do some fibers curl? Curling is related to the machinery and processes that produce different keratin filament orientation in relation to the axis of hair growth, influenced by developmental and molecular control. It is established that a curly hair shaft is produced by a curved hair follicle that have an angulated dermal implantation, with a bulb bent in the shape of golf club, while the outer root sheath is dissymmetrical; have an outer side that is convex bulging and thin and a concave side in which the cells express alpha-smooth muscle protein reflecting internal mechanical force. Yet, the exact cause of hair curling is not known. All the previous studies were short of impacting curly hair treatment. My hypothesis is that the curling mechanical force is generated by a hypersensitive contracted Arrector Pili muscle (APM) of the hair follicle. In curly hair, each APM fiber is shortened; pulling its attachment spot upward towards the epidermis and obliquely or laterally; curling the outer root sheath to produce the curved follicle described above. This contraction has the influence at a time when the young hair root is being formed and keratin microfibrils are being oriented and packed. APM is a multi-unit muscle wherein each fiber contracts independently to create the enormous diversity of curly hair types. APM contraction can be modulated by oral administration of selective smooth muscle relaxing treatment that relax the curved follicle from within. Further studies are needed to confirm the role of APM in shaping curly hair follicle including AI studies, i.e., computer-aided target identification to demonstrate APM active site that can interact with herbal small molecules.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive neuromuscular disease prevalent in 1 in 3500 to 5000 males worldwide. As a result of mutations that interrupt the reading frame of the dystrophin gene (DMD), DMD is characterized by a loss of dystrophin protein which leads to decreased muscle membrane integrity, which increases susceptibility to degeneration. CRISPR/Cas9 technology has garnered interest as an avenue for DMD therapy due to its potential for permanent exon skipping, which can restore the disrupted DMD reading frame in DMD and lead to dystrophin restoration. An RNA-guided DNA endonuclease system, CRISPR/Cas9 allows for the targeted editing of specific sequences in the genome. The efficacy and safety of CRISPR/Cas9 as a therapy for DMD has been evaluated by numerous studies in vitro and in vivo, with varying rates of success. Despite the potential of CRISPR/Cas9-mediated gene editing for the long-term treatment of DMD, its translation into the clinic is currently challenged by issues such as off-targeting, immune response activation, and sub-optimal in vivo delivery. Its nature as being mostly a personalized form of therapy also limits applicability to DMD patients, who exhibit a wide spectrum of mutations. This review summarizes the various CRISPR/Cas9 strategies that have been tested in vitro and in vivo for the treatment of DMD. Perspectives on the approach will be provided, and the challenges faced by CRISPR/Cas9 in its road to the clinic will be briefly discussed.

The convergence of artificial intelligence, robotics, and gaming has sparked critical discussions about the nature of life and the potential for artificial systems to replicate biological traits. This paper examines the defining characteristics of life—such as growth, reproduction, regulation, and sensitivity—and applies these criteria to AI-driven game entities and autonomous robots. By reviewing advancements in AI and robotics from 2015 to 2023, and grounding the analysis in biological theories, this study explores whether these artificial systems can be considered "alive" or if they are merely sophisticated simulations. The findings suggest that while artificial systems can mimic life-like behaviours, they lack essential biological traits, such as metabolism and autonomous reproduction. However, human tendencies to anthropomorphise these systems raise ethical and philosophical questions about the boundaries of life and the need for new frameworks to address the evolving role of artificial intelligence and robotics. This paper concludes by proposing directions for future research on the ethical, social, and technical implications of artificial life.

Accurate estimation of the state of health (SOH) of batteries for automotive applications, particularly in electric vehicle battery management systems (EV-BMS), is still under study and is highly relevant to ensure battery system availability. This paper proposes a comprehensive SOH estimation method that goes beyond the methods that are based on the estimation of the battery available capacity by the integral of the current, or the estimation of the increase of the internal resistance of the battery. The SOH estimator is based on a partial capacity discharge method and a linear state of charge (SOC) observer based on an equivalent electrical circuit model. This method uses readily available manufacturer data and is designed for real-time applications. The proposed method was tested and validated with three different automotive battery technologies in a Model-In-Loop (MIL) environment with OPAL-RT platform, utilizing voltage and current measurements of pulsed discharge current profiles at temperature-controlled conditions and an electric vehicle’s driving profile.

The critical role of manufacturing operations in enhancing the performance of Small and Medium Enterprises (SMEs) has become increasingly evident in recent years. This systematic review examines how manufacturing operations influence the performance of SMEs, analysing findings from 69 diverse research papers published between 2014 and 2024. Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, the review focuses on key operational strategies, including lean manufacturing and advanced manufacturing technologies, assessing their effectiveness in improving business outcomes such as efficiency, productivity, and financial performance. The methodology included a thorough review of the research methods used in the studies, identifying potential biases, gaps, and highlighting the need for diverse approaches. While manufacturing operations have led to improved productivity and increased efficiency for many SMEs, challenges such as limited resources, lack of technical expertise, and resistance to change remain prevalent. Notably, a reporting bias was observed, with 48% of the literature composed of quantitative studies, 30% being mixed-method studies, and only 20% and 1% representing qualitative and exploratory studies, respectively. This imbalance suggests an overemphasis on quantitative methods, limiting the range of ideas and understanding available. Key strategies such as lean manufacturing and advanced technologies were shown to enhance productivity by 15% to 25% in SMEs. By adopting a broad approach, this review ensures that the findings are applicable across various sectors and geographies, offering valuable insights into best practices and challenges across diverse economic contexts. The broad scope also allows for the identification of under-researched areas, fostering a more comprehensive understanding of how manufacturing operations contribute to SME success. The review provides a decision-making framework for business leaders and policy recommendations to foster SME growth in a competitive, globalized market.

Microparticles derived from biomaterials are becoming increasingly popular for various applications, particularly in drug delivery systems. In this study, the water-in-oil (W/O) emulsification-diffusion method was used to create cellulose (C), silk fibroin (SF), and C/SF composite microparticles. We then observed the morphology of all obtained microparticles using scanning electron microscopy (SEM), evaluated their functional groups using attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), and conducted thermogravimetric analysis using a thermogravimetric analyzer (TGA). SEM micrographs indicated that the native SF microparticles have the highest spherical shape with smooth surfaces. With blue dextran, the C microparticle was smaller compared to the native microparticle, while the drug-loaded SF microparticles were bigger than the native microparticle. The morphological surfaces of the C/SF composite microparticles were varied in shape and surface depending on the C/SF ratio used. The spherical shape of the C/SF composite microparticle was increased as SF content increased. Furthermore, the size of drug-loaded C/SF composite microparticles was gradually increased by the SF content. The significant functional groups in the C and SF structures were identified based on the ATR-FTIR data, and a suggestion was made regarding the interaction between the functional groups of each polymer. When compared to both native polymers, the C/SF composite microparticles exhibit improved thermal stability. The C/SF composite microparticle at a 1:3 ratio had the lowest drug release content, whereas the hydrophilicity of the C microparticle affected the highest drug release content. As a result, one crucial factor affecting the medication released from the microparticle is its thermal stability. According to the obtained results, C, SF, and C/SF composite microparticles show promise as delivery systems for drugs with controlled release.

In 1944 the architect Antonio Gómez Davó designed and built a new house for Mr. Ferrer at Rocafort in the suburbs of Valencia (Spain). In this same year, Europe, America, Russia and even Japan were still at war and Spain was only recovering from its own intestine conflict. Therefore, architectural innovations and influences were scarce as was the circulation of specialized journals on the matter. But in many creations, like the ceramic vaults and the brise-soleil, Le Corbusier himself had declared his profound nostalgia from the Mediterranean, a Sea that he had come to appreciate in his travels to the “orient”. In the case of Gómez Davó, having been born and raised in a prominent family of Valencia he could not remain indifferent to the design features that appeared in the vernacular architecture of the area, specially the type of inclined louvers of Arabic descent, that covered bow-windows and balconies and which have come to be known in Spain as the Majorcan louvers; nowadays even employed by Rafael Moneo for instance at the extension of the Painter Miro Foundation. However, with so many difficult circumstances surrounding him, Gómez Davó could not get to the point of producing a ground breaking design based on solar assumptions for the whole façade of the building, instead when providing an entrance porch apt for spending life, meals and well deserved rest hours outdoors in the pure Mediterranean tradition, he ventured to construct a surprising perforated wall oriented to the South in order to control radiation in winter and provide shade in the summer while affording excellent light and superb conditions of ventilation. By means of our own devised simulation tools we have analyzed the conditions of the house and especially of such innovative brise-soleil at times reminiscent of Alvar Aalto solutions for day-lit roofs, which he was aware intuitively and by his own incipient study of solar geometry, that needed adaptation from so distant latitudes as Finland and Valencia. By outlining such unknown and bold precedent we contribute to revitalize the early and daring pioneers of solar architecture in peripheral Spain and Europe, at the birth of critic regionalism, a fact often disregarded in conventional history of Modern Architecture.

It is documented that maternal diseases or treatments influence a newborn’s clinical status at birth; autoimmune diseases with circulating antibodies are often clinically expressed transiently in newborns due to the crossover of the specific IgG through the placenta during pregnancy. The offspring can inherit maternal genetic anomalies, but clinical expression usually becomes patent later in life. If prenatal medical history is not available or if signs or symptoms of a mother’s disease are revealed for the first time during pregnancy or postpartum, their effects on the newborn may be misattributed. In this article, we present three cases of pregnant women, without any known pathology before or during pregnancy, who gave birth to very sick preterm newborns that required admission to the Neonatal Intensive Care Unit (NICU). The neonates’ complications were considered initially as consequences of prematurity or infection, but later investigations revealed transient autoimmune disease in two of the cases (myasthenia gravis and hyperthyroidism) and a severe form of thrombophilia in the third case. In all cases, mothers were asymptomatic and unaware of their subclinical disease. Preemies’ diagnosis has contributed to the identification of their mothers’ pathology and adequate treatment was prescribed with favourable short- and long-term outcomes. In one of the cases (myasthenia gravis) both mother and child had associated infectious diseases in the perinatal period that complicated the clinical picture and created problems of diagnosis. This article intends to emphasize the paramount importance of prenatal care, for both mother and newborn. Repeated medical visits and investigations throughout the pregnancy are a good opportunity to detect subclinical diseases or predispositions. As newborns usually develop non-specific signs, one should have experience and pay attention to differentiate among etiologies. Our paper takes a reversed approach to the usual medical diagnosis pathway: from infant to mother instead of mother towards the infant, proving that inter-speciality collaboration can work bi-directionally.

This research paper examines the transformative impact of Artificial Intelligence (AI) on the global journalism industry. The integration of AI technologies, such as machine learning and natural language processing, has drastically changed journalistic practices and media operations. The study aims to understand how AI affects news production, distribution, and ethical considerations within journalism. By providing historical context and reviewing existing literature, this paper situates its analysis within the broader academic discourse. A mixed-methods approach is used for data collection and analysis, ensuring comprehensive and reliable findings. Results indicate that AI tools enhance journalistic efficiency and capabilities but also introduce challenges related to accuracy, authenticity, and editorial judgment. The implications for employment in journalism are significant, necessitating new skills and roles. The discussion interprets these findings in the context of media evolution and ethical standards. This study concludes by advocating for a balanced approach to AI adoption in journalism, emphasizing the importance of ethical guidelines, continuous journalist training, and ongoing research to navigate this evolving landscape.

