In recent years, nocturnal ozone enhancement(NOE) events have become a hot research topic in the field of atmospheric environment. By using statistically-based data analysis, we made a comparative investigation about nocturnal ozone concentrations and NOE events in 2022 and 2023, and further explored the effects of NOE events on O3 and PM2.5 at the night of the same day and the next day. The results showed that from 2022 to 2023 in Dongying, the annual average nocturnal ozone concentrations increased from 51 μg/m3 to 59 μg/m3, and the frequency of NOE events was higher in spring, summer and autumn, and lower in winter. NOE events not only had an obvious promoting effect on nocturnal O3 and Ox, and the daily maximum 8 h average concentration of O3 (MDA8-O3) of the same day (more apparent in summer and autumn), and nocturnal PM2.5 and PM2.5-bounded NO3- and SO42- (more apparent in winter), but also had a distinct influence on O3, Ox and MDA8-O3 of the next day (more apparent in summer). The results could strengthen the understanding of the phenomena of NOE events, and provide a scientific basis for the collaborative control of PM2.5 and ozone in urban areas in the Yellow River Delta, China.

(1) Background: “Zero-dose” (ZD) refers to a child not receiving any doses of the pentavalent (diphtheria-tetanus-pertussis-Haemophilus influenzae type b (Hib)-Hepatitis B) vaccine in the routine national immunization schedule. These children are vulnerable to vaccine-preventable diseases (VPDs), and are often already disadvantaged due to poverty, conflict, and lack of access to basic health services. The Luambo health district (HD) is one of the 26 HDs in the Kasai Central Province and has the largest number of ZD children. This study was conducted to examine the factors associated with ZD status in the Luambo HD; (2) Methods: We conducted a mixed study of children aged 12-23 months in the Luambo HD in the Kasai Central Province; (3) Results: A total of 445 children aged 12-23 months were included in the study, including 89 cases and 356 controls. Correlates of zero dose (ZD) status in children aged 12-23 months were mothers who were not receiving Antenatal Care (ANC), of not knowing any VPD, the fact of the children being born in Angola and the fact of the children being born at home. In addition, the perceptions of children’s parents influenced child immunization; (4) Conclusions: Missing ANC services during pregnancy leads to home delivery with consequences being lack of knowledge on childhood’s VPD and subsequently children not being vaccinated.

Reconstructing a 3D model of a scene from a set of multiple views poses a significant challenge in the field of computer vision. The advent of NeRF has marked a major breakthrough in this domain. However, there is a need to extend the capabilities of the NeRF model to enable editing tasks such as relighting and deformation, as well as to enhance its training efficiency. Neural reflectance fields introduce the concept of the reflectance equation into the NeRF framework to achieve relighting of the NeRF model. We leverage the TensoRF approach, which incorporates tensor decomposition and employs multiple tensors to store features, to expedite the training process of the NeRF model. Our novel method, called StensorR, combines the reflectance equation and tensor decomposition within the radiation field model framework. Differing from previous approaches, we employ a single tensor to store scene features and render the surface color of our scene using a simplified reflectance equation. This approach accelerates model convergence and enables relighting of the NeRF model. Experimental results demonstrate that our method achieves a 50% faster convergence rate compared to existing relighting radiation field models, while successfully enabling relighting and improving the quality of synthesized images from new viewpoints.

Introduction: Maturity-onset diabetes of the young (MODY) represents the most frequent form of monogenic diabetes mellitus (DM), currently classified in 14 distinct subtypes according to single gene mutations involved in the differentiation and function of pancreatic β-cells. Case report: The female patient at the age of 16 years old was diagnosed with non-autoimmune DM with glycated haemoglobin (HbA1c) value of 6.5%. After 6 years of dietary and lifestyle interventions due to the worsening of the glycometabolic profile, oral hypoglicemic therapy was initiated including at first only metformin, and subsequently also sulfonylureas and DPP-IV inhibitor. 11 years after diagnosis glargine insulin was started, associated 3 years later with Lispro insulin because of the worsening of the post-prandial glycaemia. According to the genetic testing a compound heterozygosis of two novel variants of uncertain/unknown clinical significance of BLK and RFX6 genes, respectively c.1013T>C (Ile338Thr) and c.1072G>A (Val358Ile), was identified. The RFX6 variant was also detected in the patient’s mother genome, while the BLK variant in her father’s. Discussion: Up to 11% of MODY has unknown etiology, suggesting that the genetic landscape is still to be explored. Recently, novel causal genes, involved in the differentiation and function of β-cells, have been identified such as RFX6, NKX2.2, NKX6.1, WFS1 and PCBD1. Genetic and clinical features of MODY variants remain highly heterogeneous, with no direct genotype-phenotype correlation especially in the low-penetrant subtypes. Thus, the aim of our paper is to present additionally to such rare case of a compound heterozygosity BLK/RFX6 underlying MODY, also a brief review of literature focused on the rare and reduced-penetrant variants, as well as on some controversies regarding this subtype of monogenic diabetes. Conclusions: Due to the limited data available, the assessment of MODY related-genes pathogenicity remains challenging especially in the setting of rare and low-penetrant subtypes. In consideration of the crucial importance of an accurate diagnosis, prognosis and management of MODY, more studies are warranted to further investigate its genetic landscape, the genotype-phenotype correlation, as well as the pathogenetic contribution of the non-genetic modifiers in this cohort of patients.

By combining general relativity and CPT symmetry, the theory of CPT gravity predicts gravitational repulsion between matter and CPT-transformed matter, i.e. antimatter inhabiting an inverted space-time. Such repulsive gravity turned out to be an excellent candidate for explaining the accelerated expansion of the Universe, without the need for dark energy. The recent results of the ALPHA-g experiment, which show gravitational attraction between antihydrogen atoms and the Earth, seem to undermine this success in the cosmological field. Analyzing the above theory, we find two solutions that can be consistent with the experimental results, while preserving the large-scale gravitational repulsion. The first highlights how repulsive gravity can be the result of the interaction with an inverted space-time, but occupied by matter and not antimatter, and therefore the antimatter present in our space-time has no reason to exhibit gravitational repulsion. The second retains the original CPT transformation, resulting in repulsive gravity between matter and antimatter, but with the caveat that antimatter immersed in our space-time cannot exhibit the PT transformation which is the cause of the repulsion. Finally, it is shown that, in a Newtonian approximation of the geodesic equation, time reversal is not a necessary operation for repulsive gravity, therefore opening the possibility of an expanding cosmos with a single time direction.

Abstract: Mast cell (MC) specific proteases are of particular interest for space biology and medicine due to their biological activity in regulating targets of a specific tissue microenvironment. MC tryptase and chymase obtain the ability to remodel connective tissue through direct and indirect mechanisms. Yet, MC specific protease expression under space flight conditions has not been adequately investigated. Using immunohistochemical stainings, we analyzed in this study the protease profile of the jejunal, gastric and hepatic MC populations in three groups of Mongolian gerbils - vivarium control, synchronous experiment, and 12-day orbital flight on the Foton-M3 spacecraft, - and in two groups - vivarium control and anti-orthostatic suspension - included in the experiment simulating effects of weightlessness in the ground-based conditions. After a space flight, there was a decreased number of MCs in the studied organs combined with an increased proportion of chymase-positive MCs and MCs with a simultaneous content of tryptase and chymase; the secretion of specific proteases into the extracellular matrix increased. These changes in the expression of proteases were observed both in the mucosal and connective tissue MC subpopulations of the stomach and jejunum. Notably, the relative content of tryptase-positive MCs in the studied organs of the digestive system decreased. Space flight conditions simulated in the synchronous experiment caused no similar significant changes in the protease profile of MC populations. The space flight conditions resulted in an increased chymase expression combined with a decreased total number of protease-positive MCs apparently due to participating in the processes of extracellular matrix remodeling and regulating the state of the cardiovascular system.

This qualitative study conducted at St. Michael's College explores the integration of philosophical dimensions in arts and sciences education and its implications for pedagogy and student learning. Drawing on three theoretical framework informed by Piaget, Sartre, and Vigotsky, the study examines the perspectives of 30 participants, including teachers and students, through semi-structured interviews. The findings reveal diverse viewpoints, with some participants emphasizing disciplinary specialization for focused skill development, while others advocate for integrating philosophical dimensions to enhance critical thinking, interdisciplinary connections, and ethical awareness. The implications highlight the importance of balancing disciplinary depth with interdisciplinary exploration in arts and sciences education. Educators are encouraged to recognize the value of disciplinary specialization while integrating philosophical dimensions to foster critical thinking skills, interdisciplinary connections, and ethical awareness among students. Recommendations include providing professional development opportunities for educators, incorporating philosophical perspectives in curriculum frameworks, and exploring the long-term impact of integrating philosophical dimensions on student learning outcomes. Future research should investigate specific pedagogical approaches, consider cultural and contextual factors, and further explore the impact of integrating philosophical horizons to advance educational practices. By embracing the integration of philosophical dimensions, educators can create meaningful learning experiences that promote critical thinking, interdisciplinary connections, and ethical awareness in arts and sciences education.

In recent years, more and more attention has been paid to the behavior of tourists and their intention to travel after certain natural disasters or social unrest. The aim of the research was to establish the influence of psychological profiles of tourists on their decision to choose a tourist destination, using three psychographic techniques BFI-10 (Big Five Inventory), AIO (Activities, Interests, Opinions), and VALS 2 (Values and lifestyle), and a freely determined six-level scale of risk and tourist attractiveness of the imagined destinations. By analyzing the results through structural modeling-path analysis, it was determined that almost all psychographic orientations derived from lifestyles negatively perceive destinations with a high degree of risk and attractiveness, while with the VALS 2 technique, only members of the action orientation tend to accept the risk and challenge of visiting high-risk destinations. The results of the research have a degree of innovation in the application of the combination of the mentioned models, as well as in the theoretical and applied aspects in supplementing the building and strategic planning of the future business.

CAR-T therapy has achieved considerable treatment success in hematologic tumors by using patient derived autologous αβ T cells. There is an impetus to broaden the applicability of this approach by using a third-party donor derived CAR-T cell product which has a potent anti-tumor function but a constrained GVHD property. In this study, CAR-T cells were prepared from Vγ9Vδ2 T cells expanded by using a novel prodrug PTA and their anti-tumor functions were assessed in conjunction with persistency, localization, and phenotype. γδ T cells were successfully transduced with a CAR specific to CEA with signaling domains of CD3ζ and CD28 (CEA.CAR-γδ T cells), and exhibited potent tumor killing function in vitro. In a xenograft mouse model, CEA.CAR-γδ T cells suppressed CEA+ tumor growth though a limited time window. CEA.CAR-γδ T cells persisted and accumulated in the tumor even after tumor progression, however, ex vivo analysis revealed that those recovered at different time points from PBMC, spleen and tumors gradually lost tumor reactivity as assessed by IFN-γ production. Provision of GITR co-stimulation enhanced anti-tumor function of CEA.CAR-γδ T cells, the result of which imposes additional measurers to be adopted in CAR-γδ T cells for an allogeneic adoptive immunotherapy.