This study aimed (1) to map the immunogenic epitopes (B and T cells) within the major BCoV structural proteins. These epitopes are believed to induce a robust im-mune response through the interaction with major histocompatibility complex (MHC class II) molecules (2) to design some novel BCoV multi-epitope-based vac-cines. To achieve these goals, we applied several integrated In-silico prediction computational tools to map these epitopes within the major BCoV structural pro-teins. The predicted epitopes were linked to some immunostimulants such as Toll-like receptors-2 (TLR2) and TLR-4. The tertiary structure of each epitope was modeled through the Alpha fold-2 colab machine learning tools. The stability and purity of each epitope were assessed using the Ramachandran plot and the Z Score values. Each multiepitope-based vaccine candidate conjugated with the Chlorotox-in B toxin as an adjuvant. We designed the vaccine constructs using various expres-sion vectors. We also predicted the affinity binding of these vaccines with the target protein using molecular docking. Our designed multiepitope vaccine candidates per each BCoV structural protein showed high antigenicity, immunogenicity, non-allergic, non-toxic, and high water solubility. Further studies are highly en-couraged to validate the efficacy of these novel BCoV vaccines in the natural host.

In many parts of the Asia, particularly in the arid regions of the middle east the date palm i.e. Phoneix dactylifera L. is considered a significant plant both culturally and economically. Over the past decade numerous biotechnological tools have been applied to revolutionize the date palm research and its cultivation process. In this comprehensive review ,we provided the in depth overview of the cutting edge developments in the date palm biotechnology, mentioning the important areas such as genomics, genetic engineering, in vitro propagation, omics technologies, and the integration of the artificial intelligence and machine learning (AI-ML).Due to these advancements ,in the date palm production how the date palm production lead the production of superior date palm cultivars with the improved yield ,fruit quality and resilience to biotic and abiotic stresses. Also it explores the application of the biotech tools in the enhancing pest and disease management strategies, increasing date palm productivity and developing the date palm based bio-factories for the production of high value compounds. This review highlights the current challenges faced by the date palm industries ,including the limited water resources ,genetic erosion , pests and disease and the need for improved postharvest handling and processing. It examines how these tools coupled with AI-based approaches can be leveraged to address these challenges and ensure the long term sustainability of date palm cultivation.

Bioactive peptides are sequences of amino acids, cut from the parent protein with en-zymes or high pressure processing that can impart a tertiary health benefit to the con-sumer that goes beyond basic human nutrition. This study explores mesopelagic fish in-cluding Maurolicus muelleri and Benthosema glaciale as sources of peptides with an-ti-inflammatory, heart health beneficial, antioxidant and other bioactivities. Bioactive peptides were generated post-catch using different enzymatic hydrolysis processes ap-plied to mesopelagic species caught from experimental cruises targeting these fish. Maurolicus muelleri and Benthosema glaciale were the dominant species processed. Bi-oactive hydrolysates included a Maurolicus muelleri Alcalase hydrolysate and a Maurolicus muelleri autolysis. Hundreds of peptide sequences were identified using mass spectrome-try from active hydrolysates. In silico analysis was used to rank identified peptide se-quences in terms of overall bioactivity using Peptide Ranker, anti-inflammatory activity using PrepAIP, ability to impart Umami flavours with Umami-MRNN and dipeptidyl peptidase IV inhibitory potential using AntiDMPpred . Thirty peptides were selected fol-lowing in silico analysis. Several of the selected peptides had sequence homology with peptides derived from other fish proteins including Atlantic salmon (peptide QCPLHR-PWAL) and thin-lipped mullet (peptide FDAFLPM). Seven peptides predicted to have an-ti-inflammatory, anti-type 2 diabetes or Umami potential using in silico strategies were chemically synthesized and their anti-inflammatory activities confirmed using in vitro bioassays with COX-1 and COX-2 enzymes. The peptide QCPLHRPWAL inhibited COX-1 and COX-2 by 82.90% (+/-0.54) and 53.84% respectively and had a selectivity index greater than 10. This peptide warrant further research as a novel anti-inflammatory/pain relief peptide. Other bioactivities associated with DPP-IV inhibition and Umami flavours de-velopment are discussed. Identified peptides offer potential for use in functional foods or topical agents to prevent pain and inflammation associated with diseases like psoriasis, arthritis and inflammatory bowel disease, however further research in vivo is required.

This study comprehensively explores Serbia's Disaster (Risk) Management System, aiming to critically evaluate its inherent strengths and weaknesses. Using descriptive-analytical methods and qualitative interpretation, SWOT analysis was applied to collect data from scientific papers, books, and institutional reports. This study delves deeply into the nuances of Serbia's Disaster Management Framework, revealing a nuanced landscape of strengths, weaknesses, and strategic improvement opportunities. Identified strengths underscore a robust foundation characterized by proficient professionals, state-of-the-art technology, and cohesive teamwork, all pivotal for effective emergency preparedness and response. Conversely, weaknesses underscore pressing imperatives for enhancements in regulatory enforcement, resource allocation, and infrastructure upgrades, presently hampering the framework's efficacy and response readiness. This research contributes to the ongoing discourse on disaster risk management and serves as a catalyst for further scholarly inquiry and policy formulation. By mapping out the structure of Serbia’s Disaster (Risk) Management Framework and integrating diverse data sources, the study enriches theoretical models and lays the groundwork for practical policy interventions. Its findings, including precise recommendations for policy reform and strategic improvements, provide valuable insights for policymakers, emergency management experts, and stakeholders seeking to enhance disaster preparedness and response capabilities on both national and global scales.

Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. However, few scholars explored the impact of agricultural land policies on carbon emissions, such as the High-standard farmland construction(HSFC) in China.Thus，by relying on provincial panel data for China for the period 2005-2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: 1) China's CEALU per unit area presented a fluctuating upward trend during the period 2005-2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%. 2) The high-standard farmland construction(HSFC) policy produced a significant carbon emission reduction effect in agricultural land use, and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing trend. 3) The carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China.

Nowadays, unmanned vehicles are widely used in various fields. However, the safety of unmanned vehicles is directly determined by the autopilot systems, and sensor faults are a very critical factor that affects the normal operation of the autopilot systems. To efficiently and comprehensively test unmanned systems for sensor faults, this paper proposes a chip-level testing platform for unmanned vehicle autopilot systems based on FPGA hardware-in-the-loop simulation. Unlike existing testing platforms, the introduction of FPGA technology allows us to achieve nanosecond real-time simulation frequency, thus realizing chip-level simulation of sensors and black-box automated testing. Firstly, we propose a set of general platform and modeling methods, and the paper presents a detailed application of the four most common necessary sensors in autopilot systems as examples. Secondly, we propose for the first time a chip-level fault testing method for unmanned systems, and build a test platform with a quadrotor vehicle, the PX4 software platform, and the Pixhawk4 hardware platform as examples. Finally, the experimental results verify that the testing platform proposed in this paper can adapt to various autopilot systems and has high simulation test reliability.

Capturing atmospheric CO2 and storing it in natural rock systems (i.e., alkaline earth silicate and hydroxide minerals) through carbonation reactions is a promising greenhouse gas mitigation research, and largely depends on the use of hydrated ultramafic rocks (serpentinites), which are widespread in orogenic belts around the globe. The Jurassic ophiolites in the Southern Apennines represent a natural analogue and a great opportunity for the mineralogical sequestration of CO2. Serpentinites of the Pollino ophiolite Massif have been widely studied for their mineralogical, petrographic, and chemical characteristics, providing major findings on their impact on environmental and human health issues. Serpentinites here have been divided into cataclastic and massive types based on their structures and are characterized by pseudomorphic and vein textures. The mineralogy of the studied serpentinites consists of lizardite, antigorite, clino-crysotile, Cr-chlorite, magnetite, tremolite, actinolite, pyroxene and calcite, and the most commonly occurring serpentine minerals are polymorphs of serpentine including lizardite, clino-crysotile and antigorite. Systematic petrographic and mineralogical studies of serpentinites in ophiolites, such as those outcropping in the Southern Apennines can represent a starting point for the study of natural materials, which can be used for CO2 storage and sequestration. A particular attention must be given to those carbonate phases, produced by carbonation processes to check whether the serpentinites of the Pollino Massif can be used for the induced mineral Carbon Capture Storage (CCS). If successful, this technique and the Pollino Massif serpentinites can become highly significant in safeguarding the health of our planet's climate.

A novel educational platform called Shared Modeling and Simulation Environment (SMSE) was initiated in the ERASMUS+ “CybPhys” project. It integrates the Jupyter platform, including Ju-pyter Notebooks, for e-learning in the STEM field. A novel platform enhances e-learning by combining Moodle with Jupyter's capabilities to create virtual labs. A survey was conducted in the spring of 2023 among bachelor and master students of Chernihiv National Polytechnic Uni-versity aimed to gather feedback from students using SMSE in their e-learning process. Two student groups were involved: one of them consisted of students using SMSE in both the autumn and spring semesters and another represented the students starting with SMSE in the spring se-mester. The survey based on the adjusted Technology Acceptance Model (TAM) was conducted to understand the acceptance of this e-learning approach. A comprehensive analysis of students’ answers based on the TAM approach revealed the inside of the process of transformation of stu-dents’ perceptions during the acquisition of the SMSE platform. Our research demonstrates that SMSE effectively merges Moodle's online learning capabilities with Jupyter notebooks, provid-ing a flexible and interactive learning experience for both in-class and remote students. It pro-vides a web-based, multifunctional e-learning environment that combines a variety of tools and technologies, giving students the possibility to be involved in all sorts of teaching activities, such as lectures, exercises, simulations, etc., through the use of one single online environment.

In the present paper, we efficiently solve the two-body problem for extreme cases such as those with high eccentricities. The use of numerical methods, with the usual variables, cannot maintain the perihelion passage accurately. In previous articles, we have verified that this problem is treated more adequately through temporal reparametrizations related to the mean anomaly through the partition function. The biparametric family of anomalies, with an appropriate partition function, allows a systematic study of these transformations. In the present work, we consider the elliptical orbit as a meridian section of the ellipsoid of revolution, and the partition function depends on two variables raised to specific parameters. One of the variables is the mean radius of the ellipsoid at the secondary, and the other is the distance to the primary. One parameter regulates the concentration of points in the apoapsis region, and the other produces a symmetrical displacement between the polar and equatorial regions. The three most used geodesy latitude variables are also studied, resulting in one not belonging to the biparametric family. However, it is in the one introduced now, which implies an extension of the biparametric method. The results obtained by the method presented here now allow a causal interpretation of the operation of numerous reparametrizations used in the study of orbital motion.

The high-quality development of urban-rural integration is a vital component of China's economy, serving as a strategic response to the in-depth deployment of new urbanization and rural revitalization strategies. This integration is underscored by the promotion of entrepreneurship in agriculture, rural areas, and among farmers, which acts as a driver for fostering high-quality development in urban-rural areas through market competition. The resulting influx of resources and commodities with similar characteristics plays a crucial role in bridging the urban-rural divide. To maintain objectivity, it is important to adopt a balanced approach and refrain from using biased language. This study delves into the connotation and internal mechanism of the high-quality development of urban-rural integration, centering on the principle of 'quality'. Specifically, it examines the role of entrepreneurship in agriculture, rural areas, and among farmers, and evaluates its direct impact and transmission mechanism. The research employs balanced panel data from 41 cities in the Yangtze River Delta region spanning from 2003 to 2021. The findings reveal that entrepreneurship in agriculture, rural areas, and among farmers serves as a catalyst for promoting high-quality urban-rural development through the construction of a virtuous cycle, whereby resource factors and commodity services are exchanged. Moreover, this deep integration yields diverse effects across economic, spatial, demographic, social, and ecological domains, underscoring the necessity of continued support for entrepreneurship in agriculture, rural areas, and among farmers to facilitate a seamless urban-rural economic cycle and fully realize the benefits of high-quality development.

One of the needs of the teaching and learning processes is the lack of information during the process, such as the emotions of students. Emotions influence learning, the ability to process information and accurately understand what we are dealing with. They profoundly affect students’ academic engagement and performance. One new way of getting such information is monitoring students' emotions. This research aims to expose 6 groups of secondary school students to video recordings for further analysis and categorization of their emotions. A model of emotional recognition (ER) during classroom learning was designed, with a custom-made code, from recorded videos to images to identify faces, action units (AUs) and consequently the emotions of each of the students shown on the screen. In addition, the ER model was optimized, from detecting few students to many students during a class. Emotions were then analysed according to the academic year, subject, and comparing the emotions at the beginning and at the end of the class. The results indicate the presence of a variety of emotions in the classroom and we found significant differences in the presence of some emotions depending on the time of class, subject and academic year, although there are no clear patterns. We discussed how emotions influence students' academic performance, and we suggest future research focus on teachers utilizing tools like this to improve student well-being and performance.

In-wheel motor vehicles are gaining attention as a new type of electric vehicle due to their efficient power units located inside each wheel hub. However, they are more susceptible to wheel resonance due to the increase in unsprung mass caused by the motor's weight. This can result in decreased both the ride comfort and driving stability. To resolve this issue, this study aims to apply an optimal switching controller with a semi-active n actuator; magnetorheological (MR) damper. For the implementation of the optimal switching controller, a road type classification is also carried out. An acceleration sensor is used for road type classification, and control logics include a ride comfort controller; the linear quadratic regulator (LQR _Paved Road) and a wheel motion controller (LQR_Off Road) for improved driving stability. For paved roads, the LQR_Paved Road control input is applied to the MR damper. However, if a road type prone to wheel resonance is detected, the control logic switches to the LQR_Off Road. During the transition, a weighted average of both LQR_ Paved Road and LQR_Off Road control input is applied to the actuator. Computer simulations are undertaken to evaluate vibration control performance, including the ride comfort and driving stability at various road profiles.

WBAN is a blessing to mankind because it can monitor people's health and activities regardless of place or time. It brings feasibility in patients’ treatment. The main problems with WBAN, however, are related to the security and privacy of health data. To prevent data misuse, health information should be safeguarded. On the other hand, the medical professional needs to receive the patient's health information promptly. As security of health data impact human life greatly so secure an efficient method is required. Efficient cryptographic technique for data protection of wireless body area network is proposed. This research aims to provide data protection in WBAN to increase data security and efficient transmission. The suggested approach offers effective security with quick key generation, quick encryption, and secure data transmission across the network. The proposed methodology is considered to be secure and will consume less time. The proposed method further uses a less complex encryption algorithm. The less complex the approach is the higher performance it will provide in wireless network. The proposed methodology will prevent many attacks, which makes the proposed approach highly suitable for wireless body area network’s security.

Although the potential of natural minerals for purification of liquid radioactive wastes (LRW) from radionuclides has been widely studied, the use of hybrid polymer composites made of zeolite is still rather scarce. This article reports on the preparation of zeolite based hybride polymer composites using the in-situ polymerization technique in the body of mineral matrix and its intercalated with copper ferrocyanide (CuFC) forms. This hybrid polymer composites have shown unique and enhanced properties as compared to the individual mineral. The change in conventional properties of two mixed minerals such as zeolite and bentonite and their intercalated with CuFC forms were probed using technics such as scanning electron microscopy (SEM), X-ray diffraction (XRD), Mossbauer spectroscopy (MS) and FT-IR analysis. The totality of analysis showed a coexistence of intercalated and percolated zeolite phases. The hybrid polymer composites exhibited both adsorption and ion-exchangr properties in removal of radionuclides from LRW.

Thermal Non-destructive Testing and Evaluation (NDT&E) is crucial in ensuring the quality and safety of industrial materials, components, and structures. It serves as a key tool for assessing their operational reliability, thus enhancing safety in a wide range of industries. There is a growing demand for dependable, swift, remote, and secure inspection and assessment techniques to detect hidden flaws, especially for sustainable solutions prompts adjustments in design and manufacturing standards. Hidden defects often emerge during the service life of these materials and structures due to various stress factors, potentially resulting in catastrophic failures. This study delves into the optimal and dependable experimental method for conducting fast, remote, and secure inspections and assessments of carbon fiber reinforced polymer materials using Infrared Imaging (IRI) as part of Thermal Non-Destructive Testing and Evaluation (TNDT&E). Additionally, it examines the post-processing approach associated with this technique. This perspective also sheds light on the current state-of-the-art infrared imaging methods employed in TNDT&E, emphasizing their strengths and weaknesses about their ability to detect subsurface defects present within the material Most of the methods discussed in previous research primarily focus on the thermal differences in specific areas of a sample using processed thermal images, even though these images come from analyzing a series of images captured over time. This study highlights the latest research in thermal/infrared non-destructive testing and evaluation, along with the related post-processing techniques. It aims to not only show hidden subsurface defects through thermal differences also provides information about how these defects change over time.

Biomass and biowaste valorisation is of major interest nowadays because of the spirit of circular economy and of the neutral environmental fingerprint global target. In the current project chondroitin sulphate (ChS) was incorporated with the crustaceous’ and shrimp’s byproduct chitosan (Chi) and the fish industry byproduct gelatine (FG) to obtain dense hydrogel membranes. Glycerol (Gly) was utilized to avoid brittleness. The formation of the hydrogel membranes is attributed to secondary interactions between the natural polymers and the plasticizer. The prepared hydrogel membranes were characterized by Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), X-ray diffraction (XRD) and thermogravimetric analysis (TGA). The surface morphology of the membranes was examined using scanning electron microscopy (SEM). Dynamic mechanical analysis (DMA) and tensile tests were also performed to evaluate the mechanical response of the membranes. The samples were also evaluated for membrane wettability, degradation rate and water vapor transmission rate (WVTR). Finally, in vitro endothelial cell attachment on the membrane were addressed. The overall results of the study indicate that the hydrogel membranes could be appropriate for external application in wound healing applications as dressings.

Continuous greenhouse gas emissions are causing global warming and impacting the habitats of many animals. Researchers in the field of electric power are making efforts to mitigate this situation. Operating and maintaining the power grid in an economic, low-carbon, and stable is challenging. To address the issue, we propose a grid dispatching technique that combines prediction technology, reinforcement learning, and optimization technology. Prediction technology can forecast future power demand and solar power generation, while reinforcement learning and optimization technology can make charging and discharging decisions for energy storage devices based on current and future grid conditions. In the power system, the aggregation of distributed energy resources increases uncertainty, particularly due to the fluctuating generation of renewable energy. This requires the use of advanced predictive control techniques to ensure long-term economic and decarbonization goals. In this paper, we present a real-time dispatching framework that integrates deep learning-based prediction, reinforcement learning-based decision-making, and stochastic optimization techniques. The framework can rapidly adapt to target uncertainty caused by various factors in real-time data distribution and control processes. The proposed framework achieved global Champion in the NeurIPS Challenge 2022 competition and demonstrated its effectiveness in practical scenarios of intelligent building energy management.

Land surface temperature (LST) is a crucial parameter in climate and ecology, exerting significant influence on meteorological conditions, ecosystems, and human life. LST data sources are diverse, with remote sensing being the prevailing means of acquisition. FY-4A/AGRI offers high-quality LST products for East Asia. In this study, we evaluated the performance of the product in Hunan Province and conducted refined analysis of surface heat resources based on the 4km/1h resolution product over a two-year period. The results demonstrate that the FY-4A LST product effectively captures surface temperature (R=0.893), albeit with a relatively high error level (Bias=-6.295℃; RMSE=8.58℃), particularly in capturing high LST values. The performance of this product is superior in the eastern flat terrain area of Hunan Province compared to its performance in the western mountainous region due to environmental conditions causing systematic errors that contribute to instability in detection deviation for this product. Surface heat resources are more abundant in eastern Hunan Province than in mountainous areas located west and southwardly, and the detailed distribution of them at finer scales is mainly influenced by the terrain and climate conditions. There is no obvious seasonal difference in the distribution of heat resources except in winter, and rapid urbanization within Chang-Zhu-Tan urban agglomeration during two years has significantly altered the spatial distribution pattern of surface heat resources across Hunan Province. These findings provide a quantitative baseline for assessing FY-4A satellite's detection capability while serving as a reference for further application of its LST products and establishing foundations for divisional classification and utilization strategies pertaining to surface heat resources within Hunan Province.

Emerging pollutants pose significant threats to Uganda's ecosystems and public health amidst rapid urbanization, industrial growth, and intensified agriculture. This systematic review comprehensively assessed these pollutants by analyzing existing Ugandan literature and research studies, revealing various types in different environmental compartments. These pollutants, including pharmaceuticals, personal care products, pesticides, industrial chemicals, heavy metals, radionuclides, biotoxins, disinfection byproducts, hydrocarbons, and microplastics, originate from urban, industrial, and agricultural regions. Wastewater and improper waste disposal are major contributors. From an initial search of 794 articles across multiple databases such as PubMed, African Journal Online (AJOL), Web of Science, Science Direct, and Google Scholar, 138 were found relevant. The review underscores potential ecological and health impacts, including antibiotic resistance, endocrine disruption, and carcinogenicity. Existing monitoring and regulation efforts are discussed, alongside the need for specific regulations, improved data collection, and public awareness campaigns. Recommendations include advanced wastewater treatment, sustainable agriculture, and source control measures. Emphasis is placed on further research to address knowledge gaps and develop effective policies and interventions. Uganda can mitigate these risks by implementing comprehensive monitoring, robust regulations, and sustainable practices, safeguarding the environment and public health.