CD39 is involved in adenosine metabolism through conversion of extracellular ATP to adenosine. Because extracellular adenosine plays a critical role in the immune suppression of tumor microenvironment, the inhibition of CD39 activity by monoclonal antibodies (mAbs) is one of the important strategies for tumor therapy. In this study, we developed specific and sensitive mAbs for mouse CD39 (mCD39) using the Cell-Based Immunization and Screening (CBIS) method. The established anti-mCD39 mAbs, which were established by the CBIS method including C₃₉Mab-1 (rat IgG_2a, kappa) and C₃₉Mab-2 (rat IgG_2a, lambda), reacted with not only mCD39-overexpressed Chinese hamster ovary-K1 (CHO/mCD39) but also endogenously mCD39-expressed cell lines, such as L1210 (mouse lymphocytic leukemia) and J774-1 (mouse macrophage-like) cell lines through flow cytometry. Kinetic analyses using flow cytometry indicated that the dissociation constant (K_D) of C₃₉Mab-1 and C₃₉Mab-2 for CHO/mCD39 was 7.3 × 10⁻⁹ M and 5.5 × 10⁻⁹ M, respectively. K_D of C₃₉Mab-1 and C₃₉Mab-2 for L1210 was 3.3 × 10⁻⁹ M and 3.6 × 10⁻¹⁰ M, respectively. Furthermore, C₃₉Mab-1 could detect the lysate of CHO/mCD39 by western blot analysis. These results indicate that C₃₉Mab-1 and C₃₉Mab-2 are useful for the detection of mCD39 in many functional studies.

Abstract: Background: Stigma in health can result in a broad range of vulnerabilities and risk for patients and healthcare providers. The media plays a role in people’s understanding of health and stigma is socially constructed through many communication channels including via media framing. Among health issues that were affected by stigma recently were the Monkeypox and Covid-19. Objectives: This research aims to examine how The Washington Post framed stigma around mon-keypox and COVID-19. Guided by the framing theory and stigma theory, online news coverage for monkeypox and COVID-19 were analyzed to understand the construction of social stigma through the media reporting. Methods: This research employed a qualitative content analysis to compare news framing in The Washington Post online news regarding monkeypox and COVID-19. Results: Based on endemic, reassurance, and sexual transmission frames, the The Washington Post predominantly defined Africa as the source of the disease, blames gay communities, and empha-sizes no need to worry about the spread of the monkeypox virus. For the COVID-19 coverage, The Washington Post described China as the source of the coronavirus and constructs the image of panic towards the spread of the virus. Conclusions: The shifts in stigma discourse essentially manifest racism, xenophobia, and sexism in public health. This research affirms that the media reinforces stigma phenomenon in health through framing and offers constructive suggestions for mitigating this issue.

Spodoptera frugiperda is an invasive pest that has spread in various parts of the world. These pests have the ability to spread and adapt highly to new habitats. Until now, it is not known with certainty the distribution of these invasive pests in Eastern Indonesia, especially Bali and Nusa Tenggara. This study aims to map the spatial distribution and genetic distribution of S. frugiperda which damages maize in the areas of Bali and Nusa Tenggara. This research was conducted using a survey method from May to September 2022 covering the islands of Bali, Lombok, Sumbawa, Sumba, Flores, and Timor. The results showed that S. frugiperda had spread evenly in Bali and Nusa Tenggara. The results of PCR amplification in the COI gene from 9 sample isolates from all research locations showed the similarity of DNA bands leading to the Spodoptera frugiperda species with a banding pattern length of 683 – 697. These results indicated that the distribution of genetic variants of corn caterpillars in Bali, NTB, and NTT was confirmed as S. frugiperda species. However, the isolated gene S. frugiferda, which was shown by the alignment results of the sequences from Lombok, was confirmed as a different strain from strains from Bali, Sumba, Sumbawa, Flores, and Timor. This incident can be seen from the difference in the protein base composition of S. frugiperda from Bali, Sumba, Sumbawa, Timor, and Flores. The results of phylogenetic analysis in this study confirmed 3 clusters of the genetic closeness of S. frugiperda. Cluster-1 comes from the results of the search for specimens of JB FAW and KB FAW from Bali, SB FAW and SB FAW Sorghum from Sumba, SW FAW from Sumbawa, KP FAW from Timor, and FL FAW from Flores. Cluster-2 is an isolate outside of our species. Cluster-3 comes from the search for LT and LS FAW specimens from Lombok. The genetic distance between cluster-1 and cluster-3 is quite far, which is 0.20 mu.

We studies the initial value problem for the fractional Navier-Stokes-Coriolis equations, which obtained by replacing the Laplacian operator in the Navier-Stokes-Coriolis equation by the more general operator $(-\Delta)^\alpha$ with $\alpha>0$. We introduce function spaces of the Besove type characterized by the time evolution semigroup associated with the general linear Stokes-Coriolis operator. Next, we establish the unique existence of global in time mild solutions for small initial data belonging to our function spaces characterized by semigroups in both the scaling subcritical and critical settings.

In this paper defines the consecutive sum of the digits of a natural number, so far as it becomes less than ten, as an arithmetic function called and then introduces some important properties of this function by proving a few theorems in a way that they can be used as a powerful tool in many cases. As an instance, by introducing a test called test, it has been shown that we are able to examine many algebraic equalities in the form of in which and are arithmetic functions and to easily study many of the algebraic and diophantine equations in the domain of whole numbers. The importance of test for algebraic equalities can be considered equivalent to dimensional equation in physics relations and formulas. Additionally, this arithmetic function can also be useful in factorizing the composite odd numbers.

This paper gives both the solutions to the puzzles of quantum gravity and a general theory of quantum gravity, further shows quantum gravity of the Universe and general black hole, and discovers their relations reflecting symmetric propertis of the standard nonlinear gravitational Lagrangian, which are not relevant to any concrete metric models. This paper concretely shows the general commutation relations of the general gravitational field operators and their zeroth, first, second and third style, respectively, of high order canonical momentum operators for the general nonlinear system of the standard gravitational Lagrangian, and then has finished all the four styles of the quantization of the standard gravity. No needing, as usual, to solve the Euler-Lagrange equation to complete the whole process of the quantization of the standard gravitational fields, namely, this paper novelly simplifies all the current quantization theories of the standard gravitational fields. So lots of the complex calculations of quantum gravitational field theories up to now can be omitted to make the physical picture clearer, simpler and more easily understanding. Therefore, the solutions to puzzles of quantum gravity are given. Consequently, this paper opens a door to study and give a general theory of the quantum gravitational field don't depending on any concrete metric models.

The present study was conducted the status of sea bass from Kokko and Kyuntone of The Gulf of Motttama Wetland (GoMW) area in Thanatpin Township in Bago Region Myanmar from September 2019 to August 2020. Fifty specimens were monthly collected, measured and weighed. Invoices of sea bass were collected for the depot and fish sellers by monthly. In Kokko, mean value of standard length and body weight were highest in March (32.70±1.58, 660.7±112.23). The mean value of standard length was peak in January (31.39±7.16) but peak of body weight was in March (963.24±280.86) in Kyuntone villages. The lowest mean value of standard length and body weight were found in June at both study areas. According to the invoice data revealed that monthly catch weight of sea bass is most abundance in October (829.92) kg in Kokko, (339.12) kg in Kyuntone. Based on price of relations to size group, small size C < 300g (41%) was mostly abundance in Kokko and in Kyuntone small size C < 300g (35%) was second abundance. Specimens were not landed in April and May. In June, young specimens were very rarely seen in both study sites. The important roles of wetland fishes, the economic valuation of GOMW in Myanmar and samples of fishing gear and value chain of sea bass in Myanmar was expressed in this study.

Here, we review findings and trends in sleep research in 2020-2021 demonstrating how COVID-19 and sleep disorders can induce the BBB leakage via neuroinflammation, which might contribute to the 'coronasomnia' phenomenon. The new studies suggest that the controlling of sleep hygiene and quality should be incorporated into the rehabilitation of COVID-19 patients. We also discuss perspective strategies for prevention of COVID-19-related BBB disorders. We demonstrate that sleep might be a novel biomarker of the BBB leakage and the analysis of sleep EEG patterns can be a breakthrough non-invasive technology for diagnosis of the COVID-19-caused BBB disruption.

Let N = N₀+ N₁+ N₂ be a Z₃-graded Novikov algebra. The main goal of the paper is to prove that over a field of characteristic not equal to 3 the algebra N is solvable if N₀ is solvable. We also show that a $Z_2$-graded Novikov algebra N=N₀+ N₂ over a field of characteristic not equal to 2 is solvable if N₀ is solvable. This implies that for every n of the form n=2^k3^l, any Z_n-graded Novikov algebra N over a field of characteristic not equal to 2,3 is solvable if N₀ is solvable.

The present study has been done using the Survey Research. The research sample scale equals 400 people, besides its statistical population is included the 15-year population and most of the city of Kerman in 2020. The method of multistage-cluster-stratified sampling was used in five districts of the city of Kerman, moreover the results have been analyzed by SPSS and AMOSS16 software, and only is one model fitted with reality among five models of designed path. The results of analysis of path diagram indicate that other coefficients of the path all of them are significant except the direct impact of one's image of the body on sport-based cultural capital and social class on the tendency toward the public sport. Other results of the study suggest that sport-based socio-economic capital leaves an indirect effect on sport-based cultural capital by which the tendency of citizens toward the sport grows up. At that showing athletic advertisements in the media are effective on the tendency of citizens to public sport.

Background: Glioblastoma is the deadliest, yet most common, brain tumor in adults, with poor survival and response to aggressive therapy. Therapeutic failure results from a number of causes inherent to these tumors. Imaging, computational, and drug delivery approaches can aid in the quest to access and kill each tumor cell in patients. One factor, interstitial fluid flow, is a driving force therapeutic delivery. However, convective and diffusive transport mechanisms are un-der-studied. In this study, we examine the application of a novel image analysis method to meas-ure fluid flow and diffusion in glioblastoma patients with MRI and compare to patient outcomes. Methods: Building on a prior imaging methodology tested and validated in vitro, in silico and in preclinical models of disease, here we apply our analysis method to archival patient data from the Ivy GAP dataset. Results: We characterize interstitial fluid flow and diffusion patterns in patients. We find strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Looking at overall magnitudes, there is significant correlation with both age and survival in this patient cohort. Additionally, we find that tumor size nor resection significantly alter the velocity magnitude. Last, we map the flow pathways in patient tumors and find variability in degree of directionality that we hypothesize in future studies may lead to information concerning treatment, invasive spread, and progression. Conclusions: Analysis of standard DCE-MRI in patients with glioblastoma offers more infor-mation regarding transport within and around tumor, can be measured post-resection and mag-nitudes correlate with patient prognosis.

Standard Model is well-performing under the three-generation, but in the wake of more physics, fourth-generation leptons and quarks are introduced. In this paper, We will be reviewing various constraints surrounding quarks and leptons of 4th Generation and tried to show the importance of quarks to understand the baryogenesis. We talked about, reviewed existing parameters and set the updated lower limits of t’ and b’ by analysis. And predicted an updated version of lower mass bounds quarks and leptons. It is also reviewed that fourth generation leptons are primarily not possible because of disintegration of Higgs Boson and an interpretation has been setup. And in final, we talked about the Unified Standard Model.

For the solution existence condition of the Navier-Stokes equation, we propose a conjecture as follows: "\emph{The Navier-Stokes equation has a solution if and only if the determinant of flow velocity gradient is not zero, namely $\det (\bm \nabla \bm v)\neq 0$.}"

The material derivative is important in continuum physics. This Letter shows that the expression $\frac{d }{dt}=\frac{\partial }{\partial t}+(\bm v\cdot \bm \nabla)$, used in most literature and textbooks, is incorrect. The correct expression $ \frac{d (:)}{dt}=\frac{\partial }{\partial t}(:)+\bm v\cdot [\bm \nabla (:)]$ is formulated. The solution existence condition of Navier-Stokes equation has been proposed from its form-solution, the conclusion is that "\emph{The Navier-Stokes equation has a solution if and only if the determinant of flow velocity gradient is not zero, namely $\det (\bm \nabla \bm v)\neq 0$.}"

Particles in classical physics are distinguishable objects, which can be picked out individually on the basis of their unique physical properties. By contrast, in quantum mechanics the standard view is that particles of the same kind (``identical particles'') are completely indistinguishable from each other. This standard view is problematic: Particle indistinguishability is irreconcilable not only with the very meaning of ``particle'' in ordinary language and in classical physical theory, but also with how this term is used in the practice of present-day physics. Moreover, the indistinguishability doctrine prevents a smooth transition from quantum particles to what we normally understand by ``particles'' in the classical limit of quantum mechanics. Elaborating on earlier work, we here discuss an alternative to the standard view that avoids these and similar problems. As it turns out, this alternative approach connects to recent discussions in quantum information theory concerning the question of when identical particles can be considered to be entangled.