The divination function of China's Yijing has led to its circulation for thousands of years. In our exploration of Yijing's characteristics using big data, we have discovered variations in results between the coin toss method and the ancient yarrow-stalk method of divination, known as "the number for the great expansion method of divination(大衍之数)". The yarrow-stalk method serves as the fundamental method of divination in Yijing and continues to hold significance in studying the essential characteristics of Yijing. Despite the complexity of yarrow calculations, advancements in computer technology and big data have simplified its application. By employing the yarrow-stalk method, we simulated changes in the 64 hexagrams, calculated probabilities and proportions of hexagram alterations, and derived fundamental characteristics and patterns of hexagrams. Additionally, we constructed the spatial representation of lines and hexagrams. Through a binary system rearrangement, we created a 64x64 matrix illustrating hexagram transformations. Subsequently, we generated 100 million random hexagrams and analyzed line and hexagram changes accordingly. Our findings indicate the following:(1) Big data analysis reveals evident asymmetry in the hexagrams obtained through the yarrow-stalk method, with a triangular fractal characteristic forming the background.(2) Each of the 64 hexagrams exhibits a distinct probability distribution when transforming into other hexagrams, which can be categorized into five types.(3)The occurrence probabilities of Laoyang, Laoyin, Shaoyang, and Shaoyin are 18.61%, 6.387%, 31.38%, and 43.62% respectively. The probabilities of Yin and Yang occurrences are nearly equal, each close to 50%. However, the probability of Laoyang is approximately three times higher than that of Laoyin.(4) Visualized and analyzed the characteristics of hexagram changes greater than 100000 times using 3D statistical maps and Sankey diagram.These results demonstrate that the yarrow-stalk method effectively unveils the characteristics and underlying patterns of the 64 hexagrams. This study provides a novel approach for scientifically exploring the internal laws governing the 64 hexagrams in Yijing.

pH is considered one of the paramount factors in bodily functions, because most of the cellular tasks exclusively rely on precise pH values. The regulation of pH is a necessary feature of the intracellular atmosphere and can be established as a strong indicator to judge a physiological abnormality in most of the cases. In this context, the current techniques for pH sensing provide us with the futuristic insight to further design therapeutic and diagnostic tools. Thus, pH-sensing (electrochemically and optically) is rapidly evolving toward exciting new applications and expanding researchers’ interests in many chemical contexts, especially in biomedical applications. The adaptation of cutting-edge technology is subsequently producing the modest form of these biosensors as wearable devices, which are providing us the opportunity to target the real-time collection of vital parameters, including pH for improved healthcare systems. The motif of this review is to provide an insight of trending tech-based systems employed in real time or in-vivo pH responsive monitoring. Herein, we briefly go through the pH regulation in the human body to help the beginners and scientific community with quick background knowledge, recent advances in the field, and pH detection in cancerous environments. In the end, we summarize our review by providing an outlook; challenges that need to be addressed and prospective integration of various pH in vivo platforms with modern electronics that can open new avenues of cutting-edge techniques for disease diagnostics and prevention.

Detecting suicidal ideation in adults with major depression is crucial for timely intervention and prevention of self-harm. As suicide is influenced by various biological, socio-cultural and psychological factors, traditional screening methods have accuracy and efficiency limitations. In certain cultures, societal stigma and marginalization can compel individuals with depression to conceal their suffering. Such individuals often turn to online social media platforms and share their experiences with peers under the protection of anonymity. Our research explored the potential of machine learning detection of suicidal ideation among Romanian adults with major depression that contributed to a web-based depression support forum. A trained algorithm (C4.5 decision tree) analyzed 125 posts fed to on a free access online support forum over 5 years (2014 – 2018) and classified them based on suicidal ideation content. 32 texts (25%) were identified as having a high probability of suicidal ideation content. 65% of the authors were male, with a mean age of 36.7±10.3 years and an average duration of illness of 3.4±1.4 years. Texts indicating positive suicidal ideation were generally shorter and elicited more general responses but fewer professional responses compared to those without suicidal ideation content. The study's main limitations include the relatively small number of classified texts, the absence of prospective information and the lack of qualitative evaluation of the excerpts' content. As socio-demographic and linguistic actuarial results were comparable to data reported by real life studies, we may consider basic text mining techniques as a screening tool that is able to detect suicidal ideation in texts written in unstructured Romanian language.

Aquathermolysis is a promising method to upgrade heavy oil in reservoir conditions. However, application of catalysts can significantly promote transformation of the heavy fragments (resins and asphaltenes) and heteroatom-containing compounds of crude oil mixture into low-molecular-weight hydrocarbons. In this paper, the comparison study of the catalytic performance of the water-soluble metal salts such as NiSO4 and FeSO4 on the aquathermolytic upgrading of heavy oil samples produced from Ashal’cha reservoir was carried out at a temperature of 300 °C for 24 hours. Iron nanoparticles contributed to the highest viscosity reduction degree - 60% in contrast to the viscosity of the native crude oil sample. The viscosity alteration is reasoned by the changes in the group composition of heavy oil after catalytic (FeSO4) aquathermolysis, where the content of resins and asphaltenes were reduced by 17% and 7%, respectively. Moreover, the aquathermolytic upgrading of heavy oil in the presence of FeSO4 led to an increase in the yield of gasoline fraction by 13% and diesel fraction by 53%. The H/C ratio, which represents the hydrogenation of crude oil, increased from 1.52 (before catalytic upgrading) to 1.99 (after catalytic upgrading). The results of Chromatomass (GC-MS) and Fourier-infrared (FT-IR) spectroscopies confirmed the intensification of destructive hydrogenation of resins and asphaltenes in the presence of the water-soluble catalysts. According to XRD and SEM-EDX results, the metal salts are thermally decomposed during the aquathermolysis process into the oxides of corresponding metals and particularly sulfided by the sulfur-containing aquathermolysis products.

Snow-covered regions are the main source of reflection of incident shortwave radiation (ISR) on Earth’s surface. The deposition of light-absorbing particles (LAPs) on these regions increases the capacity of snow to absorb ISR and decreases surface snow albedo (SSA), which intensifies the radiative forcing leading to accelerated snowmelt and modifications of the hydrologic cycle. In this work we investigate changes in SSA and radiative forcing (RF) induced by LAPs in the Upper Aconcagua River Basin (Chilean central Andes) using remote sensing satellite data (MODIS), in-situ spectral SSA measurements, and the ISR (Chilean Solar Explorer platform) during the austral-winter months (May to August) for the 2004-2016 period. To estimate the changes in SSA and RF, we define two spectral ranges: i) an enclosed range (Ecr) between 841-876 nm, which isolates effects of Black-Carbon, an important LAP derived from anthropogenic activities, and ii) a broadband range (Bbr) between 300-2500 nm. Our results show that percent variations in SSA in the Ecr are higher than in the Bbr, regardless of the total amount of radiation received, which may be attributed to the presence of LAPs as these particles have a greater impact on SSA at wavelengths in the Ecr band than in the Bbr band.

The pore-throat radius of shale oil reservoir is extremely small, and it is difficult to accurately obtain the absolute permeability and oil-water two-phase relative permeability of actual oil reservoir through conventional core experiments. However, these parameters are very important for reservoir numerical simulation. In this paper, a method for characterizing flow parameters based on pore network model that considers differential pressure flow and diffusion flow is proposed. Firstly, a digital core was reconstructed using focused ion beam scanning electron microscopy (FIB-SEM) from the Gulong shale reservoir in the Songliao Basin, China, and a pore network model was extracted. Secondly, quasi-static single-phase flow and two-phase flow equations considering diffusion were established in the pore network model. Finally, pore throat parameters, absolute permeability, and oil-water two-phase permeability curves were calculated, respectively. The results show that the pore throat distribution of Gulong shale reservoir is mainly concentrated in the nanometer scale, the mean pore radius is 87 nm, the mean throat radius is 41 nm, and the mean coordination number is 3.97; The calculated permeability considering diffusion is 0.000124mD, which is approximately twice the permeability calculated without considering diffusion; The irreducible water saturation of the Gulong shale reservoir is approximately 0.26, and the residual oil saturation is approximately 0.73. The method proposed in this paper can provide an important approach for characterizing the flow parameters of similar shale oil reservoirs.

All humans will experience the process of birth, old age, illness, and death. However, when faced with life-sustaining decisions, the families of patients are often faced with medical decisions as surrogates. In recent years, the families of patients have started to value the importance of the right to palliative care, although this often requires lengthy discussions. Therefore, this study explored the predictability of factors that affect the feeling experienced by patients’ families when signing Do-Not-Resuscitate Consent. This study used a cross-sectional study and interviewed 90 family members using a structural questionnaire. The study hypotheses were tested using a t-test, one-way analysis of variance, product–moment correlation, and hierarchical regression analysis. Attribute variables of family members, such as gender and whether they live with the patient, are predictors that affect the family member’s feeling experience when signing Do-Not-Resuscitate Consent. The emotional support from medical professionals to family members helps the family member to express their negative feelings on signing Do-Not-Resuscitate Consent; more informational support information provided to family members by medical professionals can alleviate negative feelings felt by family members when signing Do-Not-Resuscitate Consent. This study identified that family members’ knowledge about Do-Not-Resuscitate acquired from medical professionals is relatively low. It is suggested that critical care units regularly conduct training on hospice palliative care, implement standard care procedures of hospice palliative care at critical care units, and provide detailed medical information about advanced decisions to family members so as to reduce their emotional stress. This will ensure that intensive care units can also achieve the goal of critically ill hospice palliative care.

The human respiratory syncytial virus (hRSV) poses a serious risk to global public health and is a significant cause of severe lower respiratory infections. There are currently only a few therapies available to treat RSV infections, as well as no RSV vaccinations. Therefore, there is an urgent demand for clinically feasible, safe, and affordable RSV prevention and treatment alternatives. In this study, an ion-activated in situ gel comprising broad-spectrum antiviral 18β-glycyrrhetinic acid (GA) for antiviral action on RSV was developed. In this content, mechanical properties, sprayability, drug content, pH, ex vivo mucoadhesive strength, in vitro drug release pattern, and stability were all examined. Rheological properties were also tested by utilizing in vitro gelation capacity and rheological synergism tests. Finally, the optimized in situ gel's cytotoxic and antiviral activities on RSV cultured in human laryngeal epidermoid carcinoma (HEP-2) cell line were evaluated. In conclusion, the optimized in situ gel prepared with a combination of 0.5%w/w gellan gum and 0.5%w/w sodium carboxymethylcellulose demonstrated good gelation capacity and sprayability (weight deviation between T0 and T14: 0.34%), desired rheological synergism (mucoadhesive force (Fb): 9.53), mechanical characteristics (adhesiveness: 0.300 mJ ± 0.05), ex vivo bioadhesion force (19.67 g ± 1.90), drug content uniformity (RSD%: 0.494), and sustained drug release over period of 168 h (101.57% ± 0.53). The antiviral activity test results showed that the optimized in situ gel had strong anti-HRSV activity (EC50 simultaneous = 0.05 µg/ml, SI = 306; EC50 preinfection = 0.154 µg/ml, SI= 100) which was significantly higher than that of ribavirin (EC50 =4.189 µg/ml; SI= 28) used as a positive control against hRSV. In conclusion, this research has demonstrated the formulation of an effective antiviral nasal spray that has the ability to possess both prophylactic and virucidal activity.

Numerous researchers and institutions have been developing in ovo sexing technologies to improve animal welfare by identifying male embryos in an early embryonic stage and disposing of them before pain perception. This review gives a complete overview of the technological approaches reported in papers and patents by performing a thorough search using Web of Science and Patstat databases for papers and patents, respectively. Based on a total of 45 papers and 100 patent families up until 2021 reported worldwide, 11 technology categories were defined: six non-optical and five optical techniques. Every category was described for its characteristics while assessing its potential for application. Next, the dynamics of the publications of in ovo sexing techniques in both paper and patent fields were described through growth curves, and the interest or actual status was visualized using the number of paper citations and the actual legal status of the patents. When comparing the reported technologies in papers to those in patents, scientific gaps were observed, as some of the patented technologies were not reported in the scientific literature, e.g., ion mobility and mass spectrometry approaches. Generally, more diverse approaches in all categories were found in patents, although they do require more scientific evidence through papers or industrial adoption to prove their robustness. Moreover, although there is a recent trend for non-invasive techniques, invasive methods like analyzing DNA through PCR or hormones through immunosensing are still being reported (and might continue to be) in papers and patents. It was also observed that none of the technologies complies with all the industry requirements. Thus, more research and harmony between consumers, industry, and governments is necessary.