Preparing high school students for engineering disciplines is crucial for sustainable scientific and technological developments in the USA. This paper discusses a pre-college program, which not only exposes students to various engineering disciplines but also enables them to consider engineering as the profession. The four-week long “Engineering Innovation (EI)” course is offered every year to high school students by the center of outreach, Johns Hopkins University. EI program is designed to develop problem-solving skills through extensive hands-on engineering experiments. A team consisting of an instructor, generally a PhD in Engineering, and a teaching fellow, generally a high school science teacher, closely work with students to pedagogically inculcate basics of core engineering disciplines such as civil, mechanical, electrical, materials, and chemical engineering. EI values independent problem-solving skills and simultaneously promote the team spirit among students. A number of crucial engineering aspects such as professional ethics, communications, technical writing, and understanding of common engineering principles are inculcated among high school students via well-designed individual and group activities. This paper discusses the model of EI program and its impact on students learning and their preparation for the engineering career.

After reviewing foundational literature by Snyder, I will demonstrate how hope theory has been used in psychological interventions and psychiatry, how hope influences learning and medical outcomes, and how hope can be applied to difficult life circumstances. Using this literature review, hope theory will be interrogated. I will argue that hope theory has developed its way through the years to garner many strengths, however a few weaknesses do exist and will be described. I will conclude with recommendations for using hope theory in practice, including the medical field, psychological interventions and counseling, and student development.

Based on historical facts, revisited from a present-day perspective, and on the documented opinions of the scientists involved in the discovery themselves, strong arguments are given in favor of a proposal to include prominent astronomer Vesto Slipher to the suggested addition of Georges Lemaître's name to Hubble's law on the expansion of the Universe, and thus eventually call it Hubble-Lemaître-Slipher's (HLS) law.

LASER cladding is a technique which has as main purpose to improve mechanical properties of materials surface with the addition of thin layers of other materials. Cladding/coating/addition material can be transferred to the substrate by powder injection, wire feeding or paste feeding and by the method of pre-placing the powders on the substrate. LASER cladding as a technique has only about 40 years. Is not yet a current technology and more work is needed, namely in the characterization of mechanical properties of new alloys used as base or cladding materials in this process. In this paper will be done initially an historical approach, followed by a description of the principles of the LASER cladding, a description of the applicability of the process and its advantages and limitations and the paper will end with a state of the art about the advances in new metallic alloys. So, this paper presents a review and the state of the art of the technological process and will be a contribution for the divulgation of this recent technique.

Precipitation and human activities are two essential forcing dynamics that influence hydrological processes. To investigate those impacts, the Zuli River Basin (ZRB, a typical tributary basin of the Yellow River in China) was chosen to identify the impact of precipitation and human activities on runoff and sediment discharge. A double mass curve (DMC) analysis and the test methods, including accumulated variance analysis, sequential cluster, Lee-Heghnian, and moving t-test methods was utilized to determine the abrupt change point based on data from 1956 to 2015. Correlation formulas and multiple regression methods were used to calculate the runoff and sediment discharge reduction effects of soil conservation measures and to estimate the contribution rate of precipitation and soil conservation measures to runoff and sediment discharge. Our results show that the runoff reduction effect of soil conservation measures (45%) is greater than the sediment discharge reduction effect (32%). Soil conservation measures were the main factor controlling the 74.5% and 75.0% decrease in runoff and sediment discharge, respectively. Additionally, the contribution rate of vegetation measures was higher than that of engineering measures. This study provides scientific strategies for water resource management and soil conservation planning at catchment scale to face future hydrological variability.

The energy, momentum and the action associated with the time domain transition radiation fields are investigated. The results show that for a charged particle moving with speed $v$, the longitudinal momentum associated with the transition radiation is approximately equal to $E/c$ for values of $1-v/c$ smaller than about 10^-3 where $E$ is the total radiated energy and c is the speed of light in free space. The action of the transition radiation, defined as the product of the energy dissipated and the duration of the emission, increases as $1-v/c$ decreases and, for an electron, it becomes equal to $h/4\pi$ when $v=c-v_m$ where $v_m$ is the speed associated with the lowest energy state of a particle confined inside the universe and h is the Plank constant. Combining these results with Heisenberg’s uncertainty principle, an expression for the electronic charge based on other fundamental physical constants is derived. The best agreement between the experimentally observed electronic charge and the theoretical prediction is obtained when one assumes that the actual size of the universe is about 250 times larger than the visible universe.

The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew conclusions as follows. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and International Patent Classification (IPC) subclasses together constitute a meaningful measure of the innovation performance of firms.

The concept of economic self-reliance, widely known by Thai people as the philosophy of sufficiency economy, has been widely promoted in rural Thai societies. By practicing this philosophy, it is expected that the citizens’ quality of life and local environments could be sustainably improved. This study aims to explore the contribution of the community practices of the sufficiency economy philosophy to rural villagers’ quality of life improvement, and to investigate potential factors that determine the trust of villagers in the philosophy. With the purpose to propose strategies which could enhance trust and promote villagers’ practices of the philosophy, the study investigated influences of three relevant factors on trust towards the philosophy. Those factors included factors related to cognitive-based trust, factors related to emotional-based trust, and factors related to demographic characteristics. Questionnaire surveys and in-depth interviews with community leaders and local villagers were conducted in the Ban Jamrung community, in Thailand’s Rayong province. The results of the statistical analysis revealed that the residents who applied the sufficiency economy philosophy in their daily lives experienced a relatively better quality of life. Additionally, it was found that trust in the philosophy could be predicted more by rational factors than by emotional factors. These findings could be utilized to develop strategies to maintain and enhance the trust of the people in the philosophy of sufficiency economy.

This paper investigates the influence of magnetic field for a two dimensional deformations on a two temperature problem at the free surface of a semi-infinite semiconducting medium under the effect of mechanical force during a photothermal theory and the effect of hydrostatic initial stress on the medium. The Harmonic Wave Method (Normal Mode Analysis) has been used to obtain the equations of elastic waves, heat conduction equation, quasi-static electric field, carrier density, two temperature coefficient, ratios, and constitutive relationships for the thermo-magnetic-electric medium. The effects of several parameters as thermoelastic and thermoelectric coupling parameters and two temperature parameter of this force on the displacement component, force stress, carrier density and temperature distribution has been depicted graphically.

There is a growing concern about climate change being a serious threat to insurance business sustainability. Knowing if climate warming is a cause for claims and losses increase, and how this cause-effect relationship will develop in the future are two open major questions. In this article, we answer both questions by particularizing the geographical area of Spain, and a precise risk, hailstorm in crop insurance in the line of business of wine grapes. We measure climate change thanks to the Spanish Actuarial Climate Index (SACI). We use a database containing all the claims caused by hail risk in Spain from 1990 to 2022. With homogenized data, we consider as dependent variables the monthly number of claims, monthly number of loss costs equal to one, and monthly total losses. The independent variable is the monthly Spanish Actuarial Climate Index (SACI). We try to explain the former through the latter using regression and quantile regression models. Our main finding is that climate change as measured by SACI explains these three dependent variables. We also give an estimation of the increase of the monthly total losses Value at Risk, corresponding to a future increase in climate change measured in units of SACI. Spanish crop insurance managers should carefully incorporate these conclusions into their decision-making process to keep this line of business sustainable in the future.

Whole genome duplication (WGD) or polyploidization can occur at the cellular, tissue, and organismal levels. At the cellular level, tetraploidization has been proposed as a driver of aneuploidy and genome instability, and correlates strongly with cancer progression, metastasis, and development of drugs resistance[1–6]. WGD is also a key developmental strategy for regulating cell size, metabolism, and cellular function[1,7–10]. In specific tissues, WGD is involved in normal development (e.g. organogenesis), tissue homeostasis, wound healing, and regeneration[10–17]. At the organismal level, WGD propels evolutionary processes such as adaptation[18], speciation[19], and crop domestication[20]. An essential strategy to further our understanding of the mechanisms promoting WGD and its effects is to compare isogenic strains that differ only in their ploidy. Caenorhabditis elegans (C. elegans) is emerging as an animal model for these comparisons, in part because relatively stable and fertile tetraploid strains can be produced rapidly from nearly any diploid strain[7]. Here we review the use of Caenorhabditis polyploids as tools to understand important developmental processes (e.g. sex determination, dosage compensation, and allometric relationships)[21–27] and cellular processes (e.g. cell cycle regulation, chromosome dynamics during meiosis)[28–32]. We also discuss how the unique characteristics of the C. elegans WGD model will enable significant advances in our understanding of mechanisms of polyploidization and its role in development and disease.

Physics theory has yet to settle on specific descriptions for new elementary particles, for dark matter, and for dark energy forces. Our work extrapolates from the known elementary particles. The work suggests well-specified candidate descriptions for new elementary particles, dark matter, and dark energy forces. This part of the work does not depend on theories of motion. This work embraces symmetries that correlate with motion-centric conservation laws. The candidate descriptions seem to explain data that prior physics theory seems not to explain. Some of that data pertains to elementary particles. Our theory suggests relationships between masses of elementary particles. Our theory suggests a relationship between the strengths of electromagnetism and gravity. Some of that data pertains to astrophysics. Our theory seems to explain ratios of dark matter effects to ordinary matter effects. Our theory seems to explain aspects of galaxy formation. Some of that data pertains to cosmology. Our theory suggests bases for inflation and for changes in the rate of expansion of the universe. Generally, our work proposes extensions to theory in three fields. The fields are elementary particles, astrophysics, and cosmology. Our work suggests new elementary particles and seems to explain otherwise unexplained data.

The Science-Sustainability poses an interdisciplinary paradox. On the one hand, the science for sustainability has increased in OECD economies in and in China as well as in the US in particular; on the other hand; the sustainability situation has worsened (Co2 emission has risen). On the face value, the adverse correlation shows a paradox. However, without explicating the science-sustainability relationship, it leads to a premature conclusion. In this study, we have drawn on three concrete questions for concrete answers. First, whether and how interdisciplinary sciences—energy science and environmental science—contribute to the sustainability. Second, whether and how the Sino-US inter-institutional analysis varies in the science-sustainability paradox. The empirical analysis from a panel data in the interdisciplinary and inter-institutional context show mixed patterns in three ways. First, the increase in the environmental science shows an improvement in the sustainability; the energy science shows a decline in the sustainability. Second, the Chinese environmental science has a comparative advantage to American environment science for the sustainability development, and the Chinese energy science has a comparative disadvantage to the US in the sustainability development. Third, the environmental science mediates the energy science in the science-sustainability relationships. Standing alone, the increase in the energy science harms sustainability; mediated by environmental science, it benefits sustainability. The study explains the adverse role of energy science in Jevons Paradox. The study also offers some policy paths for further research how capitalisms differently innovate, form strategies, and implement the practice.

As a matter of course, the first gene must be formed in the absence of gene. On the other hand, many biopolymers including gene are produced under the genetic system in extant organisms. Thus far, no idea explaining how the first gene was formed in the absence of gene, has been proposed except the idea based on the GADV hypothesis. GADV means four amino acids; Gly [G], Ala [A], Asp [D] and Val [V]. In this article, a reliable answer to the question, how the first gene was generated, is provided. The idea is as follows. The first gene (genetic information) was formed by random joining of anticodons, GNCs, which were carried by primeval anticodon stem-loop (AntiC-SL) tRNAs produced during repeated cycles of random joining of nucleotides and degradation of oligonucleotides. However, it might be difficult for many persons to accept the idea, because tRNAs and metabolic pathways using various proteins, which are produced under genetic functions, must be used to form the first gene. Then, it is reconsidered based on definition of genetic information and minimum necessary things to generate the first gene in this article, how the first gene was generated. Consequently, it could be reconfirmed that five prototypes of members (genetic code, tRNA, metabolism, cell structure and protein) composing the fundamental life system, except gene, are certainly necessary to generate the first gene. Namely, it can be concluded that the first gene was formed through nucleotide metabolism with immature [GADV]-proteins, primeval AntiC-SL tRNA formation with immature [GADV]-proteins, formations of single-stranded (GNC)n codon sequence by random joining of anticodons, GNCs, carried by AntiC-SL tRNAs, double-stranded (ds)-(GNC)n RNA and maturation of an immature [GADV]-protein, which was produced from one strand of the ds-RNA. Thus, the first gene was formed using the five primitive or prototypes of members, which were produced in the absence of gene. There would be no other way for generating the first gene.

The goal of the manuscript is to design a relatively best control structure for the noise suppression of a drone’s camera gimbal action. The gimbal’s movement can be simplified as a rest-to-rest reorientation system that can achieve the boundary result of a dynamic system. Six different control architectures are proposed and evaluated based on their ability to control the trajectory of the dynamic-system position and speed, their running time, and quadratic cost. The robustness of the control architecture to uncertainties in inertia and sensor noise is also analyzed. Monte Carlo figures are used to assess the performance of the six control systems. The conditions for applying different architectures are identified through this analysis. The analysis and experimental tests reveal the most suitable control of the drone’s camera gimbal rotation.

Aortic disease has a significant impact on quality of life. Involvement of the aortic arch requires preservation of blood supply to the brain during surgery. Deep hypothermic circulatory arrest is an established technique for this purpose although neurological injury remains high. Additional techniques have been used to reduce the risk although controversy still remains. A three-way cannulation approach, including both carotid arteries and the femoral artery or the ascending aorta, has been used successfully for aortic arch replacement and redo procedures. We have de-veloped circuits of the circulation to simulate blood flow during this type of cannulation set up. The aim is to analyse using CARDIOSIM© cardiovascular simulation platform, how the haemodynamic and energetic parameters are affected and the benefit derived with particular reference to the cerebral circulation.

Currently, there is a high interest in smart sensors and integrated composite materials in various industries such as construction, aviation, automobile, medical, information technology, communication, and manufacturing. Here, a new conceptual design for a force and temperature sensor system is developed by integrating fiber optic Bragg grating sensors embedded within composite materials, and a mathematical model is proposed that allows one to estimate strain and temperature based on signals obtained from optical Bragg gratings. This is important for understanding the behaviors of sensors under different conditions and for creating effective monitoring systems. Describing the strain gradient distribution, especially considering different materials with different values of Young's modulus, provides insight into how different materials respond to applied forces and temperature changes. The shape of the strain gradient distribution was obtained, which is a quadratic function with a maximum value of 1500 µ, with a maximum value at the center of the lattice and a symmetrically decreasing strain value with distance from the central part of the fiber Bragg grating. With axial strain at the installation site of the Bragg grating sensor under applied force values ranging from 10 to 11 N, the change in strain was linear. As a result of theoretical research, it was found that the developed system with fiber-optic sensors based on Bragg gratings embedded in composite materials is resistant to external influences and temperature changes.

In this paper, a continuous power management for a decentralized DC microgrid (DCMG) is proposed to achieve voltage regulation and power balance even under system uncertainty and voltage sensor failure. The DCMG system achieves a continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under voltage sensor failure, a DC bus voltage (DCV) sensor fault detection algorithm is proposed. In this algorithm, the DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. When the power agent identifies the DCV sensor failure, it changes the operation properly according to the proposed control mode decision algorithm to maintain the stability of the DCMG system. When uncertain conditions such as the power variation of the distributed generations, sudden grid disconnection, DCV sensor failure, electricity price change, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. Simulation and experimental results under different test conditions confirm the reliability and effectiveness of the proposed control scheme.

This paper details the comprehensive activities conducted in a laboratory setting to assess the Structural Health Monitoring (SHM) of prefabricated building envelopes. Aimed at enhancing the structural evaluation of buildings, the focus of this research lies in employing nondestructive sensors for SHM with the objective to advance in the understanding and assessment of facade conditions. The paper outlines the methodologies employed, starting with a modal analysis to define the structural vibration's modal frequency. Subsequently, tests were defined and executed to validate building envelope compliance in case of stress typical of high-rise building. Throughout these tests, continuous monitoring of the façade was conducted using both conventional (accelerometers, extensimeter washers) and non-conventional sensors (Fiber Optic Sensing) The gathered data underwent thorough processing and analysis to provide an overall perspective on the structure's behavior during the stress test. The investigation aimed to identify whether specific physical phenomena correlate with distinct signals and to evaluate if continuous façade monitoring over the building's lifespan aids in preventing potential structural damage. Moreover, two modal analyses were conducted to compare final data and frequencies with earlier data, enabling the detection of any structural alterations. The results from compliance testing and structural analysis yielded noteworthy insights contributing to the evolving field of structural health monitoring, offering valuable findings that advance our ability to proactively manage and maintain the integrity of building structures.

We report the relative humidity (R.H.) sensing response of a resistive sensor, employing sensing layers based on a ternary nanohybrid comprising holey carbon nanohorns (CNHox), potassium chloride (KCl), and polyvinylpyrrolidone (PVP) at mass ratios 7/1/2, 6.5/1.5/2, and 6/2/2 (w/w/w/w). The sensing structure comprises a silicon substrate, a SiO2 layer, and interdigitated transducer (IDT) electrodes. The sensing film is deposited on the sensing structure via the drop-casting method. The sensing layers' morphology and composition are investigated through Scanning Electron Microscopy (S.E.M.) and RAMAN spectroscopy. The ternary hybrid-based thin film resistance increases when the sensors are exposed to R.H., ranging from 0% to 100%. The manufactured devices show a room temperature response comparable to a commercial capacitive R.H. sensor and are characterized by excellent linearity, rapid response time, and good sensitivity. The presented sensors exhibit superior performance in terms of sensitivity compared to other similarly manufactured and tested sensors that employ a CNHox-based sensing layer. We explain the sensing role of each constituent of the ternary hybrid nanocomposites based on their chemical and physical properties, electronic properties, and affinity for water molecules. Different alternative sensing mechanisms are considered and discussed, such as the decreasing number of holes in the holey CNHox at the interaction with water molecules, proton conduction, and PVP swelling.

An original approach has been proposed for designing a nanofibrous (NFs) layer using UV-cured polyvinylpyrrolidone (PVP) as a matrix, incorporating mesoporous graphene carbon (MGC) nanopowder both inside and outside the fibres, creating a sandwich-like structure. This architecture is intended to selectively adsorb and detect acetic acid vapours, which are known to cause health issues in exposed workers. The nanocomposite MGC-PVP-NFs layer was fabricated through electrospinning deposition onto interdigitated microelectrodes (IDEs) and stabilised under UV-light irradiation. To enhance the adhesion of MGC onto the surface of the nanocomposite polymeric fibres, the layer was dipped in a suspension of polyethylenimine (PEI) and MGC. The resulting structure demonstrated promising electrical and sensing properties, including rapid responses, high sensitivity, good linearity, reversibility, repeatability, and selectivity towards acetic acid vapours. Initial testing was conducted in a laboratory using a bench electrometer, followed by validation in a portable sensing device based on consumer electronic components (by ARDUINO®). This portable system was designed to provide a compact, cost-effective solution with high sensing capabilities. Under room temperature and ambient air conditions, both laboratory and portable tests exhibited favourable linear responses, with detection limits of 0.16 and 1 ppm, respectively.

This research work has been based on a previous study by the authors that characterized the behavior of a polyimide-coated FBG sensor in a structural monitoring system. Sensors applied to structural health monitoring are affected in the presence of a state of multidirectional strains simultaneously. The previous study observed the influence of transverse strain (ε_y) while keeping longitudinal strain constant (ε_x), where the direction x is the direction of the optical fiber. The present study developed an experimental methodology which has consisted of carrying out a campaign of biaxial tests on cruciform specimens with three embedded FBG sensors coated with polyimide, acrylate and ORMOCER®. Applying the Strain–Optic Theory as reference, a comparison of the results obtained with the different coatings has been studied. This experimental work has done it possible to study the influence of transverse strain (ε_y) in the longitudinal measurement of each of the FBG sensor and the influence of the coating material. Finally, the calibration procedure as well as the strain sensitivity factor K for each sensor has been defined.

In wireless sensor networks (WSNs) deployed in smart agriculture systems, accurately determining the locations of sensor nodes is crucial for efficient monitoring and control. However, in many cases, the exact positions of certain sensor nodes may be unknown. To address this challenge, this paper presents a novel method for localizing unknown sensor nodes in WSN-based smart agriculture systems using range measurements. The proposed method utilizes the Levenberg-Marquardt optimization algorithm to solve a nonlinear least squares problem and minimize the error in estimating the unknown node locations. By leveraging the known positions of a subset of sensor nodes and the inexact distance measurements between pairs of nodes, the localization problem is transformed into a nonlinear optimization problem. To validate the effectiveness of the approach, extensive simulations and experiments were conducted. The results demonstrate that the proposed method achieves accurate localization of the unknown sensor nodes, effectively enhancing the overall performance of the WSN-based smart agriculture system. Furthermore, the method demonstrates robustness against measurement noise and scalability for large-scale networks. The practical implications of this research extend beyond smart agriculture systems, as the proposed method can be applied to various WSN applications where precise node localization is essential.

The availability of multi-rotor UAVs with lifting capacities of several kilograms, allows for a new paradigm in atmospheric measurement techniques, i.e. the integration of research-grade sonic anemometers for airborne turbulence measurements. With their ability to hover and move very slowly, this approach yields an unrevealed flexibility compared to mast-based sonic anemometers, for a wide range of boundary layer investigations that require an accurate characterization of the turbulent flow. For an optimized sensor placement, potential disturbances by the propeller-induced flow (PIF), as well as the potential impact of the sensor weight and angular momentum on the flight performance in the case of a boom-mounted sensor, have to be considered.

Efficient traffic management at signalized intersections is integral to urban infrastructure development, requiring accurate estimation of delay times to mitigate congestion and enhance overall transportation systems. Traditional methodologies, including empirical observations and microsimulation software, have been prevalent in assessing delay times; however, their limitations have prompted the exploration of novel technologies like LiDAR (Light Detection and Ranging) sensors. This research study investigates and compares the accuracy of delay time estimations obtained from LiDAR sensor technology with those derived from microsimulation in AIMSUN. LiDAR sensors, known for their high-resolution, real-time data collection capabilities, offer a promising avenue for precise measurement of delay times at signalized intersections. Nonetheless, challenges in sensor placement, environmental influences, and data processing complexities suggest the need for further development and validation. In parallel, microsimulation software, exemplified by AIMSUN, provides a virtual platform for scenario testing but relies on assumptions that may not always mirror real-world traffic dynamics accurately. The comparative analysis conducted in this study aims to critically examine the discrepancies and potential complementarity between delay times obtained from LiDAR sensor technology and those derived from microsimulation in AIMSUN. The research involves an in-depth evaluation of real-time, high-resolution data collected by LiDAR sensors, assessing their accuracy in capturing the intricate movements and behavior of vehicles at signalized intersections. Simultaneously, AIMSUN microsimulation delay time models are scrutinized for their ability to accurately replicate these observed delay times. The disparities identified serve as critical insights into the challenges of both methodologies, prompting the discussion on the prospects of integrating LiDAR-derived data and microsimulation calibration processes to enhance the precision and reliability of delay time estimations. Future traffic management strategies can significantly benefit from a more accurate understanding of delay times, and this study endeavors to contribute to the advancement of methodologies in traffic engineering for more effective urban transportation systems.The paper's findings illuminate the potential and limitations of both LiDAR sensor technology and microsimulation in estimating delay times at signalized intersections. The results highlighted that the LiDAR sensors could accurately calculate delay times at a signalized intersection. Furthermore, the calculated delay time differences by LiDAR and AIMSUN at three days with the highest vehicle volumes (counts) are always less than 6.5%.