Introduction: Some of the practices in medicine are carried out of habit without proven benefits. This is the case of premature babies from 30 to 34 weeks of gestation who are always given parenteral fluids, even though this practice has been associated with an increase incidence of infection. At the end of 2017, we started a protocol of rationalization in the use of parenteral fluid. To administer nutrition/fluids, we used oral fluids by suction if this was possible or otherwise by oral/nasogastric tube at volumes of 70-80 mL/Kg/day divided every 3 hours, with 5 mL increments every 12-24 hours until 200 mL/K/day was achieved, always using breast milk when possible. Material and methods: The present study sought to compare results before and after this new policy. For this work, we review all premature babies between 30-34 weeks of gestation in two time periods, the first from 01/01/2010 to 12/31/2017 and the second from 01/01/2018 to 08/15/2022. The number of cases with and without parenteral fluids (PF), the incidence of infection, the weight at admission and discharge, and the change in the weight Z score between birth and discharge were compared. Both the anthropometric and outcome variables were compared using the different statistical methods according to each variable. Results: were found 920 cases with the described characteristics. The groups before and after the intervention did not show significant differences in their general demographic characteristics. We observed a decrease use of PF in the second period, from 425 cases (82.0%) before to 297 (26.2%) after implementation, p <0.0001 and fewer days of use (4.1 days/average before vs 1.3 after, p <0.0001) of PF. The weight at discharge and the change in weight Z-score were the same in both groups. Infections went from nine cases before to two cases after but it was not statistically significant. There were no complications due to less use of PF. Discussion: This study showed that the use of PF is not associated with significant changes in outcomes of interest, which reinforces that its use does not generate any benefit for the patient. Larger number of cases is required to detect differences in low incidence events such as infections.

Due to slow progression and susceptibility to radical forms of treatment low-grade PC is associ-ated with high overall survival (OS). With the clinical progression of PC the therapy is getting more complex. The immunosuppressive tumor microenvironment (TME) makes PC a difficult target for most immunotherapeutics. Its general immune resistance is established by i.e. immune evasion through Treg cells, synthesis of immunosuppressive mediators, and defective expression of surface neoantigens. The success of sipuleucel-T in clinical trials initiated several other clinical studies that specifically target the immune escape of the tumor and eliminate the immunosuppres-sive properties of TME. In the settings of PC treatment, this can be commonly achieved with radi-ation therapy (RT). Also, focal therapies usually applied for localized PC, such as high-intensity focused ultrasound (HIFU) therapy, cryotherapy, photodynamic therapy (PDT), or irreversible electroporation (IRE) were shown to boost anti-cancer response. Nevertheless, the present guide-lines restrict their application to localized and low-grade PC. This review explains how RT and focal therapies enhance the immune response. We also provide data supporting the combination of RT and focal treatments with immune therapies.

The purpose of this article is to disclose the strenuous efforts of Laszlo Hudec in China and Antonin Raymond in Japan and India to create a modern architectural stance by heralding an incipient space syntax. In the turn of the 19th Century, for dynastic, politic and economic reasons, Eastern Asia had very little modern Architecture. It is a surprising fact that, out of happenstance, two European architects Antonin Raymond and Laszlo Hudec, had to intervene to remedy this situation, to the point of becoming 20th Century icons in Japan and China. Their fruitful careers spanned over thirty years and included locations, like Tamil Nadu or the Philippines. The Oriental territories were not an easy ground for the bold architectural achievements that they produced. Despite of faraway strangeness and uncountable personal losses, in revolutions and wars, which eventually forced them both to leave for the United States of America and never to return, they were successful in the manner of establishing a broad avenue for Modern Asian Architecture which is still recognisable today thanks to their systematic approach. However, theirs is an endangered heritage and the intention of this article is to be a just remembrance of in which way such actions could be performed, how they predated by many years a syntactic approach to architectural composition and why their legacy should be preserved.

This paper considers the solution of the equations for ruin probabilities in infinite continuous time. Using the Fourier Transform and certain results from the theory of complex functions, these solutions are obtained as com- plex integrals in a form which may be evaluated numerically by means of the inverse Fourier Transform. In addition the relationship between the re- sults obtained for the continuous time cases, and those in the literature, are compared. Closed form ruin probabilities for the heavy tailed distributions: mixed exponential; Gamma (including Erlang); Lognormal; Weillbull; and Pareto, are derived as a result (or computed to any degree of accuracy, and without the use of simulations).

Demand response flexible loads can provide fast regulation and ancillary services as reserve capacity in power systems. This paper proposes a joint optimization dispatch control strategy for source-load system with stochastic renewable power injection and flexible thermostatically controlled loads (TCLs) and plug-in electric vehicles (PEVs). Specifically, the optimization model is characterized by a chance constraint look-ahead programming to maximal the social welfare of both units and load agents. By solving the chance constraint optimization with sample average approximation (SAA) method, the optimal power scheduling for units and TCL/PEV agents can be obtained. Secondly, two demand response control algorithms for TCLs and PEVs are proposed respectively based on the aggregate control models of the load agents. The TCLs are controlled by its temperature setpoints and PEVs are controlled by its charging power such that the DR control objective can be fulfilled. The effectiveness of the proposed dispatch and control algorithm has been demonstrated by the simulation studies on a modified IEEE 39 bus system with a wind farm, a photovoltaic power station, two TCL agents and two PEV agents.

Discrete, logic-based models are increasingly used to describe biological mechanisms. Initially introduced to study gene regulation, these models evolved to cover various molecular mechanisms, such as signalling, transcription factor cooperativity, and even metabolic processes. The abstract nature and amenability of discrete models to robust mathematical analyses make them appropriate for addressing a wide range of complex biological problems. Recent technological breakthroughs have generated a wealth of high throughput data. Novel, literature-based representations of biological processes and emerging algorithms offer new opportunities for model construction. Here, we review up-to-date efforts to address challenging biological questions by incorporating omic data into logic-based models, and discuss critical difficulties in constructing and analysing integrative, large-scale, logic-based models of biological mechanisms.

In this review, we explore a broad-based view of technologies for supporting human activities on the Moon. Primarily, we assess the state of life support systems technology beginning with physicochemical processes, waste processing, bioregenerative methods, food production systems and the robotics and advanced biological technologies that support the latter. We observe that the Moon possesses in-situ resources but that these resources are of limited value in CELSS – indeed, CELSS technology is most mature in recycling water and oxygen, the two resources that are abundant on the Moon. This places a premium on developing CELSS that recycles other elements that are rarified on the Moon including C and N in particular but also other elements such as P, S and K which might be challenging to extract from local resources. Although we focus on closed loop ecological life support systems, we also consider related technologies that involve the application of biological organisms to bioregenerative medical technologies and bioregenerative approaches to industrial activity on the Moon as potential future developments.

Objectives: The study aimed to uncover the percentages of battered women in Jordan, its causes, forms, and relationship to several social factors. Methodology: The study was conducted on a random, targeted sample of (1308) women based on social sample survey method and electronic questionnaire tool for data collection, the Descriptive statistical method and chi-square test were used to examine statistically significant differences. Results: The study found that the percentage of battered women reached 17.1% during Corona pandemic in 2020, and the increase in men's violence against women during this period of was in large and medium degrees according to the sample. Husbands were the most practicing violence against their wives at 37.5%, followed by fathers against daughters at 28.6%, and brothers against sisters at 26.8%. The causes of male violence are due to social factors represented by male domination culture, interference by family and relatives, and economic factors represented by the high cost of living, low household income and poverty. The most common forms of violence are verbal, physical, and psychological. The study found that women in southern Jordan, who are poorer and less educated, and who live in a large family, are the most abused. The study recommended activating family and community service and reform offices, solving problems of deteriorating economic situation and individual poverty, and enlightening community awareness of the dangers of domestic violence.

Vehicle routing is a critical factor in municipal solid waste (MSW) collection planning and operations. Poor routing can introduce inefficiencies and cause targeted levels of services or performance to be missed irrespective of the level of resource application. Trial and error approaches have been proven to be not the best in the planning and prediction of expected performance. This study explores various Geographic Information System (GIS) tools and analysis techniques, and how they can be applied to optimizing vehicle routes in light of challenging site conditions. Using Adentan West residential area, suburb of Accra Ghana as a case study, current performance of the trial and error method was measured and a GIS computer model was used to evaluate various optimization scenarios to determine the level of savings that can be made. Field measurements were taking with Global Positioning System (GPS) devices for waste collection activities in areas with varying characteristics and conditions, and data analysed for one selected vehicle operating four days per week. It was found that, for a scenario where only the bin collection order was optimized while route selection was restricted by the ArcGIS Network Analyst, 2.6% of travel distance and 2.21% of travel time were saved. For the second scenario where only the route selection was optimized while order of bin collection was restricted, 4.1% and 1.5% of travel distance and time respectively were saved. For a third scenario where both the order of collection and route selection were together optimized, 10.9% and 3.7% of travel distance and time respectively were saved. Lastly, by regrouping all the bins for daily collection, 4.5% and 1.2% of travel distance and time respectively were saved. The results demonstrated that there is always room for optimization of solid waste collection routing irrespective of site constraints and other challenges that the nature of bin distribution pose to drivers. In developing countries like Ghana, where there is high demand for services in the face of limited road network access, application of GIS in optimization of routes will guide providers in planning and subsequently make more savings in fuel consumption, vehicle maintenance and cost of man-hours.

The underlying physical concept of computing out-of-time-ordered correlation (OTOC) is a significant new tool within the framework of quantum field theory, which now-a-days is treated as a measure of random fluctuations. In this paper, by following the canonical quantization technique we demonstrate a computational method to quantify the two different types of Cosmological auto-correlated OTO functions during the epoch when the non-equilibrium features dominates in Primordial Cosmology. In this formulation, two distinct dynamical time scales are involved to define the quantum mechanical operators arising from cosmological perturbation scenario. We have provided detailed explanation regarding the necessity of this new formalism to quantify any random events generated from quantum fluctuations in Primordial Cosmology. We have performed an elaborative computation for the two types of two-point and four-point auto-correlated OTO functions in terms of the cosmological perturbation field variables and its canonically conjugate momenta to quantify random auto-correlations in the non-equilibrium regime. For both the cases we found significantly distinguishable non-chaotic, but random behaviour in the OTO auto-correlations, which was not pointed before in this type of studies. Finally, we have also demonstrated the classical limiting behaviour of the mentioned two types of auto-correlated OTOC functions from the thermally weighted phase space averaged Poisson Brackets, which we found exactly matches with the large time limiting behaviour of the auto-correlations in the super-horizon regime of the cosmological scalar mode fluctuation.

Background: Aquaponics are food production systems advocated for food security and health. Their sustainability from a nutritional and plant health perspective is, however, a significant challenge. Recirculated aquaculture systems (RAS) form a major part of aquaponic systems, but knowledge about their potential to benefit plant growth and plant health is limited. The current study tested if the diversity and function of microbial communities in two commercial RAS were specific to the fish species used (Tilapia or Clarias) and sampling site (fish tanks and wastewaters), and whether they confer benefits to plants and have invitro antagonistic potential towards plant pathogens. Results: Microbial diversity and composition was found to be dependent on fish species and sample site. The Tilapia RAS hosted higher bacterial diversity than the Clarias RAS; but the latter hosted higher fungal diversity. Both Tilapia and Clarias RAS hosted bacterial and fungal communities that promoted plant growth, inhibited plant pathogens and encouraged biodegradation. The production of extracellular enzymes, related to nutrient availability and pathogen control, by bacterial strains isolated from the Tilapia and Clarias systems, makes them a promising tool in aquaponics and in their system design. Conclusions: This study explored the microbial potential of the commercial RAS with either Tilapia or Clarias as a tool to benefit the aquaponic system with respect to plant growth promotion and control of plant diseases.