This study investigates the application of Light Detection and Ranging (LiDAR) sensor technology for data collection at signalized intersections characterized by a high rate of traffic crashes. The research aims to provide valuable insights into the potential of LiDAR-based data analysis to enhance road safety and traffic management at signalized intersections. The research methodology involved the deployment of LiDAR sensors at Marlboro Pike & Brooks Dr. signalized intersection in Coral Hills, Maryland. Two LiDAR sensors installed in this intersection to collect high-resolution, three-dimensional data of the intersection area from June, 1^st to July, 7^th 2023. The data included information on vehicle trajectories, speeds, and behaviors, as well as pedestrian and cyclist movement patterns. Concurrently, historical traffic crashes recorded and traffic flow data were obtained for the same intersection.The analysis of LiDAR data involved several key aspects including LiDAR data allowed for a precise evaluation of traffic flow patterns, including congestion points, traffic volume fluctuations, and peak-hour behavior. This information provided insights into potential factors contributing to crashes. By analyzing LiDAR data, the study identified near-miss incidents, which are often precursors to actual crashes. This proactive approach could assist in identifying crash-prone areas within the intersection. The LiDAR data analysis also focused on pedestrian and cyclist movements, including jaywalking and bike lane usage. The aim was to identify areas where infrastructure improvements could enhance safety for vulnerable road users. LiDAR data was compared with historical crash data to identify specific locations within the intersection that exhibited a high frequency of crashes. This information can guide targeted safety interventions. Last but not least, the study explored opportunities to optimize traffic signal timings based on real-time traffic data from LiDAR. Adaptive signal control could help mitigate congestion and reduce the risk of crashes.The results of this study demonstrated the potential of LiDAR sensor technology in collecting detailed data for traffic analysis in signalized intersections. By combining LiDAR data with historical crash records and traffic flow data, traffic engineers and urban planners can develop evidence-based strategies to reduce the frequency and severity of crashes in high-risk areas. Ultimately, this research contributes to a comprehensive understanding of how LiDAR technology can be employed to enhance road safety and traffic management, providing valuable insights for traffic engineers, urban planners, and policymakers seeking to improve the safety and efficiency of signalized intersections with a history of high traffic crashes.

Traffic congestion is a persistent and challenging problem in urban areas, leading to increased travel times, fuel consumption, and environmental pollution. Signalized intersections play a pivotal role in regulating traffic flow, and their efficiency has a direct impact on the overall traffic performance of a city. This study investigates the effect of traffic signal in managing traffic volume and reducing congestion and delays at signalized intersections through a comprehensive analysis of existing research, data collection, and simulations.The research begins by analyzing the traffic characteristics by an installed LiDAR sensor at E Cold Spring Ln – Hillen Rd intersection in Baltimore City, MD. When the signal at this intersection stopped working for some hours during a working day in September 2023, the LiDAR recorded vehicle and pedestrian counts, vehicle-vehicle and vehicle-pedestrian conflicts, and jaywalking events conflicts. The research aims to assess the impact of traffic signal failures on traffic flow, congestion, safety (V2V and V2P conflicts), and the frequency of jaywalking events before, during, and after improper performance of the traffic signal. Furthermore, this study explores the factors influencing traffic signal performance, including traffic demand, geometric layout, pedestrian interactions, and the integration of emerging technologies. The analysis results highlighted the importance of signal control systems existence at this intersection that can adjust signal timing in response to changing the real-time traffic conditions.Reduced congestion, minimized delays, and enhanced traffic flow are observed outcomes, contributing to a more sustainable and efficient urban transportation system. However, it is crucial to consider the trade-offs and challenges associated with traffic signal optimization, such as the potential for increased travel times for certain modes of transportation and the need for ongoing maintenance and updates. In conclusion, this study underscores the pivotal role of traffic signals in managing traffic volume and reducing congestion and delays at signalized intersections. Through evidence-based analysis and innovative signal control strategies, urban planners and transportation authorities can work towards creating more efficient, sustainable, and less congested transportation networks. The insights derived from this research can inform policy decisions and guide the development of future traffic management solutions, ultimately leading to improved quality of life in urban areas.

Due to the highly nonlinear, multi-stage, and strongly time-varying marine lysozyme fermentation process, it is difficult to assure the stability and prediction accuracy of the traditional single global soft sensor model on a global scale. This study innovatively proposed a soft sensor model based on an improved seagull optimization algorithm (ISOA) combined with Gaussian process regression (GPR) weighted ensemble learning. First, the sample data set is divided into multiple local sample subsets by the improved density peak clustering algorithm (ADPC). Second, the Gaussian process regression model is optimally altered with an improved seagull optimization algorithm for the purpose of establishing the corresponding sub-prediction model. Finally, the prediction model's fusion strategy is ultimately determined depending on the degree of connection between the test samples and a subset of local pieces. Simulation results show that the proposed soft sensor model, which searches GPR based on ISOA and combines various sub-models, can predict the key biochemical parameters of the marine lysozyme fermentation process better with less prediction error under the condition of fewer training data, and it can be expanded to the soft sensor models of general nonlinear systems, according to simulation results.

Ankle joint flexion and extension exercises play an important role in the rehabilitation training of patients who have been injured or bedridden for a long time before and after surgery. Accurately guiding patients to perform ankle flexion and extension exercises can significantly reduce deep vein thromboembolism. Currently, most ankle rehabilitation devices focus on assisting patients with ankle flexion and extension movements, and there is a lack of devices for effectively monitoring these movements. In this study, we designed an ankle joint flexion and extension movement monitoring device based on a pressure sensor. It is composed of an STM32 microcontroller, a pressure sensor, an HX711A/D conversion chip, and an ESP8266 WiFi communication module. The value of force and effective number of ankle joint flexion and extension movements were obtained. An experimental device was designed to verify the accuracy of the system. The results showed that the device can effectively monitor and control ankle flexion and extension movements remotely, ultimately ensuring that the patient can effectively monitor and grasp the active ankle pump movement.

The accommodative response of the human eye is predominantly driven by foveal vision but reacts also to off-foveal stimuli. Here, we report on monocular accommodation measurements using parafoveal and perifoveal annular stimuli centered around the fovea and extending up to 8 degree radial eccentricity for young emmetropic and myopic subjects. The stimuli were presented through a sequence of random defocus step changes induced by a pupil-conjugated tunable lens. A Hartmann-Shack wavefront sensor with an infrared beacon was used to measure real-time changes of ocular aberrations up to and including the 4th radial order across a 3 mm pupil at 20 Hz. Our findings show a significant reduction in accommodative response with increased radial eccentricity.

Humans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 participants (nine female, M = 25.9 with SD = 3.8 years). In this study, we recorded, respiratory, ocular, cardiac, and brain activity using functional near-infrared spectroscopy (fNIRS) while participants performed an adapted version of the warship commander task with concurrent emotional speech distraction. We tested the feasibility of decoding the experienced mental effort with a multimodal machine learning architecture. The architecture comprised feature engineering, model optimisation, and model selection to combine multimodal measurements in a cross-subject classification. Our approach reduces possible overfitting and reliably distinguishes two different levels of mental effort. These findings contribute to the prediction of different states of mental effort and pave the way toward generalised state monitoring across individuals in realistic applications.

Miniature sensors are key components for the applications in the Internet of Things (IoT), wireless sensor networks, autonomous vehicles, smart cities and smart manufacturing. As a miniature and self-powered magnetic sensor, Wiegand sensor possesses the advantageous traits including changing-rate-independent output, low cost, and remarkable repeatability and reliability. Typical Wiegand sensor requires hard magnetic pole pieces that provide external fields for triggering voltage outputs that are called Wiegand pulses. However, the wire-shaped sensing element of Wiegand sensor is the critical issue that limits the design, selection, and adoption of the external triggering magnets. Currently, the widely used pole piece materials are rare-earth magnets. However, adopting rare-earth magnets brings strong stray fields, causing electromagnetic interference (EMI) problem. In this study, patterned CoNiP hard magnets were electrodeposited on flexible substrates through microfabrication. Origami magnetization was utilized to control the resultant stray fields, and hence the pole piece of CoNiP magnets can successfully trigger the output of Wiegand pulse. In comparison, the output voltage of the triggered pulse acquired through the patterned CoNiP magnets is comparable to that by using the rare-earth magnets. Furthermore, both the volume (meanwhile the weight) of the Wiegand sensor and the EMI issue can be significantly reduced and mitigated by the CoNiP magnets.

In this work, we adapt the fine-tuning algorithm of the Naïve Bayesian (FTNB) classifier to make it more suitable for imbalanced datasets. In particular, we boost misclassified instance probability terms by an amount that is disproportional to the harmonic mean of actual and predicted classes. The intuition is that discriminative attributes when the instance is misclassified would have small probability term pair values in both the actual class due to data scarcity and the predicted class due to weak correlation. Conversely, if both values are relatively high, then the attribute has good data coverage (support) and it should not be a cause for misclassification. Since the harmonic average is dominated by the smaller value and we have an imbalanced dataset, we should enact a large update if both or either term probabilities of actual and predicted classes are small. We used several benchmark datasets (60 different balanced and imbalanced datasets) to determine if the poor performance of the NB classifier is due to the scarcity of data and compared the performance of the proposed algorithm with NB, original FTNB, and other relatively new SOTA Ensemble Imbalanced Classifiers. Our empirical results reveal that the new proposed algorithm significantly outperforms all other classifiers.

So that the levels of water stress are not harmful to the development of the crop and affect its productivity, its detection and monitoring are necessary, and it can occur in different ways. One of them is through the Crop Water Stress Index (CWSI). This index quantifies water stress through the normalization of leaf temperature between the maximum and minimum plant temperatures as a function of evaporation conditions. The responses of a low-cost infrared (IR) sensor were crossed with image processing through segmentation by the Excess Green model to develop a water stress detection system using CWSI. A soil/plant temperature map was generated through a point-to-point scan of the IR sensor. And when it overlaid with a segmented image of the experimental area, only points identified as plants had their temperature values maintained. The Non-Water-Stressed Baseline (NWSB) equation was parameterized for the same conditions of the experiment and external environmental. The experimental area was divided into three different treatments, maintained under stable water conditions throughout the experiment and the system was able to identify stably different stress values between treatments. Although the relationship between crop and environment affected the results, this work showed that using an irrigation system based on CWSI is possible.

All living cells maintain a charge distribution across their cell membrane (membrane potential) by carefully controlled ion fluxes. These bioelectric signals regulate cell behavior (such as migration, proliferation, differentiation) as well as higher-level tissue and organ patterning. Thus, voltage gradients represent an important parameter for diagnostics as well as a promising target for therapeutic interventions in birth defects, injury, and cancer. However, despite much progress in cell and molecular biology, little is known about bioelectric states in human stem cells. Here, we present simple methods to simultaneously track ion dynamics, membrane voltage, cell morphology, and cell activity (pH and ROS), using fluorescent reporter dyes in living human neurons derived from induced neural stem cells (hiNSC). We developed and tested functional protocols for manipulating ion fluxes, membrane potential, and cell activity, and tracking neural responses to wounding and re-innervation in vitro. Finally, using morphology sensor, we tested and quantified the ability of physiological actuators (neurotransmitters and pH) to manipulate nerve wound re-innervation. These methods are not specific to a particular cell type and should be broadly applicable to the study of bioelectrical controls across a wide range of combinations of models and endpoints.

This paper is focused on two topics very relevant in water distribution networks (WDNs): vulnerability assessment and the optimal placement of water quality sensors. The main novelty element of this paper is to represent the data of the problem, in this case all objects in a graph underlying a water distribution network, as discrete probability distributions. For vulnerability (and the related issue of re-silience) the metrics from network theory, widely studied and largely adopted in the water research community, reflect connectivity expressed as closeness centrality or, betweenness centrality based on the average values of shortest paths between all pairs of nodes. Also network efficiency and the related vulnerability measures are related to average of inverse distances. In this paper we propose a different approach based on the discrete probability distribution, for each node, of the node-to-node distances. For the optimal sensor placement, the elements to be represented as dis-crete probability distributions are sub-graphs given by the locations of water quality sensors. The objective functions, detection time and its variance as a proxy of risk, are accordingly represented as a discrete e probability distribution over contamination events. This problem is usually dealt with by EA algorithm. We’ll show that a probabilistic distance, specifically the Wasserstein (WST) distance, can naturally allow an effective formulation of genetic operators. Usually, each node is associated to a scalar real number, in the optimal sensor placement considered in the literature, average detection time, but in many applications, node labels are more naturally expressed as histograms or probability distributions: the water demand at each node is naturally seen as a histogram over the 24 hours cycle. The main aim of this paper is twofold: first to show how different problems in WDNs can take advantage of the representational flexibility inherent in WST spaces. Second how this flexibility translates into computational procedures.

In a previous paper, the authors dealt with the current showstoppers for morphing systems and with the reasons that have inhibited their commercial applicability. In this work, the authors ex-press a critical vision of the current status of the proposed architectures and the needs that should be accomplished to make them viable for installation onboard of commercial aircraft. The distinc-tion is essential because military and civil issues and necessities are very different, and both the solutions and difficulties to be overcome are widely diverse. Yet, still remaining in the civil seg-ment, there can be other differences, depending on the size of the aircraft, from large jets to com-muters or general aviation, in turn classifiable in tourism, acrobatic, ultralight and so on, each with their own peculiarities. Therefore, the paper wants to try to trace a common technology de-nominator, if possible, and envisage a future perspective of actual applications.

Heavy metal contaminants have serious consequences for the environment and human health. Consequently, effective methods for detecting their presence, particularly in water and food, are urgently required. Accordingly, the present study proposes a sensor for the detection of mercury Hg(II) and lead Pb(II) ions using graphene oxide (GO) as a quenching agent and aptamer solu-tion as a reagent. In the proposed device, the aptamer sequences are labeled by FAM and HEX fluorescent dyes, respectively, and are mixed with 500 ppm GO solution in a microfluidic device. The presence of Hg(II) and Pb(II) ions is then detected by measuring the change in the fluores-cence intensity of the GO/aptamer suspension as the aptamer molecules undergo fluorescence resonance energy transfer (FRET). The experimental results show that the aptamer sensors have a linear range of 10~250 nM (i.e., 2.0~50 ppb) for Hg(II) ions and 10~100 nM (i.e., 2.1~20.7 ppb) for Pb(II) ions. Furthermore, the limit of detection is around 2 ppb for both metals, which is signifi-cantly lower than the maximum limits of 6 ppb and 10 ppb prescribed by the World Health Or-ganization (WHO) for Hg(II) and Pb(II) in drinking water, respectively.

Blade Health Monitoring (BHM) is often necessary in power plants and in aviation to prevent excessive blade vibration and cracks. This article proposes a network of blade tip timing sensors operated in a distributed BHM system. A number of cooperating agents is implemented in smart conditioning units which can autonomously operate in an adverse environment and communicate with other nodes via a serial interface. The project uses special versions of reduced instruction set chips that are able to operate near the hot section of the engine. Due to the limited number of types of microprocessors available in the extended temperature range grading, it was necessary to fully utilize the limited hardware resources and implement preemptive multitasking. For this purpose, a custom operating system and communication protocol were designed. The protocol hosts the middle layer which hides the implementation of the distributed system. The presented architecture ensures the sufficient computational capacity in individual nodes of the network operated in adverse conditions. It is scalable and resistant to transmission errors.

A low-cost machine learning (ML) algorithm is proposed and discussed for spatial tracking of unknown, correlated signals in localized, ad-hoc wireless sensor networks. Each sensor is modeled as one neuron and a selected subset of these neurons are called to identify the spatial signal. The algorithm is implemented in two phases of spatial modeling and spatial tracking. The spatial signal is modeled using its M iso-contour lines at levels {ℓj}j=1M and those sensors that their sensor observations are in Δ margin of any of these levels report their sensor observations to the fusion center (FC) for spatial signal reconstruction. In spatial modeling phase, the number of these contour lines, their levels and a proper Δ are identified. In this phase, the algorithm may either use adaptive-weight stochastic gradient or scaled stochastic gradient method to select a proper Δ. Additive white Gaussian noise (AWGN) with zero mean is assumed along with the sensor observations. To reduce the observation noise’s effect, each sensor applies moving average filter on its observation to drastically reduce the effect of noise. The modeling performance, the cost and the convergence of the algorithm are discussed based on extensive computer simulations and reasoning. The algorithm is proposed for environmental monitoring. In this paper, the percentage of the communication attempts of wireless sensors is assumed as cost. Performance evaluation results show that the proposed spatial tracking approach is low cost and can model the spatial signal over time with the same performance as that of spatial modeling.

Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges and an increasing demand for developing new quality assessment methodologies that are easier and cheaper to perform. As of today, the determination of olive oil quality is performed by producers through chemical analysis and organoleptic evaluation. The chemical analysis requires the advanced equipment and chemical knowledge of certified laboratories, and has therefore a limited accessibility. In this work a minimalist, portable and low-cost sensor is presented, which can perform olive oil quality assessment using fluorescence spectroscopy. The potential of the proposed technology is explored by analyzing several olive oils of different quality levels, EVOO, virgin olive oil (VOO), and lampante olive oil (LOO). The spectral data were analyzed using a large number of machine learning methods, including artificial neural networks. The analysis performed in this work demonstrates the possibility of performing classification of olive oil in the three mentioned classes with an accuracy of 100%. These results confirm that this minimalist low-cost sensor has the potential of substituting expensive and complex chemical analysis.

The paper presents the results of a study of the concept of address fiber Bragg structures in the problem of vibration control. The mathematical model of measuring transformation is presented; the experimental study of a vibration diagnostics system based on Address Fiber Bragg Gratings is carried out; the quantitative and qualitative comparative assessment with electronic accelerometers is made; the gain by an order of magnitude in some parameters is shown.

Electromagnetic sensors have been used for inspecting small surface defects of metals. Based on the eddy-current thin-skin regime, a revised algorithm is proposed for a triple-coil drive-pickup eddy-current sensor scanning over long surface crack slots (10 mm) with different rotary angles. The method is validated by the voltage measurement of the designed EC sensor scanning over a benchmark (ferromagnetic) steel with surface defects of different depths and rotary angles. With an additional sensing coil for the designed EC sensor, the defect angle (or orientation) can be measured without spatially and coaxially rotating the excitation coil. By referring to the voltage change (due to the defect) diagram (voltage sum versus voltage different) of two sensing pairs, the rotary angle of the surface crack is retrieved with a maximum residual deviation of 3.5 %.

Anomaly occurrences in hydraulic machinery may lead to massive systems shut down, jeopardizing the safety of the machinery and its surrounding human operator(s) and environment, and the severe economic implications succeeding the faults and their associated damage. Hydraulics are mostly placed in ruthless environments, where they are consistently vulnerable to many faults. Hence, not only the machines and their components are prone to anomalies, but also the sensors attached to them, which monitor and report their health and behavioral changes. In this work, a comprehensive applicational analysis of anomalies in hydraulic systems extracted from a hydraulic test rig is thoroughly achieved. Firstly, we provided a combination of a new architecture of LSTM autoencoders and supervised machine and deep learning methodologies to perform two separate stages of fault detection and diagnosis. The two phases are condensed by: the detection phase using the LSTM autoencoder. Followed by the fault diagnosis phase represented by the classification schema. The previously mentioned framework is applied to both component and sensor faults in hydraulic systems, deployed in the form of two in-depth applicational experiments. Moreover, a thorough literature review of the past decade related work for the two stages separately is successfully conducted in this paper.

For the electromagnetic eddy current testing, various methods have been proposed for reducing the lift-off error on the measurement of samples. In this paper, instead of eliminating the measurement error caused by the lift-off effect, an algorithm has been proposed to directly measure the lift-off distance between the sensor and non-magnetic conductive plates. The algorithm is based on a sample-independent inductance (SII) feature. That is, under high working frequencies, the inductance is found sensitive to the lift-off distance and independent of the test piece under an optimal single high working frequency (43.87 kHz). Furthermore, the predicted lift-off distance is used for the thickness prediction of the non-magnetic conductive samples using an iterative method. Considering the eddy current skin depth, the thickness prediction is operated under a single lower frequency (0.20 kHz). As the inductance has different sensitivities to the lift-off and thickness, the prediction error of the sample thickness is different from that of the lift-off distance. From the experiments on three different nonmagnetic samples – aluminium, copper, and brass, the maximum prediction error of the lift-off distance and sample thickness is 1.1 mm and 5.42 % respectively at the lift-off of 12.0 mm.

Wireless Sensor Networks (WSNs) has the characteristics of large-scale deployment, flexible networking, and wide application. It is an important part of the wireless communication networks. However, due to limited energy supply, the development of WSN is greatly restricted. Wireless Rechargeable Sensor Networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a joint optimization strategy is proposed to improve the energy management efficiency for WRSNs. The joint optimization strategy is divided into two phases. In the first phase, we design an Annulus Virtual Force based Particle Swarm Optimization (AVFPSO) algorithm for area coverage planing. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a Queuing Game-based Energy Supply (QGES) algorithm is designed for energy scheduling. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy, and extends the lifetime of WSN.

Urban cities in sub-Saharan Africa (SSA) are faced with ambient air pollution. This is an important public health problem with models and limited monitoring data indicating high concentrations of pollutants such as fine particulate matter (PM_2.5). Going through most global air quality index maps, however, information about ambient pollution from SSA is scarce. We evaluated the feasibility and practicality of longitudinal measurements of ambient PM_2.5 using low-cost air quality sensors (Purple Air-II-SD) across thirteen locations in seven countries in SSA. Devices were used to gather data over a 30-day period with the aim of assessing the efficiency of its data recovery rate and identifying challenges experienced by users in each location. The median data recovery rate was 94% (range: 72% to 100%). The mean 24-hour concentration measured across all sites was 38 µg/m³ with the highest PM_2.5 period average concentration of 91 µg/m³ measured in Kampala, Uganda and lowest concentrations of 15 µg/m³ measured in Faraja, The Gambia. Kampala-Uganda and Nnewi-Nigeria recorded the longest periods with concentrations>250µg/m³. Power outages, SD memory card issues, internet connectivity problems and device safety concerns were important challenges experienced when using Purple Air-II-SD sensors. Despite some operational challenges, this study demonstrated that it is reasonably practicable and feasible to establish a network of low-cost devices to provide data on local PM_2.5 concentrations in SSA countries. Such data are crucially needed to raise public-, societal and policymaker awareness about air pollution across SSA.