Thai basil is a renowned medicinal plant and a rich source of bioactive antioxidant compounds having several health benefits, with actions to prevent of cancer, diabetes and cardiovascular disease. Plant cell and tissue culture technologies can be routinely established as an important, sustainable and low-cost biomass source for the production of high-value phytochemicals. The current study aimed at developing an effective protocol for the production of Thai basil leaf derived callus cultures with sustainable and high production of biomass and antioxidants as an alternative of leaves production. MS basal medium with various concentrations of plant growth regulators (PGRs) compatible with nutraceutical applications (i.e., gibberellic acid (GA3) and 6-benzylaminopurine (BAP) either alone or in combination with naphthalene acetic acid (NAA)) were evaluated. Among all tested PGRs, the combination BAP:NAA (5 mg/L:1 mg/L) yield maximum biomass accumulation (fresh weight (FW): 190 g/L and dry weight (DW): 13.05 g/L) as well as enhanced phenolic (346.08 mg/L) production. HPLC quantification analysis indicated high productions of chicoric acid (35.77 mg/g DW) and rosmarinic acid (7.35 mg/g DW) under optimized callus culture conditions. Antioxidant potential was assessed using both in vitro cell free and in vivo cellular antioxidant assays. Maximum in vitro antioxidant activity DPPH (93.2 % of radical scavenging activity) and ABTS (1322 µM Trolox equivalent antioxidant capacity) was also observed for the extracts from callus cultures grown on optimal conditions. In vivo cellular antioxidant activity assay confirmed the effective protection against oxidative stress of the corresponding extract by the maximum inhibition of ROS and RNS production. Compared to commercial leaves, callus extracts showed higher production of chicoric acid and rosmarinic acid associated with higher antioxidant capacity. In addition, this biological system also has a large capacity for continuous biomass production, thus demonstrating its high potential for possible nutraceutical applications.

Dalbergia sissoo (shisham), an important timber yielding multipurpose tree species of the Indian subcontinent, has been afflicted with large scale mortality due to wilt in natural forests and plantations, causing huge economic losses. Fusarium solani f. sp. dalbergiae (Fsd) has been identified as one of the causal organisms for wilt disease in D. sissoo. Present study comprises in vitro screening of ten selected genotypes of D. sissoo against two strains of Fsd in a dual culture set up under axenic condition. Callus and plantlets of ten genotypes of host plant were multiplied in vitro and were inoculated with conidial suspension of two strains of Fsd at three concentrations; 1× 10¹, 1× 10³, and 1× 10⁵ conidia/ml. Gnotobiotic evaluation of dual culture set up shows variations among D. sissoo genotypes in their response towards in vitro Fsd infection; and two genotypes (14 and 66) exhibited resistance against the pathogen strains. Callus of genotypes 14 and 66 significantly restricted the fungal mycelium growth whereas callus of remaining eight genotypes were completely infested by Fsd mycelium within 9 days. Similarly, plantlets of genotype 14 and 66, had lesser disease severity and remained green, and had fewer necrotic lesions in the roots whereas plantlets of remaining eight genotypes died within 15 days.

We have defined M cycles as modified form of Gleissberg cycles to study the quasi-periodic secular changes in sunspot activity. Using direct and proxy observations for more than 1200 years we have provided evidence for the influence of the above M cyles on the monsoon rainfall variability and occurrences of major droughts in India. The solar cycle averages of All Indian summer monsoon rainfall (AISMR) and probability of observation of below or above normal AISMR is found to show correlated variations with changes in amplitude of sunspot cycles during the years 1901-2018 AD. Major droughts in India show a preference to occur during minima and declining phases of the M cycles during the years 650-2018 AD . We could generally find low probability of occurrence of droughts in India during the medieval solar maximum epoch ( 1100-1250 AD) and during most of the prolonged sunspot minima periods including the Maunder minima. The evolution of mean Indian summer monsoon rainfall during 650-1900 AD is studied using proxy data from multiple sources with maxima during the 12^th century and minima during 14^th and 19^th centuries. The association of Indian droughts with El-Nino and the possibilities of long term prediction of Indian summer monsoon rainfall variability will be also discussed

There is a huge interest in developing novel hollow fiber (HF) membranes able to modulate neural differentiation to produce in vitro blood-brain barrier (BBB) models for biomedical and pharmaceutical research, due to the low cell-inductive properties of the polymer HFs used in current BBB models. In this work, poly(ε-caprolactone) (PCL) and composite PCL/graphene (PCL/G) HF membranes were prepared by phase inversion and were characterized in terms of mechanical, electrical, morphological, chemical, and mass transport properties. The presence of graphene in PCL/G membranes enlarged the pore size and the water flux and presented significantly higher electrical conductivity than PCL HFs. Biocompatibility assay showed that PCL/G HFs significantly increased C6 cells adhesion and differentiation towards astrocytes, may be attributed to their higher electrical conductivity in comparison to PCL HFs. On the other hand, PCL/G membranes produced a cytotoxic effect on the endothelial cell line HUVEC presumably related with a higher production of intracellular reactive oxygen species induced by the nanomaterial in this particular cell line. These results prove the potential of PCL HF membranes to grow endothelial cells and PCL/G HF membranes to differentiate astrocytes, the two characteristic cell types that could develop in vitro BBB models in future 3D co-culture systems.

In order to realize the tram's low-floor structure, most of the trams that have been recently introduced adopt an independently rotating wheelset. In the case of trains driving in two regions with different gauges, an independently rotating wheelset may be applied to utilize the variable track technology. Since the independent rotation type wheelset has no rotational restraint of the left and right wheels, the difference in rotational speed between the outer and inner wheels occurs naturally during curved driving, and it is applied to railroad vehicles traveling in steep curve sections because it smoothly drives curved driving. However, the longitudinal creep force and the lateral restoring force are weakened as the left and right rotational constraints disappear. Lack of transverse direction restoring force weakens stability while causing continuous flange contact driving or zigzag phenomenon against disturbance. Under the conditions of driving in a steep curve, these railway vehicles generate excessive wear, noise, and lateral pressure, as well as deterioration of ride comfort and derailment. In order to overcome these drawbacks, a method has been proposed in which the torque of a motor mounted on each wheel is individually controlled to generate lateral restoring force or to improve driving performance through lateral displacement control using a yaw moment. In this paper, development using HILs was performed to check the performance and stability of the individual motor torque control technology before verifying by applying the individual motor torque control to the actual vehicle. HILs were constructed by combining a real-time dynamic analysis model of a railway vehicle with a drive motor to which real individual motor control was applied. Under the conditions of driving the test track where the actual test vehicle was tested, the analysis of the driving characteristics and the control characteristics of the disturbance was performed to confirm the proposed individual motor torque control performance.

The introduction of the Internet of Things (IoT), i.e. the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like CCTV cameras, IP phones, and oscilloscopes, is overwhelming for end-users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world.

Automated controlling the harvesting systems can significantly increase the efficiency of the agricultural practices and prevent food wastes. Modeling and improvement of the combine harvester can increase the overall performance. Machine learning methods provide the opportunity of advanced modeling for accurate prediction of the highest performance of the machine. In this study, the modeling of combine harvesting id performed using radial basis function (RBF) and the hybrid machine learning method of adaptive neuro-fuzzy inference system (ANFIS) to predict various variables of the combine harvester for the optimal performance. Response surface methodology (RSM) is also used to optimize the models. The comparative study shows that the ANFIS method outperforms the RBF method.

Lemon balm extracts by dry plant material of Melissa officinalis were tested against their efficacy against for different fungal species Alternaria alternata, Fusarium oxysporum, Aspergillus flavus and Beauveria bassiana. The aqueous phase of the extract was evaluated for antioxidant, antifungal and also anti-aflatoxigenic activity. A synergism evaluation was also performed concerning, the small quantity of lemon balm polar essential oil compounds extracted into the infusion and the water soluble compounds in the extract. The experiments were conducted in solid cultures and the growth inhibition was demonstrated by measuring mycelial diameter. Additionally, the effect on conidia production was also demonstrated. Lemon balm was also used for in situ test on Pistachia vera seed against Aspergillus flavus growth and aflatoxin production. Results revealed enhancement of fungal growth by lemon balm extracts however total inhibition of aflatoxins production on Pistachia vera seeds was observed, and both actions were tried to attributed to volatile and water soluble compounds identified based on GC/MS, HPLC/DAD and LC/MS, and the observed antioxidant activity. Volatile and water - soluble compounds found to be in absolute synergism in mycelium growth enhancement and the observed anti-aflatoxigenic activity addressed to the high antioxidant activity observed and synergistic action between the other water soluble phenolic compounds identified in the extract. The findings of this study underline the high biological active potential of lemon balm extracts under various screening test since for the first time full phytochemical analysis of lemon balm extracts.

Structural information of biological macromolecules is crucial and necessary to deliver predictions about the effects of mutations—whether polymorphic or deleterious (i.e., disease causing), wherein, thermodynamic parameters, namely, folding and binding free energies potentially serve as effective biomarkers. It may be emphasized that the effect of a mutation depends on various factors, including the type of protein (globular, membrane or intrinsically disordered protein) and the structural context to which it occurs. Such information may positively aid drug-design. Furthermore, due to the intrinsic plasticity of proteins, even mutations involving radical change of the structural and physico-chemical properties of the amino acids (native vs. mutant) can still have minimal effects of protein thermodynamics. However, if a mutation causes significant perturbation of either folding or binding free energies, it is quite likely to be deleterious. Mitigating such effects is a promising alternative to the traditional approaches of designing inhibitors. This can be done by structure-based in silico screening of small molecules for which binding to the dysfunctional protein restores its wild type thermodynamics. In this review we emphasize on the effects of mutations on two important biophysical characteristics, stability and binding affinity, and how structures can be used for structure-based drug design to mitigate the effects of disease-causing variants on the above biophysical characteristics.

To obtain drop-in fuel properties from non-feed biomass, we herein report the catalytic hydrotreatment of microalgae biocrude, produced from hydrothermal liquefaction (HTL) of Spirulina. Our contribution focuses on the effect of temperature, initial H2 pressure, and residence time on the removal of heteroatoms (O and N). In contrast to common hydrotreating experimental protocols at batch scale, we devised a set of two-level factorial experiments and studied the most influential parameters affecting the removal of heteroatoms. It was found that up to 350 °C, the degree of deoxygenation (de-O) is mainly driven by temperature, whereas the degree of denitrogenation (de-N) also relies on initial H2 pressure and temperature-pressure interaction.Based on this, complete deoxygenation was obtained at mild operating conditions (350 °C), reaching a concurrent 47 % denitrogenation. Moreover, three optimized experiments are reported with 100 % removal of oxygen. In addition, the analysis by GC-MS and Sim-Dis gives insight to the fuel quality. The distribution of heteroatom N in lower (<340 °C) and higher (>340 °C) fractional cuts is studied by a fractional distillation unit following ASTM D-1160. Final results show that 63-68 % of nitrogen is concentrated in higher fractional cuts.

Almond is worldwide consumed and renowned as a valuable healthy food. In spite of this, it is also a potent source of allergenic proteins able to trigger several mild to life-threatening immunoreactions. Food processing proved to alter biochemical characteristics of proteins, thus affecting the respective allergenicity. In this paper we investigated the effect of autoclaving, preceded or not by a hydration step, on the biochemical and immunological properties of almond proteins. Any variation in the stability and immunoreactivity of almond proteins extracted from the treated materials, were evaluated by total protein quantification, ELISA assay and protein profiling by electrophoresis-based separation (SDS-PAGE). The autoclaving alone was found to weakly affect almond proteins stability, despite what observed for the combination of hydration and autoclaving, which resulted in a loss of approximately 70% of total protein content compared to untreated sample, and in a final negligible immunoreactivity, as well. The final SDS-PAGE protein pattern recorded for almonds hydrated and autoclaved disclosed significant changes. In addition, the same samples were further submitted to in vitro simulated gastro-duodenal (GI) digestion to evaluate potential changes induced by these processing on allergens digestibility. Digestion products were identified by HPLC-HRMS/MS analysis followed by software-based data mining, and complementary information were provided by analyzing the proteolytic fragments lower that 6 kDa in size. The autoclave based treatment was found not to alter the allergens digestibility, whereas an increased susceptibility to proteolytic action of digestive enzymes was observed in almonds subjected to the combination of prehydration and autoclaving. Finally, the residual immunoreactivity of the GI resistant peptides was investigated in-silico by bioinformatic tools, confirming that by following both approaches, no epitopes survived the almond digestion, thus demonstrating the potential effectiveness of these treatments to reduce almond allergenicity.

Corn fiber is a co-product of commercial ethanol dry-grind plants, which is processed into distillers dried grains with solubles (DDGS) and used as animal feed, yet it holds high potential to be used as feedstock for additional ethanol production. Due to the tight structural make-up of corn fiber, a pretreatment step is necessary to make the cellulose and hemicellulose polymers in the solid fibrous matrix more accessible to the hydrolytic enzymes. A pretreatment process was developed in which whole corn kernels were soaked in aqueous solutions of 2.5, 5.0, 7.5 and 10.0 wt% ammonia at 105oC for 24 h. The pretreated corn then was subjected to a conventional mashing procedure and subsequently ethanol fermentation using a commercial strain of natural Saccharomyces cerevisiae with addition of a commercial cellulase. Pretreatment of the corn with 7.5 wt% ammonia solution plus cellulase addition gave highest ethanol production, which improved the yield in fermentation using 25 wt% solid from 334 g ethanol/kg corn obtained in the control (no pretreatment and no cellulase addition) to 379 g ethanol/kg corn (a 14% increase). The process developed can potentially be implemented in existing dry-grind ethanol facilities as a “bolt-on” process for additional ethanol production from corn fiber, and this additional ethanol can then qualify as “cellulosic ethanol” by the EPA’s Renewable Fuels Standard and thereby receive RINS (Renewable Identification Numbers).

P-glycoprotein (P-gp), a membrane-bound transporter, can eliminate xenobiotics by transporting them out of the cells or blood-brain barrier (BBB) at the expense of ATP hydrolysis. Thus, P-gp mediated efflux plays a pivotal role in altering the absorption and disposition of a wide range of substrates. Nevertheless, the mechanism of P-gp substrate efflux is rather complex since it can take place through active transport and passive permeability in addition to multiple P-gp substrate binding sites. A nonlinear quantitative structure-activity relationship (QSAR) model was developed in this study using the novel machine learning-based hierarchical support vector regression (HSVR) scheme to explore the perplexing relationships between descriptors and efflux ratio. The predictions by HSVR were found to be in good agreement with the observed values for the molecules in the training set (n = 50, r² = 0.96, q²_CV = 0.94, RMSE = 0.10, s = 0.10) and test set (n = 13, q² = 0.80–0.87, RMSE = 0.21, s = 0.22). When subjected to a variety of statistical validations, the developed HSVR model consistently met the most stringent criteria. A mock test also asserted the predictivity of HSVR. Consequently, this HSVR model can be adopted to facilitate drug discovery and development.

Breast cancer treatment mostly revolved around radiation therapy and surgical interventions, these treatments doesn’t provide satisfactory relief to the patients and carry unmanageable side-effects. Nanomaterials show promising results in treating cancer cells and have many advantages such as high biocompatibility, bioavailability and effective therapeutic capabilities. Interestingly, fluorescent magnetic nanoparticles have been used in many biological and diagnostic applications, but there is no report of use of fluorescent magnetic submicronic polymer nanoparticles (FMSP-nanoparticles) in the treatment of human breast cancer cells. In the present study, we have tested the effect FMSP-nanoparticles on human breast cancer cells (MCF-7). We have tested different concentrations (1.25µg/1mL, 12.5µg/mL and 50µg/1mL) of FMSP-nanoparticles in MCF-7 cells and evaluated the nanoparticles response morphometrically. Our results revealed that FMSP-nanoparticles produced a concentration dependent effect on the cancer cells, dose of 1.25µg/mL produced no significant effect on the cancer cell morphology and cell death, whereas dosages of 12.5µg/mL and 50µg/mL respectively showed significant nuclear augmentation, disintegration, chromatic condensation followed by dose dependent cell death. Our results demonstrate FMSP-nanoparticles have ability to induce cell death in MCF-7 cells and may be considered as a potential anti-cancer agent for breast cancer treatments.

Myocardial infarction, more commonly known as heart attack, is a huge health problem around the world. It is a result of inadequate blood supply to certain parts of the heart and death of heart muscle cells in that region. Although it has been around for a long time, newer and newer ways of probing myocardial infarction is being followed. Bioinformatics and Systems Biology are relatively recent fields to try to give new insights into myocardial infarction. Following the footsteps of others, this in silico study has tried to chime in on the investigation into myocardial infarction. The study began with the gene expression omnibus dataset uploaded to the NCBI from a whole-genome gene expression analysis carried out at Mayo Clinic in Rochester, Minnesota. From the dataset, differentially expressed genes following first-time myocardial infarction were identified and classified into up-regulated and down-regulated ones. Gene Set Enrichment Analysis (GSEA) was carried out on the up-regulated genes which were statistically significant and corresponded with the NCBI generated annotations. Protein-Protein Interaction Network for these genes was constructed. GSEA revealed 5 transcription factors, 5 microRNAs and 3 pathways significantly associated with them. From the Protein-Protein Interaction Network, 6 key proteins (hub nodes) have been identified. These 6 proteins may open a new window of opportunity for the discovery/design of new drugs for mitigating the damage caused by myocardial infarction.

Arabic was the language of philosophy, logic, Islamic sciences and rhetorical linguistic sciences. It was used in the writing of all sciences generally and became the language of world culture. Although the other languages of the Islamic world had a little share, but all peoples of Islamic countries; Arabs and non-Arabs, Muslims and non-Muslims attributed to that movement appreciated. Hence, Arab sciences flourished in their bright ages. Arabic language was a cultural container of the ancient Greek and Latin intellectual heritage. As the ancient Greek and Latin sciences and literatures were translated into Arabic in the bright ages of Islam. Arab language was a strong bond for them, as a common human heritage for the centuries to save it from being lost, as Muslims used it to develop their sciences and arts, as Muslims in the East used the Western sciences and literatures in the modern age, because they are not Eastern or Western, but the common efforts of all humanity. Arabic language opened for the dictionaries ​​and other tongues of cross-fertilization, civil friction and simulation. Arabic had become the language of sciences: mathematics, astronomy, engineering, logic, philosophy, mysticism, agriculture, industry and economics by the continuous efforts of scientists in their scientific research, invention, experimentation, knowledge collection and classification in various fields, where orientalists recognized the Arab leadership. That scientific and literary civilization moved to Europe through Italy, Andalusia, Crusades and the Ottoman Caliphate. Europeans learned Arabic language, literature and sciences in the centers of Toledo, Fez and cities of Maghreb.

That how to improve the sensitivity and the detection ability of the Large-caliber sensor is critical to satisfy the requirement of heavy vehicle wear condition monitoring. In this paper, we introduced the LC resonance principle to the design of sensor with large flow channel (7mm). The resonant exciting coil increases the impedance change of the exciting circuit caused by wear particles which magnify the current difference between the two exciting coils and improve the sensitivity of the sensor. The resonant induction coil greatly suppresses the interference signals and magnifies the weak induced electromotive force which is beneficial to enhance the detection ability. In order to boost the detectability for different materials particles, a phase controlled variable-frequency exciting system (PCVFES) was adopted to automatically switch the exciting frequency between 284kHz for ferromagnetic particles and 420KHz for non-ferromagnetic particles. For the weak signal detection, based on the essential characteristic of the signal, we apply a simpler method that modified lock-in amplifier (MLIA) rather than the conventional algorithms (Wavelet transform, EMD). Results show that using these methods the sensitivity and the detection ability of the sensor are significantly improved and the 75μm iron particles and 220μm copper particles were successfully detected which realizes the initial abnormal wear monitoring for the large flow project.

Warren Weaver, writing about the function that science should have in mankind’s developing future, ideas and ideals, proposed to classify scientific problems into ‘problems of simplicity’, ‘problems of disorganised complexity’, and ‘problems of organised complexity’ — the huge complementary class to which all biological, human, and social problems belong. Problems of simplicity have few components and variables and have been extensively addressed in the last 400 years. Problems of disorganised complexity have a huge number of individually erratic components and variables, but possess collective regularities that can be analysed by resourcing to stochastic methods. Yet, problems of organised complexity do not yield easily to classical or statistical treatment since interrelations among phenomenon elements change during its evolution alongside commonly used state variables, affecting behaviour and outcome. Moreover, organisation, the focal point in this complementary class, is still an elusive concept despite the gigantic efforts undertaken since a century ago to tame it. This paper addresses the description, representation and study of phenomena in the ‘problems of organised complexity’ class. Grounded on relational mathematical constructs, a theoretical framework providing operational definitions and schemes for formally modelling organisations and interaction of organisations is introduced. This framework extends the general systems’ concept and provides a novel perspective for addressing organised complexity phenomena as a collection of interacting organisations.

Metalloproteinases are zinc-dependent endopeptidases that function as primary effectors of tissue remodelling, cell-signalling, and many other roles. Their regulation is ferociously complex, and is exquisitely sensitive to their molecular milieu, making in vivo studies challenging. Phenanthroline (PhN) is an inexpensive, broad-spectrum inhibitor of metalloproteinases that functions by chelating the catalytic zinc ion, however its use in vivo has been limited due to suspected off-target effects. PhN is very similar in structure to phenanthrene (Phe), a well-studied poly aromatic hydrocarbon (PAH) known to cause toxicity in aquatic animals by activating the aryl hydrocarbon receptor (AhR). We show that zebrafish are more sensitive to PhN than Phe, and that PhN causes a superset of the effects caused by Phe. Morpholino knock-down of the AhR rescues the effects of PhN that are shared with Phe, suggesting these are due to PAH toxicity. The effects of PhN that are not shared with Phe (specifically disruption of neural crest development and angiogenesis) involve processes known to depend on metalloproteinase activity. Furthermore these PhN-specific effects are not rescued by AhR knock-down, suggesting that these are bona fide effects of metalloproteinase inhibition, and that PhN can be used as a broad spectrum metalloproteinase inhibitor for studies with zebrafish in vivo.