Irrigation is a useful crop enhancement procedure up to the point where free surface water appears. Thereafter, water can begin to flow into waterways, leaching nutrients and giving rise to environmental damage, as well as being a waste of a precious resource. The current work addresses the problem of measuring free water on the surface of agricultural soils by a real-time acoustic remote sensing method. Directional acoustic transmitter and receiver arrays are used to define a ‘footprint’ on the ground from which changes in reflectance are sensed. These arrays are mounted on a moving irrigator. Chirp signals are used to provide along-path resolution and to ensure robustness against unwanted acoustic background noise from farm machinery and the irrigator. Field measurements have been conducted above a well-defined ‘quadrat’ with controlled and measured water content, and also with the instrument mounted on an operational irrigator. A structured light camera mounted above the footprint is used to validate surface water fraction. It is found that the areal fraction of free water on the soil surface can be reliably estimated from changes in the amplitude of the reflected sound waves. The mechanism giving rise to the observed acoustic reflectivity changes is discussed and a model is developed which agrees with normalized intensity observations with a coefficient of determination R2 between 0.65 and 0.83. The rms error between model predictions and observations is comparable to the rms variation of the measurements, indicating that there is insignificant error due to the choice of model.

Liquid metal alloy, incorporated with microfluidic manipulation, has become a promising candidate for flexible resistive sensor array (RSA) that can imitate the functions of human skin. One advantage of RSA with shared rows and shared columns is to reduce the number of wires from M × N to M + N (rows: M and columns: N) and hence to greatly lessen the complexity and burden on the electrical system. The associated drawback is the crosstalk effect between adjacent elements during measurement. Although many literatures have reported several methods to resolve this limitation, almost all of them focus only on the high resistance value (≥100 Ω) RSA. There is a lack of detailed experimental data that addresses low resistance RSA with sensing elements below 100 Ω. Here, we aim to fill the gap of this field. We established two common RSA readout systems, i.e. zero potential methods (ZPM) (setting non-scanned-sampling-electrode zero potential (S-NSSE-ZP) and setting non-scanned-sampling-electrode zero potential with amplifier (S-NSSE-ZP-A)) and to compare their performances in low resistance value (≤100 Ω) RSA. For ideal resistor RSA, the measurement results show that S-NSSE-ZP has at least one time higher error than S-NSSE-ZP-A.

Structural displacement is an important metric for assessing structural conditions because it has a direct relationship with the structural stiffness. Many bridge displacement measurement techniques have been developed, but most methods require fixed reference points in the vicinity of the target structure which limits field implementations. A promising alternative is to use reference-free measurement techniques that indirectly estimate the displacement by using measurements such as acceleration, and strain. This paper proposes novel reference-free bridge displacement estimation by the fusion of single acceleration with pseudo-static displacement derived from co-located strain measurements. First, we propose a conversion of the strain at the center of a beam into displacement based on the geometric relationship between strain and deflection curves with reference-free calibration. Second, an adaptive Kalman filter is proposed to fuse the displacement generated by strain with acceleration by recursively estimate the noise covariance of displacement from strain measurements which is vulnerable to measurement condition. Both numerical and experimental validations are presented to demonstrate the efficiency and robustness of the proposed approach.

The object of this research is designing of new robot-to-robot communication system working in the middle of highway/roads to support mobile safety for approaching vehicles. The result of research project directs to a group of safety robot devices which induce a vehicle on a bypass route, as a vehicle guidance method using the same, and a vehicle safety guidance system. According to an embodiment of the present invention, a safety device includes a detector configured to detect a vehicle approaching the safety device, and an image projector configured to project an image onto a road surface approaching the vehicle when the detector recognizes an approach of the vehicle. It can include. According to the present invention, when it is necessary to guide the vehicle to the bypass route, the driver of the vehicle can grasp the detour route in time and move the vehicle to the next lane.

A realistic implementation of an all-fiber CO₂ sensor, using 74 cm of hollow core PCF fiber as the cavity for light/gas interaction, has been implemented. It is based on CO₂ absorbance in the 2 μm region. The working range is from 2% to 100% CO₂ concentration at 1 atm total pressure. The response time obtained was 10 min. The use of an FBG tuned fiber ring laser, specifically designed for this application, is discussed and preliminary results with this laser are also presented.

In this work performance improvements are described of a low power consumption non-dispersive infrared (NDIR) methane (CH₄) gas sensor using customised optical thin film bandpass filters (BPF). BPF’s shape the spectral characteristic of the combined mid infrared III-V based light emitting diode (LED)/ photodiode (PD) light source/detector optopair, enhancing NDIR CH₄ sensor performance. The BPF, deposited using a novel microwave plasma assisted pulsed DC sputter deposition process, is deposited at room temperature directly onto the temperature sensitive PD heterostructure. BPF’s comprise germanium (Ge) and niobium pentoxide (Nb₂O₅) alternating high and low refractive index layers respectively. Two different optical filter designs are progressed; with BPF bandwidths (BWs) of 160 nm and 300 nm. Comparison of modelled and measured NDIR sensor performance is described, highlighting maximized signal to noise ratio (SNR) and minimized cross talk performance benefits. BPF spectral stability for various environmental temperature and humidity conditions is demonstrated.

A waterbody detection technique is an essential part of digital elevation model (DEM) generation to delineate land-water boundaries and set flattened elevations. This paper describes the technical methodology for improving the initial tile-based waterbody data that are created during production of the ASTER GDEM, because without improvement such tile-based waterbody data are not suitable for incorporating into the new ASTER GDEM Version 3. Waterbodies are classified into three categories: sea, lake, and river. For sea-waterbodies, the effect of sea ice is removed to better delineate sea shorelines in high latitude areas, because sea ice prevents accurate delineation of sea shorelines. For lake-waterbodies, the major part of the processing is to set the unique elevation value for each lake using a mosaic image that covers the entire lake area. Rivers present a unique challenge, because their elevations gradually step down from upstream to downstream. Initially, visual inspection is required to separate rivers from lakes. A stepwise elevation assignment, with a step of one meter, is carried out by manual or automated methods, depending on the situation. The ASTER GWBD product consists of a global set of 1º latitude-by-1º longitude tiles containing water body attribute and elevation data files in geographic latitude and longitude coordinates and with one arc second posting. Each tile contains 3601-by-3601 data points. All improved waterbody elevation data are incorporated into the ASTER GDEM to reflect the improved results.

Water quality monitoring was an important objective in the surroundings. In this study, we investigated the sensing characteristics of the arrayed flexible chloride sensor with XBee wireless sensing system. The sensitivity and linearity of the wireless chloride sensing devices were 91.6 mV/pCl and 0.988, respectively. The hysteresis voltages were 50.14 mV and 36.71 mV during the cycles of 1 M → 10⁻¹ M → 1 M → 10⁻³ M → 1 M and 1 M → 10⁻³ M → 1 M → 10⁻¹ M → 1 M, respectively. The selectivity coefficients of the ClO⁻ ion, ClO₄⁻ ion, NO₃⁻ ion and I⁻ ion for Cl⁻ ion were 5.0 × 10⁻², 1.0 × 10⁻¹, 5.9 × 10⁻³ and 5.6×10⁻¹, respectively. The sensing characteristics of real time measurement were investigated for dynamic microfluidic. The arrayed flexible chloride sensor was integrated with the microfluidic device, syringe pump and wireless sensing system. The sensitivity and linearity were 273.1 mV/pCl and 0.978 at 35 μL/min, respectively.

In this paper, a novel pendulum-type accelerometer based on hetero-core fiber optics has been proposed for structural health monitoring targeting large-scale civil infrastructures. Vibration measurement is a non-destructive method for diagnosing the failure of structures by assessing natural frequencies and other vibration patterns. The hetero-core fiber optic sensor utilized in the proposed accelerometer can serve as a displacement sensor with robustness to temperature changes in addition to immunity to electromagnetic interference and chemical corrosions. Thus the hetero-core sensor inside the accelerometer measures applied acceleration by detecting the rotation of an internal pendulum. A series of experiments showed that the hetero-core fiber sensor linearly responded to the rotation angle of the pendulum ranging within ±5°, and furthermore the proposed accelerometer could reproduce the waveform of input vibration in a frequency band of several Hz order.

The distribution of noble metal nanoparticles in hydrogels are influencing their nanoplasmonic response and signal used for biosensor purposes. By controlling the particle distribution, it is possible to obtain new nanoplasmonic features with new sensing modalities. Particle distributions can be characterized by using volume-imaging methods such as the focused ion beam-scanning electron microscope (FIB-SEM) and the serial block-face scanning electron microscopy (SBFSEM) techniques . Since the pore structure of hydrogels is contained by the water absorbed in the polymer network it may pose challenges for volume-imaging based on electron microscope techniques since the sample must be in a vacuum chamber. The structure of hydrogels can be conserved by choosing appropriate preparation methods, which also depends on the composition of the hydrogel used. In this paper, we have prepared low-weight percentage hydrogels, with and without gold nanorods (GNR) for conventional SEM imaging by using two different drying techniques; (1) the critical point drying (CPD) technique and (2) hexamethyldisilazane (HMDS) drying of hydrogels. A qualitative characterization of the GNR-hydrogels was carried out to study the GNRs positioned in the polymer network. The effect of the two different drying methods on the hydrogel morphology were also compared. The use of HMDS as an alternative to the CPD has several advantages involving less parametrical variables for drying, involving less effort, being cost-effective, and requires no equipment use. In addition, choosing an optimized sample preparation method for SEM with optimized imaging parameters is highly important for obtaining accurate information about materials that is not correlated to artifacts. Hence, the results obtained from the preparation methods and SEM imaging parameters in this paper are useful for developing methods for mapping the metal particle distributions in micro-hydrogels by using FIB-SEM and SBFSEM techniques.

In recent years, online social media information has been subject of study in several data science fields due to its impact on users as a communication and expression channel. Data~gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users opinions and make predictions about real events. Cyber attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ1 regularization.

An interdigitated electrode sensor was designed and microfabricated for measuring the changes in the capacitance of three phosphate selective molecularly imprinted polymer (MIP) formulations, in order to provide hydroponics users with a portable nutrient sensing tool. The MIPs investigated were synthesised using different combinations of the functional monomers methacrylic acid (MAA) and N-allylthiourea, against the template molecules diphenyl phosphate, triethyl phosphate and trimethyl phosphate. A cross-interference study between phosphate, nitrate and sulfate was carried out for the MIP materials using an inductance, capacitance and resistance (LCR) meter. Capacitance measurements were taken applying an alternating current (AC) with a potential difference of 1 V root mean square (RMS) at a frequency of 1 kHz. The cross-interference study demonstrated a strong binding preference to phosphate over the other nutrient salts tested for each formulation. The size of template molecule and length of the functional monomer side groups also determined that a combination of a short chain functional monomer in combination with a template containing large R-groups produced the optimal binding site conditions when synthesising a phosphate selective MIP.

Continuous ultrasonic in-situ monitoring for industrial applications is difficult owing to the high operating temperatures in industrial fields. It is expected that ultrasonic transducers consisting of CaBi4Ti4O15(CBT)/Pb(Zr,Ti)O3(PZT) sol-gel composite could be one solution for ultrasonic nondestructive testing (NDT) above 500 C because no couplant is required and CBT has a high Curie temperature. To verify the high temperature durability, CBT/PZT sol-gel composite films were fabricated on titanium substrates by spray coating, and the CBT/PZT samples were tested in a furnace at various temperatures. Reflected echoes with a high signal-to-noise ratio were observed up to 600 C. A thermal cycle test was conducted from room temperature to 600 C, and no significant deterioration was found after the second thermal cycle. To investigate the long-term high-temperature durability, a CBT/PZT ultrasonic transducer was tested in the furnace at 600 °C for 36 h. Ultrasonic responses were recorded every 3 h, and the sensitivity and signal-to-noise ratio were stable throughout the experiment.

Geological disposal facilities for radioactive waste pose significant challenges for robust monitoring of environmental conditions within the engineered barriers that surround the waste canister. Temperatures are elevated, due to the presence of heat generating waste, relative humidity varies from 20% to 100%, and swelling pressures within the bentonite barrier can typically be 2-10 MPa. Here, we test the robustness of a bespoke design MEMS sensor-based monitoring system, which we encapsulate in polyurethane resin. We place the sensor within an oedometer cell and show that despite a rise in swelling pressure to 2 MPa, our relative humidity (RH) measurements are unaffected. We then test the sensing system against a traditional RH sensor, using saturated bentonite with a range of RH values between 50% and 100%. Measurements differ, on average, by 2.87% RH, and are particularly far apart for values of RH greater than 98%. However, bespoke calibration of the MEMS sensing system using saturated solutions of known RH, reduces the measurement difference to an average of 1.97% RH, greatly increasing the accuracy for RH values close to 100%.

This paper presents a two-stage ADC based on pseudo-differential operational transconductance amplifier (OTA), which is designed for the readout circuit of X-ray linear array sensor. This hybrid ADC employs an incremental sigma-delta ADC and a cyclic ADC, achieving a good trade-off between accuracy and conversion speed. The two stages share the same hardware to reduce power consumption and die area. A common-mood feedback module is used to suppress the influence of charge injection, and the effectiveness is demonstrated by detailed theoretical analysis. A test chip of 14-bit ADC is fabricated in 0.35μm CMOS technology. The measured root mean square (RMS) value of DNL is 0.254 LSB, and the maximum value of INL is -0.776/+1.56 LSB. The measured effective number of bits (ENOB) is 13.43 bits.

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

A compact Mach-zehnder interferometer with a novel design of directional couplers and a phase shifter has been presented as a thermo-optical sensor. With the aim of reducing device size to micro and nano dimension silicon-on-insulator technology was employed. That allowed miniaturization of device size through the reduction of its cross sectional area to 0.066 µm² and the radius of curvature of both the arms of the directional coupler and S-bends of the phase shifter to 5 µm and C-bends to 3 µm. These nano size device dimensions made it possible to reduce the coupling gap to 0.2 µm, which resulted in a significant reduction in the coupling length. The device geometry and its performance characteristics were analyzed and optimized using coupled mode analysis and finite difference time domain simulation tools, respectively. The wavelength dependent transmission loss of the device was measured at different temperature to verify and validate its performance characteristics. Tested devices showed a remarkable temperature dependent transmission characteristic offering significant changes in transmission loss band – with as low as 0.45 ⁰C change in substrate temperature. The extinction ratio and the free spectral range of the device were 26 dB and 0.26 nm respectively in the wavelength range of 1549.5 nm – 1550.5 nm. These results imply that the devices presented here can be used as compact and highly sensitive thermal sensors and optical switches.

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

The massive amount of human biological, imaging and clinical data produced by multiple and diverse sources, necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels as well as their orchestration and links are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof of concept study cases. Personalized simulations over the actual anatomy of a patient have been carried out. The hypermodel has also applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin based clinical decision support system and the core of future in silico trial platforms, although additional retrospective adaptation and validation is necessary.

The good management of the building maintenance should be based on the regular maintenance work. Repair works are often not carried out or there are shifts in time, which causes degradation of the building. The article presents a method of planning renovation works of a MUBAR (maintenance Management in an Un-renovated Building with Abandoning Renovation) based on the consequences in case of their lack. No renovation work on individual elements in a building can cause a threat to the stability of the building structure, risking the lives of users, continuing damage to the building by damaging further elements, or even a building disaster. The method can also be applied to historic buildings. Often, due to abandonment of repairs caused most often by lack of the owner, improper manager or irresponsible users, degradation of these objects occurs. The consequences of neglected renovation of buildings lead to irreversible processes of their destruction. The aim of the article is to present the developed method of planning renovation works based on the consequences of lack of renovation works.

We know that the classical Mittag-Leffler function play an important role as solution of fractional order differential and integral equations. We introduce the j-generalized p - k Mittag-Leffler function. We evaluate the second order differential recurrence relation and four different integral representations and introduce a homogeneous linear differential equation whose one of the solution is the j-generalized p-k Mittag-Leffler function. Also we evaluate the certain relations that exist between j-generalized p - k Mittag-Leffler function and Riemann-Liouville fractional integrals and derivatives. We evaluate Mellin-Barnes integral representation of j-generalized p-k Mittag-Le er Function. The relationship of j-generalized p-k Mittag-Leffler Function with Fox H-Function and Wright hypergeometric function is also establish. we obtained its Euler transform, Laplace Transform and Mellin transform. Finally we derive some particular cases.

In this paper, we derive multifarious relationships among the two types of higher order q-Daehee polynomials and p-adic gamma function via Mahler theorem. Also, we compute some weighted p-adic q-integrals of the derivative of p-adic gamma function related to the Stirling numbers of the both kinds and the q-Bernoulli polynomials of order k.

A typical orchard's mechanical operation consists of three or four stages: lining, digging for plantation, moving the seedling from nurseries to the farm, moving the seedling to the planting hole, and planting the seedling in the hole. However, the digging the planting hole is the most time-consuming operation. In fruit orchards, robots' usage is increasingly becoming more prevalent to increase operational efficiency. They offer practical and effective services to both industry and people, whether they are assigned to plant trees, reduce the use of chemical fertilizers, or carry heavy loads to relieve staff. Robots can operate for extended periods of time and can highly adept at repetitive tasks like planting many trees. The present study aims to identify the locations for planting trees in orchards using geographic information systems (GIS), to develop an autonomous drilling machine and use the developed robot to open planting holes. There isn't a comparable study on autonomous hole planting in the literature in this regard. The agricultural mobile robot is a four wheeled nonholonomic robot with differential steering and forwarding capability to stable target positions. The designed mobile robot can be used in fully autonomous, partially autonomous, or fully manual modes. The drilling system, which is a y-axis shifter driven by a DC motor with reducer includes an auger with a 2.1 HP gasoline engine. SOLIDWORKS software was used for designing and drawing of the mobile robot and drilling system. The Microsoft Visual Basic.NET programming language was used to create the robot navigation system and drilling mechanism software. The cross-track error (XTE), which determines the distances between the actual and desired holes positions, was utilized to analyze the steering accuracy of the mobile robot to the drilling spots. Consequently, the average of the arithmetic means was determined to be 4.35 cm, and the standard deviation was 1.73 cm. This figure indicates that the suggested system is effective for drilling plant holes in orchards.

Abstract: To obtain bovine oocytes in high quality, effects of vitamin C (VC) on in vitro maturation (IVM) of bovine oocytes and early embryo development were investigated. The results showed that: 1) The IVM medium containing 50 µg/mL VC improved the oocyte maturation rate, while no effects on the development of parthenogenetic embryos; 2) The in vitro culture (IVC) medium containing 20 µg/mL VC increased the cleavage rate of the in vitro fertilized (IVF) embryos, enhanced the mRNA levels of pluripotency gene Oct4, Sox2, Cdx2 and Nanog in the blastocysts, but no effect on the blastocyst rate; 3) Combing supplemention of 50 µg/mL in IVM medium + 20 µg/ml VC in IVC medium (VC 50/20) increased the cleavage rate of IVF embryos and enhanced the mRNA levels of Oct4, Sox2, Cdx2 and Nanog in the blastocysts; 4) Combination of VC 0/20 and VC 50/20 enhanced the expression of anti-apoptotic gene Bcl-2 and VC 50/0 weakened the expression of pro-apoptotic gene Bax, while VC 0/40 and VC 0/60 increased Bax expression and decreased the Bcl-2/Bax ratio in blastocysts. Together, VC supplementation at tuned concentration as well its combination in IVM and IVC media improves the developmental rates of bovine oocytes and embryos.

Using two independent speckle imaging systems based on the recently published LSOCI method operating in contact mode on the skin, we assess the reproducibility of in vivo measurements and conduct an inter-instrument comparison. To this aim, we propose a calibration method to handle each imaging system as a comprehensive unit, which includes the laser source, optics, and camera. Our experimental results demonstrate that the microcirculation images produced by both instruments exhibit high accuracy and stability, with microcirculation activity values in excellent agreement, thereby paving the way for clinical applications.

Background: Electrical Impedance Tomography (EIT), combined with variable ventilation strate-gies and Artificial Intelligence (AI), is poised to revolutionize critical care by transitioning from reactive to predictive approaches. This integration aims to enhance patient outcomes through personalized interventions and real-time monitoring. Methods: This narrative review explores the principles and applications of EIT, variable ventilation, and AI in critical care. EIT’s impedance sensing creates dynamic images of internal physiology, aiding in the management of conditions like Acute Respiratory Distress Syndrome (ARDS). Variable ventilation mimics natural breathing variability to improve lung function and minimize ventilator-induced lung injury. AI enhances EIT through advanced image reconstruction techniques, neural networks, and digital twin technology, offering more accurate diagnostics and tailored therapeutic interventions. Conclu-sions: The confluence of EIT, variable ventilation, and AI represents a significant advancement in critical care, enabling a predictive, personalized approach. EIT provides real-time insights into lung function, guiding precise ventilation adjustments and therapeutic interventions. AI inte-gration enhances EIT's diagnostic capabilities, facilitating the development of personalized treatment plans. This synergy fosters interdisciplinary collaborations and sets the stage for in-novative research, ultimately improving patient outcomes and advancing the future of critical care.

The principal function of science education is to introduce students to core scientific concepts and practices; nevertheless, it is now impossible, in such a complex world, to neglect the ethical issues involved. Placing school science in a broader context motivates students and equips them with valuable critical skills. A meaningful example was from palm oil production and pervasive use worldwide: plantations result in major deforestation occurring in species-rich tropical regions, making the palm oil issue global in scope and highly critical for several aspects related to sustainability. This paper reports a sequence of didactic activities starting from palm oil chemistry, gradually extended initially by a multidisciplinary approach, then by interdisciplinary-systemic maps and, ultimately, through a holistic vision - involving anthropological and cultural considerations about indigenous people of deforested territories. This progressive broadening corresponds to an ever-greater penetration into the personal sphere, a condition for a real ethical consciousness. The increased students’ awareness was tested by qualitative considerations, supporting the teaching dimension more than the learning one. Contrary to disciplinary contents, the emergence of moral feelings cannot be measured but only perceived. Therefore, chemistry provides key concepts essential for global competences development in order to deal with sustainability issues with an increased ethical awareness.

The use of antibiotics in neonatal units worldwide varies significantly. We included data from 2015-2022 from the EpicLatino database, which comprises a network of 32 units in Latin America and the Caribbean with gestational age at birth (GA) of ≤ 32 weeks. A questionnaire was sent to the EpicLatino units, to correlate practice with outcomes. Negative binomial regression with standard errors and confidence intervals computed for incidence-rate ratios (IRRs) was used for comparative statistics on antibiotic days per 1000 patient-days between units. All units that responded had 1-6 differences with the reference unit (Unit 2) with the best results, but there was no clear association with the IRR. Each EpicLatino unit should review its statistics to explore possibilities for reducing antibiotic usage.

Museums are called to respond to contemporary challenges and contribute to the formation of more progressive societies. One of the major challenges of our time is climate change and museums could construct cocreated narratives around climate and implement targeted actions for the audiences through their sensorial and affective experiences. More specifically, Geology and Palaeontology museums are repositories of knowledge on geoheritage and geoconservation, recognized for their scientific, pedagogical, cultural and recreational values. The educational potential of geological and paleontological exhibits could be used in informal education activities regarding the climate emergency. Taking the above into consideration, this study focuses on both the creation and evaluation of an educational program for the Natural History Museum of Arsakeio Campus at Psychicko.