When the distance between an obstacle and a power line is less than the discharge distance, a discharge arc can be generated, resulting in interruption of power supplies. Therefore, regular safety inspections are necessary to ensure safe operations of power grids. Tall vegetation and buildings are the key factors threatening the safe operation of extra high voltage transmission lines within a power line corridor. Manual or LiDAR based-inspections are time consuming and expensive. To make safety inspections more efficient and flexible, a low-altitude unmanned aerial vehicle remote-sensing platform equipped with optical digital camera was used to inspect power line corridors. We propose a semi-patch matching algorithm based on epipolar constraints using both correlation coefficient and the shape of its curve to extract three dimensional (3D) point clouds for a power line corridor. Virtual photography was used to transform the power line direction from approximately parallel to the epipolar line to approximately perpendicular to epipolar line to improve power line measurement accuracy. The distance between the power lines and the 3D point cloud is taken as a criterion for locating obstacles within the power line corridor automatically. Experimental results show that our proposed method is a reliable, cost effective and applicable way for practical power line inspection, and can locate obstacles within the power line corridor with measurement accuracies better than ±0.5 m.

Aquaculture is rapidly becoming one of the pivotal sectors in the farm economy, driven by the increasing demand for high-quality animal protein at an affordable cost, especially with the escalating human population. However, the expansion of high-density fish populations also brings forth a challenge – the rapid transmission and spread of infectious disease agents among them. To combat this, vaccination is emerging as a reliable and standardized method for providing immunity against viral and bacterial outbreaks. The ideal vaccine is expected to be safe, effective, economical, and easily administered. The fish vaccination industry continually publishes new information on fish immunology and vaccinology, contributing to the improvement of vaccine formulation and efficacy. This review aims to offer insights into the current status of bacterial, viral, and parasitic diseases, discuss existing vaccinations, and address potential industry-threatening diseases like infectious edwardsiellosis, motile aeromonas septicemia, TiLV, salmon anemia, vibriosis, and white spot disease. Technological advancements have played a crucial role in enhancing our understanding of fish immunological mechanisms, leading to improved vaccine administration and the development of recombinant live attenuated, subunit, DNA, and RNA vaccines. However, challenges such as oral tolerance, vaccine degradation, and stressful environments persist, impacting vaccine efficacy. Addressing these challenges and gaining a deeper understanding of the fish immune system and host-pathogen interactions will be pivotal for future improvements, contributing to the sustainability of aquaculture and enhancing global food security.

Quantum mechanics could be studied through polynomial algebra, as has been demonstrated by a work (“An approach to first-principles electronic structure calculation by symbolic-numeric computation” by A. Kikuchi). We carry forward the algebraic method of quantum mechanics through algebraic number theory; the basic equations are represented by the multivariate polynomial ideals; the symbolic computations process the ideal and disentangle the eigenstates as the algebraic variety; upon which one canbuild the Galois extension of the number field, in analogy with the univariate polynomial case, to investigate the hierarchy of solutions; the Galois extension is accompanied with the group operations, which permute the eigenstates from one to another, and furnish the quantum system with a non-apparent symmetry. Besides, this sort of algebraic quantum mechanics is an embodiment of the class field theory; some of the important consequences of the latter emerge in quantum mechanics. We shall demonstrate these points through simple models; we will see the use of computational algebra facilitates such sort of analysis, which might often be complicated if we try to solve them manually.

Alkyl moieties—open chain or cyclic—are common in drug molecules and can be internal or terminal. The open-chain alkyls can be linear or branched; the cyclic alkyls may be substituted. Usually, the branches in open-chain alkyls and substituents in cycloalkyls influence both the pharmacokinetics and pharmacodynamics of a drug molecule. The hydrophobicity of alkyl moieties in drug molecules is modified by metabolic hydroxy functionalization via free-radical intermediates to give primary, secondary, or tertiary alcohols depending on the class of the substrate carbon. The hydroxymethyl groups resulting from the functionalization of methyl groups are mostly oxidized further to carboxyl groups to give carboxy metabolites. As observed from the surveyed cases in this review, hydroxy functionalization leads to loss, attenuation, or retention of pharmacologic activity with respect to the parent drug. On the other hand, carboxy functionalization leads to a loss of activity with the exception of only a few cases in which activity is retained. The exceptions are those groups in which the carboxy functionalization occurs at a position distant from a well-defined primary pharmacophore. Some parent-drug equiactive hydroxy metabolites have been developed into metabolite ester prodrugs, while some of the parent-drug carboxy metabolites have been developed into metabolite drugs. In this review, we present and discuss the above state of affairs for a variety of drug classes, using selected drug members to show the effect on pharmacologic activity as well as dependence of the metabolic change on drug molecular structure. Some subtexts found to manifest from the hydroxy and carboxy functionalization of alkyl moieties in drug molecules are presented and discussed. The review provides basis for informed predictions of (i) structural features required for metabolic hydroxy and carboxy functionalization of alkyl moieties in existing or planned small drug molecules; and (ii) whether the resulting metabolites will possess pharmacologic activity or be devoid of it.

Abstract: Autoimmune diseases (AIDs) are a group of disorders, in which the immune system attacks the body own tissues leading to chronic inflammation and organ damage. These diseases are difficult to treat due to variability in drug PK among individuals, patient responses to treatment, and the side effects of long-term immunosuppressive therapies. In recent years, pharmacometrics has emerged as a critical tool in Drug Discovery and Development (DDD) and precision medicine. The aim of this review is to explore the diverse roles that pharmacometrics has played in addressing the challenges associated with DDD and personalized therapies in the treatment of AIDs. Methods: The review synthesizes research from past two decades on pharmacometric methodologies, including Physiologically Based Pharmacokinetic (PBPK) modeling, Pharmaco-kinetic/Pharmacodynamic (PK/PD) modeling, Disease Progression (DisP) modeling, population modeling, and Quantitative Systems Pharmacology (QSP). The incorporation of Artificial Intelli-gence (AI) and Machine Learning (ML) into pharmacometrics is also discussed. Results: Pharmacometrics has demonstrated significant potential in optimizing dosing regimens, improving drug safety, and predicting patient-specific responses in AIDs. PBPK and PK/PD models have been instrumental in personalizing treatments, while DisP and QSP models provide insights into disease evolution and pathophysiological mechanisms in AIDs. AI/ML implementation has further enhanced precision of these models. Conclusions: Pharmacometrics plays a crucial role in bridging preclinical findings and clinical applications, driving more personalized and effective treatments for AIDs. Its integration into DDD and translational science in combination with AI and ML algorithms holds promise for advancing therapeutic strategies and improving autoimmune patient outcomes.

Basic education is a foundational component of the national education system and human resource development, providing crucial support for the sustainable development of various aspects of human society, including economy, social welfare, and technology. The advancement of basic education is intrinsically linked to national innovation, the well-being of the populace, and the sustainable high-quality development of society. Enhancing the ecological carrying capacity of basic education at the provincial level is critical and pragmatically significant for the coordinated, sustainable, and high-quality development of the region's socioeconomic landscape.Based on panel data from the Guangxi Zhuang Autonomous Region (hereinafter referred to as Guangxi) from 2013 to 2022, and utilizing the DPSIR theoretical model, a comprehensive evaluation index system has been established. Through statistical analysis and spatial analysis methods, this study explores the temporal and spatial evolution characteristics of the ecological carrying capacity of basic education in various regions under Guangxi's jurisdiction. A multiple linear regression model is employed to analyze the differential impacts of changes in economic structure on the ecological carrying capacity of basic education.The findings reveal a steady upward trend in the ecological carrying capacity of basic education across the municipal districts of Guangxi. The development of five subsystems—Pressure, Driving-force, and others—has also become increasingly balanced; however, the impact of each subsystem on the overall carrying capacity varies. From a formation mechanism perspective, the ecological carrying capacity of basic education in Guangxi is the result of the complex interactions of multiple factors, with notable differences in influencing factors at various stages of development.Therefore, to bridge the regional disparities in the ecological carrying capacity of basic education across the different areas of Guangxi, it is essential to adopt a range of measures that promote coordinated, balanced, and high-quality educational development among regions, effectively ensuring the long-term sustainable development of Guangxi's economy and society.

Transition zones are in the places on the track, with a change in the basic composition of the railway body. There are many sections with a sudden change in the stiffness of the structures built. When the trains are running, a longitudinal shock wave is created from the wheels, which hits these building objects with a higher stiffness and deforms the surroundings of these zones. The greatest attention should be paid mainly to the transition points from the fixed track to the classic track with a track bed, including objects of the railway substructure such as bridges, portals of tunnels, etc. As part of the research sections on the main corridor lines, a long-term inspection and monitoring was carried out with a continuous measurement system using the KRAB trolley. Height changes in the deflections of rails are evidence of their behavior. The measurements took place on a fixed track and a track with a ballast. Changes in the height jumps between the fixed railway track and the track with a gravel bed are significant and have been recorded since the tracks were put into operation. These certain height deflections allow designers to develop new, more durable construction designs.

This paper explores how smart cities can cope with land subsidence and liquefaction in the context of rapid urbanization in Japan. Since the 1960s, liquefaction has become an important topic in geotechnical engineering, and great efforts have been made to evaluate the resistance of soil to liquefaction. There is currently a lack of machine learning applications specifically for smart cities in areas such as geological hazards. This study uses two machine learning techniques, artificial neural networks and ensemble learning, to obtain a prediction model with high performance in predicting the bearing layer depth to improve the accuracy of geo-engineering surveys. The model was developed by analyzing actual survey data from 433 locations in Setegaya, Tokyo, by using artificial neural networks (ANNs) and bagging, respectively. The results show that machine learning has great advantages in predicting the bearing layer depth. In addition, compared with a single model such as artificial neural networks, the prediction performance of ensemble learning can be improved by about 20%. Both interdisciplinary approaches can help predict address risks and thus promote sustainable urban development, highlighting the potential of smart cities in the future.

Background: Heracleum sphondylium, a medicinal plant used in Romanian ethnopharmacology, proved to have a remarkable biological activity. The escalating concerns surrounding antimicrobial resistance led to a special attention to new efficient antimicrobial agents based on medicinal plants and nanotechnology. We report the preparation of a novel, simple phytocarrier that harnesses the bioactive properties of H. sphondylium and silver nanoparticles (HS-Ag system). Methods: The H. sphondylium low-metabolic profile was determined through gas chromatography–mass spectrometry and electrospray ionization–quadrupole time-of-flight–mass spectrometry. The morphostructural properties of the innovative phytocarrier were analyzed by X-ray diffraction, Fourier-transform infrared spectroscopy, Raman spectroscopy, dynamic light scattering, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The antioxidant activity was evaluated using total phenolic content, ferric reducing antioxidant power, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) in vitro assays. The antimicrobial activity screening against Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, and Escherichia coli was conducted using the agar well diffusion method. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay estimated the in vitro potential cytotoxicity on normal human dermal fibroblasts (NHDF) and cervical cancer (HeLa) cells. Results: A total of 88 biomolecules were detected, such as terpenoids, flavonoids, phenolic acids, coumarins, phenylpropanoids, iridoids, amino acids, phytosterols, fatty acids. HS-Ag phytocarrier heightened efficacy in suppressing the growth of all tested bacterial strains compared to H. sphondylium and exhibited a significant inhibition of HeLa cell viability. Conclusions: The new HS-Ag phytocarrier system holds promise for a wide range of medical applications. The data confirms the capacity to augment pertinent theoretical understanding in the innovative field of antimicrobial agents.